syngo.CT Lung CAD

K203258

Siemens Healthcare GmbH · cleared 2021-03-31 · product code OEB · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.3)

“The syngo.CT Lung CAD device is a Computer-Aided Detection (CAD) tool designed to assist radiologists in the detection of solid and subsolid (part-solid and ground glass) pulmonary nodules during review of multi-detector computed tomography (MDCT) from multivendor examinations of the chest. The software is an adjunctive tool to alert the radiologist to regions of interest (ROI) that may otherwise be overlooked. The software device is an algorithm which does not have its own user interface component for displaying of CAD marks.”

AlgorithmConvolutional Neural Networks (CNN), AI models

source quote (p.6)

“Specifically, both the predicate VC30 and VD20 share the same algorithm based on Convolutional Neural Networks (CNN) and the same basic architectural workflow. (1) new AI models for Candidate Generation and Classification components to support the extension of the claims. (3) a post-filtering module (also CNN-based) aimed at reducing false positives caused by bony protrusions or detections in the colon.”

Adaptive (vs locked)FDA source did not state this

PCCPFDA source did not state this

Cybersecurity addressedFDA source did not state this

Validation studies (3)

Reader study (MRMC)

n=232 cases

endpoints: assessing the effect on readers' diagnostic accuracy when using Lung CAD, relative to their unaided accuracy; significant improvement for the detection of pulmonary nodules (solid, part-solid and ground glass) with both reading workflows

Standalone

sample size not stated

endpoints: reduction of false positives; marks generated by the two devices are reasonably consistent

Bench

sample size not stated

endpoints: verification and validation of the device intended use; ensure safety and effectiveness; Verify the Design Specification, Risk Mitigations, identify runtime errors and memory leaks, and Verify the Logic; Verify the correct implementation of the design and test coverage specified by the software requirements and Design Specifications; System test: It is performed on the integrated product comprising the software units and components; System Validation: Validate the intended use defined in the requirements specifications and risk labelling mitigations

standards: ISO 14971:2007, IEC 62304 Edition 1.1 2015-06, IEC 62366-1 Edition 1.0 2015-02

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) K231157 (decision 2023-07-19) from Siemens Healthcare GmbH for a matching device line ("syngo.CT Lung CAD (Version VD30)") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K231157

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).