Characterization of Brain Abnormalities in Lactational Neurodevelopmental Poly I:C Rat Model of Schizophrenia and Depression Using Machine-Learning and Quantitative MRI.

BACKGROUND

A recent neurodevelopmental rat model, utilizing lactational exposure to polyriboinosinic-polyribocytidilic acid (Poly I:C) leads to mimics of behavioral phenotypes resembling schizophrenia-like symptoms in male offspring and depression-like symptoms in female offspring.

PURPOSE

To identify mechanisms of neuronal abnormalities in lactational Poly I:C offspring using quantitative MRI (qMRI) tools.

STUDY TYPE

Prospective.

ANIMAL MODEL

Twenty Poly I:C rats and 20 healthy control rats, age 130 postnatal day.

FIELD STRENGTH/SEQUENCE: 7 T. Multiflip-angle FLASH protocol for T mapping; multi-echo spin-echo T-mapping protocol; echo planar imaging protocol for diffusion tensor imaging.

ASSESSMENT

Nursing dams were injected with the viral mimic Poly I:C or saline (control group). In adulthood, quantitative maps of T, T, proton density, and five diffusion metrics were generated for the offsprings. Seven regions of interest (ROIs) were segmented, followed by extracting 10 quantitative features for each ROI.

STATISTICAL TESTS

Random forest machine learning (ML) tool was employed to identify MRI markers of disease and classify Poly I:C rats from healthy controls based on quantitative features.

RESULTS

Poly I:C rats were identified from controls with an accuracy of 82.5 ± 25.9% for females and 85.0 ± 24.0% for males. Poly I:C females exhibited differences mainly in diffusion-derived parameters in the thalamus and the medial prefrontal cortex (MPFC), while males displayed changes primarily in diffusion-derived parameters in the corpus callosum and MPFC.

DATA CONCLUSION

qMRI shows potential for identifying sex-specific brain abnormalities in the Poly I:C model of neurodevelopmental disorders.

LEVEL OF EVIDENCE

NA TECHNICAL EFFICACY: Stage 2.