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Different Diffusion Models in the Diagnosis of Brain Microstructural Changes in Post-stroke Depression Patients: A
Fang Zhang1, Jing Zhang1, Lei Zhang1
1Radiology, Huaibei People's Hospital, Huai Bei, CHN.
Cureus
|April 21, 2025
Summary
Post-stroke depression (PSD) is linked to gray matter changes. Diffusion imaging models like NODDI show promise in detecting early PSD-related brain damage, aiding diagnosis.
Area of Science:
- Neuroimaging
- Neurology
- Radiology
Background:
- Post-stroke depression (PSD) is a common complication following acute cerebral infarction.
- Identifying early microstructural brain changes associated with PSD is crucial for timely diagnosis and intervention.
- Diffusion imaging techniques offer insights into brain tissue microstructure.
Purpose of the Study:
- To compare the diagnostic effectiveness of three diffusion models: diffusion kurtosis imaging (DKI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI).
- To examine associated gray matter microstructural changes in patients with PSD.
- To evaluate the efficacy of these diffusion models in detecting PSD-related brain abnormalities.
Main Methods:
- Inclusion of 29 acute cerebral infarction patients (10 with PSD, 19 without PSD) and 18 healthy controls.
- Acquisition of diffusion spectrum imaging (DSI) data.
- Application of DKI, DTI, and NODDI models to derive microstructural parameters and perform whole-brain analysis.
Main Results:
- NODDI_ODI_p10 in the precuneus showed the highest diagnostic efficacy (AUC=0.817) in the control vs. PSD group comparison.
- DKI_MD_p10 in the anterior cingulate gyrus was most effective (AUC=0.898) in the control vs. non-PSD group comparison.
- DTI_MD_p25 in the amygdala demonstrated the highest efficacy (AUC=0.816) in the PSD vs. non-PSD group comparison.
Conclusions:
- Patients with PSD exhibit distinct gray matter microstructural abnormalities.
- Diffusion models, particularly NODDI, show potential for early detection of PSD-related neural damage.
- Different diffusion models exhibit varying diagnostic efficacies across different patient group comparisons, necessitating further large-scale validation.
