BriefCase

The Aidoc BriefCase software utilizes an artificial intelligence algorithm to analyze abdominal CT scans for suspected Intra-abdominal Free Gas (IFG), aiming to expedite radiological triage. It functions by providing rapid notifications and non-diagnostic preview images to radiologists, thereby assisting in the prioritization of potentially critical cases within the existing standard of care workflow without altering original images or serving as a diagnostic device.

Aidoc's BriefCase is a radiological computer-aided triage and notification software designed to analyze abdominal CT images for the suspected presence of Intra-abdominal Free Gas (IFG). The system employs an artificial intelligence algorithm and comprises three main modules: the Aidoc Hospital Server for image acquisition, the Aidoc Cloud Server for image processing, and the Aidoc Worklist Application which provides radiologists with notifications. Upon detecting potential IFG, BriefCase sends a notification, including a compressed, non-diagnostic preview image, to the radiologist's desktop, functioning in parallel with standard image interpretation workflows without altering original medical images or removing cases from the standard reading queue. The primary goal of BriefCase is to assist in workflow triage by flagging and communicating suspected IFG findings to expedite radiologist review and prioritization. Performance data from a pivotal retrospective study on 184 cases (67 positive, 117 negative) demonstrated a sensitivity of 91.0% (95% CI: 81.5%, 96.7%) and a specificity of 88.9% (95% CI: 81.7%, 94.0%) for identifying IFG, exceeding the 80% performance goal. Furthermore, a secondary analysis on 22 true positive cases from two US sites indicated that BriefCase's mean time-to-notification (4.4 minutes) was significantly faster than the standard-of-care mean time-to-exam-open (94.1 minutes), resulting in a mean time saving of 89.7 minutes. The device is intended for use in conjunction with other patient information and professional judgment, serving as an aid for triage rather than a standalone diagnostic tool, with clinicians remaining responsible for viewing full images per standard of care.

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. Beyond the supplemental dataset showing consistent performance across some scanner manufacturers, what is the detailed performance breakdown (sensitivity, specificity) of the AI algorithm with less common CT scanner models, varying image acquisition parameters (e.g., slice thickness, reconstruction kernels), or in patients with significant image artifacts or atypical abdominal anatomy?; What is the quantifiable impact of BriefCase on downstream clinical outcomes, such as time to appropriate intervention for Intra-abdominal Free Gas, reduction in diagnostic errors, or changes in patient morbidity, beyond the reported reduction in time-to-exam-open?; What are the ongoing validation, quality control, and algorithm update mechanisms for the BriefCase software to ensure its performance remains robust, adapts to new data or evolving presentations of Intra-abdominal Free Gas, and maintains accuracy over time in diverse clinical settings?; How does the BriefCase system differentiate true Intra-abdominal Free Gas from potential mimics or confounding findings on abdominal CT scans, and what are the common imaging characteristics of false positive and false negative notifications generated by the AI algorithm?; Considering the system architecture involving an Aidoc Hospital Server, Aidoc Cloud Server, and Aidoc Worklist Application, what are the specific measures for data security, patient privacy (e.g., efficacy of de-identification), and system interoperability with diverse hospital IT infrastructures, including various PACS and RIS environments?