A group of scientists has published a response to critical comments on their study comparing two neuroimaging methods—neuromelanin (NM) and free-water (FW) imaging—for the early diagnosis of Parkinson’s disease (PD). In their response, the researchers clarified methodological aspects that had prompted questions from colleagues, including image registration, the influence of patients’ age and scanning parameters.
Image registration and template selection
The authors of the original study acknowledged that the choice of template for image registration can affect the analysis results, particularly when studying white matter. However, they emphasised that for subcortical structures such as the substantia nigra (SN), where the anisotropy contrast of fractional anisotropy (FA) is low, the optimal registration approach remains a matter of debate. In their work, they used the ANTs SyN framework, which, according to previous studies, provides high accuracy in aligning subcortical structures, comparable to manual segmentation.
The researchers clarified that the diffusion tensor imaging (DTI) data were not registered directly using the MNI template. Instead, a two-stage process was used: first, the DTI volumes were aligned with each patient’s native T1-weighted image, and then inverse transformations were used to map the SN mask into native DTI space. This approach, based on the high-resolution ATAG atlas, has previously been used successfully to detect elevated free-water levels in the substantia nigra in idiopathic rapid eye movement sleep behaviour disorder and Parkinson’s disease. An identical processing pipeline was applied to both FW and NM data, suggesting that registration errors do not fully explain the absence of between-group differences in FW measures.
The influence of age and scanning parameters
The scientists agreed that age and Parkinson’s disease affect free-water measures in the same direction, whereas their effects on the neuromelanin signal differ within the age range studied. To account for the possible influence of age and sex on the results, these variables were included as covariates in the logistic regression models used for ROC analysis. Even after adjustment for these factors, NM measures continued to outperform FW measures in diagnostic accuracy. Multivariate regression analysis also showed that NM volume was not significantly associated with age in any subregion, whereas FW measures were associated with age in several subregions in both the early-stage PD group and the pooled sample.
Regarding repetition time (TR), the researchers noted that the TR in their study’s main cohort was 9225 ms, exceeding the recommended threshold of 6000 ms for FW imaging. Despite this, no significant differences in FW measures were found between the early-stage PD and control groups in the main cohort. A shorter TR (3100 ms) and a smaller voxel size were used in the external validation cohort, consistent with standard clinical parameters. Although these parameters may reduce sensitivity to subtle FW changes, the diagnostic pattern in the external cohort was similar to that in the main cohort. The authors consider the consistency of results across two cohorts with different scanning protocols a strength of their study, but acknowledge the need for further research using optimised diffusion sequence parameters.
Conceptual framing of the study
The researchers emphasised that their work does not position free water in the substantia nigra as a standalone diagnostic biomarker for Parkinson’s disease. The study’s primary aim was to compare the diagnostic performance of NM and FW imaging under identical scanning and data-processing conditions in a strictly defined group of patients with early-stage PD. The conclusion that NM imaging is superior in this context does not diminish the potential usefulness of FW imaging overall.
In their discussion of the work, the authors acknowledged that their findings apply to the specific task of distinguishing early-stage PD patients from controls. They also emphasised the importance of future studies assessing NM and FW imaging in more heterogeneous clinical populations, including atypical forms of parkinsonism, to determine their translational value in real-world diagnostic practice. The scientists thanked their colleagues for raising critical questions and agreed that further methodological refinement and validation in diverse clinical groups are necessary to determine the optimal role of NM and FW imaging in PD diagnosis.
