Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry

Abstract

Neuromelanin-sensitive MRI is a burgeoning non-invasive neuroimaging method with an increasing number of applications in psychiatric research. This MRI modality is sensitive to the concentration of neuromelanin, which is synthesized from intracellular catecholamines and accumulates in catecholaminergic nuclei including the dopaminergic substantia nigra and the noradrenergic locus coeruleus. Emerging data suggest the utility of neuromelanin-sensitive MRI as a proxy measure for variability in catecholamine metabolism and function, even in the absence of catecholaminergic cell loss. Given the importance of catecholamine function to several psychiatric disorders and their treatments, neuromelanin-sensitive MRI is ideally positioned as an informative and easy-to-acquire catecholaminergic index. In this review paper, we examine basic aspects of neuromelanin and neuromelanin-sensitive MRI and focus on its psychiatric applications in the contexts of mechanistic research and biomarker development. We discuss ongoing debates and state-of-the-art research into the mechanisms of the neuromelanin-sensitive MRI contrast, standardized protocols and optimized analytic approaches, and application of cutting-edge methods such as machine learning and artificial intelligence to enhance the feasibility and predictive power of neuromelanin-sensitive-MRI-based tools. We finally lay out important future directions to allow neuromelanin-sensitive-MRI to fulfill its potential as a key component of the research, and ultimately clinical, toolbox in psychiatry.

Fig. 1. Anatomy of catecholaminergic nuclei, neuromelanin synthesis, and neuromelanin-sensitive MRI.

Whole brain view (top) indicates the levels of two brainstem slices (solid black lines) corresponding to the midbrain (left) and the pons (right), where the substantia nigra (SN) and ventral tegmental area (VTA; together, SN-VTA), and locus coeruleus (LC) can be respectively visualized. Below, neuromelanin-sensitive MRI (NM-MRI) images are shown (axial view; midbrain/SN-VTA on the left and pons/LC on the right) from a non-clinical individual (with no diagnosis of neuropsychiatric disorders), with the bottom row representing simulated increases in NM-MRI contrast under different psychiatric disorders (note that images are enhanced to exaggerate effects for visual clarity). In the center, from top to bottom, a schematic shows different steps of the neuromelanin synthesis pathways for dopamine and norepinephrine (where copper participates and accumulates more prominently than iron).

Fig. 2. Clinical applications of SN-VTA NM-MRI.

a Midbrain contrast maps (axial view) showing SN-VTA from individual with schizophrenia (top) and depression (middle), and a non-clinical individual without either diagnosis (bottom) [145]. Reprinted from Biological Psychiatry, Volume 64, Issue 5, Shibata et al., “Use of Neuromelanin-Sensitive MRI to Distinguish Schizophrenic and Depressive Patients and Healthy Individuals Based on Signal Alterations in the Substantia Nigra and Locus Coeruleus,” 401-406, Copyright (2008) with permission from Elsevier. b Univariate voxelwise analysis identifies SN-VTA voxels where NM-MRI contrast is higher in cocaine users versus controls (left: significant voxels; right: bar plots and receiver operating characteristic curves) [167]. Reprinted with permission from the American Journal of Psychiatry, 177:11, Fig. 2, pages 1038-1047 (Copyright © 2020). American Psychiatric Association. All Rights Reserved. c Multi-voxel pattern analysis (MVPA) of SN-VTA NM-MRI contrast shows ability to predict severity of psychosis out of sample (left: model weight map; right: predicted versus actual severity) [11]. Reprinted from JAMA Psychiatry Volume 81, Issue 2, Wengler et al., “Generalizability and Out-of-Sample Predictive Ability of Associations Between Neuromelanin-Sensitive Magnetic Resonance Imaging and Psychosis in Antipsychotic-Free Individuals,” 1038-1047, Copyright (2024) with permission from American Medical Association.

Fig. 3. Measurement of LC NM-MRI contrast and its clinical and behavioral correlates.

a NM-MRI template centered on the pons. b Magnification of (a) overlaid with an overinclusive LC mask allowing measurement of contrast at multiple rostrocaudal levels of the LC (rainbow colors). c Pons of a representative subject in NM-MRI space. LC NM-MRI contrast is calculated relative to the central pons (white circle). d–f Magnification of (c) with warped overinclusive LC mask overlaid (yellow). This mask is eroded to localize a cross section of the core of the LC on each slice [60]. Reprinted from Human Brain Mapping Volume 44, Issue 9, Sibahi et al., “Characterization of an automated method to segment the human locus coeruleus,” 3913-3925, Copyright (2023) with permission from Wiley. g LC NM-MRI contrast reduction in Alzheimer’s disease (tau+ individuals) [66]. Reprinted from Neuropsychopharmacology Volume 47, Issue 5, Cassidy et al., “Association of locus coeruleus integrity with Braak stage and neuropsychiatric symptom severity in Alzheimer’s disease.,” 1128-1138, Copyright (2022) with permission from Springer Nature. h LC NM-MRI contrast elevation in post-traumatic stress disorder (PTSD) relative to controls (HC) [67]. Reprinted from Biological Psychiatry, McCall et al., “Evidence for locus coeruleus-norepinephrine system abnormality in military PTSD revealed by neuromelanin-sensitive MRI,” Copyright (2024) with permission from Elsevier. i LC NM-MRI contrast correlates with aversive learning [152]. Reprinted from PNAS Volume 115, Issue 9, Hammerer et al., “Locus coeruleus integrity in old age is selectively related to memories linked with salient negative events,” 2228-2233, Licensed under CC BY 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/. CNR: contrast ratio.

Fig. 4. A lab-to-clinic pipeline for NM-MRI-based biomarkers.

Sequential phases for biomarker development (following Abi-Dargham and Horga [185]) are shown on the left (blue shades), with specific NM-MRI examples corresponding to each phase (light gray boxes in the center). The current state of the field is depicted by checkmarks (addressed to some extent), an ellipsis (in progress), or an x mark (unaddressed). These phases are approximately paired with sequential steps in method development (right, green shades) that are especially relevant for each phase. Modified from Nature Medicine Volume 22, Issue 11, Abi-Dargham and Horga, “The search for imaging biomarkers in psychiatric disorders,” 1248-55, Copyright (2016) with permission from Springer Nature.