ClariSIGMAM

K203785

ClariPi Inc. · cleared 2021-09-10 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
ClariSIGMAM is a software application intended for use with compatible full field digital mammography systems.
AlgorithmSoftware application that automatically analyzes "for presentation" 2D digital mammograms to assess breast tissue composition. The software assesses the breast density of women and generates a breast density group information for the patient (BI-RADS A+B as fatty and BI-RADS C+D as dense) in accordance with the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) density classification scale.
source quote (p.5)
ClariSIGMAM software is a standalone software application that automatically analyzes "for presentation" 2D digital mammograms to assess breast tissue composition. The software assesses the breast density of women and generates a breast density group information for the patient (BI-RADS A+B as fatty and BI-RADS C+D as dense) in accordance with the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) density classification scale.
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedNo

Validation studies (5)

Retrospective clinical

sample size not stated

endpoints: Comparison of ClariSIGMAM-generated breast density estimates with Gold Standard breast density estimates

standards: ISO 14971 Medical devices - Application of risk management for medical devices, NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices issued May 11, 2005., Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.

Retrospective clinical

sample size not stated

endpoints: Reproducibility of breast density with age

standards: ISO 14971 Medical devices - Application of risk management for medical devices, NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices issued May 11, 2005., Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.

Retrospective clinical

sample size not stated

endpoints: Reproducibility of breast density estimates over time

standards: ISO 14971 Medical devices - Application of risk management for medical devices, NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices issued May 11, 2005., Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.

Retrospective clinical

sample size not stated

endpoints: Similarity of breast density estimates for left and right breasts

standards: ISO 14971 Medical devices - Application of risk management for medical devices, NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices issued May 11, 2005., Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.

Reader study (MRMC)

n=837 cases

endpoints: Comparison of breast density group information (BI-RADS A+B as fatty and BI-RADS C+D as dense) between experts' visual assessment and automated assessment with ClariSIGMAM

standards: ISO 14971 Medical devices - Application of risk management for medical devices, NEMA-PS 3.1- PS 3.20 Digital Imaging and Communications in Medicine (DICOM), Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices issued May 11, 2005., Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices issued September 6, 2017.

Reported performance (3 observations)

sensitivity0.873
source quote (p.8)
Dense 436 87.3%
specificity0.866
source quote (p.8)
Fatty 293 86.6%
agreement_kappaas written: “Kappa0.734CI [0.688, 0.781]
source quote (p.8)
n=837; Kappa 0.734 [0.688, 0.781]

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
3
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/K203785