ArticleBrain structure & function2022
Multimodal tract-based MRI metrics outperform whole brain markers in determining cognitive impact of small vessel disease-related brain injury.
Article in Brain structure & function, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06252844 (The Impact of 6-months of Resistance Training on Intrinsic Capacity, Cognition, and Brain/Circulating Biomarkers of Neuroplasticity and Neuroinflammation in Older Adults With Mild Cognitive Impairment), which is not on this map. Cited by 6 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Impact of 6-months of Resistance Training on Intrinsic Capacity, Cognition, and Brain/Circulating Biomarkers of Neuroplasticity and Neuroinflammation in Older Adults With Mild Cognitive Impairment: a Randomized Controlled Trial.
Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
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- Preoperative brain volume loss is associated with postoperative delirium in advanced heart failure patients supported by left ventricular assist device.Scientific reports · 2025Article
- Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment.Brain : a journal of neurology · 2024Article
- Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients.medRxiv : the preprint server for health sciences · 2024Article
- Brain disconnections refine the relationship between brain structure and function.Brain structure & function · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
In cerebral small vessel disease (cSVD), whole brain MRI markers of cSVD-related brain injury explain limited variance to support individualized prediction. Here, we investigate whether considering abnormalities in brain tracts by integrating multimodal metrics from diffusion MRI (dMRI) and structural MRI (sMRI), can better capture cognitive performance in cSVD patients than established approaches based on whole brain markers. We selected 102 patients (73.7 ± 10.2 years old, 59 males) with MRI-visible SVD lesions and both sMRI and dMRI. Conventional linear models using demographics and established whole brain markers were used as benchmark of predicting individual cognitive scores. Multi-modal metrics of 73 major brain tracts were derived from dMRI and sMRI, and used together with established markers as input of a feed-forward artificial neural network (ANN) to predict individual cognitive scores. A feature selection strategy was implemented to reduce the risk of overfitting. Prediction was performed with leave-one-out cross-validation and evaluated with the R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.