FDA-cleared profile

Sonic DL

GE Medical Systems,LLC (GE Healthcare)

Sonic DL is deep-learning MRI reconstruction for highly undersampled or accelerated cardiac acquisitions on compatible GE 1.5T and 3.0T MRI systems for pediatric and adult patients.

Cardiac imaging

Evidence status: each field shows source quality, applicability, and review date. Research pending, information not established in reviewed sources, and vendor documentation pending are distinct outcomes.

Clinical fit

What this tool is for

Start with the authorized purpose, then verify how it fits your service line and reading workflow.

Exact purpose: Sonic DL is deep-learning MRI reconstruction for highly undersampled or accelerated cardiac acquisitions on compatible GE 1.5T and 3.0T MRI systems for pediatric and adult patients.

Intended users: Qualified MRI technologists and interpreting physicians.

Care setting and population: Hospital and outpatient MRI departments using compatible scanner models and release-specific sequences.

Workflow role: Integrated MR reconstruction that accelerates acquisition or changes image appearance before routine professional interpretation.

Required input: Raw MRI acquisition data from supported scanners, coils, anatomies, pulse sequences, and acceleration settings.

Output and human action: Reconstructed MR image series for professional review, export, and archival.

Limitations: Performance depends on scanner, field strength, coil, sequence, anatomy, acceleration, input quality, and reconstruction setting; reconstructed images remain subject to physician review.

Regulatory identity

FDA record and catalog context

The FDA listing establishes the regulatory identity. It does not by itself establish local workflow fit, pricing, security, or performance in your environment.

FDA submission: K223523

Modality: MRI

Anatomy: Heart/Cardiovascular

Clearance type: 510(k)

Decision date: 2023-05-30

FDA status: FDA-cleared

Implementation

Questions for IT, informatics, and operations

Use these fields to structure a vendor demo, security review, and implementation estimate.

Integration: Integrated scanner reconstruction followed by normal DICOM delivery; validate reconstruction labels, geometry, quantitative values, PACS display, and downstream compatibility.

Deployment and data flow: Licensed reconstruction software integrated into the specified MRI scanner configurations.

Security and privacy: Vendor documentation pending

Training and support: Only qualified mri technologists and interpreting physicians should operate or interpret the product. Local onboarding should cover the exact release, supported population, limitations, failure examples, escalation, downtime, and competency documentation.

Monitoring and change control: Monitor by exact hardware, software, model, and algorithm version; patient population; anatomy; protocol; operator; input quality; output edits or overrides; failed studies; repeat acquisition or rework; downstream impact; downtime; incidents; recalls; and updates. Track these product-specific limits: Performance depends on scanner, field strength, coil, sequence, anatomy, acceleration, input quality, and reconstruction setting; reconstructed images remain subject to physician review.

Release and scope verification

Map the installed model, build, options, population, anatomy, inputs, outputs, and enabled AI functions to K223523 before acceptance.

exact submission · checked 2026-09-03

Later product-family features are not evidence that this cleared release includes them.

Source

Interoperability acceptance

Integrated scanner reconstruction followed by normal DICOM delivery; validate reconstruction labels, geometry, quantitative values, PACS display, and downstream compatibility.

product family · checked 2026-09-03

Test representative identifiers, orientation, geometry, measurements, units, routing, failure handling, and round trips locally. Vendor statements are current product-family context; confirm the exact cleared release and installed options.

Source Source

Clinical acceptance

Use a signed local test set for the supported population and workflow. Include common and difficult cases, exclusions, acquisition variation, failed or low-quality inputs, reviewer overrides, and downstream effects. Performance depends on scanner, field strength, coil, sequence, anatomy, acceleration, input quality, and reconstruction setting; reconstructed images remain subject to physician review.

exact submission · checked 2026-09-03

Define stop-use, escalation, rollback, and revalidation triggers before production use.

Source

Economic evaluation

Model capital and recurring cost against net staff time after review, throughput, repeat imaging or rework, room time, consumables, infrastructure, training, service, downtime, upgrade, and replacement costs.

product family · checked 2026-09-03

No exact-product price was found in the reviewed public material; vendor productivity claims are scenario inputs, not guaranteed local savings.

Source

Lifecycle monitoring

Monitor by exact hardware, software, model, and algorithm version; patient population; anatomy; protocol; operator; input quality; output edits or overrides; failed studies; repeat acquisition or rework; downstream impact; downtime; incidents; recalls; and updates. Track these product-specific limits: Performance depends on scanner, field strength, coil, sequence, anatomy, acceleration, input quality, and reconstruction setting; reconstructed images remain subject to physician review.

product family · checked 2026-09-03

Revalidate after material software, hardware, model, protocol, interface, or clinical-policy changes. Vendor statements are current product-family context; confirm the exact cleared release and installed options.

Source Source

Evidence

Performance evidence

Metrics are shown only when they are tied to a source, endpoint, population, and tested product version.

Evidence summary: K223523 reports 57 unique subjects, 107 image series from seven sites, and reader studies involving three radiologists, including cardiac pathology and healthy-volunteer image-quality comparisons. The public FDA summary supports the tested accelerated cardiac MR workflow but does not provide a single general sensitivity or specificity claim.

Reported sensitivity: Not applicable

Reported specificity: Not applicable

Unique validation subjects

57 subjects

Sonic DL cardiac-MR validation in Sonic DL.

Tested version: Sonic DL

Source

Image-series evaluations

107 series

Sonic DL cardiac-MR validation in Sonic DL.

Tested version: Sonic DL

Source

Validation sites

7 sites

Sonic DL cardiac-MR validation in Sonic DL.

Tested version: Sonic DL

Source

Reader radiologists

3 readers

Sonic DL cardiac-MR reader study in Sonic DL.

Tested version: Sonic DL

Source

K223523 FDA performance package for Sonic DL

Manufacturer accelerated cardiac-MR reconstruction, image-quality, reader, and accuracy validation · 57 unique subjects, including 46 patients and 11 healthy participants, across 7 sites and cardiac pathologies

exact submission · Tested version: Sonic DL · Sponsor or vendor study

K223523

Manufacturer evidence submitted for FDA clearance or approval; local clinical, technical, and workflow acceptance remains necessary.

Source

Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Peer-reviewed literature candidate identified by exact-name search; full product and version applicability review pending · Heart/Cardiovascular or related MRI workflow; exact product and version linkage not established

product family · Tested version: Candidate source; exact FDA submission and product version not established · Independence not established

39079600

Candidate source was found by automated exact-name search; product or version linkage and clinical endpoint were not independently established, so it must not be treated as exact-submission performance evidence.

Source

Clinical evaluation of deep learning-accelerated 3D FLAIR imaging at 1.5T and 3T for visualization of cerebral white matter lesions.

product family · Tested version: Candidate source; exact FDA submission and product version not established · Independence not established

42506799

Source

Qualitative and Quantitative Evaluation of a Deep Learning-Based Reconstruction for Accelerated Cardiac Cine Imaging.

product family · Tested version: Candidate source; exact FDA submission and product version not established · Independence not established

40150695

Source

Screening and Staging of Benign vs Malignant Pelvic Abnormalities

ClinicalTrials.gov candidate identified by exact-name search; full product and version applicability review pending · Heart/Cardiovascular or related MRI workflow; exact product and version linkage not established

product family · Tested version: Candidate source; exact FDA submission and product version not established · Independence not established

NCT07407959

Source

Economics and lifecycle

Budget and ongoing governance

These are common procurement questions; unknown values remain visible until a source supports them.

Pricing and total cost: Not established in reviewed sources

Reimbursement and coding: No separate named-product Medicare payment was identified in the reviewed CMS coverage material. Evaluate the product within the applicable imaging, procedural, or surgical service line and verify payer, site-of-service, and coding assumptions independently.

No product-specific code

No separate named-product payment identified in reviewed public material

Centers for Medicare & Medicaid Services · United States

Build a local total-cost and value model; do not infer reimbursement from FDA clearance or approval.

Source

Safety and lifecycle

Postmarket record

Recall and adverse-event records are shown only after product matching. Adverse-event reports do not establish incidence or causality.

Postmarket safety review: The 2026-09-02 openFDA device-recall snapshot contained no record matched to K223523 by exact submission identifier. This does not exclude product-family, later, or adverse-event information.

Buyer worksheet

Open questions to take to the vendor

Verify security and privacy controls: Public materials reviewed for this exact release do not establish the complete security posture. Request data-flow, identity, audit, encryption, retention, remote-access, vulnerability-management, backup, and incident-response evidence.
Verify pricing and total cost: No public list price for the exact cleared configuration was found. Obtain a written quote separating hardware or license basis, implementation, interfaces, infrastructure, training, service, upgrades, renewal, consumables, and exit costs.

Open evaluation checklist

Research record

What has been checked

This audit distinguishes completed source review from fields that have not yet been researched.

Human reviewedStatus

2026-09-04Last searched

25Fields reviewed

11Source classes checked

7Unreviewed PubMed leads

1Unreviewed trial leads

0Unreviewed FDA recall leads

Recovered from the prior exact-submission extraction and normalized under the current provenance rules. Exact FDA decision materials were reviewed for identity, indication, users, workflow, limitations, and submitted performance. Current vendor material is labeled product-family context where it does not establish the exact release. PubMed and ClinicalTrials.gov results are retained as candidate evidence with version applicability pending; CMS reimbursement context and exact-identifier openFDA postmarket results were also checked. Pricing, final security architecture, contracted services, enabled options, and local interoperability remain organization-specific evidence. Automated exact-name discovery found 7 PubMed and 1 ClinicalTrials.gov candidate records. Candidates require human product and version matching; zero candidates is not evidence that no studies exist. Native FDA recall identifiers produced 0 postmarket candidate records; 0 have been reviewed (0 published, 0 rejected) and 0 remain unreviewed.

Candidate leads remain unpublished until a human confirms the exact product and tested version.

Source classes: fda ai list, fda decision summary, fda decision material, vendor product page, peer reviewed literature, clinical trial registry, reimbursement policy, fda device recall, pubmed, clinical trials, openfda device recall

Sources

Source ledger

Sources accessed through 2026-09-03.

K223523 FDA decision source U.S. Food and Drug Administration · 2026-08-31
Artificial Intelligence-Enabled Medical Devices U.S. Food and Drug Administration · 2026-08-31
PubMed biomedical literature index U.S. National Library of Medicine · 2026-09-01
ClinicalTrials.gov study registry U.S. National Library of Medicine · 2026-09-01
Medicare Coverage Database Centers for Medicare & Medicaid Services · 2026-09-01
openFDA Device Recall API U.S. Food and Drug Administration · 2026-09-02
GE HealthCare Sonic DL announcement GE HealthCare · 2026-09-03
Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction. U.S. National Library of Medicine · 2026-09-03
Clinical evaluation of deep learning-accelerated 3D FLAIR imaging at 1.5T and 3T for visualization of cerebral white matter lesions. U.S. National Library of Medicine · 2026-09-03
Qualitative and Quantitative Evaluation of a Deep Learning-Based Reconstruction for Accelerated Cardiac Cine Imaging. U.S. National Library of Medicine · 2026-09-03
Deep Learning-Accelerated 3D Vessel Wall MRI: Prospective Evaluation of Sonic DL with Substantial Scan Time Reduction. U.S. National Library of Medicine · 2026-09-03
Fast cardiac magnetic resonance (CMR) protocol for biventricular functional assessment and tissue characterisation. U.S. National Library of Medicine · 2026-09-03
Clinical evaluation of deep learning accelerated 3D magnetic resonance cholangiopancreatography at 1.5 T and 3 T. U.S. National Library of Medicine · 2026-09-03
High-Resolution 2D versus 3D Lumbar Spine MRI Optimized with a Deep Learning Reconstruction Algorithm and Prototype Conformal Coil. U.S. National Library of Medicine · 2026-09-03
Screening and Staging of Benign vs Malignant Pelvic Abnormalities U.S. National Library of Medicine · 2026-09-03

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