The qXR-BT device is intended to generate a secondary digital chest X-ray image that facilitates confirmation of the position of a breathing tube and an anatomical landmark on adult chest X-rays. This device is intended for use by licensed physicians who are trained in the evaluation of breathing tube placement on chest X-rays. The qXR-BT image provides adjunctive information and is not a substitute for the original PA/AP image.

Device Description

qXR-BT is a standalone image analysis software used during the review of digital chest radiographic images, intended to facilitate determining the position of the breathing tube relative to the carina. Standard of care medical imaging workflows are well established, and include pre-existing software components such as a PACS, DICOM viewer and imaging worklist; qXR-BT is designed to integrate with these components.

X-rays are sent to qXR-BT by means of transmission functions within the user's PACS system. Upon completion of processing, the qXR-BT device returns results to the user's PACS or other userspecified radiology software system or database.

The input to the qXR-BT device is a chest X-ray (AP and PA, referred to as frontal) in digital imaging and communications in medicine (DICOM) format.

The qXR-BT device produces PDF and DICOM format outputs that enable users to view the position of a breathing tube and an anatomical landmark (carina).

The PDF format output contains preview images that show segmented structures outlined with a textual report describing the structures detected. The text report is restricted to the presence or absence of the breathing tubes and the carina as detected by the software device.

The DICOM format output consists of a single complete additional DICOM series for each input scan. This DICOM output contains labeled overlays indicating the location and extent of the segmentable structures, suitable for viewing in the PACS or radiology viewer.

The qXR-BT analysis module consists of a set of pre-trained convolutional neural networks (CNNs), that form the core processing component shown in Figure 1. This core processing component is coupled with a pre-processing module to prepare input DICOMs for processing by the CNNs and a post-processing module to convert the output into visual and tabular format for users.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study that demonstrates the qXR-BT device meets them, based on the provided text:

1. A table of acceptance criteria and the reported device performance:

Target Structure / Metric	Acceptance Criteria	Reported Device Performance (Mean (95% CI))
Carina (Absolute Distance)	Upper bound of 95% CI ≤ 3mm	2.15 (1.96 - 2.35)mm
Tip of Breathing Tube (Absolute Distance)	Upper bound of 95% CI ≤ 3mm	1.97 (1.80 – 2.13)mm
Distance between tip of breathing tube and carina (Absolute Error)	Upper bound of 95% CI ≤ 6mm	1.98 (1.76 – 2.20)mm

2. Sample size used for the test set and the data provenance:

Sample size: 162 Chest X-ray images.
Data Provenance: Not explicitly stated regarding country of origin or whether it was retrospective or prospective.

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

Number of experts: Three radiologists.
Qualifications of experts: From the United States; no specific experience level (e.g., years of experience) is mentioned beyond "radiologists."

4. Adjudication method for the test set:

Not explicitly stated. The text mentions "manual annotation of three radiologists," which implies an expert consensus method, but the specific adjudication rules (e.g., majority vote, independent review followed by consensus) are not detailed.

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, a multi-reader multi-case (MRMC) comparative effectiveness study with human readers was not explicitly mentioned or detailed in this summary. The performance testing described is a standalone evaluation of the algorithm's accuracy against ground truth.

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

Yes, a standalone performance study was done. The text explicitly states, "Qure.ai performed standalone performance testing to test the accuracy of qXR-BT's analysis."

7. The type of ground truth used:

Expert consensus. The ground truth was "based on manual annotation of three radiologists from United States."

8. The sample size for the training set:

The sample size for the training set is not provided in the given document. The document only mentions the test set size.

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

How the ground truth for the training set was established is not provided in the given document. The document only describes how the ground truth for the test set was established.

Summary

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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 & Human Services logo on the left and the FDA acronym followed by the full name of the agency on the right. The Department of Health & Human Services logo is a stylized depiction of an eagle. The FDA acronym and the agency's full name are in blue.

Qure.ai Technologies % Bunty Kundnani Head of Regulatory Affairs Level 7, Commerz II, International Business Park Oberoi Garden City, Goregaon (E) Mumbai, Maharashtra 400063 INDIA

Re: K212690

Trade/Device Name: qXR-BT Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH Dated: November 22, 2021 Received: November 24, 2021

Dear Bunty Kundnani:

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

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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 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 (OS) 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 (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

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) K212690

Device Name qXR-BT

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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510(k) SUMMARY Qure.ai's qXR-BT

1 SUBMITTER

Qure.ai Technologies Level 7, Commerz II, International Business Park Oberoi Garden City, Goregaon (E), Mumbai 400 063 Phone: +91-9768123013 Contact Person: Bunty Kundnani

Date Prepared: November 22, 2021

2 DEVICE

Name of Device:	qXR-BT
Common or Usual Name:	Automated Radiological Image Processing Software
Classification Name:	Medical image management and processing system
Regulatory Class:	Class II
Regulation Number:	21 CFR 892.2050
Product Code:	QIH

PREDICATE DEVICE 3

Name of Device:	ClearRead+Confirm Image Processing System
Manufacturer:	Riverain Technologies LLC
510(k) Number:	K123526

4 INTENDED USE / INDICATIONS FOR USE:

The qXR-BT device is intended to generate a secondary digital chest X-ray image that facilitates confirmation of the position of a breathing tube and an anatomical landmark on adult chest Xrays. This device is intended for use by licensed physicians who are trained in the evaluation of breathing tube placement on chest X-rays. The qXR-BT image provides adjunctive information and is not a substitute for the original PA/AP image.

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ട DEVICE DESCRIPTION

The input to the qXR-BT device is a chest X-ray (AP and PA, referred to as frontal) in digital imaging and communications in medicine (DICOM) format.

The qXR-BT device produces PDF and DICOM format outputs that enable users to view the position of a breathing tube and an anatomical landmark (carina).

Image /page/4/Figure/8 description: This image shows a flowchart of the qXR-BT Analysis process. The process starts with chest x-ray scans in DICOM format, followed by pre-processing, core processing, and post-processing. The output of the post-processing step is then used to generate a secondary image with markers and labels in DICOM format, as well as a report with a preview image and table in PDF format. The title of the flowchart is "qXR-BT Analysis".

Figure 1: Schematic showing the design of qXR-BT device

б COMPARISON WITH PREDICATE DEVICE

Like the potential predicate devices, qXR-BT facilitates the confirmation of placement of a medically inserted tube on chest X-rays. In terms of establishing substantial equivalence, the subject and predicate device have the same intended use, as an image processing tool that generates a secondary digital radiographic image to facilitate the confirmation of the position of

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medically inserted tube. The indications for use proposed for the subject device are similar to those of the predicate device, with the primary difference being that the predicate device is intended to facilitate the confirmation of multiple types of lines, tubes, and wires, while the subject device is intended to facilitate the confirmation of only one type of tube, viz. breathing tubes.

	Predicate DeviceClearRead+Confirm(K123526)	Subject DeviceqXR-BT
Device Name	ClearRead+Confirm	qXR-BT
510(k) Number	K123526	K212690
Regulation	21 CFR 892.2050	21 CFR 892.2050
Regulation Description	Medical image managementand processing systemFormerly: Picture archivingand communications system	Medical image management andprocessing system
Product Code	LLZ	QIH
Device type	Radiological ImageProcessing System	Automated Radiological ImageProcessing Software
Manufacturer	Riverain Technologies	Qure.ai Technologies
Intended use / Indicationsfor Use	ClearRead+Confirm isintended to generate anenhanced, secondary digitalradiographic image of thechest to facilitateconfirmation of line/tubes.The enhanced AP or PAimage of the chest providesimproved visibility of linesand tubes. The ClearRead+Confirm image providesadjunctive information andis not a substitute for theoriginal PA/AP image. Thisdevice is intended to be usedby trained professionals,such as physicians,radiologists, and technicians,on patients with lines andtubes and is not intended tobe used on pediatricpatients.	The qXR-BT device is intended togenerate a secondary digital chest X-ray image that facilitatesconfirmation of the position of abreathing tube and an anatomicallandmark on adult chest X-rays. Thisdevice is intended for use by licensedphysicians who are trained in theevaluation of breathing tubeplacement on chest X-rays. The qXR-BT image provides adjunctiveinformation and is not a substitutefor the original PA/AP image.
Modality	Digital chest radiograph	Digital chest radiograph
Input format	DICOM	DICOM
	Predicate DeviceClearRead+Confirm(K123526)	Subject DeviceqXR-BT
Output Format	Secondary digital chest X-rayimage	Secondary digital chest X-ray imageand other Multiple electronic reportswith localization information ofsegmented structures
Intended User	Physicians, radiologists andtechnicians	Physicians and radiologists
Hardware	No additional hardware;standalone software devicethat integrates with PACSthrough DICOM protocols	qXR-BT is standalone softwaredeployed on-premise or on thecloud, that integrates with PACS orother hardware or software imagingplatforms, including digitalradiographic processing systemsthrough DICOM protocols
Comparison of Differences between qXR-BT and the predicate device
Types of lines and tubes	Various medically insertedtubes, lines, tubes and wires	Medically inserted breathing tubes(tracheal tubes) only
Internal algorithms usedfor image processing andthe mechanism by whichthe output is displayed tothe clinician	ClearRead+Confirm uses abone suppressionmechanism with overallimage enhancements toimprove the visibility of linesand tubes and provides noboxes or markings to theuser.	qXR-BT uses pre-trainedconvolutional neural networks toprocess the images, and the devicehighlights the tip of the tube and thecarina using markings on thesecondary image.

Table 1: Comparison between qXR-BT and the Predicate Device

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7 TESTING

Software

Software verification and validation testing were conducted, and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." The software for this device has a Moderate level of concern.

Performance Testing

Qure.ai performed standalone performance testing to test the accuracy of qXR-BT's analysis. The number of Chest X-ray images used for this performance testing was 162. Table 2 shows localization accuracy for the 2 target structures – carina and tip of breathing tube and the accuracy of distance measurement between these 2 structures. The ground truth was based on manual annotation of three radiologists from United States. For the target structures, the

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standalone performance exceeded the preset acceptance criteria. The table below shows a summary of the results of performance testing.

TargetStructure(Number ofscans)	Metric	Mean(StandardDeviation)	Median (10th -90th percentile)	Mean (95% CI)	Success Criteria
Carina (162)	AbsoluteDistance	2.15 (1.25)	1.86 (0.63 -4.05)	2.15 (1.96 -2.35)	Upper bound of95% CI ≤ 3mm
Tip ofBreathingTube (162)	AbsoluteDistance	1.97 (1.09)	1.8 (0.7 - 3.64)	1.97 (1.80 –2.13)	Upper bound of95% CI ≤ 3mm
Distancebetween tipof breathingtube andcarina (162)	AbsoluteError	1.98 (1.41)	1.64 (0.27 -4.12)	1.98 (1.76 –2.20)	Upper bound of95% CI ≤ 6mm

Table 2: Overall Results of Accuracy Testing in mm

Cl = confidence interval

qXR-BT also passed software validation and system verification checks.

8 CONCLUSION

The comparison in Table 2 and the software and performance testing presented above demonstrate that the qXR-BT device is substantially equivalent to the predicate device.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).