# Integrated evaluation of Nigrosome 1 sign, neuromelanin-sensitive MR and iron deposition

## TL;DR

This study uses MRI techniques to distinguish Parkinson's Disease from healthy individuals by analyzing brain structures and iron deposits.

## Contribution

The study introduces an integrated MRI analysis combining Nigrosome-1 sign, neuromelanin volume, and iron deposition for PD diagnosis.

## Key findings

- Nigrosome-1 sign, neuromelanin volume, and iron susceptibility values significantly differentiate PD from controls.
- A logistic regression model using these parameters achieved 99% accuracy in distinguishing PD from healthy controls.
- Iron deposition in the putamen, red nucleus, and thalamus was most effective in PD discrimination.

## Abstract

To differentiate between Parkinson’s Disease (PD) and healthy controls by using integrated analysis of PD-specific MR findings including deformation of the substantia nigra pars compacta (SNpc), signal loss in neuromelanin (NM) sensitive MRI, and iron deposition in the deep gray matter (DGM) structures.

Patients with PD and healthy controls were recruited between August 2022 and December 2023. All subjects underwent 3 T MRI including a magnetization transfer contrast (MTC) and a double flip angle multi-echo protocol as part of Strategically Acquired Gradient Echo (STAGE). The data analysis included detecting the presence of Nigrosome-1 (N1) sign in the SNpc, signal intensity and volume of NM content and iron quantification through quantitative susceptibility mapping (QSM) in DGMs. The 3D regions of interest were manually demarcated on QSM maps. Mean susceptibility values from global analysis (whole structure) as well as regional high iron analysis (age-based threshold) were extracted for each individual structure. Univariate and multivariate analyses were performed using these parameters.

Nineteen patients with PD (68.0 ± 8.0 years, 10 males, Hoehn and Yahr scale 1 (n = 1), 2 (n = 13), 3 (n = 4), 4 (n = 1)) and 21 healthy controls (68.3 ± 8.6 years, 12 males) were enrolled. Discriminating PD from controls was successful using each method: N1 sign (P < 0.001), NM volume (P < 0.001), susceptibility values of global analysis (caudate, P < 0.001; putamen, P < 0.001; pulvinar, P = 0.006), regional analysis (putamen, P < 0.001; pulvinar, P = 0.009, thalamus, P = 0.008). Stepwise logistic regression analyses were performed, and the best model was created using N1 sign, NM volume, regional analysis (putamen, red nucleus and thalamus) (area under the curve of 0.99).

Integrated analysis of PD specific MR findings including N1 sign, NM volume, and iron content in the DGM structures robustly discriminates between PD and healthy controls.

The online version contains supplementary material available at 10.1007/s11604-025-01858-7.