An integrated and scalable rodent cage system enabling continuous computer vision-based behavioral analysis and AI-enhanced digital biomarker development

Abstract

1Home cage monitoring enables continuous observation of animals in familiar environments. It has large utility in preclinical testing, mechanistic studies, animal husbandry, and the general practice of the Replacement, Reduction, Refinement (3R) principles. Despite its acknowledged utility, home cage monitoring has not been broadly adopted. This is mainly due to the complexity of the tasks that must be solved to have a successful system that includes hardware and sensor development, data management, machine vision expertise, behavioral expertise, support, and user training. Here, we describe the Digital In Vivo System (DIV Sys), a modern end-to-end system for video-based rodent home cage monitoring. The DIV Sys consists of a cloud-based study design, monitoring, display, and visualization app (DIV App), local hardware for data acquisition cages (DAX), a machine learning model for tracking mice (mHydraNet) optimized for speed and accuracy, a study display and visualization app, and an advanced behavior quantification workbench (DIV Data). The platform seamlessly manages terabytes of video data in the cloud and is built around enterprise-level security and data standards. Collaborative tools enable teams across geographical locations to work together. As a demonstration of its utility, we used DIV Sys to analyze over a century of mouse videos across multiple geographic locations. We also characterized home cage behavior of 8 mouse strains and carried out customized video analysis. Together, we present a scalable home cage monitoring system for advanced behavior quantification for the rodent research community.