MEDO ARIA is designed to view and quantify ultrasound image data using machine learning techniques to aid trained medical professionals in diagnosis of developmental dysplasia of the hip (DDH). The device is intended to be used on neonates and infants, aged 0 to 12 months.

Device Description

MEDO ARIA is a cloud-based standalone software as a medical device (SaMD) that helps qualified users with image-based assessment of developmental hip dysplasia (DDH) of pediatric patients (e.g., ages 0 to 12 months). It is designed to support the workflow by helping the radiologist to evaluate, quantify, and generate reports for hip images. MEDO ARIA Software takes as an input imported Digital Imaging and Communications in Medicine (DICOM) images from ultrasound scanners and allows users to upload, browse, and view images, measure alpha angle and acetabular coverage, and manipulate 2D and 3D infant hip ultrasound images, as well as create and finalize examination reports. It provides users with a specific toolset for viewing pediatric ultrasound hip images, placing landmarks, and creating reports.

AI/ML Overview

Here's an analysis of the provided text to extract the acceptance criteria and study details for the MEDO ARIA device:

The provided document, a 510(k) summary for the MEDO ARIA device, offers limited details specifically on acceptance criteria and a dedicated "study that proves the device meets the acceptance criteria." The document primarily focuses on demonstrating substantial equivalence to a predicate device and outlining the device's features and indications for use.

However, we can infer some information from the "Performance Data" and the general context.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics. It generally states: "Safety and performance of MEDO ARIA have been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing."

Without specific numerical targets, it's impossible to create a precise table. However, based on the functionalities listed, the implied performance criteria would likely revolve around the accuracy, precision, and usability of its quantitative analysis tools (alpha angle and coverage measurement), landmark placement (manual and semi-automatic), and Graf classification.

Implied Acceptance Criteria and Reported Performance (Inferred)

Acceptance Criterion (Inferred)	Reported Device Performance
Accuracy of Alpha Angle Measurement	No specific numerical accuracy reported. The device provides quantitative analysis for "Angle (alpha angle)." Its performance has been "evaluated and verified in accordance with software specifications."
Accuracy of Acetabular Coverage Measurement	No specific numerical accuracy reported. The device provides quantitative analysis for "Distance ratio (coverage)." Its performance has been "evaluated and verified in accordance with software specifications."
Accuracy of Semi-Automatic Landmark Placement	No specific numerical accuracy reported. The device supports "Semi-automatic landmark placement" which is specified as "user-modifiable." Its performance has been "evaluated and verified in accordance with software specifications."
Correctness of Hip Graf Classification	No specific agreement rate or correctness metric reported. The device provides "Lookup-table-based Graf Classification," which is "user-modifiable." Its performance has been "evaluated and verified in accordance with software specifications."
Software Functionality and Usability (e.g., image display, navigation, report generation)	All key features listed (2D visualization, slice-scroll, manual/semi-automatic landmark placement, alpha/coverage measurements, Graf classification, report generation) are presumed to function as intended and meet internal specifications, based on "software verification and validation testing."
Compliance with Software Standards	The device was evaluated in accordance with "IEC 62304:2006/AC:2015 - Medical device software -Software life cycle processes" and the "FDA Guidance document, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.'"

2. Sample Size for the Test Set and Data Provenance

The document does not provide any specific information regarding the sample size used for the test set or the provenance (e.g., country of origin, retrospective/prospective) of the data used for any testing.

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

The document does not provide any information about the number or qualifications of experts used to establish ground truth for a test set.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for a test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it provide any effect size for human reader improvement with AI assistance. The device is described as an aid to "trained medical professionals," implying human-in-the-loop, but formal comparative studies are not detailed.

6. If a Standalone Study (algorithm only without human-in-the-loop performance) was done

The entire description of the software, particularly its role in "helping the radiologist to evaluate, quantify, and generate reports" and "aid trained medical professionals in diagnosis," suggests a human-in-the-loop context. However, the quantitative analyses (alpha angle, coverage, Graf classification) are likely performed by the algorithm in a standalone manner before the user's final decision. The document does not explicitly state if a standalone performance study (algorithm only) was conducted for these specific measurements, separate from interaction with a human.

7. The Type of Ground Truth Used

The document does not specify the type of ground truth used (e.g., expert consensus, pathology, outcomes data). Given the nature of hip ultrasound measurements, expert consensus from radiologists or orthopedic specialists reviewing the images and confirming measurements would be a likely ground truth, but this is not explicitly stated.

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size used for the training set.

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

The document does not provide any information on how the ground truth for the training set was established.

Summary of Missing Information:

The provided 510(k) summary is very high-level regarding the performance evaluation. It lacks critical details that would typically be found in a detailed clinical or validation study report, such as:

Specific quantitative acceptance criteria (e.g., "alpha angle measurement must be within X degrees of ground truth").
Performance metrics (e.g., sensitivity, specificity, AUC, mean absolute error, inter-reader variability improvement).
Details about the datasets used (size, characteristics, provenance).
Information about expert review for ground truth (number, qualifications, adjudication).
Details of any comparative studies (MRMC or standalone algorithm performance).

The current document focuses on demonstrating that software verification and validation activities were performed in accordance with applicable standards and that the device is substantially equivalent to a predicate, without delving into the specifics of how well it performs against defined metrics.

Summary

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Image /page/0/Picture/0 description: The image contains the logos of the Department of Health & Human Services and the U.S. Food & Drug Administration (FDA). The Department of Health & Human Services logo is on the left, featuring a stylized symbol. To the right is the FDA logo, with the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" and "ADMINISTRATION" in blue text.

MEDO DX Pte. Ltd. (0/A MEDO.ai) % Dornoosh Zonoobi CEO and Co-founder 32 Carpenter Street 059911 SINGAPORE

June 11, 2020

Re: K200356

Trade/Device Name: MEDO ARIA Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: QIH Dated: May 7, 2020 Received: May 8, 2020

Dear Dornoosh Zonoobi:

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/cfpmp/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); 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

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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) K200356

Device Name MEDO ARIA

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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K200356

Section 5. 510(k) Summary

5.1 General Information

510(k) Sponsor	MEDO Dx Pte. Ltd. (O/A MEDO.ai)
Address	32 CARPENTER STREET SINGAPORE 059911
Correspondence Person	Dornoosh Zonoobi
Contact Information	780-991-9462dornoosh@medo.ai
Date Prepared	May 7, 2020

5.2 Proposed Device

Proprietary Name	MEDO ARIA
Common Name	ARIA
Classification Name	Automated Radiological Image Processing Software
Regulation Number	21 CFR 892.2050
Product Code	QIH
Regulatory Class	II

5.3 Predicate Device

Proprietary Name	QLAB Advanced Quantification Software
Premarket Notification	K191647
Classification Name	Automated Radiological Image Processing Software
Regulation Number	21 CFR 892.2050
Product Code	QIH
Regulatory Class	II

5.4 Device Description

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MEDO ARIA Software takes as an input imported Digital Imaging and Communications in Medicine (DICOM) images from ultrasound scanners and allows users to upload, browse, and view images, measure alpha angle and acetabular coverage, and manipulate 2D and 3D infant hip ultrasound images, as well as create and finalize examination reports. It provides users with a specific toolset for viewing pediatric ultrasound hip images, placing landmarks, and creating reports.

Key features of the software are:

2D image visualization including one or more image frames that may have a spatial . or temporal relationship
Slice-scroll (frame scroll) ●
Manual and semi-automatic landmark placements ●
Alpha and coverage measurements 0
Hip Graf classification ●
Report generation ●

5.5 Indications for Use

5.6 Comparison of Technological Characteristics with the Predicate Device

Feature/Function	Subject DeviceMEDO ARIA	Predicate DeviceQLAB AdvancedQuantification (K191647)
Image input	Complies with DICOMStandard	Complies with DICOMStandard
Scan type	2D and 3D Ultrasound	2D and 3D Ultrasound
Image displaymode	Static	Static
Image navigationand manipulationtools	Adjust image brightness andcontrast, slice-scroll, panelayout, reset	Adjust image brightnessand contrast, slice-scroll,pane layout, reset

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2D image review	Yes, capable of reviewing allframes of multi-frame(multi-slice) image	Yes
Manual landmarkplacement	Yes	Yes
Semi-automaticlandmarkplacement	Yes, user-modifiable	Yes, user-modifiable
Quantitativeanalysis	• Angle (alpha angle)• Distance ratio (coverage)	• Distance• Area
Lookup-table-basedGraf Classification	Yes, user-modifiable	No
Report creation	Yes	No

5.7 Performance Data

Safety and performance of MEDO ARIA have been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing. Additionally, the software validation activities were performed in accordance with IEC 62304:2006/AC:2015 - Medical device software -Software life cycle processes, in addition to the FDA Guidance document, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."

5.8 Conclusion

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

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).