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Lohrke F, Madai VI, Kossen T, Aydin OU, Behland J, Hilbert A, Mutke MA, Bendszus M, Sobesky J, Frey D. Perfusion parameter map generation from TOF-MRA in stroke using generative adversarial networks. Neuroimage 2024; 298:120770. [PMID: 39117094 DOI: 10.1016/j.neuroimage.2024.120770] [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: 04/08/2024] [Revised: 06/28/2024] [Accepted: 08/02/2024] [Indexed: 08/10/2024] Open
Abstract
PURPOSE To generate perfusion parameter maps from Time-of-flight magnetic resonance angiography (TOF-MRA) images using artificial intelligence to provide an alternative to traditional perfusion imaging techniques. MATERIALS AND METHODS This retrospective study included a total of 272 patients with cerebrovascular diseases; 200 with acute stroke (from 2010 to 2018), and 72 with steno-occlusive disease (from 2011 to 2014). For each patient the TOF MRA image and the corresponding Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) were retrieved from the datasets. The authors propose an adapted generative adversarial network (GAN) architecture, 3D pix2pix GAN, that generates common perfusion maps (CBF, CBV, MTT, TTP, Tmax) from TOF-MRA images. The performance was evaluated by the structural similarity index measure (SSIM). For a subset of 20 patients from the acute stroke dataset, the Dice coefficient was calculated to measure the overlap between the generated and real hypoperfused lesions with a time-to-maximum (Tmax) > 6 s. RESULTS The GAN model exhibited high visual overlap and performance for all perfusion maps in both datasets: acute stroke (mean SSIM 0.88-0.92, mean PSNR 28.48-30.89, mean MAE 0.02-0.04 and mean NRMSE 0.14-0.37) and steno-occlusive disease patients (mean SSIM 0.83-0.98, mean PSNR 23.62-38.21, mean MAE 0.01-0.05 and mean NRMSE 0.03-0.15). For the overlap analysis for lesions with Tmax>6 s, the median Dice coefficient was 0.49. CONCLUSION Our AI model can successfully generate perfusion parameter maps from TOF-MRA images, paving the way for a non-invasive alternative for assessing cerebral hemodynamics in cerebrovascular disease patients. This method could impact the stratification of patients with cerebrovascular diseases. Our results warrant more extensive refinement and validation of the method.
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Affiliation(s)
- Felix Lohrke
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany
| | - Vince Istvan Madai
- QUEST Center for Transforming Biomedical Research, Berlin Institute of Health (BIH), Charité Universitätsmedizin Berlin, Germany; School of Computing and Digital Technology, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, United Kingdom
| | - Tabea Kossen
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany
| | - Orhun Utku Aydin
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany
| | - Jonas Behland
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany
| | - Adam Hilbert
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany
| | | | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jan Sobesky
- Centre for Stroke Research Berlin, Charité Universitätsmedizin Berlin, Germany; Johanna-Etienne-Hospital, Neuss, Germany
| | - Dietmar Frey
- CLAIM - Charité Lab for Artificial Intelligence in Medicine, Charité Universitätsmedizin Berlin, Germany; Department of Neurosurgery, Charité Universitätsmedizin Berlin, Germany.
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Pillai P, Bush SJ, Kusuma Y, Churilov L, Dowling RJ, Luu VD, Davis SM, Mitchell PJ, Yan B. Atrial fibrillation is associated with higher first pass effect following thrombectomy for large vessel occlusion. J Neurointerv Surg 2024; 16:652-656. [PMID: 37355258 DOI: 10.1136/jnis-2023-020512] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 06/10/2023] [Indexed: 06/26/2023]
Abstract
BACKGROUND First pass effect (FPE), defined as single-pass complete or near complete reperfusion during endovascular thrombectomy (EVT) for large vessel occlusion (LVO) strokes, is a critical performance metric. Atrial fibrillation (AF)-related strokes have different clot composition compared with non-AF strokes, which may impact thrombectomy reperfusion results. We compared FPE rates in AF and non-AF stroke patients to evaluate if AF-related strokes had higher FPE rates. METHODS We conducted a post-hoc analysis of the DIRECT-SAFE trial data, including patients with retrievable clots on the initial angiographic run. Patients were categorized into AF and non-AF groups. The primary outcome was the presence or absence of FPE (single-pass, single-device resulting in complete/near complete reperfusion) in AF and non-AF groups. We used multivariable logistic regression to examine the association between FPE and AF, adjusting for thrombolysis pre-thrombectomy and clot location. RESULTS We included 253 patients (67 with AF, 186 without AF). AF patients were older (mean age: 74 years vs 67.5 years, p=0.001), had a higher proportion of females (55% vs 40%, p=0.044), and experienced more severe strokes (median National Institutes of Health Stroke Scale (NIHSS) score: 17 vs 14, p=0.009) than non-AF patients. No differences were observed in thrombolytic agent usage, time metrics, or clot location. AF patients achieved a higher proportion of FPE compared with non-AF patients (55.22% vs 37.3%, adjusted odds ratio 2.00 (95% CI 1.13 to 3.55), p=0.017). CONCLUSIONS AF-related strokes in LVO patients treated with EVT were associated with FPE. This highlights the need for preparedness for multiple passes and potential adjuvant/rescue therapy in non-AF-related strokes.
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Affiliation(s)
- Presaad Pillai
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
- Neurology Unit, Department of Medicine, Queen Elizabeth Hospital, Kota Kinabalu, Malaysia
| | - Steven J Bush
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Yohanna Kusuma
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Leonid Churilov
- Melbourne Medical School, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Richard J Dowling
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vu Dang Luu
- Radiology Center, Bach Mai Hospital, Hanoi Medical University, Hanoi, Vietnam
| | - Stephen M Davis
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Peter J Mitchell
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Bernard Yan
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
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Panicker S, Wilseck ZM, Lin LY, Gemmete JJ. CT Imaging Computed Tomography/Computed Tomography Angiography/Perfusion in Acute Ischemic Stroke and Vasospasm. Neuroimaging Clin N Am 2024; 34:175-189. [PMID: 38604703 DOI: 10.1016/j.nic.2024.01.004] [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] [Indexed: 04/13/2024]
Abstract
Computed tomography (CT), CT angiography (CTA), and CT perfusion (CTP) play crucial roles in the comprehensive evaluation and management of acute ischemic stroke, aneurysmal subarachnoid hemorrhage (SAH), and vasospasm. CTP provides functional data about cerebral blood flow, allowing radiologists, neurointerventionalists, and stroke neurologists to more accurately delineate the volume of core infarct and ischemic penumbra allowing for patient-specific treatment decisions to be made. CTA and CTP are used in tandem to evaluate for vasospasm associated with aneurysmal SAH and can help provide an insight into the physiologic impact of angiographic vasospasm, better triaging patients for medical and interventional treatment.
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Affiliation(s)
| | - Zachary M Wilseck
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Leanne Y Lin
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Joseph J Gemmete
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA; Department of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, USA
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Liu H, Huang Y, Chen Y, Tang Z, Huang M, Ming Y, Wang M, Chen W, Huang Z, Qing L, Wang Q, Jia B. Family with Sequence Similarity 72 (FAM72) - A prospective biomarker for poor prognosis in patients with oral squamous cell carcinoma. Arch Oral Biol 2023; 151:105695. [PMID: 37086493 DOI: 10.1016/j.archoralbio.2023.105695] [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: 02/19/2023] [Revised: 03/20/2023] [Accepted: 04/06/2023] [Indexed: 04/24/2023]
Abstract
OBJECTIVE To study the effect of FAM72 on the prognosis of patients with oral squamous cell carcinoma (OSCC) and to explore the relationship between FAM72 and OSCC. DESIGN We used a vast array of databases and analytical vehicles to assess the relation between FAM72 and OSCC, including The Cancer Genome Atlas (TCGA), Metascape, and MethSurv. We made a preliminary verification of OSCC lines and tissues by real time quantitative polymerase chain reaction (RT-qPCR). RESULTS FAM72 was higher in OSCC than in normal tissues. Analysis of univariate COX data indicated that elevated expression of FAM72A, FAM72B, and FAM72C in OSCC was related to poor overall survival. Moreover, FAM72B and FAM72C were independent of overall survival in multiple COX regression. FAM72A-D and its coexpressed genes in Metascape were analyzed by Gene Ontology (GO), they were enriched in cellular cycle, mitotic and DNA metabolism. Gene set enrichment analysis (GSEA) demonstrated an enrichment in pathways related to cell metabolism. Additionally, high FAM72 expression related to a worse prognosis in OSCC patients. FAM72A-D linked to the infiltration of tumor immune cell in OSCC patients. We found that methylation levels are likely linked to prognosis in OSCC patients. We used RT-qPCR to ascertain the differential FAM72B and FAM72C expression levels in cancer and paracancerous tissues of OSCC, human normal oral keratinocytes (HOK), and human tongue squamous cell carcinoma (Cal-33). CONCLUSION Our findings indicate that FAM72B and FAM72C are potential molecular markers of poor prognosis in OSCC and may act as novel targets for OSCC treatment strategies.
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Affiliation(s)
- Hongyu Liu
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Yisheng Huang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Yuanxin Chen
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Zhengming Tang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Mingshu Huang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Yue Ming
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Min Wang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Weixing Chen
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Zhijie Huang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Ling Qing
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Qin Wang
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Bo Jia
- Department of Oral Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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Kossen T, Madai VI, Mutke MA, Hennemuth A, Hildebrand K, Behland J, Aslan C, Hilbert A, Sobesky J, Bendszus M, Frey D. Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease. Front Neurol 2023; 13:1051397. [PMID: 36703627 PMCID: PMC9871486 DOI: 10.3389/fneur.2022.1051397] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023] Open
Abstract
Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a temporal component (temp-pix2pix-GAN) that generates perfusion maps in an end-to-end fashion. We train our model on perfusion maps infused with expert knowledge to encode it into the GANs. The performance was trained and evaluated using the structural similarity index measure (SSIM) on two datasets including patients with acute stroke and the steno-occlusive disease. Our temp-pix2pix architecture showed high performance on the acute stroke dataset for all perfusion maps (mean SSIM 0.92-0.99) and good performance on data including patients with the steno-occlusive disease (mean SSIM 0.84-0.99). While clinical validation is still necessary for future studies, our results mark an important step toward automated expert-level perfusion maps and thus fast patient stratification.
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Affiliation(s)
- Tabea Kossen
- Charité Lab for Artificial Intelligence in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany,Department of Computer Engineering and Microelectronics, Computer Vision and Remote Sensing, Technical University Berlin, Berlin, Germany,*Correspondence: Tabea Kossen ✉
| | - Vince I. Madai
- Charité Lab for Artificial Intelligence in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany,QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charité-Universitätsmedizin Berlin, Berlin, Germany,Faculty of Computing, Engineering and the Built Environment, School of Computing and Digital Technology, Birmingham City University, Birmingham, United Kingdom
| | - Matthias A. Mutke
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Anja Hennemuth
- Department of Computer Engineering and Microelectronics, Computer Vision and Remote Sensing, Technical University Berlin, Berlin, Germany,Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany,Fraunhofer MEVIS, Bremen, Germany
| | - Kristian Hildebrand
- Department of Computer Science and Media, Berlin University of Applied Sciences and Technology, Berlin, Germany
| | - Jonas Behland
- Charité Lab for Artificial Intelligence in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Cagdas Aslan
- Department of Computer Science and Media, Berlin University of Applied Sciences and Technology, Berlin, Germany
| | - Adam Hilbert
- Charité Lab for Artificial Intelligence in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Sobesky
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany,Johanna-Etienne-Hospital, Neuss, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Dietmar Frey
- Charité Lab for Artificial Intelligence in Medicine (CLAIM), Charité-Universitätsmedizin Berlin, Berlin, Germany
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Maslias E, Puccinelli F, Nannoni S, Hajdu SD, Bartolini B, Ricciardi F, Dunet V, Maeder P, Strambo D, Saliou G, Michel P. Predictors of Endovascular Treatment Procedural Complications in Acute Ischemic Stroke: A Single-Center Cohort Study. AJNR Am J Neuroradiol 2022; 43:1743-1748. [PMID: 36423955 DOI: 10.3174/ajnr.a7705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/12/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND PURPOSE Procedural complications occur in 4%-29% of endovascular treatments in acute ischemic stroke. However, little is known about their predictors and clinical impact in the real world. We aimed to investigate the frequency and clinical impact of procedural complications of endovascular treatment and identify associated risk factors. MATERIALS AND METHODS From 2015-2019, we retrospectively reviewed all patients with acute ischemic stroke receiving endovascular treatment within 24 hours included in the Acute STroke Registry and Analysis of Lausanne. We identified patients having an endovascular treatment procedural complication (local access complication, arterial perforation, dissection or vasospasm, and embolization in a previously nonischemic territory) and performed logistic regression analyses to identify associated predictors. We also correlated procedural complications with long-term clinical outcome. RESULTS Of the 684 consecutive patients receiving endovascular treatment, 113 (16.5%) had at least 1 procedural complication. The most powerful predictors were groin puncture off-hours (OR = 2.24), treatment of 2 arterial sites (OR = 2.71), and active smoking (OR = 1.93). Patients with a complication had a significantly less favorable short-term clinical outcome (Δ-NIHSS score of -2.2 versus -4.33, P-value adjusted < .001), but a similar long-term clinical outcome (mRS at 3 months = 3 versus 2, P-value adjusted = .272). CONCLUSIONS Procedural complications are quite common in endovascular treatment and lead to a less favorable short-term but similar long-term outcome. Their association with treatment off-hours and at 2 arterial sites requires particular attention in these situations to optimize the overall benefit of endovascular treatment.
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Affiliation(s)
- E Maslias
- From the Stroke Centre (E.M., S.N., D.S., P. Michel), Neurology Service, Department of Clinical Neurosciences
| | - F Puccinelli
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - S Nannoni
- From the Stroke Centre (E.M., S.N., D.S., P. Michel), Neurology Service, Department of Clinical Neurosciences
| | - S D Hajdu
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - B Bartolini
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - F Ricciardi
- Department of Statistical Science (F.R.), University College London, London, UK
| | - V Dunet
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - P Maeder
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - D Strambo
- From the Stroke Centre (E.M., S.N., D.S., P. Michel), Neurology Service, Department of Clinical Neurosciences
| | - G Saliou
- Department of Diagnostic and Interventional Radiology (F.P., S.D.H., B.B., V.D., P. Maeder, G.S.), Neuroradiology Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - P Michel
- From the Stroke Centre (E.M., S.N., D.S., P. Michel), Neurology Service, Department of Clinical Neurosciences
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Gunter D, Puac-Polanco P, Miguel O, Thornhill RE, Yu AYX, Liu ZA, Mamdani M, Pou-Prom C, Aviv RI. Rule-based natural language processing for automation of stroke data extraction: a validation study. Neuroradiology 2022; 64:2357-2362. [PMID: 35913525 DOI: 10.1007/s00234-022-03029-1] [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: 06/20/2022] [Accepted: 07/25/2022] [Indexed: 11/30/2022]
Abstract
PURPOSE Data extraction from radiology free-text reports is time consuming when performed manually. Recently, more automated extraction methods using natural language processing (NLP) are proposed. A previously developed rule-based NLP algorithm showed promise in its ability to extract stroke-related data from radiology reports. We aimed to externally validate the accuracy of CHARTextract, a rule-based NLP algorithm, to extract stroke-related data from free-text radiology reports. METHODS Free-text reports of CT angiography (CTA) and perfusion (CTP) studies of consecutive patients with acute ischemic stroke admitted to a regional stroke center for endovascular thrombectomy were analyzed from January 2015 to 2021. Stroke-related variables were manually extracted as reference standard from clinical reports, including proximal and distal anterior circulation occlusion, posterior circulation occlusion, presence of ischemia or hemorrhage, Alberta stroke program early CT score (ASPECTS), and collateral status. These variables were simultaneously extracted using a rule-based NLP algorithm. The NLP algorithm's accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. RESULTS The NLP algorithm's accuracy was > 90% for identifying distal anterior occlusion, posterior circulation occlusion, hemorrhage, and ASPECTS. Accuracy was 85%, 74%, and 79% for proximal anterior circulation occlusion, presence of ischemia, and collateral status respectively. The algorithm confirmed the absence of variables from radiology reports with an 87-100% accuracy. CONCLUSIONS Rule-based NLP has a moderate to good performance for stroke-related data extraction from free-text imaging reports. The algorithm's accuracy was affected by inconsistent report styles and lexicon among reporting radiologists.
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Affiliation(s)
- Dane Gunter
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Paulo Puac-Polanco
- Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, The Ottawa Hospital Civic Campus Room C110, 1053 Carling Ave, Ottawa, ON, ON K1Y 4E9, Canada
| | - Olivier Miguel
- Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, The Ottawa Hospital Civic Campus Room C110, 1053 Carling Ave, Ottawa, ON, ON K1Y 4E9, Canada
| | - Rebecca E Thornhill
- Division of Medical Physics, Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, Ottawa, ON, Canada
| | - Amy Y X Yu
- Department of Medicine (Neurology), University of Toronto, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Zhongyu A Liu
- Department of Medicine (Neurology), University of Toronto, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Muhammad Mamdani
- Department of Medicine, Unity Health Toronto, University of Toronto, Toronto, ON, Canada
| | | | - Richard I Aviv
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada. .,Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, The Ottawa Hospital Civic Campus Room C110, 1053 Carling Ave, Ottawa, ON, ON K1Y 4E9, Canada.
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Pan J, Wu H, Wu T, Geng Y, Yuan R. Association Between Post-procedure Cerebral Blood Flow Velocity and Severity of Brain Edema in Acute Ischemic Stroke With Early Endovascular Therapy. Front Neurol 2022; 13:906377. [PMID: 35923831 PMCID: PMC9339960 DOI: 10.3389/fneur.2022.906377] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesWe aimed to investigate the association between post-procedure cerebral blood flow velocity (CBFV) and severity of brain edema in patients with acute ischemic stroke (AIS) who received early endovascular therapy (EVT).MethodsWe retrospectively included patients with AIS who received EVT within 24 h of onset between February 2016 and November 2021. Post-procedure CBFV of the middle cerebral artery was measured in the affected and the contralateral hemispheres using transcranial Doppler ultrasound. The severity of brain edema was measured using the three-level cerebral edema grading from the Safe Implementation of Thrombolysis in Stroke-Monitoring Study, with grades 2–3 indicating severe brain edema. The Association between CBFV parameters and severity of brain edema was analyzed.ResultsA total of 101 patients (mean age 64.2 years, 65.3% male) were included, of whom 56.3% (57/101) suffered brain edema [grade 1, 23 (22.8%); grade 2, 10 (9.9%); and grade 3, 24 (23.8%)]. Compared to patients with non-severe brain edema, patients with severe brain edema had lower affected/contralateral ratios of systolic CBFV (median 1 vs. 1.2, P = 0.020) and mean CBFV (median 0.9 vs. 1.3, P = 0.029). Multivariate logistic regression showed that severe brain edema was independently associated with affected/contralateral ratios of systolic CBFV [odds ratio (OR) = 0.289, 95% confidence interval (CI): 0.069–0.861, P = 0.028] and mean CBFV (OR = 0.278, 95% CI: 0.084–0.914, P = 0.035) after adjusting for potential confounders.ConclusionPost-procedure affected/contralateral ratio of CBFV may be a promising predictor of brain edema severity in patients with AIS who received early EVT.
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Affiliation(s)
- Jie Pan
- Suzhou Medical College of Soochow University, Suzhou, China
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Huadong Wu
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Tingting Wu
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Yu Geng
- Suzhou Medical College of Soochow University, Suzhou, China
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
- *Correspondence: Ruozhen Yuan
| | - Ruozhen Yuan
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
- Yu Geng
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10
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Clinical and therapeutic variables may influence the association between infarct core predicted by CT perfusion and clinical outcome in acute stroke. Eur Radiol 2022; 32:4510-4520. [PMID: 35182205 DOI: 10.1007/s00330-022-08590-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/07/2021] [Accepted: 01/22/2022] [Indexed: 12/30/2022]
Abstract
OBJECTIVES After an acute ischemic stroke, patients with a large CT perfusion (CTP) predicted infarct core (pIC) have poor clinical outcome. However, previous research suggests that this relationship may be relevant for subgroups of patients determined by pretreatment and treatment-related variables while negligible for others. We aimed to identify these variables. METHODS We included a cohort of 828 patients with acute proximal carotid arterial occlusions imaged with a whole-brain CTP within 8 h from stroke onset. pIC was computed on CTP Maps (cerebral blood flow < 30%), and poor clinical outcome was defined as a 90-day modified Rankin Scale score > 2. Potential mediators of the association between pIC and clinical outcome were evaluated through first-order and advanced interaction analyses in the derivation cohort (n = 654) for obtaining a prediction model. The derived model was further validated in an independent cohort (n = 174). RESULTS The volume of pIC was significantly associated with poor clinical outcome (OR = 2.19, 95% CI = 1.73 - 2.78, p < 0.001). The strength of this association depended on baseline National Institute of Health Stroke Scale, glucose levels, the use of thrombectomy, and the interaction of age with thrombectomy. The model combining these variables showed good discrimination for predicting clinical outcome in both the derivation cohort and validation cohorts (area under the receiver operating characteristic curve 0.780 (95% CI = 0.746-0.815) and 0.782 (95% CI = 0.715-0.850), respectively). CONCLUSIONS In patients imaged within 8 h from stroke onset, the association between pIC and clinical outcome is significantly modified by baseline and therapeutic variables. These variables deserve consideration when evaluating the prognostic relevance of pIC. KEY POINTS •The volume of CT perfusion (CTP) predicted infarct core (pIC) is associated with poor clinical outcome in acute ischemic stroke imaged within 8 h of onset. •The relationship between pIC and clinical outcome may be modified by baseline clinical severity, glucose levels, thrombectomy use, and the interaction of age with thrombectomy. •CTP pIC should be evaluated in an individual basis for predicting clinical outcome in patients imaged within 8 h from stroke onset.
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11
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Park KJ, Suh JY, Heo C, Kim M, Baek JH, Kim JK. Hyperoxia-Induced ΔR 1: MRI Biomarker of Histological Infarction in Acute Cerebral Stroke. Korean J Radiol 2022; 23:446-454. [PMID: 35345061 PMCID: PMC8961021 DOI: 10.3348/kjr.2021.0477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/09/2021] [Accepted: 11/25/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate whether hyperoxia-induced ΔR1 (hyperO2ΔR1) can accurately identify histological infarction in an acute cerebral stroke model. MATERIALS AND METHODS In 18 rats, MRI parameters, including hyperO2ΔR1, apparent diffusion coefficient (ADC), cerebral blood flow and volume, and 18F-fluorodeoxyglucose uptake on PET were measured 2.5, 4.5, and 6.5 hours after a 60-minutes occlusion of the right middle cerebral artery. Histological examination of the brain was performed immediately following the imaging studies. MRI and PET images were co-registered with digitized histological images. The ipsilateral hemisphere was divided into histological infarct (histological cell death), non-infarct ischemic (no cell death but ADC decrease), and non-ischemic (no cell death or ADC decrease) areas for comparisons of imaging parameters. The levels of hyperO2ΔR1 and ADC were measured voxel-wise from the infarct core to the non-ischemic region. The correlation between areas of hyperO2ΔR1-derived infarction and histological cell death was evaluated. RESULTS HyperO2ΔR1 increased only in the infarct area (p ≤ 0.046) compared to the other areas. ADC decreased stepwise from non-ischemic to infarct areas (p = 0.002 at all time points). The other parameters did not show consistent differences among the three areas across the three time points. HyperO2ΔR1 sharply declined from the core to the border of the infarct areas, whereas there was no change within the non-infarct areas. A hyperO2ΔR1 value of 0.04 s-1 was considered the criterion to identify histological infarction. ADC increased gradually from the infarct core to the periphery, without a pronounced difference at the border between the infarct and non-infarct areas. Areas of hyperO2ΔR1 higher than 0.04 s-1 on MRI were strongly positively correlated with histological cell death (r = 0.862; p < 0.001). CONCLUSION HyperO2ΔR1 may be used as an accurate and early (2.5 hours after onset) indicator of histological infarction in acute stroke.
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Affiliation(s)
- Kye Jin Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ji-Yeon Suh
- Asan Institute for Medical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Changhoe Heo
- Asan Institute for Medical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Miyeon Kim
- Asan Institute for Medical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jin Hee Baek
- Asan Institute for Medical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jeong Kon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.,Asan Institute for Medical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
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12
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Evolution of Hypodensity on Non-Contrast CT in Correlation with Collaterals in Anterior Circulation Stroke with Successful Endovascular Reperfusion. J Clin Med 2022; 11:jcm11020446. [PMID: 35054140 PMCID: PMC8777970 DOI: 10.3390/jcm11020446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 01/07/2022] [Accepted: 01/13/2022] [Indexed: 11/22/2022] Open
Abstract
Introduction: The aim of the study was to assess the impact of collaterals on the evolution of hypodensity on non-contrast CT (NCCT) in anterior circulation stroke with reperfusion by mechanical thrombectomy (MT). Methods: We retrospectively included stroke patients with middle cerebral artery occlusion who were reperfused by MT in early and late time window. Artificial intelligence (AI)-based software was used to calculate of hypodensity volumes at baseline NCCT (V1) and at follow-up NCCT 24 h after MT (V2), along with the difference between the two volumes (V2-V1) and the follow-up (V2)/baseline (V1) volume ratio (V2/V1). The same software was used to classify collateral status by using a 4-point scale where the score of zero indicated no collaterals and the score of three represented contrast filling of all collaterals. The volumetric values were correlated with the collateral scores. Results: Collateral scores had significant negative correlation with V1 (p = 0.035), V2, V2− V1 and V2/V1 (p < 0.001). In cases with collateral score = 3, V2 was significantly smaller or absent compared to V1; in those with collateral score 2, V2 was slightly larger than V1, and in those with scores 1 and 0 V2 was significantly larger than V1. These relationships were observed in both early and late time windows. Conclusions: The collateral status determined the evolution of the baseline hypodensity on NCCT in patients with anterior circulation stroke who had MT reperfusion. Damage can be stable or reversible in patients with good collaterals while in those with poor collaterals tissues that initially appear normal will frequently appear as necrotic after 24 h. With good collaterals, it is stable or can be reversible while with poor collaterals, normal looking tissue frequently appears as necrotic in follow-up exam. Hence, acute hypodensity represents different states of the ischemic brain parenchyma.
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13
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Peerlings D, van Ommen F, Bennink E, Dankbaar JW, Velthuis BK, Emmer BJ, Hoving JW, Majoie CBLM, Marquering HA, de Jong HWAM. Probability maps classify ischemic stroke regions more accurately than CT perfusion summary maps. Eur Radiol 2022; 32:6367-6375. [PMID: 35357536 PMCID: PMC9381605 DOI: 10.1007/s00330-022-08700-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/01/2022] [Accepted: 02/26/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES To compare single parameter thresholding with multivariable probabilistic classification of ischemic stroke regions in the analysis of computed tomography perfusion (CTP) parameter maps. METHODS Patients were included from two multicenter trials and were divided into two groups based on their modified arterial occlusive lesion grade. CTP parameter maps were generated with three methods-a commercial method (ISP), block-circulant singular value decomposition (bSVD), and non-linear regression (NLR). Follow-up non-contrast CT defined the follow-up infarct region. Conventional thresholds for individual parameter maps were established with a receiver operating characteristic curve analysis. Probabilistic classification was carried out with a logistic regression model combining the available CTP parameters into a single probability. RESULTS A total of 225 CTP data sets were included, divided into a group of 166 patients with successful recanalization and 59 with persistent occlusion. The precision and recall of the CTP parameters were lower individually than when combined into a probability. The median difference [interquartile range] in mL between the estimated and follow-up infarct volume was 29/23/23 [52/50/52] (ISP/bSVD/NLR) for conventional thresholding and was 4/6/11 [31/25/30] (ISP/bSVD/NLR) for the probabilistic classification. CONCLUSIONS Multivariable probability maps outperform thresholded CTP parameter maps in estimating the infarct lesion as observed on follow-up non-contrast CT. A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions. KEY POINTS • Combining CTP parameters with a logistic regression model increases the precision and recall in estimating ischemic stroke regions. • Volumes following from a probabilistic analysis predict follow-up infarct volumes better than volumes following from a threshold-based analysis. • A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.
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Affiliation(s)
- Daan Peerlings
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
| | - Fasco van Ommen
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
| | - Edwin Bennink
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands ,grid.7692.a0000000090126352Image Sciences Institute, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
| | - Jan W. Dankbaar
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
| | - Birgitta K. Velthuis
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
| | - Bart J. Emmer
- grid.509540.d0000 0004 6880 3010Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, 1105AZ The Netherlands
| | - Jan W. Hoving
- grid.509540.d0000 0004 6880 3010Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, 1105AZ The Netherlands
| | - Charles B. L. M. Majoie
- grid.509540.d0000 0004 6880 3010Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, 1105AZ The Netherlands
| | - Henk A. Marquering
- grid.509540.d0000 0004 6880 3010Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, 1105AZ The Netherlands
| | - Hugo W. A. M. de Jong
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, 3584CX The Netherlands
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14
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Bivard A, Churilov L, Ma H, Levi C, Campbell B, Yassi N, Meretoja A, Zhao H, Sharma G, Chen C, Davis S, Donnan G, Yan B, Parsons M. Does variability in automated perfusion software outputs for acute ischemic stroke matter? Reanalysis of EXTEND perfusion imaging. CNS Neurosci Ther 2021; 28:139-144. [PMID: 34786868 PMCID: PMC8673699 DOI: 10.1111/cns.13756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 10/05/2021] [Accepted: 10/21/2021] [Indexed: 11/28/2022] Open
Abstract
Aims We reprocessed the Extending the time for Thrombolysis in Emergency Neurological Deficits (EXTEND) perfusion imaging with a different automated software with the aim of comparing mismatch eligibility and outcomes. Methods EXTEND baseline perfusion imaging data were reprocessed using autoMIStar software to identify patients who were eligible based on the same target mismatch criteria as per the original trial. Results From the 225 patients fulfilling RAPID‐based mismatch criteria randomized in the EXTEND study, 196 (87%) patients met the revised mismatch criteria. Most common reasons for not meeting revised criteria were core >70 ml (n = 9), and no perfusion lesion/lack of penumbral tissue (n = 20). The revised perfusion lesion volumes were significantly smaller compared to the original RAPID volumes (median 68 ml IQR 34–102 ml vs. 42 ml 16–92 ml, p = 0.036). Of the patients who met the revised mismatch criteria, 40% receiving alteplase had modified Rankin Scale (mRS) 0–1 at 3‐month compared to 28% with placebo (Adjusted Odds Ratio (OR) = 2.23, CI 1.08–4.58, p = 0.028). In contrast, in the original mismatch cohort, 35% receiving alteplase had mRS 0–1 at 3‐month compared to 30% with placebo (adjusted OR = 1.88, p = 0.056). Conclusions These data reinforce the benefit of alteplase in the later time window, and suggest that differences in automated perfusion imaging software outputs may be clinically relevant.
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Affiliation(s)
- Andrew Bivard
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Leonid Churilov
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Henry Ma
- Department of Medicine, School of Clinical Science, Monash University, Clayton, VIC, Australia
| | - Christopher Levi
- Department of Neurology, John Hunter Hospital, Hunter Medical Research Institute, University of Newcastle, Newcastle, NSW, Australia
| | - Bruce Campbell
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Atte Meretoja
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.,Department of Neurology, Helsinki University Hospital, Helsinki, Finland
| | - Henry Zhao
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Gagan Sharma
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Chushuang Chen
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Stephen Davis
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Geoffrey Donnan
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Bernard Yan
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Mark Parsons
- Department of Neurology Liverpool Hospital, Ingham Institute of Applied Medical Research, University of New South Wales South Western Sydney Clinical School, Liverpool, NSW, Australia
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15
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Liu K, Jiang L, Zhao Y, Xia W, Ruan J, Huang H, Niu G, Yan S, Yin C. Risk factors of contrast extravasation and subsequent hemorrhagic transformation after thrombectomy. J Int Med Res 2021; 49:3000605211049074. [PMID: 34633880 PMCID: PMC8511932 DOI: 10.1177/03000605211049074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Objective The risk factors associated with iodine contrast extravasation immediately
after endovascular thrombectomy (EVT) and subsequent hemorrhagic
transformation within 24 hours remain unclear. Methods Mixed images, iodine overlay maps, and virtual non-contrast images were
reconstructed from 106 consecutive acute ischemic stroke patients who
underwent dual energy computed tomography immediately and 24 hours after
EVT. Multivariate analyses of clinical and radiological data were performed
to explore independent predictors of iodine contrast extravasation and
hemorrhagic transformation. Results Sixty-eight (64.2%) patients exhibited pure iodine contrast extravasation
after EVT; 30.9% developed hemorrhagic transformation within 24 hours after
EVT. The number of stent retriever passes was independently associated with
both iodine contrast extravasation (odds ratio 1.608; 95% confidence
interval (CI) 1.047–2.469) and subsequent hemorrhagic transformation (odds
ratio 1.477; 95% CI 1.003–2.175). Patients with more than two stent
retriever passes were more likely to exhibit iodine contrast extravasation
(sensitivity = 68.2%, specificity = 81.5%), while those with more than three
stent retriever passes more often exhibited hemorrhage after iodine contrast
extravasation (sensitivity = 64.6%, specificity = 87.2%). Conclusions The number of stent retriever passes was an independent predictor for both
iodine contrast extravasation and subsequent hemorrhagic transformation.
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Affiliation(s)
- Keqin Liu
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lin Jiang
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuqi Zhao
- Department of Neurology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Wenqing Xia
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jie Ruan
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Huan Huang
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Guozhong Niu
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shenqiang Yan
- Department of Neurology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Congguo Yin
- Department of Neurology, Hangzhou First Hospital, Zhejiang University School of Medicine, Hangzhou, China
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16
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Nicolas-Jilwan M, Wintermark M. Automated Brain Perfusion Imaging in Acute Ischemic Stroke: Interpretation Pearls and Pitfalls. Stroke 2021; 52:3728-3738. [PMID: 34565174 DOI: 10.1161/strokeaha.121.035049] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Recent advancements in computed tomography technology, including improved brain coverage and automated processing of the perfusion data, have reinforced the use of perfusion computed tomography imaging in the routine evaluation of patients with acute ischemic stroke. The DAWN (Diffusion Weighted Imaging or Computerized Tomography Perfusion Assessment With Clinical Mismatch in the Triage of Wake Up and Late Presenting Strokes Undergoing Neurointervention) and DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trials have established the benefit of endovascular thrombectomy in patients with acute ischemic stroke with anterior circulation large vessel occlusion up to 24 hours of last seen normal, using perfusion imaging-based patient selection. The compelling data has prompted stroke centers to increasingly introduce automated perfusion computed tomography imaging in the routine evaluation of patients with acute ischemic stroke. We present a comprehensive overview of the acquisition and interpretation of automated perfusion imaging in patients with acute ischemic stroke with a special emphasis on the interpretation pearls, pitfalls, and stroke mimicking conditions.
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Affiliation(s)
- Manal Nicolas-Jilwan
- Division of Neuroradiology, Department of Radiology, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia (M.N.-J.)
| | - Max Wintermark
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford Healthcare, CA (M.W.)
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17
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Goldman-Yassen AE, Straka M, Uhouse M, Dehkharghani S. Normative distribution of posterior circulation tissue time-to-maximum: Effects of anatomic variation, tracer kinetics, and implications for patient selection in posterior circulation ischemic stroke. J Cereb Blood Flow Metab 2021; 41:1912-1923. [PMID: 33444095 PMCID: PMC8327115 DOI: 10.1177/0271678x20982395] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The generalization of perfusion-based, anterior circulation large vessel occlusion selection criteria to posterior circulation stroke is not straightforward due to physiologic delay, which we posit produces physiologic prolongation of the posterior circulation perfusion time-to-maximum (Tmax). To assess normative Tmax distributions, patients undergoing CTA/CTP for suspected ischemic stroke between 1/2018-3/2019 were retrospectively identified. Subjects with any cerebrovascular stenoses, or with follow-up MRI or final clinical diagnosis of stroke were excluded. Posterior circulation anatomic variations were identified. CTP were processed in RAPID and segmented in a custom pipeline permitting manually-enforced arterial input function (AIF) and perfusion estimations constrained to pre-specified vascular territories. Seventy-one subjects (mean 64 ± 19 years) met inclusion. Median Tmax was significantly greater in the cerebellar hemispheres (right: 3.0 s, left: 2.9 s) and PCA territories (right: 2.9 s; left: 3.3 s) than in the anterior circulation (right: 2.4 s; left: 2.3 s, p < 0.001). Fetal PCA disposition eliminated ipsilateral PCA Tmax delays (p = 0.012). Median territorial Tmax was significantly lower with basilar versus any anterior circulation AIF for all vascular territories (p < 0.001). Significant baseline delays in posterior circulation Tmax are observed even without steno-occlusive disease and vary with anatomic variation and AIF selection. The potential for overestimation of at-risk volumes in the posterior circulation merits caution in future trials.
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Affiliation(s)
- Adam E Goldman-Yassen
- Department of Radiology, New York University Langone Medical Center, New York, NY, USA.,Department of Radiology, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | | | - Michael Uhouse
- Department of Radiology, George Washington University, Washington, DC, USA
| | - Seena Dehkharghani
- Department of Radiology, New York University Langone Medical Center, New York, NY, USA.,Department of Neurology, New York University Langone Medical Center, New York, NY, USA
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18
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Shankar JJS. Variation in CT perfusion protocol has implications on defining irreversibly damaged ischemic brain parenchyma. Eur Radiol 2021; 31:8315-8316. [PMID: 34338843 DOI: 10.1007/s00330-021-08209-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 06/29/2021] [Accepted: 07/04/2021] [Indexed: 10/20/2022]
Abstract
KEY POINTS • Computed tomographic perfusion (CTP) is increasingly being used in the characterization of brain ischemia.• Variations in post-processing protocols continue to be a challenge, resulting in a slight variation of CTP results.• We need to adopt a universal acquisition protocol to help optimize output of CTP.
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Affiliation(s)
- Jai Jai Shiva Shankar
- Rady Faculty of Health Sciences, Radiology Department, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB, R3A 1R9, Canada.
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19
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Course of Early Neurologic Symptom Severity after Endovascular Treatment of Anterior Circulation Large Vessel Occlusion Stroke: Association with Baseline Multiparametric CT Imaging and Clinical Parameters. Diagnostics (Basel) 2021; 11:diagnostics11071272. [PMID: 34359354 PMCID: PMC8303279 DOI: 10.3390/diagnostics11071272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/01/2021] [Accepted: 07/12/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Neurologic symptom severity and deterioration at 24 hours (h) predict long-term outcomes in patients with acute large vessel occlusion (LVO) stroke of the anterior circulation. We aimed to examine the association of baseline multiparametric CT imaging and clinical factors with the course of neurologic symptom severity in the first 24 h after endovascular treatment (EVT). Methods: Patients with LVO stroke of the anterior circulation were selected from a prospectively acquired consecutive cohort of patients who underwent multiparametric CT, including non-contrast CT, CT angiography and CT perfusion before EVT. The symptom severity was assessed on admission and after 24 h using the 42-point National Institutes of Health Stroke Scale (NIHSS). Clinical and imaging data were compared between patients with and without early neurological deterioration (END). END was defined as an increase in ≥4 points, and a significant clinical improvement as a decrease in ≥4 points, compared to NIHSS on admission. Multivariate regression analyses were used to determine independent associations of imaging and clinical parameters with NIHSS score increase or decrease in the first 24 h. Results: A total of 211 patients were included, of whom 38 (18.0%) had an END. END was significantly associated with occlusion of the internal carotid artery (odds ratio (OR), 4.25; 95% CI, 1.90–9.47) and the carotid T (OR, 6.34; 95% CI, 2.56–15.71), clot burden score (OR, 0.79; 95% CI, 0.68–0.92) and total ischemic volume (OR, 1.01; 95% CI, 1.00–1.01). In a comprehensive multivariate analysis model including periprocedural parameters and complications after EVT, carotid T occlusion remained independently associated with END, next to reperfusion status and intracranial hemorrhage. Favorable reperfusion status and small ischemic core volume were associated with clinical improvement after 24 h. Conclusions: The use of imaging parameters as a surrogate for early NIHSS progression in an acute LVO stroke after EVT reached limited performance with only carotid T occlusion as an independent predictor of END. Reperfusion status and early complications in terms of intracranial hemorrhage are critical factors that influence patient outcome in the acute stroke phase after EVT.
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20
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Campbell BCV, Lansberg MG, Broderick JP, Derdeyn CP, Khatri P, Sarraj A, Saver JL, Vagal A, Albers GW. Acute Stroke Imaging Research Roadmap IV: Imaging Selection and Outcomes in Acute Stroke Clinical Trials and Practice. Stroke 2021; 52:2723-2733. [PMID: 34233464 DOI: 10.1161/strokeaha.121.035132] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND PURPOSE The Stroke Treatment Academic Industry Roundtable (STAIR) sponsored an imaging session and workshop during the Stroke Treatment Academic Industry Roundtable XI via webinar on October 1 to 2, 2020, to develop consensus recommendations, particularly regarding optimal imaging at primary stroke centers. METHODS This forum brought together stroke neurologists, neuroradiologists, neuroimaging research scientists, members of the National Institute of Neurological Disorders and Stroke, industry representatives, and members of the US Food and Drug Administration to discuss imaging priorities in the light of developments in reperfusion therapies, particularly in an extended time window, and reinvigorated interest in brain cytoprotection trials. RESULTS The imaging session summarized and compared the imaging components of recent acute stroke trials and debated the optimal imaging strategy at primary stroke centers. The imaging workshop developed consensus recommendations for optimizing the acquisition, analysis, and interpretation of computed tomography and magnetic resonance acute stroke imaging, and also recommendations on imaging strategies for primary stroke centers. CONCLUSIONS Recent positive acute stroke clinical trials have extended the treatment window for reperfusion therapies using imaging selection. Achieving rapid and high-quality stroke imaging is therefore critical at both primary and comprehensive stroke centers. Recommendations for enhancing stroke imaging research are provided.
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Affiliation(s)
- Bruce C V Campbell
- Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital (B.C.V.C.), University of Melbourne, Parkville, Victoria, Australia.,Florey Institute of Neuroscience and Mental Health (B.C.V.C.), University of Melbourne, Parkville, Victoria, Australia
| | - Maarten G Lansberg
- Department of Neurology & Stanford Stroke Center, Stanford University School of Medicine, CA (M.G.L., G.W.A.)
| | | | - Colin P Derdeyn
- Department of Radiology, Iowa Institute of Biomedical Imaging, University of Iowa Hospitals and Clinics (C.P.D.)
| | - Pooja Khatri
- Department of Neurology (J.P.B., P.K.), University of Cincinnati, OH
| | - Amrou Sarraj
- UT McGovern Medical School, Department of Neurology, Houston (A.S.)
| | - Jeffrey L Saver
- Department of Neurology and Comprehensive Stroke Center, David Geffen School of Medicine, University of California Los Angeles (J.L.S.)
| | - Achala Vagal
- Department of Radiology (A.V.), University of Cincinnati, OH
| | - Gregory W Albers
- Department of Neurology & Stanford Stroke Center, Stanford University School of Medicine, CA (M.G.L., G.W.A.)
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21
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Divel SE, Christensen S, Segars WP, Lansberg MG, Pelc NJ. A dynamic simulation framework for CT perfusion in stroke assessment built from first principles. Med Phys 2021; 48:3500-3510. [PMID: 33877693 DOI: 10.1002/mp.14887] [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: 06/29/2020] [Revised: 01/24/2021] [Accepted: 04/02/2021] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Physicians utilize cerebral perfusion maps (e.g., cerebral blood flow, cerebral blood volume, transit time) to prescribe the plan of care for stroke patients. Variability in scanning techniques and post-processing software can result in differences between these perfusion maps. To determine which techniques are acceptable for clinical care, it is important to validate the accuracy and reproducibility of the perfusion maps. Validation using clinical data is challenging due to the lack of a gold standard to assess cerebral perfusion and the impracticality of scanning patients multiple times with different scanning techniques. In contrast, simulated data from a realistic digital phantom of the cerebral perfusion in acute stroke patients would enable studies to optimize and validate the scanning and post-processing techniques. METHODS We describe a complete framework to simulate CT perfusion studies for stroke assessment. We begin by expanding the XCAT brain phantom to enable spatially varying contrast agent dynamics and incorporate a realistic model of the dynamics in the cerebral vasculature derived from first principles. A dynamic CT simulator utilizes the time-concentration curves to define the contrast agent concentration in the object at each time point and generates CT perfusion images compatible with commercially available post-processing software. We also generate ground truth perfusion maps to which the maps generated by post-processing software can be compared. RESULTS We demonstrate a dynamic CT perfusion study of a simulated patient with an ischemic stroke and the resulting perfusion maps generated by post-processing software. We include a visual comparison between the computer-generated perfusion maps and the ground truth perfusion maps. The framework is highly tunable; users can modify the perfusion properties (e.g., occlusion location, CBF, CBV, and MTT), scanner specifications (e.g., focal spot size and detector configuration), scanning protocol (e.g., kVp and mAs), and reconstruction parameters (e.g., slice thickness and reconstruction filter). CONCLUSIONS This framework provides realistic test data with the underlying ground truth that enables a robust assessment of CT perfusion techniques and post-processing methods for stroke assessment.
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Affiliation(s)
- Sarah E Divel
- Departments of Electrical Engineering and Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Soren Christensen
- Stanford Stroke Center, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - William P Segars
- Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology and Biomedical Engineering, Medical Physics Graduate Program, Duke University, Durham, NC, 27705, USA
| | - Maarten G Lansberg
- Department of Neurology and Neurological Sciences and the Stanford Stroke Center, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Norbert J Pelc
- Departments of Bioengineering and Radiology, Stanford University, Stanford, CA, 94305, USA
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22
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Fabritius MP, Tiedt S, Puhr-Westerheide D, Grosu S, Maurus S, Schwarze V, Rübenthaler J, Stueckelschweiger L, Ricke J, Liebig T, Kellert L, Feil K, Dimitriadis K, Kunz WG, Reidler P. Computed Tomography Perfusion Deficit Volumes Predict Functional Outcome in Patients With Basilar Artery Occlusion. Stroke 2021; 52:2016-2023. [PMID: 33947212 DOI: 10.1161/strokeaha.120.032924] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Matthias P Fabritius
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Steffen Tiedt
- Institute for Stroke and Dementia Research (S.T., K.D.), University Hospital, LMU Munich, Germany
| | - Daniel Puhr-Westerheide
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Sergio Grosu
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Stefan Maurus
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Vincent Schwarze
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Johannes Rübenthaler
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Lena Stueckelschweiger
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Jens Ricke
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Thomas Liebig
- Department of Neuroradiology (T.L.), University Hospital, LMU Munich, Germany
| | - Lars Kellert
- Department of Neurology (L.K., K.F., K.D.), University Hospital, LMU Munich, Germany
| | - Katharina Feil
- Department of Neurology (L.K., K.F., K.D.), University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (K.F.), University Hospital, LMU Munich, Germany
| | - Konstantinos Dimitriadis
- Institute for Stroke and Dementia Research (S.T., K.D.), University Hospital, LMU Munich, Germany.,Department of Neurology (L.K., K.F., K.D.), University Hospital, LMU Munich, Germany
| | - Wolfgang G Kunz
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
| | - Paul Reidler
- Department of Radiology (M.P.F., D.P.-W., S.G., S.M., V.S., J.R., L.S., J.R., W.G.K., P.R.), University Hospital, LMU Munich, Germany
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23
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Frey D, Livne M, Leppin H, Akay EM, Aydin OU, Behland J, Sobesky J, Vajkoczy P, Madai VI. A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease. Biomed Eng Online 2021; 20:44. [PMID: 33933080 PMCID: PMC8088619 DOI: 10.1186/s12938-021-00880-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 04/20/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available. RESULTS We present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging. CONCLUSIONS The presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete.
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Affiliation(s)
- Dietmar Frey
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany.
- Department of Neurosurgery, Charité University Medicine Berlin, Berlin, Germany.
| | - Michelle Livne
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
| | - Heiko Leppin
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
| | - Ela M Akay
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
- Department of Neurosurgery, Charité University Medicine Berlin, Berlin, Germany
| | - Orhun U Aydin
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
- Department of Neurosurgery, Charité University Medicine Berlin, Berlin, Germany
| | - Jonas Behland
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
- Department of Neurosurgery, Charité University Medicine Berlin, Berlin, Germany
| | - Jan Sobesky
- Johanna Etienne Hospital Neuss, Berlin, Germany
- Centre for Stroke Research Berlin, Charité University Medicine Berlin, Berlin, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité University Medicine Berlin, Berlin, Germany
| | - Vince I Madai
- Charite Lab for Artificial Intelligence in Medicine, Department of Neurosurgery, Charité University Medicine Berlin, Chariteplatz 1, 10115, Berlin, Germany
- School of Computing and Digital Technology, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham, UK
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24
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Pico F, Lapergue B, Ferrigno M, Rosso C, Meseguer E, Chadenat ML, Bourdain F, Obadia M, Hirel C, Duong DL, Deltour S, Aegerter P, Labreuche J, Cattenoy A, Smadja D, Hosseini H, Guillon B, Wolff V, Samson Y, Cordonnier C, Amarenco P. Effect of In-Hospital Remote Ischemic Perconditioning on Brain Infarction Growth and Clinical Outcomes in Patients With Acute Ischemic Stroke: The RESCUE BRAIN Randomized Clinical Trial. JAMA Neurol 2021; 77:725-734. [PMID: 32227157 DOI: 10.1001/jamaneurol.2020.0326] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Importance Treatment with remote ischemic perconditioning has been reported to reduce brain infarction volume in animal models of stroke. Whether this neuroprotective effect was observed in patients with acute ischemic stroke remains unknown. Objective To determine whether treatment with remote ischemic perconditioning administered to the leg of patients with acute ischemic stroke can reduce brain infarction volume growth. Design, Setting, and Participants This proof-of-concept multicenter prospective randomized open-label with blinded end point clinical trial was performed from January 12, 2015, to May 2, 2018. Patients were recruited from 11 stroke centers in France. Of the 188 patients who received magnetic resonance imaging within 6 hours of symptom onset and were confirmed to have carotid ischemic stroke, 93 were randomized to receive treatment with lower-limb remote ischemic perconditioning in addition to standard care (the intervention group), and 95 were randomized to receive standard care alone (the control group). Interventions Randomization on a 1:1 ratio to receive treatment with remote ischemic perconditioning (4 cycles of 5-minute inflations and 5-minute deflations to the thigh to 110 mm Hg above systolic blood pressure) in addition to standard care or standard care alone. Main Outcomes and Measures The change in brain infarction volume growth between baseline and 24 hours, measured by a diffusion-weighted sequence of magnetic resonance imaging scans of the brain. Results A total of 188 patients (mean [SD] age, 67.2 [15.7] years; 98 men [52.1%]) were included in this intention-to-treat analysis. At hospital admission, the median National Institutes of Health Stroke Scale score was 10 (interquartile range [IQR], 6-16) and the median brain infarction volume was 11.4 cm3 (IQR, 3.6-35.8 cm3); 164 patients (87.2%) received intravenous thrombolysis, and 64 patients (34.0%) underwent mechanical thrombectomy. The median increase in brain infarction growth was 0.30 cm3 (IQR, 0.11-0.48 cm3) in the intervention group and 0.37 cm3 (IQR, 0.19-0.55 cm3) in the control group (mean between-group difference on loge-transformed change, -0.07; 95% CI, -0.33 to 0.18; P = .57). An excellent outcome (defined as a score of 0-1 on the 90-day modified Rankin Scale or a score equal to the prestroke modified Rankin Scale score) was observed in 46 of 90 patients (51.1%) in the intervention group and 37 of 91 patients (40.7%) in the control group (P = .12). No significant differences in 90-day mortality were observed between the intervention and control groups (14 of 90 patients; Kaplan-Meier estimate, 15.8% vs 10 of 91 patients; Kaplan-Meier estimate, 10.4%, respectively; P = .45) or with symptomatic intracerebral hemorrhage (4 of 88 patients [4.5%] in both groups; P = .97). Conclusions and Relevance In this study, treatment with remote ischemic perconditioning, during or after reperfusion therapies, had no significant effect on brain infarction volume growth at 24 hours after symptom onset. Trial Registration ClinicalTrials.gov Identifier: NCT02189928.
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Affiliation(s)
- Fernando Pico
- Department of Neurology and Stroke Center, Versailles Mignot Hospital, Versailles, France.,University of Versailles Saint-Quentin-en-Yvelines and Paris-Saclay University, Saint-Aubin, France.,Laboratoire de Recherche Vasculaire Translationnelle, Inserm U1148, Paris, France
| | - Bertrand Lapergue
- University of Versailles Saint-Quentin-en-Yvelines and Paris-Saclay University, Saint-Aubin, France.,Neurology and Stroke Center, Hôpital Foch, Suresnes, France
| | - Marc Ferrigno
- Department of Degenerative and Vascular Cognitive Disorders, Inserm U1171, Université de Lille, Lille, France.,Department of Neurology, Centre Hospitalier Universitaire de Lille, Lille, France
| | - Charlotte Rosso
- Assistance Publique-Hopitaux de Paris, Service des Urgences Cerebro-Vasculaires, Hôpital Pitié-Salpêtrière, Paris, France.,Centre National de la Recherche Scientifique, Inserm U1127, Unite Mixte de Recherche 7225, Institut du Cerveau et de la Moelle Epiniere, Sorbonne Universite, Paris, France
| | - Elena Meseguer
- Assistance Publique-Hôpitaux de Paris, Department of Neurology and Stroke Center, Bichat University Hospital, Universite Paris Diderot, Sorbonne Cite, Paris, France
| | - Marie-Laure Chadenat
- Department of Neurology and Stroke Center, Versailles Mignot Hospital, Versailles, France
| | | | - Michael Obadia
- Neurology and Stroke Center, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Catherine Hirel
- Department of Neurology and Stroke Center, Versailles Mignot Hospital, Versailles, France.,University of Versailles Saint-Quentin-en-Yvelines and Paris-Saclay University, Saint-Aubin, France
| | - Duc Long Duong
- Department of Neurology and Stroke Center, Versailles Mignot Hospital, Versailles, France
| | - Sandrine Deltour
- Assistance Publique-Hopitaux de Paris, Service des Urgences Cerebro-Vasculaires, Hôpital Pitié-Salpêtrière, Paris, France
| | - Philippe Aegerter
- Assistance Publique-Hôpitaux de Paris, Vieillissement et Maladies Chroniques, IndianaSERM, Unité Mixte de Recherche 1168, Universite de Versailles Saint-Quentin-en-Yvelines, Versailles, France.,Department of Biostatistics, Université de Lille, Lille, France
| | - Julien Labreuche
- Unité de Recherche EA 2694-Sante Publique: Epidemiologie et Qualite des Soins, Centre Hospitalier Universitaire de Lille, Lille, France
| | - Amina Cattenoy
- Délégation à la Recherche Clinique, Versailles Mignot Hospital, Versailles, France
| | - Didier Smadja
- Stroke Unit, Centre Hospitalier Sud Francilien, Corbeil-Essonnes, France
| | - Hassan Hosseini
- Assistance Publique-Hopitaux de Paris, Stroke Center, Henri Mondor Hospital, Université Paris-Est Créteil, Creteil, France
| | - Benoit Guillon
- Department of Neurology, University Hospital of Nantes, Nantes, France
| | - Valérie Wolff
- Stroke Unit, Strasbourg University Hospital, Strasbourg, France
| | - Yves Samson
- Assistance Publique-Hopitaux de Paris, Service des Urgences Cerebro-Vasculaires, Hôpital Pitié-Salpêtrière, Paris, France
| | - Charlotte Cordonnier
- Department of Degenerative and Vascular Cognitive Disorders, Inserm U1171, Université de Lille, Lille, France.,Department of Neurology, Centre Hospitalier Universitaire de Lille, Lille, France
| | - Pierre Amarenco
- Laboratoire de Recherche Vasculaire Translationnelle, Inserm U1148, Paris, France.,Assistance Publique-Hôpitaux de Paris, Department of Neurology and Stroke Center, Bichat University Hospital, Universite Paris Diderot, Sorbonne Cite, Paris, France
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25
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Maslias E, Nannoni S, Ricciardi F, Bartolini B, Strambo D, Puccinelli F, Hajdu SD, Eskandari A, Saliou G, Michel P. Procedural Complications During Early Versus Late Endovascular Treatment in Acute Stroke: Frequency and Clinical Impact. Stroke 2021; 52:1079-1082. [PMID: 33467881 DOI: 10.1161/strokeaha.120.031349] [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] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Endovascular treatment (EVT) in acute ischemic stroke is effective in the late time window in selected patients. However, the frequency and clinical impact of procedural complications in the early versus late time window has received little attention. METHODS We retrospectively studied all acute ischemic strokes from 2015 to 2019 receiving EVT in the Acute Stroke Registry and Analysis of Lausanne. We compared the procedural EVT complications in the early (<6 hours) versus late (6-24 hours) window and correlated them with short-term clinical outcome. RESULTS Among 695 acute ischemic strokes receiving EVT (of which 202 were in the late window), 113 (16.3%) had at least one procedural complication. The frequency of each single, and for overall procedural complications was similar for early versus late EVT (16.2% versus 16.3%, Padj=0.90). Procedural complications lead to a significantly less favorable short-term outcome, reflected by the absence of National Institutes of Health Stroke Scale improvement in late EVT (delta-National Institutes of Health Stroke Scale-24 hours, -2.5 versus 2, Padj=0.01). CONCLUSIONS In this retrospective analysis of consecutive EVT, the frequency of procedural complications was similar for early and late EVT patients but very short-term outcome seemed less favorable in late EVT patients with complications.
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Affiliation(s)
- Errikos Maslias
- Stroke Centre, Neurology Service, Department of Clinical Neurosciences (E.M., S.N., D.S., A.E., P.M.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Stefania Nannoni
- Stroke Centre, Neurology Service, Department of Clinical Neurosciences (E.M., S.N., D.S., A.E., P.M.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Federico Ricciardi
- Department of Statistical Science, University College London, United Kingdom (F.R.)
| | - Bruno Bartolini
- Service of Diagnostic and Interventional Radiology, Interventional Neuroradiological Unit (B.B. F.P., S.D.H., G.S.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Davide Strambo
- Stroke Centre, Neurology Service, Department of Clinical Neurosciences (E.M., S.N., D.S., A.E., P.M.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Francesco Puccinelli
- Service of Diagnostic and Interventional Radiology, Interventional Neuroradiological Unit (B.B. F.P., S.D.H., G.S.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Steven David Hajdu
- Service of Diagnostic and Interventional Radiology, Interventional Neuroradiological Unit (B.B. F.P., S.D.H., G.S.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Ashraf Eskandari
- Stroke Centre, Neurology Service, Department of Clinical Neurosciences (E.M., S.N., D.S., A.E., P.M.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Guillaume Saliou
- Service of Diagnostic and Interventional Radiology, Interventional Neuroradiological Unit (B.B. F.P., S.D.H., G.S.), Lausanne University Hospital and University of Lausanne, Switzerland
| | - Patrik Michel
- Stroke Centre, Neurology Service, Department of Clinical Neurosciences (E.M., S.N., D.S., A.E., P.M.), Lausanne University Hospital and University of Lausanne, Switzerland
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26
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Chen C, Parsons MW, Levi CR, Spratt NJ, Lin L, Kleinig T, Butcher K, Cheng X, Dong Q, O'Brien B, Avivi RI, Krause M, Sylaja PN, Choi P, Bhuta S, Yin C, Yang J, Wang P, Qiu W, Bivard A. What Is the "Optimal" Target Mismatch Criteria for Acute Ischemic Stroke? Front Neurol 2021; 11:590766. [PMID: 33584495 PMCID: PMC7874100 DOI: 10.3389/fneur.2020.590766] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 12/11/2020] [Indexed: 11/27/2022] Open
Abstract
We aimed to compare Perfusion Imaging Mismatch (PIM) and Clinical Core Mismatch (CCM) criteria in ischemic stroke patients to identify the effect of these criteria on selected patient population characteristics and clinical outcomes. Patients from the INternational Stroke Perfusion Imaging REgistry (INSPIRE) who received reperfusion therapy, had pre-treatment multimodal CT, 24-h imaging, and 3 month outcomes were analyzed. Patients were divided into 3 cohorts: endovascular thrombectomy (EVT), intravenous thrombolysis alone with large vessel occlusion (IVT-LVO), and intravenous thrombolysis alone without LVO (IVT-nonLVO). Patients were classified using 6 separate mismatch criteria: PIM-using 3 different measures to define the perfusion deficit (Delay Time, Tmax, or Mean Transit Time); or CCM-mismatch between age-adjusted National Institutes of Health Stroke Scale and CT Perfusion core, defined as relative cerebral blood flow <30% within the perfusion deficit defined in three ways (as above). We assessed the eligibility rate for each mismatch criterion and its ability to identify patients likely to respond to treatment. There were 994 patients eligible for this study. PIM with delay time (PIM-DT) had the highest inclusion rate for both EVT (82.7%) and IVT-LVO (79.5%) cohorts. In PIM positive patients who received EVT, recanalization was strongly associated with achieving an excellent outcome at 90-days (e.g., PIM-DT: mRS 0-1, adjusted OR 4.27, P = 0.005), whereas there was no such association between reperfusion and an excellent outcome with any of the CCM criteria (all p > 0.05). Notably, in IVT-LVO cohort, 58.2% of the PIM-DT positive patients achieved an excellent outcome compared with 31.0% in non-mismatch patients following successful recanalization (P = 0.006). Conclusion: PIM-DT was the optimal mismatch criterion in large vessel occlusion patients, combining a high eligibility rate with better clinical response to reperfusion. No mismatch criterion was useful to identify patients who are most likely response to reperfusion in non-large vessel occlusion patients.
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Affiliation(s)
- Chushuang Chen
- Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia
| | - Mark W Parsons
- Department of Neurology, Liverpool Hospital, University of New South Wales, Sydney, NSW, Australia
| | - Christopher R Levi
- Department of Neurology, John Hunter Hospital, University of Newcastle, Callaghan, NSW, Australia.,Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Neil J Spratt
- Department of Neurology, John Hunter Hospital, University of Newcastle, Callaghan, NSW, Australia.,Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Longting Lin
- Department of Neurology, Liverpool Hospital, University of New South Wales, Sydney, NSW, Australia
| | - Timothy Kleinig
- Department of Neurology, Royal Adelaide Hospital, Adelaide, SA, Australia
| | - Kenneth Butcher
- Prince of Wales Medical School, University of New South Wales, Sydney, NSW, Australia
| | - Xin Cheng
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Billy O'Brien
- Department of Neurology, Gosford Hospital, Gosford, NSW, Australia
| | - Richard I Avivi
- Division of Neuroradiology, Department of Medical Imaging, University of Toronto and Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Martin Krause
- Department of Neurology, Kolling Institute, Royal North Shore Hospital, University of Sydney, Sydney, NSW, Australia
| | - P N Sylaja
- Department of Neurology, Sri Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Philip Choi
- Department of Neurology, Box Hill Hospital, Melbourne, VIC, Australia
| | - Sandeep Bhuta
- Department of Medical Imaging, Gold Coast University Hospital, Southport, QLD, Australia
| | - Congguo Yin
- Department of Neurology, Hangzhou First Hospital, Zhejiang, China
| | - Jianhong Yang
- Department of Neurology, Ningbo First Hospital, Zhejiang, China
| | - Peng Wang
- Department of Neurology, Taizhou First People's Hospital, Zhejiang, China
| | - Weiwen Qiu
- Department of Neurology, Lishui People's Hospital, Zhejiang, China
| | - Andrew Bivard
- Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia
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27
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Dehkharghani S, Lansberg M, Venkatsubramanian C, Cereda C, Lima F, Coelho H, Rocha F, Qureshi A, Haerian H, Mont'Alverne F, Copeland K, Heit J. High-Performance Automated Anterior Circulation CT Angiographic Clot Detection in Acute Stroke: A Multireader Comparison. Radiology 2021; 298:665-670. [PMID: 33434110 DOI: 10.1148/radiol.2021202734] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Identification of large vessel occlusion (LVO) is critical to the management of acute ischemic stroke and prerequisite to endovascular therapy in recent trials. Increasing volumes and data complexity compel the development of fast, reliable, and automated tools for LVO detection to facilitate acute imaging triage. Purpose To investigate the performance of an anterior circulation LVO detection platform in a large mixed sample of individuals with and without LVO at cerebrovascular CT angiography (CTA). Materials and Methods In this retrospective analysis, CTA data from recent cerebrovascular trials (CRISP [ClinicalTrials.gov NCT01622517] and DASH) were enriched with local repositories from 11 worldwide sites to balance demographic and technical variables in LVO-positive and LVO-negative examinations. CTA findings were reviewed independently by two neuroradiologists from different institutions for intracranial internal carotid artery (ICA) or middle cerebral artery (MCA) M1 LVO; these observers were blinded to all clinical variables and outcomes. An automated analysis platform was developed and tested for prediction of LVO presence and location relative to reader consensus. Discordance between readers with respect to LVO presence or location was adjudicated by a blinded tertiary reader at a third institution. Sensitivity, specificity, and receiver operating characteristics were assessed by an independent statistician, and subgroup analyses were conducted. Prespecified performance thresholds were set at a lower bound of the 95% CI of sensitivity and specificity of 0.8 or greater at mean times to notification of less than 3.5 minutes. Results A total of 217 study participants (mean age, 64 years ± 16 [standard deviation]; 116 men; 109 with positive findings of LVO) were evaluated. Prespecified performance thresholds were exceeded (sensitivity, 105 of 109 [96%; 95% CI: 91, 99]; specificity, 106 of 108 [98%; 95% CI: 94, 100]). Sensitivity and specificity estimates across age, sex, location, and vendor subgroups exceeded 90%. The area under the receiver operating characteristic curve was 99% (95% CI: 97, 100). Mean processing and notification time was 3 minutes 18 seconds. Conclusion The results confirm the feasibility of fast automated high-performance detection of intracranial internal carotid artery and middle cerebral artery M1 occlusions. © RSNA, 2021 See also the editorial by Kloska in this issue.
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Affiliation(s)
- Seena Dehkharghani
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Maarten Lansberg
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Chitra Venkatsubramanian
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Carlo Cereda
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Fabricio Lima
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Henrique Coelho
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Felipe Rocha
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Abid Qureshi
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Hafez Haerian
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Francisco Mont'Alverne
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Karen Copeland
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Jeremy Heit
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
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Zhao C, Martin T, Shao X, Alger JR, Duddalwar V, Wang DJJ. Low Dose CT Perfusion With K-Space Weighted Image Average (KWIA). IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3879-3890. [PMID: 32746131 PMCID: PMC7704693 DOI: 10.1109/tmi.2020.3006461] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
CTP (Computed Tomography Perfusion) is widely used in clinical practice for the evaluation of cerebrovascular disorders. However, CTP involves high radiation dose (≥~200mGy) as the X-ray source remains continuously on during the passage of contrast media. The purpose of this study is to present a low dose CTP technique termed K-space Weighted Image Average (KWIA) using a novel projection view-shared averaging algorithm with reduced tube current. KWIA takes advantage of k-space signal property that the image contrast is primarily determined by the k-space center with low spatial frequencies and oversampled projections. KWIA divides each 2D Fourier transform (FT) or k-space CTP data into multiple rings. The outer rings are averaged with neighboring time frames to achieve adequate signal-to-noise ratio (SNR), while the center region of k-space remains unchanged to preserve high temporal resolution. Reduced dose sinogram data were simulated by adding Poisson distributed noise with zero mean on digital phantom and clinical CTP scans. A physical CTP phantom study was also performed with different X-ray tube currents. The sinogram data with simulated and real low doses were then reconstructed with KWIA, and compared with those reconstructed by standard filtered back projection (FBP) and simultaneous algebraic reconstruction with regularization of total variation (SART-TV). Evaluation of image quality and perfusion metrics using parameters including SNR, CNR (contrast-to-noise ratio), AUC (area-under-the-curve), and CBF (cerebral blood flow) demonstrated that KWIA is able to preserve the image quality, spatial and temporal resolution, as well as the accuracy of perfusion quantification of CTP scans with considerable (50-75%) dose-savings.
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Brauner R, Auriel E, Raphaeli G. Contact aspiration compared to stent retriever as sole intention to treat large-vessel occlusion in ischemic stroke. INTERDISCIPLINARY NEUROSURGERY 2020. [DOI: 10.1016/j.inat.2020.100835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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McDougall CC, Chan L, Sachan S, Guo J, Sah RG, Menon BK, Demchuk AM, Hill MD, Forkert ND, d'Esterre CD, Barber PA. Dynamic CTA-Derived Perfusion Maps Predict Final Infarct Volume: The Simple Perfusion Reconstruction Algorithm. AJNR Am J Neuroradiol 2020; 41:2034-2040. [PMID: 33004342 DOI: 10.3174/ajnr.a6783] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 07/07/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Infarct core volume measurement using CTP (CT perfusion) is a mainstay paradigm for stroke treatment decision-making. Yet, there are several downfalls with cine CTP technology that can be overcome by adopting the simple perfusion reconstruction algorithm (SPIRAL) derived from multiphase CTA. We compare SPIRAL with CTP parameters for the prediction of 24-hour infarction. MATERIALS AND METHODS Seventy-two patients had admission NCCT, multiphase CTA, CTP, and 24-hour DWI. All patients had successful/quality reperfusion. Patient-level and cohort-level receiver operator characteristic curves were generated to determine accuracy. A 10-fold cross-validation was performed on the cohort-level data. Infarct core volume was compared for SPIRAL, CTP-time-to-maximum, and final DWI by Bland-Altman analysis. RESULTS When we compared the accuracy in patients with early and late reperfusion for cortical GM and WM, there was no significant difference at the patient level (0.83 versus 0.84, respectively), cohort level (0.82 versus 0.81, respectively), or the cross-validation (0.77 versus 0.74, respectively). In the patient-level receiver operating characteristic analysis, the SPIRAL map had a slightly higher, though nonsignificant (P < .05), average receiver operating characteristic area under the curve (cortical GM/WM, r = 0.82; basal ganglia = 0.79, respectively) than both the CTP-time-to-maximum (cortical GM/WM = 0.82; basal ganglia = 0.78, respectively) and CTP-CBF (cortical GM/WM = 0.74; basal ganglia = 0.78, respectively) parameter maps. The same relationship was observed at the cohort level. The Bland-Altman plot limits of agreement for SPIRAL and time-to-maximum infarct volume were similar compared with 24-hour DWI. CONCLUSIONS We have shown that perfusion maps generated from a temporally sampled helical CTA are an accurate surrogate for infarct core.
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Affiliation(s)
- C C McDougall
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Department of Radiology (C.C.M., B.K.M., N.D.F., C.D.d.E., P.A.B.).,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - L Chan
- Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.)
| | - S Sachan
- Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.)
| | - J Guo
- Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.)
| | - R G Sah
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - B K Menon
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Department of Radiology (C.C.M., B.K.M., N.D.F., C.D.d.E., P.A.B.).,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - A M Demchuk
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - M D Hill
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - N D Forkert
- Department of Radiology (C.C.M., B.K.M., N.D.F., C.D.d.E., P.A.B.).,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Alberta Children's Hospital Research Institute (N.D.F.), University of Calgary, Calgary, Alberta, Canada
| | - C D d'Esterre
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program.,Department of Radiology (C.C.M., B.K.M., N.D.F., C.D.d.E., P.A.B.).,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Department of Clinical Neurosciences (C.C.M., L.C., S.S., J.G., R.G.S., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - P A Barber
- From the Department of Clinical Neurosciences (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d., P.A.B.), Calgary Stroke Program .,Department of Radiology (C.C.M., B.K.M., N.D.F., C.D.d.E., P.A.B.).,Hotchkiss Brain Institute (C.C.M., B.K.M., A.M.D., M.D.H., N.D.F., C.C.d.E., P.A.B.).,Seaman Family Centre (C.C.M., R.G.S., B.K.M., A.M.D., M.D.H., C.D.d.E., P.A.B.), Foothills Medical Centre, Calgary, Alberta, Canada
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Suh CH, Jung SC, Kim B, Cho SJ, Woo DC, Oh WY, Lee JG, Kim KW. Neuroimaging in Randomized, Multi-Center Clinical Trials of Endovascular Treatment for Acute Ischemic Stroke: A Systematic Review. Korean J Radiol 2020; 21:42-57. [PMID: 31920028 PMCID: PMC6960311 DOI: 10.3348/kjr.2019.0354] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 10/01/2019] [Indexed: 01/01/2023] Open
Abstract
Appropriate use and analysis of neuroimaging techniques is an inevitable aspect of clinical trials for patients with acute ischemic stroke. Neuroimaging examinations were recently used to define the core eligibility criteria and outcomes in acute ischemic stroke research. Recent clinical trials for endovascular treatment in acute ischemic stroke have also demonstrated the efficacy or safety of endovascular treatment using various imaging modalities as well as clinical indices. Furthermore, independent imaging reviews and imaging core laboratory assessments are essential to manage and analyze imaging data in order to enhance the reliability of the outcomes. Therefore, we systematically reviewed the use of neuroimaging in recent randomized clinical trials for endovascular treatment of acute ischemic stroke in order to provide a thorough summary, which would serve as a resource guiding the use of appropriate imaging protocols and analyses in future clinical trials for acute ischemic stroke. This review will help researchers select appropriate imaging biomarkers among the various imaging protocols available and apply the selected type of imaging examination for each study in accordance with the academic purpose.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
| | - Byungjun Kim
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Se Jin Cho
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Dong Cheol Woo
- Bioimaging Center, Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea
| | - Woo Yong Oh
- Clinical Research Division, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju, Korea
| | - Jong Gu Lee
- Clinical Research Division, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju, Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.,Asan Image Metrics, Clinical Trial Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea
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Siegler JE, Messé SR, Sucharew H, Kasner SE, Mehta T, Arora N, Starosciak AK, De Los Rios La Rosa F, Barnhill NR, Mistry AM, Patel K, Assad S, Tarboosh A, Dakay K, Salwi S, Wagner J, Bennett A, Jagadeesan BD, Streib C, Weber SA, Chitale R, Volpi JJ, Mayer SA, Yaghi S, Jayaraman M, Khatri P, Mistry EA. Thrombectomy in DAWN- and DEFUSE-3-Ineligible Patients: A Subgroup Analysis From the BEST Prospective Cohort Study. Neurosurgery 2020; 86:E156-E163. [PMID: 31758197 DOI: 10.1093/neuros/nyz485] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 08/28/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Because of the overwhelming benefit of thrombectomy for highly selected trial patients with large vessel occlusion (LVO), some trial-ineligible patients are being treated in practice. OBJECTIVE To determine the safety and efficacy of thrombectomy in DAWN/DEFUSE-3-ineligible patients. METHODS Using a multicenter prospective observational study of consecutive patients with anterior circulation LVO who underwent late thrombectomy, we compared symptomatic intracerebral hemorrhage (sICH) and good outcome (90-d mRS 0-2) among DAWN/DEFUSE-3-ineligible patients to trial-eligible patients and to untreated DAWN/DEFUSE-3 controls. RESULTS Ninety-eight patients had perfusion imaging and underwent thrombectomy >6 h; 46 (47%) were trial ineligible (41% M2 occlusions, 39% mild deficits, 28% ASPECTS <6). In multivariable regression, the odds of a good outcome (aOR 0.76, 95% CI 0.49-1.19) and sICH (aOR 3.33, 95% CI 0.42-26.12) were not different among trial-ineligible vs eligible patients. Patients with mild deficits were more likely to achieve a good outcome (aOR 3.62, 95% CI 1.48-8.86) and less sICH (0% vs 10%, P = .16), whereas patients with ASPECTS <6 had poorer outcomes (aOR 0.14, 95% CI 0.05-0.44) and more sICH (aOR 24, 95% CI 5.7-103). Compared to untreated DAWN/DEFUSE-3 controls, trial-ineligible patients had more sICH (13%BEST vs 3%DAWN [P = .02] vs 4%DEFUSE [P = .05]), but were more likely to achieve a good outcome at 90 d (36%BEST vs 13%DAWN [P < .01] vs 17%DEFUSE [P = .01]). CONCLUSION Thrombectomy is used in practice for some patients ineligible for the DAWN/DEFUSE-3 trials with potentially favorable outcomes. Additional trials are needed to confirm the safety and efficacy of thrombectomy in broader populations, such as large core infarction and M2 occlusions.
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Affiliation(s)
- James E Siegler
- Department of Neurology, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Steven R Messé
- Department of Neurology, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Heidi Sucharew
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.,Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio
| | - Scott E Kasner
- Department of Neurology, Hospital of the University of Pennsylvania, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Tapan Mehta
- Department of Neurology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurosurgery, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Radiology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurology, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Neurosurgery, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Radiology, Hennepin County Medical Center, Minneapolis, Minnesota
| | - Niraj Arora
- Department of Neurology, Jackson Memorial Hospital, Miami, Florida
| | | | | | - Natasha R Barnhill
- Department of Neurology, Oregon Health and Science University, Portland, Oregon
| | - Akshitkumar M Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kishan Patel
- Department of Neurology, Houston Methodist Medical Center, Houston, Texas
| | - Salman Assad
- Department of Neurology, Henry Ford Health System, Detroit, Michigan
| | - Amjad Tarboosh
- Department of Neurology, Henry Ford Health System, Detroit, Michigan
| | - Katarina Dakay
- Department of Neurology, Brown University, Providence, Rhode Island
| | - Sanjana Salwi
- School of Medicine, Vanderbilt University, Nashville, Tennessee
| | - Jeff Wagner
- Department of Neurology, Blue Sky Neurology, Englewood, Colorado
| | - Alicia Bennett
- Department of Neurology, Blue Sky Neurology, Englewood, Colorado
| | - Bharathi D Jagadeesan
- Department of Neurology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurosurgery, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Radiology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurology, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Neurosurgery, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Radiology, Hennepin County Medical Center, Minneapolis, Minnesota
| | - Christopher Streib
- Department of Neurology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurosurgery, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Radiology, University of Minnesota Medical Center, School of Medicine, University of Minnesota, Minneapolis, Minnesota.,Department of Neurology, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Neurosurgery, Hennepin County Medical Center, Minneapolis, Minnesota.,Department of Radiology, Hennepin County Medical Center, Minneapolis, Minnesota
| | - Stewart A Weber
- Department of Neurology, Oregon Health and Science University, Portland, Oregon
| | - Rohan Chitale
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - John J Volpi
- Department of Neurology, Houston Methodist Medical Center, Houston, Texas
| | - Stephan A Mayer
- Department of Neurology, Henry Ford Health System, Detroit, Michigan
| | - Shadi Yaghi
- Department of Neurology, Brown University, Providence, Rhode Island
| | | | - Pooja Khatri
- Department of Neurology, University of Cincinnati, Cincinnati, Ohio
| | - Eva A Mistry
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
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Dehkharghani S, Yaghi S, Bowen MT, Pisani L, Scher E, Haussen DC, Nogueira RG. Mild fever as a catalyst for consumption of the ischaemic penumbra despite endovascular reperfusion. Brain Commun 2020; 2:fcaa116. [PMID: 33033801 PMCID: PMC7532660 DOI: 10.1093/braincomms/fcaa116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 05/18/2020] [Accepted: 06/23/2020] [Indexed: 11/26/2022] Open
Abstract
Cerebrovascular ischaemia is potentiated by hyperthermia, and even mild temperature elevation has proved detrimental to ischaemic brain. Infarction progression following endovascular reperfusion relates to multiple patient-specific and procedural variables; however, the potential influence of mild systemic temperature fluctuations is not fully understood. This study aims to assess the relationship between systemic temperatures in the early aftermath of acute ischaemic stroke and the loss of at-risk penumbral tissues, hypothesizing consumption of the ischaemic penumbra as a function of systemic temperatures, irrespective of reperfusion status. A cross-sectional, retrospective evaluation of a single-institution, prospectively collected endovascular therapy registry was conducted. Patients with anterior circulation, large vessel occlusion acute ischaemic stroke who underwent initial CT perfusion, and in whom at least four-hourly systemic temperatures were recorded beginning from presentation and until the time of final imaging outcome were included. Initial CT perfusion core and penumbra volumes and final MRI infarction volumes were computed. Systemic temperature indices including temperature maxima were recorded, and pre-defined temperature thresholds varying between 37°C and 38°C were examined in unadjusted and adjusted regression models which included glucose, collateral status, reperfusion status, CT perfusion-to-reperfusion delay, general anaesthesia and antipyretic exposure. The primary outcome was the relative consumption of the penumbra, reflecting normalized growth of the at-risk tissue volume ≥10%. The final study population comprised 126 acute ischaemic stroke subjects (mean 63 ± 14.5 years, 63% women). The primary outcome of penumbra consumption ≥10% occurred in 51 (40.1%) subjects. No significant differences in baseline characteristics were present between groups, with the exception of presentation glucose (118 ± 26.6 without versus 143.1 ± 61.6 with penumbra consumption, P = 0.009). Significant differences in the likelihood of penumbra consumption relating to systemic temperature maxima were observed [37°C (interquartile range 36.5 − 37.5°C) without versus 37.5°C (interquartile range 36.8 − 38.2°C) with penumbra consumption, P = 0.001]. An increased likelihood of penumbra consumption was observed for temperature maxima in unadjusted (odds ratio 3.57, 95% confidence interval 1.65 − 7.75; P = 0.001) and adjusted (odds ratio 3.06, 95% confidence interval 1.33 − 7.06; P = 0.009) regression models. Significant differences in median penumbra consumption were present at a pre-defined temperature maxima threshold of 37.5°C [4.8 ml (interquartile range 0 − 11.5 ml) versus 21.1 ml (0 − 44.7 ml) for subjects not reaching or reaching the threshold, respectively, P = 0.007]. Mild fever may promote loss of the ischaemic penumbra irrespective of reperfusion, potentially influencing successful salvage of at-risk tissue volumes following acute ischaemic stroke.
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Affiliation(s)
- Seena Dehkharghani
- Department of Radiology, New York University Langone Health, New York, NY, USA
| | - Shadi Yaghi
- Department of Neurology, New York University Langone Health, New York, NY, USA
| | - Meredith T Bowen
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Leonardo Pisani
- Department of Neurology, Emory University Hospital, Atlanta, GA, USA
| | - Erica Scher
- Department of Neurology, New York University Langone Health, New York, NY, USA
| | - Diogo C Haussen
- Department of Neurology, Emory University Hospital, Atlanta, GA, USA.,Department of Neurology, Marcus Stroke and Neuroscience Center, Grady Memorial Hospital, Atlanta, GA 30303, USA
| | - Raul G Nogueira
- Department of Neurology, Emory University Hospital, Atlanta, GA, USA.,Department of Neurology, Marcus Stroke and Neuroscience Center, Grady Memorial Hospital, Atlanta, GA 30303, USA
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White PM, Gregson B, Cora EA, Dixit A, Subramanian G, Joshi Y, Simister R, Lakey R, Maiter A, Ford GA. Evaluation of stroke thrombectomy including patients where IV thrombolysis is contraindicated or has failed: a randomized trial of two novel thrombectomy devices. J Neurointerv Surg 2020; 13:311-318. [PMID: 32665431 DOI: 10.1136/neurintsurg-2020-016038] [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: 03/20/2020] [Revised: 06/16/2020] [Accepted: 06/17/2020] [Indexed: 11/04/2022]
Abstract
BACKGROUND Study was a PROBE design phase II randomized controlled trial (RCT). We assessed trial feasibility and technical efficacy and safety of two novel thrombectomy devices - ERIC (a retriever device) and SOFIA (a distal access catheter) - used alone or in combination depending on operator preference. METHODS Four UK neuroscience centers enrolled adults with proximal large artery occlusion (LAO) stroke on imaging where arterial puncture was achievable within 5.5 hours (8.5 hours for posterior circulation) of symptom onset; National Institutes of Health Stroke Scale (NIHSS) ≥6 with limited ischemic change on CT imaging. Randomization was 2:1 into intervention arm (ERIC and/or SOFIA). Patients and core lab were blinded to allocation. Primary outcome was independent core lab adjudication of reperfusion (modified Thrombolysis in Cerebral Infarction (mTICI) scale). Secondary outcomes were modified Rankin score (mRS) at 90 and 365 days (independence and shift analysis), 30-day mortality, symptomatic intracranial hemorrhage (sICH), procedural complications and NIHSS change. RESULTS Sixty-six patients were enrolled. TICI 2B/3 reperfusion was achieved in 72% in intervention compared with 90% in control arm on intention to treat (ITT) analysis (P=0.2) and 78% compared with 86% on per protocol analysis (P=0.7). Functional independence at 90 days was 40% (intervention) compared with 43% (control) on ITT analysis (P=1.0). sICH rates were low at 0% and 5%, respectively (P=0.3). The 30-day mortality was 9% intervention compared with 14% control (P=0.7). CONCLUSIONS Study indicated feasibility of a phase II RCT trial approach for assessing new thrombectomy devices. In a broad LAO stroke population ERIC and SOFIA were not statistically different from control devices. Larger trials are needed.
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Affiliation(s)
- Philip M White
- Translational and Clinical Research Institute, Newcastle University Faculty of Medical Sciences, Newcastle upon Tyne, Tyne & Wear, UK .,Neuroradiology, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, Tyne & Wear, UK
| | - Barbara Gregson
- Translational and Clinical Research Institute, Newcastle University Faculty of Medical Sciences, Newcastle upon Tyne, Tyne & Wear, UK
| | - Elena Adela Cora
- Neuroradiology, Capital Health Halifax Infirmary Site, Halifax, Nova Scotia, Canada
| | - Anand Dixit
- Neuroradiology, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, Tyne & Wear, UK.,Institute of Translational & Clinical Medicine, Newcastle University, Newcastle upon Tyne, Tyne and Wear, UK
| | - Ganesh Subramanian
- Nottingham University Hospitals NHS Trust, Nottingham, Nottinghamshire, UK
| | - Yogish Joshi
- Neuroradiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, Cambridgeshire, UK
| | - Robert Simister
- Consultant Stroke Neurologist UCLH Comprehensive Stroke Service, University College London Faculty of Medical Sciences, London, UK
| | - Rachel Lakey
- Newcastle Clinical Trials Unit, Newcastle University Faculty of Medical Sciences, Newcastle upon Tyne, Tyne & Wear, UK
| | - Ahmed Maiter
- Faculty of Medical Sciences, Newcastle University Faculty of Medical Sciences, Newcastle upon Tyne, Tyne & Wear, UK
| | - Gary A Ford
- Stroke Medicine, Oxford University, Oxford, Oxfordshire, UK
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Etherton MR, Gadhia RR, Schwamm LH. Thrombolysis beyond 4.5 h in Acute Ischemic Stroke. Curr Neurol Neurosci Rep 2020; 20:35. [PMID: 32607627 DOI: 10.1007/s11910-020-01055-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
PURPOSE OF REVIEW The purpose of this article is to review the current approaches using neuroimaging techniques to expand eligibility for intravenous thrombolytic therapy in acute ischemic stroke patients with stroke of unknown symptom onset. RECENT FINDINGS In recent years, several randomized, placebo-controlled trials have shown neuroimaging-guided approaches to be feasible in determining eligibility for alteplase beyond 4.5 h from last known well, and efficacious for reducing disability. DWI-FLAIR mismatch on MRI is an effective tool to identify stroke lesions less than 4.5 h in onset in patients with stroke of unknown symptom onset. Additionally, an automated perfusion-based approach, assessing for a disproportionate amount of salvageable tissue, is effective in identifying patients likely to benefit from late window alteplase treatment. In patients with stroke of unknown symptom onset, an individualized approach using neuroimaging to determine time of stroke onset or presence of salvageable brain tissue is feasible in the acute setting and associated with improved long-term outcomes.
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Affiliation(s)
- Mark R Etherton
- JPK Stroke Research Center, Department of Neurology, Massachusetts General Hospital (MGH) and Harvard Medical School, Boston, MA, USA.
| | - Rajan R Gadhia
- Department of Neurology, Eddy Scurlock Stroke Center, Houston Methodist, Houston, TX, USA
| | - Lee H Schwamm
- JPK Stroke Research Center, Department of Neurology, Massachusetts General Hospital (MGH) and Harvard Medical School, Boston, MA, USA
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Weyland CS, Neuberger U, Seker F, Nagel S, Arthur Ringleb P, Möhlenbruch MA, Bendszus M, Pfaff JA. Effect of treatment technique on radiation exposure in mechanical thrombectomy for acute ischaemic stroke: A matched-pair analysis. Neuroradiol J 2020; 33:286-291. [PMID: 32419602 DOI: 10.1177/1971400920925433] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE This study aimed to compare radiation exposure (RE) in patients receiving mechanical thrombectomy (MT) for large-vessel occlusions in the anterior circulation using direct thrombo-aspiration (DT) versus stent-retriever thrombectomy under continuous distal aspiration (STA). METHODS This was a retrospective single-centre analysis of an Institutional Review Board-approved stroke database of a comprehensive stroke centre focusing on RE per dose area product, procedure time (PT) and fluoroscopy time (FT) in patients receiving MT. Patients who received MT with DT were matched with patients treated using STA according to occlusion location, mode of anaesthesia, manoeuvre count and sex. RESULTS Apart from patient age (DT: M = 74 years (standard deviation (SD)=13 years); STA: M = 79 years (SD = 11 years); p = 0.023), there was no difference in baseline patient characteristics (n = 68 per group). PT (DT: median = 26 minutes (interquartile range (IQR) = 21-38 minutes); STA: median = 49 minutes (IQR 37-77 minutes); p < 0.0001) and FT (DT: median = 12 minutes (IQR 7-18 minutes); STA: median = 26 minutes (IQR 14-43 minutes); p < 0.0001) were shorter in patients who received MT using DT. RE (DT: median = 62.6 Gy·cm2 (IQR 41.7-89.4 Gy·cm2); STA: median = 89.8 Gy·cm2 (IQR 53.7-131.7 Gy·cm2); p = 0.034) was significantly lower in patients who received MT using DT. This represents a relative increase of RE, FT and PT by 43.6%, 116.6% and 88.5%, respectively, in patients who received MT using STA. CONCLUSION MT using DT is associated with shorter FT and PT and lower RE compared to matched patients treated with STA.
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Affiliation(s)
| | - Ulf Neuberger
- Department of Neuroradiology, Heidelberg University Hospital, Germany
| | - Fatih Seker
- Department of Neuroradiology, Heidelberg University Hospital, Germany
| | - Simon Nagel
- Department of Neurology, Heidelberg University Hospital, Germany
| | | | | | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Germany
| | - Johannes Ar Pfaff
- Department of Neuroradiology, Heidelberg University Hospital, Germany
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Turner AC, Schwamm LH, Etherton MR. Acute ischemic stroke: improving access to intravenous tissue plasminogen activator. Expert Rev Cardiovasc Ther 2020; 18:277-287. [PMID: 32323590 DOI: 10.1080/14779072.2020.1759422] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Since approval by the United States Food and Drug Administration in 1996, alteplase utilization rates for acute ischemic stroke have increased. Despite its efficacy for improving stroke outcomes, however, the majority of ischemic stroke patients still do not receive alteplase. To address this issue, different methods for improving access to alteplase have been tested with varying degrees of success. AREAS COVERED This article gives an overview of the recent approaches pursued to improve access to alteplase for acute ischemic stroke patients. Utilization of stroke systems of care, quality metrics, and quality-improvement initiatives to improve alteplase treatment rates are discussed. The implementation of Telestroke networks to improve access and timely evaluation by a stroke specialist are also reviewed. Lastly, this review discusses the use of neuroimaging techniques to identify alteplase candidates in stroke of unknown symptom onset or beyond the 4.5-h treatment window. EXPERT COMMENTARY Expanding access to alteplase therapy for acute ischemic stroke is a multi-faceted approach. Specific considerations based on region, population, and health-care resources should be considered for each strategy. Neuroimaging approaches to identify alteplase-eligible patients beyond the 4.5-h treatment window are a recent development in acute stroke care that holds promise for increasing alteplase treatment rates.
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Affiliation(s)
- Ashby C Turner
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School , Boston, MA, USA
| | - Lee H Schwamm
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School , Boston, MA, USA
| | - Mark R Etherton
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School , Boston, MA, USA
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Abstract
PURPOSE OF REVIEW Until recently, intravenous thrombolysis and mechanical thrombectomy for acute stroke treatment relied on reported information on the known time of symptom onset and was limited to treatment within a narrow time window. New trials have provided evidence for imaging-based effective reperfusion treatment in an extended time window and unknown-onset stroke. This review summarizes evidence from recent clinical trials and suggests a simple algorithm for the choice of imaging modalities to guide evidence-based reperfusion treatment of acute stroke. RECENT FINDINGS Two trials have provided evidence for benefit of mechanical thombectomy in patients with stroke from large vessel occlusion up to 24 h after symptom onset or with unknown symptom onset who have a small infarct core but large perfusion lesion or severe clinical deficit (DAWN, DEFUSE-3). An MRI-based trial has demonstrated the benefit of intravenous thrombolysis with alteplase in patients with unknown onset stroke who present with MRI findings of DWI-FLAIR mismatch (WAKE-UP). Another trial demonstrated benefit of intravenous alteplase in an extended or unknown time-window in patients with penumbral pattern on MRI or CT perfusion (EXTEND). SUMMARY In stroke patients with unknown symptom onset or known symptom onset up to 24 h, advanced imaging with MRI or with CT perfusion can guide effective acute reperfusion treatment with mechanical thrombectomy and intravenous alteplase.
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Siegler JE, Olsen A, Rosenberg J, Cristancho D, Pulst-Korenberg J, Raab L, Woo JH, Messé SR. Mismatch between automated CTP and ASPECTS score in patients with anterior large vessel occlusion. Clin Neurol Neurosurg 2020; 194:105797. [PMID: 32222652 DOI: 10.1016/j.clineuro.2020.105797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 03/17/2020] [Accepted: 03/18/2020] [Indexed: 01/01/2023]
Abstract
OBJECTIVES To evaluate the relationship between delay to computed tomography perfusion and estimated core infarct volumes in patients with large vessel occlusion (LVO). PATIENTS AND METHODS A retrospective registry of consecutive adults >18 years old who underwent CTP in clinical practice for suspected LVO within 24 h of LKN at 3 academic hospitals was queried (06/2017 - 12/2017). CT and CTP findings were compared over time as a continuous variable, and dichotomized by ≤6 h or 6-24 h from LKN. RESULTS Of 410 screened patients, 75 had LVO, of whom 60 (14.6 %) met inclusion criteria (median age 78y [IQR 64-84], 36 were female [60 %]), and 39 (65.0 %) underwent thrombectomy. Thirty (50 %) presented in the extended window (6-24 h) and had lower ASPECTS scores compared to patients in the early window (median 7 vs. 9, p < 0.01). Perfusion core (rCBF <30 %) volumes were similar (median 8 vs. 25, p = 0.10). After adjustment for age, NIHSS, and thrombolysis, there was a trend for lower ASPECTS for every hour after LKN (proportional OR 0.92, 95 %CI 0.84-1.00, p = 0.06), but no change in perfusion core (p = 0.37) or Tmax>6 s volumes (p = 0.29), or mismatch ratios (p = 0.48) after adjusting for age, NIHSS, ASPECTS, and thrombolysis. CONCLUSION As time progresses in anterior LVO, the unenhanced CT is more sensitive than CTP for detecting irreversibly damaged tissue. These results underscore the importance of carefully reviewing the unenhanced and perfusion CT when considering a patient for thrombectomy.
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Affiliation(s)
- James E Siegler
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States.
| | - Andrew Olsen
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - Jon Rosenberg
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - Daniel Cristancho
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - Johannes Pulst-Korenberg
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - Lindsay Raab
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - John H Woo
- Department of Radiology, Division of Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
| | - Steven R Messé
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA, 19104, United States
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40
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Khalil AA, Villringer K, Filleböck V, Hu JY, Rocco A, Fiebach JB, Villringer A. Non-invasive monitoring of longitudinal changes in cerebral hemodynamics in acute ischemic stroke using BOLD signal delay. J Cereb Blood Flow Metab 2020; 40:23-34. [PMID: 30334657 PMCID: PMC6928563 DOI: 10.1177/0271678x18803951] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Relative delays in blood-oxygen-level-dependent (BOLD) signal oscillations can be used to assess cerebral perfusion without using contrast agents. However, little is currently known about the utility of this method in detecting clinically relevant perfusion changes over time. We investigated the relationship between longitudinal BOLD delay changes, vessel recanalization, and reperfusion in 15 acute stroke patients with vessel occlusion examined within 24 h of symptom onset (D0) and one day later (D1). We created BOLD delay maps using time shift analysis of resting-state functional MRI data and quantified perfusion lesion volume changes (using the D1/D0 volume ratio) and severity changes (using a linear mixed model) over time. Between baseline and follow-up, BOLD delay lesions shrank (median D1/D0 ratio = 0.2, IQR = 0.03-0.7) and BOLD delay severity decreased (b = -4.4 s) in patients with recanalization, whereas they grew (median D1/D0 ratio = 1.47, IQR = 1.1-1.7) and became more severe (b = 4.3 s) in patients with persistent vessel occlusion. Clinically relevant changes in cerebral perfusion in early stroke can be detected using BOLD delay, making this non-invasive method a promising option for detecting tissue at risk of infarction and monitoring stroke patients following recanalization therapy.
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Affiliation(s)
- Ahmed A Khalil
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Mind, Brain, Body Institute, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kersten Villringer
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Vivien Filleböck
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jiun-Yiing Hu
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andrea Rocco
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jochen B Fiebach
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Arno Villringer
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Mind, Brain, Body Institute, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
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41
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Siegler JE, Messé SR, Sucharew H, Kasner SE, Mehta T, Arora N, Starosciak AK, De Los Rios La Rosa F, Barnhill NR, Mistry AM, Patel K, Assad S, Tarboosh A, Dakay K, Wagner J, Bennett A, Jagadeesan B, Streib C, Weber SA, Chitale R, Volpi JJ, Mayer SA, Yaghi S, Jayaraman MV, Khatri P, Mistry EA. Noncontrast CT versus Perfusion-Based Core Estimation in Large Vessel Occlusion: The Blood Pressure after Endovascular Stroke Therapy Study. J Neuroimaging 2019; 30:219-226. [PMID: 31762108 DOI: 10.1111/jon.12682] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Revised: 11/08/2019] [Accepted: 11/11/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND AND PURPOSE The 2018 AHA guidelines recommend perfusion imaging to select patients with acute large vessel occlusion (LVO) for thrombectomy in the extended window. However, the relationship between noncontrast CT and CT perfusion imaging has not been sufficiently characterized >6 hours after last known normal (LKN). METHODS From a multicenter prospective cohort of consecutive adults who underwent thrombectomy for anterior LVO 0-24 hours after LKN, we correlated baseline core volume (rCBF < 30%) and the Alberta Stroke Program Early CT Scale (ASPECTS) score. We compared perfusion findings between patients with an unfavorable ASPECTS (<6) against those with a favorable ASPECTS (≥6), and assessed findings over time. RESULTS Of 485 enrolled patients, 177 met inclusion criteria (median age: 69 years, interquartile range [IQR: 57-81], 49% female, median ASPECTS 8 [IQR: 6-9], median core 10 cc [IQR: 0-30]). ASPECTS and core volume moderately correlated (r = -.37). A 0 cc core was observed in 54 (31%) patients, 70% of whom had ASPECTS <10. Of the 28 patients with ASPECTS <6, 3 (11%) had a 0 cc core. After adjustment for age and stroke severity, there was a lower ASPECTS for every 1 hour delay from LKN (cOR: 0.95, 95% confidence of interval [CI]: 0.91-1.00, P = .04). There was no difference in core (P = .51) or penumbra volumes (P = .87) across patients over time. CONCLUSIONS In this multicenter prospective cohort of patients who underwent thrombectomy, one-third of patients had normal CTP core volumes despite nearly three quarters of patients showing ischemic changes on CT. This finding emphasizes the need to carefully assess both noncontrast and perfusion imaging when considering thrombectomy eligibility.
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Affiliation(s)
- James E Siegler
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Steven R Messé
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Heidi Sucharew
- Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH
| | - Scott E Kasner
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Tapan Mehta
- Department of Neurology, University of Minnesota Medical Center, Minneapolis, MN.,Department of Neurology, Fairview Southdale Hospital, Minneapolis, MN.,Department of Neurology, Hennepin County Medical Center, Minneapolis, MN
| | - Niraj Arora
- Department of Neurology, Jackson Memorial Hospital, Miami, FL
| | | | | | - Natasha R Barnhill
- Department of Neurology, Oregon Health and Science University, Portland, OR
| | | | - Kishan Patel
- Department of Neurology, Houston Methodist Medical Center, Houston, TX
| | - Salman Assad
- Department of Neurology, Henry Ford Health System, Detroit, MI
| | - Amjad Tarboosh
- Department of Neurology, Henry Ford Health System, Detroit, MI
| | - Katarina Dakay
- Department of Neurology, Brown University, Providence, RI
| | - Jeff Wagner
- Department of Neurology, Blue Sky Neurology, Englewood, CO
| | - Alicia Bennett
- Department of Neurology, Blue Sky Neurology, Englewood, CO
| | - Bharathi Jagadeesan
- Department of Radiology, University of Minnesota Medical Center, Minneapolis, MN
| | - Christopher Streib
- Department of Neurology, University of Minnesota Medical Center, Minneapolis, MN.,Department of Neurology, Fairview Southdale Hospital, Minneapolis, MN
| | - Stewart A Weber
- Department of Neurology, Oregon Health and Science University, Portland, OR
| | - Rohan Chitale
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN
| | - John J Volpi
- Department of Neurology, Houston Methodist Medical Center, Houston, TX
| | - Stephan A Mayer
- Department of Neurology, Henry Ford Health System, Detroit, MI
| | - Shadi Yaghi
- Department of Neurology, Brown University, Providence, RI
| | - Mahesh V Jayaraman
- Department of Neurology, Brown University, Providence, RI.,Department of Diagnostic Imaging, Brown University, Providence, RI.,Department of Neurosurgery, Brown University, Providence, RI
| | - Pooja Khatri
- Department of Neurology, University of Cincinnati, Cincinnati, OH
| | - Eva A Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN
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Lorenzano S, Rost NS, Khan M, Li H, Batista LM, Chutinet A, Green RE, Thankachan TK, Thornell B, Muzikansky A, Arai K, Som AT, Pham LDD, Wu O, Harris GJ, Lo EH, Blumberg JB, Milbury PE, Feske SK, Furie KL. Early molecular oxidative stress biomarkers of ischemic penumbra in acute stroke. Neurology 2019; 93:e1288-e1298. [PMID: 31455665 DOI: 10.1212/wnl.0000000000008158] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 04/28/2019] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVES To assess whether plasma biomarkers of oxidative stress predict diffusion-perfusion mismatch in patients with acute ischemic stroke (AIS). METHODS We measured plasma levels of oxidative stress biomarkers such as F2-isoprostanes (F2-isoPs), total and perchloric acid Oxygen Radical Absorbance Capacity (ORACTOT and ORACPCA), urinary levels of 8-oxo-7,8-dihydro-2'-deoxyguoanosine, and inflammatory and tissue-damage biomarkers (high-sensitivity C-reactive protein, matrix metalloproteinase-2 and -9) in a prospective study of patients with AIS presenting within 9 hours of symptom onset. Diffusion-weighted (DWI) and perfusion-weighted (PWI) MRI sequences were analyzed with a semiautomated volumetric method. Mismatch was defined as baseline mean transit time volume minus DWI volume. A percent mismatch cutoff of >20% was considered clinically significant. A stricter definition of mismatch was also used. Mismatch salvage was the region free of overlap by final infarction. RESULTS Mismatch >20% was present in 153 of 216 (70.8%) patients (mean [±SD] age 69.2 ± 14.3 years, 41.2% women). Patients with mismatch >20% were more likely to have higher baseline plasma levels of ORACPCA (p = 0.020) and F2-isoPs (p = 0.145). Multivariate binary logistic regression demonstrated that lnF2-isoP (odds ratio [OR] 2.44, 95% confidence interval [CI] 1.19-4.98, p = 0.014) and lnORACPCA (OR 4.18, 95% CI 1.41-12.41, p = 0.010) were independent predictors of >20% PWI-DWI mismatch and the stricter mismatch definition, respectively. lnORACTOT significantly predicted mismatch salvage volume (>20% mismatch p = 0.010, stricter mismatch definition p = 0.003). CONCLUSIONS Elevated hyperacute plasma levels of F2-isoP and ORAC are associated with radiographic evidence of mismatch and mismatch salvage in patients with AIS. If validated, these findings may add to our understanding of the role of oxidative stress in cerebral tissue fate during acute ischemia.
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Affiliation(s)
- Svetlana Lorenzano
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
| | - Natalia S Rost
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Muhib Khan
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Hua Li
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Leonardo M Batista
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Aurauma Chutinet
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Rebecca E Green
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Tijy K Thankachan
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Brenda Thornell
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Alona Muzikansky
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Ken Arai
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Angel T Som
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Loc-Duyen D Pham
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Ona Wu
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Gordon J Harris
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Eng H Lo
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
| | - Jeffrey B Blumberg
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Paul E Milbury
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Steven K Feske
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Karen L Furie
- From the J. Philip Kistler Stroke Research Center (S.L., N.S.R., L.M.B., A.C., R.E.G., T.K.T., B.T.), Department of Neurology, and Department of Radiology (H.L., G.J.H.), Massachusetts General Hospital and Harvard Medical School, Boston; Department of Neurology (M.K., K.L.F.), Rhode Island Hospital, Alpert Medical School of Brown University, Providence; Massachusetts General Hospital Biostatistics Center (A.M.), Boston; Neuroprotection Research Laboratory (K.A., A.T.S., L.-D.D.P., E.H.L.), Neuroscience Center, Departments of Neurology and Radiology, Massachusetts General Hospital and Harvard Medical School; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Antioxidant Research Laboratory (J.B.B.), Jean Mayer USDA Human Nutrition Research Center on Aging, and Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy (P.E.M.), Tufts University; and Department of Neurology (S.K.F.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Siegler JE, Rosenberg J, Cristancho D, Olsen A, Pulst-Korenberg J, Raab L, Cucchiara B, Messé SR. Computed tomography perfusion in stroke mimics. Int J Stroke 2019; 15:299-307. [PMID: 31409213 DOI: 10.1177/1747493019869702] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To describe the prevalence and patterns of abnormal findings on automated computed tomography perfusion in patients with stroke mimic. METHODS We reviewed a retrospective multi-site cohort of consecutive patients undergoing computed tomography perfusion for suspected acute ischemic stroke within 24 h from last normal (June 2017 to December 2017). The primary outcome was the diagnosis of stroke mimic. Hypoperfusion abnormalities on iSchemaView RAPID automated computed tomography perfusion were compared between patients with stroke/transient ischemic attack and stroke mimic using mixed-effects multivariable logistic regression, focusing on absence of perfusion abnormalities and discordance with clinical symptoms and computed tomography angiography findings. RESULTS Of 410 consecutive patients who underwent computed tomography perfusion, 348 met inclusion criteria (178 (51%) stroke, 19 (6%) transient ischemic attack, and 151 (43%) mimic). Time-to-maximum of the tissue residue function (Tmax>6s) abnormalities were seen in 42 (28%) patients with stroke mimic and 122 (62%) patients with stroke/transient ischemic attack (p < 0.001). Patients with stroke mimic were more likely to have a normal Tmax pattern (volume = 0mL; adjusted OR: 2.2, 95% CI: 1.1-4.3, p = 0.02). When the Tmax pattern was abnormal, a higher proportion of patients with stroke mimic had Tmax patterns fully discordant with clinical symptoms than patients with stroke/transient ischemic attack (28/39 (71%) vs. 10/115 (9%), p < 0.001). Fully discordant Tmax abnormalities were strongly associated with stroke mimic (adjusted OR: 48.6, 95% CI: 7.0-336, p < 0.001), with a negative predictive value for identifying mimic of 91% (95% CI: 85-94%). CONCLUSION While one-quarter of patients with stroke mimic show Tmax abnormalities on automated RAPID computed tomography perfusion imaging, the majority of patterns were discordant with symptoms and vessel status. Normal or fully discordant Tmax abnormalities are were more common with stroke mimic and may inform stroke treatment decision making.
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Affiliation(s)
- James E Siegler
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jon Rosenberg
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Cristancho
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Olsen
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Lindsay Raab
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Brett Cucchiara
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Steven R Messé
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
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Siegler JE, Olsen A, Pulst-Korenberg J, Cristancho D, Rosenberg J, Raab L, Cucchiara B, Messé SR. Multicenter Volumetric Assessment of Artifactual Hypoperfusion Patterns using Automated CT Perfusion Imaging. J Neuroimaging 2019; 29:573-579. [PMID: 31199025 DOI: 10.1111/jon.12641] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 05/20/2019] [Accepted: 05/22/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND AND PURPOSE Automated computed tomography perfusion (CTP) is recommended to inform selection of stroke patients for thrombectomy >6 hours from last known normal (LKN). However, artifacts on automated perfusion output may overestimate the tissue at risk leading to misclassification of thrombectomy eligibility in some patients. METHODS We conducted a retrospective multisite study of consecutive patients with anterior large vessel occlusion (LVO) undergoing CTP (6/2017-12/2017). The primary outcome was the RAPID automated Tmax > 6 seconds volume that was discordant with clinical symptoms and vessel imaging, manually assessed by two independent readers. The discordant penumbral volume was compared to the automated output and corrected mismatch ratios were generated. RESULTS Of 410 consecutive patients who underwent CTP for suspected stroke, 60 (15%) had acute anterior circulation LVO. Of these, 26 (43%) had Tmax > 6 seconds abnormalities discordant with clinical symptoms and vessel imaging. There was strong interrater agreement on artifact volume (r2 = 0.927). Among patients with discordant Tmax imaging, the median artifactual volume was 12cc (IQR 3-21cc), accounting for a median of 8% of the automated Tmax > 6 seconds volume (IQR 3-16%, range 1-64%). Recalculation of the Tmax > 6 seconds volume resulted in 1 patient being reclassified as having an "unfavorable" mismatch ratio (2.04-1.40). CONCLUSION Nearly half of patients had evidence of artifactual penumbral imaging on automated CTP, which rarely lead to misclassification of thrombectomy eligibility. Although artifactual findings are reliably identified by trained raters, our results emphasize the need to evaluate CTP results with knowledge of the patient's clinical symptoms and vascular imaging.
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Affiliation(s)
- James E Siegler
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Andrew Olsen
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | | | - Daniel Cristancho
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Jon Rosenberg
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Lindsay Raab
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Brett Cucchiara
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Steven R Messé
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
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Huo X, Liu R, Gao F, Ma N, Mo D, Liao X, Wang C, Sun X, Song L, Jia B, Liu L, Wang B, Pan Y, Wang Y, Liu L, Zhao X, Wang Y, Miao Z. Effect of Hyperglycemia at Presentation on Outcomes in Acute Large Artery Occlusion Patients Treated With Solitaire Stent Thrombectomy. Front Neurol 2019; 10:71. [PMID: 30837929 PMCID: PMC6390827 DOI: 10.3389/fneur.2019.00071] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 01/18/2019] [Indexed: 01/21/2023] Open
Abstract
Background: Sporadic data showed hyperglycemia at presentation is associated with poor outcomes in patients with acute ischemic stroke (AIS) under mechanical thrombectomy (MT) treatment. Objective: This study aims to evaluate the relationship of admission hyperglycemia and outcomes in patients treated with solitaire stent thrombectomy. Methods: This multicenter prospective study registered patients with AIS due to anterior circulation large vessel occlusion (LVO) suitable for MT with Solitaire stent retriever. We analyzed the influence of admission hyperglycemia (≥7.8 mmol/L) and serum glucose on functional independence which is defined as modified Rankin Scale score (mRS) of 0–2, symptomatic intracranial hemorrhage (sICH) and several outcomes of interest using univariable and multiple logistic regression analysis. Results: This study involved 17 stroke centers across China and consecutively recruited 149 patients. Patients with hyperglycemia at presentation less frequently exhibited a functional independence at 3 months than patients without hyperglycemia (22.2 vs. 66.4%; odds ratio 0.75, 95% confidence interval 0.61–0.92; P = 0.005). Higher glucose levels were correlated with worse outcome (per 1 mmol/L increase in glucose: odds ratio for mRS score 0–2 at 3 months 0.17, 95% confidence interval 0.06–0.45; P < 0.001) at 3 months and sICH (per 1 mmol/L increase in glucose: odds ratio for sICH was 8.2, 95% confidence interval 1.13–29.57; P < 0.001) after thrombectomy. Conclusions: Higher admission serum glucose and hyperglycemia were independently correlated with lower functional independence at 3 months in patients treated with Solitaire stent thrombectomy of anterior circulation LVO. Higher admission serum glucose was also associated with sICH after thrombectomy.
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Affiliation(s)
- Xiaochuan Huo
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Raynald Liu
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Feng Gao
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Ma
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dapeng Mo
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaoling Liao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunjuan Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuan Sun
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ligang Song
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baixue Jia
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lian Liu
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bo Wang
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Liping Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhongrong Miao
- Interventional Neuroradiology Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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Campbell BCV, Majoie CBLM, Albers GW, Menon BK, Yassi N, Sharma G, van Zwam WH, van Oostenbrugge RJ, Demchuk AM, Guillemin F, White P, Dávalos A, van der Lugt A, Butcher KS, Cherifi A, Marquering HA, Cloud G, Macho Fernández JM, Madigan J, Oppenheim C, Donnan GA, Roos YBWEM, Shankar J, Lingsma H, Bonafé A, Raoult H, Hernández-Pérez M, Bharatha A, Jahan R, Jansen O, Richard S, Levy EI, Berkhemer OA, Soudant M, Aja L, Davis SM, Krings T, Tisserand M, San Román L, Tomasello A, Beumer D, Brown S, Liebeskind DS, Bracard S, Muir KW, Dippel DWJ, Goyal M, Saver JL, Jovin TG, Hill MD, Mitchell PJ. Penumbral imaging and functional outcome in patients with anterior circulation ischaemic stroke treated with endovascular thrombectomy versus medical therapy: a meta-analysis of individual patient-level data. Lancet Neurol 2018; 18:46-55. [PMID: 30413385 DOI: 10.1016/s1474-4422(18)30314-4] [Citation(s) in RCA: 247] [Impact Index Per Article: 41.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Revised: 08/15/2018] [Accepted: 08/15/2018] [Indexed: 12/24/2022]
Abstract
BACKGROUND CT perfusion (CTP) and diffusion or perfusion MRI might assist patient selection for endovascular thrombectomy. We aimed to establish whether imaging assessments of irreversibly injured ischaemic core and potentially salvageable penumbra volumes were associated with functional outcome and whether they interacted with the treatment effect of endovascular thrombectomy on functional outcome. METHODS In this systematic review and meta-analysis, the HERMES collaboration pooled patient-level data from all randomised controlled trials that compared endovascular thrombectomy (predominantly using stent retrievers) with standard medical therapy in patients with anterior circulation ischaemic stroke, published in PubMed from Jan 1, 2010, to May 31, 2017. The primary endpoint was functional outcome, assessed by the modified Rankin Scale (mRS) at 90 days after stroke. Ischaemic core was estimated, before treatment with either endovascular thrombectomy or standard medical therapy, by CTP as relative cerebral blood flow less than 30% of normal brain blood flow or by MRI as an apparent diffusion coefficient less than 620 μm2/s. Critically hypoperfused tissue was estimated as the volume of tissue with a CTP time to maximum longer than 6 s. Mismatch volume (ie, the estimated penumbral volume) was calculated as critically hypoperfused tissue volume minus ischaemic core volume. The association of ischaemic core and penumbral volumes with 90-day mRS score was analysed with multivariable logistic regression (functional independence, defined as mRS score 0-2) and ordinal logistic regression (functional improvement by at least one mRS category) in all patients and in a subset of those with more than 50% endovascular reperfusion, adjusted for baseline prognostic variables. The meta-analysis was prospectively designed by the HERMES executive committee, but not registered. FINDINGS We identified seven studies with 1764 patients, all of which were included in the meta-analysis. CTP was available and assessable for 591 (34%) patients and diffusion MRI for 309 (18%) patients. Functional independence was worse in patients who had CTP versus those who had diffusion MRI, after adjustment for ischaemic core volume (odds ratio [OR] 0·47 [95% CI 0·30-0·72], p=0·0007), so the imaging modalities were not pooled. Increasing ischaemic core volume was associated with reduced likelihood of functional independence (CTP OR 0·77 [0·69-0·86] per 10 mL, pinteraction=0·29; diffusion MRI OR 0·87 [0·81-0·94] per 10 mL, pinteraction=0·94). Mismatch volume, examined only in the CTP group because of the small numbers of patients who had perfusion MRI, was not associated with either functional independence or functional improvement. In patients with CTP with more than 50% endovascular reperfusion (n=186), age, ischaemic core volume, and imaging-to-reperfusion time were independently associated with functional improvement. Risk of bias between studies was generally low. INTERPRETATION Estimated ischaemic core volume was independently associated with functional independence and functional improvement but did not modify the treatment benefit of endovascular thrombectomy over standard medical therapy for improved functional outcome. Combining ischaemic core volume with age and expected imaging-to-reperfusion time will improve assessment of prognosis and might inform endovascular thrombectomy treatment decisions. FUNDING Medtronic.
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Affiliation(s)
- Bruce C V Campbell
- Department of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
| | - Charles B L M Majoie
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, Netherlands
| | | | - Bijoy K Menon
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Foothills Hospital, Calgary, AB, Canada
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia; The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Gagan Sharma
- Department of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Wim H van Zwam
- Department of Radiology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands
| | - Robert J van Oostenbrugge
- Department of Neurology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands
| | - Andrew M Demchuk
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Foothills Hospital, Calgary, AB, Canada
| | - Francis Guillemin
- Clinical Investigation Centre-Clinical Epidemiology, INSERM 1433, University of Lorraine and University Hospital of Nancy, Nancy, France
| | - Philip White
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Antoni Dávalos
- Department of Neuroscience, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Aad van der Lugt
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Kenneth S Butcher
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Aboubaker Cherifi
- Clinical Investigation Centre-Innovative Technology, INSERM 1433, University of Lorraine and University Hospital of Nancy, Nancy, France
| | - Henk A Marquering
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, Netherlands; Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, Netherlands
| | - Geoffrey Cloud
- Stroke Unit, Alfred Hospital and Monash University, Melbourne, VIC, Australia
| | | | - Jeremy Madigan
- Department of Neuroradiology, Atkinson Morley Regional Neuroscience Centre, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Catherine Oppenheim
- Department of Neuroradiology, Sainte-Anne Hospital and Paris-Descartes University, INSERM U894, Paris, France
| | - Geoffrey A Donnan
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Yvo B W E M Roos
- Department of Neurology, Academic Medical Center, Amsterdam, Netherlands
| | - Jai Shankar
- Department of Radiology, QEII Health Science Center, Dalhousie University, Halifax, NS, Canada
| | - Hester Lingsma
- Department of Public Health, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Alain Bonafé
- Department of Neuroradiology, Hôpital Gui-de Chauliac, Montpellier, France
| | - Hélène Raoult
- Department of Neuroradiology, CHU Pontchaillou, Rennes, France
| | - María Hernández-Pérez
- Department of Neuroscience, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Aditya Bharatha
- Division of Diagnostic and Interventional Neuroradiology, Department of Medical Imaging, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Reza Jahan
- Division of Interventional Neuroradiology, University of California Los Angeles, Los Angeles, CA, USA
| | - Olav Jansen
- Department of Radiology and Neuroradiology, Universitätsklinikum Kiel, Kiel, Germany
| | - Sébastien Richard
- Department of Neurology, Stroke Unit, CIC-1433, INSERM U1116, University Hospital of Nancy, Nancy, France
| | - Elad I Levy
- Department of Neurosurgery, State University of New York at Buffalo, Buffalo, NY, USA
| | - Olvert A Berkhemer
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, Netherlands; Department of Radiology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Marc Soudant
- Clinical Investigation Centre-Clinical Epidemiology, INSERM 1433, University of Lorraine and University Hospital of Nancy, Nancy, France
| | - Lucia Aja
- Department of Neurology, Hospital de Bellvitge, Barcelona, Spain
| | - Stephen M Davis
- Department of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Timo Krings
- Department of Radiology, Toronto Western Hospital and University Health Network, University of Toronto, Toronto, ON, Canada
| | - Marie Tisserand
- Department of Neuroradiology, Foch Hospital, Suresnes, France
| | - Luis San Román
- Stroke Unit, Alfred Hospital and Monash University, Melbourne, VIC, Australia
| | | | - Debbie Beumer
- Department of Radiology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands
| | - Scott Brown
- Altair Biostatistics, St Louis Park, MN, USA
| | - David S Liebeskind
- Neurovascular Imaging Research Core, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Serge Bracard
- Department of Diagnostic and Interventional Neuroradiology, INSERM U 947, University of Lorraine and University Hospital of Nancy, Nancy, France
| | - Keith W Muir
- Institute of Neuroscience and Psychology, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, UK
| | - Diederik W J Dippel
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Mayank Goyal
- Department of Radiology, University of Calgary, Foothills Hospital, Calgary, AB, Canada
| | - Jeffrey L Saver
- Department of Neurology and Comprehensive Stroke Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Tudor G Jovin
- Stroke Institute, Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Michael D Hill
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Foothills Hospital, Calgary, AB, Canada
| | - Peter J Mitchell
- Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
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Di Giuliano F, Picchi E, Sallustio F, Ferrazzoli V, Alemseged F, Greco L, Minosse S, Da Ros V, Diomedi M, Garaci F, Marziali S, Floris R. Accuracy of advanced CT imaging in prediction of functional outcome after endovascular treatment in patients with large-vessel occlusion. Neuroradiol J 2018; 32:62-70. [PMID: 30303448 DOI: 10.1177/1971400918805710] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND AND PURPOSE Computed tomography perfusion (CTP) and multiphase CT angiography (mCTA) help selection for endovascular treatment (EVT) in anterior ischemic stroke (AIS). Our aim was to investigate the ability of perfusion maps and collateral score to predict functional outcome after EVT. PATIENTS AND METHODS Patients with M1-middle cerebral artery occlusion, evaluated by mCTA and CTP and treated with EVT within six hours of onset, were enrolled. Perfusion parametric maps of cerebral blood flow (CBF), cerebral blood volume (CBV) and time to maximum of tissue residue function ( Tmax) were generated; areas of altered perfusion were manually outlined to obtain volumes CBFv, CBVv, Tmax,v16-25s and Tmax,v9.5-25s . Diffusion-weighted imaging (DWI) at 24-36 hours was used to manually outline the ischemic core (volume: DWIv). Collateral vessels were assessed on mCTA considering extent and delay of maximal enhancement (six-point scale). Functional outcome was evaluated by modified Rankin Scale score at three months. Volumes in good and poor outcome groups were compared by Wilcoxon rank-sum test t, and their discriminative ability for outcome was determined by receiver operating characteristic analysis. A logistic regression model, including Tmax, CBF and collaterals, was used to differentiate good and poor outcome. RESULTS Seventy-one patients (mean age 75 ± 11 years, range 45-99 years) were included. Tmax,v16-25s , Tmax,v9.5-25s , CBVv, CBFv and DWIv were statistically different between the two groups. CBF had the best discriminative value for good and poor outcome (area under the curve (AUC) 0.73; 64.5% sensitivity; 74.4% specificity); the logistic regression model might be promising (AUC 0.79, 64.5% sensitivity, 82.1% specificity). CONCLUSIONS In patients with AIS, the combined use of CTP and mCTA predicts functional outcome of EVT and might allow better selection.
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Affiliation(s)
| | - Eliseo Picchi
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Fabrizio Sallustio
- 2 Department of Neuroscience, Comprehensive Stroke Center, University of Tor Vergata, Italy
| | | | - Fana Alemseged
- 2 Department of Neuroscience, Comprehensive Stroke Center, University of Tor Vergata, Italy.,3 Department of Medicine and Neurology, Royal Melbourne Hospital, University of Melbourne, Australia
| | - Laura Greco
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Silvia Minosse
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Valerio Da Ros
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Marina Diomedi
- 2 Department of Neuroscience, Comprehensive Stroke Center, University of Tor Vergata, Italy.,4 I.R.C.C.S., Santa Lucia Foundation, Italy
| | - Francesco Garaci
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Simone Marziali
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
| | - Roberto Floris
- 1 Department of Biomedicine and Prevention, University of Tor Vergata, Italy
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Bang OY. Stem cell therapy for stroke: lessons learned from recent successful randomized trials of
interventional therapy for stroke. PRECISION AND FUTURE MEDICINE 2018. [DOI: 10.23838/pfm.2018.00058] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
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Giacalone M, Rasti P, Debs N, Frindel C, Cho TH, Grenier E, Rousseau D. Local spatio-temporal encoding of raw perfusion MRI for the prediction of final lesion in stroke. Med Image Anal 2018; 50:117-126. [PMID: 30268970 DOI: 10.1016/j.media.2018.08.008] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 07/28/2018] [Accepted: 08/31/2018] [Indexed: 10/28/2022]
Abstract
We address the medical image analysis issue of predicting the final lesion in stroke from early perfusion magnetic resonance imaging. The classical processing approach for the dynamical perfusion images consists in a temporal deconvolution to improve the temporal signals associated with each voxel before performing prediction. We demonstrate here the value of exploiting directly the raw perfusion data by encoding the local environment of each voxel as a spatio-temporal texture, with an observation scale larger than the voxel. As a first illustration for this approach, the textures are characterized with local binary patterns and the classification is performed using a standard support vector machine (SVM). This simple machine learning classification scheme demonstrates results with 95% accuracy on average while working only raw perfusion data. We discuss the influence of the observation scale and evaluate the interest of using post-processed perfusion data with this approach.
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Affiliation(s)
- Mathilde Giacalone
- CREATIS, CNRS UMR-5220, INSERM U1206, Université Lyon 1, INSA Lyon Bât. Blaise Pascal, 7 avenue Jean Capelle, Villeurbanne 69621, France
| | - Pejman Rasti
- LARIS, UMR IRHS INRA, Université d'Angers 62 avenue Notre Dame du Lac, Angers 49000, France
| | - Noelie Debs
- CREATIS, CNRS UMR-5220, INSERM U1206, Université Lyon 1, INSA Lyon Bât. Blaise Pascal, 7 avenue Jean Capelle, Villeurbanne 69621, France
| | - Carole Frindel
- CREATIS, CNRS UMR-5220, INSERM U1206, Université Lyon 1, INSA Lyon Bât. Blaise Pascal, 7 avenue Jean Capelle, Villeurbanne 69621, France
| | - Tae-Hee Cho
- CREATIS, CNRS UMR-5220, INSERM U1206, Université Lyon 1, INSA Lyon Bât. Blaise Pascal, 7 avenue Jean Capelle, Villeurbanne 69621, France
| | - Emmanuel Grenier
- ENS-Lyon, UMR CNRS 5669 'UMPA', and INRIA Alpes, project NUMED, Lyon F-69364, France
| | - David Rousseau
- LARIS, UMR IRHS INRA, Université d'Angers 62 avenue Notre Dame du Lac, Angers 49000, France.
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Donahue MJ, Hendrikse J. Improved detection of cerebrovascular disease processes: Introduction to the Journal of Cerebral Blood Flow and Metabolism special issue on cerebrovascular disease. J Cereb Blood Flow Metab 2018; 38:1387-1390. [PMID: 30160626 PMCID: PMC6125974 DOI: 10.1177/0271678x17739802] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Approximately 15 million individuals suffer a stroke worldwide each year, and stroke results in death or permanent disability in two-thirds of these individuals. Due to increased knowledge and management of modifiable risk factors, stroke incidence in developed countries is declining, however remains high at just under 1 million patients per year in the United States alone. Further improving management of patients with cerebrovascular disease (CVD) ultimately will require development and clinical adoption of sensitive markers of hemodynamic and metabolic failure, as well as trials that evaluate how to interpret these markers to optimize therapies. Realizing this goal and reducing the complete burden of CVD is dependent on an improved understanding of the pathophysiological processes that underlie CVD in all stages, including sub-clinical disease processes, acute stroke, and post-stroke recovery mechanisms. This document serves as an introduction to the Journal of Cerebral Blood Flow and Metabolism special issue on cerebrovascular diseases, which is comprised of contributions from experts in each of the above stages of CVD, and outlines current standards for patient management and emerging directions that have potential for improving patient care over the next decade.
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Affiliation(s)
- Manus J Donahue
- 1 Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,2 Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA.,3 Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA.,4 Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, USA
| | - Jeroen Hendrikse
- 5 Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
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