Editorial for “Cross‐Scanner Harmonization of Neuromelanin‐Sensitive MRI for Multisite Studies”

In translational neuropsychiatry, the last decades are marked by a dire need of biomarkers. Effective biomarkers would foster a mechanistic understanding of mental disorders, could help to differentiate neurobiological subtypes across diagnostic categories, and may eventually predict treatment response. Alterations in the dopaminergic system feature prominently in pathophysiological theories of several neuropsychiatric disorders, such as schizophrenia, addictions, or Parkinson’s disorder (PD), and accessible proxy measures of the dopamine system are therefore an ideal candidate for clinically meaningful biomarkers. Dopaminergic signaling is involved in a variety of basic and relevant psychological processes including reward processing, motivation, as well as learning and memory functions and alterations in those functions may contribute to the development of neuropsychiatric conditions. For example, pathophysiological theories of addiction posit altered dopaminergic neurotransmission to underlie the attribution of incentive salience to drug-related stimuli. In psychosis, dysregulated firing of dopaminergic neurons has been proposed to elicit aberrant salience for otherwise neutral cues and contribute to the emergence of psychotic symptoms such as delusional ideation. In patients with schizophrenia, molecular imaging based on radiopharmaceuticals provided evidence for a hyperdopaminergic state in the striatum. Here, positron emission tomography with radioligands such as 18Fdihydroxyphenylalanine (DOPA), functioning as precursors of dopamine, is used to measure presynaptic dopamine functioning. In a comparison across several dopamine proxies, a meta-analysis found strong effect sizes for increased striatal dopamine synthesis capacity, dopamine release capacity, and synaptic dopamine release in patients with schizophrenia. Reaching beyond the diagnostic category of schizophrenia, a cross-diagnostic, more dimensional approach linking altered dopaminergic neurotransmission with psychotic symptoms is warranted. However, molecular imaging is expensive, sometimes not feasible for patient samples and increases exposure to radiation. In the last decade, a low-cost, time-efficient alternative based on a metabolized product of dopamine, neuromelanin, has emerged. Neuromelanin-sensitive magnetic resonance imaging (NM-MRI) first gained traction in the field of neurodegenerative disorders. In PD, a relatively broad application of NM-MRI sequences resulted in a meta-analysis confirming high diagnostic accuracy. A more recent study showed that neuromelanin in the substantia nigra is associated with dopamine release capacity in patients with schizophrenia as well as psychotic symptoms. This multimodal study presents a fruitful starting point and presumably will lead to broader use of NM-MRI in patients with schizophrenia. To this purpose and in order to be a clinically useful biomarker, NM-MRI needs to be comparable across different scanners and sites. The study by Wengler et al in the current issue of JMRI aims to enhance reproducibility of NM-MRI sequences in nonclinical individuals. They demonstrated that employing a conventional harmonization method (ComBat) leads to removal of unwanted nonbiological variability (such as scanner effects) while maintaining biological variability associated with age in a large sample of healthy subjects at three study sites and five different scanners. Preprocessing pipelines were aligned across sites and NM-MRI contrast to noise ratio (CNR) maps of the neuromelanin-including region substantia nigra-ventral tegmental area complex were calculated with regard to a reference region according to standards established in the recent literature on NM-MRI. Median CNR was compared by use of ANOVA and found to be significantly different in the raw but not in the harmonized CNR. This was confirmed by a support vector machine classifier, which showed high above-chance accuracy for MRI scanner classification in the raw but not in the harmonized CNR. For both, raw and harmonized voxelwise CNR values, SVR regression could predict age and was not significantly different. This suggested that biologically meaningful variability was preserved by this procedure and therefore ComBat harmonization provides an effective means to harmonize NM-MRI data. This conclusion was elegantly derived by several converging methods of analysis. It remains to be seen if the promising outcomes of harmonization hold up for