Interpretable Models for Detecting and Monitoring Elevated Intracranial
  Pressure
Darryl Hannan Steven C. Nesbit Ximing Wen Glen Smith Qiao Zhang Alberto Goffi Vincent Chan Michael J. Morris John C. Hunninghake Nicholas E. Villalobos Edward Kim Rosina O. Weber Christopher J. MacLellan
Detecting elevated intracranial pressure (ICP) is crucial in diagnosing and
managing various neurological conditions. These fluctuations in pressure are
transmitted to the optic nerve sheath (ONS), resulting in changes to its
diameter, which can then be detected using ultrasound imaging devices. However,
interpreting sonographic images of the ONS can be challenging. In this work, we
propose two systems that actively monitor the ONS diameter throughout an
ultrasound video and make a final prediction as to whether ICP is elevated. To
construct our systems, we leverage subject matter expert (SME) guidance,
structuring our processing pipeline according to their collection procedure,
while also prioritizing interpretability and computational efficiency. We
conduct a number of experiments, demonstrating that our proposed systems are
able to outperform various baselines. One of our SMEs then manually validates
our top system's performance, lending further credibility to our approach while
demonstrating its potential utility in a clinical setting.