Different Diffusion Models in the Diagnosis of Brain Microstructural Changes in Post-stroke Depression Patients: A Comparative Study

Objective The study aimed to compare the diagnostic effectiveness of different diffusion models in patients with post-stroke depression (PSD) by examining associated gray matter microstructural changes. Methods Twenty-nine acute cerebral infarction patients (10 with PSD (mean age: 55.20±8.64 years, four female), 19 without PSD (mean age: 63.26±8.69 years, eight female)), and 18 age- and gender-matched healthy people (mean age: 58.67±9.02 years, eight female) were included. Their age, gender, body mass index, education level, insomnia status, and cognitive assessment scores were analyzed. All underwent diffusion spectrum imaging scans. Three diffusion models (diffusion kurtosis imaging (DKI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI)) were used to obtain parameters. Whole-brain analysis was done to find gray matter regions with PSD-related changes and evaluate model efficacy. Results PSD patients had higher depression scores and lower average education levels. Regions like the middle frontal gyrus were studied. In the control and PSD group comparison, NODDI_ODI_p10 in the precuneus had the highest diagnostic efficacy, with an area under the curve (AUC) of 0.817. For the control and non-PSD groups, DKI_MD_p10 in the anterior cingulate gyrus was most effective, AUC = 0.898. In the PSD and non-PSD group comparison, DTI_MD_p25 in the amygdala had the highest efficacy, AUC = 0.816. Conclusion PSD patients show microstructural abnormalities. Diffusion models can help detect early PSD-related damage, with the neurite orientation dispersion and density imaging model showing promise. However, different models have different efficacies in various group comparisons, and more large-scale research is needed to confirm their diagnostic value.