Differentiating Treatment-Resistant Depression With and Without Parkinsonism in the Elderly From a Psychiatric Perspective by 99mTc-TRODAT-1 SPECT Imaging

Abstract

Objectives: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists. This study aimed to differentiate elderly treatment-resistant depression (TRD) comorbid with parkinsonism from elderly TRD without Parkinsonism as well as elderly healthy controls using striatum dopamine transporter (DAT) imaging by ^99mTc TRODAT-1 SPECT.

Methods: Three groups were enrolled, including patients with TRD, patients with TRD comorbid with parkinsonism, and healthy controls. To obtain the DAT availability, the specific uptake ratios of the bilateral striatum were evaluated. Linear regression analyses were performed to evaluate the relationship between age and DAT level in the subregions of the striatum. Machine learning was applied to categorize the three groups with 10-fold cross-validation.

Results: The study enrolled 32 patients with TRD ( $66.15\pm 6.82$ ), 36 TRD patients with parkinsonism ( $70.27\pm 5.63$ ), and 74 healthy elderly ( $66.95\pm 10.59$ ). A normative DAT concentration by age was established, providing a reference for clinical use. DAT levels differed among groups (all pairwise p < 0.01), with healthy controls exhibiting the highest levels, followed by patients with TRD, and then TRD patients with parkinsonism. Further, the Fine k-NN classifier emerged as the top performer to achieve 85.7% accuracy.

Conclusions: Besides clinical assessment, dopaminergic assessment may help differentiate parkinsonism from TRD in old age. The findings of lower DAT availability in TRD suggest that TRD may be a prodromal symptom of Parkinson's disease. Psychiatrists should consider comorbid neurodegenerative disorders in elderly, depressed patients and use clinical assessment, neurological examination, and brain imaging for early Parkinson's Disease screening.

Keywords: TRODAT‐SPECT; dopaminergic transporter; machine learning; parkinson's disease; parkinsonism; treatment‐resistant depression.