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Olafson ER, Sperber C, Jamison KW, Bowren MD, Boes AD, Andrushko JW, Borich MR, Boyd LA, Cassidy JM, Conforto AB, Cramer SC, Dula AN, Geranmayeh F, Hordacre B, Jahanshad N, Kautz SA, Tavenner BP, MacIntosh BJ, Piras F, Robertson AD, Seo NJ, Soekadar SR, Thomopoulos SI, Vecchio D, Weng TB, Westlye LT, Winstein CJ, Wittenberg GF, Wong KA, Thompson PM, Liew SL, Kuceyeski AF. Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers. Brain Commun 2024; 6:fcae254. [PMID: 39171205 PMCID: PMC11336660 DOI: 10.1093/braincomms/fcae254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 05/27/2024] [Accepted: 07/30/2024] [Indexed: 08/23/2024] Open
Abstract
Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.
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Affiliation(s)
- Emily R Olafson
- Department of Radiology, Weill Cornell Medicine, New York City, NY 10021, USA
| | - Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern 3012, Switzerland
| | - Keith W Jamison
- Department of Radiology, Weill Cornell Medicine, New York City, NY 10021, USA
| | - Mark D Bowren
- Department of Neurology, Carver College of Medicine, Iowa City, IA 52242, USA
| | - Aaron D Boes
- Department of Neurology, Carver College of Medicine, Iowa City, IA 52242, USA
- Department of Psychiatry, Carver College of Medicine, Iowa City, IA 52242, USA
- Department of Pediatrics, Carver College of Medicine, Iowa City, IA 52242, USA
| | - Justin W Andrushko
- Department of Physical Therapy, Faculty of Medicine, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, United Kingdom
| | - Michael R Borich
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Lara A Boyd
- Department of Physical Therapy, Faculty of Medicine, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Jessica M Cassidy
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adriana B Conforto
- Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paolo 05652-900, Brazil
- Hospital Israelita Albert Einstein, São Paulo 05652-900, Brazil
| | - Steven C Cramer
- Department Neurology, UCLA, California Rehabilitation Institute, Los Angeles, CA 90033, USA
| | - Adrienne N Dula
- Department of Neurology, Dell Medical School at The University of Texas Austin, Austin, TX 78712, USA
| | - Fatemeh Geranmayeh
- Clinical Language and Cognition Group, Department of Brain Sciences, Imperial College London, London W12 0HS, United Kingdom
| | - Brenton Hordacre
- Innovation, Implementation and Clinical Translation (IIMPACT) in Health, Allied Health and Human Performance, University of South Australia, Adelaide 5000, Australia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC 29425, USA
| | - Steven A Kautz
- Department of Health Sciences & Research, Medical University of South Carolina, Charleston, SC 29425, USA
- Ralph H. Johnson VA Health Care System, Charleston, SC 29425, USA
| | - Bethany P Tavenner
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90033, USA
| | - Bradley J MacIntosh
- Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Computational Radiology and Artificial Intelligence (CRAI), Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo 0372, Norway
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome 00179, Italy
| | - Andrew D Robertson
- Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Schlegel-UW Research Institute for Aging, Waterloo, ON N2J 0E2, Canada
| | - Na Jin Seo
- Department of Health Sciences & Research, Medical University of South Carolina, Charleston, SC 29425, USA
- Ralph H. Johnson VA Health Care System, Charleston, SC 29425, USA
- Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Surjo R Soekadar
- Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité—Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC 29425, USA
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome 00179, Italy
| | - Timothy B Weng
- Department of Neurology, Dell Medical School at The University of Texas Austin, Austin, TX 78712, USA
- Department of Diagnostic Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo 0372, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0372, Norway
| | - Carolee J Winstein
- Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA 90033, USA
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - George F Wittenberg
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
- GRECC, HERL, Department of Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA 15213, USA
| | - Kristin A Wong
- Department of Physical Medicine & Rehabilitation, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC 29425, USA
| | - Sook-Lei Liew
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Amy F Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York City, NY 10021, USA
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2
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Olafson ER, Sperber C, Jamison KW, Bowren MD, Boes AD, Andrushko JW, Borich MR, Boyd LA, Cassidy JM, Conforto AB, Cramer SC, Dula AN, Geranmayeh F, Hordacre B, Jahanshad N, Kautz SA, Lo B, MacIntosh BJ, Piras F, Robertson AD, Seo NJ, Soekadar SR, Thomopoulos SI, Vecchio D, Weng TB, Westlye LT, Winstein CJ, Wittenberg GF, Wong KA, Thompson PM, Liew SL, Kuceyeski AF. Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.19.545638. [PMID: 37693419 PMCID: PMC10491132 DOI: 10.1101/2023.06.19.545638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.
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Affiliation(s)
- Emily R Olafson
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Keith W Jamison
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Mark D Bowren
- Department of Neurology, Carver College of Medicine, Iowa City, IA, USA
| | - Aaron D Boes
- Departments of Neurology, Psychiatry, and Pediatrics, Carver College of Medicine, Iowa City, IA, USA
| | - Justin W Andrushko
- Department of Physical Therapy, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Michael R Borich
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Lara A Boyd
- Department of Physical Therapy, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Jessica M Cassidy
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adriana B Conforto
- Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paolo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Steven C Cramer
- Dept. Neurology, UCLA; California Rehabilitation Institute, Los Angeles, CA, USA
| | - Adrienne N Dula
- Department of Neurology, Dell Medical School at The University of Texas Austin, Austin, TX, USA
| | - Fatemeh Geranmayeh
- Clinical Language and Cognition Group. Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Brenton Hordacre
- Innovation, Implementation and Clinical Translation (IIMPACT) in Health, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC, USA
| | - Steven A Kautz
- Department of Health Sciences & Research, Medical University of South Carolina, Charleston, SC, USA
- Ralph H Johnson VA Health Care System, Charleston, SC, USA
| | - Bethany Lo
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA
| | - Bradley J MacIntosh
- Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Computational Radiology and Artificial Intelligence (CRAI), Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Andrew D Robertson
- Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Schlegel-UW Research Institute for Aging, Waterloo, ON, Canada
| | - Na Jin Seo
- Department of Health Sciences & Research, Medical University of South Carolina, Charleston, SC, USA
- Ralph H Johnson VA Health Care System, Charleston, SC, USA
- Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Surjo R Soekadar
- Dept. of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC, USA
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Timothy B Weng
- Department of Neurology, Dell Medical School at The University of Texas Austin, Austin, TX, USA
- Department of Diagnostic Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX, USA
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Carolee J Winstein
- Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, USA
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - George F Wittenberg
- Departments of Neurology, Bioengineering, Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
- GRECC, HERL, Department of Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Kristin A Wong
- Department of Physical Medicine & Rehabilitation, Dell Medical School, University of Texas at Austin, Austin, TX, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Charleston, SC, USA
| | - Sook-Lei Liew
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Amy F Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
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3
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Toba MN, Malherbe C, Godefroy O, Rushmore RJ, Zavaglia M, Maatoug R, Mandonnet E, Valero-Cabré A, Hilgetag CC. Reply: Inhibition between human brain areas or methodological artefact? Brain 2020; 143:e39. [PMID: 32413896 DOI: 10.1093/brain/awaa093] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Monica N Toba
- Laboratory of Functional Neurosciences (EA 4559), University of Picardie Jules Verne, Amiens, France.,FRONTLAB Team, Cerebral Dynamics, Plasticity and Rehabilitation Group, Paris Brain Institute, ICM, Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F-75013, and IHU-A-ICM, Paris, France
| | - Caroline Malherbe
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Neurology, Head and Neuro Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Olivier Godefroy
- Laboratory of Functional Neurosciences (EA 4559), University of Picardie Jules Verne, Amiens, France.,Department of Neurology, Amiens University Hospital, Amiens, France
| | - R Jarrett Rushmore
- Laboratory of Cerebral Dynamics, Plasticity and Rehabilitation, Boston University School of Medicine, Boston, MA 02118, USA
| | - Melissa Zavaglia
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Focus Area Health, Jacobs University Bremen, Germany
| | - Redwan Maatoug
- FRONTLAB Team, Cerebral Dynamics, Plasticity and Rehabilitation Group, Paris Brain Institute, ICM, Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F-75013, and IHU-A-ICM, Paris, France
| | - Emmanuel Mandonnet
- Department of Neurosurgery, Lariboisière Hospital, APHP, Paris, France, and University Paris 7, Paris, France
| | - Antoni Valero-Cabré
- FRONTLAB Team, Cerebral Dynamics, Plasticity and Rehabilitation Group, Paris Brain Institute, ICM, Sorbonne Universités, UPMC Paris 06, Inserm UMR S 1127, CNRS UMR 7225, F-75013, and IHU-A-ICM, Paris, France.,Laboratory of Cerebral Dynamics, Plasticity and Rehabilitation, Boston University School of Medicine, Boston, MA 02118, USA.,Cognitive Neuroscience and Information Technology Research Program, Open University of Catalonia (UOC), Barcelona, Catalunya, Spain
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Health Sciences Department, Boston University, 635 Commonwealth Ave. Boston, MA 02215, USA
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