MammoScreen BD

K241561

Therapixel · cleared 2024-10-02 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“MammoScreen BD is a software-only device (SaMD) using artificial intelligence to assist radiologists in the interpretation of mammograms.”
AlgorithmImage feature-based with deep learning
source quote (p.8)
“Image feature-based with deep learning”
Adaptive (vs locked)FDA source did not state this
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 (1)

Reader study (MRMC)

n=922 patients · 3 site(s)

endpoints: A confusion matrix between the density value assigned by MammoScreen BD and the ground truth.; Accuracy, defined as the number of correctly classified examinations divided by the total number of examinations included in the dataset.

standards: IEC 62304:2006/A1:2016- Medical device software - Software life-cycle processes

Reported performance (19 observations)

agreement_kappaas written: “quadratically-weighted Cohen's kappa (four-class)”89.03CI [87.43 – 90.56]
source quote (p.10)
“On the four-class task, MammoScreen BD achieved a quadratically-weighted Cohen's kappa of 89.03, 95% confidence interval [87.43 – 90.56].”
accuracyas written: “Accuracy (four-class)”84.68CI [82.68, 86.67]
source quote (p.11)
“Accuracy = 84.68 with CI = [82.68, 86.67]”
agreement_kappaas written: “Cohen's Kappa (linear) (four-class)”82.94CI [80.67, 85.22]
source quote (p.11)
“Cohen's Kappa (linear) = 82.94 with CI = [80.67, 85.22]”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (binary)”84.5CI [81.46, 87.36]
source quote (p.11)
“On the binary classification task, MammoScreen BD achieved a quadratically-weighted Cohen's kappa of 84.50, 95% confidence interval [81.46, 87.36].”
accuracyas written: “Accuracy (binary)”92.29CI [90.82, 93.77]
source quote (p.11)
“Accuracy = 92.29 with CI = [90.82, 93.77]”
agreement_kappaas written: “Cohen's Kappa (linear) (binary)”84.5CI [81.46, 87.36]
source quote (p.11)
“Cohen's Kappa (linear) = 84.50 with CI = [81.46, 87.36]”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (FFDM)”89.11CI [87.01 – 91.00]
source quote (p.13)
“When considering FFDM mammogram only, MammoScreen BD achieved a quadratically-weighted Cohen's kappa of 89.11, 95% CI [87.01 – 91.00]”
accuracyas written: “Accuracy (FFDM)”84.85CI [82.09, 87.33]
source quote (p.13)
“Accuracy = 84.85 with CI = [82.09, 87.33]”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (2DSM)”88.89CI [85.88 – 91.50]
source quote (p.13)
“The same metric achieves a value of 88.89, 95% CI [85.88 – 91.50] when evaluated on 2DSM mammograms”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Age < 55)”87.93CI [85.19 – 90.26]
source quote (p.14)
“Age <55: 87.93 (95% CI: 85.19 – 90.26)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (55 <= Age < 65)”91.22CI [88.05 – 93.77]
source quote (p.14)
“55 ≤ Age < 65: 91.22 (95% CI: 88.05 – 93.77)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Age >= 65)”87.15CI [82.70 – 90.96]
source quote (p.14)
“Age ≥ 65: 87.15 (95% CI: 82.70 – 90.96)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Thickness < 50 mm)”85.81CI [81.99 – 89.30]
source quote (p.16)
“Thickness < 50 mm: 85.81 (95% CI: 81.99 – 89.30)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (50 mm <= Thickness < 70 mm)”86.9CI [84.25 – 89.34]
source quote (p.16)
“50 mm ≤ Thickness < 70 mm: 86.90 (95% CI: 84.25 – 89.34)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Thickness >= 70 mm)”89.29CI [85.19 – 92.89]
source quote (p.16)
“Thickness ≥ 70 mm: 89.29 (95% CI: 85.19 – 92.89)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (White race)”87.88CI [81.82 – 93.18]
source quote (p.18)
“White: 87.88 (95% CI: 81.82 – 93.18)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Asian race)”87.11CI [80.22 – 93.04]
source quote (p.18)
“Asian: 87.11 (95% CI: 80.22 – 93.04)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (Black or African American race)”90.82CI [85.58 – 94.97]
source quote (p.18)
“Black or African American: 90.82 (95% CI: 85.58 – 94.97)”
agreement_kappaas written: “quadratically-weighted Cohen's kappa (American Indian or Alaska native or native Hawaiian or Pacific islander race)”53.85CI [0.00 - 83.33]
source quote (p.18)
“American Indian or Alaska native or native Hawaiian or Pacific islander: 53.85 (95% CI: 0.00 - 83.33)”

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
2
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243685 (decision 2025-08-22) from Therapixel for a matching device line ("MammoScreen BD") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243685

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243679 (decision 2025-07-03) from Therapixel for a matching device line ("MammoScreen® (4)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243679

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/K241561