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Bieth T, Facque V, Altmayer V, Poisson I, Ovando-Tellez M, Moreno-Rodriguez S, Lopez-Persem A, Mandonnet E, Volle E. Impaired creative cognition after surgery for an IDH-mutated glioma: A proof-of-concept study. Cortex 2024; 174:219-233. [PMID: 38593576 DOI: 10.1016/j.cortex.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/11/2023] [Accepted: 02/27/2024] [Indexed: 04/11/2024]
Abstract
Assessment of high cognitive functions, such as creativity, is often overlooked in medical practice. However, it is crucial to understand the impact of brain tumors, specifically low-grade gliomas, on creative cognition, as these tumors predominantly affect brain regions associated with cognitive creativity. In this study, we investigated creative cognition using the Alternative Uses Task (AUT) and the Combination of Associates Task (CAT) in a cohort of 29 patients who underwent brain surgery for a low-grade glioma, along with 27 control participants. While the group of patients did not exhibit deficits in clinical neuropsychological assessments, our results revealed significant impairment in generating original and creative ideas compared to the control group. Furthermore, when analyzing the specific brain regions affected by the tumors, patients with lesions overlapping the left rostro-lateral prefrontal cortex, a critical region for creativity, displayed more pronounced impairments in the CAT compared to patients with lesions outside this region. These findings provide proof of concept that patients can experience impaired creative cognition following surgery for low-grade glioma, highlighting the importance of assessing higher-order cognitive functions, including creativity, in neurosurgical patients. Moreover, beyond its clinical relevance, our study contributes to advancing our understanding of the neuroscience of creativity.
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Affiliation(s)
- Théophile Bieth
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France; Neurology Department, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
| | - Valentine Facque
- Humans Matter, France; Department of Neurosurgery, Lariboisière Hospital, Paris, France
| | - Victor Altmayer
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France; Neurology Department, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Isabelle Poisson
- Department of Neurosurgery, Lariboisière Hospital, Paris, France
| | - Marcela Ovando-Tellez
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Sarah Moreno-Rodriguez
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Alizée Lopez-Persem
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Emmanuel Mandonnet
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurosurgery, Lariboisière Hospital, Paris, France; Université de Paris Cité, Paris, France.
| | - Emmanuelle Volle
- Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, Paris, France.
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Shah K, Bhartia V, Biswas C, Sahu A, Shetty PM, Singh V, Velayutham P, Awate SP, Moiyadi AV. Tumor location and neurocognitive function-Unravelling the association and identifying relevant anatomical substrates in intra-axial brain tumors. Neurooncol Adv 2024; 6:vdae020. [PMID: 38464948 PMCID: PMC10924535 DOI: 10.1093/noajnl/vdae020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024] Open
Abstract
Background Neurocognitive function is a key outcome indicator of therapy in brain tumors. Understanding the underlying anatomical substrates involved in domain function and the pathophysiological basis of dysfunction can help ameliorate the effects of therapy and tailor directed rehabilitative strategies. Methods Hundred adult diffuse gliomas were co-registered onto a common demographic-specific brain template to create tumor localization maps. Voxel-based lesion symptom (VLSM) technique was used to assign an association between individual voxels and neuropsychological dysfunction in various domains (attention and executive function (A & EF), language, memory, visuospatial/constructive abilities, and visuomotor speed). The probability maps thus generated were further co-registered to cortical and subcortical atlases. A permutation-based statistical testing method was used to evaluate the statistically and clinically significant anatomical parcels associated with domain dysfunction and to create heat maps. Results Neurocognition was affected in a high proportion of subjects (93%), with A & EF and memory being the most affected domains. Left-sided networks were implicated in patients with A & EF, memory, and language deficits with the perisylvian white matter tracts being the most common across domains. Visuospatial dysfunction was associated with lesions involving the right perisylvian cortical regions, whereas deficits in visuomotor speed were associated with lesions involving primary visual and motor output pathways. Conclusions Significant baseline neurocognitive deficits are prevalent in gliomas. These are multidomain and the perisylvian network especially on the left side seems to be very important, being implicated in dysfunction of many domains.
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Affiliation(s)
- Kanchi Shah
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Vinayak Bhartia
- Computer Science and Engineering Department, Indian Institute of Technology (IIT) Bombay. Mumbai, Maharashtra, India
| | - Chandrima Biswas
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Arpita Sahu
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
- Department of Radiodiagnosis, Tata Memorial Center, Mumbai, Maharashtra, India
| | - Prakash M Shetty
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Vikas Singh
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Parthiban Velayutham
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - Suyash P Awate
- Computer Science and Engineering Department, Indian Institute of Technology (IIT) Bombay. Mumbai, Maharashtra, India
| | - Aliasgar V Moiyadi
- Neurosurgical Services, Department of Surgical Oncology, Tata Memorial Center, Mumbai, Maharashtra, India
- Department of Health Sciences, Homi Bhabha National Institute, Mumbai, Maharashtra, India
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Cargnelutti E, Maieron M, D'Agostini S, Ius T, Skrap M, Tomasino B. Preoperative plasticity in the functional naming network of patients with left insular gliomas. Neuroimage Clin 2023; 41:103561. [PMID: 38176362 PMCID: PMC10797139 DOI: 10.1016/j.nicl.2023.103561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/22/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
Plasticity could take place as a compensatory process following brain glioma growth. Only a few studies specifically explored plasticity in patients affected by a glioma invading the left insula; even more, plasticity of the insular cortex in task-based functional language network is almost unexplored. In the current study, we explored potential plasticity in a consecutive series of 22 patients affected by a glioma centered to the left insula, by comparing their preoperative object-naming functional network with that of a group of healthy controls. After having controlled for demographic variables, fMRI results showed that patients vs. controls activated a cluster in the right, contralesional pars triangularis including the Broca's area. On the other hand, controls did not significantly activate any brain region more than patients. At behavioral level, patients retained a generally preserved naming performance as well as a proficient language processing profile. These findings suggest that involvement of language-specific areas in the healthy hemisphere could help compensate for the left, affected insula, thus allowing preservation of the naming functions. Results are commented in relation to lesion site, naming performance, and potential relevance for neurosurgery.
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Affiliation(s)
- Elisa Cargnelutti
- Scientific Institute IRCCS "Eugenio Medea", Dipartimento/Unità Operativa Pasian di Prato, 33037 Pasian di Prato, Italy
| | - Marta Maieron
- Department of Physics, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
| | - Serena D'Agostini
- Neuroradiology Unit, Department of Diagnostic Imaging, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
| | - Tamara Ius
- Neurosurgery Unit, Head-Neck and Neurosciences Department, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
| | - Miran Skrap
- Neurosurgery Unit, Head-Neck and Neurosciences Department, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
| | - Barbara Tomasino
- Scientific Institute IRCCS "Eugenio Medea", Dipartimento/Unità Operativa Pasian di Prato, 33037 Pasian di Prato, Italy.
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Jönsson H, Ahlström H, Kullberg J. Spatial mapping of tumor heterogeneity in whole-body PET-CT: a feasibility study. Biomed Eng Online 2023; 22:110. [PMID: 38007471 PMCID: PMC10675915 DOI: 10.1186/s12938-023-01173-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 11/17/2023] [Indexed: 11/27/2023] Open
Abstract
BACKGROUND Tumor heterogeneity is recognized as a predictor of treatment response and patient outcome. Quantification of tumor heterogeneity across all scales may therefore provide critical insight that ultimately improves cancer management. METHODS An image registration-based framework for the study of tumor heterogeneity in whole-body images was evaluated on a dataset of 490 FDG-PET-CT images of lung cancer, lymphoma, and melanoma patients. Voxel-, lesion- and subject-level features were extracted from the subjects' segmented lesion masks and mapped to female and male template spaces for voxel-wise analysis. Resulting lesion feature maps of the three subsets of cancer patients were studied visually and quantitatively. Lesion volumes and lesion distances in subject spaces were compared with resulting properties in template space. The strength of the association between subject and template space for these properties was evaluated with Pearson's correlation coefficient. RESULTS Spatial heterogeneity in terms of lesion frequency distribution in the body, metabolic activity, and lesion volume was seen between the three subsets of cancer patients. Lesion feature maps showed anatomical locations with low versus high mean feature value among lesions sampled in space and also highlighted sites with high variation between lesions in each cancer subset. Spatial properties of the lesion masks in subject space correlated strongly with the same properties measured in template space (lesion volume, R = 0.986, p < 0.001; total metabolic volume, R = 0.988, p < 0.001; maximum within-patient lesion distance, R = 0.997, p < 0.001). Lesion volume and total metabolic volume increased on average from subject to template space (lesion volume, 3.1 ± 52 ml; total metabolic volume, 53.9 ± 229 ml). Pair-wise lesion distance decreased on average by 0.1 ± 1.6 cm and maximum within-patient lesion distance increased on average by 0.5 ± 2.1 cm from subject to template space. CONCLUSIONS Spatial tumor heterogeneity between subsets of interest in cancer cohorts can successfully be explored in whole-body PET-CT images within the proposed framework. Whole-body studies are, however, especially prone to suffer from regional variation in lesion frequency, and thus statistical power, due to the non-uniform distribution of lesions across a large field of view.
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Affiliation(s)
- Hanna Jönsson
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
| | - Håkan Ahlström
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden
- Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
| | - Joel Kullberg
- Section of Radiology, Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden
- Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
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5
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Cheng Y, Liu L, Gu X, Lu Z, Xia Y, Chen J, Tang L. Graph fusion prediction of autism based on attentional mechanisms. J Biomed Inform 2023; 146:104484. [PMID: 37659698 DOI: 10.1016/j.jbi.2023.104484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/16/2023] [Accepted: 08/31/2023] [Indexed: 09/04/2023]
Abstract
Autism spectrum disorder (ASD) is a pervasive developmental disorder, and the earlier detection and timely intervention for treatment positively affect the prognosis of patients. Deep learning algorithms based on graph structure have achieved good results in autism prediction in recent years. However, there are problems with standardized operations in extracting features and combining neighborhood node features with the structure of the graph dependent, which limits the generalization ability of the trained model to other graph structures. In this paper, we propose a graph fusion autism prediction model based on attentional mechanisms(AGF) to address the above problems. The AGF model represents the overall population (patients or healthy controls) as a sparse graph, where nodes are subjects, and non-imaging features are integrated as edge weights. Different weights can be defined for different nodes in the neighborhood through the attention mechanism without relying on prior knowledge of the graph structure. The model is also able to dynamically fuse multiple sparse graphs obtained from different non-imaging features by way of training weight assignment. Its performance is also compared with several other models (e.g., S-AGF, GCN, etc.), and the results show that it has superior prediction accuracy compared to the baseline model. The results show that this improvement of graph fusion works better on the ABIDE databases, and the classification accuracy can reach 73.9%. The datasets and source code are freely available at https://github.com/chengyu-github1012/Graph-Fusion.git. Strengths and limitations of this study: graph fusion; disease prediction; noise.
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Affiliation(s)
- Yu Cheng
- School of Information, Yunnan Normal University, Yunnan, China
| | - Lin Liu
- School of Information, Yunnan Normal University, Yunnan, China; Engineering Research Center of Computer Vision and Intelligent Control Technology, Department of Education of Yunnan Province
| | - Xiaoai Gu
- School of Information, Yunnan Normal University, Yunnan, China
| | - Zhonghao Lu
- School of Information, Yunnan Normal University, Yunnan, China
| | - Yujing Xia
- School of Information, Yunnan Normal University, Yunnan, China
| | - Juan Chen
- School of Information, Yunnan Normal University, Yunnan, China
| | - Lin Tang
- Faculty Of Education, Yunnan Normal University, Yunnan, China; Key Laboratory of Educational Information for Nationalities Ministry of Education, Yunnan Normal University, Yunnan, China.
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6
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van Opijnen MP, Tesileanu CMS, Dirven L, van der Meer PB, Wijnenga MMJ, Vincent AJPE, Broekman MLD, Dubbink HJ, Kros JM, van Duinen SG, Smits M, French PJ, van den Bent MJ, Taphoorn MJB, Koekkoek JAF. IDH1/2 wildtype gliomas grade 2 and 3 with molecular glioblastoma-like profile have a distinct course of epilepsy compared to IDH1/2 wildtype glioblastomas. Neuro Oncol 2023; 25:701-709. [PMID: 35972438 PMCID: PMC10076940 DOI: 10.1093/neuonc/noac197] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND IDH1/2 wildtype (IDHwt) glioma WHO grade 2 and 3 patients with pTERT mutation and/or EGFR amplification and/or + 7/-10 chromosome gain/loss have a similar overall survival time as IDHwt glioblastoma patients, and are both considered glioblastoma IDHwt according to the WHO 2021 classification. However, differences in seizure onset have been observed. This study aimed to compare the course of epilepsy in the 2 glioblastoma subtypes. METHODS We analyzed epilepsy data of an existing cohort including IDHwt histologically lower-grade glioma WHO grade 2 and 3 with molecular glioblastoma-like profile (IDHwt hLGG) and IDHwt glioblastoma patients. Primary outcome was the incidence proportion of epilepsy during the disease course. Secondary outcomes included, among others, onset of epilepsy, number of seizure days, and antiepileptic drug (AED) polytherapy. RESULTS Out of 254 patients, 78% (50/64) IDHwt hLGG and 68% (129/190) IDHwt glioblastoma patients developed epilepsy during the disease (P = .121). Epilepsy onset before histopathological diagnosis occurred more frequently in IDHwt hLGG compared to IDHwt glioblastoma patients (90% vs 60%, P < .001), with a significantly longer median time to diagnosis (3.5 vs 1.3 months, P < .001). Median total seizure days was also longer for IDHwt hLGG patients (7.0 vs 3.0, P = .005), and they received more often AED polytherapy (32% vs 17%, P = .028). CONCLUSIONS Although the incidence proportion of epilepsy during the entire disease course is similar, IDHwt hLGG patients show a significantly higher incidence of epilepsy before diagnosis and a significantly longer median time between first seizure and diagnosis compared to IDHwt glioblastoma patients, indicating a distinct clinical course.
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Affiliation(s)
- Mark P van Opijnen
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurosurgery, Haaglanden Medical Center, The Hague, the Netherlands
| | - C Mircea S Tesileanu
- Department of Neurology, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Linda Dirven
- Department of Neurology, Haaglanden Medical Center, The Hague, the Netherlands
| | - Pim B van der Meer
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Marike L D Broekman
- Department of Neurosurgery, Haaglanden Medical Center, The Hague, the Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, the Brain Tumor Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Johan M Kros
- Department of Pathology, the Brain Tumor Center, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sjoerd G van Duinen
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Pim J French
- Department of Neurology, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Martin J van den Bent
- Department of Neurology, the Brain Tumor Center, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Martin J B Taphoorn
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurology, Haaglanden Medical Center, The Hague, the Netherlands
| | - Johan A F Koekkoek
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurology, Haaglanden Medical Center, The Hague, the Netherlands
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7
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Presurgical Executive Functioning in Low-Grade Glioma Patients Cannot Be Topographically Mapped. Cancers (Basel) 2023; 15:cancers15030807. [PMID: 36765764 PMCID: PMC9913560 DOI: 10.3390/cancers15030807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 01/18/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
Executive dysfunctions have a high prevalence in low-grade glioma patients and may be the result of structural disconnections of particular subcortical tracts and/or networks. However, little research has focused on preoperative low-grade glioma patients. The frontotemporoparietal network has been closely linked to executive functions and is substantiated by the superior longitudinal fasciculus. The aim of this study was to investigate their role in executive functions in low-grade glioma patients. Patients from two neurological centers were included with IDH-mutated low-grade gliomas. The sets of preoperative predictors were (i) distance between the tumor and superior longitudinal fasciculus, (ii) structural integrity of the superior longitudinal fasciculus, (iii) overlap between tumor and cortical networks, and (iv) white matter disconnection of the same networks. Linear regression and random forest analyses were performed. The group of 156 patients demonstrated significantly lower performance than normative samples and had a higher prevalence of executive impairments. However, both regression and random forest analyses did not demonstrate significant results, meaning that neither structural, cortical network overlap, nor network disconnection predictors explained executive performance. Overall, our null results indicate that there is no straightforward topographical explanation of executive performance in low-grade glioma patients. We extensively discuss possible explanations, including plasticity-induced network-level equipotentiality. Finally, we stress the need for the development of novel methods to unveil the complex and interacting mechanisms that cause executive deficits in low-grade glioma patients.
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8
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Mrah S, Descoteaux M, Wager M, Boré A, Rheault F, Thirion B, Mandonnet E. Network-level prediction of set-shifting deterioration after lower-grade glioma resection. J Neurosurg 2022; 137:1329-1337. [PMID: 35245898 DOI: 10.3171/2022.1.jns212257] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 01/13/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The aim of this study was to predict set-shifting deterioration after resection of low-grade glioma. METHODS The authors retrospectively analyzed a bicentric series of 102 patients who underwent surgery for low-grade glioma. The difference between the completion times of the Trail Making Test parts B and A (TMT B-A) was evaluated preoperatively and 3-4 months after surgery. High dimensionality of the information related to the surgical cavity topography was reduced to a small set of predictors in four different ways: 1) overlap between surgical cavity and each of the 122 cortical parcels composing Yeo's 17-network parcellation of the brain; 2) Tractotron: disconnection by the cavity of the major white matter bundles; 3) overlap between the surgical cavity and each of Yeo's networks; and 4) disconets: signature of structural disconnection by the cavity of each of Yeo's networks. A random forest algorithm was implemented to predict the postoperative change in the TMT B-A z-score. RESULTS The last two network-based approaches yielded significant accuracies in left-out subjects (area under the receiver operating characteristic curve [AUC] approximately equal to 0.8, p approximately equal to 0.001) and outperformed the two alternatives. In single tree hierarchical models, the degree of damage to Yeo corticocortical network 12 (CC 12) was a critical node: patients with damage to CC 12 higher than 7.5% (cortical overlap) or 7.2% (disconets) had much higher risk to deteriorate, establishing for the first time a causal link between damage to this network and impaired set-shifting. CONCLUSIONS The authors' results give strong support to the idea that network-level approaches are a powerful way to address the lesion-symptom mapping problem, enabling machine learning-powered individual outcome predictions.
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Affiliation(s)
- Sofiane Mrah
- 1Department of Neurosurgery, Hôpital Lariboisière, AP-HP, Paris, France
| | - Maxime Descoteaux
- 2Sherbrooke Connectivity Imaging Lab, Department of Computer Science, Faculty of Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- 3Imeka Solutions, Sherbrooke, Quebec, Canada
| | - Michel Wager
- 4Department of Neurosurgery, CHU Poitiers, DACTIM-LMA, CNRS 7348, Poitiers, France
| | - Arnaud Boré
- 3Imeka Solutions, Sherbrooke, Quebec, Canada
| | | | | | - Emmanuel Mandonnet
- 1Department of Neurosurgery, Hôpital Lariboisière, AP-HP, Paris, France
- 6Frontlab, Paris Brain Institute (ICM), CNRS UMR 7225, INSERM U1127, Paris, France
- 7Université de Paris, Paris, France
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9
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Imaging fetal anatomy. Semin Cell Dev Biol 2022; 131:78-92. [PMID: 35282997 DOI: 10.1016/j.semcdb.2022.02.023] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/23/2022] [Accepted: 02/23/2022] [Indexed: 02/07/2023]
Abstract
Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.
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Li X, Abiko K, Sheriff S, Maudsley AA, Urushibata Y, Ahn S, Tha KK. The Distribution of Major Brain Metabolites in Normal Adults: Short Echo Time Whole-Brain MR Spectroscopic Imaging Findings. Metabolites 2022; 12:metabo12060543. [PMID: 35736476 PMCID: PMC9228869 DOI: 10.3390/metabo12060543] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/05/2022] [Accepted: 06/08/2022] [Indexed: 12/10/2022] Open
Abstract
This prospective study aimed to evaluate the variation in magnetic resonance spectroscopic imaging (MRSI)-observed brain metabolite concentrations according to anatomical location, sex, and age, and the relationships among regional metabolite distributions, using short echo time (TE) whole-brain MRSI (WB-MRSI). Thirty-eight healthy participants underwent short TE WB-MRSI. The major metabolite ratios, i.e., N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, glutamate + glutamine (Glx)/Cr, and myoinositol (mI)/Cr, were calculated voxel-by-voxel. Their variations according to anatomical regions, sex, and age, and their relationship to each other were evaluated by using repeated-measures analysis of variance, t-tests, and Pearson’s product-moment correlation analyses. All four metabolite ratios exhibited widespread regional variation across the cerebral hemispheres (corrected p < 0.05). Laterality between the two sides and sex-related variation were also shown (p < 0.05). In several regions, NAA/Cr and Glx/Cr decreased and mI/Cr increased with age (corrected p < 0.05). There was a moderate positive correlation between NAA/Cr and mI/Cr in the insular lobe and thalamus and between Glx/Cr and mI/Cr in the parietal lobe (r ≥ 0.348, corrected p ≤ 0.025). These observations demand age- and sex- specific regional reference values in interpreting these metabolites, and they may facilitate the understanding of glial-neuronal interactions in maintaining homeostasis.
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Affiliation(s)
- Xinnan Li
- Laboratory for Biomarker Imaging Science, Hokkaido University Graduate School of Biomedical Science and Engineering, Sapporo 060-8638, Japan;
| | - Kagari Abiko
- Department of Rehabilitation, Hokkaido University Hospital, Sapporo 060-8648, Japan;
- Department of Rehabilitation, Sapporo Azabu Neurosurgical Hospital, Sapporo 065-0022, Japan
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, FL 33146, USA; (S.S.); (A.A.M.)
| | - Andrew A. Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL 33146, USA; (S.S.); (A.A.M.)
| | | | - Sinyeob Ahn
- Siemens Healthineers, San Francisco, CA 94553, USA;
| | - Khin Khin Tha
- Laboratory for Biomarker Imaging Science, Hokkaido University Graduate School of Biomedical Science and Engineering, Sapporo 060-8638, Japan;
- Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo 060-8638, Japan
- Correspondence: ; Tel.: +81-11-706-8183
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11
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Duffau H. White Matter Tracts and Diffuse Lower-Grade Gliomas: The Pivotal Role of Myelin Plasticity in the Tumor Pathogenesis, Infiltration Patterns, Functional Consequences and Therapeutic Management. Front Oncol 2022; 12:855587. [PMID: 35311104 PMCID: PMC8924360 DOI: 10.3389/fonc.2022.855587] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 02/14/2022] [Indexed: 12/18/2022] Open
Abstract
For many decades, interactions between diffuse lower-grade glioma (LGG) and brain connectome were neglected. However, the neoplasm progression is intimately linked to its environment, especially the white matter (WM) tracts and their myelin status. First, while the etiopathogenesis of LGG is unclear, this tumor seems to appear during the adolescence, and it is mostly located within anterior and associative cerebral areas. Because these structures correspond to those which were myelinated later in the brain maturation process, WM myelination could play a role in the development of LGG. Second, WM fibers and the myelin characteristics also participate in LGG diffusion, since glioma cells migrate along the subcortical pathways, especially when exhibiting a demyelinated phenotype, which may result in a large invasion of the parenchyma. Third, such a migratory pattern can induce functional (neurological, cognitive and behavioral) disturbances, because myelinated WM tracts represent the main limitation of neuroplastic potential. These parameters are critical for tailoring an individualized therapeutic strategy, both (i) regarding the timing of active treatment(s) which must be proposed earlier, before a too wide glioma infiltration along the WM bundles, (ii) and regarding the anatomic extent of surgical resection and irradiation, which should take account of the subcortical connectivity. Therefore, the new science of connectomics must be integrated in LGG management, based upon an improved understanding of the interplay across glioma dissemination within WM and reactional neural networks reconfiguration, in order to optimize long-term oncological and functional outcomes. To this end, mechanisms of activity-dependent myelin plasticity should be better investigated.
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Affiliation(s)
- Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", Institute of Functional Genomics, National Institute for Health and Medical Research (INSERM) U1191, University of Montpellier, Montpellier, France
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12
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Haddad AF, Young JS, Oh JY, Okada H, Aghi MK. The immunology of low-grade gliomas. Neurosurg Focus 2022; 52:E2. [PMID: 35104791 PMCID: PMC9283531 DOI: 10.3171/2021.11.focus21587] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 11/16/2021] [Indexed: 12/14/2022]
Abstract
Low-grade gliomas (LGGs), which harbor an isocitrate dehydrogenase (IDH) mutation, have a better prognosis than their high-grade counterparts; nonetheless, they remain incurable and impart significant negative impacts on patients' quality of life. Although immunotherapies represent a novel avenue of treatment for patients with LGGs, they have not yet been successful. Accurately selecting and evaluating immunotherapies requires a detailed understanding of LGG tumor immunology and the underlying tumor immune phenotype. A growing body of literature suggests that LGGs significantly differ in their immunology from high-grade gliomas, highlighting the importance of investigation into LGG immunology specifically. In this review, the authors aimed to discuss relevant research surrounding the LGG tumor immune microenvironment, including immune cell infiltration, tumor immunogenicity, checkpoint molecule expression, the impact of an IDH mutation, and implications for immunotherapies, while also briefly touching on current immunotherapy trials and future directions for LGG immunology research.
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13
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Haddad AF, Young JS, Morshed RA, Josephson SA, Cha S, Berger MS. Pseudo-insular glioma syndrome: illustrative cases. JOURNAL OF NEUROSURGERY: CASE LESSONS 2021; 2:CASE21481. [PMID: 35854917 PMCID: PMC9281470 DOI: 10.3171/case21481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 09/20/2021] [Indexed: 11/15/2022]
Abstract
BACKGROUND Lower-grade insular gliomas often appear as expansile and infiltrative masses on magnetic resonance imaging (MRI). However, there are nonneoplastic lesions of the insula, such as demyelinating disease and vasculopathies, that can mimic insular gliomas. OBSERVATIONS The authors report two patients who presented with headaches and were found to have mass lesions concerning for lower-grade insular glioma based on MRI obtained at initial presentation. However, on the immediate preoperative MRI obtained a few weeks later, both patients had spontaneous and complete resolution of the insular lesions. LESSONS Tumor mimics should always be in the differential diagnosis of brain masses, including those involving the insula. The immediate preoperative MRI (within 24–48 hours of surgery) must be compared carefully with the initial presentation MRI to assess interval change that suggests tumor mimics to avoid unnecessary surgical intervention.
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Affiliation(s)
| | | | | | | | - Soonmee Cha
- Radiology, University of California, San Francisco, San Francisco, California
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14
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Gómez Vecchio T, Neimantaite A, Corell A, Bartek J, Jensdottir M, Reinertsen I, Solheim O, Jakola AS. Lower-Grade Gliomas: An Epidemiological Voxel-Based Analysis of Location and Proximity to Eloquent Regions. Front Oncol 2021; 11:748229. [PMID: 34621684 PMCID: PMC8490663 DOI: 10.3389/fonc.2021.748229] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 08/27/2021] [Indexed: 01/14/2023] Open
Abstract
Background Glioma is the most common intra-axial tumor, and its location relative to critical areas of the brain is important for treatment decision-making. Studies often report tumor location based on anatomical taxonomy alone since the estimation of eloquent regions requires considerable knowledge of functional neuroanatomy and is, to some degree, a subjective measure. An unbiased and reproducible method to determine tumor location and eloquence is desirable, both for clinical use and for research purposes. Objective To report on a voxel-based method for assessing anatomical distribution and proximity to eloquent regions in diffuse lower-grade gliomas (World Health Organization grades 2 and 3). Methods A multi-institutional population-based dataset of adult patients (≥18 years) histologically diagnosed with lower-grade glioma was analyzed. Tumor segmentations were registered to a standardized space where two anatomical atlases were used to perform a voxel-based comparison of the proximity of segmentations to brain regions of traditional clinical interest. Results Exploring the differences between patients with oligodendrogliomas, isocitrate dehydrogenase (IDH) mutated astrocytomas, and patients with IDH wild-type astrocytomas, we found that the latter were older, more often had lower Karnofsky performance status, and that these tumors were more often found in the proximity of eloquent regions. Eloquent regions are found slightly more frequently in the proximity of IDH-mutated astrocytomas compared to oligodendrogliomas. The regions included in our voxel-based definition of eloquence showed a high degree of association with performing biopsy compared to resection. Conclusion We present a simple, robust, unbiased, and clinically relevant method for assessing tumor location and eloquence in lower-grade gliomas.
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Affiliation(s)
- Tomás Gómez Vecchio
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Alice Neimantaite
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Alba Corell
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden.,Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jiri Bartek
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.,Department of Neurosurgery, Rigshospitalet, Copenhagen, Denmark
| | - Margret Jensdottir
- Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden
| | - Ingerid Reinertsen
- Department of Health Research, SINTEF Digital, Trondheim, Norway.,Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Ole Solheim
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Asgeir S Jakola
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden.,Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
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15
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Hartung SL, Mandonnet E, de Witt Hamer P, Klein M, Wager M, Rech F, Pallud J, Pessanha Viegas C, Ille S, Krieg SM, Robe PA, van Zandvoort MJE. Impaired Set-Shifting from Dorsal Stream Disconnection: Insights from a European Series of Right Parietal Lower-Grade Glioma Resection. Cancers (Basel) 2021; 13:cancers13133337. [PMID: 34283043 PMCID: PMC8267741 DOI: 10.3390/cancers13133337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 06/18/2021] [Accepted: 06/24/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Awake surgery with cognitive monitoring has increasingly been implemented to preserve brain networks and functionality. More recently, not only surgery in the left but also in the right hemisphere, i.c., the parietal lobe, was associated with potential risk for deficits in cognitive functions, such as cognitive flexibility. We describe an explorative pilot study in an international consortium within clinical care as usual. Careful interpretation of our findings indicates that disconnection of the lateral part of the dorsal stream correlated with impaired set-shifting. More importantly, it illustrates the need for international collaboration on neuropsychological tests and methodologies to improve our understanding of white matter networks at risk during awake surgery. Abstract Awake surgery with cognitive monitoring has increasingly been implemented to preserve brain networks and functionality. More recently, not only surgery in the left but also in the right hemisphere, i.c., the parietal lobe, was associated with potential risk for deficits in cognitive functions, such as cognitive flexibility. In this explorative pilot study, we compare cognitive performance more than three months after surgery with baseline measurements and explore the association between cognitive decline and subcortical tracts that may have been severed during surgery in the right hemisphere. Twenty-two patients who underwent surgery for a right parietal low-grade glioma were assessed pre- and postoperatively using the Trail Making Test and the Stroop task to administer set-shifting abilities and inhibition. Volume measurements and lesion–symptom mapping analyses were performed on postoperative MRI scans. Careful interpretation of the results shows a change in TMT performance and not on the Stroop Task when the lateral part of the arcuate fasciculus is damaged, indicating that disconnection of the lateral part of the dorsal stream might be correlated specifically with impaired set-shifting and not with inhibition. More importantly, this study underlines the need for international concertation to allow larger studies to increase power and perform more detailed analyses.
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Affiliation(s)
- Suzanne L. Hartung
- Department of Neurology and Neurosurgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (P.A.R.); (M.J.E.v.Z.)
- Correspondence:
| | | | - Philip de Witt Hamer
- Department of Neurosurgery, Location VUmc, Cancer Center Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands;
| | - Martin Klein
- Department of Medical Psychology and Brain Tumor Center Amsterdam at Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands;
| | - Michel Wager
- Department of Neurological Surgery, Poitiers University Hospital, 86021 Poitiers, France;
| | - Fabien Rech
- CHRU-Nancy, Service de Neurochirurgie, Université de Lorraine, F-54000 Nancy, France;
- CNRS, CRAN, Université de Lorraine, F-54000 Nancy, France
| | - Johan Pallud
- Department of Neursurgery, Saint-Anne Hospital, 75014 Paris, France;
| | | | - Sebastian Ille
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University Munich, 80333 Munich, Germany; (S.I.); (S.M.K.)
| | - Sandro M. Krieg
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University Munich, 80333 Munich, Germany; (S.I.); (S.M.K.)
| | - Pierre A. Robe
- Department of Neurology and Neurosurgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (P.A.R.); (M.J.E.v.Z.)
| | - Martine J. E. van Zandvoort
- Department of Neurology and Neurosurgery, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (P.A.R.); (M.J.E.v.Z.)
- Department of Experimental Psychology, Utrecht University, 3584 CS Utrecht, The Netherlands
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16
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Latini F, Fahlström M, Beháňová A, Sintorn IM, Hodik M, Staxäng K, Ryttlefors M. The link between gliomas infiltration and white matter architecture investigated with electron microscopy and diffusion tensor imaging. Neuroimage Clin 2021; 31:102735. [PMID: 34247117 PMCID: PMC8274339 DOI: 10.1016/j.nicl.2021.102735] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 05/23/2021] [Accepted: 06/15/2021] [Indexed: 11/21/2022]
Abstract
Diffuse low-grade gliomas (DLGG) display different preferential locations in eloquent and secondary associative brain areas. The reason for this tendency is still unknown. We hypothesized that the intrinsic architecture and water diffusion properties of the white matter bundles in these regions may facilitate gliomas infiltration. Magnetic resonance imaging of sixty-seven diffuse low-grade gliomas patients were normalized to/and segmented in MNI space to create three probabilistic infiltration weighted gradient maps according to the molecular status of each tumor group (IDH mutated, IDH wild-type and IDH mutated/1p19q co-deleted). Diffusion tensor imaging (DTI)- based parameters were derived for five major white matter bundles, displaying regional differences in the grade of infiltration, averaged over 20 healthy individuals acquired from the Human connectome project (HCP) database. Transmission electron microscopy (TEM) was used to analyze fiber density, fiber diameter and g-ratio in 100 human white matter regions, sampled from cadaver specimens, reflecting areas with different gliomas infiltration in each white matter bundle. Histological results and DTI-based parameters were compared in anatomical regions of high- and low grade of infiltration (HIF and LIF) respectively. We detected differences in the white matter infiltration of five major white matter bundles in three groups. Astrocytomas IDHm infiltrated left fronto-temporal subcortical areas. Astrocytomas IDHwt were detected in the posterior-temporal and temporo-parietal regions bilaterally. Oligodendrogliomas IDHm/1p19q infiltrated anterior subcortical regions of the frontal lobes bilaterally. Regional differences within the same white matter bundles were detected by both TEM- and DTI analysis linked to different topographical variables. Our multimodal analysis showed that HIF regions, common to all the groups, displayed a smaller fiber diameter, lower FA and higher RD compared with LIF regions. Our results suggest that the both morphological features and diffusion parameters of the white matter may be different in regions linked to the preferential location of DLGG.
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Affiliation(s)
- Francesco Latini
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden.
| | - Markus Fahlström
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Andrea Beháňová
- Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Ida-Maria Sintorn
- Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Monika Hodik
- Immunology, Genetics and Pathology - Biovis Platform, Uppsala University, Uppsala, Sweden
| | - Karin Staxäng
- Immunology, Genetics and Pathology - Biovis Platform, Uppsala University, Uppsala, Sweden
| | - Mats Ryttlefors
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
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17
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Tatekawa H, Uetani H, Hagiwara A, Yao J, Oughourlian TC, Ueda I, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Bahri S, Pope WB, Salamon N, Ellingson BM. Preferential tumor localization in relation to 18F-FDOPA uptake for lower-grade gliomas. J Neurooncol 2021; 152:573-582. [PMID: 33704629 DOI: 10.1007/s11060-021-03730-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 03/01/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE Although tumor localization and 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. METHODS Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. RESULTS Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. CONCLUSION Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.
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Affiliation(s)
- Hiroyuki Tatekawa
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia C Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Issei Ueda
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Shadfar Bahri
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. .,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA. .,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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18
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Liu D, Chen J, Hu X, Hu G, Liu Y, Yang K, Xiao C, Zou Y, Liu H. Contralesional homotopic functional plasticity in patients with temporal glioma. J Neurosurg 2021; 134:417-425. [PMID: 31923896 DOI: 10.3171/2019.11.jns191982] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 11/05/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVE This study aimed to explore the contralesional homotopic functional plasticity in the brain of patients with unilateral temporal glioma. METHODS Demographic, neurocognitive, and resting-state functional MRI data were collected from 17 patients with temporal glioma (10 in the right lobe and 7 in the left lobe), along with 14 age- and sex-matched healthy controls. The amplitude of low-frequency fluctuation (ALFF) of the contralesional homotopic region and 2 control regions was examined. The region-of-interest-based analysis was used to determine the altered functional connectivity (FC) of the contralesional homotopic region, showing significantly different intrinsic regional brain activity between patients and controls. Partial correlation analysis was conducted to determine the association between the altered neural activity and behavioral characteristics. RESULTS Compared with controls, patients with right temporal glioma exhibited significantly increased ALFF in the contralesional homotopic hippocampus and parahippocampal region. In addition, the intrinsic regional activity in these regions was negatively correlated with the visuospatial score (r = -0.718, p = 0.045). Whole-brain FC analysis revealed significantly increased FC between the left hippocampus and parahippocampal regions and the left inferior temporal gyrus, and decreased FC between the left hippocampus and parahippocampal regions and the left inferior frontal gyrus. No significant changes were found in the 2 control regions. CONCLUSIONS Contralesional homotopic regions are instrumental in the process of neural plasticity and functional compensation observed in patients with unilateral temporal glioma. The observed findings might be used to help preoperative evaluation or rehabilitation of postsurgical patients.
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Affiliation(s)
- Dongming Liu
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
| | - Jiu Chen
- 2Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, Jiangsu
- 3Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu; and
| | - Xinhua Hu
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
- 3Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu; and
| | - Guanjie Hu
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
| | - Yong Liu
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
| | - Kun Yang
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
| | - Chaoyong Xiao
- 3Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu; and
- 4Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuanjie Zou
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
- 3Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu; and
| | - Hongyi Liu
- 1Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu
- 3Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu; and
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19
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Fang S, Zhou C, Wang Y, Jiang T. Contralesional functional network reorganization of the insular cortex in diffuse low-grade glioma patients. Sci Rep 2021; 11:623. [PMID: 33436741 PMCID: PMC7804949 DOI: 10.1038/s41598-020-79845-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 12/14/2020] [Indexed: 12/15/2022] Open
Abstract
Diffuse low-grade gliomas (DLGGs) growing on the insular lobe induce contralesional hemispheric insular lobe compensation of damaged functioning by increasing cortical volumes. However, it remains unclear how functional networks are altered in patients with insular lobe DLGGs during functional compensation. Thirty-five patients with insular DLGGs were classified into the left (insL, n = 16) and right groups (insR, n = 19), and 33 healthy subjects were included in the control group. Resting state functional magnetic resonance imaging was used to generate functional connectivity (FC), and network topological properties were evaluated using graph theoretical analysis based on FC matrices. Network-based statistics were applied to compare differences in the FC matrices. A false discovery rate was applied to correct the topological properties. There was no difference in the FC of edges between the control and insL groups; however, the nodal shortest path length of the right insular lobe was significantly increased in the insL group compared to the control group. Additionally, FC was increased in the functional edges originating from the left insular lobe in the insR group compared to the control group. Moreover, there were no differences in topological properties between the insR and control groups. The contralesional insular lobe is crucial for network alterations. The detailed patterns of network alterations were different depending on the affected hemisphere. The observed network alterations might be associated with functional network reorganization and functional compensation.
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Affiliation(s)
- Shengyu Fang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119, the Western Road of the southern 4th Ring Road, Beijing, 100070, China
| | - Chunyao Zhou
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119, the Western Road of the southern 4th Ring Road, Beijing, 100070, China
| | - Yinyan Wang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China. .,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119, the Western Road of the southern 4th Ring Road, Beijing, 100070, China.
| | - Tao Jiang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China. .,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119, the Western Road of the southern 4th Ring Road, Beijing, 100070, China. .,Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors Chinese (2019RU11), Chinese Academy of Medical Sciences, Beijing, China.
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20
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Scheufele K, Subramanian S, Biros G. Fully Automatic Calibration of Tumor-Growth Models Using a Single mpMRI Scan. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:193-204. [PMID: 32931431 PMCID: PMC8565678 DOI: 10.1109/tmi.2020.3024264] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Our objective is the calibration of mathematical tumor growth models from a single multiparametric scan. The target problem is the analysis of preoperative Glioblastoma (GBM) scans. To this end, we present a fully automatic tumor-growth calibration methodology that integrates a single-species reaction-diffusion partial differential equation (PDE) model for tumor progression with multiparametric Magnetic Resonance Imaging (mpMRI) scans to robustly extract patient specific biomarkers i.e., estimates for (i) the tumor cell proliferation rate, (ii) the tumor cell migration rate, and (iii) the original, localized site(s) of tumor initiation. Our method is based on a sparse reconstruction algorithm for the tumor initial location (TIL). This problem is particularly challenging due to nonlinearity, ill-posedeness, and ill conditioning. We propose a coarse-to-fine multi-resolution continuation scheme with parameter decomposition to stabilize the inversion. We demonstrate robustness and practicality of our method by applying the proposed method to clinical data of 206 GBM patients. We analyze the extracted biomarkers and relate tumor origin with patient overall survival by mapping the former into a common atlas space. We present preliminary results that suggest improved accuracy for prediction of patient overall survival when a set of imaging features is augmented with estimated biophysical parameters. All extracted features, tumor initial positions, and biophysical growth parameters are made publicly available for further analysis. To our knowledge, this is the first fully automatic scheme that can handle multifocal tumors and can localize the TIL to a few millimeters.
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21
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Ilan Y. Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes. Front Digit Health 2020; 2:569178. [PMID: 34713042 PMCID: PMC8521820 DOI: 10.3389/fdgth.2020.569178] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 10/02/2020] [Indexed: 12/13/2022] Open
Abstract
Artificial intelligence (AI) digital health systems have drawn much attention over the last decade. However, their implementation into medical practice occurs at a much slower pace than expected. This paper reviews some of the achievements of first-generation AI systems, and the barriers facing their implementation into medical practice. The development of second-generation AI systems is discussed with a focus on overcoming some of these obstacles. Second-generation systems are aimed at focusing on a single subject and on improving patients' clinical outcomes. A personalized closed-loop system designed to improve end-organ function and the patient's response to chronic therapies is presented. The system introduces a platform which implements a personalized therapeutic regimen and introduces quantifiable individualized-variability patterns into its algorithm. The platform is designed to achieve a clinically meaningful endpoint by ensuring that chronic therapies will have sustainable effect while overcoming compensatory mechanisms associated with disease progression and drug resistance. Second-generation systems are expected to assist patients and providers in adopting and implementing of these systems into everyday care.
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22
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Jun E, Na K, Kang W, Lee J, Suk H, Ham B. Identifying
resting‐state
effective connectivity abnormalities in
drug‐naïve
major depressive disorder diagnosis via graph convolutional networks. Hum Brain Mapp 2020. [DOI: 10.1002/hbm.25175 10.1002/hbm.25175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Eunji Jun
- Department of Brain and Cognitive Engineering Korea University Seoul Republic of Korea
| | - Kyoung‐Sae Na
- Department of Psychiatry Gachon University Gil Medical Center Incheon Republic of Korea
| | - Wooyoung Kang
- Department of Biomedical Sciences Korea University College of Medicine Seoul Republic of Korea
| | - Jiyeon Lee
- Department of Brain and Cognitive Engineering Korea University Seoul Republic of Korea
| | - Heung‐Il Suk
- Department of Brain and Cognitive Engineering Korea University Seoul Republic of Korea
- Department of Artificial Intelligence Korea University Seoul Republic of Korea
| | - Byung‐Joo Ham
- Department of Psychiatry Korea University Anam Hospital, Korea University College of Medicine Seoul Republic of Korea
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23
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Darlix A, Rigau V, Duffau H. Neoformazioni intracraniche: gliomi di grado II. Neurologia 2020. [DOI: 10.1016/s1634-7072(20)44227-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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24
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Jun E, Na KS, Kang W, Lee J, Suk HI, Ham BJ. Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks. Hum Brain Mapp 2020; 41:4997-5014. [PMID: 32813309 PMCID: PMC7643383 DOI: 10.1002/hbm.25175] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 07/13/2020] [Accepted: 08/01/2020] [Indexed: 02/06/2023] Open
Abstract
Major depressive disorder (MDD) is a leading cause of disability; its symptoms interfere with social, occupational, interpersonal, and academic functioning. However, the diagnosis of MDD is still made by phenomenological approach. The advent of neuroimaging techniques allowed numerous studies to use resting-state functional magnetic resonance imaging (rs-fMRI) and estimate functional connectivity for brain-disease identification. Recently, attempts have been made to investigate effective connectivity (EC) that represents causal relations among regions of interest. In the meantime, to identify meaningful phenotypes for clinical diagnosis, graph-based approaches such as graph convolutional networks (GCNs) have been leveraged recently to explore complex pairwise similarities in imaging/nonimaging features among subjects. In this study, we validate the use of EC for MDD identification by estimating its measures via a group sparse representation along with a structured equation modeling approach in a whole-brain data-driven manner from rs-fMRI. To distinguish drug-naïve MDD patients from healthy controls, we utilize spectral GCNs based on a population graph to successfully integrate EC and nonimaging phenotypic information. Furthermore, we devise a novel sensitivity analysis method to investigate the discriminant connections for MDD identification in our trained GCNs. Our experimental results validated the effectiveness of our method in various scenarios, and we identified altered connectivities associated with the diagnosis of MDD.
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Affiliation(s)
- Eunji Jun
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Kyoung-Sae Na
- Department of Psychiatry, Gachon University Gil Medical Center, Incheon, Republic of Korea
| | - Wooyoung Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jiyeon Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Heung-Il Suk
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.,Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
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25
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Latini F, Fahlström M, Hesselager G, Zetterling M, Ryttlefors M. Differences in the preferential location and invasiveness of diffuse low-grade gliomas and their impact on outcome. Cancer Med 2020; 9:5446-5458. [PMID: 32537906 PMCID: PMC7402839 DOI: 10.1002/cam4.3216] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 05/14/2020] [Accepted: 05/16/2020] [Indexed: 12/16/2022] Open
Abstract
Background Low‐grade gliomas (LGGs) are primary diffuse slow‐growing brain tumors derived from glial cells. The management of these tumors is dependent on their location, which often harbors eloquent areas. We retrospectively recorded the location of diffuse gliomas to identify whether specific differences exist between the histological types. Methods We analyzed 102 patients with previous histological diagnosis of WHO‐II astrocytomas (62) and WHO‐II oligodendrogliomas (40) according to WHO‐2016 classification. MRI sequences (T2‐FLAIR) were used for tumor volume segmentation and to create a frequency map of their locations within the Montreal Neurological Institute (MNI) space. The Brain‐Grid (BG) system (standardized radiological tool of intersected lines according to anatomical landmarks) was created and merged with a tractography atlas for infiltration analysis. Results Astrocytomas frequently infiltrated association and projection white matter pathways within fronto‐temporo‐insular regions on the left side. Oligodendrogliomas infiltrated larger white matter networks (association‐commissural‐projection) of the frontal lobe bilaterally. A critical number of infiltrated BG voxels (7 for astrocytomas, 10 for oligodendrogliomas) significantly predicted shorter overall survival (OS) in both groups. Bilateral tumor extension in astrocytomas and preoperative tumor volume in oligodendrogliomas were independent prognostic factors for shorter OS. Conclusions Astrocytomas and oligodendrogliomas differ in preferential location, and this has an impact on the type and the extent of white matter involvement. The number of BG voxels infiltrated reflected different tumor invasiveness and its impact on OS in both groups. All this new information may be valuable in neurosurgical oncology to classify and plan treatment for patients with diffuse gliomas.
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Affiliation(s)
- Francesco Latini
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
| | - Markus Fahlström
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Göran Hesselager
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
| | - Maria Zetterling
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
| | - Mats Ryttlefors
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
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26
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Estienne T, Lerousseau M, Vakalopoulou M, Alvarez Andres E, Battistella E, Carré A, Chandra S, Christodoulidis S, Sahasrabudhe M, Sun R, Robert C, Talbot H, Paragios N, Deutsch E. Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation. Front Comput Neurosci 2020; 14:17. [PMID: 32265680 PMCID: PMC7100603 DOI: 10.3389/fncom.2020.00017] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 02/11/2020] [Indexed: 01/30/2023] Open
Abstract
Image registration and segmentation are the two most studied problems in medical image analysis. Deep learning algorithms have recently gained a lot of attention due to their success and state-of-the-art results in variety of problems and communities. In this paper, we propose a novel, efficient, and multi-task algorithm that addresses the problems of image registration and brain tumor segmentation jointly. Our method exploits the dependencies between these tasks through a natural coupling of their interdependencies during inference. In particular, the similarity constraints are relaxed within the tumor regions using an efficient and relatively simple formulation. We evaluated the performance of our formulation both quantitatively and qualitatively for registration and segmentation problems on two publicly available datasets (BraTS 2018 and OASIS 3), reporting competitive results with other recent state-of-the-art methods. Moreover, our proposed framework reports significant amelioration (p < 0.005) for the registration performance inside the tumor locations, providing a generic method that does not need any predefined conditions (e.g., absence of abnormalities) about the volumes to be registered. Our implementation is publicly available online at https://github.com/TheoEst/joint_registration_tumor_segmentation.
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Affiliation(s)
- Théo Estienne
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
- Université Paris-Saclay, CentraleSupélec, Mathématiques et Informatique pour la Complexité et les Systèmes, Gif-sur-Yvette, France
| | - Marvin Lerousseau
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Maria Vakalopoulou
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, CentraleSupélec, Mathématiques et Informatique pour la Complexité et les Systèmes, Gif-sur-Yvette, France
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Emilie Alvarez Andres
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
| | - Enzo Battistella
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
- Université Paris-Saclay, CentraleSupélec, Mathématiques et Informatique pour la Complexité et les Systèmes, Gif-sur-Yvette, France
| | - Alexandre Carré
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
| | - Siddhartha Chandra
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Stergios Christodoulidis
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Predictive Biomarkers and Novel Therapeutic Strategies in Oncology, Villejuif, France
| | - Mihir Sahasrabudhe
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Roger Sun
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Charlotte Robert
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
| | - Hugues Talbot
- Université Paris-Saclay, CentraleSupélec, Inria, Centre de Vision Numérique, Gif-sur-Yvette, France
| | - Nikos Paragios
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
| | - Eric Deutsch
- Gustave Roussy-CentraleSupélec-TheraPanacea Center of Artificial Intelligence in Radiation Therapy and Oncology, Gustave Roussy Cancer Campus, Villejuif, France
- Université Paris-Saclay, Institut Gustave Roussy, Inserm, Molecular Radiotherapy and Innovative Therapeutics, Villejuif, France
- Gustave Roussy Cancer Campus, Department of Radiation Oncology, Villejuif, France
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Skjulsvik AJ, Bø HK, Jakola AS, Berntsen EM, Bø LE, Reinertsen I, Myrmel KS, Sjåvik K, Åberg K, Berg T, Dai HY, Kloster R, Torp SH, Solheim O. Is the anatomical distribution of low-grade gliomas linked to regions of gliogenesis? J Neurooncol 2020; 147:147-157. [PMID: 31983026 PMCID: PMC7075820 DOI: 10.1007/s11060-020-03409-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/20/2020] [Indexed: 12/02/2022]
Abstract
INTRODUCTION According to the stem cell theory, two neurogenic niches in the adult human brain may harbor cells that initiate the formation of gliomas: The larger subventricular zone (SVZ) and the subgranular zone (SGZ) in the hippocampus. We wanted to explore whether defining molecular markers in low-grade gliomas (LGG; WHO grade II) are related to distance to the neurogenic niches. METHODS Patients treated at two Norwegian university hospitals with population-based referral were included. Eligible patients had histopathological verified supratentorial low-grade glioma. IDH mutational status and 1p19q co-deletion status was retrospectively assessed. 159 patients were included, and semi-automatic tumor segmentation was done from pre-treatment T2-weighted (T2W) or Fluid-Attenuated Inversion Recovery (FLAIR) images. 3D maps showing the anatomical distribution of the tumors were then created for each of the three molecular subtypes (IDH mutated/1p19q co-deleted, IDH mutated and IDH wild-type). Both distance from tumor center and tumor border to the neurogenic niches were recorded. RESULTS In this population-based cohort of previously untreated low-grade gliomas, we found that low-grade gliomas are more often found closer to the SVZ than the SGZ, but IDH wild-type tumors are more often found near SGZ. CONCLUSION Our study suggests that the stem cell origin of IDH wild-type and IDH mutated low-grade gliomas may be different.
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Affiliation(s)
- Anne Jarstein Skjulsvik
- Department of Pathology, St. Olavs University Hospital, Trondheim, Norway
- Departments of Clinical and Molecular Medicine, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Hans Kristian Bø
- Department of Diagnostic Imaging, Nordland Hospital Trust, Bodø, Norway
- Department of Circulation and Medical Imaging, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Asgeir Store Jakola
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, Gothenburg, Sweden
- Department of Neuroscience and Movement Medicine, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Erik Magnus Berntsen
- Department of Circulation and Medical Imaging, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway
| | - Lars Eirik Bø
- Department of Health Research, SINTEF Digital, Trondheim, Norway
| | | | | | - Kristin Sjåvik
- Department of Neurosurgery, University Hospital of North Norway, Tromsö, Norway
| | - Kristin Åberg
- Department of Clinical Pathology, University Hospital of North Norway, Tromsö, Norway
| | - Thomas Berg
- Department of Clinical Pathology, University Hospital of North Norway, Tromsö, Norway
| | - Hong Yan Dai
- Department of Pathology, St. Olavs University Hospital, Trondheim, Norway
| | - Roar Kloster
- Department of Neurosurgery, University Hospital of North Norway, Tromsö, Norway
| | - Sverre Helge Torp
- Department of Pathology, St. Olavs University Hospital, Trondheim, Norway
- Departments of Clinical and Molecular Medicine, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Ole Solheim
- Department of Neurosurgery, St. Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway
- Department of Neuroscience and Movement Medicine, Faculty of Medicine, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
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28
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Roux A, Roca P, Edjlali M, Sato K, Zanello M, Dezamis E, Gori P, Lion S, Fleury A, Dhermain F, Meder JF, Chrétien F, Lechapt E, Varlet P, Oppenheim C, Pallud J. MRI Atlas of IDH Wild-Type Supratentorial Glioblastoma: Probabilistic Maps of Phenotype, Management, and Outcomes. Radiology 2019; 293:633-643. [PMID: 31592732 DOI: 10.1148/radiol.2019190491] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background Tumor location is a main prognostic parameter in patients with glioblastoma. Probabilistic MRI-based brain atlases specifying the probability of tumor location associated with important demographic, clinical, histomolecular, and management data are lacking for isocitrate dehydrogenase (IDH) wild-type glioblastomas. Purpose To correlate glioblastoma location with clinical phenotype, surgical management, and outcomes by using a probabilistic analysis in a three-dimensional (3D) MRI-based atlas. Materials and Methods This retrospective study included all adults surgically treated for newly diagnosed IDH wild-type supratentorial glioblastoma in a tertiary adult surgical neuro-oncology center (2006-2016). Semiautomated tumor segmentation and spatial normalization procedures to build a 3D MRI-based atlas were validated. The authors performed probabilistic analyses by using voxel-based lesion symptom mapping technology. The Liebermeister test was used for binary data, and the generalized linear model was used for continuous data. Results A total of 392 patients (mean age, 61 years ± 13; 233 men) were evaluated. The authors identified the preferential location of glioblastomas according to subventricular zone, age, sex, clinical presentation, revised Radiation Therapy Oncology Group-Recursive Partitioning Analysis class, Karnofsky performance status, O6-methylguanine DNA methyltransferase promoter methylation status, surgical management, and survival. The superficial location distant from the eloquent area was more likely associated with a preserved functional status at diagnosis (348 of 392 patients [89%], P < .05), a large surgical resection (173 of 392 patients [44%], P < .05), and prolonged overall survival (163 of 334 patients [49%], P < .05). In contrast, deep location and location within eloquent brain areas were more likely associated with an impaired functional status at diagnosis (44 of 392 patients [11%], P < .05), a neurologic deficit (282 of 392 patients [72%], P < .05), treatment with biopsy only (183 of 392 patients [47%], P < .05), and shortened overall survival (171 of 334 patients [51%], P < .05). Conclusion The authors identified the preferential location of isocitrate dehydrogenase wild-type glioblastomas according to parameters of interest and provided an image-based integration of multimodal information impacting survival results. This suggests the role of glioblastoma location as a surrogate and multimodal parameter integrating several known prognostic factors. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Huang in this issue.
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Affiliation(s)
- Alexandre Roux
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Pauline Roca
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Myriam Edjlali
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Kanako Sato
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Marc Zanello
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Edouard Dezamis
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Pietro Gori
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Stéphanie Lion
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Ariane Fleury
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Frédéric Dhermain
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Jean-François Meder
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Fabrice Chrétien
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Emmanuèle Lechapt
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Pascale Varlet
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Catherine Oppenheim
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
| | - Johan Pallud
- From the Department of Neurosurgery, Sainte-Anne Hospital, Paris, France (A.R., M.Z., E.D., J.P.); Paris Descartes University, Sorbonne Paris Cité, Paris, France (A.R., P.R., M.E., M.Z., J.F.M., F.C., E.L., P.V., C.O., J.P.); UMR 1266 INSERM, IMA-BRAIN, Institute of Psychiatry and Neurosciences of Paris, Paris, France (A.R., P.R., M.E., K.S., M.Z., P.G., S.L., A.F., J.F.M., P.V., C.O., J.P.); Department of Neuroradiology, Sainte-Anne Hospital, Paris, France (M.E., J.F.M., C.O.); Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (K.S.); LTCI, Telecom ParisTech, Paris, France (P.G.); Department of Radiotherapy, Gustave Roussy University Hospital, Villejuif, France (F.D.); and Department of Neuropathology, Sainte-Anne Hospital, Paris, France (F.C., E.L., P.V.)
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Correspondence between cerebral glucose metabolism and BOLD reveals relative power and cost in human brain. Nat Commun 2019; 10:690. [PMID: 30741935 PMCID: PMC6370887 DOI: 10.1038/s41467-019-08546-x] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Accepted: 01/17/2019] [Indexed: 12/02/2022] Open
Abstract
The correspondence between cerebral glucose metabolism (indexing energy utilization) and synchronous fluctuations in blood oxygenation (indexing neuronal activity) is relevant for neuronal specialization and is affected by brain disorders. Here, we define novel measures of relative power (rPWR, extent of concurrent energy utilization and activity) and relative cost (rCST, extent that energy utilization exceeds activity), derived from FDG-PET and fMRI. We show that resting-state networks have distinct energetic signatures and that brain could be classified into major bilateral segments based on rPWR and rCST. While medial-visual and default-mode networks have the highest rPWR, frontoparietal networks have the highest rCST. rPWR and rCST estimates are generalizable to other indexes of energy supply and neuronal activity, and are sensitive to neurocognitive effects of acute and chronic alcohol exposure. rPWR and rCST are informative metrics for characterizing brain pathology and alternative energy use, and may provide new multimodal biomarkers of neuropsychiatric disorders. The brain primarily uses glucose to generate energy, but the relationship of neuronal activity to glucose utilization is not necessarily a simple linear one. Here, the authors introduce relative power (rPWR) and relative cost (rCST) as new metrics to quantify how brain activity relates to glucose consumption.
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Latini F, Fahlström M, Berntsson SG, Larsson EM, Smits A, Ryttlefors M. A novel radiological classification system for cerebral gliomas: The Brain-Grid. PLoS One 2019; 14:e0211243. [PMID: 30677090 PMCID: PMC6345500 DOI: 10.1371/journal.pone.0211243] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Accepted: 01/09/2019] [Indexed: 11/23/2022] Open
Abstract
Purpose Standard radiological/topographical classifications of gliomas often do not reflect the real extension of the tumor within the lobar-cortical anatomy. Furthermore, these systems do not provide information on the relationship between tumor growth and the subcortical white matter architecture. We propose the use of an anatomically standardized grid system (the Brain-Grid) to merge serial morphological magnetic resonance imaging (MRI) scans with a representative tractographic atlas. Two illustrative cases are presented to show the potential advantages of this classification system. Methods MRI scans of 39 patients (WHO grade II and III gliomas) were analyzed with a standardized grid created by intersecting longitudinal lines on the axial, sagittal, and coronal planes. The anatomical landmarks were chosen from an average brain, spatially normalized to the Montreal Neurological Institute (MNI) space and the Talairach space. Major white matter pathways were reconstructed with a deterministic tracking algorithm on a reference atlas and analyzed using the Brain-Grid system. Results In all, 48 brain grid voxels (areas defined by 3 coordinates, axial (A), coronal (C), sagittal (S) and numbers from 1 to 4) were delineated in each MRI sequence and on the tractographic atlas. The number of grid voxels infiltrated was consistent, also in the MNI space. The sub-cortical insula/basal ganglia (A3-C2-S2) and the fronto-insular region (A3-C2-S1) were most frequently involved. The inferior fronto-occipital fasciculus, anterior thalamic radiation, uncinate fasciculus, and external capsule were the most frequently associated pathways in both hemispheres. Conclusions The Brain-Grid based classification system provides an accurate observational tool in all patients with suspected gliomas, based on the comparison of grid voxels on a morphological MRI and segmented white matter atlas. Important biological information on tumor kinetics including extension, speed, and preferential direction of progression can be observed and even predicted with this system. This novel classification can easily be applied to both prospective and retrospective cohorts of patients and increase our comprehension of glioma behavior.
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Affiliation(s)
- Francesco Latini
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
- * E-mail:
| | - Markus Fahlström
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Shala G. Berntsson
- Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden
| | - Elna-Marie Larsson
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Anja Smits
- Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Mats Ryttlefors
- Department of Neuroscience, Neurosurgery, Uppsala University, Uppsala, Sweden
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Bouwen BLJ, Pieterman KJ, Smits M, Dirven CMF, Gao Z, Vincent AJPE. The Impacts of Tumor and Tumor Associated Epilepsy on Subcortical Brain Structures and Long Distance Connectivity in Patients With Low Grade Glioma. Front Neurol 2018; 9:1004. [PMID: 30538668 PMCID: PMC6277571 DOI: 10.3389/fneur.2018.01004] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 11/06/2018] [Indexed: 12/12/2022] Open
Abstract
Low grade gliomas in cerebral cortex often cause symptoms related to higher cerebral functions such as attention, memory and executive function before treatment is initiated. Interestingly, focal tumors residing in one cortical region can lead to a diverse range of symptoms, indicating that the impact of a tumor is extended to multiple brain regions. We hypothesize that the presence of focal glioma in the cerebral cortex leads to alterations of distant subcortical areas and essential white matter tracts. In this study, we analyzed diffusion tensor imaging scans in glioma patients to study the effect of glioma on subcortical gray matter nuclei and long-distance connectivity. We found that the caudate nucleus, putamen and thalamus were affected by cortical glioma, displaying both volumetric and diffusion alterations. The cerebellar cortex contralateral to the tumor side also showed significant volume decrease. Additionally, tractography of the cortico-striatal and cortico-thalamic projections shows similar diffusion alterations. Tumor associated epilepsy might be an important contributing factor to the found alterations. Our findings indeed confirm concurrent structural and connectivity abrasions of brain areas distant from brain tumor, and provide insights into the pathogenesis of diverse neurological symptoms in glioma patients.
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Affiliation(s)
- Bibi L J Bouwen
- Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Kay J Pieterman
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Clemens M F Dirven
- Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Zhenyu Gao
- Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
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Almairac F, Duffau H, Herbet G. Contralesional macrostructural plasticity of the insular cortex in patients with glioma: A VBM study. Neurology 2018; 91:e1902-e1908. [PMID: 30305447 DOI: 10.1212/wnl.0000000000006517] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 08/01/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess the homotopic structural plasticity in case of unilateral damage of the insula. METHODS To detect changes in gray matter volumes of the contralesional insula from structural MRIs, we used voxel-based morphometry (VBM) in a sample of 84 patients with a diffuse low-grade glioma invading the left insula (insL group; n = 47) or the right insula (insR group; n = 37). RESULTS The region of interest-based VBM analysis highlighted a large cluster of voxels with gray matter volume increase in the contralesional insula in both patient groups (k = 2,214 voxels for insL and k = 879 voxels for insR, p < 0.05, family-wise error corrected) compared with 24 age-matched healthy controls. Gray matter volume was increased for the entire insula (t 69 = 3.63, p = 0.0016 for insL; t 59 = 3.54, p = 0.0024 for insR, Bonferroni corrected), whereas no significant changes were found in 2 control regions for both patient groups. Furthermore, an increase of 24.6% and 31.6% in the gray matter volume was observed in the insula-related VBM cluster for insL and insR patients, respectively, compared with healthy controls (t 69 = 7.39, p = 2.59 × 10-10 and t 59 = 7.51, p = 3.61 × 10-10). CONCLUSIONS The reported results demonstrate that slow-growing but massive lesion infiltration of the insula induces marked increase of gray matter volume in the contralateral one. Our findings give support for a homotopic reorganization that might be a physiologic basis for the high level of functional compensation observed in patients with glioma.
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Affiliation(s)
- Fabien Almairac
- From the Department of Neurosurgery (F.A.), Pasteur 2 Hospital, Nice University Medical Center, Université Côte d'Azur; Department of Neurosurgery (H.D., G.H.), Gui de Chauliac Hospital, and Institute for Neurosciences of Montpellier (H.D., G.H.), INSERM 1051, Team "Plasticity of Central Nervous System, Human Stem Cells and Glial Tumors," Saint Eloi Hospital, Montpellier University Medical Center; and University of Montpellier (H.D., G.H.), France
| | - Hugues Duffau
- From the Department of Neurosurgery (F.A.), Pasteur 2 Hospital, Nice University Medical Center, Université Côte d'Azur; Department of Neurosurgery (H.D., G.H.), Gui de Chauliac Hospital, and Institute for Neurosciences of Montpellier (H.D., G.H.), INSERM 1051, Team "Plasticity of Central Nervous System, Human Stem Cells and Glial Tumors," Saint Eloi Hospital, Montpellier University Medical Center; and University of Montpellier (H.D., G.H.), France
| | - Guillaume Herbet
- From the Department of Neurosurgery (F.A.), Pasteur 2 Hospital, Nice University Medical Center, Université Côte d'Azur; Department of Neurosurgery (H.D., G.H.), Gui de Chauliac Hospital, and Institute for Neurosciences of Montpellier (H.D., G.H.), INSERM 1051, Team "Plasticity of Central Nervous System, Human Stem Cells and Glial Tumors," Saint Eloi Hospital, Montpellier University Medical Center; and University of Montpellier (H.D., G.H.), France.
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Parisot S, Ktena SI, Ferrante E, Lee M, Guerrero R, Glocker B, Rueckert D. Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease. Med Image Anal 2018; 48:117-130. [DOI: 10.1016/j.media.2018.06.001] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 05/31/2018] [Accepted: 06/01/2018] [Indexed: 10/14/2022]
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Abstract
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.
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Affiliation(s)
- Ahmed Hosny
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chintan Parmar
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - John Quackenbush
- Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University College of Physicians and Surgeons, New York, NY, USA
- Department of Radiology, New York Presbyterian Hospital, New York, NY, USA
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
- Department of Radiology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Abstract
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.
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Affiliation(s)
- Ahmed Hosny
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chintan Parmar
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - John Quackenbush
- Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University College of Physicians and Surgeons, New York, NY, USA
- Department of Radiology, New York Presbyterian Hospital, New York, NY, USA
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
- Department of Radiology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Hirono S, Ozaki K, Ito D, Matsutani T, Iwadate Y. Hammock Middle Cerebral Artery and Delayed Infarction in Lenticulostriate Artery After Staged Resection of Giant Insular Glioma. World Neurosurg 2018; 117:80-83. [PMID: 29886303 DOI: 10.1016/j.wneu.2018.05.226] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 05/29/2018] [Accepted: 05/30/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND Delayed infarction in the lenticulostriate artery (LSA) area after insular glioma resection is not common, and its pathophysiology remains unknown. CASE DESCRIPTION A 32-year-old right-handed man with a giant insular low-grade glioma with frontal and temporal extension underwent awake craniotomy with an intentional staged surgery strategy. Preoperative radiologic images demonstrated a diagonally elevated middle cerebral artery (MCA) by the temporal tumor and a significantly compressed striatum. With intraoperative subcortical direct electrical stimulation, the resection was finalized in the temporal part of the tumor due to the semantic paraphasia induced in the temporal stem, fatigue, and loss of concentration. The immediate postoperative clinical course was uneventful. However, on postoperative day 20, he suddenly experienced right hemiparesis. Repeated images revealed infarction in the LSA area. The previously compressed striatum was then relieved and relocated to its original position in just 20 days, and the M1 segment of the MCA was remarkably downward, in which the MCA resembled a hammock. Angiography confirmed the hammock-shaped MCA and significantly stretched LSA, suggesting the combination of freed striatum from the compression and loss of temporal structure by the tumor resection as the key mechanism of severe dislocation of the MCA and delayed ischemia. CONCLUSIONS In a staged resection of giant insular glioma, attention should be paid to a possible severe dislocation of the MCA in a delayed postoperative period, which may lead to LSA stretching and delayed infarction.
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Affiliation(s)
- Seiichiro Hirono
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chuo-ku, Chiba-city, Chiba, Japan.
| | - Ko Ozaki
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chuo-ku, Chiba-city, Chiba, Japan
| | - Daisuke Ito
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chuo-ku, Chiba-city, Chiba, Japan
| | - Tomoo Matsutani
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chuo-ku, Chiba-city, Chiba, Japan
| | - Yasuo Iwadate
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chuo-ku, Chiba-city, Chiba, Japan
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Awake Surgery for Gliomas within the Right Inferior Parietal Lobule: New Insights into the Functional Connectivity Gained from Stimulation Mapping and Surgical Implications. World Neurosurg 2018; 112:e393-e406. [DOI: 10.1016/j.wneu.2018.01.053] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2017] [Revised: 01/07/2018] [Accepted: 01/11/2018] [Indexed: 11/30/2022]
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Abstract
INTRODUCTION Radical glioma resection improves overall survival, both in low-grade and high-grade glial tumors. However, preservation of the quality of life is also crucial. Areas covered: Due to the diffuse feature of gliomas, which invade the central nervous system, and due to considerable variations of brain organization among patients, an individual cerebral mapping is mandatory to solve the classical dilemma between the oncological and functional issues. Because functional neuroimaging is not reliable enough, intraoperative electrical stimulation, especially in awake patients benefiting from a real-time cognitive monitoring, is the best way to increase the extent of resection while sparing eloquent neural networks. Expert commentary: Here, we propose a paradigmatic shift from image-guided resection to functional mapping-guided resection, based on the study of the dynamic distribution of delocalized cortico-subcortical circuits at the individual level, i.e., the investigation of brain connectomics and neuroplastic potential. This surgical philosophy results in an improvement of both oncological outcomes and quality of life. This highlights the need to reinforce the link between glioma surgery and cognitive neurosciences.
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Affiliation(s)
| | - Hugues Duffau
- b Department of Neurosurgery , Gui de Chauliac Hospital, Montpellier University Medical Center , Montpellier , France.,c National Institute for Health and Medical Research (INSERM), U1051 Laboratory, Team "Brain Plasticity, Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier , Montpellier University Medical Center , Montpellier , France
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Abstract
Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.
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Montesano G, Allegrini D, Colombo L, Rossetti LM, Pece A. Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties. PLoS One 2017; 12:e0185256. [PMID: 29020026 PMCID: PMC5636074 DOI: 10.1371/journal.pone.0185256] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2016] [Accepted: 09/08/2017] [Indexed: 12/24/2022] Open
Abstract
The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.
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Affiliation(s)
- Giovanni Montesano
- University of Milan, School of Ophthalmology, Milan, Italy
- ASST Santi Paolo e Carlo–Eye Clinic, Milan, Italy
- City, University of London, Optometry and Visual Sciences, London, United Kingdom
- * E-mail:
| | - Davide Allegrini
- Eye clinic, Humanitas Gavazzeni, Humanitas University, Milan, Italy
| | | | - Luca M. Rossetti
- University of Milan, School of Ophthalmology, Milan, Italy
- ASST Santi Paolo e Carlo–Eye Clinic, Milan, Italy
| | - Alfredo Pece
- Eye Clinic, Melegnano Hospital, Vizzolo Predabissi, Italy
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Schiffler P, Tenberge JG, Wiendl H, Meuth SG. Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects. Front Hum Neurosci 2017; 11:352. [PMID: 28729829 PMCID: PMC5498510 DOI: 10.3389/fnhum.2017.00352] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 06/20/2017] [Indexed: 11/13/2022] Open
Abstract
The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.
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Affiliation(s)
- Patrick Schiffler
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Jan-Gerd Tenberge
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Heinz Wiendl
- Department of Neurology, University Hospital MünsterMünster, Germany
| | - Sven G Meuth
- Department of Neurology, University Hospital MünsterMünster, Germany
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Darlix A, Deverdun J, Menjot de Champfleur N, Castan F, Zouaoui S, Rigau V, Fabbro M, Yordanova Y, Le Bars E, Bauchet L, Gozé C, Duffau H. IDH mutation and 1p19q codeletion distinguish two radiological patterns of diffuse low-grade gliomas. J Neurooncol 2017; 133:37-45. [PMID: 28434111 DOI: 10.1007/s11060-017-2421-0] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 04/09/2017] [Indexed: 02/06/2023]
Abstract
Diffuse low-grade gliomas (DLGG) prognosis is variable, depending on several factors, including the isocitrate dehydrogenase (IDH) mutation and the 1p19q codeletion. A few studies suggested associations between these parameters and tumor radiological characteristics including topography. Our aim was analyzing the correlations between the IDH and 1p19q statuses and the tumor intracerebral distribution (at the lobar and voxel levels), volume, and borders. We conducted a retrospective, monocentric study on a consecutive series of 198 DLGG patients. The IDH and 1p19q statuses were recorded. The pre-treatment magnetic resonance FLAIR imagings were reviewed for determination of lobar topography, tumor volume, and characterisation of tumor borders (sharp or indistinct). We conducted a voxel-based lesion-symptom mapping analysis to investigate the correlations between the IDH and 1p19q statuses and topography at the voxel level. The IDH mutation and 1p19q statuses were correlated with the tumor topography defined using lobar anatomy (p < 0.001 and p = 0.004, respectively). Frontal tumors were more frequently IDH-mutant (87.1 vs. 57.4%) and 1p19q codeleted (45.2 vs. 17.0%) than temporo-insular lesions. At the voxel level, these associations were not found. Tumors with sharp borders were more frequently IDH-mutant (p = 0.001) while tumors with indistinct borders were more frequently IDH wild-type and 1p19q non-codeleted (p < 0.001). Larger tumors at diagnosis (possibly linked to a slower growth rate) were more frequently IDH-mutant (p < 0.001). IDH wild-type, 1p19q non-codeleted temporo-insular tumors are distinct from IDH-mutant, 1p19q codeleted frontal tumors. Further studies are needed to determine whether the therapeutic strategy should be adapted to each pattern.
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Affiliation(s)
- Amélie Darlix
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier (ICM) - Val d'Aurelle, 208 Rue des Apothicaires, 34298, Montpellier, France. .,INSERM U1051, Montpellier Neurosciences Institute, 80 Avenue Augustin Fliche, 34091, Montpellier, France.
| | - Jérémy Deverdun
- Department of Neuroradiology, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
| | | | - Florence Castan
- Biometrics Unit, Institut Régional du Cancer de Montpellier (ICM) - Val d'Aurelle, 208 Rue des Apothicaires, 34298, Montpellier, France
| | - Sonia Zouaoui
- Department of Epidemiology, French Brain Tumor Database, GNOLR, Registre des Tumeurs de l'Hérault, Institut Régional du Cancer de Montpellier (ICM) - Val d'Aurelle, 208 Rue des Apothicaires, 34298, Montpellier, France.,Department of Neurosurgery, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
| | - Valérie Rigau
- Department of Pathology, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
| | - Michel Fabbro
- Department of Medical Oncology, Institut Régional du Cancer de Montpellier (ICM) - Val d'Aurelle, 208 Rue des Apothicaires, 34298, Montpellier, France
| | - Yordanka Yordanova
- INSERM U1051, Montpellier Neurosciences Institute, 80 Avenue Augustin Fliche, 34091, Montpellier, France.,Department of Neurosurgery, Percy Military Hospital, 101 Avenue Henri Barbusse, 92140, Clamart, France
| | - Emmanuelle Le Bars
- Department of Neuroradiology, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
| | - Luc Bauchet
- INSERM U1051, Montpellier Neurosciences Institute, 80 Avenue Augustin Fliche, 34091, Montpellier, France.,Department of Neurosurgery, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
| | - Catherine Gozé
- INSERM U1051, Montpellier Neurosciences Institute, 80 Avenue Augustin Fliche, 34091, Montpellier, France.,Laboratory of Cellular and Tumoral Biology, Biopathology Department, Arnaud de Villeneuve Hospital, 371 Avenue du Doyen Gaston Giraud, 34090, Montpellier, France
| | - Hugues Duffau
- INSERM U1051, Montpellier Neurosciences Institute, 80 Avenue Augustin Fliche, 34091, Montpellier, France.,Department of Neurosurgery, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34090, Montpellier, France
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Li WQ, Zhong NZ, He J, Li YM, Hou LJ, Liu HM, Xia CY, Wang LZ, Lu YC. High ATP2A2 expression correlates with better prognosis of diffuse astrocytic tumor patients. Oncol Rep 2017; 37:2865-2874. [PMID: 28339043 DOI: 10.3892/or.2017.5528] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 03/03/2017] [Indexed: 11/05/2022] Open
Abstract
Novel molecular markers are required for defining subsets of diffuse astrocytic tumor patients with differing prognoses. Here, we examined ATP2A2 expression in 109 human diffuse astrocytic tumor samples (39 grade II diffuse astrocytoma (DA), 19 grade III anaplastic astrocytoma (AA), 51 grade IV glioblastoma) and its correlation with patient clinicopathologic characteristics. ATP2A2 expression significantly correlated with tumor grade and survival (P<0.05). High ATP2A2 expression was detected in 35.3% (18/51) of glioblastoma patients, compared to 61.5% (24/39) in grade II, and 52.6% (10/19) in grade III astrocytoma patients (P=0.043). The median survival was 45±5.3 (95% CI, 34.7-55.3) months in patients with high ATP2A2 expression and 16±5.0 (95% CI, 6.3-25.7) months in patients with low ATP2A2 expression (P<0.0001). Additionally, high grade astrocytoma patients with high ATP2A2 expression showed longer survival (median, 31.0±4.9 months, 95% CI, 21.4-40.7) than those with low ATP2A2 expression (median: 13.0±1.6 months, 95% CI, 9.9-16.1; P=0.027). Furthermore, both ATP2A2 overexpression and IDH1 mutation were detected in secondary glioblastoma, AA developed from DA and oligodendrogiomas with IDH1 mutation. The MTT assays showed that lentiviral ATP2A2 overexpression significantly suppressed the clonogenic growth of glioblastoma U251MG cells (P<0.05). Xenografts stably overexpressing ATP2A2 were markedly smaller in size 4 weeks post inoculation (P<0.05). Our findings identified high ATP2A2 expression in a subset of astrocytoma patients that was associated with better prognosis and ATP2A2 suppressed astrocytoma growth.
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Affiliation(s)
- Wei-Qing Li
- Department of Pathology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Nan-Zhe Zhong
- Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Jin He
- Department of Pathology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Yi-Ming Li
- Department of Neurosurgery, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Li-Jun Hou
- Department of Neurosurgery, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Hui-Min Liu
- Department of Pathology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Chun-Yan Xia
- Department of Pathology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Liang-Zhe Wang
- Department of Pathology, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
| | - Yi-Cheng Lu
- Department of Neurosurgery, Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China
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Parisot S, Ktena SI, Ferrante E, Lee M, Moreno RG, Glocker B, Rueckert D. Spectral Graph Convolutions for Population-Based Disease Prediction. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION − MICCAI 2017 2017. [DOI: 10.1007/978-3-319-66179-7_21] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
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45
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The etiopathogenesis of diffuse low-grade gliomas. Crit Rev Oncol Hematol 2016; 109:51-62. [PMID: 28010898 DOI: 10.1016/j.critrevonc.2016.11.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 11/18/2016] [Accepted: 11/22/2016] [Indexed: 12/13/2022] Open
Abstract
The origins of diffuse low-grade gliomas (DLGG) are unknown. Beyond some limited data on their temporal and cellular origins, the mechanisms and risk factors involved are poorly known. First, based on strong relationships between DLGG development and the eloquence of brain regions frequently invaded by these tumors, we propose a "functional theory" to explain the origin of DLGG. Second, the biological pathways involved in DLGG genesis may differ according to tumor location (anatomo-molecular correlations). The cellular and molecular mechanisms of such "molecular theory" will be reviewed. Third, the geographical distribution of diffuse WHO grade II-III gliomas within populations is heterogeneous, suggesting possible environmental risk factors. We will discuss this "environmental theory". Finally, we will summarize the current knowledge on genetic susceptibility in gliomas ("genetic predisposition theory"). These crucial issues illustrate the close relationships between the pathophysiology of gliomagenesis, the anatomo-functional organization of the brain, and personalized management of DLGG patients.
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46
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Paragios N, Ferrante E, Glocker B, Komodakis N, Parisot S, Zacharaki EI. (Hyper)-graphical models in biomedical image analysis. Med Image Anal 2016; 33:102-106. [DOI: 10.1016/j.media.2016.06.028] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 06/16/2016] [Accepted: 06/16/2016] [Indexed: 11/29/2022]
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47
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Bilello M, Akbari H, Da X, Pisapia JM, Mohan S, Wolf RL, O’Rourke DM, Martinez-Lage M, Davatzikos C. Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma. Neuroimage Clin 2016; 12:34-40. [PMID: 27358767 PMCID: PMC4916067 DOI: 10.1016/j.nicl.2016.03.007] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 03/09/2016] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE In treating glioblastoma (GB), surgical and chemotherapeutic treatment guidelines are, for the most part, independent of tumor location. In this work, we compiled imaging data from a large cohort of GB patients to create statistical atlases illustrating the disease spatial frequency as a function of patient demographics as well as tumor characteristics. MATERIALS AND METHODS Two-hundred-six patients with pathology-proven glioblastoma were included. Of those, 65 had pathology-proven recurrence and 113 had molecular subtype and genetic information. We used validated software to segment the tumors in all patients and map them from patient space into a common template. We then created statistical maps that described the spatial location of tumors with respect to demographics and tumor characteristics. We applied a chi-square test to determine whether pattern differences were statistically significant. RESULTS The most frequent location for glioblastoma in our patient population is the right temporal lobe. There are statistically significant differences when comparing patterns using demographic data such as gender (p = 0.0006) and age (p = 0.006). Small and large tumors tend to occur in separate locations (p = 0.0007). The tumors tend to occur in different locations according to their molecular subtypes (p < 10(- 6)). The classical subtype tends to spare the frontal lobes, the neural subtype tend to involve the inferior right frontal lobe. Although the sample size is limited, there was a difference in location according to EGFR VIII genotype (p < 10(- 4)), with a right temporal dominance for EFGR VIII negative tumors, and frontal lobe dominance in EGFR VIII positive tumors. CONCLUSIONS Spatial location of GB is an important factor that correlates with demographic factors and tumor characteristics, which should therefore be considered when evaluating a patient with GB and might assist in personalized treatment.
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Affiliation(s)
- Michel Bilello
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Hamed Akbari
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Xiao Da
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Jared M. Pisapia
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, USA
| | - Suyash Mohan
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Ronald L. Wolf
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Donald M. O’Rourke
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, USA
| | - Maria Martinez-Lage
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, USA
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