Global Burden of Small Vessel Disease–Related Brain Changes on MRI Predicts Cognitive and Functional Decline

Author:

Jokinen Hanna12,Koikkalainen Juha345,Laakso Hanna M.12,Melkas Susanna1,Nieminen Tuomas3,Brander Antti6,Korvenoja Antti7,Rueckert Daniel8,Barkhof Frederik910,Scheltens Philip1112,Schmidt Reinhold13,Fazekas Franz13,Madureira Sofia14,Verdelho Ana14,Wallin Anders15,Wahlund Lars-Olof16,Waldemar Gunhild17,Chabriat Hugues18,Hennerici Michael19,O’Brien John20,Inzitari Domenico2122,Lötjönen Jyrki3423,Pantoni Leonardo24,Erkinjuntti Timo1

Affiliation:

1. From the Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital (H.J., H.M.L., S. Melkas, T.E.), Finland

2. Department of Psychology and Logopedics, Faculty of Medicine (H.J., H.M.L.), Finland

3. Combinostics, Ltd, Finland (J.K., T.N., J.L.)

4. VTT Technical Research Centre of Finland (J.K., J.L.)

5. Faculty of Health Sciences, University of Eastern Finland (J.K.)

6. Department of Radiology, Medical Imaging Center, Tampere University Hospital, Finland (A.B.)

7. Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital (A.K.), Finland

8. Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom (D.R.)

9. Department of Radiology and Nuclear Medicine (F.B.), Neuroscience Campus Amsterdam, VU University Medical Center, the Netherlands

10. Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.)

11. Alzheimer Center and Department of Neurology (P.S.), Neuroscience Campus Amsterdam, VU University Medical Center, the Netherlands

12. NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, University College London, United Kingdom (F.B.)

13. Department of Neurology, Medical University of Graz, Austria (R.S., F.F.)

14. Department of Neurosciences, Santa Maria Hospital, University of Lisbon, Portugal (S. Madureira, A.V.)

15. Sahlgrenska Academy, Institute of Neuroscience and Physiology, Section for Psychiatry and Neurochemistry, University of Gothenburg, Sweden (A.W.)

16. Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Sweden (L.-O.W.)

17. Department of Neurology, Danish Dementia Research Centre, Rigshospitalet, University of Copenhagen, Denmark (G.W.)

18. Department of Neurology, Hopital Lariboisiere, APHP and INSERM U1161–University Denis Diderot (DHU NeuroVasc), France (H.C.)

19. Medical Faculty Mannheim, University of Heidelberg, Germany (M.H.)

20. Department of Psychiatry, University of Cambridge, United Kingdom (J.O.)

21. Institute of Neuroscience, Italian National Research Council (D.I.)

22. Department NEUROFARBA, University of Florence, Italy (D.I.)

23. Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Finland (J.L.)

24. L. Sacco Department of Biomedical and Clinical Sciences, University of Milan, Italy (L.P.).

Abstract

Background and Purpose— Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple types of small vessel disease–related brain changes and examined their individual and combined predictive value on cognitive and functional abilities. Methods— Magnetic resonance imaging scans of 560 older individuals from LADIS (Leukoaraiosis and Disability Study) were analyzed using automated atlas- and convolutional neural network–based segmentation methods yielding volumetric measures of white matter hyperintensities, lacunes, enlarged perivascular spaces, chronic cortical infarcts, and global and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years. Results— The strongest predictors of cognitive performance and functional outcome over time were the total volumes of white matter hyperintensities, gray matter, and hippocampi ( P <0.001 for global cognitive function, processing speed, executive functions, and memory and P <0.001 for poor functional outcome). Volumes of lacunes, enlarged perivascular spaces, and cortical infarcts were significantly associated with part of the outcome measures, but their contribution was weaker. In a multivariable linear mixed model, volumes of white matter hyperintensities, lacunes, gray matter, and hippocampi remained as independent predictors of cognitive impairment. A combined measure of these markers based on Z scores strongly predicted cognitive and functional outcomes ( P <0.001) even above the contribution of the individual brain changes. Conclusions— Global burden of small vessel disease–related brain changes as quantified by an image segmentation tool is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of white matter hyperintensities, lacunar, gray matter, and hippocampal volumes could be used as an imaging marker associated with vascular cognitive impairment.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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