Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers

Author:

Olafson Emily R1ORCID,Sperber Christoph2ORCID,Jamison Keith W1,Bowren Mark D3ORCID,Boes Aaron D345ORCID,Andrushko Justin W67,Borich Michael R8,Boyd Lara A69ORCID,Cassidy Jessica M10ORCID,Conforto Adriana B1112,Cramer Steven C13,Dula Adrienne N14,Geranmayeh Fatemeh15,Hordacre Brenton16ORCID,Jahanshad Neda17,Kautz Steven A1819,Tavenner Bethany P20ORCID,MacIntosh Bradley J2122,Piras Fabrizio23,Robertson Andrew D2124,Seo Na Jin181925ORCID,Soekadar Surjo R26,Thomopoulos Sophia I17,Vecchio Daniela23,Weng Timothy B1427,Westlye Lars T2829ORCID,Winstein Carolee J3031,Wittenberg George F32333435,Wong Kristin A36,Thompson Paul M17,Liew Sook-Lei37,Kuceyeski Amy F1ORCID

Affiliation:

1. Department of Radiology, Weill Cornell Medicine , New York City, NY 10021 , USA

2. Department of Neurology, Inselspital, University Hospital Bern, University of Bern , Bern 3012 , Switzerland

3. Department of Neurology, Carver College of Medicine , Iowa City, IA 52242 , USA

4. Department of Psychiatry, Carver College of Medicine , Iowa City, IA 52242 , USA

5. Department of Pediatrics, Carver College of Medicine , Iowa City, IA 52242 , USA

6. Department of Physical Therapy, Faculty of Medicine, The University of British Columbia , Vancouver, BC V6T 1Z4 , Canada

7. Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University , Newcastle upon Tyne NE1 8ST , United Kingdom

8. Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine , Atlanta, GA 30322 , USA

9. Djavad Mowafaghian Centre for Brain Health, University of British Columbia , Vancouver, BC V6T 1Z4 , Canada

10. Department of Health Sciences, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599 , USA

11. Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo , Sao Paolo 05652-900 , Brazil

12. Hospital Israelita Albert Einstein , São Paulo 05652-900 , Brazil

13. Department Neurology, UCLA, California Rehabilitation Institute , Los Angeles, CA 90033 , USA

14. Department of Neurology, Dell Medical School at The University of Texas Austin , Austin, TX 78712 , USA

15. Clinical Language and Cognition Group, Department of Brain Sciences, Imperial College London , London W12 0HS , United Kingdom

16. Innovation, Implementation and Clinical Translation (IIMPACT) in Health, Allied Health and Human Performance, University of South Australia , Adelaide 5000 , Australia

17. Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California , Charleston, SC 29425 , USA

18. Department of Health Sciences & Research, Medical University of South Carolina , Charleston, SC 29425 , USA

19. Ralph H. Johnson VA Health Care System , Charleston, SC 29425 , USA

20. Chan Division of Occupational Science and Occupational Therapy, University of Southern California , Los Angeles, CA 90033 , USA

21. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute , Toronto, ON M4N 3M5 , Canada

22. Computational Radiology and Artificial Intelligence (CRAI), Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital , Oslo 0372 , Norway

23. Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS , Rome 00179 , Italy

24. Schlegel-UW Research Institute for Aging , Waterloo, ON N2J 0E2 , Canada

25. Department of Rehabilitation Sciences, Medical University of South Carolina , Charleston, SC 29425 , USA

26. Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité—Universitätsmedizin Berlin , Berlin 10117 , Germany

27. Department of Diagnostic Medicine, Dell Medical School, The University of Texas at Austin , Austin, TX 78712 , USA

28. Department of Psychology, University of Oslo , Oslo 0372 , Norway

29. NORMENT, Division of Mental Health and Addiction, Oslo University Hospital , Oslo 0372 , Norway

30. Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California , Los Angeles, CA 90033 , USA

31. Department of Neurology, Keck School of Medicine, University of Southern California , Los Angeles, CA 90033 , USA

32. Department of Neurology, University of Pittsburgh , Pittsburgh, PA 15213 , USA

33. Department of Bioengineering, University of Pittsburgh , Pittsburgh, PA 15213 , USA

34. Department of Physical Medicine & Rehabilitation, University of Pittsburgh , Pittsburgh, PA 15213 , USA

35. GRECC, HERL, Department of Veterans Affairs Pittsburgh Healthcare System , Pittsburgh, PA 15213 , USA

36. Department of Physical Medicine & Rehabilitation, Dell Medical School, University of Texas at Austin , Austin, TX 78712 , USA

37. Stevens Neuroimaging and Informatics Institute, University of Southern California , Los Angeles, CA 90033 , USA

Abstract

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 (R2 = 0.210, P < 0.001), performing significantly better than 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 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 R2 = 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.

Funder

Canadian Institutes of Health Research

Michael Smith Foundation for Health Research

National Institute of General Medical Sciences

NIH

Lone Star Stroke Research Consortium

Wellcome Trust

Italian Ministry of Health

Ricerca Corrente 23

National Institute of Child Health and Human Development

European Research Council

Federal Ministry of Education and Research

Enhancing NeuroImaging Genetics

Big Data to Knowledge

Lonestar Stoke

European Union's Horizon 2020

Dept. of Veterans Affairs Rehabilitation Research & Development Service

Enhancing NeuroImaging Genetics through Meta Analysis

Publisher

Oxford University Press (OUP)

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