(164 days)
NS-HGlio, K221738
Not Found
Yes.
The device explicitly states it uses a "machine learning-based algorithm" and a "machine learning methodology" to perform its functions, and also mentions "Artificial Intelligence Machine Learning (AI/ML) Algorithm" as the Model Type.
No
The device is a software tool used to assist physicians with visualization, segmentation, and quantification of lesions in FDG-PET/CT scans for diagnostic and monitoring purposes, not for treating any condition.
Yes
The device is a diagnostic device because it assists trained interpreting physicians with the visualization of suspected lesions and calculation of total volume of all lesions in a body, providing information that can be used in addition to standard of care image interpretation of FDG-PET/CT scans for patients with FDG-avid lymphomas.
Yes
The device explicitly states it is a "software device" and performs its functions through a "machine learning-based algorithm" for image analysis and quantification. There is no mention of any hardware components integral to its function or any hardware verification/validation.
No.
The device processes imaging data to assist physicians in visualizing and quantifying lesions, which does not involve analyzing in vitro biological samples.
No
The letter does not state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The section "Control Plan Authorized (PCCP) and relevant text" explicitly states "Not Found".
Intended Use / Indications for Use
Opulus™ Lymphoma Precision is a software device that uses a machine learning-based algorithm to automate segmentation and visualization of lesions along with automation of measurement of total metabolic tumor volume within whole-body FDG-PET/CT scans of patients with FDG-avid lymphomas.
Opulus™ Lymphoma Precision is used to assist trained interpreting physicians with visualization of suspected lesions and calculation of total volume of all lesions in a body. This information can be used in addition to the standard of care image interpretation of FDG-PET/CT scans. Opulus™ Lymphoma Precision annotated images can be reviewed by an appropriately trained physician.
The algorithm is assistive, and requires a radiologist review, who will make the final decision on FDG-PET/CT image interpretation.
Product codes
QIH
Device Description
Opulus™ Lymphoma Precision is an assistive tool which can be used by physicians to automate the labor intensive task of quantifying disease burden in whole-body FDG-PET/CT scans of patients already diagnosed with FDG-avid lymphomas. It does so by using a machine learning methodology to localize and segment FDG-PET activity ('hot-spots' on FDG-PET scans) of lymphoma lesions within a PET/CT image. Opulus™ Lymphoma Precision does not screen for or diagnose lymphoma. It is intended for patients already diagnosed with FDG-avid lymphoma.
The following is a list of key functionalities algorithm performs to accomplish the proposed intended use.
- localization and segmentation,
- visualization of lymphoma-related tumor lesions
- quantification of Total Metabolic Tumor Volume (TMTV)
Opulus™ Lymphoma Precision aids the efficiency of medical professionals by automatically generating tumor boundary Regions of Interest (ROIs) and quantifying TMTV, which is a tedious task when performed manually. The physician has the option to accept/reject the output generated by the device. The user does not have the ability to modify the device output.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
FDG-PET/CT scans, Standard DICOM format - PET with the associated attenuation correction CT
Anatomical Site
Whole-body
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Trained interpreting physicians, radiologists
Description of the training set, sample size, data source, and annotation protocol
The performance validation dataset was fully independent from the training and characterization datasets: FDG-PET/CT scans came from an independent set of patients and the manual reads were performed by an independent pool of radiologists. Further, the performance validation dataset was not available to the algorithm developers during the algorithm training.
Description of the test set, sample size, data source, and annotation protocol
The performance validation study of the Opulus™ Lymphoma Precision algorithm included 182 unique patients' FDG-PET/CT scans with various gender, ethnicity and age that were representative of the Intended Use and population for the algorithm. The respective FDG-PET/CT scans were obtained from multiple geographical locations across the U.S., Canada, Europe, Australia, and Taiwan, using scanners from different manufacturers and models including GE, Siemens, Philips.
Reference standard (ground truth) was established using three radiologists/nuclear medicine physicians with expertise in interpreting PET/CT scans from patients with FDG-avid lymphoma. The ground truth for each scan was based on the independent input from three radiologists randomly selected from a pool of nine radiologists.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
The performance validation study was conducted using 182 unique patients' FDG-PET/CT scans. The objectives were to demonstrate agreement of TMTV quantitative estimates between aTMTV and manual (mTMTV) and accuracy in lesion segmentation by comparing aTMTV-generated contours and ground truth. The dataset was evaluated using metrics of absolute agreement between the Opulus™ Lymphoma Precision algorithm output and the ground truth TMTV under cubic root, as well as with the Dice Similarity Coefficient (DSC).
Key results: The mean difference between Opulus™ Lymphoma Precision algorithm and the ground truth was -0.20 cm (95% CI, cm: -0.50, 0.10) for TMTV values
§ 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).
FDA 510(k) Clearance Letter - Opulus™ Lymphoma Precision
Page 1
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
Doc ID # 04017.07.05
May 30, 2025
Roche Molecular Systems, Inc.
Aarti Shukla
Regulatory Affairs Manager
2881 Scott Blvd
Santa Clara, California 95050
Re: K243863
Trade/Device Name: Opulus™ Lymphoma Precision
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical image management and processing system
Regulatory Class: Class II
Product Code: QIH
Dated: April 28, 2025
Received: April 29, 2025
Dear Aarti Shukla:
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.
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K243863 - Aarti Shukla
Page 2
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 (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-reporting-combination-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 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.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
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-devices/medical-device-safety/medical-device-reporting-mdr-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/medical-devices/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-devices/device-advice-comprehensive-regulatory-
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K243863 - Aarti Shukla
Page 3
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,
Daniel M. Krainak, Ph.D.
Assistant Director
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
Page 4
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below.
Submission Number (if known): K243863
Device Name: Opulus™ Lymphoma Precision
Indications for Use (Describe)
Opulus™ Lymphoma Precision is a software device that uses a machine learning-based algorithm to automate segmentation and visualization of lesions along with automation of measurement of total metabolic tumor volume within whole-body FDG-PET/CT scans of patients with FDG-avid lymphomas.
Opulus™ Lymphoma Precision is used to assist trained interpreting physicians with visualization of suspected lesions and calculation of total volume of all lesions in a body. This information can be used in addition to the standard of care image interpretation of FDG-PET/CT scans. Opulus™ Lymphoma Precision annotated images can be reviewed by an appropriately trained physician.
The algorithm is assistive, and requires a radiologist review, who will make the final decision on FDG-PET/CT image interpretation.
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.
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DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
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Page 5
Opulus™ Lymphoma Precision 510(k) Summary
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of 21 CFR 807.92.
| Submitter Name | Roche Molecular Systems, Inc. |
|---|---|
| Address | 2881 Scott Blvd |
| Santa Clara, CA 95050 USA | |
| Contact | Aarti Shukla |
| Regulatory Affairs Manager, RIS | |
| Phone: (408) 705-7215 | |
| Fax: (925) 225-0207 | |
| aarti.shukla@roche.com | |
| Date Prepared | December 16, 2024 |
| Proprietary Name | Automated Total Metabolic Tumor Volume (aTMTV) |
| Common Name | Opulus™ Lymphoma Precision |
| Classification Name | Automated Radiological Image Processing Software |
| Regulation Number | 21 CFR 892.2050 |
| Regulatory Class | II |
| Product Codes | QIH, Automated Radiological Image Processing Software |
| Predicate Device | NS-HGlio, K221738 |
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1. DEVICE DESCRIPTION
Opulus™ Lymphoma Precision is an assistive tool which can be used by physicians to automate the labor intensive task of quantifying disease burden in whole-body FDG-PET/CT scans of patients already diagnosed with FDG-avid lymphomas. It does so by using a machine learning methodology to localize and segment FDG-PET activity ('hot-spots' on FDG-PET scans) of lymphoma lesions within a PET/CT image. Opulus™ Lymphoma Precision does not screen for or diagnose lymphoma. It is intended for patients already diagnosed with FDG-avid lymphoma.
The following is a list of key functionalities algorithm performs to accomplish the proposed intended use.
- localization and segmentation,
- visualization of lymphoma-related tumor lesions
- quantification of Total Metabolic Tumor Volume (TMTV)
Opulus™ Lymphoma Precision aids the efficiency of medical professionals by automatically generating tumor boundary Regions of Interest (ROIs) and quantifying TMTV, which is a tedious task when performed manually. The physician has the option to accept/reject the output generated by the device. The user does not have the ability to modify the device output.
2. INDICATIONS FOR USE
Opulus™ Lymphoma Precision is a software device that uses a machine learning-based algorithm to automate segmentation and visualization of lesions along with automation of measurement of total metabolic tumor volume within whole-body FDG-PET/CT scans of patients with FDG-avid lymphomas.
Opulus™ Lymphoma Precision is used to assist trained interpreting physicians with visualization of suspected lesions and calculation of total volume of all lesions in a body. This information can be used in addition to the standard of care image interpretation of FDG-PET/CT scans. Opulus™ Lymphoma Precision annotated images can be reviewed by an appropriately trained physician.
The algorithm is assistive, and requires a radiologist review, who will make the final decision on FDG-PET/ CT image interpretation.
Page 7
3. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH PREDICATE DEVICE
| Feature/function | Opulus™ Lymphoma Precision (subject device) | NS-HGlio (predicate device) |
|---|---|---|
| Model Type | Artificial Intelligence Machine Learning (AI/ML) Algorithm | Artificial Intelligence Machine Learning (AI/ML) Algorithm |
| Patient population | Patients already pathologically diagnosed with FDG-avid lymphomas | Patients already pathologically diagnosed to have brain tumors |
| Input | Standard DICOM format - PET with the associated attenuation correction CT | Standard DICOM format - four different MRI sequences |
| Output | Report and image overlay | Report and image overlay |
| Segmentation | Segments disease related tracer uptake in FDG-avid lymphomas | Segments disease related contrast uptake and FLAIR image intensity changes in high-grade gliomas (HGG) |
| Visualization | Overlay of segmentation mask on input PET/CT images | Overlay of segmentation mask on input MRI images |
| Quantification | Volumetric measurements derived from segmented lymphoma disease burden | Volumetric measurements derived from segmented HGG disease burden |
| Ground truth Establishment | Reference standard (ground truth) was established using three US board certified radiologists/nuclear medicine physicians with expertise in identifying and segmenting FDG-avid lymphoma related uptake | Reference standard (ground truth) was established using three board certified neuroradiologists with expertise in identifying and segmenting high grade gliomas |
4. PERFORMANCE EVALUATION
Safety and performance of Opulus™ Lymphoma Precision have been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing. The software verification and 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, "Content of Premarket Submissions for Device Software Functions" June 14, 2023.
The performance validation study of the Opulus™ Lymphoma Precision algorithm included 182 unique patients' FDG-PET/CT scans with various gender, ethnicity and age that were representative of the Intended Use and population for the algorithm. The respective FDG-PET/CT scans were obtained from multiple geographical locations across the U.S., Canada, Europe, Australia, and Taiwan, using scanners from different manufacturers and models including GE, Siemens, Philips.
Page 8
The Performance validation study data was a fully independent dataset from the training and characterization datasets: FDG-PET/CT scans came from an independent set of patients and the manual reads were performed by an independent pool of radiologists. Further, the performance validation dataset was not available to the algorithm developers during the algorithm training.
| Patient Characteristic | Percentage (%) |
|---|---|
| Gender | |
| Female | 34.6% |
| Male | 65.4% |
| Ethnicity | |
| Hispanic Or Latino | 1.6% |
| Not Hispanic Or Latino | 96.2% |
| Not Reported | 1.6% |
| Unknown | 0.5% |
| Age groups | |
| =70 y | 32.4% |
Reference standard (ground truth) was established using three radiologists/nuclear medicine physicians with expertise in interpreting PET/CT scans from patients with FDG-avid lymphoma. The ground truth for each scan was based on the independent input from three radiologists randomly selected from a pool of nine radiologists.
The objectives of the performance validation study were to demonstrate agreement of TMTV quantitative estimates between aTMTV and manual (mTMTV), confirming that there is an acceptable difference between aTMTV and mTMTV and accuracy in lesion segmentation by comparing aTMTV-generated contours and ground truth. The dataset was evaluated using metrics of absolute agreement between the Opulus™ Lymphoma Precision algorithm output and the ground truth TMTV under cubic root, as well as with the Dice Similarity Coefficient (DSC).
Page 9
The mean difference between Opulus™ Lymphoma Precision algorithm and the ground truth was -0.20 cm (95% CI, cm: -0.50, 0.10) for TMTV values