The Zebra HealthCXR device is a software workflow tool designed to aid the clinical assessment of adult Chest X-Ray cases with features suggestive of pleural effusion in the medical care environment. HealthCXR analyzes cases using an artificial intelligence algorithm to identify suspected findings. It makes case-level output available to a PACS/worldion for worklist prioritization or triage. HealthCXR 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 pleural effusion or otherwise preclude clinical assessment of X-Ray cases.

Device Description

The HealthCXR solution is a software product that automatically identifies suspected findings on chest x-rays (e.g. pleural effusion) and notifies PACS/workstation of the presence of this critical finding in the scan. This notification allows for worklist prioritization of the identified scan and assists clinicians in viewing the prioritized scan before others. The device aim is to aid in prioritization and triage of radiological medical images only.

The software is automatic and is capable of analyzing PA or AP chest x-rays. If a suspected finding is found in a scan, the alert is automatically sent to the PACS/workstation used by the radiologist or to a standalone desktop application in parallel with the ongoing standard of care. The PACS/workstation prioritizes and displays the study through its worklist interface. The standalone desktop application, Zebra Worklist, includes a compressed preview image meant for informational purposed only and is not intended for diagnostic use.

The HealthCXR device works in parallel to and in conjunction with the standard care of workflow. After a chest x-ray has been performed, a copy of the study is automatically retrieved and processed by the HealthCXR device performs the analysis of the study and returns a notification about the relevant pathology to the PACS/workstation which prioritizes it through the worklist interface or alternatively, the Zebra Worklist will notify the user through the standalone desktop application. The clinician is then able to review the study earlier than in standard of care workflow.

The software does not recommend treatment or provide a diagnosis. It is meant as a tool to assist in improved workload prioritization of critical cases. The final diagnosis is provided by a radiologist after reviewing the scan itself.

The following modules compose the HealthCXR software for Pleural Effusion:

Data input and validation: Following retrieval of a study, the validation feature assessed the input data (i.e. age, modality, view) to ensure compatibility for processing by the algorithm.

Pleural Effusion algorithm: Once a study has been validated, the algorithm analyzes the frontal chest x-ray for detection of suspected finding suggestive of pleural effusion.

IMA Integration feature: The study analysis and the results of a successful study analysis is provided to IMA, to then be sent to the PACS/workstation for prioritization.

Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

AI/ML Overview

HealthCXR Acceptance Criteria and Performance Study

This response details the acceptance criteria and the study conducted to prove the HealthCXR device meets these criteria, based on the provided FDA 510(k) summary.

1. Table of Acceptance Criteria and Reported Device Performance

Performance Metric	Acceptance Criteria (Implicit from "exceeds the required technical method" and "substantially equivalent to the predicate" or explicit goals)	Reported Device Performance
Area Under the Curve (AUC)	> 0.95 (Explicitly stated for effective triage)	0.9885 (95% CI: [0.9815, 0.9956])
Operating Point 1: Equal Sensitivity & Specificity	Substantially equivalent to predicate device performance	Sensitivity: 96.74% (95% CI: [92.79; 96.48])Specificity: 93.17% (95% CI: [89.57; 95.58])
Operating Point 2: High Specificity	Substantially equivalent to predicate device performance	Sensitivity: 93.84% (95% CI: [90.36; 96.12])Specificity: 97.12% (95% CI: [94.43; 98.53])
Mean Processing Time	Substantially equivalent to predicate device performance	Operating Point 1: 27.76 seconds Operating Point 2: 20.18 seconds

Note: The acceptance criteria for sensitivity and specificity are implicitly derived from the statement that the device met the performance goal and was found to be "substantially equivalent to the predicate device, HealthPNX (K190362)." The document does not explicitly state numerical thresholds for the predicate's performance for these specific metrics, but rather that the HealthCXR results were comparable. The AUC goal of >0.95 for effective triage is explicitly stated.

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

Sample Size: 554 anonymized Chest X-ray cases.
Data Provenance: Retrospective cohort from the USA and Israel.
- 276 cases positive for Pleural Effusion.
- 278 cases negative for Pleural Effusion (including confounding imaging factors).

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

Number of Experts: Three (3)
Qualifications: US Board-Certified Radiologists.

4. Adjudication Method for the Test Set

The document states the data was "truthed (ground truth) by three US Board-Certified Radiologists." It does not explicitly state the adjudication method (e.g., 2+1, 3+1). It can be inferred that a consensus or majority opinion was used to establish the ground truth among the three, but the specific process isn't detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, What was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

No MRMC comparative effectiveness study involving human readers and AI assistance was reported in this document. The study focused on the standalone performance of the AI algorithm.

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 states: "The stand-alone detection accuracy was measured on this cohort respective to the ground truth."

7. The Type of Ground Truth Used

Expert consensus (established by three US Board-Certified Radiologists).

8. The Sample Size for the Training Set

The document does not provide the sample size for the training set. It only describes the validation data set.

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

The document does not provide information on how the ground truth for the training set was established. It only details the establishment of ground truth for the test/validation set.

Summary

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November 26, 2019

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Zebra Medical Vision, Ltd. % Flair Bar VP Operations Shefayim Commercial Center PO Box 25 Shefayim, 6099000 ISRAEL

Re: K192320

Trade/Device Name: HealthCXR Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer-assisted prioritization software Regulatory Class: Class II Product Code: QFM Dated: November 3, 2019 Received: November 6, 2019

Dear Flair Bar:

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

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801); medical device reporting of medical device-related adverse events) (21 CFR 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 medical devices and radiation-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,

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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Indications for Use

510(k) Number (if known) K192320

Device Name HealthCXR

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)

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Image /page/3/Picture/0 description: The image shows the Zebra Medical Vision logo. The logo consists of a yellow horizontal line on the left, followed by a stylized black and white zebra head in the center, and the word "zebra" in black on the right. Below the word "zebra" is the text "MEDICAL.VISION" in a smaller font.

5. 510 (k) Summary

510(K) Summary - HealthCXR Zebra Medical Vision Ltd.

510(k) Number – K192320

I. Applicant's Name: Flair Bar, VP Operations Zebra Medical Vision Ltd. Shefayim Commercial Center PO Box 25 Shefayim, 6099000 ISRAEL Telephone: +972-9-8827795 Fax: +972-9-8827795

Date Prepared: November 22, 2019

II. Device
Trade Name: HealthCXR

Classification Name: QFM - Radiological Computer-Assisted Prioritization Software

Regulation Number: 892.2080

Classification:

Class II, Radiology

III. Predicate Device:

The HealthCXR device is substantially equivalent to the following device:

Proprietary Name	HealthPNX
Premarket Notification	K190362
Classification Name	Radiological Computer-Assisted Prioritization Software
Regulation Number	21 CFR 892.2080
Product Code	QFM
Regulatory Class	II

IV. Device Description

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Image /page/4/Picture/0 description: The image contains the logo for Zebra Medical Vision. The logo consists of a stylized black and white zebra stripe design to the left, followed by the word "zebra" in black lowercase letters. Below "zebra" is the text "MEDICAL.VISION" in smaller, uppercase letters. To the left of the zebra stripe design is a yellow horizontal bar.

The following modules compose the HealthCXR software for Pleural Effusion:

Data input and validation: Following retrieval of a study, the validation feature assessed the input data (i.e. age, modality, view) to ensure compatibility for processing by the algorithm.

Pleural Effusion algorithm: Once a study has been validated, the algorithm analyzes the frontal chest x-ray for detection of suspected finding suggestive of pleural effusion.

IMA Integration feature: The study analysis and the results of a successful study analysis is provided to IMA, to then be sent to the PACS/workstation for prioritization.

Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

V. Intended Use/Indication for Use:

The Zebra HealthCXR device is a software workflow tool designed to aid the clinical assessment of adult Chest X-Ray cases with features suggestive of pleural effusion in the medical care

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Image /page/5/Picture/0 description: The image shows the Zebra Medical Vision logo. The logo consists of a stylized black and white zebra-striped "Z" symbol to the left of the word "zebra" in black, with the words "MEDICAL.VISION" in smaller black font below it. There is a yellow horizontal bar to the left of the zebra symbol.

environment. HealthCXR analyzes cases using an artificial intelligence algorithm to identify suspected findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage. HealthCXR 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 pleural effusion or otherwise preclude clinical assessment of X-Ray cases.

Technological Characteristics Compared to Predicate Device: VI.

The technological characteristics, e.g., overall design, mechanism of action, mode of operation, performance characteristics, etc., and the intended use of the HealthCXR device are substantially equivalent to the predicate device cited above.

						A comparison of the technological characteristics with the predicate is summarized below.

TechnologicalCharacteristics	Proposed DeviceHealthCXR	Predicate DeviceHealthPNX (K190362)	Summary
Indication forUse/Intended Use	The Zebra HealthCXR device is asoftware workflow tool designedto aid the clinical assessment ofadult Chest X-Ray cases withfeatures suggestive of pleuraleffusion in the medical careenvironment. HealthCXRanalyzes cases using an artificialintelligence algorithm to identifysuspected findings. It makes case-level output available to aPACS/workstation for worklistprioritization or triage.HealthCXR is not intended todirect attention to specificportions or anomalies of animage. Its results are not intendedto be used on a stand-alone basisfor clinical decision-making noris it intended to rule out PleuralEffusion or otherwise precludeclinical assessment of X-Raycases.	The Zebra Pneumothoraxdevice is a softwareworkflow tool designed toaid the clinical assessment ofadult Chest X-Ray cases withfeatures suggestive ofPneumothorax in the medicalcare environment.HealthPNX analyzes casesusing an artificial intelligencealgorithm to identifysuspected findings. It makescase-level output available toa PACS/workstation forworklist prioritization ortriage. HealthPNX is notintended to direct attention tospecific portions oranomalies of the image. Itsresults are not intended to beused on a stand-alone basisfor clinical decision-makingnor is it intended to rule outPneumothorax or otherwisepreclude clinical assessmentof X-Ray cases.	Similar expect for lesiontype
Notification-only,parallel workflowtool	Yes	Yes	Same
User	Radiologist	Radiologist	Same
Radiological imagesformat	DICOM	DICOM	Same
Identify patients withprespecifiedclinical condition	Yes	Yes	Same
Clinical condition	Pleural Effusion	Pneumothorax	Different but as per theproduct classificationdefinition, both identify“time sensitive imaging.”
Alert to finding	Yes; notification flagged forreview on hospital worklist orZebra list	Yes; notification flagged forreview on hospital worklist.	Similar, HealthCXR canbe directly integrated fornotification on thehospital worklist or onthe Zebra list application.Both notificationsoperate in parallel withthe standard of care.
Independent ofstandard of careworkflow	Yes; No cases are removedfrom worklist	Yes; No cases are removedfrom worklist	Same
Modality	X-Ray	X-Ray	Same
Body part	Chest	Chest	Same
Artificial Intelligencealgorithm	Yes	Yes	Same
Limited to analysis ofimaging data	Yes	Yes	Same
Aids promptidentification ofcases with indicatedfindings	Yes	Yes	Same
Preview Image	Presentation of a preview of thestudy for initial assessment, notmeant for diagnostic purposes.The device operated in parallelwith the standard of care, whichremains the default option for allcases.	Presentation of notificationfor initial assessment notmeant for diagnosticpurposes. The deviceoperates in parallel with thestandard of care, whichremains the default option forall cases.	Similar, HealthCXRprovides an additionalthumbnail view of theoriginal exam as previewonly on the Zebra list orRadiology Assistant, notfor diagnostic use.
Multiple operatingpoints	Yes; 2 optional operating points	No; single operating point	Different, but bothoperating points aresubstantially equivalentto the performancepredicate device andcomply with DEN170073 Special control1(iii)
Where results are	PACS / Workstation	PACS / Workstation	Same
received

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Image /page/6/Picture/0 description: The image shows the logo for Zebra Medical Vision. The logo consists of a stylized "Z" symbol on the left, followed by the word "zebra" in lowercase letters. Below the word "zebra" are the words "MEDICAL.VISION" in smaller font. The logo is black and white.

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Image /page/7/Picture/0 description: The image shows the logo for Zebra Medical Vision. The logo consists of a stylized "Z" symbol on the left, followed by the word "zebra" in lowercase letters. Below the word "zebra" is the text "MEDICAL.VISION" in smaller capital letters. The logo is simple and modern, and the use of black and white gives it a clean and professional look.

VII. Performance Data:

Safety and performance of HealthCXR has been evaluated and verified in accordance with software specifications and applicable performance standards through Software Development and Validation & Verification Process to ensure performance according to specifications, User Requirements and Federal Regulations and Guidance documents, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices".

The performance of the HealthCXR device has been validated in a performance study for triage of time sensitive chest X-Ray cases. The data included a retrospective cohort of 554 anonymized Chest X-ray cases from the USA and Israel, including 276 cases positive for Pleural Effusion and 278 cases negative for Pleural Effusion, as well as confounding imaging factors. The validation data set was truthed (ground truth) by three US Board-Certified Radiologists (truthers). The stand-alone detection accuracy was measured on this cohort respective to the ground truth.

The HealthCXR device detection accuracy met the accuracy performance goals for AUC. sensitivity, and specificity for two defined operating points. Overall, the HealthCXR was able to demonstrate an area under the curve (AUC) of 0.9885 (95% CI: [0.9815, 0.9956]), which is both comparable to the predicate device, and exceeds the required technical method under the QFM product code. The device establishes effective triage based on an AUC >95%. The sensitivity and specificity of the HealthCXR was reported for two operating points, the first for equal sensitivity and specificity and the second operating point for a higher specificity. At both operating points, the HealthCXR performance met the performance goal and was found to be substantially equivalent to the predicate device, HealthPNX (K190362). The first operating point showed a sensitivity of 96.74% (95% CI: [92.79; 96.48]) and a specificity of 93.17% (95% CI: [89.57; 95.58]). The second, "high-specificity" operating point, reported a sensitivity of 93.84% (95% CI: [90.36;96.12%) and a specificity of 97.12%% (95% CI: [94.43 ;98.53]).

In addition, we assessed the performance time of the HealthCXR that reflects the time it takes for the device to analyze the study and send a notification to the worklist. The HealthCXR device mean processing time was 27.76 seconds for the "Equal Sensitivity and Specificity" operating point, and 20.18 seconds for the "High Specificity" operating point, a timing performance that is substantially equivalent to the predicate. This establishes that the HealthCXR meets its intended use statement.

VIII. Conclusion

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Image /page/8/Picture/0 description: The image shows the Zebra Medical Vision logo. The logo consists of a yellow horizontal line, a stylized black and white zebra symbol, and the word "zebra" in black, with the words "MEDICAL.VISION" in smaller letters below it. The logo is clean and modern, and the colors are bright and eye-catching.

The subject HealthCXR device and the HealthPNX predicate device are both software-only devices intended to aid in triage of radiological images, independent of standard of care workflow. The labeling of both devices are limited to the categorization of exams and are not to be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.

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, and do not remove cases from the standard of care. The minor differences between the subject device and the predicate raise no new issues of safety or effectiveness. In addition, performance testing demonstrates that the HealthCXR performs as intended. The HealthCXR device is therefore substantially equivalent to the HealthPNX predicate.

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.