BriefCase-Triage

Aidoc Medical's BriefCase-Triage is an AI-powered radiological software designed to enhance workflow prioritization in hospital networks by flagging suspect incidental Pulmonary Embolism cases. It utilizes an artificial intelligence algorithm to rapidly analyze contrast-enhanced lung images, providing timely notifications to facilitate clinician assessment without serving as a primary diagnostic tool.

Aidoc Medical, Ltd. has developed BriefCase-Triage, a radiological computer-aided triage and notification software. This device is intended to assist hospital networks and trained medical specialists in workflow prioritization by flagging and communicating suspect cases of incidental Pulmonary Embolism (iPE) pathologies. It uses an artificial intelligence algorithm to analyze contrast-enhanced images that include the lungs in adults and transitional adolescents aged 18 and older, providing notifications with compressed preview images for informational purposes. BriefCase-Triage does not alter original medical images and is not intended for primary diagnostic use, instead aiding in the triage and prioritization of images to facilitate timely assessment by clinicians. Performance studies demonstrated that BriefCase-Triage successfully achieved its primary endpoint goals for sensitivity and specificity, with results of 91.7% and 91.4% respectively. The device also showed significant improvement in time-to-notification compared to a similar product, processing cases in an average of 40.2 seconds. This rapid notification capability contributes to quicker workflow turnaround times for time-sensitive cases. Technologically, BriefCase-Triage is very similar to its predicate, with minor architectural and performance adjustments that do not introduce new safety or effectiveness concerns. Both operate in parallel to standard care workflows, ensuring that cases are not removed or deprioritized, thereby maintaining the integrity of the diagnostic process.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. What specific types of "incidental" pulmonary embolism are best identified by BriefCase-Triage, and what are its limitations for less common presentations?; How does the integration of BriefCase-Triage into existing hospital network PACS systems impact the overall efficiency and potential for alert fatigue among radiologists?; Are there specific patient demographics or image characteristics (e.g., image quality, patient movement) that might negatively affect the accuracy or performance of the AI algorithm?; What are the long-term outcomes for patients whose iPEs were detected and triaged by BriefCase-Triage compared to traditional diagnostic pathways?; Given its non-primary diagnostic role, what validation steps are in place to ensure that clinicians do not over-rely on the system or miss findings not flagged by the AI?