Methinks NCCT Stroke

K250685

Methinks Software S.L. · cleared 2025-06-16 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The Methinks NCCT Stroke device is an AI/ML Software as a Medical Device.”
Algorithmartificial intelligence algorithm
source quote (p.4)
“Methinks NCCT Stroke uses an artificial intelligence algorithm to analyze images and highlight cases with suspected (1) ICH and (2) LVO in the cloud in parallel to the ongoing standard of care image interpretation.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.8)
“Cybersecurity has been considered and addressed as part of the software verification process, in line with Section 524B of the FD&C Act as a Cyber device. Methinks implemented a risk-based cybersecurity strategy including secure design principles, vulnerability assessment, Software Bill of Materials (SBOM), and penetration testing. These activities ensure the software's safety, effectiveness, and robustness against potential cybersecurity threats.”

Validation studies (2)

Retrospective clinical

n=358 cases

endpoints: evaluate the software's performance in identifying NCCT head images containing intracranial hemorrhage (ICH) and Large Vessel Occlusion (LVO) findings

standards: EN ISO 14971:2019, ISO 62304:2015

Reader study (MRMC)

n=335 cases

endpoints: compare NCCT LVO sensitivity of the device to that of radiologists; expert non-inferiority; non-expert superiority

Reported performance (4 observations)

sensitivity94.7CI 89.3% - 97.8%
source quote (p.9)
“Specifically, ICH performance was observed at Se: 94.7% (95% CI: 89.3% - 97.8%)”
specificity99.5CI 97.5% - 99.9%
source quote (p.9)
“Sp: 99.5% (95% CI: 97.5% - 99.9%)”
sensitivityas written: “LVO Sensitivity”76.4CI 67.3% - 83.9%
source quote (p.9)
“and LVO was observed at Se: 76.4% (95% CI: 67.3% - 83.9%)”
specificityas written: “LVO Specificity”91.1CI 86.6% - 94.5%
source quote (p.9)
“and Sp: 91.1% (95% CI: 86.6% - 94.5%).”

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); 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/K250685