chAI Dx develops research-stage clinical decision support tools that infer intracranial pressure (ICP) from routine brain MRI using physics-informed, CSF-sensitive imaging techniques. By providing uncertainty‑aware quantitative insights, the platform aims to complement clinicians’ judgment in cases where invasive ICP measurements are unavailable or ambiguous, without altering existing diagnostic workflows. The current prototype demonstrates interactive mock demos with illustrative data for clinician feedback.
Funding
Funding not disclosed
Founders
Product
Problem
Intracranial pressure (ICP) is typically measured invasively, providing only episodic data and leaving clinicians with uncertainty when MRI scans appear normal but clinical suspicion remains high.
Solution
chAI Dx builds a research-stage decision‑support platform that derives non‑invasive, physics‑informed estimates of ICP from routine, CSF‑sensitive brain MRI scans. By imposing known physical constraints on the MRI data, the system generates quantitative ICP values together with uncertainty metrics. These outputs are presented as supplemental information that clinicians can consult alongside existing diagnostic workflows, helping to clarify borderline cases without requiring changes to current imaging protocols.
Target Audience
Primary users are neurologists, neurosurgeons, and radiologists who evaluate patients with suspected intracranial hypertension and need additional quantitative insight when conventional imaging is inconclusive.
Features
- Physics-informed modeling that ties MRI signal characteristics to cerebrospinal fluid dynamics
- Extraction of quantitative ICP estimates from standard brain MRI sequences
- Uncertainty-aware reporting that conveys confidence intervals for each estimate
- Integration as a decision‑support overlay that does not alter existing MRI acquisition or interpretation workflows
- Interactive mock‑demo interface for clinician feedback and iterative refinement