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

Hanna Jokinen^{1

2}, Juha Koikkalainen^{3

4

5}, Hanna M Laakso^{1

2}, Susanna Melkas¹, Tuomas Nieminen³, Antti Brander⁶, Antti Korvenoja⁷, Daniel Rueckert⁸, Frederik Barkhof^{9

10}, Philip Scheltens^{11

12}, Reinhold Schmidt¹³, Franz Fazekas¹³, Sofia Madureira¹⁴, Ana Verdelho¹⁴, Anders Wallin¹⁵, Lars-Olof Wahlund¹⁶, Gunhild Waldemar¹⁷, Hugues Chabriat¹⁸, Michael Hennerici¹⁹, John O'Brien²⁰, Domenico Inzitari^{21

22}, Jyrki Lötjönen^{3

4

23}, Leonardo Pantoni²⁴, Timo Erkinjuntti¹

Affiliations

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.).

PMID: 31699021
PMCID: PMC6924941
DOI: 10.1161/STROKEAHA.119.026170

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

Hanna Jokinen et al. Stroke. 2020 Jan.

. 2020 Jan;51(1):170-178.

doi: 10.1161/STROKEAHA.119.026170. Epub 2019 Nov 8.

Authors

Affiliations

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.).

PMID: 31699021
PMCID: PMC6924941
DOI: 10.1161/STROKEAHA.119.026170

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.

Keywords: brain; cerebral small vessel diseases; humans; image processing, computer assisted; neuropsychology.

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Figures

**Figure 1.**
Flowchart of the image analysis methods (detailed description given in the online-only Data Supplement). 3D indicates 3 dimensional; EPVS, enlarged perivascular space; FLAIR, fluid-attenuated inversion recovery; and WMH, white matter hyperintensities.

**Figure 2.**
Examples of the segmentation results for brain structures, white matter hyperintensities (WMH), lacunes, cortical infarcts, and enlarged perivascular spaces (EPVS). **Top**, Original T1/fluid-attenuated inversion recovery images. **Bottom**, Segmentation results overlaid with color on the original images.

See this image and copyright information in PMC

Comment in

Global small vessel disease brain changes predict cognitive decline.
Fyfe I. Fyfe I. Nat Rev Neurol. 2020 Jan;16(1):2-3. doi: 10.1038/s41582-019-0296-8. Nat Rev Neurol. 2020. PMID: 31776476 No abstract available.

References

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

Affiliations

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

Authors

Affiliations

Abstract

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References

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Medical