Cross-Scanner Harmonization of Neuromelanin-Sensitive MRI for Multisite Studies

Background: Neuromelanin-sensitive magnetic resonance imaging (NM-MRI) is a validated measure of neuromelanin concentration in the substantia nigra–ventral tegmental area (SN–VTA) complex and is a proxy measure of dopaminergic function with potential as a noninvasive biomarker. The development of generalizable biomarkers requires large-scale samples necessitating harmonization approaches to combine data collected across sites. Purpose: To develop a method to harmonize NM-MRI across scanners and sites. Study Type: Prospective. Population: A total of 128 healthy subjects (18–73 years old; 45% female) from three sites and five MRI scanners. Field Strength/Sequence: 3.0 T; NM-MRI two-dimensional gradient-recalled echo with magnetization-transfer pulse and three-dimensional T1-weighted images. Assessment: NM-MRI contrast (contrast-to-noise ratio [CNR]) maps were calculated and CNR values within the SN–VTA (defined previously by manual tracing on a standardized NM-MRI template) were determined before harmonization (raw CNR) and after ComBat harmonization (harmonized CNR). Scanner differences were assessed by calculating the classification accuracy of a support vector machine (SVM). To assess the effect of harmonization on biological variability, support vector regression (SVR) was used to predict age and the difference in goodness-of-fit (Δr) was calculated as the correlation (between actual and predicted ages) for the harmonized CNR minus the correlation for the raw CNR. Statistical Tests: Permutation tests were used to determine if SVM classification accuracy was above chance level and if SVR Δr was significant. A P-value <0.05 was considered significant. Results: In the raw CNR, SVM MRI scanner classification was above chance level (accuracy = 86.5%). In the harmonized CNR, the accuracy of the SVM was at chance level (accuracy = 29.5%; P = 0.8542). There was no significant difference in age prediction using the raw or harmonized CNR (Δr = −0.06; P = 0.7304). Data Conclusion: ComBat harmonization removes differences in SN–VTA CNR across scanners while preserving biologically meaningful variability associated with age. Level of Evidence: 2. Technical Efficacy: 1.