Koios DS for Breast

K190442

Koios Medical, Inc. · cleared 2019-07-03 · product code POK · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“Koios Decision Support (DS) for Breast is a software application designed to assist trained interpreting physicians in analyzing the breast ultrasound images of patients with soft tissue breast lesions who are being referred for further diagnostic ultrasound examination.”
Algorithmmachine learning-based decision support system; computer vision and machine learning techniques
source quote (p.3)
“Koios DS for Breast is a machine learning-based decision support system, indicated as an adjunct to diagnostic ultrasound for breast cancer. The engine uses computer vision and machine learning techniques embedded within a software capable of reading, interpreting, analyzing, and generating findings from ultrasound data. The underlying engine draws upon knowledge learned from a large database of known cases, tying image features to their eventual diagnosis, to form a predictive model.”
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=900 patients

endpoints: impact on Interpreting Physician (Reader) performance as defined by the area under the Receiver Operating Characteristic (ROC) Curve (AUC) when Koios DS for Breast and an ultrasound examination are combined (USE + DS), compared to USE Alone

Bench

n=900 patients

endpoints: AUC

Bench

n=1,300 cases

endpoints: overall accuracy; concordance with trained interpreting physicians

Reported performance (7 observations)

aurocas written: “auc”0.882
source quote (p.15)
“System performance on the 900 cases reported an AUC of 88.2%.”
aurocas written: “mean AUC shift”0.037
source quote (p.11)
“the Koios DS for Breast study showed a mean shift of +0.037.”
aurocas written: “AUC (USE + DS)”0.6797CI .6653, .6941
source quote (p.15)
“USE + DS was .6797 (.6653, .6941) with 95% CI demonstrating a significant increase in the metric (a = .05).”
agreement_kappaas written: “Kappa: Reader vs Reader (Shape)”0.769CI [0.711, 0.826]
source quote (p.16)
“Shape 0.769 [0.711, 0.826]”
agreement_kappaas written: “Kappa: Reader vs Reader (Orientation)”0.728CI [0.655, 0.801]
source quote (p.16)
“Orientation 0.728 [0.655, 0.801]”
agreement_kappaas written: “Kappa: System vs Reader (Shape)”0.738CI [0.679, 0.797]
source quote (p.16)
“Shape 0.738 [0.679, 0.797]”
agreement_kappaas written: “Kappa: System vs Reader (Orientation)”0.744CI [0.675, 0.813]
source quote (p.16)
“Orientation 0.744 [0.675, 0.813]”

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
2
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K242130 (decision 2024-11-15) from Koios Medical, Inc. for a matching device line ("Koios DS") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K242130

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K212616 (decision 2021-12-16) from Koios Medical, Inc. for a matching device line ("Koios DS") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K212616

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/K190442