Psychiatric practice critically needs objective, biomarker-based assessments to improve diagnostic accuracy and treatment strategies. Differential diagnosis, the process of distinguishing between conditions with similar symptoms, is particularly challenging in psychiatry. This study explores the potential of near-infrared spectroscopy (NIRS) neuroimaging as a clinically viable tool to support differential diagnosis for individuals presenting with depressive symptoms across various psychiatric disorders.
This multi-site replication study, conducted across seven hospitals in Japan, investigated the effectiveness of NIRS in differentiating between major depressive disorder (MDD), bipolar disorder, and schizophrenia in patients exhibiting depressive symptoms. The research involved 673 patients (315 women, 358 men) diagnosed with these psychiatric disorders and 1007 healthy volunteers (530 women, 477 men). The study leveraged a brief verbal fluency task (under 3 minutes) to induce fronto-temporal cortical haemodynamic responses, which were then measured using NIRS. The spatiotemporal characteristics of these brain responses were analyzed to assess the accuracy of single-subject classification for differential diagnosis.
An algorithm was developed using data from one site and subsequently validated using data from the remaining six sites. The findings demonstrated that frontal haemodynamic patterns identified by NIRS effectively distinguished between patients with MDD and those with bipolar disorder or schizophrenia, all presenting with depressive symptoms. The accuracy rate was 74.6% for differentiating MDD from the other disorders and 85.5% for identifying bipolar disorder or schizophrenia when compared to MDD.
These results indicate that neuroimaging-guided differential diagnosis, utilizing NIRS, holds significant promise as a biomarker in psychiatry. This approach could substantially contribute to personalized care within clinical settings by offering a more objective method for distinguishing between psychiatric disorders that manifest with overlapping depressive symptoms. Further research is needed to examine the influence of clinical variables such as age and sex, and systemic factors like autonomic nervous system activity, to further refine the accuracy of NIRS-based classification. Improving the precision of differential diagnosis through tools like NIRS is crucial for tailoring effective and individualized treatment plans for patients with complex psychiatric conditions.
