uAI EasyTriage-Rib

K193271 · Shanghai United Imaging Intelligence Co., Ltd. · QFM · Jan 15, 2021 · Radiology

Device Facts

• Record ID: K193271
• Device Name: uAI EasyTriage-Rib
• Applicant: Shanghai United Imaging Intelligence Co., Ltd.
• Product Code: QFM · Radiology
• Decision Date: Jan 15, 2021
• Decision: SESE
• Submission Type: Traditional
• Regulation: 21 CFR 892.2080
• Device Class: Class 2
• Attributes: AI/ML, Software as a Medical Device

Intended Use

uAl EasyTriage-Rib is a radiological computer-assisted triage and notification software device for analysis of CT chest images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing trauma studies with suspected positive findings of multiple (3 or more) acute rib fractures. uAl EasyTriage-Rib uses an artificial intelligence algorithm to analyze images and highlight studies with suspected multiple (3 or more) acute rib fractures in a standalone application for study list prioritization or triage in parallel to ongoing standard of care. The user is presented with notifications of cases with suspected findings. Notifications include compressed preview images that are meant for informational purposes 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 uAl EasyTriage-Rib, in conjunction with other clinical information and professional judgment, are to be used to assist with triage/prioritization of medical images. Notified radiologists who read the original medical images are responsible for the diagnostic decision.

Device Story

Device analyzes CT chest images to identify multiple (3 or more) acute rib fractures; utilizes deep learning AI algorithm to flag studies for triage; operates in parallel to standard of care; does not remove cases from reading queues. System comprises server module and studylist application; provides passive notifications to radiologist workstations; includes compressed preview images for informational purposes. Radiologists use notifications to prioritize review of trauma studies; device does not provide diagnostic output; original medical images remain unaltered. Intended for hospital networks; assists in managing time-critical conditions like flail chest; improves workflow efficiency by highlighting suspected positive cases.

Clinical Evidence

Retrospective, blinded, multicenter study of 200 CT chest cases (>1mm slice thickness) from GE and Siemens scanners. Primary endpoint: software performance in identifying multiple (3 or more) acute rib fractures. Results: sensitivity 92.7% (95% CI: 84.8%-97.3%), specificity 84.7% (95% CI: 77.0%-90.7%), AUC 0.939 (95% CI: 0.906, 0.972). Secondary endpoint: time-to-notification compared to predicate (HealthVCF) using 76 true positive studies; average time 69.56s vs 61.36s, demonstrating comparable performance.

Technological Characteristics

Radiological computer-assisted triage and notification software. Deep learning AI algorithm trained on medical images. Modality: CT chest. Connectivity: standalone application integrated with PACS/workstation. Output: passive notification with compressed preview images. Software-based analysis only; no hardware components.

Indications for Use

Indicated for analysis of CT chest images to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing trauma studies with suspected positive findings of multiple (3 or more) acute rib fractures.

Regulatory Classification

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.

Special Controls

Radiological computer aided triage and notification software must comply with the following special controls: 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. Standalone 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. 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.

*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.

Predicate Devices

• HealthVCF (K192901)

Submission Summary (Full Text)

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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health and Human Services logo on the left and the FDA logo on the right. The FDA logo is in blue and includes the letters "FDA" followed by the words "U.S. Food & Drug Administration".

January 15, 2021

Shanghai United Imaging Intelligence Co., Ltd. % Zhao Xiaojing Quality & Regulatory Manager No. 199, Huanke Road Shanghai, Shanghai 201210 CHINA

# Re: K193271

Trade/Device Name: uAI EasyTriage-Rib Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QFM Dated: December 8, 2020 Received: December 8, 2020

Dear Zhao Xiaojing:

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 (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 located 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.

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 and Part 809); medical device reporting of medical device-related adverse events) (21 CFR

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803) for devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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 ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely.

For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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510(k) Number (if known) K193271 Device Name

#### uAl EasyTriage-Rib

Indications for Use (Describe)

uAl EasyTriage-Rib is a radiological computer-assisted triage and notification software device for analysis of CT chest images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing trauma studies with suspected positive findings of multiple (3 or more) acute rib fracture(s).

uAl EasyTriage-Rib uses an artificial intelligence algorithm to analyze images and highlight studies with suspected multiple (3 or more) acute rib fracture(s) in a standalone application for study list prioritization or triage in parallel to ongoing standard of care. The user is presented with notifications of cases with suspected findings. Notifications include compressed preview images that are meant for informational purposes 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 diaqnostic device.

The results of uAl EasyTriage-Rib, in conjunction with other clinical information and professional judgment, are to be used to assist with triage/prioritization of medical images. Notified radiologists who read the original medical images are responsible for the diagnostic decision.

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

## K193271

### Shanghai United Imaging Intelligence Co., Ltd.'s uAl EasyTriage-Rib

#### Submitter:

Shanghai United Imaging Intelligence Co., Ltd. Floor 23-26, No.701 Yunjin Road, Xuhui District, Shanghai Phone: [phone] Contact Person: ZHAO Xiaojing

Date Prepared: January 14, 2021

Name of Device: uAI EasyTriage-Rib

Common or Usual Name/ Classification Name: Radiological Computer-Assisted Prioritization Software For Lesions

Regulatory Class: Class II

Product Code: QFM (21 C.F.R. 892.2080)

Predicate Device: Zebra Medical Vision Ltd.'s HealthVCF (K192901)

## Device Description

uAl EasyTriage-Rib is a radiological computer-assisted triage and notification software device indicated for analysis of CT chest images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing studies with suspected positive findings of multiple (3 or more) acute rib fractures. The device consists of the following two modules: (1) uAl EasyTriage-Rib Server; and (2) uAl EasyTriage-Rib Studylist Application that provides the user interface in which notifications from the application are received.

#### Intended Use / Indications for Use

uAl EasyTriage-Rib is a radiological computer-assisted triage and notification software device for analysis of CT chest images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing trauma studies with suspected positive findings of multiple (3 or more) acute rib fractures.

uAl EasyTriage-Rib uses an artificial intelligence algorithm to analyze images and highlight studies with suspected multiple (3 or more) acute rib fractures in a standalone application for study list prioritization or triage in parallel to ongoing standard of care. The user is presented with notifications of cases with suspected findings. Notifications include compressed preview images that are meant for informational purposes 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.

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The results of uAl EasyTriage-Rib, in conjunction with other clinical information and professional judgment, are to be used to assist with triage/prioritization of medical images. Notified radiologists who read the original medical images are responsible for the diagnostic decision.

# Justification for Time Criticality of Indication

The device aims to triage multiple (3 or more) rib fractures since the condition of multiple rib fractures is time sensitive in clinical practice. Specifically,

- The presence of 3 or more rib fractures is highly predictive of poor clinical outcomes including respiratory failure and overall mortality [1-10].
- . The presence of 3 or more rib fractures is incorporated into US clinical quidelines for trauma patient management [1, 11, 15-24].
- Flail chest, which occurs in a subset of patients with 3 or more rib fractures, is a ● potentially life threatening condition that requires prompt management [1, 14,15, 25-281.

Accordingly, rib fracture is a time-critical condition that is appropriate to prioritize for review. In this setting, high sensitivity is a crucial consideration so that all appropriate cases may be identified and promptly interpreted.

# Comparison of Technological Characteristics with the Predicate Device

HealthVCF (K192901) is the predicate device. The subject and predicate device are both radiological computer-assisted triage and notification software. Both devices are artificial intelligence algorithms incorporated software packages that analyze CT images for fracture(s). Both devices process images intended to aid in prioritization and triage of radiological medical images. The subject device is intended to provide notifications for cases with suspected positive findings of multiple (3 or more) acute rib fractures by analysis of CT chest images and the predicate device is intended to analyze chest and abdominal CT scans and flags those that are suggestive of the presence of at least one vertebral compression at the exam level. This difference does not affect the intended use of both devices, which is to prioritize timesensitive fractures for trained clinician review.

Both software devices provide passive notifications to a clinician of the availability of time sensitive radiological medical images for review based on computer aided image analysis performed by the device's AI algorithm. The subject device flags cases with the suspected positive findings on the Studylist Application on the workstations of the radiologist. Those notifications work in parallel to the standard of care. They prompt the radiologist to start preemptive triage of a flagged case, upon which he may turn to the local PACS to perform the review. In addition, both devices show preview images for positive findings.

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The predicate and subject devices process CT images using similar techniques and a similar artificial intelligence algorithm. Specifically, the subject and predicate software utilize a deep learning algorithm trained on medical images. The deep-learning process allows for high accuracy in the detection of initial suspect positive findings. As a system, the uAl EasyTriage-Rib raises the same types of safety and effectiveness questions as the predicate; namely, accurate detection of findings within the reviewed and processed study on which a physician can base a clinically useful triage/prioritization assessment considering all available clinical information.

lt is important to note that, like the predicate, the device does not remove cases from a reading queue. Again, both devices operate in parallel with the standard of care, which remains the default option for all cases.

| Technological<br>Characteristics | Subject Device<br>uAl EasyTriage-Rib<br>(K193271) | Predicate Device<br>HealthVCF<br>(K192901) | Summary |
|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indication for<br>Use/Intended<br>Use | uAl EasyTriage-Rib is a<br>radiological computer-<br>assisted triage and<br>notification software<br>device for analysis of CT<br>chest images. The device<br>is intended to assist<br>hospital networks and<br>trained radiologists in<br>workflow triage by<br>flagging and prioritizing<br>trauma studies with<br>suspected positive<br>findings of multiple (3 or<br>more) acute rib fractures.<br>uAl EasyTriage-Rib uses<br>an artificial intelligence<br>algorithm to analyze<br>images and highlight<br>studies with suspected<br>multiple (3 or more) acute<br>rib fractures in a<br>standalone application for<br>study list prioritization or<br>triage in parallel to<br>ongoing standard of care.<br>The user is presented<br>with notifications of cases<br>with suspected findings | HealthVCF is a passive<br>notification for<br>prioritization-only,<br>parallel-workflow<br>software tool used by<br>clinicians to prioritize<br>specific patients within<br>the standard-of-care<br>bone health setting for<br>suspected vertebral<br>compression fractures.<br>HealthVCF uses an<br>artificial intelligence<br>algorithm to analyze<br>chest and abdominal<br>CT scans and flags<br>those that are<br>suggestive of the<br>presence of at least<br>one vertebral<br>compression at the<br>exam level. These<br>flags are viewed by the<br>clinician in Bone Health<br>and Fracture Liaison<br>Service programs in<br>the medical setting via<br>a worklist application<br>on their Picture | Similar except<br>for lesion type.<br>Both findings<br>are<br>appropriately<br>time sensitive.<br>Performance<br>data will<br>support uAl<br>EasyTriage-Rib<br>indications. |
| Technological<br>Characteristics | Subject Device<br>uAl EasyTriage-Rib<br>(K193271) | Predicate Device<br>HealthVCF<br>(K192901) | Summary |
| Notifications include<br>compressed preview<br>images that are meant for<br>informational purposes<br>only and not intended for<br>diagnostic use beyond<br>notification. The device<br>does not alter the original<br>medical image and is not<br>intended to be used as a<br>diagnostic device.<br>The results of uAl<br>EasyTriage-Rib, in<br>conjunction with other<br>clinical information and<br>professional judgment,<br>are to be used to assist<br>with triage/prioritization of<br>medical images. Notified<br>radiologists who read the<br>original medical images<br>are responsible for the<br>diagnostic decision. | Archiving and<br>Communication<br>System (PACS).<br>HealthVCF does not<br>send a proactive alert<br>directly to the user.<br>HealthVCF does not<br>provide diagnostic<br>information beyond<br>triage and prioritization,<br>it does not remove<br>cases from the<br>radiology worklist, and<br>should not be used in<br>place of full patient<br>evaluation, or relied<br>upon to make or<br>confirm diagnosis. | | |
| Notification-only,<br>parallel workflow<br>tool | Yes | Yes | Same, both<br>devices<br>produce<br>passive<br>notifications |
| User | Radiologist | Bone Health Clinician | Radiologists are<br>common users<br>for products<br>under product<br>code QFM for<br>Radiological<br>Computer-<br>Assisted<br>Prioritization<br>Software For<br>Lesions |
| Identify patients<br>with pre-<br>specified clinical<br>condition | Yes | Yes | Same |
| Clinical condition | Multiple (3 or more) acute<br>rib fractures | Vertebral compression<br>fracture | Different but<br>both findings |
| Technological<br>Characteristics | Subject Device<br>uAl EasyTriage-Rib<br>(K193271) | Predicate Device<br>HealthVCF<br>(K192901) | Summary |
| | | | indicate pre-<br>specified<br>clinical<br>conditions for<br>triage |
| Alert to finding | Yes; notification flagged<br>for review | Yes; notification<br>flagged for review | Same |
| Independent of<br>standard of care<br>workflow | Yes; No cases are<br>removed from worklist | Yes; No cases are<br>removed from worklist | Same |
| Modality | CT | CT | Same |
| Body part | Chest | Chest and abdomen | Similar, both<br>include "chest". |
| Artificial<br>Intelligence<br>algorithm | Yes | Yes | Same |
| Limited to<br>analysis of<br>imaging data | Yes | Yes | Same |
| Aids prompt<br>identification of<br>cases with<br>indicated<br>findings | Yes | Yes | Same |
| Where results<br>are received | Workstation | PACS / Workstation | Different but<br>both provide a<br>passive<br>notification to<br>the workstation<br>of the presence<br>of suspected<br>finding in the<br>scan |

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

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## Performance Data

UII conducted a retrospective, blinded, multicenter study with the uAl EasyTriage-Rib software with the primary endpoint to evaluate the software's performance in identifying CT chest images containing multiple (3 or more) acute rib fractures in 200 cases from multiple US clinical sites. The 200 cases had >1mm slice thickness and were from GE and Siemens scanners. The sensitivity was 92.7% (95% Cl: 84.8%-97.3%) and specificity was 84.7% (95% Cl: 77.0%-90.7%). The AUC was 0.939 (95% Cl: 0.906, 0.972).

An important consideration with these data is the presence of chronic rib fractures in the

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dataset and the difficulty in distinguishing these findings from acute rib fractures, resulting in a decrease of specificity when acute fractures are the target condition. Specifically, certain chronic fractures can present as a pseudoarthrosis and/or malunion, findings that are difficult to distinguish from acute fractures. Accordingly, such findings are clinically relevant to review so as to exclude acute fracture.

Overall, the benefit-risk profile is favorable, and reflects the benefit of detecting 3 or more acute rib fractures with the high degree of sensitivity, and alerting the radiologist to the presence of this low incidence condition so that the study can be promptly interpreted.

In addition, a secondary endpoint measure was uAl EasyTriage-Rib's potential clinical benefit of worklist prioritization. For that purpose, we tested all the 76 true positive studies from clinical data set to compare the time-to-notification metric with Zebra Medical Vision Ltd.'s HealthVCF (K192901). The uAl EasyTriage-Rib time-to-notification is defined from the beginning of downloading the DICOM data from the PACS to the time of notification shown in the Studylist.

As shown in the table below, the average time-to-notification of uAl EasyTriage-Rib among 76 true positive studies 69.56 seconds is comparable to the time-to-notification of the HealthVCF software documented for an average of 61.36 seconds, suggesting that the radiologist can receive a notification timely on the status of studies with potential rib fracture findings with the help of uAI EasyTriage-Rib.

| Time-to-notification | Average performance time<br>(seconds) |
|----------------------|---------------------------------------|
| uAl EasyTriage-Rib | 69.56 |
| HealthVCF | 61.36 |

In summary, the performance on 200 cases establishes the achievement of effective triage by the uAl EasyTriage-Rib as well as effective notification functionality of the application, as compared to the time-to-notification of HealthVCF. The results show that it can detect rib fractures and reach the preset standard.

# Conclusions

The uAI EasyTriage-Rib is as safe and effective as the HealthVCF. The uAI EasyTriage-Rib has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended use of the device and do not affect its safety and effectiveness when used as labeled. In addition, the minor technological differences between the uAl EasyTriage-Rib and its predicate device raise no new issues of safety or effectiveness. Performance data demonstrate that the uAl EasyTriage-Rib is as safe and effective as the HealthVCF. Thus, the uAl EasyTriage-Rib is substantially equivalent.

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