QP-Prostate® CAD

K242683

Quibim S.L. · cleared 2025-03-18 · product code QDQ · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“QP-Prostate® CAD is an artificial intelligence-based Computed Aided Detection and Diagnosis (CADe/CADx) image processing software that automatically detects and identifies suspected lesions in the prostate gland based on bi-parametric prostate MRI.”
Algorithmartificial intelligence-based, based on Neural Networks and Machine Learning
source quote (p.6)
“Both devices are artificial intelligence-based, but they differ in algorithm methodology (e.g. ProstatID™™ is based on random forest and QP-Prostate® CAD is based on Neural Networks and Machine Learning).”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Retrospective clinical

n=247 cases

endpoints: AUC-ROC at lesion level; sensitivity at lesion level; specificity at lesion level

Reader study (MRMC)

n=228 cases

endpoints: performance advantage of using QP-Prostate® CAD output compared to not using its output for diagnosis of csPCa lesions by clinical readers, determined by the AUCaided versus AUCunaided at case level; performance advantage of using QP-Prostate® CAD output compared to not using its output for diagnosis of csPCa lesions by clinical readers, determined by sensitivity and specificity of the readers with and without QP-Prostate® CAD at case level

Reported performance (5 observations)

sensitivity0.795CI 95% CI: 0.722-0.861
source quote (p.11)
“Sensitivity (high and moderate suspicion markers) 0.795 (95% CI: 0.722-0.861)”
aurocas written: “auc”0.732CI 95% CI: 0.668-0.791
source quote (p.11)
“AUC-ROC 0.732 (95% CI: 0.668-0.791)”
false_positive_rate_per_imageas written: “False Positive Rate per Case (high suspicion marker, any biopsy source)”0.417CI 95% CI: 0.313-0.522
source quote (p.11)
“False Positive Rate per Case (high suspicion marker, any biopsy source) 0.417 (95% CI: 0.313-0.522)”
false_positive_rate_per_imageas written: “False Positive Rate per Case (high and moderate suspicion markers, any biopsy source)”0.855CI 95% CI: 0.709-0.996
source quote (p.11)
“False Positive Rate per Case (high and moderate suspicion markers, any biopsy source) 0.855 (95% CI: 0.709-0.996)”
aurocas written: “ΔAUC (AUCaided- AUCunaided)”0.019CI 95% CI: 0.001-0.038
source quote (p.12)
“ΔAUC (AUCaided- AUCunaided) 0.019 (95% CI: 0.001-0.038)”

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/K242683