Clarius OB Al is intended to assist in measurements of fetal biometric parameters (i.e., head circumference, abdominal circumference, femur length, bi-parietal diameter, crown rump length) on ultrasound data acquired by the Clarius Ultrasound Scanner (i.e., curvilinear scanner). The user shall be a healthcare professional trained and qualified in ultrasound. The user retains the responsibility of confirming the validity of the measurements based on standard practices and clinical judgment. Clarius OB Al is indicated for use in adult patients only.

Device Description

Clarius OB Al is a machine learning algorithm that is incorporated into the Clarius App software as part of the complete Clarius Ultrasound Scanner system for use in obstetric (OB) ultrasound imaging applications. Clarius OB Al is intended for use by trained healthcare practitioners for non-invasive measurements of fetal biometric parameters on ultrasound data acquired by the Clarius Ultrasound Scanner system (i.e., curvilinear scanner) using a deep learning image segmentation algorithm.

During the ultrasound imaging procedure, the anatomical site is selected through a preset software selection (i.e., OB, Early OB) within the Clarius App in which Clarius OB Al will engage to segment the fetal anatomy and place calipers for measurement of fetal biometric parameters.

Clarius OB Al operates by performing the following tasks:

Automatic detection and measurement of head circumference (HC)
Automatic detection and measurement of abdominal circumference (AC)
Automatic detection and measurement of femur length (FL)
Automatic detection and measurement of bi-parietal diameter (BPD)
Automatic detection and measurement of crown rump length (CRL)

Clarius OB Al operates by performing automatic measurements of fetal biometric parameters. The user has the option to manually adjust the measurements made by Clarius OB Al by moving the caliper crosshairs. Clarius OB Al does not perform any functions that could not be accomplished manually by a trained and qualified user. Clarius OB AI is intended for use in B-Mode only.

Clarius OB Al is an assistive tool intended to inform clinical management and is not intended to replace The clinician retains the ultimate responsibility of ascertaining the clinical decision-making. measurements based on standard practices and clinical judgment. Clarius OB Al is indicated for use in adult patients only.

Clarius OB Al is incorporated into the Clarius App software, which is compatible with iOS and Android operating systems two versions prior to the latest iOS or Android stable release build and is intended for use with the following Clarius Ultrasound Scanner system transducer (previously 510(k)-cleared in K213436). Clarius OB Al is not a stand-alone software device.

AI/ML Overview

Here's a summary of the acceptance criteria and study details for the Clarius OB AI device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Parameter	Acceptance Criteria (Implicit)	Clarius OB AI Reported Performance
Fetal Biometric Measurements (HC, AC, FL, BPD, CRL)	Non-inferiority to manual measurements performed by qualified experts	Clarius OB AI was found to be non-inferior to human experts with statistically significant p-values (<2.2e-16) for all fetal biometric measurements.
Agreement with Expert Measurements	Strong agreement	Strong agreement shown between Clarius OB AI measurements and the mean of expert clinicians' measurements for all fetal biometrics. Strong agreements also shown with individual expert measurements.
Inter-rater Reliability (ICC)	High correlation (implied for both device-expert and expert-expert)	ICC across all fetal biometrics between Clarius OB AI and the reviewers was calculated to be 0.99 (95% CI 0.994—0.997).
Segmentation Performance (Dice Score)	High score	Range of average Dice scores (for all anatomical structures) between Clarius OB AI and reviewers was 0.84 (95% CI 0.83—0.87) to 0.97 (95% CI 0.96—0.97).
Segmentation Performance (Jaccard Score)	High score	Range of average Jaccard scores (for all anatomical structures) between Clarius OB AI and reviewers was 0.73 (95% CI 0.72—0.74) to 0.94 (95% CI 0.93—0.94).
Clinical Usability / Performance as Intended	Device performs as intended in a representative user environment, meets product requirements, is clinically usable, and meets users' needs for semi-automated fetal biometric measurements.	Validation study showed consistent results among all users, meeting pre-defined acceptance criteria. Users successfully activated Clarius OB AI, obtained images, performed live segmentation, automatic measurements, manual adjustments, and saved measurements.

2. Sample Size for Test Set and Data Provenance

Sample Size for Test Set: 347 subjects
Data Provenance: Retrospective analysis of anonymized ultrasound images from 25 clinical sites in the United States, Canada, Philippines, Australia, Kenya, Belgium, and Malaysia. The data represented different ethnic groups and ages (15-45 years). The test data was explicitly stated to be independent from the training and validation (tuning) datasets.

3. Number of Experts and Qualifications for Ground Truth

Number of Experts: 3 reviewers (clinical truthers) per image.
Qualifications of Experts: Qualified experts with relevant (i.e., OB/fetal) ultrasound experience.

4. Adjudication Method for Test Set

Adjudication Method: Each image had fetal biometric measurements performed by 3 reviewers. Each reviewer was blinded to the Clarius OB AI output and the other reviewers' annotations. The reported performance metrics (e.g., ICC, Dice, Jaccard) compare the Clarius OB AI output against the mean of the expert clinicians' measurements, indicating that the mean of the three expert measurements served as the ground truth. This is a form of consensus, where the average of multiple independent readings establishes the reference.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

The provided text describes a study where device performance was compared to human experts, but it does not describe a comparative effectiveness study designed to measure the effect size of how much human readers improve with AI vs. without AI assistance (i.e., human-in-the-loop performance). The study focuses on the standalone performance of the AI compared to human experts.

6. If a Standalone (Algorithm Only) Performance Study was done

Yes, a standalone performance study was done. The "Summary of the Verification Study" specifically states that the primary objective was to verify that Clarius OB AI automeasurements are non-inferior to manual measurements performed by expert clinicians, and each reviewer was blinded to the Clarius OB AI output. This indicates an evaluation of the algorithm's performance independent of human interaction.

7. Type of Ground Truth Used

Expert Consensus: The ground truth for the test set was established by manual measurements and boundary outlines (segmentation) performed by 3 qualified expert clinicians, with the mean of these measurements serving as the reference for comparison with the AI.

8. Sample Size for the Training Set

The document mentions that the Clarius OB Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. It states that the validation (tuning) data was 10% of the training data. However, the exact sample size for the training set is not explicitly provided. It only states that validation data was 10% of training data, and the test set was independent.

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

The document states: "...anonymized ultrasound images from 25 clinical sites in the United States, Philippines, Australia, Kenya, Belgium, Malaysia, and Canada, representing various ethnicities and ages." And "The Clarius OB Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. The validation (tuning) data was 10% of the training data, while the test data was independent and labelled by experts."

While it confirms experts labeled the test data, it does not explicitly describe how the ground truth for the training set was established. It only generally mentions "clinical and/or artificial data intended for non-invasive analysis (i.e., quantitative and/or qualitative) of ultrasound data." and that the data was from "anonymized multi-center database". It's implied that this training data would similarly be labeled for the AI to learn from, but the specific process (e.g., number of experts, qualifications, adjudication for training data) is not detailed.

Summary

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Image /page/0/Picture/0 description: The image contains 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 logo on the right. The FDA logo features the letters 'FDA' in a blue square, followed by the words 'U.S. FOOD & DRUG ADMINISTRATION' in blue text.

Clarius Mobile Health Corp. Agatha Szeliga Director, Regulatory Affairs 205-2980 Virtual Way Vancouver, BC V5M 4X3 Canada

Re: K233955

June 14, 2024

Trade/Device Name: Clarius OB AI Regulation Number: 21 CFR 892.1550 Regulation Name: Ultrasonic pulsed doppler imaging system Regulatory Class: Class II Product Code: IYN, QIH Dated: May 7, 2024 Received: May 7, 2024

Dear Agatha Szeliga:

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

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

FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act. Under 21 CFR 807.81(a)(3), a new

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premarket notification is required if there is a major change or modification in the intended use of a device, or if there is a change or modification in a device that could significantly affect the safety or effectiveness of the device, e.g., a significant change or modification in design, material, chemical composition, energy source, or manufacturing process. Accordingly, if deviations from the established PCCP result in a major change or modification in the intended use of the device, or result in a change or modification in the device that could significantly affect the safety or effectiveness of the a new premarket notification would be required consistent with section 515C(b)(1) of the Act and 21 CFR 807.81(a)(3). Failure to submit such a premarket submission would constitute adulteration and misbranding under sections 501(f)(1)(B) and 502(o) of the Act, respectively.

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).

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 (OS) 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-regulatory

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assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Jessica Lamb

Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

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Indications for Use

Form Approved: OMB No. 0910-0120 Expiration Date: 07/31/2026 See PRA Statement below.

Submission Number (if known)

K233955

Device Name

Clarius OB Al

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)

CONTINUE ON A SEPARATE PAGE IF NEEDED.

This section applies only to requirements of the Paperwork Reduction Act of 1995.

DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.

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"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."

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Image /page/4/Picture/0 description: The image shows the Clarius logo. On the left is an orange icon that looks like three curved lines that form a C shape. To the right of the icon is the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal.

510(k) Summary

This 510(k) summary of safety and effectiveness information is submitted in accordance with the requirements of 21 CFR § 807.92.

Subject Device Trade Name:	Clarius OB AI
Device Classification Name:	Ultrasonic Pulsed Doppler Imaging System; AutomatedRadiological Image Processing Software

Regulation Number, Name and Product Code:

Regulation Number	Regulation Name	Primary Product Code
21 CFR § 892.1550	Ultrasonic Pulsed Doppler Imaging System	IYN
Regulation Number	Regulation Name	Secondary Product Code
21 CFR § 892.2050	Medical Image Management and Processing System	QIH

FDA 510(k) Review Panel:	Radiology
Classification:	Class II
Manufacturer:	Clarius Mobile Health Corp.205-2980 Virtual WayVancouver, BC V5M 4X3 Canada
Contact Name:	Agatha SzeligaDirector, Regulatory Affairsagatha.szeliga@clarius.com
Date 510(k) Summary Prepared:	June 13, 2024

Predicate Device Information:

Device Trade Name:	Sonio Detect
510(k) Reference:	K230365
Manufacturer Name:	Sonio
Regulation Name:	Ultrasonic Pulsed Doppler Imaging System
Device Classification Name:	Ultrasonic Pulsed Doppler Imaging SystemUltrasonic Pulsed Echo Imaging SystemMedical Image Management and Processing System
Product Code(s):	IYN; IYO; QIH
Regulation Number:	21 CFR § 892.1550; 21 CFR § 892.1560; 21 CFR § 892.2050
Regulatory Class:	Class II

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Image /page/5/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange icon on the left and the word "clarius" in dark teal on the right. To the right of the word "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal. The icon on the left is a stylized "C" made up of three curved lines.

Note: The predicate device has not been subject to a design-related recall.

Device Description

Clarius OB Al operates by performing the following tasks:

Automatic detection and measurement of head circumference (HC)
Automatic detection and measurement of abdominal circumference (AC)
Automatic detection and measurement of femur length (FL)
Automatic detection and measurement of bi-parietal diameter (BPD)
Automatic detection and measurement of crown rump length (CRL)

Clarius Ultrasound Transducer	C3 HD3
Clarius App Software	Clarius Ultrasound App (Clarius App) for iOS;Clarius Ultrasound App (Clarius App) for Android

Indications for Use for Clarius OB Al

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Image /page/6/Picture/0 description: The image is the logo for Clarius Ultrasound. The logo consists of an orange symbol that looks like a stylized letter C made of three curved lines. To the right of the symbol is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" in a smaller font and the same dark teal color. The logo is simple and modern, and the colors are bright and eye-catching.

be a healthcare professional trained and qualified in ultrasound. The user retains the responsibility of confirming the validity of the measurements based on standard practices and clinical judgment. Clarius OB Al is indicated for use in adult patients only.

Comparison of the Subject Device and Legally Marketed Device for Demonstration of Substantial Equivalence

The following table provides a comparison of the subject device, Clarius OB Al, to the predicate device. A comparison of the subject device to the predicate device shows that the subject device has the same intended use, similar indications for use, the same principle of operation, and is based on a similar Al/ML algorithm providing segmentation and measurement of fetal biometric parameters, comparable to the legally marketed device referenced herein.

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Image /page/7/Picture/0 description: The image shows the Clarius ultrasound anywhere logo. The logo consists of an orange symbol that looks like three letter C's nested inside each other. To the right of the symbol is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" stacked on top of each other, also in dark teal.

Table 1 - Comparison of the Subject Device to the Legally Marketed Predicate Device

Criteria	SUBJECT DEVICE	PREDICATE DEVICE	RATIONALE(if subject device differsfrom predicate device)
	Clarius OB AI	Sonio Detect
510(k) Holder/ Manufacturer	Clarius Mobile Health Corp.	Sonio	Not applicable
Submission Reference	Current Submission	K230365	Not applicable
Product Code(s)	IYN; QIH	IYN; IYO; QIH	The "IYN" primary productcode is the same as thepredicate device and the"QIH" secondary productcode is the same as thepredicate device.
Device Classification Name	Ultrasonic Pulsed Doppler ImagingSystem;Medical Image Management andProcessing System	Ultrasonic Pulsed Doppler ImagingSystem;Ultrasonic Pulsed Echo Imaging System;Medical Image Management andProcessing System	The "Ultrasonic PulsedDoppler Imaging System"and the "Medical ImageManagement andProcessing System" deviceclassification names arethe same as the predicatedevice.
Regulation Number	21 CFR § 892.1550;21 CFR § 892.2050	21 CFR § 892.1550;21 CFR § 892.1560;21 CFR § 892.2050	The "21 CFR § 892.1550"regulation number and the"21 CFR § 892.2050"regulation number are thesame as the predicatedevice.
Intended Use	Intended for use as an assistive tool/aidduring the acquisition and interpretationof fetal ultrasound images through non-invasive processing of ultrasound imagesutilizing an artificial intelligence/machine-learning algorithm.	Intended for use as an assistive tool/aidduring the acquisition and interpretationof fetal ultrasound images through non-invasive processing of ultrasound imagesutilizing an artificial intelligence/machine-learning algorithm.	Same as predicate device.
Indications for Use	Clarius OB AI is intended to assist inmeasurements of fetal biometricparameters (i.e., head circumference,abdominal circumference, femur	Sonio Detect is intended to analyze fetalultrasound images and clips usingmachine learning techniques toautomatically detect views, detect	Both the predicate andsubject device areindicated for analysis offetal ultrasound images
Criteria	SUBJECT DEVICE	PREDICATE DEVICE	RATIONALE(if subject device differs
	Clarius OB AI	Sonio Detect	from predicate device)
	length, bi-parietal diameter, crownrump length) on ultrasound dataacquired by the Clarius UltrasoundScanner (i.e., curvilinear scanner).The user shall be a healthcareprofessional trained and qualified inultrasound. The user retains theresponsibility of confirming thevalidity of the measurements basedon standard practices and clinicaljudgment. Clarius OB AI is indicatedfor use in adult patients only.	anatomical structures within the viewsand verify quality criteria of the views.The device is intended for use as aconcurrent reading aid during theacquisition and interpretation of fetalultrasound images.	using AI/ML techniques.Both devices detectvarious fetal anatomies;the predicate deviceprovides qualitativeinformation to the user,whereas the subjectdevice provides semi-automated quantitativeinformation regardingfetal biometrics. Both thepredicate and subjectdevices are intended foruse as an adjunctive 'tool'or aid by the user for theinterpretation of fetalultrasound images and arenot intended to replaceclinical decision making.The differences in theindications for use do notimpact the safety andeffectiveness of thesubject device relative tothe predicate device.
Radiological application/ Supportedmodality	Ultrasound	Ultrasound	Same as predicate device.
Clinical application(s)	Obstetrics/Fetal	Obstetrics/Fetal	Same as predicate device.
Principle of Operation/ Technology	Ultrasound image processing softwareapplication implementing artificialintelligence utilizing non-adaptivemachine learning algorithms trained with	Ultrasound image processing softwareapplication implementing artificialintelligence utilizing non-adaptivemachine learning algorithms trained with	Same as predicate device.
	clinical and/or artificial data intended for	clinical and/or artificial data intended for
Criteria	SUBJECT DEVICE	PREDICATE DEVICE	RATIONALE(if subject device differsfrom predicate device)
	Clarius OB AI	Sonio Detect
Quantitative and/or QualitativeAnalysis	non-invasive analysis (i.e., quantitativeand/or qualitative) of ultrasound data.Fetal biometry/measurement of fetalbiometric parameters (i.e., HC, AC, BPD,CRL, FL)	non-invasive analysis (i.e., quantitativeand/or qualitative) of ultrasound data.Detection, verification, and qualitativeanalysis of fetal anatomical structures	The subject deviceperforms semi-automatedmeasurements of fetalbiometrics, whereas thepredicate device detects,verifies, and performsqualitative analysis of fetalanatomies.
Algorithm Methodology	Artificial Intelligence (AI)	Artificial Intelligence (AI)	Same as predicate device.
Automation (Yes or No)	Yes	Yes	Same as predicate device.
Environment of Use	Healthcare setting (e.g., hospital, clinic)	Healthcare setting (e.g., hospital, clinic)	Same as predicate device.
Intended Users	Licensed healthcare professionals	Licensed healthcare professionals	Same as predicate device.
Platform	Embedded in the Clarius ultrasound app	Cloud-based and stand-alone software	The subject device isembedded in theultrasound app, which ispart of the ultrasoundsystem, whereas, thepredicate device is cloud-based, stand-alonesoftware

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sound y anywhere

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sound ر where

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Image /page/10/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange icon that looks like three curved lines forming a C shape. To the right of the icon is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" stacked on top of each other in a smaller font size and the same dark teal color.

Non-Clinical Performance Testing Summary

Clarius OB Al was designed and developed by Clarius Mobile Health Corp. in accordance with the applicable requirements, design controls, and standards to establish safety and effectiveness of the device.

Non-clinical performance testing has demonstrated that Clarius OB Al complies with the following FDArecognized consensus standards:

StandardRecognitionNumber	Title of Standard
13-79	IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes
5-125	ISO 14971:2019 Medical devices — Application of risk management to medical devices
12-349	NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set
5-129	IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering tomedical devices
5-134	ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labellingand information to be supplied

Safety and performance of Clarius OB Al have been evaluated through verification testing in accordance with applicable specifications and performance standards. The traceability analysis provides traceability between the requirement specifications, risks, and verifications, risks, and verification testing of the subject device. All requirements and risk controls have been successfully verified and traced. A comprehensive risk analysis was performed for the subject device and appropriate risk controls have been implemented to mitigate hazards.

Software verification and validation activities were conducted in accordance with IEC 62304:2006 + AMD1:2015 – Medical device software – Software lifecycle processes and ISO 14971:2019 Medical devices – Application of risk management to medical devices, and in accordance with relevant FDA guidance documents, General Principles of Software Validation, Final Guidance for Industry and FDA Staff (issued January 11, 2002), Guidance for the Content of Premarket Submissions for Device Software Functions (issued June 14, 2023), and Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions (issued September 27, 2023).

Clarius conforms to the cybersecurity requirements by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed or transferred from a medical device to an external recipient.

Clarius OB Al was tested and found to be safe and effective for the intended users, intended patient population, and use environments, as demonstrated through verification testing. Validation testing was performed to ensure that the final product meets the requirements for the specified clinical application and performs as intended to meet users' needs, while demonstrating substantial equivalence to the predicate device.

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Image /page/11/Picture/0 description: The image shows the Clarius ultrasound logo. The logo consists of an orange symbol that looks like three letter C's nested inside each other, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal.

Clinical Performance Testing Summary

Following completion of the Clarius OB Al model training and tuning, which was conducted to create a documented baseline of the AI model, verification testing, and clinical validation were performed.

The clinical performance of Clarius OB Al was evaluated through a retrospective analysis of anonymized ultrasound images from 25 clinical sites in the United States, Canada, Philippines, Australia, Kenya, Belgium, and Malaysia, representing different ethnic groups and ages. The age of the subjects in the study ranged from 15 - 45 years. The verification data was entirely independent from the training, validation (tuning), and test datasets.

The Clarius OB Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. The validation (tuning) data was 10% of the training data, while the test data was independent and labelled by experts. The DNN parameters and weights were updated based on the validation (tuning) data at each epoch. The model's generalizability was evaluated on the test data. The test data was exclusive and independent to ensure robust results.

The objective of clinical performance testing (verification) was to verify that Clarius OB Al automeasurements are non-inferior to manual measurements performed by qualified experts with relevant (i.e., OB/fetal) ultrasound experience.

Summary of the Verification Study

Ultrasound images were randomly obtained from an anonymized multi-center database of images from the United States, Philippines, Australia, Kenya, Belgium, Malaysia, and Canada, representing various ethnicities and ages. The age of the study ranged from 15 - 45 years. Institutions included in the Clarius OB Al model training and tuning dataset were excluded from this study. Images of the fetal head, abdomen, and femur were collected in cases where the gestational age was greater than 13 weeks and images of the entire fetus were collected in cases where the gestational age was less than 13 weeks. The total sample size included in the study was 347 subjects.

The primary objective of the retrospective verification study was to verify that Clarius OB Al fetal biometric measurements (i.e., CRL, BPD, HC, AC, and FL) are non-inferior to manual measurements performed by expert clinicians. The secondary objective of the study was to verify a high correlation between fetal gestational age calculated using manual expert measurements and Clarius OB Al biometric measurements. To calculate the gestational age from fetal biometric measurements Hadlock equations were used. Each reviewer also outlined the boundaries (segmentation) of the fetus, fetal head, and femur as applicable. Each image had fetal biometric measurements performed by 3 reviewers (clinical truthers). Each reviewer was blinded to the Clarius OB Al output and the other reviewers' annotations as well. All obstetric exams of the fetus/fetal anatomy were captured using a Clarius C3 (curvilinear) ultrasound scanner.

An assessment of the magnitude of the difference between Clarius OB Al and human experts' fetal biometric measurements was performed to ascertain whether Clarius OB Al measurement is non-inferior to those of human experts/ qualified ultrasound users. Clarius OB Al was found to be non-inferior to human experts with statistically significant p-values (<2.2 e-16) for the various fetal biometric measurements. The fetal gestational age in the study ranged from around 58 days to 271 days.

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Image /page/12/Picture/0 description: The image shows the Clarius ultrasound anywhere logo. The logo consists of an orange symbol that looks like three concentric letter C's, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal.

Strong agreement was shown between the Clarius OB Al measurements and the mean of the expert clinicians' measurements for all fetal biometrics (HC, BPD, FL, AC, and CRL). The Clarius OB Al model also showed strong agreements with individual expert measurements. The intraclass correlation coefficients (ICC) for inter-rater reliability were calculated between reviewer pairs and between the Clarius OB Al output and the mean reviewer measurement. ICC across all fetal biometrics between Clarius OB Al and the reviewers was calculated to be 0.99 (95% Cl 0.994—0.997). To assess the segmentation performance of Clarius OB Al, the average dice and Jaccard scores between the Clarius OB Al model vs. each reviewer and between each reviewer pair were also calculated. The range of the average Jaccard scores (for all anatomical structures) between Clarius OB Al and the reviewers was 0.73 (95% Cl 0.72--0.74) to 0.94 (95% Cl 0.93--0.94), and the range of the average dice scores (for all anatomical structures) between Clarius OB Al and the reviewers was 0.84 (95% Cl 0.83--0.87) to 0.97 (95% Cl 0.96--0.97).

The results of the retrospective analysis have demonstrated that Clarius OB Al measurement output adequately aligns with expert clinicians' manual measurement, confirming that Clarius OB Al measurements of fetal biometric parameters are non-inferior to those of human clinical experts. Therefore, the performance of Clarius OB Al has been verified for fetal biometric measurements for use in obstetric/fetal ultrasound applications and has been determined as reliable and accurate to clinical experts.

Summary of the Clinical Validation Study

A clinical validation study was conducted to evaluate the design and clinical utility of Clarius OB AI, as incorporated into the Clarius App software, to determine if the device performs as intended in a representative user environment, meets the product requirements, is clinically usable, and meets users' needs for use in semi-automated fetal biometric measurements.

The results of the validation study showed consistent results among all users, meeting the pre-defined acceptance criteria. The users were able to activate Clarius OB AI using Clarius' C3 scanner and choose the appropriate preset (i.e., OB, Early OB), obtain images of the fetal anatomy of interest (i.e., fetal head, femur, abdomen, or fetus), perform live segmentation, perform automatic measurements of fetal biometric parameters (AC, FL, HC, BPD, CRL), manually adjust the measurements, change the segmentation mask opacity, and save the fetal biometric measurements with each exam.

Therefore, based on the results of the clinical validation study it has been determined that Clarius OB Al performs as intended and meets user needs for use in semi-automated measurements of fetal biometric parameters in obstetric/fetal ultrasound applications for calculation of fetal gestational age.

Predetermined Change Control Plan (PCCP)

Clarius OB Al uses a machine learning (ML) algorithm for measurement of fetal biometric parameters (i.e., head circumference, abdominal circumference, femur length, bi-parietal diameter, crown rump length) on ultrasound image data acquired by the Clarius Ultrasound Scanner.

Modifications to Clarius OB Al will be made in accordance with its Predetermined Change Control Plan (PCCP). The PCCP provides a description of the device's planned modifications, a modification protocol to test, verify, validate, and implement the modifications in a manner that ensures the continued safety and effectiveness of the device, mitigating risks associated with changes to the OB Al model to not

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Image /page/13/Picture/0 description: The image shows the Clarius ultrasound anywhere logo. The logo consists of an orange icon on the left, followed by the word "clarius" in dark teal, and the words "ultrasound anywhere" in a smaller font size, also in dark teal, on the right. The icon is a stylized letter C made up of three curved lines.

adversely impact the device's performance, safety, or effectiveness associated with its indications for use, and an impact assessment of the planned modifications.

The modifications outlined in the PCCP are summarized in the table below. In accordance with the PCCP, the modified Clarius OB AI algorithm will be adequately trained, tested, and locked before release of the modified OB Al model. Implemented modifications to the Clarius OB Al algorithm will be communicated to users via the Clarius App software update notification and through updated labelling.

Modification	Rationale	Testing Methods	Impact Assessment
Modification of modelarchitecture	Improvement andoptimization of ClariusOB Al's performance	Re-training of the OB Almodel with new data tooptimize itsperformance followedby internal testing anda comparison of theoriginal OB Al model tothe modified OB Almodel (usingperformance metrics)and clinicalperformance testing(verification andvalidation).	Improvedperformancemetrics of modifiedOB Al model withincreased accuracyand more robustgestational ageestimates displayedto users.Benefit-RiskAnalysis:Benefits: Improvedperformance;generalization fordiverse cases.Risks: Overfitting;unintended bias.Risk Mitigation:Properregularizationtechniques andcross-validation anddropout will beemployed tomitigate overfitting.Internal testing andverification will beconducted tomitigate unintendedbiases.
Modification of modeltraining methods andparameters	Improvement andoptimization of ClariusOB AI's performance	Internal testing and acomparison of theoriginal OB Al model tothe modified OB AImodel (using	Improvedperformancemetrics of modifiedOB Al model.
Modification	Rationale	Testing Methods	Impact Assessment
		performance metrics)and clinicalperformance testing(verification andvalidation).	Benefit-RiskAnalysis:Benefits: Improvedperformance;generalization fordiverse cases.Risks: Overfitting;unintended bias.Risk Mitigation:Properregularizationtechniques andcross-validation anddropout will beemployed tomitigate overfitting.Internal testing andverification will beconducted tomitigate unintendedbiases.
Modification of post-processing algorithms	Improvement andoptimization of ClariusOB Al's performanceand robustness	Internal testing and acomparison of theoriginal OB Al model tothe modified OB AImodel (usingperformance metrics)and clinicalperformance testing(verification andvalidation).	Improvedperformancemetrics of modifiedOB Al model.Benefit-RiskAnalysis:Benefits: Improvedperformance;generalization fordiverse cases.Risks: Overfitting;unintended bias.Risk Mitigation:Properregularizationtechniques andcross-validation anddropout will beemployed tomitigate overfitting.
Modification	Rationale	Testing Methods	Impact Assessment
			Internal testing andverification will beconducted tomitigate unintendedbiases.
Modification of datainput sources	To enable use of ClariusOB Al on newer modelsof the 510(k)-clearedClarius UltrasoundScanner system	Re-training of the OB AImodel to expand its usewith new data sources(i.e., new 510(k)-cleared models of theClarius UltrasoundScanner), internaltesting, and clinicalperformance testing(verification andvalidation) to assessesits performance withthe new data inputsources.	By accommodating awider array of imagegeometries andcharacteristics withthe use of new510(k)-clearedClarius scanners, theupdated OB Almodel will be betterequipped to handledifferent models ofthe ClariusUltrasound Scannerused in varyingclinical scenarios.Benefit-RiskAnalysis:Benefits: Enhancedcompatibility;Flexibility for diverseclinical settings.Risks: Data skewingand concept drift.Risk Mitigation:Internal testing andverification datasetswithin the intendedpatient populationwill ensure that dataskewing andconcept drift aremitigated.

Summary of changes to Clarius OB AI per the PCCP:

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Image /page/14/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange symbol that looks like three letter C's nested inside each other. To the right of the symbol is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" stacked on top of each other in a smaller font.

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Image /page/15/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange symbol that looks like three concentric letter C's, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" stacked on top of each other, also in dark teal.

Conclusion & Summary of Substantial Equivalence

Based on the information presented in this Traditional 510(k) premarket notification and based on the fundamental scientific technology utilizing artificial intelligence/machine learning algorithms,

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Image /page/16/Picture/0 description: The image shows the Clarius ultrasound anywhere logo. The logo consists of an orange icon that looks like a stylized letter C, followed by the word "clarius" in dark teal. To the right of "clarius" is the phrase "ultrasound anywhere", also in dark teal. The logo is simple and modern, and it conveys the idea of portable ultrasound technology.

technological characteristics, principle of operation, intended use, and environment of use, Clarius OB Al has been determined to be substantially equivalent in terms of safety and effectiveness to the legally marketed predicate device.

The subject device and the predicate device employ radiological (ultrasound) image processing software applications which implement artificial intelligence/machine learning algorithms trained with clinical and/or artificial data intended for non-invasive analysis of ultrasound data, utilizing similar machinelearning based algorithms for use in obstetric/fetal ultrasound imaging applications for assessment of fetal anatomy and biometrics.

Performance testing of Clarius OB Al, including the results from verification and validation studies, has demonstrated that Clarius OB AI measurement output adequately aligns with expert clinicians' manual measurements, and thereby performs as intended for use in semi-automated fetal biometric measurements for calculation of fetal gestational age, meeting user needs.

Any differences in the indications for use or technological characteristics between the subject device and the legally marketed device do not raise any issues related to safety or effectiveness. Therefore, Clarius OB Al is as safe and effective as the predicate device, Sonio Detect (K230365), and therefore substantially equivalent.

Regulation Number and Section

§ 892.1550 Ultrasonic pulsed doppler imaging system.

(a)
Identification. An ultrasonic pulsed doppler imaging system is a device that combines the features of continuous wave doppler-effect technology with pulsed-echo effect technology and is intended to determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic tissue characteristics such as velocity of blood or tissue motion. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.