Sonic DL is a Deep Learning based image reconstruction technique that is available for use on GE Healthcare 1.5T and 3.0T MR systems. Sonic DL reconstructs MR images from highly under-sampled data, and thereby enables highly accelerated acquisitions. Sonic DL is intended for cardiac imaging, and for patients of all ages.

Device Description

Sonic DL is a new software feature intended for use with GE Healthcare MR systems. It consists of a deep learning based reconstruction algorithm that is applied to data from MR cardiac cine exams obtained using a highly accelerated acquisition technique.

Sonic DL is an optional feature that is integrated into the MR system software and activated through a purchasable software option key.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study details for the Sonic DL device, based on the provided document:

Sonic DL Acceptance Criteria and Study Details

1. Table of Acceptance Criteria and Reported Device Performance

The document describes the performance of Sonic DL in comparison to conventional ASSET Cine images. While explicit numerical acceptance criteria for regulatory clearance are not stated, the studies aim to demonstrate non-inferiority or superiority in certain aspects. The implicit acceptance criteria are:

Diagnostic Quality: Sonic DL images must be rated as being of diagnostic quality.
Functional Measurement Agreement: Functional cardiac measurements (e.g., LV volumes, EF, CO) from Sonic DL images must agree closely with those from conventional ASSET Cine images, ideally within typical inter-reader variability.
Reduced Scan Time: Sonic DL must provide significantly shorter scan times.
Preserved Image Quality: Image quality must be preserved despite higher acceleration.
Single Heartbeat Imaging (Functional): Enable functional imaging in a single heartbeat.
Rapid Free-Breathing Functional Imaging: Enable rapid functional imaging without breath-holds.

Implicit Acceptance Criterion	Reported Device Performance
Diagnostic Quality	"on average the Sonic DL images were rated as being of diagnostic quality" (second reader study).
Functional Measurement Agreement	"the inter-method variability (coefficient of variability comparing functional measurements taken with Sonic DL images versus measurements using the conventional ASSET Cine images) was smaller than the inter-observer intra-method variability for the conventional ASSET Cine images for all parameters, indicating that Sonic DL is suitable for performing functional cardiac measurements" (first reader study). "Functional measurements using Sonic DL 1 R-R free breathing images from 10 subjects were compared to functional measurements using the conventional ASSET Cine breath hold images, and showed close agreement" (additional clinical testing for 1 R-R free breathing).
Reduced Scan Time	"providing a significant reduction in scan time compared to the conventional ASSET Cine images" (second reader study). "the Sonic DL feature provided significantly shorter scan times than the conventional Cine imaging" (overall conclusion).
Preserved Image Quality	"capable of reconstructing Cine images from highly under sampled data that are similar to the fully sampled Cine images in terms of image quality and temporal sharpness" (nonclinical testing). "the image quality of 13 Sonic DL 1 R-R free breathing cases was evaluated by a U.S. board certified radiologist, and scored higher than the corresponding conventional free breathing Cine images from the same subjects" (additional clinical testing for 1 R-R free breathing).
Single Heartbeat Functional Imaging	"Sonic DL is capable of achieving a 12 times acceleration factor and obtaining free-breathing images in a single heartbeat (1 R-R)" (additional clinical testing).
Rapid Free-Breathing Functional Imaging	"Sonic DL is capable of... obtaining free-breathing images in a single heartbeat (1 R-R)" (additional clinical testing).

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

The document describes two primary reader evaluation studies and additional clinical testing.

First Reader Study (Functional Measurements):
- Sample Size: 107 image series from 57 unique subjects (46 patients, 11 healthy volunteers).
- Data Provenance: Data from 7 sites: 2 GE Healthcare facilities and 5 external clinical collaborators. This indicates data from multiple sources, likely a mix of prospective and retrospective collection. The geographic origin of these sites is not explicitly stated but implies a multi-center study potentially from different countries where GE Healthcare operates or collaborates.
Second Reader Study (Image Quality Assessment):
- Sample Size: 127 image sets, which included a subset of the subjects from the first study.
- Data Provenance: Same as the first reader study (clinical sites and healthy volunteers at GE Healthcare facilities).
Additional Clinical Testing (1 R-R Free Breathing):
- Functional Measurements: 10 subjects.
- Image Quality Evaluation: 13 subjects.
- Data Provenance: In vivo cardiac cine images from 19 healthy volunteers. This implies prospective collection or a subset of prospectively collected healthy volunteer data.

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

First Reader Study (Functional Measurements): Three radiologists. Qualifications are not explicitly stated, but their role in making quantitative measurements implies expertise in cardiac MRI.
Second Reader Study (Image Quality Assessment): Three radiologists. Qualifications are not explicitly stated, but their role in blinded image quality assessments implies expertise in cardiac MRI interpretation.
Additional Clinical Testing (1 R-R Free Breathing Image Quality): One U.S. board certified radiologist.

4. Adjudication Method for the Test Set

The document does not explicitly state an adjudication method (like 2+1, 3+1, or none) for either the functional measurements or the image quality assessments. For the first study, it mentions "inter-method variability" and "inter-observer intra-method variability," suggesting that the readings from the three radiologists were compared against each other and against the conventional method, but not necessarily adjudicated to establish a single "ground truth" per case. For the second study, "blinded image quality assessments" were performed, and ratings were averaged, but no adjudication process is described.

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

A clear MRMC comparative effectiveness study, in the sense of measuring human reader improvement with AI vs. without AI assistance, is not explicitly described.

The studies compare the performance of Sonic DL images (algorithm output) against conventional images, with human readers evaluating both.

The first reader study compares quantitative measurements from Sonic DL images to conventional images, indicating suitability for performing functional cardiac measurements by showing smaller inter-method variability than inter-observer intra-method variability for conventional images. This suggests Sonic DL is at least as reliable as the variability between conventional human measurements.
The second reader study involves blinded image quality assessments of both conventional and Sonic DL images, confirming that Sonic DL images were rated as diagnostic quality.
The additional clinical testing for 1 R-R free breathing shows that Sonic DL images were "scored higher than the corresponding conventional free breathing Cine images" by a U.S. board-certified radiologist.

These are comparisons of the image quality and output from the AI system versus conventional imaging, interpreted by readers, rather than measuring human reader performance assisted by the AI system.

Therefore, the effect size of how much human readers improve with AI vs. without AI assistance is not provided because the studies were designed to evaluate the image output quality and measurement agreement of the AI-reconstructed images themselves, not to assess an AI-assisted workflow for human readers.

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

Yes, standalone performance was assessed for image quality metrics.

Nonclinical Testing: "Model accuracy metrics such as Peak-Signal-to-Noise (PSNR), Root-Mean-Square Error (RMSE), Structural Similarity Index Measure (SSIM), and Mean Absolute Error (MAE) were used to compare simulated Sonic DL images with different levels of acceleration and numbers of phases to the fully sampled images." This is a standalone evaluation of the algorithm's output quality against a reference.
In Vivo Testing: "model accuracy and temporal sharpness evaluations were conducted using in vivo cardiac cine images obtained from 19 health volunteers." This is also a standalone technical evaluation of the algorithm's output on real data.

7. The Type of Ground Truth Used

Nonclinical Testing (Simulated Data): The ground truth was the "fully sampled images" generated from an MRXCAT phantom and a digital phantom.
Clinical Testing (Reader Studies):
- Functional Measurements: The "ground truth" for comparison was the measurements taken from the "conventional ASSET Cine images." The variability of these conventional measurements across readers also served as a baseline for comparison. This is a form of clinical surrogate ground truth (comparing to an established accepted method).
- Image Quality Assessments: The "ground truth" was the expert consensus/opinion of the radiologists during their blinded assessments of diagnostic quality.
- Additional Clinical Testing (1 R-R Free Breathing): Functional measurements were compared to "conventional ASSET Cine breath hold images" (clinical surrogate ground truth). Image quality was based on the scoring by a "U.S. board certified radiologist" (expert opinion).

No pathology or outcomes data were used as ground truth. The ground truth in the clinical setting was primarily based on established imaging techniques (conventional MR) and expert radiologist assessments.

8. The Sample Size for the Training Set

The document does not explicitly state the sample size for the training set used for the deep learning model. It only describes the data used for testing the device.

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

Since the training set size is not provided, the method for establishing its ground truth is also not described in the provided text. Typically, for deep learning reconstruction, the "ground truth" for training often involves fully sampled or high-quality reference images corresponding to the undersampled input data.

Summary

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May 30, 2023

GE Medical Systems,LLC (GE Healthcare) % Glen Sabin Regulatory Affairs Director 3200 N Grandview Blvd. WAUKESHA WI 53188

Re: K223523

Trade/Device Name: Sonic DL Regulation Number: 21 CFR 892.1000 Regulation Name: Magnetic resonance diagnostic device Regulatory Class: Class II Product Code: LNH Dated: April 28, 2023 Received: April 28, 2023

Dear Glen Sabin:

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

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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,

D.R.X.

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

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Indications for Use

510(k) Number (if known) K223523

Device Name Sonic DL

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
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Prescription Use (Part 21 CFR 801 Subpart D)

| Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary

K223523

In accordance with 21 CFR 807.92 the following summary of information is provided:

Date:	24 May 2023
Submitter:	GE Medical Systems, LLC3200 N. Grandview Blvd.Waukesha, WI 53188
Primary Contact:	Glen SabinRegulatory Affairs DirectorPhone: 262 894-4968Email: Glen.Sabin@GE.com
Secondary Contact:	Sandra WestphalSenior Regulatory Affairs LeaderPhone: 262 720-8872Email: Sandra.Westphal@GE.com
Device Trade Name:	Sonic DL
Common / Usual Name:	MR System
Classification Name:	Magnetic Resonance Diagnostic Device
Regulation Number:	21 CFR 892.1000
Primary Product Code:	LNH
Predicate Device:
510(k) Number:	K213668
Device Name:	SIGNA Hero
Manufacturer:	GE Medical Systems, LLC

Device Description:

Sonic DL is an optional feature that is integrated into the MR system software and activated through a purchasable software option key.

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Indications for Use:

The Indications for Use statement for the proposed device is provided below:

Comparison of Technological Characteristics:

The proposed Sonic DL software feature that is the subject of this 510(k) is similar to the 2D FIESTA Cine feature with ASSET acceleration that is included in the predicate SIGNA Hero. K213668. The predicate device uses breath holds and a conventional parallel imaging acceleration technique (ASSET) that typically achieves acceleration factors between 2 and 4, and acquires each slice in 6 to 10 heartbeats. Sonic DL can achieve acceleration factors as high as 12, and enables single heartbeat (1 R-R) imaging with either breath holds or free breathing.

Summary of Nonclinical Testing:

The performance of the Sonic DL reconstruction algorithm has been evaluated using simulated data generated from an MRXCAT phantom, and a digital phantom. Model accuracy metrics such as Peak-Signal-to-Noise (PSNR), Root-Mean-Square Error (RMSE), Structural Similarity Index Measure (SSIM), and Mean Absolute Error (MAE) were used to compare simulated Sonic DL images with different levels of acceleration and numbers of phases to the fully sampled images. Additionally, line profiles across the heart at different phases were used to evaluate both inplane and temporal sharpness.

The nonclinical testing demonstrated that Sonic DL is capable of reconstructing Cine images from highly under sampled data that are similar to the fully sampled Cine images in terms of image quality and temporal sharpness.

Summary of Clinical Testing:

Two reader evaluation studies were performed using Sonic DL images acquired from clinical sites and from healthy volunteers at GE Healthcare facilities. In one study, three radiologists were asked to determine various quantitative measurements such as left ventricular volumes, ejection fraction, and cardiac output using both conventional Cine and Sonic DL image sets as summarized below:

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Number of image series evaluated:	107
Number of unique subjects:	57
Patients:	46
Healthy volunteers:	11
Sites contributing data:	7
GE Healthcare facilities:	2
External collaborators (clinical sites):	5
Gender of subjects:
Male:	35
Female:	22
Age range of subjects:	12 weeks to 82 years old
Pathology:	Subjects from clinical sites included examples of various cardiac pathology, including structural heart disease, ischemic cardiomyopathy, and non-ischemic cardiomyopathy.
Equipment Used:	GE HealthCare 1.5T and 3.0T MR Systems
Acquisition Parameters:
Field of View:	28 - 46 cm
In-plane resolution:	1.3 – 2.2 mm(both x and y directions)
Acquired Temporal Resolution (frame rate)	23.7 – 70.2 ms

The results showed that the inter-method variability (coefficient of variability comparing functional measurements taken with Sonic DL images versus measurements using the conventional ASSET Cine images) was smaller than the inter-observer intra-method variability for the conventional ASSET Cine images for all parameters, indicating that Sonic DL is suitable for performing functional cardiac measurements.

In a second study, three radiologists were asked to perform blinded image quality assessments of both conventional 2D FIESTA Cine images with ASSET acceleration, and Sonic DL images obtained with different number of R-R intervals and different acceleration factors. This study involved 127 image sets which included a subset of the subjects described above, and included different cardiac views such as short axis, long axis, and aortic valve images. The results of this study showed that on average the Sonic DL images were rated as being of diagnostic quality while providing a significant reduction in scan time compared to the conventional ASSET Cine images.

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In addition to the two reader studies described above, other tests were performed. Similar to the nonclinical testing using the digital phantom, model accuracy and temporal sharpness evaluations were conducted using in vivo cardiac cine images obtained from 19 health volunteers.

Finally, clinical testing has been performed to demonstrate that Sonic DL is capable of achieving a 12 times acceleration factor and obtaining free-breathing images in a single heartbeat (1 R-R). Functional measurements using Sonic DL 1 R-R free breathing images from 10 subjects were compared to functional measurements using the conventional ASSET Cine breath hold images, and showed close agreement. Additionally, the image quality of 13 Sonic DL 1 R-R free breathing cases was evaluated by a U.S. board certified radiologist, and scored higher than the corresponding conventional free breathing Cine images from the same subjects.

The results of the clinical testing confirmed that the Sonic DL feature provides images that are of diagnostic quality, and that allow functional measurements that are within typical inter reader variability to the same measurements taken with conventional images. Additionally, the Sonic DL feature provided significantly shorter scan times that the conventional Cine imaging.

Conclusions Drawn from Performance Testing:

The nonclinical and clinical testing demonstrated that Sonic DL satisfies the product claims of reducing scan times while preserving image quality, enabling single heartbeat functional imaging, and enabling rapid free-breathing functional imaging.

The proposed Sonic DL software feature has been developed under GE Healthcare's quality system and is at least as safe and effective as the 2D FIESTA Cine feature with ASSET acceleration that is used in the legally marketed predicate device. The performance testing did not identify any new hazards, adverse effects, safety concerns, or performance concerns that are significantly different from those associated with cardiac cine MR imaging in general.

Therefore, GE Healthcare believes that Sonic DL is substantially equivalent to the predicate device and is safe and effective for its intended use.

Regulation Number and Section

§ 892.1000 Magnetic resonance diagnostic device.

(a)
Identification. A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).(b)
Classification. Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.