FDA-cleared profile

DeepHealth ProstateAI

Quantib B.V.

DeepHealth ProstateAI is a Computer-Aided Detection and Diagnosis (CADe/x) software device developed to aid trained physicians in the detection and characterization of prostate cancer lesions using MR imaging data in patients aged 40 years and older. DeepHealth ProstateAI analyzes T2W, ADC and DWI MR images. Combined with the MR images the software requires a binary mask containing the prostate gland segmentation. Output consists of ROI candidates including segmentations, and per ROI a classification indicating the likelihood of prostate cancer. The device is intended to assist in the detection of prostate cancer across the full range of grade groups (ISUP Grade Group >= 1), including clinically significant prostate cancer (ISUP Grade Group >= 2). Device outputs shall be input for a visualization and adaptation tool. DeepHealth ProstateAI is intended to be used as a concurrent reading aid for physicians assessing prostate MRI exams. Analysis by DeepHealth ProstateAI is not intended as a replacement for interpreting prostate abnormalities using MR image data consistent with clinical recommendations (e.g., including DCE information when available); nor should patient management decisions be made solely based on the results of DeepHealth ProstateAI.

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
DeepHealth ProstateAI is a Computer-Aided Detection and Diagnosis (CADe/x) software device developed to aid trained physicians in the detection and characterization of prostate cancer lesions using MR imaging data in patients aged 40 years and older. DeepHealth ProstateAI analyzes T2W, ADC and DWI MR images. Combined with the MR images the software requires a binary mask containing the prostate gland segmentation. Output consists of ROI candidates including segmentations, and per ROI a classification indicating the likelihood of prostate cancer. The device is intended to assist in the detection of prostate cancer across the full range of grade groups (ISUP Grade Group >= 1), including clinically significant prostate cancer (ISUP Grade Group >= 2). Device outputs shall be input for a visualization and adaptation tool. DeepHealth ProstateAI is intended to be used as a concurrent reading aid for physicians assessing prostate MRI exams. Analysis by DeepHealth ProstateAI is not intended as a replacement for interpreting prostate abnormalities using MR image data consistent with clinical recommendations (e.g., including DCE information when available); nor should patient management decisions be made solely based on the results of DeepHealth ProstateAI.
Public source Exact FDA submission Checked 2026-09-01

Exact-submission indication text from the ACR AI Central model card. FDA labeling remains controlling.

Intended users
Healthcare professionals qualified to read and interpret prostate MRI exams (radiologists or other qualified physicians)
Public source Exact FDA submission Checked 2026-09-01

Intended-user text reported in the exact-submission ACR model card.

Care setting and population
Adult
Public source Exact FDA submission Checked 2026-09-01

Patient-population text reported in the exact-submission ACR model card; institutional setting may still require vendor confirmation.

Workflow role
Segmentation or contouring
Public source Exact FDA submission Checked 2026-09-01

Conservative normalization of explicit wording in an exact-submission source.

Required input
MR images or data. Inclusion criteria: T2W, ADC, and DWI MR images of the prostate gland combined with a binary mask containing the prostate gland segmentation from a cleared device; patients aged 40 years and older; adult males with a prostate gland undergoing MRI exams with clinical indicators suggestive of possible prostate cancer (elevated serum PSA, abnormal digital rectal examination, family history of prostate cancer, or known genetic markers)
Public source Exact FDA submission Checked 2026-09-01

Conservative normalization of explicit wording in an exact-submission source.

Output and human action
The AI model outputs ROI candidates including segmentations of detected regions within and extending from the prostate, and per ROI a categorical classification indicating the likelihood of prostate cancer (low, moderate, or high suspicion). Low suspicion (green) corresponds to 20% likelihood of PCa; moderate suspicion (yellow) corresponds to >20% to <80%; high suspicion (red) corresponds to 80%. Outputs are exported as DICOM Segmentation Objects or NIfTI files for display in PACS viewers as color-coded overlays.
Public source Exact FDA submission Checked 2026-09-01

Clinical output reported in the exact-submission ACR model card.

Limitations
Exclusion criteria: Not intended for use in emergency departments, intensive care units, general practitioner offices, mobile imaging units, or patient homes. Not intended as a replacement for physician interpretation or for stand-alone diagnostic use.
Public source Exact FDA submission Checked 2026-09-01

Limitations and supported-acquisition details reported in the exact-submission ACR model card.

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
K253682
FDA source Exact FDA submission Checked 2026-08-31
Modality
MRI
Public source Exact FDA submission Checked 2026-09-01

Imaging modality reported in the exact-submission ACR AI Central model card.

Anatomy
Prostate
Public source Exact FDA submission Checked 2026-09-01

Anatomy normalized from explicit exact-submission ACR model-card wording.

Clearance type
510(k)
FDA source Exact FDA submission Checked 2026-08-31
Decision date
2026-04-29
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
The exact-submission ACR model card explicitly references DICOM and PACS in the described input, output, or workflow; exact interfaces, versions, and local compatibility require confirmation.
Public source Exact FDA submission Checked 2026-09-01

Interoperability terms explicitly reported in the exact-submission ACR model card; interface versions and local compatibility still require confirmation.

Deployment and data flow
Research pending
Needs research Exact FDA submission Checked 2026-08-31

Attach an exact-product deployment and data-flow source.

Security and privacy
Vendor documentation pending
Vendor confirmation Exact FDA submission Checked 2026-08-13

FDA authorization does not establish the current commercial security posture. Request data-flow diagrams, hosting and retention details, access controls, audit logging, attestations, and incident-response documentation.

Training and support
Vendor documentation pending
Vendor confirmation Exact FDA submission Checked 2026-08-13

Training, onboarding, competency, and support commitments are commercial implementation details that require current vendor documentation.

Monitoring and change control
Vendor documentation pending
Vendor confirmation Exact FDA submission Checked 2026-08-13

Local acceptance testing, production monitoring, drift review, update control, and incident escalation require a current vendor and site-specific governance plan.

Input or output interoperability

DICOM is explicitly referenced in the described input, output, or workflow.

exact submission · checked 2026-09-01

The model card does not establish every supported DICOM object, transfer method, or local interface.

Result destination

PACS is explicitly referenced as a result destination.

exact submission · checked 2026-09-01

Confirm supported products, versions, routing behavior, and display requirements during local evaluation.

Evidence

Performance evidence

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

Evidence summary
Study type: Both. Cases: 250. Reader-study cases: 247
Public source Exact FDA submission Checked 2026-09-01

Structured study metadata from the exact-submission ACR model card; this is not an independent evidence synthesis.

Reported sensitivity
Research pending
Needs research Exact FDA submission Checked 2026-08-31

This field has not been curated yet.

Reported specificity
Research pending
Needs research Exact FDA submission Checked 2026-08-31

This field has not been curated yet.

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

DeepHealth ProstateAI regulatory performance study summary

Stand-alone performance and reader study (ACR AI Central category) · Adult

exact submission · Tested version: Exact product version not reported; regulatory study summarized for FDA submission K253682 · n=250 · Independence not established

K253682

ACR AI Central summarizes the regulatory study; consult the exact FDA materials before comparative use.

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
Vendor documentation pending
Vendor confirmation Exact FDA submission Checked 2026-08-13

FDA submission materials do not establish current commercial pricing. Request the pricing unit, term, minimum commitment, implementation fees, and included support from the vendor.

Reimbursement and coding
Research pending
Needs research Exact FDA submission Checked 2026-08-31

Determine whether any product-specific CPT/HCPCS pathway exists and separate it from billing for the underlying imaging service.

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
Not established in reviewed sources
Reviewed sources checked Exact FDA submission Checked 2026-09-04

No native submission-identifier match was found in the checked openFDA radiology recall snapshot. Product-name, manufacturer, and adverse-event searches remain necessary; this does not establish that no recall or safety report exists.

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.

Automated sources checkedStatus
2026-09-04Last searched
17Fields reviewed
5Source classes checked
0Unreviewed PubMed leads
0Unreviewed trial leads
0Unreviewed FDA recall leads

Exact-submission ACR model-card fields were normalized under the current provenance rules; vendor and independent-study confirmation remain distinct. Automated exact-name discovery found 0 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, acr ai central product, pubmed, clinical trials, openfda device recall

Sources

Source ledger

Sources accessed through 2026-09-02.

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