1
|
Schettini F, Palleschi M, Mannozzi F, Brasó-Maristany F, Cecconetto L, Galván P, Mariotti M, Ferrari A, Scarpi E, Miserocchi A, Nanni O, Sanfeliu E, Prat A, Rocca A, De Giorgi U. CDK4/6-Inhibitors Versus Chemotherapy in Advanced HR+/HER2-Negative Breast Cancer: Results and Correlative Biomarker Analyses of the KENDO Randomized Phase II Trial. Oncologist 2024; 29:e622-e634. [PMID: 38175669 PMCID: PMC11067809 DOI: 10.1093/oncolo/oyad337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND The optimal treatment approach for hormone receptor-positive/HER2-negative metastatic breast cancer (HR+/HER2-negative MBC) with aggressive characteristics remains controversial, with lack of randomized trials comparing cyclin-dependent kinase (CDK)4/6-inhibitors (CDK4/6i) + endocrine therapy (ET) with chemotherapy + ET. MATERIALS AND METHODS We conducted an open-label randomized phase II trial (NCT03227328) to investigate whether chemotherapy + ET is superior to CDK4/6i + ET for HR+/HER2-negative MBC with aggressive features. PAM50 intrinsic subtypes (IS), immunological features, and gene expression were assessed on baseline samples. RESULTS Among 49 randomized patients (median follow-up: 35.2 months), median progression-free survival (mPFS) with chemotherapy + ET (11.2 months, 95% confidence interval [CI]: 7.7-15.4) was numerically shorter than mPFS (19.9 months, 95% CI: 9.0-30.6) with CDK4/6i + ET (hazard ratio: 1.41, 95% CI: 0.75-2.64). Basal-like tumors under CDK4/6i + ET exhibited worse PFS (mPFS: 11.4 months, 95% CI: 3.00-not reached [NR]) and overall survival (OS; mOS: 18.8 months, 95% CI: 18.8-NR) compared to other subtypes (mPFS: 20.7 months, 95% CI: 9.00-33.4; mOS: NR, 95% CI: 24.4-NR). In the chemotherapy arm, luminal A tumors showed poorer PFS (mPFS: 5.1 months, 95% CI: 2.7-NR) than other IS (mPFS: 13.2 months, 95% CI: 10.6-28.1). Genes/pathways involved in BC cell survival and proliferation were associated with worse outcomes, as opposite to most immune-related genes/signatures, especially in the CDK4/6i arm. CD24 was the only gene significantly associated with worse PFS in both arms. Tertiary lymphoid structures and higher tumor-infiltrating lymphocytes also showed favorable survival trends in the CDK4/6i arm. CONCLUSIONS The KENDO trial, although closed prematurely, adds further evidence supporting CDK4/6i + ET use in aggressive HR+/HER2-negative MBC instead of chemotherapy. PAM50 IS, genomic, and immunological features are promising biomarkers to personalize therapeutic choices.
Collapse
Affiliation(s)
- Francesco Schettini
- Translational Genomics and Targeted Therapies in Solid Tumors Group, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Medical Oncology Department, Hospital Clinic of Barcelona, Barcelona, Spain
- Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Michela Palleschi
- Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Francesca Mannozzi
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Fara Brasó-Maristany
- Translational Genomics and Targeted Therapies in Solid Tumors Group, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Lorenzo Cecconetto
- Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Patricia Galván
- Translational Genomics and Targeted Therapies in Solid Tumors Group, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Marita Mariotti
- Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Alessia Ferrari
- UO Medicina Oncologia, Ospedale Ramazzini, Azienda USL di Modena, Carpi, Italy
| | - Emanuela Scarpi
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Anna Miserocchi
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Oriana Nanni
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| | - Esther Sanfeliu
- Medical Oncology Department, Hospital Clinic of Barcelona, Barcelona, Spain
- Department of Pathology, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, Barcelona, Spain
| | - Aleix Prat
- Translational Genomics and Targeted Therapies in Solid Tumors Group, August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
- Cancer Institute and Blood Diseases, Hospital Clínic of Barcelona, Barcelona, Spain
- Breast Cancer Unit, Institute of Oncology Barcelona (IOB), Quirónsalud, Barcelona, Spain
- Reveal Genomics, Barcelona, Spain
| | - Andrea Rocca
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Ugo De Giorgi
- Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori,”Meldola, Italy
| |
Collapse
|
2
|
Umana GE, Molina C, Miserocchi A, Marcus HJ. Introduction. Introducing mixed reality in neurosurgical practice. Neurosurg Focus 2024; 56:E1. [PMID: 38163357 DOI: 10.3171/2023.11.focus23584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Affiliation(s)
- Giuseppe E Umana
- 1Department of Neurosurgery, Trauma Center, Gamma Knife Center, Cannizzaro Hospital, Catania, Italy
| | - Camilo Molina
- 2Department of Neurological Surgery, Washington University School of Medicine, St. Louis, Missouri; and
| | - Anna Miserocchi
- 3Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Hani J Marcus
- 3Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| |
Collapse
|
3
|
Hall GR, Hutchings F, Horsley J, Simpson CM, Wang Y, de Tisi J, Miserocchi A, McEvoy AW, Vos SB, Winston GP, Duncan JS, Taylor PN. Epileptogenic networks in extra temporal lobe epilepsy. Netw Neurosci 2023; 7:1351-1362. [PMID: 38144694 PMCID: PMC10631792 DOI: 10.1162/netn_a_00327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/22/2023] [Indexed: 12/26/2023] Open
Abstract
Extra temporal lobe epilepsy (eTLE) may involve heterogenous widespread cerebral networks. We investigated the structural network of an eTLE cohort, at the postulated epileptogenic zone later surgically removed, as a network node: the resection zone (RZ). We hypothesized patients with an abnormal connection to/from the RZ to have proportionally increased abnormalities based on topological proximity to the RZ, in addition to poorer post-operative seizure outcome. Structural and diffusion MRI were collected for 22 eTLE patients pre- and post-surgery, and for 29 healthy controls. The structural connectivity of the RZ prior to surgery, measured via generalized fractional anisotropy (gFA), was compared with healthy controls. Abnormal connections were identified as those with substantially reduced gFA (z < -1.96). For patients with one or more abnormal connections to/from the RZ, connections with closer topological distance to the RZ had higher proportion of abnormalities. The minority of the seizure-free patients (3/11) had one or more abnormal connections, while most non-seizure-free patients (8/11) had abnormal connections to the RZ. Our data suggest that eTLE patients with one or more abnormal structural connections to/from the RZ had more proportional abnormal connections based on topological distance to the RZ and associated with reduced chance of seizure freedom post-surgery.
Collapse
Affiliation(s)
- Gerard R. Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Frances Hutchings
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jonathan Horsley
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Callum M. Simpson
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jane de Tisi
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- UCL/UCLH NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Anna Miserocchi
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Andrew W. McEvoy
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sjoerd B. Vos
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Nedlands, Australia
| | - Gavin P. Winston
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, Canada
| | - John S. Duncan
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- UCL/UCLH NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| |
Collapse
|
4
|
Medri M, Savoia F, Foca F, Miserocchi A, Quaglino P, Rubatto M, Gullo G, Nardini C, Panasiti V, DE Tursi M, DI Marino P, Brancaccio G, Giunta EF, Napolitano S, Cinotti E, Brusasco M, Stanganelli I. A retrospective observational study on cutaneous adverse events induced by immune checkpoint inhibitors. Ital J Dermatol Venerol 2023; 158:437-444. [PMID: 38015482 DOI: 10.23736/s2784-8671.23.07542-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
BACKGROUND Cutaneous adverse events (CAEs) related to oncological therapies are a common scenario in daily clinical practice. METHODS This is a retrospective observational study collecting the data regarding CAEs of patients treated with immune checkpoints inhibitors (ICIs) in four different Italian centers. RESULTS Of 323 patients included, 305 were evaluable for this analysis; 182 patients (59.7%) had metastatic cutaneous melanoma (CM), 99 (32.5%) non-small cell lung cancer (NSCLC) and 24 (7.8%) renal cell carcinoma (RCC). The most frequent CAEs that we found, considering all the 305 patients, were pruriginous maculopapular rash (10.2% of the patients), vitiligo-like areas (7.2% of the patients), psoriasiform rash (6.2% of the patients), asymptomatic maculopapular rash (4.6% of the patients), and lichenoid rash (4.3% of the patients). Vitiligo-like areas occurred more frequently in patients with CM, while a lichenoid rash was more frequently observed in patients with RCC. Treatment interruption was related to drug-induced CAEs in 15.4% of melanoma patients and 0.0% of lung and kidney patients. Patients developing a cutaneous adverse event had better overall response rate and higher progression free survival and overall survival than the patients without CAEs. CONCLUSIONS Our study brings new information on the characteristics of CAEs related to ICIs treatment in three different types of cancers, CM, NSCLC and RCC.
Collapse
Affiliation(s)
- Matelda Medri
- Unit of Skin Cancer, IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori, IRST, Meldola, Forlì-Cesena, Italy
| | - Francesco Savoia
- Unit of Skin Cancer, IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori, IRST, Meldola, Forlì-Cesena, Italy -
| | - Flavia Foca
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori, IRST, Meldola, Forlì-Cesena, Italy
| | - Anna Miserocchi
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori, IRST, Meldola, Forlì-Cesena, Italy
| | - Pietro Quaglino
- Department of Medical Sciences, Dermatologic Clinic, University of Turin Medical School, Turin, Italy
| | - Marco Rubatto
- Department of Medical Sciences, Dermatologic Clinic, University of Turin Medical School, Turin, Italy
| | - Giulia Gullo
- Department of Medical Sciences, Dermatologic Clinic, University of Turin Medical School, Turin, Italy
| | - Chiara Nardini
- Department of Medical Sciences, Dermatologic Clinic, University of Turin Medical School, Turin, Italy
| | - Vincenzo Panasiti
- Unit of Plastic and Reconstructive Surgery, Campus Bio-Medico University, Rome, Italy
| | - Michele DE Tursi
- Department of Innovative Technologies in Medicine and Dentistry, University G. D'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Pietro DI Marino
- Department of Innovative Technologies in Medicine and Dentistry, University G. D'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Emilio F Giunta
- Unit of Oncology, Luigi Vanvitelli University of Campania, Naples, Italy
| | | | - Elisa Cinotti
- Unit of Dermatology, Department of Medical, Surgical and Neurological Sciences, University of Siena, Siena, Italy
| | - Marco Brusasco
- Unit of Dermatology, Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy
| | - Ignazio Stanganelli
- Unit of Skin Cancer, IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori, IRST, Meldola, Forlì-Cesena, Italy
- Unit of Dermatology, Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy
| |
Collapse
|
5
|
Sheybani L, Vivekananda U, Rodionov R, Diehl B, Chowdhury FA, McEvoy AW, Miserocchi A, Bisby JA, Bush D, Burgess N, Walker MC. Wake slow waves in focal human epilepsy impact network activity and cognition. Nat Commun 2023; 14:7397. [PMID: 38036557 PMCID: PMC10689494 DOI: 10.1038/s41467-023-42971-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/27/2023] [Indexed: 12/02/2023] Open
Abstract
Slow waves of neuronal activity are a fundamental component of sleep that are proposed to have homeostatic and restorative functions. Despite this, their interaction with pathology is unclear and there is only indirect evidence of their presence during wakefulness. Using intracortical recordings from the temporal lobe of 25 patients with epilepsy, we demonstrate the existence of local wake slow waves (LoWS) with key features of sleep slow waves, including a down-state of neuronal firing. Consistent with a reduction in neuronal activity, LoWS were associated with slowed cognitive processing. However, we also found that LoWS showed signatures of a homeostatic relationship with interictal epileptiform discharges (IEDs): exhibiting progressive adaptation during the build-up of network excitability before an IED and reducing the impact of subsequent IEDs on network excitability. We therefore propose an epilepsy homeostasis hypothesis: that slow waves in epilepsy reduce aberrant activity at the price of transient cognitive impairment.
Collapse
Affiliation(s)
- Laurent Sheybani
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - James A Bisby
- Division of Psychiatry, University College London, London, UK
| | - Daniel Bush
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Neil Burgess
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Institute of Cognitive Neuroscience, University College London, London, UK.
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK.
- NIHR University College London Hospitals Biomedical Research Centre, London, UK.
| |
Collapse
|
6
|
Horsley JJ, Thomas RH, Chowdhury FA, Diehl B, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Winston GP, Duncan JS, Wang Y, Taylor PN. Complementary structural and functional abnormalities to localise epileptogenic tissue. EBioMedicine 2023; 97:104848. [PMID: 37898096 PMCID: PMC10630610 DOI: 10.1016/j.ebiom.2023.104848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 10/11/2023] [Accepted: 10/11/2023] [Indexed: 10/30/2023] Open
Abstract
BACKGROUND When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. METHODS We retrospectively investigated data from 43 patients (42% female) with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. FINDINGS Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p = 0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. INTERPRETATION Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. FUNDING This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.
Collapse
Affiliation(s)
- Jonathan J Horsley
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia; Centre for Medical Image Computing, Computer Science Department, University College London, London, United Kingdom
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Division of Neurology, Department of Medicine, Queen's University, Kingston, Canada
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter N Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| |
Collapse
|
7
|
Owen TW, Janiukstyte V, Hall GR, Chowdhury FA, Diehl B, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Wang Y, Taylor PN. Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome. Brain Commun 2023; 5:fcad292. [PMID: 37953844 PMCID: PMC10636564 DOI: 10.1093/braincomms/fcad292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/24/2023] [Accepted: 10/24/2023] [Indexed: 11/14/2023] Open
Abstract
Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.
Collapse
Affiliation(s)
- Thomas W Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Vytene Janiukstyte
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Gerard R Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Andrew McEvoy
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - John S Duncan
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Fergus Rugg-Gunn
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Peter N Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| |
Collapse
|
8
|
Horsley JJ, Thomas RH, Chowdhury FA, Diehl B, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Winston GP, Duncan JS, Wang Y, Taylor PN. Complementary structural and functional abnormalities to localise epileptogenic tissue. ArXiv 2023:arXiv:2304.03192v3. [PMID: 37064531 PMCID: PMC10104180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Background When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. Methods We retrospectively investigated data from 43 patients with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. Findings Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p=0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. Interpretation Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. Funding This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.
Collapse
Affiliation(s)
- Jonathan J. Horsley
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Rhys H. Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A. Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew W. McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sjoerd B. Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
- Centre for Medical Image Computing, Computer Science Department, University College London, London, United Kingdom
| | - Matthew C. Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Division of Neurology, Department of Medicine, Queen’s University, Kingston, Canada
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter N. Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| |
Collapse
|
9
|
Sinha N, Duncan JS, Diehl B, Chowdhury FA, de Tisi J, Miserocchi A, McEvoy AW, Davis KA, Vos SB, Winston GP, Wang Y, Taylor PN. Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery. Neurology 2023; 101:e1293-e1306. [PMID: 37652703 PMCID: PMC10558161 DOI: 10.1212/wnl.0000000000207661] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 06/02/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Surgery is an effective treatment for drug-resistant epilepsy, which modifies the brain's structure and networks to regulate seizure activity. Our objective was to examine the relationship between brain structure and function to determine the extent to which this relationship affects the success of the surgery in controlling seizures. We hypothesized that a stronger association between brain structure and function would lead to improved seizure control after surgery. METHODS We constructed functional and structural brain networks in patients with drug-resistant focal epilepsy by using presurgery functional data from intracranial EEG (iEEG) recordings, presurgery and postsurgery structural data from T1-weighted MRI, and presurgery diffusion-weighted MRI. We quantified the relationship (coupling) between structural and functional connectivity by using the Spearman rank correlation and analyzed this structure-function coupling at 2 spatial scales: (1) global iEEG network level and (2) individual iEEG electrode contacts using virtual surgeries. We retrospectively predicted postoperative seizure freedom by incorporating the structure-function connectivity coupling metrics and routine clinical variables into a cross-validated predictive model. RESULTS We conducted a retrospective analysis on data from 39 patients who met our inclusion criteria. Brain areas implanted with iEEG electrodes had stronger structure-function coupling in seizure-free patients compared with those with seizure recurrence (p = 0.002, d = 0.76, area under the receiver operating characteristic curve [AUC] = 0.78 [95% CI 0.62-0.93]). Virtual surgeries on brain areas that resulted in stronger structure-function coupling of the remaining network were associated with seizure-free outcomes (p = 0.007, d = 0.96, AUC = 0.73 [95% CI 0.58-0.89]). The combination of global and local structure-function coupling measures accurately predicted seizure outcomes with a cross-validated AUC of 0.81 (95% CI 0.67-0.94). These measures were complementary to other clinical variables and, when included for prediction, resulted in a cross-validated AUC of 0.91 (95% CI 0.82-1.0), accuracy of 92%, sensitivity of 93%, and specificity of 91%. DISCUSSION Our study showed that the strength of structure-function connectivity coupling may play a crucial role in determining the success of epilepsy surgery. By quantitatively incorporating structure-function coupling measures and standard-of-care clinical variables into presurgical evaluations, we may be able to better localize epileptogenic tissue and select patients for epilepsy surgery. CLASSIFICATION OF EVIDENCE This is a Class IV retrospective case series showing that structure-function mapping may help determine the outcome from surgical resection for treatment-resistant focal epilepsy.
Collapse
Affiliation(s)
- Nishant Sinha
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada.
| | - John S Duncan
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Beate Diehl
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Fahmida A Chowdhury
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Jane de Tisi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Anna Miserocchi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Andrew William McEvoy
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Kathryn A Davis
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Sjoerd B Vos
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Gavin P Winston
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Yujiang Wang
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Peter Neal Taylor
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| |
Collapse
|
10
|
Owen TW, Janiukstyte V, Hall GR, Horsley JJ, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg‐Gunn F, Wang Y, Taylor PN. Identifying epileptogenic abnormalities through spatial clustering of MEG interictal band power. Epilepsia Open 2023; 8:1151-1156. [PMID: 37254660 PMCID: PMC10472397 DOI: 10.1002/epi4.12767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/22/2023] [Indexed: 06/01/2023] Open
Abstract
Successful epilepsy surgery depends on localizing and resecting cerebral abnormalities and networks that generate seizures. Abnormalities, however, may be widely distributed across multiple discontiguous areas. We propose spatially constrained clusters as candidate areas for further investigation and potential resection. We quantified the spatial overlap between the abnormality cluster and subsequent resection, hypothesizing a greater overlap in seizure-free patients. Thirty-four individuals with refractory focal epilepsy underwent pre-surgical resting-state interictal magnetoencephalography (MEG) recording. Fourteen individuals were totally seizure-free (ILAE 1) after surgery and 20 continued to have some seizures post-operatively (ILAE 2+). Band power abnormality maps were derived using controls as a baseline. Patient abnormalities were spatially clustered using the k-means algorithm. The tissue within the cluster containing the most abnormal region was compared with the resection volume using the dice score. The proposed abnormality cluster overlapped with the resection in 71% of ILAE 1 patients. Conversely, an overlap only occurred in 15% of ILAE 2+ patients. This effect discriminated outcome groups well (AUC = 0.82). Our novel approach identifies clusters of spatially similar tissue with high abnormality. This is clinically valuable, providing (a) a data-driven framework to validate current hypotheses of the epileptogenic zone localization or (b) to guide further investigation.
Collapse
Affiliation(s)
- Thomas W. Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Vytene Janiukstyte
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Gerard R. Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Jonathan J. Horsley
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Andrew McEvoy
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
| | - Anna Miserocchi
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
| | - Jane de Tisi
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - John S. Duncan
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Fergus Rugg‐Gunn
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
- UCL Queen Square Institute of NeurologyLondonUK
- National Hospital for Neurology & NeurosurgeryLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| |
Collapse
|
11
|
Wang Y, Schroeder GM, Horsley JJ, Panagiotopoulou M, Chowdhury FA, Diehl B, Duncan JS, McEvoy AW, Miserocchi A, de Tisi J, Taylor PN. Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue. Epilepsia 2023; 64:2070-2080. [PMID: 37226553 PMCID: PMC10962550 DOI: 10.1111/epi.17663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 05/26/2023]
Abstract
OBJECTIVE Identifying abnormalities on interictal intracranial electroencephalogram (iEEG), by comparing patient data to a normative map, has shown promise for the localization of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of approximately 1 min. However, the temporal stability of findings has not been established. METHODS Here, we generated a normative map of iEEG in nonpathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (.92-8.62 days of iEEG data, mean = 4.58 days per patient, >4800 hours recording). To assess the localizing value of band power abnormality, we computedD RS -a measure of how different the surgically resected and spared tissue was in terms of band power abnormalities-over time. RESULTS In each patient, theD RS value was relatively consistent over time. The medianD RS of the entire recording period separated seizure-free (International League Against Epilepsy [ILAE] = 1) and not-seizure-free (ILAE> 1) patients well (area under the curve [AUC] = .69). This effect was similar interictally (AUC = .69) and peri-ictally (AUC = .71). SIGNIFICANCE Our results suggest that band power abnormality D_RS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.
Collapse
Affiliation(s)
- Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle Upon TyneUK
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - Gabrielle M. Schroeder
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Jonathan J. Horsley
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Mariella Panagiotopoulou
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | | | - Beate Diehl
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - John S. Duncan
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | | | | | - Jane de Tisi
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle Upon TyneUK
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| |
Collapse
|
12
|
Joensen BH, Bush D, Vivekananda U, Horner AJ, Bisby JA, Diehl B, Miserocchi A, McEvoy AW, Walker MC, Burgess N. Hippocampal theta activity during encoding promotes subsequent associative memory in humans. Cereb Cortex 2023; 33:8792-8802. [PMID: 37160345 PMCID: PMC10321091 DOI: 10.1093/cercor/bhad162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/19/2023] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
Hippocampal theta oscillations have been implicated in associative memory in humans. However, findings from electrophysiological studies using scalp electroencephalography or magnetoencephalography, and those using intracranial electroencephalography are mixed. Here we asked 10 pre-surgical epilepsy patients undergoing intracranial electroencephalography recording, along with 21 participants undergoing magnetoencephalography recordings, to perform an associative memory task, and examined whether hippocampal theta activity during encoding was predictive of subsequent associative memory performance. Across the intracranial electroencephalography and magnetoencephalography studies, we observed that theta power in the hippocampus increased during encoding, and that this increase differed as a function of subsequent memory, with greater theta activity for pairs that were successfully retrieved in their entirety compared with those that were not remembered. This helps to clarify the role of theta oscillations in associative memory formation in humans, and further, demonstrates that findings in epilepsy patients undergoing intracranial electroencephalography recordings can be extended to healthy participants undergoing magnetoencephalography recordings.
Collapse
Affiliation(s)
- Bárður H Joensen
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
- UCL Institute of Cognitive Neuroscience, UCL, London, WC1N 3AZ, United Kingdom
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm 17165, Sweden
- Department of Psychology, Uppsala University, Uppsala 751 42, Sweden
| | - Daniel Bush
- Department of Neuroscience, Physiology and Pharmacology, UCL, London, WC1E 6BT, United Kingdom
| | - Umesh Vivekananda
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
| | - Aidan J Horner
- Department of Psychology, University of York, York, YO10 5DD, United Kingdom
- York Biomedical Research Institute, University of York, York, YO10 5DD, United Kingdom
| | - James A Bisby
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
- UCL Institute of Cognitive Neuroscience, UCL, London, WC1N 3AZ, United Kingdom
- Division of Psychiatry, UCL, London, W1T 7BN, United Kingdom
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
| | - Andrew W McEvoy
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
| | - Matthew C Walker
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
| | - Neil Burgess
- UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom
- UCL Institute of Cognitive Neuroscience, UCL, London, WC1N 3AZ, United Kingdom
- Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, United Kingdom
| |
Collapse
|
13
|
Jozsa F, Gaier C, Ma Y, Kitchen N, McEvoy A, Miserocchi A, Samandouras G, Sethi H, Thorne L, Hill C, Darie L. Safety and efficacy of brain biopsy: Results from a single institution retrospective cohort study. Brain Spine 2023; 3:101763. [PMID: 37383459 PMCID: PMC10293303 DOI: 10.1016/j.bas.2023.101763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/30/2023] [Accepted: 06/10/2023] [Indexed: 06/30/2023]
Abstract
Introduction Brain biopsy provides important histopathological diagnostic information for patients with new intracranial lesions. Although a minimally invasive technique, previous studies report an associated morbidity and mortality between 0.6% and 6.8%. We sought to characterise the risk linked to this procedure, and to establish the feasibility of instigating a day-case brain biopsy pathway at our institution. Materials and methods This single-centre retrospective case series study included neuronavigation guided mini craniotomy and frameless stereotactic brain biopsies carried out between April 2019 and December 2021. Exclusion criteria were interventions performed for non-neoplastic lesions. Demographic data, clinical and radiological presentation, type of biopsy, histology and complications in the post-operative period were recorded. Results Data from 196 patients with a mean age of 58.7 years (SD+/-14.4 years) was analysed. 79% (n=155) were frameless stereotactic biopsies and 21% (n=41) neuronavigation guided mini craniotomy biopsies. Complications resulting in acute intracerebral haemorrhage and death, or new persistent neurological deficits were observed in 2% of patients (n=4; 2 frameless stereotactic; 2 open). Less severe complications or transient symptoms were noted in 2.5% of cases (n=5). 8 patients had minor haemorrhages in the biopsy tract with no clinical ramifications. Biopsy was non-diagnostic in 2.5% (n=5) of cases. Two cases were subsequently identified as lymphoma. Other reasons included insufficient sampling, necrotic tissue, and target error. Discussion and conclusion This study demonstrates that brain biopsy is a procedure with an acceptably low rate of severe complications and mortality, in line with previously published literature. This supports the development of day-case pathway allowing improved patient flow, reducing the risk of iatrogenic complications associated with hospital stay, such as infection and thrombosis.
Collapse
Affiliation(s)
- Felix Jozsa
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Celia Gaier
- University College London Medical School, London, UK
| | - Yangxinrui Ma
- University College London Medical School, London, UK
| | - Neil Kitchen
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Andrew McEvoy
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Anna Miserocchi
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - George Samandouras
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Huma Sethi
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Lewis Thorne
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Ciaran Hill
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
- UCL Cancer Institute, University College London, 72 Huntley Street, London, UK
| | - Lucia Darie
- Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| |
Collapse
|
14
|
Giampiccolo D, Binding LP, Caciagli L, Rodionov R, Foulon C, de Tisi J, Granados A, Finn R, Dasgupta D, Xiao F, Diehl B, Torzillo E, Van Dijk J, Taylor PN, Koepp M, McEvoy AW, Baxendale S, Chowdhury F, Duncan JS, Miserocchi A. Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery. Brain 2023; 146:2377-2388. [PMID: 37062539 PMCID: PMC10232243 DOI: 10.1093/brain/awad085] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 02/08/2023] [Accepted: 03/02/2023] [Indexed: 04/18/2023] Open
Abstract
Around 50% of patients undergoing frontal lobe surgery for focal drug-resistant epilepsy become seizure free post-operatively; however, only about 30% of patients remain seizure free in the long-term. Early seizure recurrence is likely to be caused by partial resection of the epileptogenic lesion, whilst delayed seizure recurrence can occur even if the epileptogenic lesion has been completely excised. This suggests a coexistent epileptogenic network facilitating ictogenesis in close or distant dormant epileptic foci. As thalamic and striatal dysregulation can support epileptogenesis and disconnection of cortico-thalamostriatal pathways through hemispherotomy or neuromodulation can improve seizure outcome regardless of focality, we hypothesize that projections from the striatum and the thalamus to the cortex may contribute to this common epileptogenic network. To this end, we retrospectively reviewed a series of 47 consecutive individuals who underwent surgery for drug-resistant frontal lobe epilepsy. We performed voxel-based and tractography disconnectome analyses to investigate shared patterns of disconnection associated with long-term seizure freedom. Seizure freedom after 3 and 5 years was independently associated with disconnection of the anterior thalamic radiation and anterior cortico-striatal projections. This was also confirmed in a subgroup of 29 patients with complete resections, suggesting these pathways may play a critical role in supporting the development of novel epileptic networks. Our study indicates that network dysfunction in frontal lobe epilepsy may extend beyond the resection and putative epileptogenic zone. This may be critical in the pathogenesis of delayed seizure recurrence as thalamic and striatal networks may promote epileptogenesis and disconnection may underpin long-term seizure freedom.
Collapse
Affiliation(s)
- Davide Giampiccolo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Institute of Neuroscience, Cleveland Clinic London, London SW1X 7HY, UK
| | - Lawrence P Binding
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Computer Science, Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Chris Foulon
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Alejandro Granados
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Roisin Finn
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Debayan Dasgupta
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Emma Torzillo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jan Van Dijk
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Matthias Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Institute of Neuroscience, Cleveland Clinic London, London SW1X 7HY, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Fahmida Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Institute of Neuroscience, Cleveland Clinic London, London SW1X 7HY, UK
| |
Collapse
|
15
|
Peter Binding L, Neal Taylor P, O'Keeffe AG, Giampiccolo D, Fleury M, Xiao F, Caciagli L, de Tisi J, Winston GP, Miserocchi A, McEvoy A, Duncan JS, Vos SB. The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change. Neuroimage Clin 2023; 38:103444. [PMID: 37300974 PMCID: PMC10300575 DOI: 10.1016/j.nicl.2023.103444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/04/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Anterior temporal lobe resection (ATLR) is a successful treatment for medically-refractory temporal lobe epilepsy (TLE). In the language-dominant hemisphere, 30%- 50% of individuals experience a naming decline which can impact upon daily life. Measures of structural networks are associated with language performance pre-operatively. It is unclear if analysis of network measures may predict post-operative decline. METHODS White matter fibre tractography was performed on preoperative diffusion MRI of 44 left lateralised and left resection individuals with TLE to reconstruct the preoperative structural network. Resection masks, drawn on co-registered pre- and post-operative T1-weighted MRI scans, were used as exclusion regions on pre-operative tractography to estimate the post-operative network. Changes in graph theory metrics, cortical strength, betweenness centrality, and clustering coefficient were generated by comparing the estimated pre- and post-operative networks. These were thresholded based on the presence of the connection in each patient, ranging from 75% to 100% in steps of 5%. The average graph theory metric across thresholds was taken. We incorporated leave-one-out cross-validation with smoothly clipped absolute deviation (SCAD) least absolute shrinkage and selection operator (LASSO) feature selection and a support vector classifier to assess graph theory metrics on picture naming decline. Picture naming was assessed via the Graded Naming Test preoperatively and at 3 and 12 months post-operatively and the outcome was classified using the reliable change index (RCI) to identify clinically significant decline. The best feature combination and model was selected using the area under the curve (AUC). The sensitivity, specificity and F1-score were also reported. Permutation testing was performed to assess the machine learning model and selected regions difference significance. RESULTS A combination of clinical and graph theory metrics were able to classify outcome of picture naming at 3 months with an AUC of 0.84. At 12 months, change in strength to cortical regions was best able to correctly classify outcome with an AUC of 0.86. Longitudinal analysis revealed that betweenness centrality was the best metric to identify patients who declined at 3 months, who will then continue to experience decline from 3 to 12 months. Both models were significantly higher AUC values than a random classifier. CONCLUSION Our results suggest that inferred changes of network integrity were able to correctly classify picture naming decline after ATLR. These measures may be used to prospectively to identify patients who are at risk of picture naming decline after surgery and could potentially be utilised to assist tailoring the resection in order to prevent this decline.
Collapse
Affiliation(s)
- Lawrence Peter Binding
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.
| | - Peter Neal Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; CNNP lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, United Kingdom
| | - Aidan G O'Keeffe
- School of Mathematical Sciences, University of Nottingham, United Kingdom; Institute of Epidemiology and Healthcare, UCL, London WC1E 6BT, United Kingdom
| | - Davide Giampiccolo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom; Department of Neurosurgery, Institute of Neurosciences, Cleveland Clinic London, United Kingdom
| | - Marine Fleury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Lorenzo Caciagli
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jane de Tisi
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine, Division of Neurology, Queens University, Kingston, Canada
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom
| | - Andrew McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Sjoerd B Vos
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| |
Collapse
|
16
|
Fiore G, Porto E, Pluderi M, Ampollini AM, Borsa S, Legnani FG, Giampiccolo D, Miserocchi A, Bertani GA, DiMeco F, Locatelli M. Prevention of Post-Operative Pain after Elective Brain Surgery: A Meta-Analysis of Randomized Controlled Trials. Medicina (Kaunas) 2023; 59:medicina59050831. [PMID: 37241063 DOI: 10.3390/medicina59050831] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/02/2023] [Accepted: 04/20/2023] [Indexed: 05/28/2023]
Abstract
Background and Objective: To analyze the effects of several drug for pain prevention in adults undergoing craniotomy for elective brain surgery. Material and Methods: A systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The inclusion criteria were limited to randomized controlled trials (RCTs) that evaluated the effectiveness of pharmacological treatments for preventing post-operative pain in adults (aged 18 years or older) undergoing craniotomies. The main outcome measures were represented by the mean differences in validated pain intensity scales administered at 6 h, 12 h, 24 h and 48 h post-operatively. The pooled estimates were calculated using random forest models. The risk of bias was evaluated using the RoB2 revised tool, and the certainty of evidence was assessed according to the GRADE guidelines. Results: In total, 3359 records were identified through databases and registers' searching. After study selection, 29 studies and 2376 patients were included in the meta-analysis. The overall risk of bias was low in 78.5% of the studies included. The pooled estimates of the following drug classes were provided: NSAIDs, acetaminophen, local anesthetics and steroids for scalp infiltration and scalp block, gabapentinoids and agonists of adrenal receptors. Conclusions: High-certainty evidence suggests that NSAIDs and acetaminophen may have a moderate effect on reducing post-craniotomy pain 24 h after surgery compared to control and that ropivacaine scalp block may have a bigger impact on reducing post-craniotomy pain 6 h after surgery compared to control. Moderate-certainty evidence indicates that NSAIDs may have a more remarkable effect on reducing post-craniotomy pain 12 h after surgery compared to control. No moderate-to-high-certainty evidence indicates effective treatments for post-craniotomy pain prevention 48 h after surgery.
Collapse
Affiliation(s)
- Giorgio Fiore
- Unit of Neurosurgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Edoardo Porto
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico C. Besta, 20133 Milan, Italy
- Department of Neurosurgery, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Mauro Pluderi
- Unit of Neurosurgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | | | - Stefano Borsa
- Unit of Neurosurgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | | | - Davide Giampiccolo
- Institute of Neuroscience, Cleveland Clinic London, Grosvenor Place, London SW1X 7HY, UK
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College, London WC1E 6BT, UK
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Giulio Andrea Bertani
- Unit of Neurosurgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Francesco DiMeco
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico C. Besta, 20133 Milan, Italy
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Marco Locatelli
- Unit of Neurosurgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
| |
Collapse
|
17
|
Binding LP, Dasgupta D, Taylor PN, Thompson PJ, O'Keeffe AG, de Tisi J, McEvoy AW, Miserocchi A, Winston GP, Duncan JS, Vos SB. Contribution of White Matter Fiber Bundle Damage to Language Change After Surgery for Temporal Lobe Epilepsy. Neurology 2023; 100:e1621-e1633. [PMID: 36750386 PMCID: PMC10103113 DOI: 10.1212/wnl.0000000000206862] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 12/12/2022] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND AND OBJECTIVES In medically refractory temporal lobe epilepsy (TLE), 30%-50% of patients experience substantial language decline after resection in the language-dominant hemisphere. In this study, we investigated the contribution of white matter fiber bundle damage to language change at 3 and 12 months after surgery. METHODS We studied 127 patients who underwent TLE surgery from 2010 to 2019. Neuropsychological testing included picture naming, semantic fluency, and phonemic verbal fluency, performed preoperatively and 3 and 12 months postoperatively. Outcome was assessed using reliable change index (RCI; clinically significant decline) and change across timepoints (postoperative scores minus preoperative scores). Functional MRI was used to determine language lateralization. The arcuate fasciculus (AF), inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, middle longitudinal fasciculus (MLF), and uncinate fasciculus were mapped using diffusion MRI probabilistic tractography. Resection masks, drawn comparing coregistered preoperative and postoperative T1 MRI scans, were used as exclusion regions on preoperative tractography to estimate the percentage of preoperative tracts transected in surgery. Chi-squared assessments evaluated the occurrence of RCI-determined language decline. Independent sample t tests and MM-estimator robust regressions were used to assess the impact of clinical factors and fiber transection on RCI and change outcomes, respectively. RESULTS Language-dominant and language-nondominant resections were treated separately for picture naming because postoperative outcomes were significantly different between these groups. In language-dominant hemisphere resections, greater surgical damage to the AF and IFOF was related to RCI decline at 3 months. Damage to the inferior frontal subfasciculus of the IFOF was related to change at 3 months. In language-nondominant hemisphere resections, increased MLF resection was associated with RCI decline at 3 months, and damage to the anterior subfasciculus was related to change at 3 months. Language-dominant and language-nondominant resections were treated as 1 cohort for semantic and phonemic fluency because there were no significant differences in postoperative decline between these groups. Postoperative seizure freedom was associated with an absence of significant language decline 12 months after surgery for semantic fluency. DISCUSSION We demonstrate a relationship between fiber transection and naming decline after temporal lobe resection. Individualized surgical planning to spare white matter fiber bundles could help to preserve language function after surgery.
Collapse
Affiliation(s)
- Lawrence Peter Binding
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia.
| | - Debayan Dasgupta
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Peter Neal Taylor
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Pamela Jane Thompson
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Aidan G O'Keeffe
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Jane de Tisi
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Andrew William McEvoy
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Anna Miserocchi
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Gavin P Winston
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - John S Duncan
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| | - Sjoerd B Vos
- From the Department of Computer Science (L.P.B., S.B.V.), Centre for Medical Image Computing, Department of Clinical and Experimental Epilepsy (L.B.P., D.D., P.N.T., P.J.T., J.d.T., A.W.M., A.M., G.P.W., J.S.D.), UCL Queen Square Institute of Neurology, and Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, University College London; Victor Horsley Department of Neurosurgery (D.D., A.W.M., A.M.), and Department of Neuropsychology (P.J.T.), National Hospital for Neurology and Neurosurgery, Queen Square, London; CNNP Lab (P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University; School of Mathematical Sciences (A.G.O.), University of Nottingham; Epilepsy Society MRI Unit (J.d.T., G.P.W., J.S.D.), Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom; Department of Medicine (G.P.W.), Division of Neurology, Queen's University, Kingston, Canada; and Centre for Microscopy (S.B.V), Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
| |
Collapse
|
18
|
Owen T, Janiukstyte V, Hall GR, Chowdhury FA, Diehl B, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Wang Y, Taylor PN. Interictal MEG abnormalities to guide intracranial electrode implantation and predict surgical outcome. ArXiv 2023:arXiv:2304.05199v1. [PMID: 37090233 PMCID: PMC10120748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography (MEG). Quantitative abnormality mapping using MEG has recently been shown to have potential clinical value. We hypothesised that if quantifiable MEG abnormalities were sampled by iEEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent MEG and subsequent iEEG recordings as part of pre-surgical evaluation. Eyes-closed resting-state interictal MEG band power abnormality maps were derived from 70 healthy controls as a normative baseline. MEG abnormality maps were compared to iEEG electrode implantation, with the spatial overlap of iEEG electrode placement and cerebral MEG abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue, and subsequent resection of the strongest abnormalities determined by MEG and iEEG corresponded to surgical success. Intracranial electrodes were implanted in brain tissue with the most abnormal MEG findings - in individuals that were seizure-free post-operatively (T=3.9, p=0.003), but not in those who did not become seizure free. The overlap between MEG abnormalities and electrode placement distinguished surgical outcome groups moderately well (AUC=0.68). In isolation, the resection of the strongest abnormalities as defined by MEG and iEEG separated surgical outcome groups well, AUC=0.71, AUC=0.74 respectively. A model incorporating all three features separated surgical outcome groups best (AUC=0.80). Intracranial EEG is a key tool to delineate the EZ and help render individuals seizure-free post-operatively. We showed that data-driven abnormality maps derived from resting-state MEG recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of post-operative seizure-freedom, which leverages both MEG and iEEG recordings, could aid patient counselling of expected outcome.
Collapse
Affiliation(s)
- Tom Owen
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Vytene Janiukstyte
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Gerard R Hall
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Andrew McEvoy
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - John S Duncan
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Fergus Rugg-Gunn
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Peter Neal Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| |
Collapse
|
19
|
Owen TW, Schroeder GM, Janiukstyte V, Hall GR, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg‐Gunn F, Wang Y, Taylor PN. MEG abnormalities and mechanisms of surgical failure in neocortical epilepsy. Epilepsia 2023; 64:692-704. [PMID: 36617392 PMCID: PMC10952279 DOI: 10.1111/epi.17503] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
OBJECTIVE Epilepsy surgery fails to achieve seizure freedom in 30%-40% of cases. It is not fully understood why some surgeries are unsuccessful. By comparing interictal magnetoencephalography (MEG) band power from patient data to normative maps, which describe healthy spatial and population variability, we identify patient-specific abnormalities relating to surgical failure. We propose three mechanisms contributing to poor surgical outcome: (1) not resecting the epileptogenic abnormalities (mislocalization), (2) failing to remove all epileptogenic abnormalities (partial resection), and (3) insufficiently impacting the overall cortical abnormality. Herein we develop markers of these mechanisms, validating them against patient outcomes. METHODS Resting-state MEG recordings were acquired for 70 healthy controls and 32 patients with refractory neocortical epilepsy. Relative band-power spatial maps were computed using source-localized recordings. Patient and region-specific band-power abnormalities were estimated as the maximum absolute z-score across five frequency bands using healthy data as a baseline. Resected regions were identified using postoperative magnetic resonance imaging (MRI). We hypothesized that our mechanistically interpretable markers would discriminate patients with and without postoperative seizure freedom. RESULTS Our markers discriminated surgical outcome groups (abnormalities not targeted: area under the curve [AUC] = 0.80, p = .003; partial resection of epileptogenic zone: AUC = 0.68, p = .053; and insufficient cortical abnormality impact: AUC = 0.64, p = .096). Furthermore, 95% of those patients who were not seizure-free had markers of surgical failure for at least one of the three proposed mechanisms. In contrast, of those patients without markers for any mechanism, 80% were ultimately seizure-free. SIGNIFICANCE The mapping of abnormalities across the brain is important for a wide range of neurological conditions. Here we have demonstrated that interictal MEG band-power mapping has merit for the localization of pathology and improving our mechanistic understanding of epilepsy. Our markers for mechanisms of surgical failure could be used in the future to construct predictive models of surgical outcome, aiding clinical teams during patient pre-surgical evaluations.
Collapse
Affiliation(s)
- Thomas W. Owen
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Gabrielle M. Schroeder
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Vytene Janiukstyte
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Gerard R. Hall
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | | | | | | | | | | | - Yujiang Wang
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
- UCL Queen Square Institute of NeurologyLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Peter N. Taylor
- Computational Neurology, Neuroscience & Psychiatry Lab, ICOS Group, School of ComputingNewcastle UniversityNewcastle upon TyneUK
- UCL Queen Square Institute of NeurologyLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| |
Collapse
|
20
|
Dasgupta D, Finn R, Chari A, Giampiccolo D, de Tisi J, O'Keeffe AG, Miserocchi A, McEvoy AW, Vos SB, Duncan JS. Hippocampal resection in temporal lobe epilepsy: Do we need to resect the tail? Epilepsy Res 2023; 190:107086. [PMID: 36709527 PMCID: PMC10626579 DOI: 10.1016/j.eplepsyres.2023.107086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 12/24/2022] [Accepted: 01/09/2023] [Indexed: 01/13/2023]
Abstract
INTRODUCTION Anteromesial temporal lobe resection is the most common surgical technique used to treat drug-resistant mesial temporal lobe epilepsy, particularly when secondary to hippocampal sclerosis. Structural and functional imaging data suggest the importance of sparing the posterior hippocampus for minimising language and memory deficits. Recent work has challenged the view that maximal posterior hippocampal resection improves seizure outcome. This study was designed to assess whether resection of posterior hippocampal atrophy was associated with improved seizure outcome. METHODS Retrospective analysis of a prospective database of all anteromesial temporal lobe resections performed in individuals with hippocampal sclerosis at our epilepsy surgery centre, 2013-2021. Pre- and post-operative MRI were reviewed by 2 neurosurgical fellows to assess whether the atrophic segment, displayed by automated hippocampal morphometry, was resected, and ILAE seizure outcomes were collected at 1 year and last clinical follow-up. Data analysis used univariate and binary logistic regression. RESULTS Sixty consecutive eligible patients were identified of whom 70% were seizure free (ILAE Class 1 & 2) at one year. There was no statistically significant difference in seizure freedom outcomes in patients who had complete resection of atrophic posterior hippocampus or not (Fisher's Exact test statistic 0.69, not significant at p < .05) both at one year, and at last clinical follow-up. In the multivariate analysis only a history of status epilepticus (OR=0.2, 95%CI:0.042-0.955, p = .04) at one year, and pre-operative psychiatric disorder (OR=0.145, 95%CI:0.036-0.588, p = .007) at last clinical follow-up, were associated with a reduced chance of seizure freedom. SIGNIFICANCE Our data suggest that seizure freedom is not associated with whether or not posterior hippocampal atrophy is resected. This challenges the traditional surgical dogma of maximal posterior hippocampal resection in anteromesial temporal lobe resections and is a step further optimising this surgical procedure to maximise seizure freedom and minimise associated language and memory deficits.
Collapse
Affiliation(s)
- Debayan Dasgupta
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.
| | - Roisin Finn
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.
| | - Aswin Chari
- Department of Neurosurgery, Great Ormond Street Hospital, London, UK; Developmental Neuroscience, Great Ormond Street Institute of Child Health, University College London, London, UK.
| | - Davide Giampiccolo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; Institute of Neurosciences, Cleveland Clinic London, London, UK.
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Aidan G O'Keeffe
- School of Mathematical Sciences, University of Nottingham, Nottingham, UK. aidan.o'
| | - Anna Miserocchi
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.
| | - Andrew W McEvoy
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.
| | - Sjoerd B Vos
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK; Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia.
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
| |
Collapse
|
21
|
Khoo A, Alim-Marvasti A, de Tisi J, Diehl B, Walker MC, Miserocchi A, McEvoy AW, Chowdhury FA, Duncan JS. Value of semiology in predicting epileptogenic zone and surgical outcome following frontal lobe epilepsy surgery. Seizure 2023; 106:29-35. [PMID: 36736149 DOI: 10.1016/j.seizure.2023.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/11/2023] [Accepted: 01/30/2023] [Indexed: 02/01/2023] Open
Abstract
OBJECTIVE To evaluate the ability of semiology alone in localising the epileptogenic zone (EZ) in people with frontal lobe epilepsy (FLE) who underwent resective surgery. METHODS We examined data on all individuals who had FLE surgery at our centre between January 01, 2011 and December 31, 2020. Descriptions of ictal semiology were obtained from video-EEG telemetry reports and presurgical multidisciplinary meeting summaries. The putative EZ was represented by the final site of resection. We assessed how well initial and combined set-of-semiologies correlated anatomically with the EZ, using a semiology visualisation tool to generate probabilistic cortical heatmaps of involvement in seizures. RESULTS Sixty-one individuals had FLE surgery over the study period. Twelve months following surgery, 28/61 (46%) were completely seizure-free, with a further eight experiencing only auras. Comparing the semiology database with the putative EZ, combined set-of-semiology correctly lateralised in 77% (95% CI: 69-85%), localised to the frontal lobe in 57% (95% CI: 48-67%), frontal lobe subregions in 52% (95% CI: 43-62%), and frontal gyri in 25% (95% CI: 16-33%). No difference in degree of correlation was seen comparing those with ongoing seizures 12 months after surgery to those seizure free. SIGNIFICANCE Semiology alone was able to correctly lateralize the putative EZ in 77%, and localise to a sublobar level in approximately half of individuals who had FLE surgery. Semiology is not adequate alone and must be combined with imaging and EEG data to identify the epileptogenic zone.
Collapse
Affiliation(s)
- Anthony Khoo
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; College of Medicine and Public Health, Flinders University, Bedford Park, SA, 5042, Australia.
| | - Ali Alim-Marvasti
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Jane de Tisi
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Beate Diehl
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Matthew C Walker
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Andrew W McEvoy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Fahmida A Chowdhury
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - John S Duncan
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| |
Collapse
|
22
|
Gvozdanovic A, Jozsa F, Fersht N, Grover PJ, Kirby G, Kitchen N, Mangiapelo R, McEvoy A, Miserocchi A, Patel R, Thorne L, Williams N, Kosmin M, Marcus HJ. Integration of a personalised mobile health (mHealth) application into the care of patients with brain tumours: proof-of-concept study (IDEAL stage 1). BMJ Surg Interv Health Technol 2022; 4:e000130. [PMID: 36579146 PMCID: PMC9791405 DOI: 10.1136/bmjsit-2021-000130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 11/23/2022] [Indexed: 12/24/2022] Open
Abstract
Objectives Brain tumours lead to significant morbidity including a neurocognitive, physical and psychological burden of disease. The extent to which they impact the multiple domains of health is difficult to capture leading to a significant degree of unmet needs. Mobile health tools such as Vinehealth have the potential to identify and address these needs through real-world data generation and delivery of personalised educational material and therapies. We aimed to establish the feasibility of Vinehealth integration into brain tumour care, its ability to collect real-world and (electronic) patient-recorded outcome (ePRO) data, and subjective improvement in care. Design A mixed-methodology IDEAL stage 1 study. Setting A single tertiary care centre. Participants Six patients consented and four downloaded and engaged with the mHealth application throughout the 12 weeks of the study. Main outcome measures Over a 12-week period, we collected real-world and ePRO data via Vinehealth. We assessed qualitative feedback from mixed-methodology surveys and semistructured interviews at recruitment and after 2 weeks. Results 565 data points were captured including, but not limited to: symptoms, activity, well-being and medication. EORTC QLQ-BN20 and EQ-5D-5L completion rates (54% and 46%) were impacted by technical issues; 100% completion rates were seen when ePROs were received. More brain cancer tumour-specific content was requested. All participants recommended the application and felt it improved care. Conclusions Our findings indicate value in an application to holistically support patients living with brain cancer tumours and established the feasibility and safety of further studies to more rigorously assess this.
Collapse
Affiliation(s)
- Andrew Gvozdanovic
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Felix Jozsa
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Naomi Fersht
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Patrick James Grover
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Neil Kitchen
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Andrew McEvoy
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Anna Miserocchi
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Lewis Thorne
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Norman Williams
- University College London Division of Surgery and Interventional Science, London, UK
| | - Michael Kosmin
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Hani J Marcus
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| |
Collapse
|
23
|
Ferreira-Atuesta C, de Tisi J, McEvoy AW, Miserocchi A, Khoury J, Yardi R, Vegh DT, Butler J, Lee HJ, Deli-Peri V, Yao Y, Wang FP, Zhang XB, Shakhatreh L, Siriratnam P, Neal A, Sen A, Tristram M, Varghese E, Biney W, Gray WP, Peralta AR, Rainha-Campos A, Gonçalves-Ferreira AJC, Pimentel J, Arias JF, Terman S, Terziev R, Lamberink HJ, Braun KPJ, Otte WM, Rugg-Gunn FJ, Gonzalez W, Bentes C, Hamandi K, O'Brien TJ, Perucca P, Yao C, Burman RJ, Jehi L, Duncan JS, Sander JW, Koepp M, Galovic M. Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults. Brain 2022:6841346. [DOI: 10.1093/brain/awac437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 10/20/2022] [Accepted: 11/06/2022] [Indexed: 11/24/2022] Open
Abstract
Abstract
More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications (ASMs). We aimed to identify predictors of seizure recurrence after starting postoperative ASM withdrawal and develop and validate predictive models.
We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started ASM withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting ASM withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of ASM withdrawal were focal non motor-aware seizures after surgery and before withdrawal (adjusted hazards ratio [aHR] 5.5, 95% confidence interval [CI] 2.7-11.1), history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of ASM withdrawal (aHR 0.9, 95% CI 0.8-0.9), and number of ASMs at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models.
We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative ASMs withdrawal. These multicentre-validated models may assist clinicians when discussing ASM withdrawal after surgery with their patients.
Collapse
Affiliation(s)
- Carolina Ferreira-Atuesta
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
- Department of Neurology, Icahn School of Medicine at Mount Sinai , New York , USA
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | - Jean Khoury
- Cleveland Clinic Epilepsy Center , Cleveland , USA
| | - Ruta Yardi
- Cleveland Clinic Epilepsy Center , Cleveland , USA
| | | | - James Butler
- Constantiaberg Mediclinic Hospital, Division of Neurology, Neuroscience Institute, University of Cape Town , South Africa
| | - Hamin J Lee
- Constantiaberg Mediclinic Hospital, Division of Neurology, Neuroscience Institute, University of Cape Town , South Africa
| | - Victoria Deli-Peri
- Constantiaberg Mediclinic Hospital, Division of Neurology, Neuroscience Institute, University of Cape Town , South Africa
| | - Yi Yao
- Department of Epilepsy Surgery, Shenzhen Children's Hospital , Shenzhen, Guangdong , China
- Department of Functional Neurosurgery, Xiamen Humanity Hospital , Xiamen, FuJian , China
| | - Feng-Peng Wang
- Department of Functional Neurosurgery, Xiamen Humanity Hospital , Xiamen, FuJian , China
| | - Xiao-Bin Zhang
- Department of Functional Neurosurgery, Xiamen Humanity Hospital , Xiamen, FuJian , China
| | - Lubna Shakhatreh
- Department of Neuroscience, Central Clinical School, Alfred Health, Monash University , Level 6, Melbourne VIC 3000 , Australia
- Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne , Parkville, VIC 3050 , Australia
- Neurology Department, Alfred Health , Melbourne, VIC 3000 , Australia
| | | | - Andrew Neal
- Department of Neuroscience, Central Clinical School, Alfred Health, Monash University , Level 6, Melbourne VIC 3000 , Australia
- Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne , Parkville, VIC 3050 , Australia
- Neurology Department, Alfred Health , Melbourne, VIC 3000 , Australia
| | - Arjune Sen
- Oxford Epilepsy Research Group, NIHR Biomedical Research Centre, Nuffield Department of Clinical Neurosciences, University of Oxford , UK
- Department of Neurology, 3rd Floor, West Wing, John Radcliffe Hospital , Oxford OX3 9DU , UK
| | - Maggie Tristram
- Oxford Epilepsy Research Group, NIHR Biomedical Research Centre, Nuffield Department of Clinical Neurosciences, University of Oxford , UK
- Department of Neurology, 3rd Floor, West Wing, John Radcliffe Hospital , Oxford OX3 9DU , UK
| | - Elizabeth Varghese
- Department of Neurology, University Hospital of Wales , Cardiff, CF144XW , UK
| | - Wendy Biney
- Department of Neurology, University Hospital of Wales , Cardiff, CF144XW , UK
| | - William P Gray
- The Wales Epilepsy Unit, Department of Neurology, University Hospital of Wales and Division of Psychological Medicine and Clinical Neurosciences Cardiff, Cardiff University , Cardiff, CF144XW , UK
| | - Ana Rita Peralta
- Centro de Referência para Epilepsias Refratárias (member of EpiCare). Hospital de Santa Maria - Centro Hospitalar Universitário Lisboa Norte. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa , Lisboa , Portugal
| | - Alexandre Rainha-Campos
- Centro de Referência para Epilepsias Refratárias (member of EpiCare). Hospital de Santa Maria - Centro Hospitalar Universitário Lisboa Norte. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa , Lisboa , Portugal
| | - António J C Gonçalves-Ferreira
- Centro de Referência para Epilepsias Refratárias (member of EpiCare). Hospital de Santa Maria - Centro Hospitalar Universitário Lisboa Norte. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa , Lisboa , Portugal
| | - José Pimentel
- Centro de Referência para Epilepsias Refratárias (member of EpiCare). Hospital de Santa Maria - Centro Hospitalar Universitário Lisboa Norte. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa , Lisboa , Portugal
| | | | - Samuel Terman
- University of Michigan Department of Neurology , Ann Arbor, MI 48109 , USA
| | - Robert Terziev
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich , Zurich , Switzerland
| | - Herm J Lamberink
- Department of Neurology, Haaglanden Medical Center , The Hague , The Netherlands
- Department of Child Neurology, University Medical Center Utrecht , Utrecht , The Netherlands
| | - Kees P J Braun
- Department of Child Neurology, University Medical Center Utrecht , Utrecht , The Netherlands
| | - Willem M Otte
- Department of Child Neurology, University Medical Center Utrecht , Utrecht , The Netherlands
| | - Fergus J Rugg-Gunn
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | | | - Carla Bentes
- Centro de Referência para Epilepsias Refratárias (member of EpiCare). Hospital de Santa Maria - Centro Hospitalar Universitário Lisboa Norte. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa , Lisboa , Portugal
| | - Khalid Hamandi
- The Wales Epilepsy Unit, Department of Neurology, University Hospital of Wales and Division of Psychological Medicine and Clinical Neurosciences Cardiff, Cardiff University , Cardiff, CF144XW , UK
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, Alfred Health, Monash University , Level 6, Melbourne VIC 3000 , Australia
- Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne , Parkville, VIC 3050 , Australia
| | - Piero Perucca
- Department of Neuroscience, Central Clinical School, Alfred Health, Monash University , Level 6, Melbourne VIC 3000 , Australia
- Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne , Parkville, VIC 3050 , Australia
- Neurology Department, Alfred Health , Melbourne, VIC 3000 , Australia
- Department of Medicine, Austin Health, The University of Melbourne; Comprehensive Epilepsy Program , Austin Health, Heidelberg, VIC 3084 , Australia
| | - Chen Yao
- Department of Neurosurgery, the First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital , Shenzhen, Guangdong , China
- Shenzhen Epilepsy Center (Shenzhen Children's Hospital and Shenzhen Second People's Hospital), Shenzhen , China
| | - Richard J Burman
- Constantiaberg Mediclinic Hospital, Division of Neurology, Neuroscience Institute, University of Cape Town , South Africa
- Oxford Epilepsy Research Group, NIHR Biomedical Research Centre, Nuffield Department of Clinical Neurosciences, University of Oxford , UK
- Department of Neurology, 3rd Floor, West Wing, John Radcliffe Hospital , Oxford OX3 9DU , UK
| | - Lara Jehi
- Cleveland Clinic Epilepsy Center , Cleveland , USA
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | - Josemir W Sander
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
- Department of Neurology, West China Hospital, Sichuan University , Chengdu 610041 , China
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede 2103SW , The Netherlands
| | - Matthias Koepp
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy (DCEE), NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology , London, WC1N 3BG UK
- Chalfont Centre for Epilepsy , Chalfont St Peter SL9 0RJ , UK
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich , Zurich , Switzerland
| |
Collapse
|
24
|
Binding L, Taylor P, Baxendale S, McEvoy A, Miserocchi A, Duncan J, Vos S. Network changes predicting language decline following anterior temporal lobe resection. J Neurol Psychiatry 2022. [DOI: 10.1136/jnnp-2022-abn2.32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Anterior temporal lobe resection (ATLR), while successful can result in lasting impairment of language function. White matter bundles have been shown to explain some of the variance seen in language decline after ATLR. Network analysis of the structural connectome has been shown superior in predicting preoperative language ability but remains unexplored in predicting postoperative ability.Diffusion MRI-based tractography was used to generate the preoperative connectome on 54 left-lat- eralised (as determined by functional MRI), left-hemisphere ATLR. Postoperative connectomes were estimated via manually drawn resection masks. Graded naming test (GNT), semantic, and letter fluency were binarised into significant decline or not (via their reliable change indices). Strength (sum of connec- tions) and betweenness centrality (interconnectivity) network changes were generated using pre- and postoperative connectomes as predictor variables. Each model was entered into a linear support vector machine incorporating synthetic minority over-sampling technique for class imbalances.Strength changes alone accurately predicted 81.6% of patients who had GNT decline. Betweenness centrality changes accurately predicted 73.3% of patients who had letter fluency decline. Patients with semantic decline were predicted equally as well by strength and betweenness centrality changes (accuracy=71.1%).These findings demonstrate the usefulness of the structural network in predicting and potentially prevent- ing postoperative language decline.
Collapse
|
25
|
Dasgupta D, Miserocchi A, McEvoy AW, Duncan JS. Previous, current, and future stereotactic EEG techniques for localising epileptic foci. Expert Rev Med Devices 2022; 19:571-580. [PMID: 36003028 DOI: 10.1080/17434440.2022.2114830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required. AREAS COVERED This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally. EXPERT OPINION We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future.
Collapse
Affiliation(s)
- Debayan Dasgupta
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.,Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Anna Miserocchi
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew W McEvoy
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
| |
Collapse
|
26
|
Khoo A, de Tisi J, Foong J, Bindman D, O'Keeffe AG, Sander JW, Miserocchi A, McEvoy AW, Duncan JS. Long-term seizure, psychiatric and socioeconomic outcomes after frontal lobe epilepsy surgery. Epilepsy Res 2022; 186:106998. [PMID: 35985250 DOI: 10.1016/j.eplepsyres.2022.106998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 07/17/2022] [Accepted: 08/09/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Resective surgery for selected individuals with frontal lobe epilepsy can be effective, although multimodal outcomes are less established than in temporal lobe epilepsy. We describe long-term seizure remission and relapse patterns, psychiatric comorbidity, and socioeconomic outcomes following frontal lobe epilepsy surgery. METHODS We reviewed individual data on frontal lobe epilepsy procedures at our center between 1990 and 2020. This included the presurgical evaluation, operative details and annual postoperative seizure and psychiatric outcomes, prospectively recorded in an epilepsy surgery database. Outcome predictors were subjected to multivariable analysis, and rates of seizure freedom were analyzed using Kaplan-Meier methods. We used longitudinal assessment of the Index of Multiple Deprivation to assess change in socioeconomic status over time. RESULTS A total of 122 individuals with a median follow-up of seven years were included. Of these, 33 (27 %) had complete seizure freedom following surgery, with a further 13 (11 %) having only auras. Focal MRI abnormality, histopathology (focal cortical dysplasia, cavernoma or dysembryoplastic neuronal epithelial tumor) and fewer anti-seizure medications at the time of surgery were predictive of a favorable outcome; 67 % of those seizure-free for the first 12 months after surgery never experienced a seizure relapse. Thirty-one of 50 who had preoperative psychiatric pathology noticed improved psychiatric symptomatology by two years postoperatively. New psychiatric comorbidity was diagnosed in 15 (13 %). Persistent motor complications occurred in 5 % and dysphasia in 2 %. No significant change in socioeconomic deciles of deprivation was observed after surgery. SIGNIFICANCE Favorable long-term seizure, psychiatric and socioeconomic outcomes can be seen following frontal lobe epilepsy surgery. This is a safe and effective treatment that should be offered to suitable individuals early.
Collapse
Affiliation(s)
- Anthony Khoo
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; College of Medicine and Public Health, Flinders University, Bedford Park SA 5042, Australia.
| | - Jane de Tisi
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Jacqueline Foong
- Department of Neuropsychiatry, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Dorothea Bindman
- Department of Neuropsychiatry, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Aidan G O'Keeffe
- School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK
| | - Josemir W Sander
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK; Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, Heemstede 2103SW, Netherlands; Department of Neurology, West China Hospital, & Institute of Brain Science & Brain-inspired Technology, Sichuan University, Chengdu 610041, China
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Andrew W McEvoy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - John S Duncan
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
| |
Collapse
|
27
|
Binding L, Taylor P, Thompson P, Baxendale S, Tisi JD, McEvoy A, Miserocchi A, Winston G, Duncan J, Vos SB. 009 Language decline following white matter tract damage during anterior temporal lobe resection in language dominant hemisphere. J Neurol Neurosurg Psychiatry 2022. [DOI: 10.1136/jnnp-2022-abn.334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Anterior temporal lobe resection (ATLR) for temporal lobe epilepsy (TLE) has remission rates up to 80%, however is underutilised, in part because of the risk of language decline following surgery. Language decline occurs in up to 50% of ATLR in the language dominant side. This can occur despite careful planning with functional MRI (fMRI) language mapping. Several white matter bundles are close to the resection area which could contribute to language decline. Diffusion MRI-based fibre tracking to map the arcuate, uncinate, inferior fronto-occipital, inferior, and middle longitudinal fasciculus was performed on 43 patients. We extracted the left-sided bundles in those temporal lobe epilepsy patients who had left-dominant language based on verbal fluency functional MRI (fMRI) and a left-sided resection. Resection masks were manually drawn and used as exclusion regions. Changes from pre- to post-operative tractography and language ability were measured as percentages. Linear regression revealed that the McKenna Graded Naming test decline was predicted by the arcuate and middle longitudinal fasciculus resection (F(2,41)=5.562, p=0.007) with an adjusted R2 of 0.175. These findings demonstrate that damage to anterior arcuate extensions and the middle longitudinal fasciculus affects picture naming ability.lawrence.binding.19@ucl.ac.uk
Collapse
|
28
|
Taylor PN, Papasavvas CA, Owen TW, Schroeder GM, Hutchings FE, Chowdhury FA, Diehl B, Duncan JS, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Wang Y. Normative brain mapping of interictal intracranial EEG to localize epileptogenic tissue. Brain 2022; 145:939-949. [PMID: 35075485 PMCID: PMC9050535 DOI: 10.1093/brain/awab380] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 08/19/2021] [Accepted: 09/03/2021] [Indexed: 11/14/2022] Open
Abstract
The identification of abnormal electrographic activity is important in a wide range of neurological disorders, including epilepsy for localizing epileptogenic tissue. However, this identification may be challenging during non-seizure (interictal) periods, especially if abnormalities are subtle compared to the repertoire of possible healthy brain dynamics. Here, we investigate if such interictal abnormalities become more salient by quantitatively accounting for the range of healthy brain dynamics in a location-specific manner. To this end, we constructed a normative map of brain dynamics, in terms of relative band power, from interictal intracranial recordings from 234 participants (21 598 electrode contacts). We then compared interictal recordings from 62 patients with epilepsy to the normative map to identify abnormal regions. We proposed that if the most abnormal regions were spared by surgery, then patients would be more likely to experience continued seizures postoperatively. We first confirmed that the spatial variations of band power in the normative map across brain regions were consistent with healthy variations reported in the literature. Second, when accounting for the normative variations, regions that were spared by surgery were more abnormal than those resected only in patients with persistent postoperative seizures (t = -3.6, P = 0.0003), confirming our hypothesis. Third, we found that this effect discriminated patient outcomes (area under curve 0.75 P = 0.0003). Normative mapping is a well-established practice in neuroscientific research. Our study suggests that this approach is feasible to detect interictal abnormalities in intracranial EEG, and of potential clinical value to identify pathological tissue in epilepsy. Finally, we make our normative intracranial map publicly available to facilitate future investigations in epilepsy and beyond.
Collapse
Affiliation(s)
- Peter N Taylor
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Christoforos A Papasavvas
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Thomas W Owen
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Gabrielle M Schroeder
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Frances E Hutchings
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Beate Diehl
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - John S Duncan
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Andrew W McEvoy
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Sjoerd B Vos
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Matthew C Walker
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Yujiang Wang
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| |
Collapse
|
29
|
Shapey J, Xie Y, Nabavi E, Ebner M, Saeed SR, Kitchen N, Dorward N, Grieve J, McEvoy AW, Miserocchi A, Grover P, Bradford R, Lim YM, Ourselin S, Brandner S, Jaunmuktane Z, Vercauteren T. Optical properties of human brain and tumour tissue: An ex vivo study spanning the visible range to beyond the second near-infrared window. J Biophotonics 2022; 15:e202100072. [PMID: 35048541 DOI: 10.1002/jbio.202100072] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 06/14/2023]
Abstract
Neuro-oncology surgery would benefit from detailed intraoperative tissue characterization provided by noncontact, contrast-agent-free, noninvasive optical imaging methods. In-depth knowledge of target tissue optical properties across a wide-wavelength spectrum could inform the design of optical imaging and computational methods to enable robust tissue analysis during surgery. We adapted a dual-beam integrating sphere to analyse small tissue samples and investigated ex vivo optical properties of five types of human brain tumour (meningioma, pituitary adenoma, schwannoma, low- and high-grade glioma) and nine different types of healthy brain tissue across a wavelength spectrum of 400 to 1800 nm. Fresh and frozen tissue samples were analysed. All tissue types demonstrated similar absorption spectra, but the reduced scattering coefficients of tumours show visible differences in the obtained optical spectrum compared to those of surrounding normal tissue. These results underline the potential of optical imaging technologies for intraoperative tissue characterization.
Collapse
Affiliation(s)
- Jonathan Shapey
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Yijing Xie
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Elham Nabavi
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Michael Ebner
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Shakeel R Saeed
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- The Ear Institute, University College London, London, UK
- The Royal National Throat, Nose and Ear Hospital, London, UK
| | - Neil Kitchen
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Neil Dorward
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Joan Grieve
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew W McEvoy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Patrick Grover
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Robert Bradford
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Yau-Mun Lim
- Division of Neuropathology, UCL Queen Square Institute of Neurology, and The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, and The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Zane Jaunmuktane
- Division of Neuropathology, UCL Queen Square Institute of Neurology, and The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| |
Collapse
|
30
|
Jha A, Diehl B, Strange B, Miserocchi A, Chowdhury F, McEvoy AW, Nachev P. Orienting to fear under transient focal disruption of the human amygdala. Brain 2022; 146:135-148. [PMID: 35104842 PMCID: PMC9825557 DOI: 10.1093/brain/awac032] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 10/28/2021] [Accepted: 01/08/2022] [Indexed: 01/13/2023] Open
Abstract
Responding to threat is under strong survival pressure, promoting the evolution of systems highly optimized for the task. Though the amygdala is implicated in 'detecting' threat, its role in the action that immediately follows-'orienting'-remains unclear. Critical to mounting a targeted response, such early action requires speed, accuracy, and resilience optimally achieved through conserved, parsimonious, dedicated systems, insured against neural loss by a parallelized functional organization. These characteristics tend to conceal the underlying substrate not only from correlative methods but also from focal disruption over time scales long enough for compensatory adaptation to take place. In a study of six patients with intracranial electrodes temporarily implanted for the clinical evaluation of focal epilepsy, we investigated gaze orienting to fear during focal, transient, unilateral direct electrical disruption of the amygdala. We showed that the amygdala is necessary for rapid gaze shifts towards faces presented in the contralateral hemifield regardless of their emotional expression, establishing its functional lateralization. Behaviourally dissociating the location of presented fear from the direction of the response, we implicated the amygdala not only in detecting contralateral faces, but also in automatically orienting specifically towards fearful ones. This salience-specific role was demonstrated within a drift-diffusion model of action to manifest as an orientation bias towards the location of potential threat. Pixel-wise analysis of target facial morphology revealed scleral exposure as its primary driver, and induced gamma oscillations-obtained from intracranial local field potentials-as its time-locked electrophysiological correlate. The amygdala is here reconceptualized as a functionally lateralized instrument of early action, reconciling previous conflicting accounts confined to detection, and revealing a neural organisation analogous to the superior colliculus, with which it is phylogenetically kin. Greater clarity on its role has the potential to guide therapeutic resection, still frequently complicated by impairments of cognition and behaviour related to threat, and inform novel focal stimulation techniques for the management of neuropsychiatric conditions.
Collapse
Affiliation(s)
- Ashwani Jha
- Correspondence to: Ashwani Jha UCL Queen Square Institute of Neurology, London, UK E-mail:
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, London, UK
| | - Bryan Strange
- CTB-UPM and Department of Neuroimaging, Reina Sofia Centre for Alzheimer's Research, Madrid, Spain
| | | | | | | | - Parashkev Nachev
- Correspondence may also be addressed to: Parashkev Nachev E-mail:
| |
Collapse
|
31
|
Mancini L, Casagranda S, Gautier G, Peter P, Lopez B, Thorne L, McEvoy A, Miserocchi A, Samandouras G, Kitchen N, Brandner S, De Vita E, Torrealdea F, Rega M, Schmitt B, Liebig P, Sanverdi E, Golay X, Bisdas S. CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing. Eur J Nucl Med Mol Imaging 2022; 49:2377-2391. [PMID: 35029738 PMCID: PMC9165287 DOI: 10.1007/s00259-022-05676-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/31/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE Accurate glioma classification affects patient management and is challenging on non- or low-enhancing gliomas. This study investigated the clinical value of different chemical exchange saturation transfer (CEST) metrics for glioma classification and assessed the diagnostic effect of the presence of abundant fluid in glioma subpopulations. METHODS Forty-five treatment-naïve glioma patients with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status received CEST MRI (B1rms = 2μT, Tsat = 3.5 s) at 3 T. Magnetization transfer ratio asymmetry and CEST metrics (amides: offset range 3-4 ppm, amines: 1.5-2.5 ppm, amide/amine ratio) were calculated with two models: 'asymmetry-based' (AB) and 'fluid-suppressed' (FS). The presence of T2/FLAIR mismatch was noted. RESULTS IDH-wild type had higher amide/amine ratio than IDH-mutant_1p/19qcodel (p < 0.022). Amide/amine ratio and amine levels differentiated IDH-wild type from IDH-mutant (p < 0.0045) and from IDH-mutant_1p/19qret (p < 0.021). IDH-mutant_1p/19qret had higher amides and amines than IDH-mutant_1p/19qcodel (p < 0.035). IDH-mutant_1p/19qret with AB/FS mismatch had higher amines than IDH-mutant_1p/19qret without AB/FS mismatch ( < 0.016). In IDH-mutant_1p/19qret, the presence of AB/FS mismatch was closely related to the presence of T2/FLAIR mismatch (p = 0.014). CONCLUSIONS CEST-derived biomarkers for amides, amines, and their ratio can help with histomolecular staging in gliomas without intense contrast enhancement. T2/FLAIR mismatch is reflected in the presence of AB/FS CEST mismatch. The AB/FS CEST mismatch identifies glioma subgroups that may have prognostic and clinical relevance.
Collapse
Affiliation(s)
- Laura Mancini
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK.
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK.
| | | | | | | | | | - Lewis Thorne
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Andrew McEvoy
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Anna Miserocchi
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Neil Kitchen
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, London, UK
- The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Enrico De Vita
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Francisco Torrealdea
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | - Marilena Rega
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | | | | | - Eser Sanverdi
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Xavier Golay
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Sotirios Bisdas
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| |
Collapse
|
32
|
Bongiovanni A, Foca F, Menis J, Stucci SL, Artioli F, Guadalupi V, Forcignanò MR, Fantini M, Recine F, Mercatali L, Spadazzi C, Burgio MA, Fausti V, Miserocchi A, Ibrahim T. Immune Checkpoint Inhibitors With or Without Bone-Targeted Therapy in NSCLC Patients With Bone Metastases and Prognostic Significance of Neutrophil-to-Lymphocyte Ratio. Front Immunol 2021; 12:697298. [PMID: 34858389 PMCID: PMC8631508 DOI: 10.3389/fimmu.2021.697298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/08/2021] [Indexed: 12/26/2022] Open
Abstract
Introduction Bone metastases (BMs) are a negative prognostic factor in patients with non-small cell lung cancer (NSCLC). Although immune-checkpoint inhibitors (ICIs) have dramatically changed the therapeutic landscape of NSCLC, little information is available on BMs from NSCLC treated with ICIs alone or in association with bone-targeted therapy (BTT) such as zoledronate or denosumab. Methods From 2014 to 2020, 111 of the 142 patients with BMs secondary to NSCLC extrapolated from the prospective multicenter Italian BM Database were eligible for analysis. Information on blood count, comorbidities, and toxicity was retrospectively collected. The neutrophil-to-lymphocyte ratio (NLR) pre- and post-treatment was calculated. Survival was analyzed using the Kaplan-Meier method, with statistical significance of survival differences assessed using the log-rank test. Results Median age was 66 (range, 42-84) years. Performance status (PS) Eastern Cooperative Oncology Group (ECOG) was 0-1 in 79/111 patients. The majority of patients (89.2%) had adenocarcinoma histology. At a median follow-up of 47.4 months, median progression-free (mPFS) and overall survival (mOS) was 4.9 (95%CI, 2.8-10.0) and 11.9 (95%CI, 8.2-14.4) months, respectively. Forty-six (43.4%) patients with BM NSCLC underwent first- or further-line therapy with ICIs: 28 (60.8%) received nivolumab, 9 (19.6%) pembrolizumab, and 9 (19.6%) atezolizumab. Of the 46 patients treated with ICIs, 30 (65.2%) underwent BTT: 24 (80.0%) with zoledronate and 6 (20.0%) with denosumab. The ICI-alone group had an mOS of 15.8 months [95%CI, 8.2-not evaluable (NE)] vs. 21.8 months (95%CI, 14.5-not evaluable) for the ICI plus BTT group and 7.5 (95%CI, 6.1-10.9) months for the group receiving other treatments (p < 0.001). NLR ≤5 had a positive impact on OS. Conclusion BTT appears to have a synergistic effect when used in combination with ICIs, improving patient survival.
Collapse
Affiliation(s)
- Alberto Bongiovanni
- Osteoncology and Rare Tumors Center (CDO-TR), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Flavia Foca
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Jessica Menis
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.,Medical Oncology Department, Istituto Oncologico Veneto IRCCS, Padova, Italy.,Medical Oncology, Department of Medicine, University of Verona, Azienda Ospedaliera Universitaria Integrata (AOUI) di Verona, Verona, Italy
| | - Stefania Luigia Stucci
- Medical Oncology Unit, Policlinico Hospital of Bari Department of Biomedical Sciences and Human Oncology University of Bari "A. Moro", Bari, Italy
| | | | | | | | | | | | - Laura Mercatali
- Osteoncology and Rare Tumors Center (CDO-TR), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Chiara Spadazzi
- Osteoncology and Rare Tumors Center (CDO-TR), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Marco Angelo Burgio
- Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Valentina Fausti
- Osteoncology and Rare Tumors Center (CDO-TR), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Anna Miserocchi
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Toni Ibrahim
- Osteoncology and Rare Tumors Center (CDO-TR), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| |
Collapse
|
33
|
Sone D, Ahmad M, Thompson PJ, Baxendale S, Vos SB, Xiao F, de Tisi J, McEvoy AW, Miserocchi A, Duncan JS, Koepp MJ, Galovic M. Optimal Surgical Extent for Memory and Seizure Outcome in Temporal Lobe Epilepsy. Ann Neurol 2021; 91:131-144. [PMID: 34741484 PMCID: PMC8916104 DOI: 10.1002/ana.26266] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 10/21/2021] [Accepted: 10/31/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVE Postoperative memory decline is an important consequence of anterior temporal lobe resection (ATLR) for temporal lobe epilepsy (TLE), and the extent of resection may be a modifiable factor. This study aimed to define optimal resection margins for cognitive outcome while maintaining a high rate of postoperative seizure freedom. METHODS This cohort study evaluated the resection extent on postoperative structural MRI using automated voxel-based methods and manual measurements in 142 consecutive patients with unilateral drug refractory TLE (74 left, 68 right TLE) who underwent standard ATLR. RESULTS Voxel-wise analyses revealed that postsurgical verbal memory decline correlated with resections of the posterior hippocampus and inferior temporal gyrus, whereas larger resections of the fusiform gyrus were associated with worsening of visual memory in left TLE. Limiting the posterior extent of left hippocampal resection to 55% reduced the odds of significant postoperative verbal memory decline by a factor of 8.1 (95% CI 1.5-44.4, p = 0.02). Seizure freedom was not related to posterior resection extent, but to the piriform cortex removal after left ATLR. In right TLE, variability of the posterior extent of resection was not associated with verbal and visual memory decline or seizures after surgery. INTERPRETATION The extent of surgical resection is an independent and modifiable risk factor for cognitive decline and seizures after left ATLR. Adapting the posterior extent of left ATLR might optimize postoperative outcome, with reduced risk of memory impairment while maintaining comparable seizure-freedom rates. The current, more lenient, approach might be appropriate for right ATLR. ANN NEUROL 2021.
Collapse
Affiliation(s)
- Daichi Sone
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK.,Department of Psychiatry, The Jikei University School of Medicine, Tokyo, Japan
| | - Maria Ahmad
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - Pamela J Thompson
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK.,Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy, University College London Queen Square Institute of Neurology, London, UK.,Magnetic Resonance Imaging Unit, Epilepsy Society, Chalfont St Peter, UK.,Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| |
Collapse
|
34
|
Leon-Rojas JE, Iqbal S, Vos SB, Rodionov R, Miserocchi A, McEvoy AW, Vakharia VN, Mancini L, Galovic M, Sparks RE, Ourselin S, Cardoso JM, Koepp MJ, Duncan JS. Resection of the piriform cortex for temporal lobe epilepsy: a Novel approach on imaging segmentation and surgical application. Br J Neurosurg 2021:1-6. [PMID: 34406102 DOI: 10.1080/02688697.2021.1966385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/09/2021] [Accepted: 08/05/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND The piriform cortex (PC) occupies both banks of the endorhinal sulcus and has an important role in the pathophysiology of temporal lobe epilepsy (TLE). A recent study showed that resection of more than 50% of PC increased the odds of becoming seizure free by a factor of 16. OBJECTIVE We report the feasibility of manual segmentation of PC and application of the Geodesic Information Flows (GIF) algorithm to automated segmentation, to guide resection. METHODS Manual segmentation of PC was performed by two blinded independent examiners in 60 patients with TLE (55% Left TLE, 52% female) with a median age of 35 years (IQR, 29-47 years) and 20 controls (60% Women) with a median age of 39.5 years (IQR, 31-49). The GIF algorithm was used to create an automated pipeline for parcellating PC which was used to guide excision as part of temporal lobe resection for TLE. RESULTS Right PC was larger in patients and controls. Parcellation of PC was used to guide anterior temporal lobe resection, with subsequent seizure freedom and no visual field or language deficit. CONCLUSION Reliable segmentation of PC is feasible and can be applied prospectively to guide neurosurgical resection that increases the chances of a good outcome from temporal lobe resection for TLE.
Collapse
Affiliation(s)
- Jose E Leon-Rojas
- NeurALL Research Group, Medical School, Universidad Internacional del Ecuador, Quito, Ecuador
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Sabahat Iqbal
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Sjoerd B Vos
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK
| | - Roman Rodionov
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Anna Miserocchi
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew W McEvoy
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Vejay N Vakharia
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Laura Mancini
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Marian Galovic
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Department of Neurology, Zurich University Hospital, Zurich, Switzerland
| | - Rachel E Sparks
- School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK
| | - Jorge M Cardoso
- School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK
| | - Matthias J Koepp
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - John S Duncan
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| |
Collapse
|
35
|
Vakharia VN, Vos SB, Winston GP, Gutman MJ, Wykes V, McEvoy AW, Miserocchi A, Sparks R, Ourselin S, Duncan JS. Intraoperative overlay of optic radiation tractography during anteromesial temporal resection: a prospective validation study. J Neurosurg 2021; 136:543-552. [PMID: 34330090 DOI: 10.3171/2020.12.jns203437] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 12/02/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Anteromesial temporal lobe resection (ATLR) results in long-term seizure freedom in patients with drug-resistant focal mesial temporal lobe epilepsy (MTLE). There is significant anatomical variation in the anterior projection of the optic radiation (OR), known as Meyer's loop, between individuals and between hemispheres in the same individual. Damage to the OR results in contralateral superior temporal quadrantanopia that may preclude driving in 33%-66% of patients who achieve seizure freedom. Tractography of the OR has been shown to prevent visual field deficit (VFD) when surgery is performed in an interventional MRI (iMRI) suite. Because access to iMRI is limited at most centers, the authors investigated whether use of a neuronavigation system with a microscope overlay in a conventional theater is sufficient to prevent significant VFD during ATLR. METHODS Twenty patients with drug-resistant MTLE who underwent ATLR (9 underwent right-side ATLR, and 9 were male) were recruited to participate in this single-center prospective cohort study. Tractography of the OR was performed with preoperative 3-T multishell diffusion data that were overlaid onto the surgical field by using a conventional neuronavigation system linked to a surgical microscope. Phantom testing confirmed overlay projection errors of < 1 mm. VFD was quantified preoperatively and 3 to 12 months postoperatively by using Humphrey and Esterman perimetry. RESULTS Perimetry results were available for all patients postoperatively, but for only 11/20 (55%) patients preoperatively. In 1/20 (5%) patients, a significant VFD occurred that would prevent driving in the UK on the basis of the results on Esterman perimetry. The VFD was identified early in the series, despite the surgical approach not transgressing OR tractography, and was subsequently found to be due to retraction injury. Tractography was also used from this point onward to inform retractor placement, and no further significant VFDs occurred. CONCLUSIONS Use of OR tractography with overlay outside of an iMRI suite, with application of an appropriate error margin, can be used during approach to the temporal horn of the lateral ventricle and carries a 5% risk of VFD that is significant enough to preclude driving postoperatively. OR tractography can also be used to inform retractor placement. These results warrant a larger prospective comparative study of the use of OR tractography-guided mesial temporal resection.
Collapse
Affiliation(s)
- Vejay N Vakharia
- 1Department of Clinical and Experimental Epilepsy, University College London and Epilepsy Society MRI Unit, London.,2National Hospital for Neurology and Neurosurgery, Queen Square, London
| | - Sjoerd B Vos
- 3Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, United Kingdom
| | - Gavin P Winston
- 1Department of Clinical and Experimental Epilepsy, University College London and Epilepsy Society MRI Unit, London.,2National Hospital for Neurology and Neurosurgery, Queen Square, London.,4Department of Medicine, Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | | | - Victoria Wykes
- 6Institute of Cancer and Genomic Sciences, University of Birmingham.,7Department of Neurosurgery, Queen Elizabeth Hospital, Birmingham; and
| | - Andrew W McEvoy
- 1Department of Clinical and Experimental Epilepsy, University College London and Epilepsy Society MRI Unit, London.,2National Hospital for Neurology and Neurosurgery, Queen Square, London
| | - Anna Miserocchi
- 1Department of Clinical and Experimental Epilepsy, University College London and Epilepsy Society MRI Unit, London.,2National Hospital for Neurology and Neurosurgery, Queen Square, London
| | - Rachel Sparks
- 8School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, United Kingdom
| | - Sebastien Ourselin
- 8School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, United Kingdom
| | - John S Duncan
- 1Department of Clinical and Experimental Epilepsy, University College London and Epilepsy Society MRI Unit, London.,2National Hospital for Neurology and Neurosurgery, Queen Square, London
| |
Collapse
|
36
|
Gvozdanovic A, Mangiapelo R, Patel R, Kirby G, Kitchen N, Miserocchi A, McEvoy A, Grover P, Thorne L, Fersht N, Williams NR, Marcus H, Kosmin M. Implementation of the Vinehealth application, a digital health tool, into the care of patients living with brain cancer. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.e13582] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13582 Background: Cancers of the brain lead to significant neurocognitive, physical and psychological morbidities. Digital technologies provide a novel platform to capture and evaluate these needs. Mobile health (mHealth) applications typically focus on one aspect of care rather than addressing the multimodal needs of the demographic of these patients. The Vinehealth application aims to address this by tracking symptoms, delivering machine learning-based personalised educational content, and facilitating reminders for medications and appointments. Where mHealth interventions traditionally lack the evidence-based approach of pharmaceuticals, this study acts as an initial step in the rigorous assessment of a new digital health tool. Methods: A mixed methodology approach was applied to evaluate the Vinehealth application as a care delivery adjunct. Patients with brain cancer were recruited from the day of their procedure ± 7 days. Over a 12-week period, we collected real-world and ePRO data via the application. We assessed qualitative feedback from mixed-methodology surveys and semi-structured interviews at onboarding and after two weeks of application use. Results: Six participants enrolled of whom four downloaded the application; four completed all interviews. One patient set up their device incorrectly and so couldn't receive the questionnaires; excluding this patient, the EQ-5D-5L and EORTC QLQ-BN20 completion rates were 100% and 83% respectively. Average scores (±SD) at onboarding and offboarding were EQ-5D-5L: 2.07±1.28 and 1.73±1.22, and QLQ-BN20: 13.33 and 22.5. In total: 212 symptoms, 174 activity, and 47 medication data points were captured, and 113 educational articles were read. Participants were generally optimistic about application use. All users stated they would recommend Vinehealth and expressed subjective improvements in care. Accessibility issues in the ePRO delivery system which impacted completion rate were identified and have subsequently been fully addressed. Conclusions: This feasibility study showed acceptable patient use, led to a subjective improvement in care, and demonstrated effective collection of real-world and validated ePRO data. This provides a strong basis to further explore the integration of the Vinehealth application into brain cancer care. This study will inform the design of a larger, more comprehensive trial continuing to evaluate improvements in care delivery through data collection, educational support and patient empowerment.
Collapse
Affiliation(s)
- Andrew Gvozdanovic
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | | | | | | | - Neil Kitchen
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Anna Miserocchi
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Andy McEvoy
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Patrick Grover
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Lewis Thorne
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Naomi Fersht
- University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | | | - Hani Marcus
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Michael Kosmin
- University College London Hospitals NHS Foundation Trust, London, United Kingdom
| |
Collapse
|
37
|
Valmorri L, Vertogen B, Zingaretti C, Miserocchi A, Volpi R, Clemente A, Bondi I, Valli I, Rudnas B, Martinelli G, Nanni O. Clinical research activities during COVID-19: the point of view of a promoter of academic clinical trials. BMC Med Res Methodol 2021; 21:91. [PMID: 33931012 PMCID: PMC8086972 DOI: 10.1186/s12874-021-01291-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 04/21/2021] [Indexed: 11/19/2022] Open
Abstract
Background During the COVID-19 emergency, IRST IRCCS, an Italian cancer research institute and promoter of no profit clinical studies, adapted its activities and procedures as per European and national guidelines to maintain a high standard of clinical trials, uphold participant safety and guarantee the robustness and reliability of the data collected. This study presents the measures adopted by our institute with the aim of providing information that could be useful to other academic centers promoting clinical trials during the pandemic. Main text After an in-depth analysis of European and Italian guidelines and consultation and analysis of publications regarding the actions implemented by international no profit clinical trial promoters during the emergency, we monitored the way in which the institute managed clinical trials, verifying compliance with regulatory guidelines and clinical procedures, and evaluating screening and recruitment trends in studies. During the pandemic, our center activated a new clinical trial for the treatment of patients with COVID-19. A number of procedural changes in clinical trials were also authorized through notified amendments, in accordance with Italian Medicines Agency (AIFA) guidelines. Patient screening and enrolment was not interrupted in any site participating in multicenter interventional clinical trials on drugs. The institute provided clear indications about essential procedures to be followed, identifying those that could be postponed or carried out by telephone/teleconference. All external sites were monitored remotely, avoiding on-site visits. Although home-working was encouraged, the presence of staff in the central office was also guaranteed to ensure the continuity of promoter activities. Conclusions Some measures adopted by IRST could also be effective outside of the COVID-19 period, e.g. numerous activities relating to clinical trial management could be performed on a home-working basis, using suitable digital technologies. In the future, electronic medical records and shared guidelines will be essential for the correct identification and management of trial risks, including the protection of the rights and privacy of subjects taking part. Promoter supervision could be increased by implementing centralized monitoring tools to guarantee data quality. Closer collaboration between promoters and local study staff is needed to optimize trial management. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-021-01291-0.
Collapse
Affiliation(s)
- Linda Valmorri
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy.
| | - Bernadette Vertogen
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Chiara Zingaretti
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Anna Miserocchi
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Roberta Volpi
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Alberto Clemente
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Isabella Bondi
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Irene Valli
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Britt Rudnas
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Giovanni Martinelli
- Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy
| | - Oriana Nanni
- Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| |
Collapse
|
38
|
Granados A, Perez-Garcia F, Schweiger M, Vakharia V, Vos SB, Miserocchi A, McEvoy AW, Duncan JS, Sparks R, Ourselin S. A generative model of hyperelastic strain energy density functions for multiple tissue brain deformation. Int J Comput Assist Radiol Surg 2021; 16:141-150. [PMID: 33165705 PMCID: PMC7822772 DOI: 10.1007/s11548-020-02284-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 10/23/2020] [Indexed: 11/06/2022]
Abstract
PURPOSE Estimation of brain deformation is crucial during neurosurgery. Whilst mechanical characterisation captures stress-strain relationships of tissue, biomechanical models are limited by experimental conditions. This results in variability reported in the literature. The aim of this work was to demonstrate a generative model of strain energy density functions can estimate the elastic properties of tissue using observed brain deformation. METHODS For the generative model a Gaussian Process regression learns elastic potentials from 73 manuscripts. We evaluate the use of neo-Hookean, Mooney-Rivlin and 1-term Ogden meta-models to guarantee stability. Single and multiple tissue experiments validate the ability of our generative model to estimate tissue properties on a synthetic brain model and in eight temporal lobe resection cases where deformation is observed between pre- and post-operative images. RESULTS Estimated parameters on a synthetic model are close to the known reference with a root-mean-square error (RMSE) of 0.1 mm and 0.2 mm between surface nodes for single and multiple tissue experiments. In clinical cases, we were able to recover brain deformation from pre- to post-operative images reducing RMSE of differences from 1.37 to 1.08 mm on the ventricle surface and from 5.89 to 4.84 mm on the resection cavity surface. CONCLUSION Our generative model can capture uncertainties related to mechanical characterisation of tissue. When fitting samples from elastography and linear studies, all meta-models performed similarly. The Ogden meta-model performed the best on hyperelastic studies. We were able to predict elastic parameters in a reference model on a synthetic phantom. However, deformation observed in clinical cases is only partly explained using our generative model.
Collapse
Affiliation(s)
- Alejandro Granados
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | | | - Martin Schweiger
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Vejay Vakharia
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Sjoerd B Vos
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Anna Miserocchi
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew W McEvoy
- National Hospital for Neurology and Neurosurgery, London, UK
| | - John S Duncan
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Rachel Sparks
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sébastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| |
Collapse
|
39
|
Sinha N, Wang Y, Moreira da Silva N, Miserocchi A, McEvoy AW, de Tisi J, Vos SB, Winston GP, Duncan JS, Taylor PN. Structural Brain Network Abnormalities and the Probability of Seizure Recurrence After Epilepsy Surgery. Neurology 2020; 96:e758-e771. [PMID: 33361262 PMCID: PMC7884990 DOI: 10.1212/wnl.0000000000011315] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 09/24/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE We assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences. METHODS We examined data from 51 patients with TLE who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the preoperative structural, diffusion, and postoperative structural MRI, we generated 2 networks: presurgery network and surgically spared network. Standardizing these networks with respect to controls, we determined the number of abnormal nodes before surgery and expected to be spared by surgery. We incorporated these 2 abnormality measures and 13 commonly acquired clinical data from each patient into a robust machine learning framework to estimate patient-specific chances of seizures persisting after surgery. RESULTS Patients with more abnormal nodes had a lower chance of complete seizure freedom at 1 year and, even if seizure-free at 1 year, were more likely to relapse within 5 years. The number of abnormal nodes was greater and their locations more widespread in the surgically spared networks of patients with poor outcome than in patients with good outcome. We achieved an area under the curve of 0.84 ± 0.06 and specificity of 0.89 ± 0.09 in predicting unsuccessful seizure outcomes (International League Against Epilepsy [ILAE] 3-5) as opposed to complete seizure freedom (ILAE 1) at 1 year. Moreover, the model-predicted likelihood of seizure relapse was significantly correlated with the grade of surgical outcome at year 1 and associated with relapses up to 5 years after surgery. CONCLUSION Node abnormality offers a personalized, noninvasive marker that can be combined with clinical data to better estimate the chances of seizure freedom at 1 year and subsequent relapse up to 5 years after ATLR. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that node abnormality predicts postsurgical seizure recurrence.
Collapse
Affiliation(s)
- Nishant Sinha
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada.
| | - Yujiang Wang
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Nádia Moreira da Silva
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Anna Miserocchi
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Andrew W McEvoy
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Jane de Tisi
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Sjoerd B Vos
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Gavin P Winston
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - John S Duncan
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Peter N Taylor
- From the Translational and Clinical Research Institute (N.S.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (N.S., Y.W., N.M.d.S., P.N.T.), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle Upon Tyne; NIHR University College London Hospitals Biomedical Research Centre (Y.W., A.M., A.W.M., J.d.T., S.B.V., G.P.W., J.S.D., P.N.T.), UCL Institute of Neurology, Queen Square; Centre for Medical Image Computing (S.B.V.), University College London; Epilepsy Society MRI Unit (S.B.V., G.P.W., J.S.D), Chalfont St Peter, UK; and Department of Medicine (G.P.W.,), Division of Neurology, Queen's University, Kingston, Ontario, Canada
| |
Collapse
|
40
|
Tariq K, Das JM, Monaghan S, Miserocchi A, McEvoy A. A case report of Vagus nerve stimulation for intractable hiccups. Int J Surg Case Rep 2020; 78:219-222. [PMID: 33360634 PMCID: PMC7773651 DOI: 10.1016/j.ijscr.2020.12.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 12/08/2020] [Accepted: 12/11/2020] [Indexed: 11/27/2022] Open
Abstract
Intractable hiccups are associated with significant morbidity and may lead to mortality. Several medical, pharmacological, surgical and novel treatment options are available. Vagus nerve stimulator placement is a novel surgical option for the treatment of intractable hiccups. Vagus nerve stimulator is currently not approved for the indication of intractable hiccups.
Introduction Intractable hiccups frequently result from an underlying pathology and can cause considerable illness in the patients. Initial remedies such as drinking cold water, induction of emesis, carotid sinus massage or Valsalva manoeuvre all seem to work by over stimulating the Vagus nerve. Pharmacotherapy with baclofen, gabapentin and other centrally and peripherally acting agents such as chlorpromazine and metoclopramide are reserved as second line treatment. Medical refractory cases even indulge in unconventional therapies such as hypnosis, massages and acupuncture. Surgical intervention, although undertaken very rarely, predominantly revolves around phrenic nerve crushing, blockade or pacing. A novel surgical strategy is emerging in the form of Vagus nerve stimulator (VNS) placement with three cases cited in literature to date with varying degrees of success. Here the authors report a case of VNS placement for intractable hiccups with partial success, in accordance with SCARE-2018 guidelines. Presentation of the case An 85-year-old gentleman with a 9-year history of intractable hiccups secondary to pneumonia came to our hospital. The hiccups were symptomatic causing anorexia, insomnia, irritability, depression, exhaustion, muscle wasting and weight loss. The patient underwent countless medical evaluations. All examinations and investigations yielded normal results. The patient underwent aggressive pharmacotherapy, home remedies and unconventional therapies for intractable hiccups but to no avail. He also underwent left phrenic nerve blocking and resection without therapeutic success. The patient presented to our hospital and decision for VNS insertion was taken for compassionate reasons considering patient morbidity. The patient demonstrated significant improvement in his symptoms following VNS insertion. Discussion A temporary hiccup is an occasional happening experienced by everyone. However, intractable hiccups are associated with significant morbidity and often mortality. Several medical, pharmacological, surgical and novel treatment options are available for intractable hiccups. Conclusion VNS insertion is a novel surgical option for the treatment of intractable hiccups.
Collapse
Affiliation(s)
- Kanza Tariq
- National Hospital for Neurology and Neurosurgery, Queen's Square, London, UK.
| | - Joe M Das
- National Hospital for Neurology and Neurosurgery, Queen's Square, London, UK
| | - Sasha Monaghan
- National Hospital for Neurology and Neurosurgery, Queen's Square, London, UK
| | - Anna Miserocchi
- National Hospital for Neurology and Neurosurgery, Queen's Square, London, UK
| | - Andrew McEvoy
- National Hospital for Neurology and Neurosurgery, Queen's Square, London, UK
| |
Collapse
|
41
|
Galovic M, de Tisi J, McEvoy AW, Miserocchi A, Vos SB, Borzi G, Cueva Rosillo J, Vuong KA, Nachev P, Duncan JS, Koepp MJ. Resective surgery prevents progressive cortical thinning in temporal lobe epilepsy. Brain 2020; 143:3262-3272. [PMID: 33179036 PMCID: PMC7719024 DOI: 10.1093/brain/awaa284] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 05/25/2020] [Accepted: 07/14/2020] [Indexed: 12/17/2022] Open
Abstract
Focal epilepsy in adults is associated with progressive atrophy of the cortex at a rate more than double that of normal ageing. We aimed to determine whether successful epilepsy surgery interrupts progressive cortical thinning. In this longitudinal case-control neuroimaging study, we included subjects with unilateral temporal lobe epilepsy (TLE) before (n = 29) or after (n = 56) anterior temporal lobe resection and healthy volunteers (n = 124) comparable regarding age and sex. We measured cortical thickness on paired structural MRI scans in all participants and compared progressive thinning between groups using linear mixed effects models. Compared to ageing-related cortical thinning in healthy subjects, we found progressive cortical atrophy on vertex-wise analysis in TLE before surgery that was bilateral and localized beyond the ipsilateral temporal lobe. In these regions, we observed accelerated annualized thinning in left (left TLE 0.0192 ± 0.0014 versus healthy volunteers 0.0032 ± 0.0013 mm/year, P < 0.0001) and right (right TLE 0.0198 ± 0.0016 versus healthy volunteers 0.0037 ± 0.0016 mm/year, P < 0.0001) presurgical TLE cases. Cortical thinning in these areas was reduced after surgical resection of the left (0.0074 ± 0.0016 mm/year, P = 0.0006) or right (0.0052 ± 0.0020 mm/year, P = 0.0006) anterior temporal lobe. Directly comparing the post- versus presurgical TLE groups on vertex-wise analysis, the areas of postoperatively reduced thinning were in both hemispheres, particularly, but not exclusively, in regions that were affected preoperatively. Participants who remained completely seizure-free after surgery had no more progressive thinning than that observed during normal ageing. Those with postoperative seizures had small areas of continued accelerated thinning after surgery. Thus, successful epilepsy surgery prevents progressive cortical atrophy that is observed in TLE and may be potentially neuroprotective. This effect was more pronounced in those who remained seizure-free after temporal lobe resection, normalizing the rate of atrophy to that of normal ageing. These results provide evidence of epilepsy surgery preventing further cerebral damage and provide incentives for offering early surgery in refractory TLE.
Collapse
Affiliation(s)
- Marian Galovic
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Giuseppe Borzi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Institute of Neurology, University of Catanzaro, Italy
- Neurology Unit, Ospedale Civile San’Agostino Estense, Azienda Ospedaliero-Universitaria Modena, Modena Italy
| | - Juana Cueva Rosillo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Khue Anh Vuong
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Parashkev Nachev
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| |
Collapse
|
42
|
Vivekananda U, Bush D, Bisby JA, Baxendale S, Rodionov R, Diehl B, Chowdhury FA, McEvoy AW, Miserocchi A, Walker MC, Burgess N. Theta power and theta-gamma coupling support long-term spatial memory retrieval. Hippocampus 2020; 31:213-220. [PMID: 33263940 PMCID: PMC7898809 DOI: 10.1002/hipo.23284] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/11/2020] [Accepted: 11/15/2020] [Indexed: 11/07/2022]
Abstract
Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations to support long‐term memory. Here we asked 10 presurgical epilepsy patients undergoing intracranial EEG recording to perform a long‐term spatial memory task in desktop virtual reality and found that increased theta power in two discrete bands (“low” 2‐5 Hz and “high” 6‐11 Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between “low” theta phase and gamma amplitude during the same period was associated with improved task performance. Finally, low and high gamma amplitude appeared to peak at different phases of the theta cycle; providing a novel connection between human hippocampal function and rodent data. These results help to elucidate the role of theta oscillations and theta‐gamma phase‐amplitude coupling in human long‐term memory.
Collapse
Affiliation(s)
- Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Daniel Bush
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK
| | - James A Bisby
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Neil Burgess
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK.,Wellcome Centre for Human NeuroImaging, University College London, London, UK
| |
Collapse
|
43
|
Ramaraju S, Wang Y, Sinha N, McEvoy AW, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Taylor PN. Removal of Interictal MEG-Derived Network Hubs Is Associated With Postoperative Seizure Freedom. Front Neurol 2020; 11:563847. [PMID: 33071948 PMCID: PMC7543719 DOI: 10.3389/fneur.2020.563847] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 08/20/2020] [Indexed: 01/21/2023] Open
Abstract
Objective: To investigate whether MEG network connectivity was associated with epilepsy duration, to identify functional brain network hubs in patients with refractory focal epilepsy, and assess if their surgical removal was associated with post-operative seizure freedom. Methods: We studied 31 patients with drug refractory focal epilepsy who underwent resting state magnetoencephalography (MEG), and structural magnetic resonance imaging (MRI) as part of pre-surgical evaluation. Using the structural MRI, we generated 114 cortical regions of interest, performed surface reconstruction and MEG source localization. Representative source localized signals for each region were correlated with each other to generate a functional brain network. We repeated this procedure across three randomly chosen one-minute epochs. Network hubs were defined as those with the highest intra-hemispheric mean correlations. Post-operative MRI identified regions that were surgically removed. Results: Greater mean MEG network connectivity was associated with a longer duration of epilepsy. Patients who were seizure free after surgery had more hubs surgically removed than patients who were not seizure free (AUC = 0.76, p = 0.01) consistently across three randomly chosen time segments. Conclusion: Our results support a growing literature implicating network hub involvement in focal epilepsy, the removal of which by surgery is associated with greater chance of post-operative seizure freedom.
Collapse
Affiliation(s)
- Sriharsha Ramaraju
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Nishant Sinha
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Fergus Rugg-Gunn
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| |
Collapse
|
44
|
Vakharia VN, Sparks RE, Granados A, Miserocchi A, McEvoy AW, Ourselin S, Duncan JS. Refining Planning for Stereoelectroencephalography: A Prospective Validation of Spatial Priors for Computer-Assisted Planning With Application of Dynamic Learning. Front Neurol 2020; 11:706. [PMID: 32765411 PMCID: PMC7380116 DOI: 10.3389/fneur.2020.00706] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 06/10/2020] [Indexed: 11/17/2022] Open
Abstract
Objective: Stereoelectroencephalography (SEEG) is a procedure in which many electrodes are stereotactically implanted within different regions of the brain to estimate the epileptogenic zone in patients with drug-refractory focal epilepsy. Computer-assisted planning (CAP) improves risk scores, gray matter sampling, orthogonal drilling angles to the skull and intracerebral length in a fraction of the time required for manual planning. Due to differences in planning practices, such algorithms may not be generalizable between institutions. We provide a prospective validation of clinically feasible trajectories using “spatial priors” derived from previous implantations and implement a machine learning classifier to adapt to evolving planning practices. Methods: Thirty-two patients underwent consecutive SEEG implantations utilizing computer-assisted planning over 2 years. Implanted electrodes from the first 12 patients (108 electrodes) were used as a training set from which entry and target point spatial priors were generated. CAP was then prospectively performed using the spatial priors in a further test set of 20 patients (210 electrodes). A K-nearest neighbor (K-NN) machine learning classifier was implemented as an adaptive learning method to modify the spatial priors dynamically. Results: All of the 318 prospective computer-assisted planned electrodes were implanted without complication. Spatial priors developed from the training set generated clinically feasible trajectories in 79% of the test set. The remaining 21% required entry or target points outside of the spatial priors. The K-NN classifier was able to dynamically model real-time changes in the spatial priors in order to adapt to the evolving planning requirements. Conclusions: We provide spatial priors for common SEEG trajectories that prospectively integrate clinically feasible trajectory planning practices from previous SEEG implantations. This allows institutional SEEG experience to be incorporated and used to guide future implantations. The deployment of a K-NN classifier may improve the generalisability of the algorithm by dynamically modifying the spatial priors in real-time as further implantations are performed.
Collapse
Affiliation(s)
- Vejay N Vakharia
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Chalfont Centre for Epilepsy, London, United Kingdom
| | - Rachel E Sparks
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Alejandro Granados
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Chalfont Centre for Epilepsy, London, United Kingdom
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Chalfont Centre for Epilepsy, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Chalfont Centre for Epilepsy, London, United Kingdom
| |
Collapse
|
45
|
da Silva NM, Forsyth R, McEvoy A, Miserocchi A, de Tisi J, Vos SB, Winston GP, Duncan J, Wang Y, Taylor PN. Network reorganisation following anterior temporal lobe resection and relation with post-surgery seizure relapse: A longitudinal study. Neuroimage Clin 2020; 27:102320. [PMID: 32623138 PMCID: PMC7334605 DOI: 10.1016/j.nicl.2020.102320] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/12/2020] [Accepted: 06/13/2020] [Indexed: 12/18/2022]
Abstract
Diffusion changes assessed at two time points following epilepsy surgery. Graph theory and connectometry revealed substantial longitudinal diffusion changes. Changes were found beyond the site of resection. Postoperative seizure freedom associated with longitudinal structural changes.
Objective To characterise temporal lobe epilepsy (TLE) surgery-induced changes in brain network properties, as measured using diffusion weighted MRI, and investigate their association with postoperative seizure-freedom. Methods For 48 patients who underwent anterior temporal lobe resection, diffusion weighted MRI was acquired pre-operatively, 3–4 months post-operatively (N = 48), and again 12 months post-operatively (N = 13). Data for 17 controls were also acquired over the same period. After registering all subjects to a common space, we performed two complementary analyses of the subjects’ quantitative anisotropy (QA) maps. 1) A connectometry analysis which is sensitive to changes in subsections of fasciculi. 2) A graph theory approach which integrates connectivity information across the wider brain network. Results We found significant postoperative alterations in QA in patients relative to controls measured over the same period. Reductions were primarily located in the uncinate fasciculus and inferior fronto-occipital fasciculus ipsilaterally for all patients. Larger reductions were associated with postoperative seizure-freedom in left TLE. Increased QA was mainly located in corona radiata and corticopontine tracts. Graph theoretic analysis revealed widespread increases in nodal betweenness centrality, which were not associated with patient outcomes. Conclusion Substantial alterations in QA occur in the months after epilepsy surgery, suggesting Wallerian degeneration and strengthening of specific white matter tracts. Greater reductions in QA were related to postoperative seizure freedom in left TLE.
Collapse
Affiliation(s)
- Nádia Moreira da Silva
- CNNP lab(1), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Rob Forsyth
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Andrew McEvoy
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Anna Miserocchi
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Jane de Tisi
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Sjoerd B Vos
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom
| | - Gavin P Winston
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Medicine, Division of Neurology, Queen's University, Kingston, Canada
| | - John Duncan
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom
| | - Yujiang Wang
- CNNP lab(1), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Peter N Taylor
- CNNP lab(1), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom.
| |
Collapse
|
46
|
Wang Y, Sinha N, Schroeder GM, Ramaraju S, McEvoy AW, Miserocchi A, de Tisi J, Chowdhury FA, Diehl B, Duncan JS, Taylor PN. Interictal intracranial electroencephalography for predicting surgical success: The importance of space and time. Epilepsia 2020; 61:1417-1426. [PMID: 32589284 PMCID: PMC7611164 DOI: 10.1111/epi.16580] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 05/21/2020] [Accepted: 05/21/2020] [Indexed: 12/14/2022]
Abstract
Objective Predicting postoperative seizure freedom using functional correlation networks derived from interictal intracranial electroencephalography (EEG) has shown some success. However, there are important challenges to consider: (1) electrodes physically closer to each other naturally tend to be more correlated, causing a spatial bias; (2) implantation location and number of electrodes differ between patients, making cross-subject comparisons difficult; and (3) functional correlation networks can vary over time but are currently assumed to be static. Methods In this study, we address these three challenges using intracranial EEG data from 55 patients with intractable focal epilepsy. Patients additionally underwent preoperative magnetic resonance imaging (MRI), intraoperative computed tomography, and postoperative MRI, allowing accurate localization of electrodes and delineation of the removed tissue. Results We show that normalizing for spatial proximity between nearby electrodes improves prediction of postsurgery seizure outcomes. Moreover, patients with more extensive electrode coverage were more likely to have their outcome predicted correctly (area under the receiver operating characteristic curve > 0.9, P « 0.05) but not necessarily more likely to have a better outcome. Finally, our predictions are robust regardless of the time segment analyzed. Significance Future studies should account for the spatial proximity of electrodes in functional network construction to improve prediction of postsurgical seizure outcomes. Greater coverage of both removed and spared tissue allows for predictions with higher accuracy.
Collapse
Affiliation(s)
- Yujiang Wang
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.,Institute of Neurology, University College London, London, UK
| | - Nishant Sinha
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - Gabrielle M Schroeder
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Sriharsha Ramaraju
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Andrew W McEvoy
- Institute of Neurology, University College London, London, UK
| | - Anna Miserocchi
- Institute of Neurology, University College London, London, UK
| | - Jane de Tisi
- Institute of Neurology, University College London, London, UK
| | | | - Beate Diehl
- Institute of Neurology, University College London, London, UK
| | - John S Duncan
- Institute of Neurology, University College London, London, UK
| | - Peter N Taylor
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.,Institute of Neurology, University College London, London, UK
| |
Collapse
|
47
|
Granados A, Rodionov R, Vakharia V, McEvoy AW, Miserocchi A, O'Keeffe AG, Duncan JS, Sparks R, Ourselin S. Automated computation and analysis of accuracy metrics in stereoencephalography. J Neurosci Methods 2020; 340:108710. [PMID: 32339522 PMCID: PMC7456795 DOI: 10.1016/j.jneumeth.2020.108710] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/27/2020] [Accepted: 03/28/2020] [Indexed: 11/25/2022]
Abstract
Automatic computation of SEEG accuracy metrics agree with those done manually. The choice of image to generate a scalp model has an effect on entry point metrics. Metrics have the lowest mean and variability when using an electrode bolt axis. Lateral shift deviation should include a measure of insertion depth error.
Background Implantation accuracy of electrodes during neurosurgical interventions is necessary to ensure safety and efficacy. Typically, metrics are computed by visual inspection which is tedious, prone to inter-/intra-observer variation, and difficult to replicate across sites. New Method We propose an automated approach for computing implantation metrics and investigate potential sources of error. We focus on accuracy metrics commonly reported in the literature to validate our approach against metrics computed manually including entry point (EP) and target point (TP) localisation errors and angle differences between planned and implanted trajectories in 15 patients with a total of 158 stereoelectroencephalography (SEEG) electrodes. We evaluate the effect of line-of-best-fit approaches, EP definition and lateral versus Euclidean distance on metrics to provide recommendations for reporting implantation accuracy metrics. Results We found no bias between manual and automated approaches for calculating accuracy metrics with limits of agreement of ±1 mm and ±1°. Automated metrics are robust to sources of errors including registration and electrode bending. We observe the highest error in EP deviations of μ = 0.25 mm when the post-implantation CT is used to define the point of entry. Comparison with Existing Method(s) We found no reports of automated approaches for quality assessment of SEEG electrode implantation. Neither the choice of metrics nor the possible errors that could occur have been investigated previously. Conclusions Our automated approach is useful to avoid human errors, unintentional bias and variation that may be introduced when manually computing metrics. Our work is relevant and timely to facilitate comparisons of studies reporting implantation accuracy.
Collapse
Affiliation(s)
- Alejandro Granados
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
| | - Roman Rodionov
- National Hospital of Neurology and Neurosurgery, London, UK
| | - Vejay Vakharia
- National Hospital of Neurology and Neurosurgery, London, UK
| | | | | | | | - John S Duncan
- National Hospital of Neurology and Neurosurgery, London, UK; Dept of Clin and Experim Epilepsy, UCL Queen Square, Inst of Neurol, UK
| | - Rachel Sparks
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Sébastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| |
Collapse
|
48
|
Marcus HJ, Vakharia VN, Sparks R, Rodionov R, Kitchen N, McEvoy AW, Miserocchi A, Thorne L, Ourselin S, Duncan JS. Computer-Assisted Versus Manual Planning for Stereotactic Brain Biopsy: A Retrospective Comparative Pilot Study. Oper Neurosurg (Hagerstown) 2020; 18:417-422. [PMID: 31381800 PMCID: PMC8414905 DOI: 10.1093/ons/opz177] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 04/01/2019] [Indexed: 12/26/2022]
Abstract
BACKGROUND Stereotactic brain biopsy is among the most common neurosurgical procedures. Planning
an optimally safe surgical trajectory requires careful attention to a number of features
including the following: (1) traversing the skull perpendicularly; (2) minimizing
trajectory length; and (3) avoiding critical neurovascular structures. OBJECTIVE To evaluate a platform, SurgiNav, for automated trajectory planning in stereotactic
brain biopsy. METHODS A prospectively maintained database was searched between February and August 2017 to
identify all adult patients who underwent stereotactic brain biopsy and for whom
postoperative imaging was available. In each case, the standard preoperative,
T1-weighted, gadolinium-enhanced magnetic resonance imaging was used to generate a model
of the cortex. A surgical trajectory was then generated using computer-assisted planning
(CAP) , and metrics of the trajectory were compared to the trajectory of the previously
implemented manual plan (MP). RESULTS Fifteen consecutive patients were identified. Feasible trajectories were generated
using CAP in all patients, and the mean angle determined using CAP was more
perpendicular to the skull than using MP (10.0° vs 14.6° from orthogonal;
P = .07), the mean trajectory length was shorter (38.5 vs 43.5 mm;
P = .01), and the risk score was lower (0.27 vs 0.52;
P = .03). CONCLUSION CAP for stereotactic brain biopsy appears feasible and may be safer in selected
cases.
Collapse
Affiliation(s)
- Hani J Marcus
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Vejay N Vakharia
- Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Rachel Sparks
- Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, United Kingdom
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
| | - Neil Kitchen
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Andrew W McEvoy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Lewis Thorne
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Sebastien Ourselin
- Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, United Kingdom
| | - John S Duncan
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
| |
Collapse
|
49
|
Vakharia VN, Sparks R, Miserocchi A, Vos SB, O'Keeffe A, Rodionov R, McEvoy AW, Ourselin S, Duncan JS. Computer-Assisted Planning for Stereoelectroencephalography (SEEG). Neurotherapeutics 2019; 16:1183-1197. [PMID: 31432448 PMCID: PMC6985077 DOI: 10.1007/s13311-019-00774-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Stereoelectroencephalography (SEEG) is a diagnostic procedure in which multiple electrodes are stereotactically implanted within predefined areas of the brain to identify the seizure onset zone, which needs to be removed to achieve remission of focal epilepsy. Computer-assisted planning (CAP) has been shown to improve trajectory safety metrics and generate clinically feasible trajectories in a fraction of the time needed for manual planning. We report a prospective validation study of the use of EpiNav (UCL, London, UK) as a clinical decision support software for SEEG. Thirteen consecutive patients (125 electrodes) undergoing SEEG were prospectively recruited. EpiNav was used to generate 3D models of critical structures (including vasculature) and other important regions of interest. Manual planning utilizing the same 3D models was performed in advance of CAP. CAP was subsequently employed to automatically generate a plan for each patient. The treating neurosurgeon was able to modify CAP generated plans based on their preference. The plan with the lowest risk score metric was stereotactically implanted. In all cases (13/13), the final CAP generated plan returned a lower mean risk score and was stereotactically implanted. No complication or adverse event occurred. CAP trajectories were generated in 30% of the time with significantly lower risk scores compared to manually generated. EpiNav has successfully been integrated as a clinical decision support software (CDSS) into the clinical pathway for SEEG implantations at our institution. To our knowledge, this is the first prospective study of a complex CDSS in stereotactic neurosurgery and provides the highest level of evidence to date.
Collapse
Affiliation(s)
- Vejay N Vakharia
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK.
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK.
| | - Rachel Sparks
- School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Sjoerd B Vos
- Wellcome Trust EPSRC Interventional and Surgical Sciences, University College London, London, UK
| | - Aidan O'Keeffe
- Department of Statistical Science, University College London, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| |
Collapse
|
50
|
Li K, Vakharia VN, Sparks R, Rodionov R, Vos SB, McEvoy AW, Miserocchi A, Wang M, Ourselin S, Duncan JS. Stereoelectroencephalography electrode placement: Detection of blood vessel conflicts. Epilepsia 2019; 60:1942-1948. [PMID: 31329275 PMCID: PMC6851756 DOI: 10.1111/epi.16294] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 06/27/2019] [Accepted: 06/28/2019] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Various forms of vascular imaging are performed to identify vessels that should be avoided during stereoelectroencephalography (SEEG) planning. Digital subtraction angiography (DSA) is the gold standard for intracranial vascular imaging. DSA is an invasive investigation, and a balance is necessary to identify all clinically relevant vessels and not to visualize irrelevant vessels that may unnecessarily restrict electrode placement. We sought to estimate the size of vessels that are clinically significant for SEEG planning. METHODS Thirty-three consecutive patients who underwent 354 SEEG electrode implantations planned with computer-assisted planning and DSA segmentation between 2016 and 2018 were identified from a prospectively maintained database. Intracranial positions of electrodes were segmented from postimplantation computed tomography scans. Each electrode was manually reviewed using "probe-eye view" with the raw preoperative DSA images for vascular conflicts. The diameter of vessels and the location of conflicts were noted. Vessel conflicts identified on raw DSA images were cross-referenced against other modalities to determine whether the conflict could have been detected. RESULTS One hundred sixty-six vessel conflicts were identified between electrodes and DSA-identified vessels, with 0-3 conflicts per electrode and a median of four conflicts per patient. The median diameter of conflicting vessels was 1.3 mm (interquartile range [IQR] = 1.0-1.5 mm). The median depth of conflict was 31.0 mm (IQR = 14.3-45.0 mm) from the cortical surface. The addition of sulcal models to DSA, magnetic resonance venography (MRV), and T1 + gadolinium images, as an exclusion zone during computer-assisted planning, would have prevented the majority of vessel conflicts. We were unable to determine whether vessels were displaced or transected by the electrodes. SIGNIFICANCE Vascular segmentation from DSA images was significantly more sensitive than T1 + gadolinium or MRV images. Electrode conflicts with vessels 1-1.5 mm in size did not result in a radiologically detectable or clinically significant hemorrhage and could potentially be excluded from consideration during SEEG planning.
Collapse
Affiliation(s)
- Kuo Li
- Department of NeurosurgeryThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
- Chalfont Centre for EpilepsyChalfontUK
| | - Vejay N. Vakharia
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
- Chalfont Centre for EpilepsyChalfontUK
| | - Rachel Sparks
- School of Biomedical Engineering and Imaging SciencesSt Thomas’ HospitalKing's College LondonLondonUK
| | - Roman Rodionov
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
- Chalfont Centre for EpilepsyChalfontUK
| | - Sjoerd B. Vos
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Andrew W. McEvoy
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
| | - Anna Miserocchi
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
| | - Maode Wang
- Department of NeurosurgeryThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging SciencesSt Thomas’ HospitalKing's College LondonLondonUK
| | - John S. Duncan
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- National Hospital for Neurology and Neurosurgery, Queen SquareLondonUK
- Chalfont Centre for EpilepsyChalfontUK
| |
Collapse
|