Background: This study aimed to evaluate portable functional near-infrared spectroscopy (fNIRS) device as an adjunct diagnostic tool for bipolar and unipolar disorders while performing cognitive tasks.
Methods: 150 participants were divided into three groups including bipolar, unipolar disorder, and healthy controls (50:50:50), matched by age, gender, and family history of mood disorder. Hemodynamics in the frontal cortex were monitored by fNIRS during the Stroop Color-Word Test and Verbal Fluency Test. The GLM compared the differences in oxy-hemoglobin levels between the two groups. The Receiver Operating Characteristic (ROC) graph was generated for each neuroanatomical area.
Results: For people with BD group, the area under the ROC curve (AUC) for the left orbitofrontal cortex was maximal during the VFT [AUC = 0.727, 95%CI = 0.617-0.824]. The Youden's index reached a peak (0.40) at the optimal cut-point value (HbO2 cutoff <0.180 μmol/ml for BD) in which the sensitivity was 82 %; specificity was 58 %; PPV was 0.66; NPV was 0.76 and correct classification rate was 70 %. Regarding the UD group, during VFT, the highest value AUC [AUC = 0.822, 95%CI = 0.740-0.903] was recorded in the left dorsolateral prefrontal cortex with the optimal cut-off value (HbO2cutoff ≥0.163 μmol/ml for healthy controls; <0.163 for unipolar disorder), the sensitivity was 72 %; specificity was 82 %; PPV was 0.80; NPV was 0.75, correct classification rate was 77 %, and the Youden's index was 0.54.
Conclusion: Assessing hemodynamics during VFT using portable fNIRS offers the potential as an adjunct diagnostic tool for mood disorders in low-resource environments.
Keywords: Artificial intelligence; Bipolar disorder; Depression; Diagnosis; Machine learning; Neuroimaging.
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