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Systematic validation of structural brain networks in cerebral small vessel disease.

ABSTRACT: Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability.Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.

SUBMITTER: Dewenter A

PROVIDER: S-EPMC9125482 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Systematic validation of structural brain networks in cerebral small vessel disease.

Dewenter Anna A Gesierich Benno B Ter Telgte Annemieke A Wiegertjes Kim K Cai Mengfei M Jacob Mina A MA Marques José P JP Norris David G DG Franzmeier Nicolai N de Leeuw Frank-Erik FE Tuladhar Anil M AM Duering Marco M

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20211220 6

Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration a ...[more]

PMID: 34929104

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Project description:Background Cerebral small-vessel disease (cSVD) is an important cause of stroke and vascular dementia. Most cases are multifactorial, but an emerging minority have a monogenic cause. While NOTCH3 is the best-known gene, several others have been reported. We aimed to summarize the cerebral phenotypes associated with these more recent cSVD genes. Methods and Results We performed a systematic review (PROSPERO [International Prospective Register of Systematic Reviews]: CRD42020196720), searching Medline/Embase (conception to July 2020) for any language publications describing COL4A1/2, TREX1, HTRA1, ADA2, or CTSA pathogenic variant carriers. We extracted data about individuals' characteristics and clinical and vascular radiological cerebral phenotypes. We summarized phenotype frequencies per gene, comparing patterns across genes. We screened 6485 publications including 402, and extracted data on 390 individuals with COL4A1, 123 with TREX1, 44 with HTRA1 homozygous, 41 with COL4A2, 346 with ADA2, 82 with HTRA1 heterozygous, and 14 with CTSA. Mean age ranged from 15 (ADA2) to 59 years (HTRA1 heterozygotes). Clinical phenotype frequencies varied widely: stroke, 9% (TREX1) to 52% (HTRA1 heterozygotes); cognitive features, 0% (ADA2) to 64% (HTRA1 homozygotes); and psychiatric features, 0% (COL4A2; ADA2) to 57% (CTSA). Among individuals with neuroimaging, vascular radiological phenotypes appeared common, ranging from 62% (ADA2) to 100% (HTRA1 homozygotes; CTSA). White matter lesions were the most common pathology, except in ADA2 and COL4A2 cases, where ischemic and hemorrhagic lesions dominated, respectively. Conclusions There appear to be differences in cerebral manifestations across cSVD genes. Vascular radiological changes were more common than clinical neurological phenotypes, and present in the majority of individuals with reported neuroimaging. However, these results may be affected by age and biases inherent to case reports. In the future, better characterization of associated phenotypes, as well as insights from population-based studies, should improve our understanding of monogenic cSVD to inform genetic testing, guide clinical management, and help unravel underlying disease mechanisms.

Dataset Information

Systematic validation of structural brain networks in cerebral small vessel disease.

Publications

Systematic validation of structural brain networks in cerebral small vessel disease.

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