BriefCase

BriefCase is a software device utilizing an artificial intelligence deep-learning algorithm to analyze head CT Angiography images for suspected Brain Aneurysms over 5mm, aiming to expedite workflow triage for medical specialists. It functions by providing notifications of potential positive cases to a desktop application, running in parallel to standard care, to facilitate earlier review of critical findings without altering the original diagnostic images.

BriefCase is a radiological computer-aided triage and notification software developed to analyze head CT Angio (CTA) images for the detection of potential Brain Aneurysms (BA) larger than 5 mm. Its primary function is to assist hospital networks and trained medical specialists by improving workflow triage through the flagging and communication of suspected positive BA cases. The system operates using an artificial intelligence algorithm that analyzes images and delivers notifications of suspect cases to a standalone desktop application, running in parallel with, and not replacing, the standard of care image interpretation. These notifications include compressed preview images, which are for informational purposes only and not for diagnostic use, ensuring the original medical image remains unaltered and is the basis for any clinical decisions. The technological foundation of BriefCase is a deep-learning algorithm specifically trained on head CTA images to identify BAs. The system architecture is comprised of three key modules: the Aidoc Hospital Server (AHS) for DICOM image acquisition, de-identification, and filtering; the Aidoc Cloud Server (ACS) for image processing using the AI algorithm; and the Aidoc Worklist Application, which provides the user interface for receiving notifications and viewing the worklist. A retrospective, multicenter pivotal study involving 268 cases (96 positive BA, 172 negative) demonstrated the software's efficacy, achieving a sensitivity of 88.5% and a specificity of 89.5%. Furthermore, the study highlighted significant potential for time-saving in clinical workflows, with the BriefCase system delivering notifications for true positive BA cases at a mean time of 4.2 minutes, compared to a mean standard-of-care time-to-exam-open of 89.4 minutes, suggesting an average time saving of over an hour.

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. How does the algorithm's performance, with a sensitivity of 88.5% and specificity of 89.5% for brain aneurysms >5mm, change for aneurysms at or slightly below this size threshold, or with varying morphologies and locations?; What are the typical integration challenges and timelines for deploying the three-module BriefCase system (Aidoc Hospital Server, Aidoc Cloud Server, Aidoc Worklist Application) within existing hospital PACS and IT infrastructures?; Given the Positive Predictive Value (PPV) of 42.4%, what is the anticipated impact on radiologist workload from reviewing false positive notifications, and are there features to help manage or learn from these instances?; The study reported a mean time-to-notification of 4.2 minutes; how does this time vary with fluctuations in image data load or network latency between the hospital server and the cloud processing unit?; How robust is the BriefCase algorithm to variations in head CT Angiography (CTA) acquisition parameters, contrast timing, and image noise levels across different scanner models and manufacturers beyond those included in the pivotal study?