Quantifying Pharmacodynamics in a Mouse Inflammation Model Via CARS and SRS Imaging Paired with Machine Learning Analysis

The onset and progression of dermal inflammation are easy to diagnose, but challenging to quantify, stage, and measure. CARS and SRS imaging are modalities capable of providing insight into the dynamics of structural and drug/fluid concentration changes throughout a time course of tissue imaging. This work displays two main avenues of exploration using dermatitis-induced mouse models. First, we track inflammation development and resolution over a four-day time course, capturing CARS and SRS image data at multiple time points to use in a machine learning (ML) based approach trained to classify the extent of inflammation in the provided images. Second, we treat mice with anti-inflammatory agents to determine whether these agents truly help with inflammation resolution, using our ML-based approach trained on structural and concentration rich images as a proxy for the pharmacodynamic response. We additionally use ML interpretability methods to aid in the justification of our results.