ScreenDx

K241891

Imvaria, Inc · cleared 2025-01-10 · product code QWO · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
ScreenDx is a software-only device that receives and analyzes lung computed tomography (CT) imaging data in order to assess for interstitial lung findings compatible with interstitial lung disease.
Algorithm3-D deep learning algorithm, machine learning pattern recognition
source quote (p.6)
The Analysis System is composed of a 3-D deep learning algorithm trained to identify interstitial lung findings compatible with interstitial lung disease.
Adaptive (vs locked)No
source quote (p.6)
The algorithm takes in the ingested CT scan, runs it through the locked model, and classifies whether interstitial lung findings compatible with interstitial lung disease appear to be present.
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 (2)

Retrospective clinical

n=3,018 cases

endpoints: software's performance in CT chest cases containing interstitial lung findings compatible with interstitial lung disease versus those without such patterns; 80% sensitivity; 80% specificity

standards: IEC 62304

Prospective clinical

n=2,482 cases

endpoints: ability to identify positive cases in a low prevalence population

Reported performance (6 observations)

sensitivity91.4CI 89.0-93.3%
source quote (p.14)
Specifically, sensitivity was observed to be 91.4% (89.0 - 93.3%)
specificity95.2CI 94.3-96.1%
source quote (p.14)
and specificity was observed to be 95.2% (CI: 94.3 - 96.1%).
ppvas written: “PPV85.1CI 82.3-87.6%
source quote (p.14)
PPV 85.1% [CI: 82.3-87.6%]
npvas written: “NPV97.4CI 96.6-98.0%
source quote (p.14)
NPV 97.4% [CI: 96.6-98.0%]
sensitivityas written: “Additional Validation Study Device Sensitivity87CI 85.8-88.5%
source quote (p.16)
Device Sensitivity 87% [CI: 85.8-88.5%]
specificityas written: “Additional Validation Study Device Specificity98CI 97.5-98.5%
source quote (p.16)
Device Specificity 98% [CI: 97.5-98.5%]

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). 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).

RIGOR™ Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: radar.healthai.com/precedent/device/K241891