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Frid P, Xu H, Mitchell BD, Drake M, Wasselius J, Gaynor B, Ryan K, Giese AK, Schirmer M, Donahue KL, Irie R, Bouts MJRJ, McIntosh EC, Mocking SJT, Dalca AV, Giralt-Steinhauer E, Holmegaard L, Jood K, Roquer J, Cole JW, McArdle PF, Broderick JP, Jimenez-Conde J, Jern C, Kissela BM, Kleindorfer DO, Lemmens R, Meschia JF, Rosand J, Rundek T, Sacco RL, Schmidt R, Sharma P, Slowik A, Thijs V, Woo D, Worrall BB, Kittner SJ, Petersson J, Golland P, Wu O, Rost NS, Lindgren A. Migraine-Associated Common Genetic Variants Confer Greater Risk of Posterior vs. Anterior Circulation Ischemic Stroke☆. J Stroke Cerebrovasc Dis 2022; 31:106546. [PMID: 35576861 PMCID: PMC10601407 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/01/2022] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE To examine potential genetic relationships between migraine and the two distinct phenotypes posterior circulation ischemic stroke (PCiS) and anterior circulation ischemic stroke (ACiS), we generated migraine polygenic risk scores (PRSs) and compared these between PCiS and ACiS, and separately vs. non-stroke control subjects. METHODS Acute ischemic stroke cases were classified as PCiS or ACiS based on lesion location on diffusion-weighted MRI. Exclusion criteria were lesions in both vascular territories or uncertain territory; supratentorial PCiS with ipsilateral fetal posterior cerebral artery; and cases with atrial fibrillation. We generated migraine PRS for three migraine phenotypes (any migraine; migraine without aura; migraine with aura) using publicly available GWAS data and compared mean PRSs separately for PCiS and ACiS vs. non-stroke control subjects, and between each stroke phenotype. RESULTS Our primary analyses included 464 PCiS and 1079 ACiS patients with genetic European ancestry. Compared to non-stroke control subjects (n=15396), PRSs of any migraine were associated with increased risk of PCiS (p=0.01-0.03) and decreased risk of ACiS (p=0.010-0.039). Migraine without aura PRSs were significantly associated with PCiS (p=0.008-0.028), but not with ACiS. When comparing PCiS vs. ACiS directly, migraine PRSs were higher in PCiS vs. ACiS for any migraine (p=0.001-0.010) and migraine without aura (p=0.032-0.048). Migraine with aura PRS did not show a differential association in our analyses. CONCLUSIONS Our results suggest a stronger genetic overlap between unspecified migraine and migraine without aura with PCiS compared to ACiS. Possible shared mechanisms include dysregulation of cerebral vessel endothelial function.
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Affiliation(s)
- P Frid
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden; Section of Neurology, Skåne University Hospital, Malmö, Sweden.
| | - H Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - B D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD, USA
| | - M Drake
- Department of Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden; Department of Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
| | - J Wasselius
- Department of Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden; Department of Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
| | - B Gaynor
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - K Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - A K Giese
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - M Schirmer
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - K L Donahue
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - R Irie
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - M J R J Bouts
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - E C McIntosh
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - S J T Mocking
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - A V Dalca
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
| | - E Giralt-Steinhauer
- Department of Neurology, Neurovascular Research Group (NEUVAS), IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Spain
| | - L Holmegaard
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - K Jood
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - J Roquer
- Department of Neurology, Neurovascular Research Group (NEUVAS), IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Spain
| | - J W Cole
- Department of Neurology, University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore, MD, USA
| | - P F McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - J P Broderick
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - J Jimenez-Conde
- Department of Neurology, Neurovascular Research Group (NEUVAS), IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Spain
| | - C Jern
- Department of Laboratory Medicine, Institute of Biomedicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - B M Kissela
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - D O Kleindorfer
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - R Lemmens
- Department of Neurosciences, Experimental Neurology, VIB Center for Brain & Disease Research, Department of Neurology, University Hospitals Leuven, KU Leuven - University of Leuven, Leuven, Belgium
| | - J F Meschia
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - J Rosand
- Henry and Allison McCance Center for Brain Health Massachusetts General Hospital, Boston, USA
| | - T Rundek
- Department of Neurology, Miller School of Medicine, University of Miami, The Evelyn F. McKnight Brain Institute, FL, USA
| | - R L Sacco
- Department of Neurology, Miller School of Medicine, University of Miami, The Evelyn F. McKnight Brain Institute, FL, USA
| | - R Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Austria
| | - P Sharma
- Institute of Cardiovascular Research, Royal Holloway University of London (ICR2UL), Egham, United Kingdom
| | - A Slowik
- Department of Neurology, Jagiellonian University Medical College, Krakow, Poland
| | - V Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health, and Department of Neurology, Austin Health, Heidelberg, Australia
| | - D Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - B B Worrall
- Departments of Neurology and Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - S J Kittner
- Department of Neurology, University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore, MD, USA
| | - J Petersson
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
| | - P Golland
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
| | - O Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - N S Rost
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden; Section of Neurology, Skåne University Hospital, Lund, Sweden
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Frid P, Drake M, Giese AK, Wasselius J, Schirmer MD, Donahue KL, Cloonan L, Irie R, Bouts MJRJ, McIntosh EC, Mocking SJT, Dalca AV, Sridharan R, Xu H, Giralt-Steinhauer E, Holmegaard L, Jood K, Roquer J, Cole JW, McArdle PF, Broderick JP, Jimenez-Conde J, Jern C, Kissela BM, Kleindorfer DO, Lemmens R, Meschia JF, Rundek T, Sacco RL, Schmidt R, Sharma P, Slowik A, Thijs V, Woo D, Worrall BB, Kittner SJ, Mitchell BD, Petersson J, Rosand J, Golland P, Wu O, Rost NS, Lindgren A. Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study. J Neurol 2020; 267:649-658. [PMID: 31709475 PMCID: PMC7035231 DOI: 10.1007/s00415-019-09613-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 10/28/2019] [Accepted: 10/30/2019] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Posterior circulation ischemic stroke (PCiS) constitutes 20-30% of ischemic stroke cases. Detailed information about differences between PCiS and anterior circulation ischemic stroke (ACiS) remains scarce. Such information might guide clinical decision making and prevention strategies. We studied risk factors and ischemic stroke subtypes in PCiS vs. ACiS and lesion location on magnetic resonance imaging (MRI) in PCiS. METHODS Out of 3,301 MRIs from 12 sites in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN), we included 2,381 cases with acute DWI lesions. The definition of ACiS or PCiS was based on lesion location. We compared the groups using Chi-squared and logistic regression. RESULTS PCiS occurred in 718 (30%) patients and ACiS in 1663 (70%). Diabetes and male sex were more common in PCiS vs. ACiS (diabetes 27% vs. 23%, p < 0.05; male sex 68% vs. 58%, p < 0.001). Both were independently associated with PCiS (diabetes, OR = 1.29; 95% CI 1.04-1.61; male sex, OR = 1.46; 95% CI 1.21-1.78). ACiS more commonly had large artery atherosclerosis (25% vs. 20%, p < 0.01) and cardioembolic mechanisms (17% vs. 11%, p < 0.001) compared to PCiS. Small artery occlusion was more common in PCiS vs. ACiS (20% vs. 14%, p < 0.001). Small artery occlusion accounted for 47% of solitary brainstem infarctions. CONCLUSION Ischemic stroke subtypes differ between the two phenotypes. Diabetes and male sex have a stronger association with PCiS than ACiS. Definitive MRI-based PCiS diagnosis aids etiological investigation and contributes additional insights into specific risk factors and mechanisms of injury in PCiS.
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Affiliation(s)
- Petrea Frid
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden.
- Department of Neurology and Rehabilitation Medicine, Neurology, Skåne University Hospital, Malmö, Sweden.
- Department of Neurology, Skåne University Hospital, Jan Waldenströms gata 19, 205 02, Malmö, Sweden.
| | - Mattias Drake
- Department of Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden
- Department of Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
| | - A K Giese
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - J Wasselius
- Department of Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden
- Department of Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
| | - M D Schirmer
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
- Department of Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - K L Donahue
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - L Cloonan
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - R Irie
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - M J R J Bouts
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - E C McIntosh
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - S J T Mocking
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - A V Dalca
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - R Sridharan
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
| | - H Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - E Giralt-Steinhauer
- Neurovascular Research Group (NEUVAS), Department of Neurology, IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Barcelona, Spain
| | - L Holmegaard
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - K Jood
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - J Roquer
- Neurovascular Research Group (NEUVAS), Department of Neurology, IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Barcelona, Spain
| | - J W Cole
- Department of Neurology, University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore, MD, USA
| | - P F McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - J P Broderick
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - J Jimenez-Conde
- Neurovascular Research Group (NEUVAS), Department of Neurology, IMIM-Hospital del Mar (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autonoma de Barcelona, Barcelona, Spain
| | - C Jern
- Institute of Biomedicine, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - B M Kissela
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - D O Kleindorfer
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - R Lemmens
- Department of Neurosciences, Experimental Neurology, KU Leuven-University of Leuven, Louvain, Belgium
- VIB Center for Brain and Disease Research, Louvain, Belgium
- Department of Neurology, University Hospitals Leuven, Louvain, Belgium
| | - J F Meschia
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - T Rundek
- Department of Neurology and Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - R L Sacco
- Department of Neurology and Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - R Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Graz, Austria
| | - P Sharma
- Institute of Cardiovascular Research, Royal Holloway University of London (ICR2UL), Egham, UK
- Ashford and St Peter's Hospital, Ashford, UK
| | - A Slowik
- Department of Neurology, Jagiellonian University Medical College, Kraków, Poland
| | - V Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health, Heidelberg, Australia
- Department of Neurology, Austin Health, Heidelberg, Australia
| | - D Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - B B Worrall
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - S J Kittner
- Department of Neurology, University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore, MD, USA
| | - B D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD, USA
| | - J Petersson
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
- Department of Neurology and Rehabilitation Medicine, Neurology, Skåne University Hospital, Malmö, Sweden
| | - J Rosand
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
- Center for Genomic Research, Massachusetts General Hospital, Boston, MA, USA
- Division of Neurocritical Care and Emergency Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - P Golland
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
| | - O Wu
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - N S Rost
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden
- Department of Neurology and Rehabilitation Medicine, Neurology, Skåne University Hospital, Lund, Sweden
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Winzeck S, Mocking SJT, Bezerra R, Bouts MJRJ, McIntosh EC, Diwan I, Garg P, Chutinet A, Kimberly WT, Copen WA, Schaefer PW, Ay H, Singhal AB, Kamnitsas K, Glocker B, Sorensen AG, Wu O. Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI. AJNR Am J Neuroradiol 2019; 40:938-945. [PMID: 31147354 DOI: 10.3174/ajnr.a6077] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 04/19/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Accurate automated infarct segmentation is needed for acute ischemic stroke studies relying on infarct volumes as an imaging phenotype or biomarker that require large numbers of subjects. This study investigated whether an ensemble of convolutional neural networks trained on multiparametric DWI maps outperforms single networks trained on solo DWI parametric maps. MATERIALS AND METHODS Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. To assess the generalizability of the approach, we applied the best-performing model to an independent Evaluation Cohort of 151 subjects. Agreement between manual and automated segmentations for identifying patients with large lesion volumes was calculated across multiple thresholds (21, 31, 51, and 70 cm3). RESULTS An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks (P < .001). Automated volumes correlated with manually measured volumes (Spearman ρ = 0.91, P < .001) for the independent cohort. For the task of identifying patients with large lesion volumes, agreement between manual outlines and automated outlines was high (Cohen κ, 0.86-0.90; P < .001). CONCLUSIONS Acute infarcts are more accurately segmented using ensembles of convolutional neural networks trained with multiparametric maps than by using a single model trained with a solo map. Automated lesion segmentation has high agreement with manual techniques for identifying patients with large lesion volumes.
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Affiliation(s)
- S Winzeck
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts.,Division of Anaesthesia (S.W.), Department of Medicine, University of Cambridge, Cambridge, UK
| | - S J T Mocking
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - R Bezerra
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - M J R J Bouts
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - E C McIntosh
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - I Diwan
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - P Garg
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - A Chutinet
- Departments of Neurology (A.C., W.T.K., H.A., A.B.S.).,Department of Medicine (A.C.), Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - W T Kimberly
- Departments of Neurology (A.C., W.T.K., H.A., A.B.S.)
| | - W A Copen
- Radiology (W.A.C., P.W.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - P W Schaefer
- Radiology (W.A.C., P.W.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - H Ay
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts.,Departments of Neurology (A.C., W.T.K., H.A., A.B.S.)
| | - A B Singhal
- Departments of Neurology (A.C., W.T.K., H.A., A.B.S.)
| | - K Kamnitsas
- Department of Computing (K.K., B.G.), Imperial College London, London, UK
| | - B Glocker
- Department of Computing (K.K., B.G.), Imperial College London, London, UK
| | - A G Sorensen
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - O Wu
- From the Department of Radiology (S.W., S.J.T.M., R.B., M.J.R.J.B., E.C.M., I.D., P.G., H.A., A.G.S., O.W.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
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