EW10-EC02 Endoscopy Support Program

K230751

FUJIFILM Corporation · cleared 2023-12-15 · product code QNP · Gastroenterology-Urology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Against this background, the company has developed this software (EW10-EC02), a new AI-based CAD system, to support Health Care Provider (HCP) detection of large intestine polyps in colonoscopic images.”
Algorithmartificial intelligence-based algorithm
source quote (p.8)
“Support Program utilizes an artificial intelligence-based algorithm to perform the polyp detection function.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (3)

Bench

sample size not stated

endpoints: passing results on all applicable unit, integration, and requirements testing

standards: General Principles of Software Validation, Guidance for Industry and FDA Staff

Bench

n=149 images

endpoints: demonstrate that the object-level, frame-level and overall algorithmic performance is sufficient to fulfill the indications for use of the EW10-EC02

Prospective clinical

n=1,031 patients · 12 site(s)

endpoints: Adenoma per colonoscopy (APC); Positive predictive value (PPV); Positive percent agreement (PPA)

Reported performance (4 observations)

sensitivity0.955
source quote (p.9)
“Sensitivity per lesion WLI mode 95.1% LCI mode 95.5%”
aurocas written: “auc”0.87CI 0.86-0.88
source quote (p.11)
“The AUC values of ROC curves were respectively 0.79(WLI) and 0.87(LCI).”
ppvas written: “Positive Predictive Value (PPV) - Adenoma Detected (CAC group)”0.486
source quote (p.16)
“Adenoma Detected 504 (48.6%)”
agreement_kappaas written: “Positive Percent Agreement (PPA) - Positive Detected (CAC group)”0.607
source quote (p.16)
“Positive Detected 629 (60.7%)”

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); 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 Gastroenterology-Urology 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/K230751