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CINA CHEST is a radiological computer aided triage and notification software indicated for use in the analysis of Chest and Thoraco-abdominal CT angiography. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and communicating suspected positive findings of (1) Chest CT angiography for Pulmonary Embolism (PE) and (2) Chest or Thoraco-abdominal CT angiography for Aortic Dissection (AD).

CINA CHEST uses an artificial intelligence algorithm to analyze images and highlight cases with detected PE and AD on a standalone Web application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected PE or AD findings. Notifications include compressed preview images that are meant for informational purposes only, and are not intended for diagnostic use beyond notification. The device does not alter the original medical image, and it is not intended to be used as a diagnostic device.

The results of CINA CHEST are intended to be used in conjunction with other patient information and based on professional judgment to assist with triage/prioritization of medical images. Notified clinicians are ultimately responsible for reviewing full images per the standard of care.

CINA CHEST is a radiological computer-assisted triage and notification software device.

The software system is based on algorithm-programmed components and is comprised of a standard off-the-shelf operating system and additional image processing applications.

DICOM images are received, recorded and filtered before processing. The series are processed chronologically by running algorithms on each series to detect suspected positive findings of a pulmonary embolism (PE) or an aortic dissection (AD), then notifications on the flagged series are sent to the Worklist Application.

The Worklist Application (on premise) displays the pop-up notifications of new studies with suspected findings when they come in, and provides both active and passive notifications. Active notifications are in the form of a small pop-up containing patient name, accession number and the type of suspected findings (PE or AD). All the chest and thoraco-abdominal CT angiography studies received by CINA CHEST device are displayed in the worklist and those on which the algorithms have detected a suspected finding (PE or AD) are marked with an icon (i.e., passive notification). In addition, a compressed, small black and white image that is marked "not for diagnostic use" is displayed as a preview function. This compressed preview is meant for informational purposes only, does not contain any marking of the findings, and is not intended for primary diagnosis beyond notification. Presenting the radiologist with notification facilitates earlier triage by allowing one to prioritize images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.

Here's a detailed breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided FDA 510(k) summary for CINA CHEST:

Acceptance Criteria and Reported Device Performance

Study Details

1. Sample sizes used for the test set and the data provenance:

   • Pulmonary Embolism (PE): 396 clinical anonymized cases.
   • Aortic Dissection (AD): 298 clinical anonymized cases.
   • Data Provenance: Retrospective, multicenter study. Data was provided from multiple US clinical sites (230 US cities for PE, and 200 US cities for AD).

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: "Several US-board-certified radiologist readers." The exact number is not specified beyond "several".
   • Qualifications: US-board-certified radiologists. No specific years of experience are mentioned.

3. Adjudication method for the test set:

   • The ground truth was established by "concurrence of several US-board-certified radiologist readers." This implies a consensus-based adjudication, but the specific method (e.g., majority vote, unanimous agreement, or an independent adjudicator in case of disagreement) is not explicitly detailed.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, an MRMC comparative effectiveness study was not reported. The study described is a standalone performance evaluation of the CINA CHEST software against a ground truth. It assesses the device's ability to identify PE and AD cases for triage, not the improvement of human readers with AI assistance.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, a standalone study was done. The document explicitly states: "Avicenna.Al conducted a retrospective, multicenter and blinded study with the CINA CHEST software with the primary endpoint to evaluate the software's performance..." and later refers to "The results of the standalone assessment study demonstrated an overall agreement (Accuracy)..." This confirms the study evaluated the algorithm's performance in isolation.

6. The type of ground truth used:

   • Expert Consensus. The ground truth was "established by concurrence of several US-board-certified radiologist readers."

7. The sample size for the training set:

   • The document does not specify the sample size for the training set. It only details the test set used for performance evaluation.

8. How the ground truth for the training set was established:

   • Since the training set sample size is not provided, the method for establishing its ground truth is also not detailed in this document. It is common for AI algorithms to be trained on data with ground truth established by expert radiologists or pathology, but this specific information is absent here.

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