Radiology AI Directory

FDA-cleared profile

SubtlePET

Subtle Medical, Inc.

SubtlePET is DICOM image-processing software that reduces noise in FDG, amyloid, 18F-DOPA, 18F-DCFPyL, Ga-68 Dotatate, and Ga-68 PSMA PET images for radiologist or nuclear-medicine-physician review.

Nuclear medicine
Evidence status: each field states its source quality, applicability, and review date. Research pending, information not established, and vendor documentation pending remain distinct outcomes.

Clinical details

What this tool is for

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

Exact purpose
SubtlePET is DICOM image-processing software that reduces noise in FDG, amyloid, 18F-DOPA, 18F-DCFPyL, Ga-68 Dotatate, and Ga-68 PSMA PET images for radiologist or nuclear-medicine-physician review.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Intended users
Qualified nuclear medicine physicians, radiologists, technologists, and trained PET/CT professionals.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Care setting and population
PET/CT departments using a compatible scanner, supported acquisition, and the labeled reconstruction workflow.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Workflow role
PET image denoising, reconstruction, or quantitative image-processing support before professional review.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Required input
Supported PET sinogram, list-mode, or reconstructed DICOM data and required CT or acquisition metadata.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Output and human action
Processed PET image series, quantitative values, and visual identifiers for professional review.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Limitations
The cleared tracer, reconstruction input, scanner, acquisition, dose, noise level, and quantitative use determine applicability; image-processing benefit is not a universal diagnostic-performance claim.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03

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
K211964
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Modality
PET/SPECT/Nuclear Medicine
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Anatomy
Multi-region
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Clearance type
510(k)
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Decision date
2021-09-28
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
FDA status
FDA-cleared
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31

Implementation

Questions for IT, informatics, and operations

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

Integration
K211964 describes a DICOM 3.0 receive-process-forward workflow. The current Subtle Medical conformance material is family context; validate node configuration, identifiers, supported transfer syntaxes, routing, and rollback for the installed release.
  • Public source
  • Product family
  • Checked 2026-09-03

Current vendor materials are product-family evidence for K211964; confirm the exact cleared version, enabled options, deployment, and local compatibility.

Deployment and data flow
Software integrated with the supported PET/CT scanner or deployed as a connected DICOM processing service.
  • Public source
  • Product family
  • Checked 2026-09-03

Current vendor materials are product-family evidence for K211964; confirm the exact cleared version, enabled options, deployment, and local compatibility.

Security and privacy
Vendor documentation pending
  • Vendor confirmation
  • Exact FDA submission
  • Checked 2026-09-03

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.

Training and support
Only qualified nuclear medicine physicians, radiologists, technologists, and trained pet/ct professionals should operate or interpret the product. Local onboarding should cover the exact release, supported population, limitations, failure examples, escalation, downtime, and competency documentation.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
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: The cleared tracer, reconstruction input, scanner, acquisition, dose, noise level, and quantitative use determine applicability; image-processing benefit is not a universal diagnostic-performance claim.
  • Public source
  • Product family
  • Checked 2026-09-03

Current vendor materials are product-family evidence for K211964; confirm the exact cleared version, enabled options, deployment, and local compatibility.

Release and scope verification

Map the installed model, build, options, population, anatomy, inputs, outputs, and enabled AI functions to K211964 before acceptance.

exact submission · checked 2026-09-03

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

Source

Interoperability acceptance

K211964 describes a DICOM 3.0 receive-process-forward workflow. The current Subtle Medical conformance material is family context; validate node configuration, identifiers, supported transfer syntaxes, routing, and rollback for the installed release.

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.

SourceSourceSource

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. The cleared tracer, reconstruction input, scanner, acquisition, dose, noise level, and quantitative use determine applicability; image-processing benefit is not a universal diagnostic-performance claim.

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: The cleared tracer, reconstruction input, scanner, acquisition, dose, noise level, and quantitative use determine applicability; image-processing benefit is not a universal diagnostic-performance claim.

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.

SourceSourceSource

Evidence

Performance evidence

Metrics are shown only when they are tied to a source, endpoint, population, and tested product version. Candidate literature without exact product and version linkage is not shown as product evidence.

Evidence summary
K211964 describes a deep-neural-network residual noise-reduction workflow that receives DICOM 3.0 images, processes them, and forwards the results to a PACS or workstation. FDA software, image-quality, and functional testing supports the cleared processing workflow; no universal diagnostic-performance, dose-reduction, or tracer-independent claim is established.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-03
Reported sensitivity
Not applicable
  • Not applicable
  • Not applicable
  • Checked 2026-09-03

Sensitivity is not the primary endpoint for this system, reconstruction, segmentation, guidance, or quantitative function. Use the task-specific evidence below.

Reported specificity
Not applicable
  • Not applicable
  • Not applicable
  • Checked 2026-09-03

Specificity is not the primary endpoint for this system, reconstruction, segmentation, guidance, or quantitative function. Use the task-specific evidence below.

No contextualized exact-version metric has completed evidence review. Regulatory-document values, when available, are shown above with their limitations.

K211964 FDA performance package for SubtlePET

  • DesignManufacturer software, image-quality, DICOM, and functional validation
  • PopulationSupported PET images using the labeled radiotracers and DICOM node workflow
  • Scopeexact submission
  • Tested versionSubtlePET
  • IndependenceSponsor or vendor study

K211964

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

Source

3 unlinked candidate evidence records are retained for source review and excluded from this evidence display.

Costs and setup

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
  • Reviewed sources checked
  • Exact FDA submission
  • Checked 2026-09-03

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.

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.
  • Public source
  • Not applicable
  • Checked 2026-09-03

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 K211964 by exact submission identifier. This does not exclude product-family, later, or adverse-event information.
  • Public source
  • Exact FDA submission
  • Checked 2026-09-03

Exact-identifier review does not prove absence of all product-family safety signals.

Buyer worksheet

Open questions to take to the vendor

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
10Awaiting review PubMed leads
0Awaiting review 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 10 PubMed and 0 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 & history

How this profile was documented

Open the ledger for source dates, scope, and research-record updates.

View source ledger and history

Source ledger

  1. K211964 FDA decision source

    U.S. Food and Drug Administration - Accessed 2026-08-31

    Scope: regulatoryIdentity, purpose, modality, anatomy

  2. Artificial Intelligence-Enabled Medical Devices

    U.S. Food and Drug Administration - Accessed 2026-08-31

    Scope: regulatoryIdentity, modalityContext

  3. PubMed biomedical literature index

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery

  4. ClinicalTrials.gov study registry

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery, studyStatus

  5. Medicare Coverage Database

    Centers for Medicare & Medicaid Services - Accessed 2026-09-01

    Scope: coverage, codingContext

  6. openFDA Device Recall API

    U.S. Food and Drug Administration - Accessed 2026-09-02

    Scope: recallDiscovery, nativeSubmissionMatching

  7. Subtle Medical DICOM conformance statement

    Subtle Medical - Accessed 2026-09-03

    Scope: integration, deployment, productFamilyContext

  8. SubtlePET government product information

    Subtle Medical - Accessed 2026-09-03

    Scope: productFamilyContext, currentCommercialContext

  9. Evaluation of PET/CT Artificial Intelligence Image Reconstructions VS Harmonized Clinical Reconstruction.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  10. Clinical and phantom validation of a deep learning based denoising algorithm for F-18-FDG PET images from lower detection counting in comparison with the standard acquisition.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  11. Imaging quality of an artificial intelligence denoising algorithm: validation in (68)Ga PSMA-11 PET for patients with biochemical recurrence of prostate cancer.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  12. The impact of introducing deep learning based [(18)F]FDG PET denoising on EORTC and PERCIST therapeutic response assessments in digital PET/CT.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  13. Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  14. Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  15. Artificial intelligence-based PET denoising could allow a two-fold reduction in [(18)F]FDG PET acquisition time in digital PET/CT.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  16. Clinical value of artificial intelligence in reducing PET image acquisition time: routine clinical validation using qualitative, quantitative, and radiomic analysis on a cohort of 282 patients undergoing [(18)F]FDG and [(68)Ga]Ga-PSMA-11 PET/CT.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  17. Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

  18. Implantation of an Artificial Intelligence Denoising Algorithm Using SubtlePET™ with Various Radiotracers: 18F-FDG, 68Ga PSMA-11 and 18F-FDOPA, Impact on the Technologist Radiation Doses.

    U.S. National Library of Medicine - Accessed 2026-09-03

    Scope: evidenceStudies, productFamilyContext, evidenceDiscovery

Research history

  1. K211964 FDA decision

    Regulatory record

    510(k)

  2. Source-review record updated

    Research record

    human reviewed

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