K Number

Device Name

Avenda Health AI Prostate Cancer Planning Software

Manufacturer

Avenda Health, Inc.

Date Cleared

2022-11-22

(169 days)

Product Code

POK COM

Regulation Number

892.2060

Intended Use

The Avenda Health AI Prostate Cancer Planning Software is an artificial intelligence (AI)-based decision support software, indicated as an adjunct to the review of magnetic resonance (MR) prostate images and biopsy findings in the prostate oncological workflow. The Avenda Health AI Prostate Cancer Planning Software is designed to support the prostate oncological workflow by helping the user with the segmentation of MR image features, including the prostate; in the evaluation, quantification, and documentation of lesions; and in pre-planning for diagnostic and interventional procedures such as biopsy and/or soft tissue ablation. The device is intended to be used by physicians trained in the oncological workflow in a clinical setting for planning and guidance for clinical, interventional, diagnostic, and/or treatment procedures of the prostate. The Avenda Health Al Prostate Cancer Planning Software's lesion characterization functions are intended for use on patients with a pathology-confirmed Gleason Grade Group (GGG) ≥ 2 lesion and for whom corresponding biopsy coordinate information have been uploaded. These functions are indicated for the extent of known disease. Extent of known disease refers to the boundary of a pathology confirmed lesion of GGG ≥ 2 for a particular patient. Specifically, using prostate MR images, biopsy, pathology, and clinical data, the device creates and displays a cancer map that assigns a probability to each voxel within the prostate, indicating its probability for containing clinically significant prostate cancer (csPCa, defined as GGG ≥ 2 ). A user selects a threshold for the cancer map to create a boundary of the lesion. The lesion boundary is assigned an Encapsulation Confidence Score indicating the confidence that all csPCa is encapsulated within the boundary. The Encapsulation Confidence Score is from a lookup table generated by a database of cases with known ground-truth. When interpreted by a trained physician, this information may be useful in supporting lesion characterization and subsequent patient management. The Avenda Health Al Prostate Planning Software may also be used as a medical image application, for the viewing. manipulation, 3D-visualization, and comparison of MR prostate images can be viewed in a number of output formats including volume rendering. It enables visualization of information that would otherwise have to be visually compared disjointedly.

Device Description

The Avenda Health AI Prostate Cancer Planning Software ("AI Prostate Cancer Planning Software" or "Software") is an artificial intelligence (AI)-based decision support software, indicated as an adjunct to the review of magnetic resonance (MR) prostate images and biopsy findings in the prostate oncological workflow. The Avenda Health AI Prostate Cancer Planning Software is designed to support the prostate oncological workflow by helping the user with the segmentation of MR image features, including the prostate; in the evaluation, quantification, and documentation of lesions; and in pre-planning for diagnostic and interventional procedures such as biopsy and/or soft tissue ablation. The device is intended to be used by physicians trained in the oncological workflow in a clinical setting for planning and guidance for clinical, interventional, diagnostic, and/or treatment procedures of the prostate. The software has three main features: - 1. Artificial Intelligence (AI) Powered Prostate MRI Segmentation Tool, - 2. AI Powered Lesion Contour Tool, and - 3. Simulated Interventional Tool Placement. The user can choose which subset of features of the Software to employ based on the specific oncological workflow. Not all features are required to be used for every workflow. Once the user has completed planning and has reviewed and verified the information, it can be exported into a supported file format such that it can be imported into a compatible interventional system or biopsy system.

More Information

Contact

Type

Center

Panel

Date Received

Product Code

Subsequent Product Codes

Applicant Name (Manufacturer)

Device Name

Decision

Street 1

Street 2

City

State

Country Code

ZIP

Postal Code

Class Advise Committee

SSP Indicator

Third Party Reviewed

Expedited Review

Predicate Devices

DEN170022

Reference Devices

DynaCAD

AI/ML (Artificial Intelligence / Machine Learning)

Yes
The document explicitly states the device is "artificial intelligence (AI)-based" and lists "Artificial Intelligence (AI) Powered Prostate MRI Segmentation Tool" and "AI Powered Lesion Contour Tool" as key features. It also mentions an "artificial intelligence-powered algorithm" and "Machine learning-based algorithm".

Therapeutic

No.
This device is an AI-based decision support software intended as an adjunct to assist physicians in planning and guiding clinical, interventional, diagnostic, and/or treatment procedures, not directly providing therapy itself.

Diagnostic

Explanation: The "Intended Use / Indications for Use" section states that the software is "designed to support the prostate oncological workflow by helping the user with the segmentation of MR image features... in the evaluation, quantification, and documentation of lesions; and in pre-planning for diagnostic and interventional procedures such as biopsy and/or soft tissue ablation." While it supports diagnostic procedures, its primary role is "decision support software" rather than directly providing a diagnosis. It helps physicians in planning and guiding procedures based on existing MR images and biopsy findings. The lesion characterization functions "may be useful in supporting lesion characterization and subsequent patient management" when interpreted by a trained physician, indicating a supportive role rather than a definitive diagnostic one.

SaMD (Software as a Medical Device)

Yes

The device description explicitly states "The Avenda Health AI Prostate Cancer Planning Software ("AI Prostate Cancer Planning Software" or "Software") is an artificial intelligence (AI)-based decision support software...". The entire description focuses on the software's functions and capabilities, with no mention of accompanying hardware components required for its operation beyond standard computing infrastructure for image processing.

IVD (In Vitro Diagnostic)

Based on the provided information, the Avenda Health AI Prostate Cancer Planning Software is not an In Vitro Diagnostic (IVD).

Here's why:

IVDs analyze samples taken from the human body. The Avenda Health software analyzes images of the prostate (MR images) and information from biopsy findings. It does not directly analyze biological samples like blood, urine, or tissue.
The intended use is for planning and guidance based on imaging and existing pathology. The software is used as an adjunct to review MR images and biopsy findings, and to assist in planning procedures. It is not performing a test on a biological sample to diagnose a condition.
The device description focuses on image processing and AI-based decision support. The features described are related to segmenting images, evaluating lesions within images, and simulating procedures based on image data.

While the software uses information derived from pathology (biopsy findings), it is not performing the pathology test itself. It is using the results of that test in conjunction with imaging data to provide decision support for planning.

Therefore, the Avenda Health AI Prostate Cancer Planning Software falls under the category of a medical device that processes and analyzes medical images and related data, rather than an In Vitro Diagnostic device.

PCCP (Predetermined Change Control Plan) Authorized

No
The provided text does not contain any explicit statement that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device.

Overview

Intended Use / Indications for Use

The Avenda Health AI Prostate Cancer Planning Software's lesion characterization functions are intended for use on patients with a pathology-confirmed Gleason Grade Group (GGG) ≥ 2 lesion and for whom corresponding biopsy coordinate information have been uploaded. These functions are indicated for the extent of known disease. Extent of known disease refers to the boundary of a pathology confirmed lesion of GGG ≥ 2 for a particular patient. Specifically, using prostate MR images, biopsy, pathology, and clinical data, the device creates and displays a cancer map that assigns a probability to each voxel within the prostate, indicating its probability for containing clinically significant prostate cancer (csPCa, defined as GGG ≥ 2 ). A user selects a threshold for the cancer map to create a boundary of the lesion. The lesion boundary is assigned an Encapsulation Confidence Score indicating the confidence that all csPCa is encapsulated within the boundary. The Encapsulation Confidence Score is from a lookup table generated by a database of cases with known ground-truth. When interpreted by a trained physician, this information may be useful in supporting lesion characterization and subsequent patient management.

The Avenda Health AI Prostate Planning Software may also be used as a medical image application, for the viewing. manipulation, 3D-visualization, and comparison of MR prostate images can be viewed in a number of output formats including volume rendering. It enables visualization of information that would otherwise have to be visually compared disjointedly.

Product codes

POK

Device Description

1. Artificial Intelligence (AI) Powered Prostate MRI Segmentation Tool,
1. AI Powered Lesion Contour Tool, and
1. Simulated Interventional Tool Placement.

The user can choose which subset of features of the Software to employ based on the specific oncological workflow. Not all features are required to be used for every workflow. Once the user has completed planning and has reviewed and verified the information, it can be exported into a supported file format such that it can be imported into a compatible interventional system or biopsy system.

Mentions image processing

Yes

Mentions AI, DNN, or ML

Mentions AI, ML.

Input Imaging Modality

Magnetic Resonance (MR) prostate images.

Anatomical Site

Prostate only

Indicated Patient Age Range

Not Found

Intended User / Care Setting

Physicians trained in the oncological workflow (Radiologist/Urologist) in a clinical setting

Description of the training set, sample size, data source, and annotation protocol

Not Found

Description of the test set, sample size, data source, and annotation protocol

Standalone performance testing for the prostate segmentation and lesion contouring algorithms within standalone test datasets, established against clinically valid ground truths. Specifically, the prostate segmentation algorithm has been determined to accurately segment the prostate organ in T2-weighted MRI in a standalone test set of 137 patients. Furthermore, the lesion contouring algorithm has been validated for accuracy in contouring GGG >2 lesions in the intended use population within a representative, independent whole mount pathology dataset of N=50 patients.

Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)

Study Type: Non-clinical Testing (Software verification and validation, Standalone performance testing, Human factors usability testing).
- Sample Size: 137 patients for prostate segmentation, 50 patients for lesion contouring.
- Key results: Software verification and validation demonstrated that the Proposed Device performs in accordance with its specification for every requirement and functionality. Standalone performance testing showed accurate segmentation of the prostate in T2-weighted MRI and validated the accuracy of the lesion contouring algorithm for GGG >2 lesions. Human factors usability testing demonstrated that representative intended users can use the device safely and effectively.
Study Type: Multi-reader, multi-case (MRMC) study.
- Sample Size: Cases within a prostate whole mount pathology database derived from GGG 2-3 patients. Ten practicing urologists or radiologists.
- Key results: Lesion contours produced using the Proposed Device had superior sensitivity (mean 97.4% vs 38.2%, p

Regulation Number and Section

§ 892.2060 Radiological computer-assisted diagnostic software for lesions suspicious of cancer.

(a)
Identification. A radiological computer-assisted diagnostic software for lesions suspicious of cancer is an image processing prescription device intended to aid in the characterization of lesions as suspicious for cancer identified on acquired medical images such as magnetic resonance, mammography, radiography, or computed tomography. The device characterizes lesions based on features or information extracted from the images and provides information about the lesion(s) to the user. Diagnostic and patient management decisions are made by the clinical user.(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 image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, and algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will improve reader performance as intended.
(iii) Results from performance testing protocols that demonstrate that the device improves reader performance in the intended use population when used in accordance with the instructions for use. The performance assessment must be based on appropriate diagnostic accuracy measures (
e.g., receiver operator characteristic plot, sensitivity, specificity, predictive value, and diagnostic likelihood ratio). The test dataset must contain sufficient numbers of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, concomitant diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals of the device for these individual subsets can be characterized for the intended use population and imaging equipment.(iv) Standalone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; and description of verification and validation activities including system level test protocol, pass/fail criteria, results, and cybersecurity).(2) Labeling must include:
(i) A detailed description of the patient population for which the device is indicated for use.
(ii) A detailed description of the intended reading protocol.
(iii) A detailed description of the intended user and recommended user training.
(iv) A detailed description of the device inputs and outputs.
(v) A detailed description of compatible imaging hardware and imaging protocols.
(vi) Warnings, precautions, and limitations, including situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality or for certain subpopulations), as applicable.(vii) Detailed instructions for use.
(viii) A detailed summary of the performance testing, including: Test methods, dataset characteristics, results, and a summary of sub-analyses on case distributions stratified by relevant confounders (
e.g., lesion and organ characteristics, disease stages, and imaging equipment).

Summary

Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo in blue, with the words "U.S. FOOD & DRUG" stacked on top of the word "ADMINISTRATION".

November 22, 2022

Avenda Health, Inc. % Brittany Berry-Pusey, Ph.D. Co-Founder and COO 4130 Overland Avenue CULVER CITY CA 90230

Re: K221624

Trade/Device Name: Avenda Health AI Prostate Cancer Planning Software Regulation Number: 21 CFR 892.2060 Regulation Name: Radiological computer-assisted diagnostic software for lesions suspicious of cancer Regulatory Class: Class II Product Code: POK Dated: October 23, 2022 Received: October 24, 2022

Dear Brittany Berry-Pusey:

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

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

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's

requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); 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,

FDA

Daniel M. Krainak, Ph.D. Assistant Director Magnetic Resonance and Nuclear Medicine Team DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

Indications for Use

510(k) Number (if known) K221624

Device Name

Avenda Health AI Prostate Cancer Planning Software

Indications for Use (Describe)

The Avenda Health Al Prostate Cancer Planning Software's lesion characterization functions are intended for use on patients with a pathology-confirmed Gleason Grade Group (GGG) ≥ 2 lesion and for whom corresponding biopsy coordinate information have been uploaded. These functions are indicated for the extent of known disease. Extent of known disease refers to the boundary of a pathology confirmed lesion of GGG ≥ 2 for a particular patient. Specifically, using prostate MR images, biopsy, pathology, and clinical data, the device creates and displays a cancer map that assigns a probability to each voxel within the prostate, indicating its probability for containing clinically significant prostate cancer (csPCa, defined as GGG ≥ 2 ). A user selects a threshold for the cancer map to create a boundary of the lesion. The lesion boundary is assigned an Encapsulation Confidence Score indicating the confidence that all csPCa is encapsulated within the boundary. The Encapsulation Confidence Score is from a lookup table generated by a database of cases with known ground-truth. When interpreted by a trained physician, this information may be useful in supporting lesion characterization and subsequent patient management.

The Avenda Health Al Prostate Planning Software may also be used as a medical image application, for the viewing. manipulation, 3D-visualization, and comparison of MR prostate images can be viewed in a number of output formats including volume rendering. It enables visualization of information that would otherwise have to be visually compared disjointedly.

X 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.

The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:

Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov

"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."

510(k) Notification K221624

GENERAL INFORMATION [807.92(a)(1)]

Applicant:

Avenda Health, Inc. 4130 Overland Avenue Culver City, CA 90230 USA

Contact Person:

Brittany Berry-Pusey, Ph.D. Co-Founder and COO, Avenda Health, Inc. Phone: 310-957-5202 Email: brit@avendahealth.com

Prepared By:

Veranex, Inc. Regulatory, Clinical, and Quality Services 224 Airport Parkway, Suite 250 San Jose, CA 95110 USA

Date Prepared: November 18, 2022

DEVICE INFORMATION [807.92(a)(2)]

Trade Name:

Avenda Health AI Prostate Cancer Planning Software

Generic/Common Name:

Medical Image Software Application and Decision Support Software

Classification:

21 CFR$892.2060, Radiological computer-assisted diagnostic software for lesions suspicious of cancer

Product Code:

POK, Computer-Assisted Diagnostic Software For Lesions Suspicious For Cancer

PREDICATE DEVICE [807.92(a)(3)]

Quantitative Insights, Inc. QuantX (DEN170022)

DEVICE DESCRIPTION [807.92(a)(4)]

1. Artificial Intelligence (AI) Powered Prostate MRI Segmentation Tool,
1. AI Powered Lesion Contour Tool, and
1. Simulated Interventional Tool Placement.

INDICATIONS FOR USE [807.92(a)(5)]

5.0 510(k) SUMMARY

lesion boundary is assigned an Encapsulation Confidence Score indicating the confidence that all csPCa is encapsulated within the boundary. The Encapsulation Confidence Score is from a lookup table generated by a database of cases with known ground-truth. When interpreted by a trained physician, this information may be useful in supporting lesion characterization and subsequent patient management.

The Avenda Health AI Prostate Planning Software may also be used as a medical image application, for the viewing, manipulation, 3D-visualization, and comparison of MR prostate images. The images can be viewed in a number of output formats including volume rendering. It enables visualization of information that would otherwise have to be visually compared disjointedly.

COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICES [807.92(a)(6)]

Avenda Health, Inc. believes that the Avenda Health AI Prostate Cancer Planning Software (the "Proposed Device") is substantially equivalent to the predicate device, Quantitative Insights, Inc. QuantX (DEN170022, "QuantX"). Like QuantX, the Proposed Device is used by physicians to support tasks within the oncological workflow. The range of functionalities supported by the Proposed Device, which include segmentation, lesion characterization, and image overlays (i.e., simulated tool placement to support subsequent treatment planning), in addition to basic magnetic resonance image (MRI) and medical information review functionalities, is similar to those available in the identified predicate device. QuantX is selected as the predicate device because, like the Proposed Device, its primary imaging functionality is to characterize lesions suspicious for cancer through an artificial intelligence-powered algorithm and provide information to support the physician user's interpretation of the patient's medical and imaging information. DynaCAD is selected as a reference device to support the performance testing methodology for the prostate segmentation function. The Proposed Device is substantially equivalent to the identified predicate device.

SUBSTANTIAL EQUIVALENCE

The Proposed Device and the predicate device have the same intended use and similar Indications for Use. Both devices also have similar technological characteristics, and any differences in technological characteristics do not raise different questions of safety and effectiveness. The results of performance bench, usability, and reader performance testing demonstrated that the Proposed Device meets the established specifications necessary for consistent performance to achieve its intended use as safely and as effectively as the predicate device. Further, the results of the performance bench, usability, and reader performance testing confirmed that the technological differences do not raise different questions of safety and effectiveness. As such, the Avenda Health AI Prostate Cancer Planning Software is substantially equivalent to the predicate device, QuantX (DEN170022).

PERFORMANCE DATA [807.92(b)]

All necessary testing was conducted on the Avenda Health AI Prostate Cancer Planning Software to support a determination of substantial equivalence to the predicate devices.

Non-clinical Testing Summary:

Avenda has performed software verification, validation, and usability testing to demonstrate that: 1) the device performs to its intended use in accordance with design specifications, and 2) the technological differences presented in the Proposed Device do not raise different questions of safety and effectiveness. These tests include:

Software verification and validation demonstrated that the Proposed Device performs in ● accordance with its specification for every requirement and functionality.
Standalone performance testing for the prostate segmentation and lesion contouring algorithms within standalone test datasets, established against clinically valid ground truths. Specifically, the prostate segmentation algorithm has been determined to accurately segment the prostate organ in T2-weighted MRI in a standalone test set of 137 patients. Furthermore, the lesion contouring algorithm has been validated for accuracy in contouring GGG >2 lesions in the intended use population within a representative, independent whole mount pathology dataset of N=50 patients.
Human factors usability testing for the Proposed Device has demonstrated that . representative intended users can use the device safely and effectively, without significant use-related risks.

Reader Study Summary:

A multi-reader, multi-case (MRMC) study was conducted for the Avenda Health AI Prostate Cancer Planning Software ("Proposed Device") to demonstrate that the device improves reader performance for prostate cancer lesion contouring in the intended use population.

Overall, the study dataset consisted of cases within a prostate whole mount pathology database derived from GGG 2-3 patients, which is representative of the device patient population. Each whole mount sample included 3D surfaces and pathology labels representing tumors as annotated on the whole mount prostatectomy slides, which are registered to preoperative T2-weighted MRI. Ten practicing urologists or radiologists from different institutions with a range of experience levels (2 to 23 years of clinical practice experience) participated in this reader study. Each reader reviewed each case. For each case, the reader created a prostate cancer lesion contour based both on standard of care (SOC) practices and with the assistance of the Proposed Device. The lesion contours created with each method were evaluated against whole mount pathology data as ground truth and subsequently compared to one another as well as hemi-gland contours, in order to assess the ability of the Proposed Device to improve reader ability in lesion contouring.

The study results demonstrated that lesion contours produced using the Proposed Device had superior sensitivity (mean 97.4% vs 38.2%, p