SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

High resolution multi-parametric probabilistic in vivo atlas of dorsolateral nigral hyperintensity via 7 T MRI.

Sci Data · 2025-06-07

DOI: 10.1038/s41597-025-05325-wPMID: 40483299

Open accessResearch Support, Non-U.S. Gov't; Dataset; data-paper; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

The role of Nigrosome 1 (N1) in neurodegeneration and motor disorders, particularly in Parkinson's disease (PD), is increasingly recognized. The study of this region using quantitative measures, such as iron quantification through Quantitative Susceptibility Mapping (QSM), can provide enlightening insights into some pathological features of these diseases representing important biomarkers. However, the small size and the vanishing contrast with respect to the surrounding substantia nigra in PD patients make the segmentation of N1 challenging. For this reason, we provide a probabilistic atlas of the N1 portion corresponding to the swallow-tail hyperintensity, hereafter referred to as the Dorsolateral Nigral Hyperintensity (DNH), created on a high-resolution multi-parametric template from T1-weighted, T2*-weighted, and QSM images acquired in vivo at 7 T. The atlas also includes quantitative T2* and R2* templates and is provided in the MNI standard space. It aims to facilitate the study of N1, avoiding operator-dependent biases in segmentations, and allowing the standardisation of the quantitative assessment.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.