BriefCase-Triage: CARE (Clinical AI Reasoning Engine) Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device is a radiological computer aided triage and notification software indicated for use in the analysis of contrast and non-contrast CT images of the chest, abdomen, or chest/abdomen, in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive findings, per study, of:

Pneumothorax;
Pericardial effusion;
Large aortic aneurysm
Shoulder Fracture or Dislocation

The device flags cases with at least one suspected finding to assist with triage/prioritization of medical images. The device will provide a flag for each suspected finding within this study. A preview image will be provided for each distinct suspected finding.

BriefCase-Triage uses a foundation model-based artificial intelligence (AI) system to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected findings. Notifications include compressed preview images for each suspected finding that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical images and is not intended to be used as a diagnostic device.

The results of BriefCase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.

Device Description

BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device is a radiological computer-assisted triage and notification software device. The software is based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.

The BriefCase-Triage device receives images that match meta-data criteria according to the BriefCase-Triage predefined set of parameters. Then, the BriefCase-Triage processes the series chronologically, identifying cases with suspected positive finding(s) and selecting key slice(s) for preview. BriefCase-Triage output consists of suspected positive flag/notification regarding the existence of each finding in the analyzed study. Each finding includes a Representative Key Slice. The Key Slice(s) may be presented to the users as compressed, low-quality, grayscale, preview images with the date and time imprinted. The previews are not annotated and are captioned with the disclaimer "Not for diagnostic use, for prioritization only" according to the device requirement from the Image Communication Platform (ICP).

Presenting the users with worklist prioritization facilitates efficient triage by prompting the user to assess the relevant original images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study proving device performance, based on the provided FDA 510(k) clearance letter:

1. Acceptance Criteria and Reported Device Performance

The core acceptance criteria are based on standalone performance metrics for each of the four clinical indications.

Indication	Acceptance Criteria (Default Operating Point)	Reported Device Performance (Default Operating Point)
Pneumothorax	AUC > 0.95 (lower bound 95% CI); Sensitivity > 80%; Specificity > 80%	AUC: 98.9 (95% CI: 97.8-99.7) Sensitivity: 94.8% (95% CI: 89.5%-97.9%) Specificity: 95.9% (95% CI: 91.3%-98.5%)
Pericardial effusion	AUC > 0.95 (lower bound 95% CI); Sensitivity > 80%; Specificity > 80%	AUC: 99.1 (95% CI: 98.0-99.8) Sensitivity: 96.4% (95% CI: 91.7%-98.8%) Specificity: 96.5% (95% CI: 92.0%-98.8%)
Large aortic aneurysm	AUC > 0.95 (lower bound 95% CI); Sensitivity > 80%; Specificity > 80%	AUC: 99.5 (95% CI: 98.9-99.9) Sensitivity: 97.1% (95% CI: 92.7%-99.2%) Specificity: 97.2% (95% CI: 92.9%-99.2%)
Shoulder fracture or dislocation	AUC > 0.95 (lower bound 95% CI); Sensitivity > 80%; Specificity > 80%	AUC: 99.9 (95% CI: 99.7-100) Sensitivity: 97.8% (95% CI: 93.7%-99.5%) Specificity: 99.3% (95% CI: 96.2%-100.0%)
Time-to-notification	Comparability with predicate device in time savings to standard of care.	Subject Device Mean: 49.9 seconds (95% CI: 46.4-53.5) Predicate Device Mean: 10.7 seconds (95% CI: 10.5-10.9) Note: While the subject device's time is longer, the conclusion states comparability regarding time savings to standard of care review, implying it still offers significant benefit.

Study Proving Device Meets Acceptance Criteria

The study conducted was a retrospective, blinded, multicenter standalone performance analysis.

2. Sample size used for the test set and the data provenance:
* Sample Size: N = 280 for each of the 4 clinical indications, totaling 772 unique scans across all indications.
* Data Provenance: The cases were collected from 6 US-based clinical sites, representing diverse geographic locations and site types. The data was "distinct in time or center from the cases used to train the algorithm," and "sequestered from algorithm development activities." This indicates a high level of independence for the test set. The data is retrospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
* Number of Experts: Three (3)
* Qualifications: Senior board-certified radiologists.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
* The document states ground truth was "determined by three senior board-certified radiologists." It does not explicitly mention an adjudication method like 2+1 or 3+1, but the plural "radiologists" and the method of "determined by" suggests a consensus or majority opinion among these three, rather than individual opinions without interaction.

5. 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 MRMC comparative effectiveness study was explicitly described. The study was a "standalone performance analysis" of the software itself. The comparison of "time-to-notification" with the predicate device implies a comparison of software performance characteristics related to triage, not a study of human readers with and without AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
* Yes, a standalone performance study was done. The document explicitly refers to it as a "standalone performance analysis" to "evaluate the software's performance."

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
* Expert Consensus: The ground truth was established by "three senior board-certified radiologists."

8. The sample size for the training set:
* The document does not specify the exact sample size for the training set. It only mentions that the "algorithm was trained during software development on images of the pathology."

9. How the ground truth for the training set was established:
* The ground truth for the training set was established by "labeled ('tagged') images. In that process, each image in the training dataset was tagged based on the presence of the critical finding." The method or type of tagging (e.g., by experts, automated, etc.) is not detailed, but it's implied that there was a process of assigning labels/tags to the images to indicate the presence or absence of the target pathologies.

Summary

FDA 510(k) Clearance Letter - BriefCase-Triage: CARE Multi-Triage CT

Page 1

U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov

Doc ID # 04017.08.03

Aidoc Medical, Ltd.
Amalia Schreier
SVP of Regulation and Legal
34 Hamasger St.
Tel Aviv, 6721119
Israel

Re: K253578
Trade/Device Name: BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device
Regulation Number: 21 CFR 892.2080
Regulation Name: Radiological Computer Aided Triage And Notification Software
Regulatory Class: Class II
Product Code: QAS
Dated: January 27, 2026
Received: January 27, 2026

Dear Amalia Schreier:

We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"

March 26, 2026

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Aidoc Medical, Ltd.
Amalia Schreier
SVP of Regulation and Legal
34 Hamasger St.
Tel Aviv, 6721119
Israel

March 26, 2026

Dear Amalia Schreier:

U.S. Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov

K253578 - Amalia Schreier Page 2

(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

Your device is also subject to, among other requirements, the Quality Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13484 clause 8.3 (Nonconforming product), and ISO 13485 clause 8.5 (Corrective and preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the Quality Management System Regulation (QMSR) (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

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K253578 - Amalia Schreier Page 3

Sincerely,

Jessica Lamb
Assistant Director
Imaging Software
DHT8B: Division of Radiological Imaging
Devices and Electronic Products
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health

Enclosure

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Indications for Use

Please type in the marketing application/submission number, if it is known. This textbox will be left blank for original applications/submissions.	K253578
Please provide the device trade name(s).

BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device

Please provide your Indications for Use below.

Pneumothorax;
Pericardial effusion;
Large aortic aneurysm
Shoulder Fracture or Dislocation

Please select the types of uses (select one or both, as applicable).	☒ Prescription Use (21 CFR 801 Subpart D)
	☐ Over-The-Counter Use (21 CFR 801 Subpart C)

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510(K) SUMMARY

BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device

Submitter: Aidoc Medical, Ltd.
34 Hamasger St.
Tel-Aviv, Israel, 6721119
Phone: +972-73-7946870
Contact Person: Amalia Schreier, LL.M, SVP Regulation and Legal
Date Prepared: February 12, 2026

Name of Device:
BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device

Classification Name: Radiological computer-assisted triage and notification software device
Regulatory Class: Class II
Product Code: QAS, QFM
Predicate Device: Briefcase-Triage for AD (K251406)

Device Description

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The algorithm was trained during software development on images of the pathology. As is customary in the field of machine learning, deep learning algorithm development consisted of training on labeled ("tagged") images. In that process, each image in the training dataset was tagged based on the presence of the critical finding.

Intended Use / Indications for Use

Pneumothorax;
Pericardial effusion;
Large aortic aneurysm
Shoulder Fracture or Dislocation

Summary of Technological Characteristics

BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device is substantially equivalent to BriefCase-Triage for Aortic Dissection (AD) (K251406). As explained in more detail below, BriefCase-Triage device has the same intended use and similar indications for use, technological characteristics, and principles of operation as the previously cleared predicate BriefCase-Triage for AD (K251406). While the specific clinical indications differ, each indication remains independently time-sensitive. Additionally, both devices have modules fine tuned from a locked foundation model.

A substantial equivalence chart comparing the similarities and differences between the BriefCase-Triage and its predicate device is provided in Table 1 below. The differences in the technological characteristics do not raise different questions of safety or effectiveness. Standalone testing demonstrates that the subject device is substantially equivalent to its predicate device.

Both the predicate and subject device are radiological computer-aided triage and notification software programs. Both devices are artificial intelligence, deep-learning algorithms incorporated in software components for use with

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DICOM format CT images, PACS, and radiology workstations.

Both devices are intended to aid in triage and prioritization of radiological images and utilize the same design of deep learning algorithm trained on medical images. Both devices are intended to provide the specialists with notifications and unannotated, compressed, low-quality, and grayscale preview images of suspect studies for the purpose of preemptive triage.

The subject and predicate Briefcase-Triage devices raise the same types of safety and effectiveness questions, namely, accurate triage of findings within the processed study. It is important to note that, like the predicate, the subject device neither removes cases from the standard of care reading queue nor de-prioritized cases. Both devices operate in parallel with the standard of care, which remains the default option for all cases.

A table comparing the key features of the subject and the predicate devices is provided below.

Table 1. Key Feature Comparison

	Subject Device	Predicate Device
	Aidoc's BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation	Aidoc's Briefcase-Triage for AD (K251406)
Intended Use / Indications for Use	BriefCase-Triage: CARE (Clinical AI Reasoning Engine) Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device is a radiological computer aided triage and notification software indicated for use in the analysis of contrast and non-contrast CT images of the chest, abdomen, or chest/abdomen, in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive findings, per study, of: 1. Pneumothorax; 2. Pericardial effusion; 3. Large aortic aneurysm 4. Shoulder Fracture or Dislocation The device flags cases with at least one suspected finding to assist with triage/prioritization of medical images. The device will provide a flag for each suspected	BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of CT chest, abdomen, or chest/abdomen exams with contrast (CTA and CT with contrast) in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspected positive findings of Aortic Dissection (AD) pathology. BriefCase-Triage uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected findings. Notifications include compressed preview images that are meant for informational purposes

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	Subject Device	Predicate Device
	Aidoc's BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation	Aidoc's Briefcase-Triage for AD (K251406)
	finding within this study. A preview image will be provided for each distinct suspected finding. BriefCase-Triage uses a foundation model-based artificial intelligence (AI) system to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected findings. Notifications include compressed preview images for each suspected finding that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical images and is not intended to be used as a diagnostic device. The results of BriefCase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.	only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of BriefCase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/ prioritization.
User population	Hospital networks and appropriately trained medical specialists	Hospital networks and appropriately trained medical specialists
Clinical Indication	1. Pneumothorax; 2. Pericardial effusion; 3. Large aortic aneurysm; 4. Shoulder fracture or dislocation	1. Aortic Dissection
Anatomical region of interest	Chest, abdomen, or chest/abdomen	Chest, abdomen, or chest/abdomen

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	Subject Device	Predicate Device
	Aidoc's BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation	Aidoc's Briefcase-Triage for AD (K251406)
Data acquisition protocol	Contrast and non-contrast CT images	CTA and CT with contrast
Notification-only (/notification alerts), parallel workflow tool	Yes	Yes
Images format	DICOM	DICOM
Interference with standard workflow	No. No cases are removed from desktop app or deprioritized	No. No cases are removed from desktop app or deprioritized
Inclusion/Exclusion criteria for clinical performance testing	Inclusion Criteria: • Patient population: CT scans performed on adults/transitional adults ≥ 18 years of age • Slice thickness: 0.5 mm - 5.0 mm axial • Contrast-enhanced and non-contrast CT images* Exclusion Criteria • All studies that have an inadequate field of view. *Contrast and non-contrast CT images of the chest, abdomen, or chest/abdomen as applicable to indication-specific inclusion criteria.	Inclusion Criteria • Scans performed on adults/transitional adolescents ≥ 18 years of age. • CT exams with contrast (CTA and CT with contrast) that include at least part of the aorta • Slice thickness 0.5 mm - 5.0 mm Exclusion Criteria • All studies that have an inadequate field of view.

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	Subject Device	Predicate Device
	Aidoc's BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation	Aidoc's Briefcase-Triage for AD (K251406)
Additional Operating Points	4 Additional Operating Points	4 Additional Operating Points
Algorithm	Multi-triage module, locked artificial intelligence algorithm fine tuned from a foundation model.	Single-triage module, locked, artificial intelligence algorithm fine tuned from a foundation model.
Structure	- Integrated with image routing module via image communication platform (ICP) (image acquisition). - Algorithm module (image processing) - Integrated with desktop application for workflow integration (feed and non-diagnostic Image Viewer).	- Integrated with image routing module via image communication platform (ICP) (image acquisition). - Algorithm module (image processing) - Integrated with desktop application for workflow integration (feed and non-diagnostic Image Viewer).

Performance Data

Pivotal Study Summary

Aidoc conducted a retrospective, blinded, multicenter study with the BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation software to evaluate the standalone performance analysis individually for each of the 4 clinical indications supported by BriefCase-Triage. The standalone performance study evaluated the software's performance in identifying contrast-enhanced and non-contrast CT images in cases from 6 US-based clinical sites, representing diverse geographic locations and site types.

Each of 4-clinical indications had a sample size of N = 280 each, with 772 unique scans included across device indications.

The study compared the software's performance to the ground truth, as determined by three senior board-certified radiologists. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm. Test pivotal study data was sequestered from algorithm development activities, and use of the data is managed by appropriate Quality Management System procedures.

Primary endpoints were pre-specified standalone performance goal (PG) of area under the curve (AUC) > 0.95 lower bound 95% confidence interval for the finding level receiver operating characteristic (ROC) curve. Secondary

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endpoints were sensitivity, specificity and BriefCase time-to-notification compared to the predicate device. Positive Predictive Value (PPV), Negative Predictive Value (NPV), Positive Likelihood Ratio (PLR), and Negative Likelihood Ratio (NLR) were also assessed.

AUC, Sensitivity and Specificity

AUC, Sensitivity and Specificity of 4-clinical indication exceeded the pre-specified performance goal (PG) of area under the curve (AUC) > 0.95 lower bound 95% confidence interval for the finding level receiver operating characteristic (ROC) curve and 80% for both sensitivity and specificity, as further detailed in Table 2 below:

Table 2. AUC, Sensitivity, Specificity

Indication 1: Pneumothorax

AUC	Sensitivity (Se)	Specificity (Sp)	Case Count
AUC	95% CI	Se	95% CI
98.9	97.8-99.7	94.8%	89.5%-97.9%

Indication 2: Pericardial effusion

AUC	Sensitivity (Se)	Specificity (Sp)	Case Count
AUC	95% CI	Se	95% CI
99.1	98.0-99.8	96.4%	91.7%-98.8%

Indication 3: Large aortic aneurysm

AUC	Sensitivity (Se)	Specificity (Sp)	Case Count
AUC	95% CI	Se	95% CI
99.5	98.9-99.9	97.1%	92.7%-99.2%

Indication 4: Shoulder fracture or dislocation

AUC	Sensitivity (Se)	Specificity (Sp)	Case Count
AUC	95% CI	Se	95% CI
99.9	99.7-100	97.8%	93.7%-99.5%

Time to Notification

In addition, the time-to-notification metric observed for the BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation software was compared to the equivalent metric of the predicate device. The Briefcase-Triage time-to-notification includes the time to get the DICOM exam, de-identify it, upload it to the cloud, analyze and send a notification on a positive suspect result back to the desktop application.

The BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation software time-to-notification was measured for all True Positive cases (i.e., identified as positive both by the reviewers as well as the Briefcase-Triage device) and is given in Table 3 below. The Table also displays the same metric reported for the predicate Briefcase-Triage for AD.

The time-to-notification results obtained for the subject Briefcase-Triage device show comparability with the predicate with regard to time savings to the standard of care review. The BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation mean time-to-notification for the subject device triage was 49.9 seconds (95% CI: 46.4-53.5). The time-to-notification for

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the predicate Briefcase-Triage for AD was 10.7 seconds (95% CI: 10.5-10.9).

Table 3. Time-to-notification comparison for Briefcase-Triage devices (Seconds)

Time-to-notification	Mean Estimate (seconds)	N	95% Lower CL	95% Upper CL	Median	IQR
Predicate K251406 Processing Time	10.7	212	10.5	10.9	10.4	0.4
BriefCase-Triage and compatible image communication platform Time-to-notification	49.9	536	46.4	53.5	38.8	33.1

Thus, the reported similar time-to-notification data demonstrates that when using the subject BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation the clinician may have the same benefit in time-to-notification as with the predicate Briefcase-Triage for AD.

Table 4 presents the mean age of patients whose scans were reviewed for BriefCase-Triage, with the standard deviation. Gender distribution, Scanner distribution and slice thickness can also be found in Tables 5-7 below.

Table 4. Descriptive Statistics for Age

Indication 1: Pneumothorax

Age (Years)
Mean
60.4

Indication 2: Pericardial effusion

Age (Years)
Mean
61.2

Indication 3: Large aortic aneurysm

Age (Years)
Mean
66.6

Indication 4: Shoulder fracture or dislocation

Age (Years)
Mean
61.5

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Table 5. Descriptive Statistics for Gender

Indication 1: Pneumothorax

*5 cases were unknown for gender, 4 positive and 1 negative

Gender	Female		Male		All
	N	%	N	%	N	%
Positive	47	17.1%	83	30.2%	130	47.3%
Negative	80	29.1%	65	23.6%	145	52.7%
All	127	46.2%	148	53.8%	275	100.0%

Indication 2: Pericardial effusion

Gender	Female		Male		All
	N	%	N	%	N	%
Positive	76	27.1%	62	22.1%	138	49.3%
Negative	80	28.6%	62	22.1%	142	50.7%
All	156	55.7%	124	44.3%	280	100.0%

Indication 3: Large aortic aneurysm

Gender	Female		Male		All
	N	%	N	%	N	%
Positive	42	15.0%	96	34.3%	138	49.3%
Negative	82	29.3%	60	21.4%	142	50.7%
All	124	44.3%	156	55.7%	280	100.0%

Indication 4: Shoulder fracture or dislocation

*8 cases were unknown for gender, all positive

Gender	Female		Male		All
	N	%	N	%	N	%
Positive	48	17.6%	80	29.4%	128	47.1%
Negative	76	27.9%	68	25.0%	144	52.9%
All	124	45.6%	148	54.4%	272	100%

Table 6. Frequency Distribution of Manufacturer

Indication 1: Pneumothorax

Manufacturer	N	%
GE MEDICAL SYSTEMS	80	28.6%
Philips	68	24.3%
SIEMENS	69	24.6%
TOSHIBA	63	22.5%
Total	280	100%

Indication 2: Pericardial effusion

Manufacturer	N	%
GE MEDICAL SYSTEMS	100	35.70%

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| Philips | 63 | 22.5% |
| SIEMENS | 60 | 21.4% |
| TOSHIBA | 57 | 20.4% |
| Total | 280 | 100% |

Indication 3: Large aortic aneurysm

Manufacturer	N	%
GE MEDICAL SYSTEMS	95	33.90%
Philips	63	22.5%
SIEMENS	66	23.60%
TOSHIBA	56	20.0%
Total	280	100

Indication 4: Shoulder fracture or dislocation

Manufacturer	N	%
GE MEDICAL SYSTEMS	92	32.9%
Philips	58	20.7%
SIEMENS	66	23.6%
TOSHIBA	64	22.9%
Total	280	100%

Table 7. Frequency Distribution of Slice Thickness

Indication 1: Pneumothorax

Slice Thickness (mm)	N	%
0.5-1	67	23.9%
1-2.5	71	25.4%
2.5-5	142	50.7%
Total	280	100%

Indication 2: Pericardial effusion

Slice Thickness (mm)	N	%
0.5-1	56	20.0%
1-2.5	91	32.5%
2.5-5	133	47.5%
Total	280	100%

Indication 3: Large aortic aneurysm

Slice Thickness (mm)	N	%
0.5-1	63	22.5%
1-2.5	84	30.0%
2.5-5	133	47.5%
Total	280	100%

Indication 4: Shoulder fracture or dislocation

Slice Thickness (mm)	N	%
0.5-1	85	30.4%
1-2.5	73	26.1%
2.5-5	122	43.6%
Total	280	100%

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Clinical Subgroups and Confounders:

Pathologies present in negative cases: Inflammatory; Oncology; Heart and Vascular; Trauma; Chronic Disease; Fully Negative; and None of the above

Additional Operating Points

In addition to the default (balanced) operating point that was selected to maximize both sensitivity and specificity, a total of four additional operating points (AOP1-AOP4) were selected for each indication, allowing to enhance sensitivity or specificity while maintaining a lower bound 95% confidence interval of 80% for specificity and sensitivity (respectively) for each operating point. AOP1 corresponds to the highest sensitivity point estimate with acceptable specificity. AOP4 corresponds to the highest specificity point estimate with acceptable sensitivity. AOP2 and AOP3 represent operating points between the two, while maintaining acceptable performance.

Table 8. Sensitivity, Specificity for AOP1-AOP4

Indication 1: Pneumothorax

AOP1

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
98.5%	94.7%-99.8%

AOP2

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
97.8%	93.6%-99.5%

AOP3

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
90.3%	84.0%-94.7%

AOP4

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
88.8%	82.2%-93.6%

Indication 2: Pericardial effusion

AOP1

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
97.1%	92.7%-99.2%

AOP2

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
95.7%	90.8%-98.4%

AOP3

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
94.2%	88.9%-97.5%

AOP4

Sensitivity (Se)	Specificity (Sp)
Se	95% CI

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| 91.3% | 85.3%-95.4% | 100.0% | 97.4%-100.0% |

Indication 3: Large aortic aneurysm

AOP1

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
97.8%	93.8%-99.5%

AOP2

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
96.4%	91.7%-98.8%

AOP3

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
94.9%	89.8%-97.9%

AOP4

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
87.7%	81.0%-92.7%

Indication 4: Shoulder fracture or dislocation

AOP1

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
100.0%	97.3%-100.0%

AOP2

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
99.3%	96.0%-100.0%

AOP3

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
92.6%	86.9%-96.4%

AOP4

Sensitivity (Se)	Specificity (Sp)
Se	95% CI
89.0%	82.5%-93.7%

In summary, performance goals were achieved for the default and four additional operating points. Combined with the comparison results of time-to-notification metric with the predicate device, these data establish the achievement by the subject Briefcase-Triage of preemptive triage in the range of several minutes.

Cybersecurity

Cybersecurity has been incorporated into the software development lifecycle in alignment with Section 524B of the FD&C Act and FDA cybersecurity guidance. Aidoc has implemented a risk-based approach to cybersecurity, including secure design practices, vulnerability assessments, a Software Bill of Materials (SBOM), and penetration testing. These efforts support the safety, effectiveness, and resilience of the software against cybersecurity threats.

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Conclusions

The subject BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation device and the predicate Briefcase-Triage for AD device (K251406) are intended to aid in prioritization and triage of radiological images for the indications for suspected positive findings of incidental pulmonary embolism pathologies. Both devices are software components consisting of deep learning AI algorithms that process images and produce analysis results, which are displayed to the user by a prioritization alert and a compressed, low-quality, grayscale, unannotated preview image(s). In both devices, the labeling clearly states that the devices are not for diagnostic use and instructs the user to further evaluate and diagnose based only on the original images in the local PACS.

Both devices operate in parallel to the standard of care workflow in the sense that they do not change the original image, do not provide any marking on the output preview, do not remove images from the standard of care FIFO queue and do not de-prioritize cases, thus not disturbing standard interpretation of the images. Both devices notify the radiologist of time-sensitive critical cases within the range of several minutes, and thus contribute similarly to the standard of care workflow turnaround time reduction through preemptive triage.

The subject BriefCase-Triage: CARE Multi-Triage CT for Pneumothorax; Pericardial effusion; Large aortic aneurysm; Shoulder fracture or dislocation is thus substantially equivalent to the predicate Briefcase-Triage for AD (K251406).

Regulation Number and Section

§ 892.2080 Radiological computer aided triage and notification software.

(a)
Identification. Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
e.g., improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.