Transpara

K193229

ScreenPoint Medical B.V. · cleared 2020-03-05 · product code QDQ · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.5)

“Transpara™ is a software only application designed to be used by physicians to improve interpretation of digital mammography and digital breast tomosynthesis.”

AlgorithmDeep learning algorithms

source quote (p.5)

“'Deep learning' algorithms are applied to FFDM images and DBT slices for recognition of suspicious calcifications and soft tissue lesions (including densities, masses, architectural distortions, and asymmetries). Algorithms are trained with a large database of biopsy-proven examples of breast cancer, benign abnormalities, and examples of normal tissue.”

Adaptive (vs locked)FDA source did not state this

PCCPNo

Cybersecurity addressedNo

Validation studies (2)

Standalone

sample size not stated

endpoints: determining stand-alone performance of the algorithms; algorithm performance is non-inferior or better in comparison to Transpara 1.3.0

standards: ISO 14971:2007 Medical Devices - Application Of Risk Management To Medical Devices, IEC 62304:2015 Medical Device Software - Software Life Cycle Processes, DEN180005 Decision summary with special controls for class II radiology device

Reader study (MRMC)

n=240 cases

endpoints: superior breast-level area under the receiver operating characteristic curve (AUC, ROC) between conditions when radiologists use Transpara™ to read DBT exams at a significance level alpha 0.05; reading time reduction; non-inferior or higher sensitivity; non-inferior or higher specificity; reading time reduction on normal exams; standalone AUC performance of Transpara™ was non-inferior to the average AUC performance of the readers

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

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

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

re_clearance
The FDA AI/ML device list shows a newer 510(k) K241831 (decision 2024-11-25) from ScreenPoint Medical B.V. for a matching device line ("Transpara (2.1.0)") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K241831
re_clearance
The FDA AI/ML device list shows a newer 510(k) K232096 (decision 2023-12-11) from Screenpoint Medical B.V. for a matching device line ("Transpara Density 1.0.0") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K232096
re_clearance
The FDA AI/ML device list shows a newer 510(k) K221347 (decision 2022-08-03) from ScreenPoint Medical B.V. for a matching device line ("Transpara 1.7.2") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K221347
re_clearance
The FDA AI/ML device list shows a newer 510(k) K210404 (decision 2021-06-02) from ScreenPoint Medical B.V. for a matching device line ("Transpara 1.7.0") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K210404

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). 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).