ProFound Detection (V4.0)

K240417

iCAD, Inc. · cleared 2024-11-08 · product code QDQ · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“ProFound Detection V4.0 is a computer-assisted detection and diagnosis (CAD) software device intended to be used concurrently by interpreting physicians while reading digital breast tomosynthesis (DBT) exams from compatible DBT systems.”
Algorithmneural network architecture that detects malignant soft-tissue densities and calcifications in digital breast tomosynthesis (DBT) images and assigns confidence scores (Certainty of Finding and Case Scores) for malignancy.
source quote (p.9)
“This has been accomplished by changing the neural network architecture for each subsystem and retraining the model, and by the processing of prior images when they are available. ... Each detected finding will also be assigned a "score” that corresponds to the ProFound Detection V4.0 algorithm's confidence that the detected finding is a cancer (Certainty of Finding). Certainty of Finding scores are a percentage in range of 0% to 100% to indicate CAD's confidence that the finding is malignant. ProFound Detection V4.0 also assigns a score to each case (Case Score) as a percentage in range of 0% to 100% to indicate CAD's confidence that the case has malignant findings.”
Adaptive (vs locked)No
source quote (p.8)
“In accordance with the PCCP, the CAD algorithm will be trained, tuned, and locked prior to commercial release of the algorithm with the extended DBT image acquisition system(s) listed in the PCCP.”
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP).”
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=952 cases

endpoints: Sensitivity; False Positives Per Image (FPPI); Area Under the ROC Curve (AUC)

Reported performance (3 observations)

sensitivity0.9004CI 0.8633-0.9374
source quote (p.9)
“0.9004 (0.8633-0.9374)”
specificity0.6205CI 0.5846-0.6565
source quote (p.9)
“0.6205 (0.5846-0.6565)”
aurocas written: “auc”0.8753CI 0.8475-0.9032
source quote (p.9)
“0.8753 (0.8475-0.9032)”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K240417