Precision DL is a deep learning-based image processing method intended to enhance image quality of non-ToF PET images for clinical oncology purpose, using F-18 FDG. Precision DL may be used for patients of all ages.

Device Description

Precision DL is a deep learning-based image processing method intended for PET oncology 18F-FDG images obtained using the predicate device Omni Legend PET/CT system. Precision DL enhances the non-ToF Q.Clear images to have image quality performance similar to PET images obtained using ToF capable PET systems, including enhancement in image Contrast Recovery (CR), Contrast to Noise Ratio (CNR), and quantitation accuracy. Precision DL's training used clinical data from diverse clinical sites, accounting for relevant variations in patients and sites' protocols.

Precision DL brings three deep learning models to provide users the choice between different strengths of contrast enhancement and noise reduction. The three models, Low, Medium, and High Precision DL, are trained such that the High Precision DL brings the highest contrast enhancement and lowest noise reduction, while the Low Precision DL brings the lowest contrast enhancement and highest noise reduction. Medium Precision DL brings contrast-noise tradeoff in between High and Low Precision DL.

Precision DL is deployed within the acquisition and processing software of Omni Legend, for processing images produced using non-ToF Q.Clear image reconstruction.

AI/ML Overview

Here's an analysis of the acceptance criteria and study for Precision DL, based on the provided FDA 510(k) summary:

Device: Precision DL (Deep Learning-based image processing for non-ToF PET images)

Intended Use: Enhance image quality of non-ToF PET images for clinical oncology using F-18 FDG.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary describes performance improvements over non-ToF Q.Clear reconstruction. It does not explicitly state discrete acceptance criteria values but rather demonstrates general improvements in imaging metrics and equivalence to ToF images.

Metric / Acceptance Criteria	Reported Device Performance (Precision DL vs. non-ToF Q.Clear)
Quantitation Accuracy	Improved accuracy. Performance similar to ToF images.
Contrast Recovery (CR)	Enhanced. Performance similar to ToF images.
Contrast-to-Noise Ratio (CNR)	Enhanced. Performance similar to ToF images.
Lesion Detectability	Explicitly tested, and implied improvement given CR and CNR enhancements.
Dose / Time Reduction	Explicitly tested. (Specific results not detailed, but likely aims to show maintenance of quality with reduced dose/time, or enhanced quality at standard dose/time).
Overall Image Quality (Clinical Assessment)	Acceptable diagnostic results by board-certified radiologists, demonstrating acceptable image quality.
Preference (Clinical Assessment)	Readers preferred Precision DL images over unassisted images, and found them similar to Discovery MI ToF images.
Safety and Effectiveness (Regulatory Acceptance)	No new questions of safety or effectiveness, hazards, unexpected results, or adverse effects were identified compared to the predicate device. Substantially Equivalent.

2. Sample Size Used for the Test Set and Data Provenance

Sample Size (Clinical Data for Bench Testing): 80 PET-CT exams.
- 40 exams from an Omni Legend system.
- 40 exams from Discovery MI systems (with hardware-based ToF).
Sample Size (Clinical Reader Study): Not explicitly stated precisely for the number of cases and images. It mentions "clinical cases of the same patients obtained on Discovery MI and Omni Legend with Precision DL."
Data Provenance: Multiple clinical sites in North America, Europe, and Israel. The data was "segregated, completely independent, and not used in any stage of the algorithm development, including training." This indicates prospective or retrospectively collected data used for testing only.

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

Number of Experts (for Ground Truth related to phantom data): Not applicable for phantom data, as ground truth is known from inserted lesions.
Number of Experts (for Clinical Reader Study): "Board certified radiologists." The exact number is not explicitly stated in the summary, nor are their specific years of experience. However, the study involved reviews and preference questions by these experts.

4. Adjudication Method

The summary mentions a "clinical reader study" where "board certified radiologists... answered blinded preference questions comparing clinical cases." This suggests individual reader assessments were aggregated, but it does not explicitly state an adjudication method like 2+1 or 3+1 for resolving discrepancies in diagnostic findings. The focus appears to be on overall image quality and preference rather than a specific diagnostic consensus for each case.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Yes, a clinical reader study was performed, which included "board certified radiologists" reviewing "clinical cases." They answered "blinded preference questions comparing clinical cases of the same patients obtained on Discovery MI and Omni Legend with Precision DL."
Effect Size of Human Readers with AI vs. Without AI Assistance: The summary states, "The results of the reader study and preference questions support the determination of substantial equivalence. All readers attested that their assessments of Precision DL demonstrated acceptable diagnostic results." While it indicates positive results and physician acceptance, it does not quantify an effect size of how much human readers improved their performance (e.g., in diagnostic accuracy, confidence, or reduced read time) with AI assistance compared to reading without AI assistance (i.e., using only non-ToF Q.Clear images). The study primarily focused on image quality acceptability and preference.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, a standalone performance assessment was conducted as part of the "additional engineering bench testing." This included quantitative assessments using both clinical and phantom data for metrics such as Quantitation Accuracy, Contrast Recovery, Contrast-to-Noise Ratio, Lesion Detectability, and Dose/Time Reduction. This part of the testing directly evaluated the algorithm's output (processed images) against established ground truths/references.

7. Type of Ground Truth Used

For Bench Testing (Quantitative Metrics):
- Phantom Data: Known quantitation from inserted lesions of known size, location, and contrast.
- Clinical Data: Discovery MI's ToF PET images served as a reference for comparison, implying they are considered the gold standard for high-quality images that Precision DL aims to emulate.
For Clinical Reader Study: The "ground truth" here is implied to be the expert consensus on acceptable diagnostic quality and preference rather than a definitive diagnosis based on pathology or long-term outcomes for each case. The goal was to confirm that the enhanced images retained or improved diagnostic acceptability.

8. Sample Size for the Training Set

The summary states, "Precision DL's training used clinical data from diverse clinical sites, accounting for relevant variations in patients and sites' protocols."
However, the specific sample size for the training set is not provided in the given text.

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

The summary indicates that Precision DL "is trained to enhance non-ToF images to have IQ performance similar to ToF images." This implies that the ground truth for training would likely be high-quality ToF PET images (potentially from a system like Discovery MI) that the algorithm was designed to mimic or achieve certain quality metrics aligned with ToF performance.
The text doesn't detail the process of establishing ground truth for individual images within the training set, but it's reasonable to infer a reference standard from ToF images was used.

Summary

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April 27, 2023

GE Healthcare % George Mashour Senior Regulatory Affairs Manager GE Medical Systems Israel 4 Hayozma Street Tirat Hacarmel, 30200 ISRAEL

Re: K223212

Trade/Device Name: Precision DL Regulation Number: 21 CFR 892.1200 Regulation Name: Emission computed tomography system Regulatory Class: Class II Product Code: KPS Dated: March 27, 2023 Received: March 29, 2023

Dear George Mashour:

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

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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 (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,

D. Ray Kennedy

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 Ouality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known)

K223212

Device Name

Precision DL

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.

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510(k) SUMMARY OF SAFETY AND EFFECTIVNESS

This 510(k) summary of Safety and Effectiveness information is submitted in accordance with the requirement of 21 CFR Part 807.87(h):

Date:	March 29, 2023
Submitter:	GE Medical Systems Israel, Functional Imaging (GE Healthcare)4 Hayozma StreetTirat Hacarmel, 30200, Israel
Primary Contact:	George MashourSR. Regulatory Affairs ManagerGE Medical Systems Israel, Functional ImagingTel: +972-54-7464808Email: george.mashour@ge.com
Secondary Contact:	John JaeckleChief Regulatory Affairs Engineer and StrategistGE HealthcareTel: 262-424-9547email: john.jaeckle@ge.com
Device Trade Name:	Precision DL
Device Classification:	Class II
Regulation Number:	21CFR 892.1200
Product Codes:	KPS

Predicate Device Information
Device Name:	Omni Legend
Manufacturer:	GE Medical Systems Israel, Functional Imaging
510(k) Number:	K221932
Regulation Number/Product Code:	21CFR 892.1200 & 21CFR 892.1750KPS & JAK

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Reference Device Information
Device Name:	Discovery MI
Manufacturer:	GE Medical Systems, LLC.
510(k) Number:	K161574
Regulation Number/Product Code:	21CFR 892.1200 & 21CFR 892.1750KPS & JAK

Device Description

Precision DL is deployed within the acquisition and processing software of Omni Legend, for processing images produced using non-ToF Q.Clear image reconstruction.

Intended Use

Precision DL is a deep learning-based image processing method intended for Positron Emission Tomography images.

Indications for Use

Precision DL is a deep learning-based image processing method to enhance image quality of non-ToF PET images for clinical oncology purpose, using F-18 FDG. Precision DL may be used for patients of all ages.

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Technological Characteristics

Precision DL is an image processing option for the predicate Omni Legend device that produces substantially equivalent images to those produced using non-ToF Q.Clear reconstruction. Since the Precision DL option is deployed within Omni Legend's acquisition and processing software, it utilizes the same hardware and software platform as the non-ToF Q.Clear reconstruction. The table below summarizes the substantive feature / technological differences between the predicate device and the proposed device:

Specification	Predicate Device	Proposed Device
	Omni Legend (K221932)including non-ToF Q.Clear ImageReconstruction	Precision DLon Omni Legend
Technology	Iterative non-ToF imagereconstruction algorithm	Deep learning-based imageprocessing trained to enhance non-ToF images to have IQ performancesimilar to ToF images.

Precision DL's technological characteristics do not raise new questions of safety or effectiveness, and did not introduce any new risks/hazards, warnings, or limitations.

Determination of Substantial Equivalence:

Summary of Non-Clinical Testing

Precision DL has successfully completed the design control testing per GE's quality system. No additional hazards were identified, and no unexpected test results were observed. Precision DL was designed under the Quality System Regulations of 21CFR 820 and ISO 13485. GE believes that the extensive bench testing and the physician evaluations performed are sufficient for FDA's substantial equivalence determination.

The following quality assurance measures have been applied to the development of the system:

· Requirement Definition
Risk Analysis
Technical Design Reviews
Formal Design Reviews
Software Development Lifecycle
Testing on unit level (Module verification)
· Integration testing (System verification)
· System Testing:
- Safety Testing (Verification)
- System and Image Performance Testing (Verification)
- o Simulating Use Testing (Validation)

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Additional engineering bench testing also included testing that demonstrates performance and substantiates the product claims. The testing confirmed performance improvements over existing non-ToF Q.Clear reconstruction and compared performance to ToF reconstruction using the same data from the reference Discovery MI that has hardware-based ToF. The test datasets included both clinical and NEMA Image Quality phantom data, which was segregated, completely independent, and not used in any stage of the algorithm development, including training. The clinical data consisted of 80 PET-CT exams from multiple clinical sites in North America, Europe, and Israel. 40 exams were obtained on an Omni Legend system while the other 40 were obtained on Discovery MI systems incorporating a range of Axial Field of Views. The clinical exams spanned typical patient demographics for F-18 FDG oncological imaging with typical site-specific oncology imaging protocols, without specific inclusion criteria. The ground truth was Discovery MI's ToF PET images and known quantitation from inserted lesions of known size, location, and contrast. The additional non-clinical testing included testing for:

Quantitation Accuracy
Contrast Recovery
Contrast-to-Noise Ratio
트 Lesion Detectability
Dose / Time Reduction

All the testing and results did not raise new or different questions of safety and effectiveness than associated with predicate device. We consider the proposed device is substantially equivalent to the predicate device.

The substantial equivalence is also based on the software documentation for a "Moderate" level of concern. GE believes that Precision DL is of comparable type and substantially equivalent to the predicate device.

Clinical Testing

A clinical reader study using Omni Legend images processed with Precision DL was conducted at two clinical sites. The study included review by board certified radiologists to assess overall image quality of Precision DL images. The board-certified radiologists also answered blinded preference questions comparing clinical cases of the same patients obtained on Discovery MI and Omni Legend with Precision DL. The results of the reader study and preference questions support the determination of substantial equivalence. All readers attested that their assessments of Precision DL demonstrated acceptable diagnostic results.

Substantial Equivalence Conclusion

The changes associated with Precision DL do not create a new Intended Use and represent technological characteristics that produce images of equivalent diagnostic quality.

GE's quality system's design verification, and risk management processes did not identify any new questions of safety or effectiveness, hazards, unexpected results, or adverse effects stemming from the changes to the predicate.

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Based on development under GE Healthcare's quality system, the successful system and software verification and validation testing, the additional engineering bench testing, and the clinical testing demonstrates that Precision DL is substantially equivalent to, and hence as safe and as effective for its Intended Use, as the legally marketed predicate device.

Regulation Number and Section

§ 892.1200 Emission computed tomography system.

(a)
Identification. An emission computed tomography system is a device intended to detect the location and distribution of gamma ray- and positron-emitting radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. This generic type of device may include signal analysis and display equipment, patient and equipment supports, radionuclide anatomical markers, component parts, and accessories.(b)
Classification. Class II.