EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM (EFAI AASCTA) is a radiological computer aided triage and notification software indicated for use in the analysis of chest-abdomen CTA in adults aged 22 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive cases of aortic dissection (AD) or aortic intramural hematoma (IMH) pathology.

EFAI AASCTA uses an artificial intelligence algorithm to identify suspected findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage. EFAI AASCTA is not intended to direct attention to specific portions or anomalies of an image. Its results are not intended to be used on a stand-alone basis for clinical decisionmaking nor is it intended to rule out AAS or otherwise preclude clinical assessment of computed tomography cases.

Device Description

EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM (EFAI AASCTA) is a radiological computer-assisted triage and notification software system. The software uses deep learning techniques to automatically analyze chest or chest-abdomen CTA and alerts the PACS/RIS workstation once images with features suggestive of AD or IMH are identified.

Through the use of EFAI AASCTA, a radiologist is able to review studies with features suggestive of AD or IMH earlier than in standard of care workflow.

The device is intended to provide a passive notification through the PACS/workstation to the radiologists indicating the existence of a case that may potentially benefit from the prioritization. It does not mark, highlight, or direct users' attention to a specific location on the original chest or chest-abdomen CTA. The device aims to aid in prioritization and triage of radiological medical images only.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study details for the EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM, based on the provided document:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Performance Metric	Acceptance Criteria (Lower Bound of 95% CI)	Reported Device Performance (95% CI)
Sensitivity	> 0.8	0.929 (0.878 - 0.960)
Specificity	> 0.8	0.915 (0.871 - 0.945)
Processing Time	Not explicitly stated as an AC	37.86 seconds (35.22 - 40.50)

2. Sample Size Used for the Test Set and Data Provenance

Sample Size for Test Set: 380 CTA studies (156 positive cases, 224 negative cases).
Data Provenance: Retrospective, multisite clinical validation study. The data was collected in the United States. None of the studies in the test set were used for model development or analytical validation. The study population included 51.58% females and 48.42% males, with a mean age of 62.90 years. CT scanner manufacturers included Philips, Toshiba, Siemens, GE, and others.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Number of Experts: Three.
Qualifications of Experts: U.S. board-certified radiologists.

4. Adjudication Method for the Test Set

Adjudication Method: Majority agreement between the three experts. (Described as "the reference standard (ground truth) was generated by the majority agreement between the three experts.")

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not reported. The study focused on the standalone performance of the AI algorithm.

6. Standalone Performance Study

Yes, a standalone performance study was conducted. The results reported (sensitivity and specificity) are for the EFAI AASCTA by itself, "in the absence of any interaction with a clinician."

7. Type of Ground Truth Used

Ground Truth Type: Expert consensus. Specifically, the "majority agreement between the three experts" (U.S. board-certified radiologists) determined the presence of AD or IMH for each case.

8. Sample Size for the Training Set

The document does not explicitly state the sample size for the training set. It only mentions that none of the 380 studies in the validation test set were used for model development (training) or analytical validation.

9. How the Ground Truth for the Training Set Was Established

The document does not explicitly state how the ground truth for the training set was established. It only discusses the ground truth establishment for the test set.

Summary

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April 8, 2024

Ever Fortune.AI, Co., Ltd. Ti-Hao Wang Chief Technology Officer Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd. West Dist. Taichung City, 403020, TAIWAN

Re: K240291

EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT Trade/Device Name: SYSTEM Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: OAS Dated: January 31, 2024 Received: February 1, 2024

Dear Ti-Hao Wang:

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/cdrb/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" (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).

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Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 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 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-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (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.

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-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/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-device-advice-comprehensive-regulatoryassistance/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).

Sincerely,

Samul for

Jessica Lamb, Ph.D Assistant Director Imaging Software Team 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

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Indications for Use

510(k) Number (if known) K240291

Device Name EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)

X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary

General Information 1.

510(k) Sponsor	Ever Fortune.AI Co., Ltd.
Address	Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd.West Dist.Taichung City 403020TAIWAN
Applicant	Joseph Chang
Contact Information	886-04-23213838 #216joseph.chang@everfortune.ai
Correspondence Person	Ti-Hao Wang
Contact Information	886-04-23213838 #168thothwang@gmail.com tihao.wang@everfortune.ai
Date Prepared	January, 2024

2. Proposed Device

Proprietary Name	EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROMEASSESSMENT SYSTEM
Common Name	EFAI AASCTA
Classification Name	Radiological computer aided triage and notification software
Regulation Number	21 CFR 892.2080
Product Code	QAS
Regulatory Class	II

3. Predicate Device

Proprietary Name	BriefCase
Premarket Notification	K222329
Classification Name	Radiological computer aided triage and notification software
Regulation Number	21 CFR 892.2080
Product Code	QAS
Regulatory Class	II

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Device Description 4.

Through the use of EFAI AASCTA, a radiologist is able to review studies with features suggestive of AD or IMH earlier than in standard of care workflow.

ട. Intended Use / Indications for Use

EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM (EFAI AASCTA) is a radiological computer aided triage and notification software indicated for use in the analysis of chest or chest-abdomen CTA in adults aged 22 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive cases of aortic dissection (AD) or aortic intramural hematoma (IMH) pathology.

EFAI AASCTA uses an artificial intelligence algorithm to identify suspected findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage. EFAI AASCTA is not intended to direct attention to specific portions or anomalies of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out AAS or otherwise preclude clinical assessment of computed tomography angiography cases.

Comparison of Technological Characteristics with Predicate Device 6.

Feature/Function	Proposed Device:EFAI AASCTA(K240291)	Predicate Device:BriefCase(K222329)
IntendedUse/Indicationfor Use	EFAI CARDIOSUITE CTAACUTE AORTIC SYNDROMEASSESSMENT SYSTEM (EFAI	BriefCase is a radiologicalcomputer-aided triage and notificationsoftware indicated for use in the analysis
	AASCTA) is a radiologicalcomputer aided triage andnotification software indicated foruse in the analysis of chest orchest-abdomen CTA in adults aged22 and older. The device isintended to assist hospital networksand appropriately trained medicalspecialists in workflow triage byflagging and communicatingsuspected positive cases of aorticdissection (AD) or aortic intramuralhematoma (IMH) pathology.EFAI AASCTA uses an artificialintelligence algorithm to identifysuspected findings. It makescase-level output available to aPACS/workstation for worklistprioritization or triage. EFAIAASCTA is not intended to directattention to specific portions oranomalies of an image. Its resultsare not intended to be used on astand-alone basis for clinicaldecision-making nor is it intendedto rule out AAS or otherwisepreclude clinical assessment ofcomputed tomography angiographycases.	of CT exams with contrast (CTA and CTwith contrast) that include the chest inadults or transitional adolescents aged 18and older. The device is intended to assisthospital networks and appropriatelytrained medical specialists in workflowtriage by flagging and communicatingsuspected positive cases of aorticdissection (AD) pathology. BriefCaseuses an artificial intelligence algorithm toanalyze images and highlight cases withdetected findings on a standaloneapplication in parallel to the ongoingstandard of care image interpretation. Theuser is presented with notifications forcases with suspected findings.Notifications include compressedpreview images that are meant forinformational purposes only and notintended for diagnostic use beyondnotification. The device does not alter theoriginal medical image and is notintended to be used as a diagnosticdevice. The results of BriefCase areintended to be used in conjunction withother patient information and based onthe user's professional judgment, to assistwith triage/prioritization of medicalimages. Notified clinicians areresponsible for viewing full images perthe standard of care.
User population	Hospitalnetworksandappropriatelytrainedmedicalspecialists	Hospital networks and appropriatelytrained medical specialists
Anatomicalregion of interest	Chest and thoracoabdominal	Chest, abdomen and thoracoabdominal
Data acquisitionprotocol	chest or chest-abdomen CTA	CT exams with contrast (CTA and CTwith contrast) that include the chest
Notification-only(notificationalerts), parallelworkflow tool	Yes	Yes
Imagesformat	DICOM	DICOM
Interference withstandardworkflow	No	No
Algorithm	Artificial intelligence algorithm with database of images	Artificial intelligence algorithm with database of images

EFAI AASCTA Traditional 510(k)

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7. Performance Data

Performance of the EFAI AASCTA has been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing. Additionally, the software validation activities were performed in accordance with IEC 62304:2006/A1:2016 - Medical device software - Software life cycle processes, in addition to the FDA Guidance documents, "Content of Premarket Submissions for Device Software Functions" and "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions."

Ever Fortune.AI conducted a retrospective, blinded, multisite clinical validation study with the proposed device EFAI AASCTA with a pre-determined primary and secondary endpoint and performance goals to evaluate the performance of the EFAI AASCTA in identifying positive findings of aortic dissection (AD) or aortic intramural hematoma (IMH) from chest or chest-abdomen CTA scans on a validation dataset of 380 CTA studies (156 positives and 224 negatives) consecutively collected in the United States. None of the studies was used as part of the EFAI AASCTA model development or analytical validation testing.

The study population contained 51.58% females and 48.42% males, and the mean age of cases was 62.90 years. The CT scanner manufacturers of images were acquired from Philips, Toshiba, Siemens. GE, and others. Confounding cases in the dataset include possible confounders as follows: Artifact. Limited Field, Atherosclerotic Disease, Aortic Aneurysm, Arterial Dissection, and Vessel Disease.

The presence of AD or IMH in each case was determined independently by three U.S. board-certified radiologists, and the reference standard (ground truth) was generated by the majority agreement between the three experts. The performance criteria were set such that the lower bounds of 95% confidence intervals (Cls) of both sensitivity and specificity should exceed 0.8.

The observed results of the standalone performance validation study demonstrated that EFAI AASCTA by itself, in the absence of any interaction with a clinician, can provide case-level notifications with features suggestive of positive findings (AD or IMH) with satisfactory results. The EFAI AASCTA was able to demonstrate sensitivity and specificity of 0.929 (95% CI=0.878-0.960) and 0.915 (95% CI=0.871-0.945) respectively, which is substantially equivalent to the predicate device (BriefCase, K222329). The secondary endpoint of the observed system processing time per study is 37.86 seconds (95% CI=35.22-40.50) on average and was comparable with the predicate device (38 seconds).

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In addition, the results of the subgroup analysis, which included different genders, age groups. CT manufacturer groups, and CT slice thickness groups, demonstrated that EFAI AASCTA consistently performed high performance, underscoring its reliability and effectiveness across diverse subgroups. We also evaluated the device's performance in cases with image quality issues (including Artifact and Limited Field) and accompanying radiologic findings (including Atherosclerotic Disease, Aortic Aneurysm, Arterial Dissection, and Vessel Disease) to assess the impact of these potential confounders. The device consistently performed reliably across these circumstances. Furthermore, our analysis of the device's ability to identify specific characteristics of positive findings, including their type, Stanford classification, and location, revealed that EFAI AASCTA maintains stable performance. In conclusion, the results demonstrate that the EFAI AASCTA device is determined to be substantially equivalent in safety and effectiveness to the predicate device. BriefCase.

8. Safety & Effectiveness

EFAI AASCTA has been designed, verified and validated in compliance with 21 CFR, Part 820.30 requirements. The device has been designed to meet the requirements associated with ISO 14971:2019 Medical devices - Application of risk management to medical devices. The EFAI AASCTA performance has been validated using retrospective data from case data and through the use of Reader comparison analysis.

9. Conclusion

Based on the information submitted in this premarket notification, and based on the indications for use, technological characteristics, and performance testing, the EFAI AASCTA raises no new questions of safety and effectiveness and is substantially equivalent to the predicate device in terms of safety, efficacy, and performance.

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.