Vollständiger Abstract
Worum geht es in dieser Arbeit?
Vascular cognitive impairment and dementia (VCID) is a leading modifiable contributor to dementia, accounting for an estimated 27-33% of attributable dementia cases. Neuroimaging is central to detection, phenotyping, and longitudinal monitoring. This neuroradiology-focused review integrates the STRIVE-2 imaging lexicon with the VasCog-2 clinical framework and reviews the advanced MRI techniques most pertinent to VCID, spanning clinically established to emerging research approaches: arterial spin labelling, diffusion tensor imaging including peak width of skeletonised mean diffusivity (PSMD), quantitative susceptibility mapping, vessel architecture imaging, and resting-state functional MRI. Unlike previous reviews, we consolidate operational quantitative thresholds already informing decisions (the Staals total small-vessel-disease score, longitudinal white matter hyperintensity progression linked to dementia risk, microbleed and cortical superficial siderosis (cSS) criteria for anti-amyloid therapy eligibility, and validated PSMD reference ranges) and we critically address gaps between research-grade acquisitions and routine clinical workflows. Automated segmentation and structured reporting are transitioning into deployment, expanding the radiologist's role to combine pattern recognition with quantitative characterisation. We outline current limitations of standardisation, reproducibility, and external validation that remain prerequisites before quantitative VCID imaging achieves formal regulatory biomarker qualification.
Abstract: PubMed · Datensatz
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Daniel Bell
- Quelle
- Radiopaedia.org
- Publikation
- 2024-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
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- ISSN / ISBN
- Nicht angegeben
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Zitierfähiger Nachweis
Daniel Bell (2024). BJR|Artificial Intelligence. Radiopaedia.org. https://doi.org/10.1093/bjr/tqag182