ArticleActa radiologica open2021
Utility of manual fractional anisotropy measurements in the management of patients with Parkinson disease: a feasibility study with a 1.5-T magnetic resonance imaging system.
Article in Acta radiologica open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Early Alterations in De Novo Parkinson's Disease Revealed by Diffusion Tensor Imaging: Preliminary Study.Diagnostics (Basel, Switzerland) · 2025Article
- Parkinson's disease in the spinal cord: An exploratory study to establish T2*w, MTR and diffusion-weighted imaging metric values.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Article
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2 authors at 1 institution in 1 country.
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Abstract
backgroundDiffusion tensor imaging has emerged as a promising tool for quantitative analysis of neuronal damage in Parkinson disease, with potential value for diagnostic and prognostic evaluation. PURPOSE: The aim of this study was to examine Parkinson disease-associated alterations in specific brain regions revealed by diffusion tensor imaging and how such alterations correlate with clinical variables. MATERIAL AND
methodsDiffusion tensor imaging was performed on 42 Parkinson disease patients and 20 healthy controls with a 1.5-T scanner. Manual fractional anisotropy measurements were performed for the ventral, intermediate, and dorsal portions of the substantia nigra, as well as for the cerebral peduncles, putamen, thalamus, and supplementary motor area. The correlation analysis between these measurements and the clinical variables was performed using
resultsCompared to healthy controls, Parkinson disease patients had significantly reduced fractional anisotropy values in the substantia nigra (
conclusionManual fractional anisotropy measurements in the substantia nigra were confirmed to be feasible with a 1.5-T scanner. Diffusion tensor imaging data can be used as a reliable biomarker of Parkinson disease that can be used to support diagnosis, prognosis, and progression/treatment monitoring.
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