AutoChamber is an AI-powered software tool designed to analyze both non-contrast and contrast-enhanced chest CT scans to automatically measure and report volumes of cardiac chambers including left atrium, left ventricle, right atrium, right ventricle, and left ventricular wall. It assists healthcare providers by providing quantitative imaging data that helps identify conditions such as enlarged heart and left ventricular hypertrophy, thus aiding in further clinical evaluation and management of cardiovascular risk.
AI-powered quantitative imaging tool that measures and reports cardiac chambers volumes from non-contrast and contrast-enhanced chest CT scans to aid physicians in investigating signs of enlarged heart and related conditions.
AI uses deep learning model to identify cardiac chambers in DICOM CT scans, calculates chamber volumes by pixel counting, provides measurements adjusted by body surface area and percentile reference data, and outputs volumetric values and cardiothoracic ratio. User must validate ROI placement; software is post-processing only.
Software verification and validation tests demonstrated that AutoChamber meets all functional requirements. Clinical validation was based on retrospective analyses comparing AutoChamber measurements with cardiac MRI in 5003 cases, with paired non-contrast and contrast-enhanced CT scans in 1433 patients, and comparisons with reference devices in additional cohorts. No prospective studies were required. Animal, sterilization, and biocompatibility testing were not applicable.
No predicate devices specified
Submission
3/22/2024
FDA Approval
10/10/2024
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