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 T₁ mapping; multi-echo spin-echo T₂-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 T₁, T₂, 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.