Rapid CTA 360

K251151

iSchemaView · cleared 2025-07-16 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“Rapid CTA 360 device is a radiological computer-assisted Triage and Notification Software device using AI/ML.”
AlgorithmAI/ML software algorithm
source quote (p.6)
“Rapid CTA 360 uses an AI software algorithm to analyze images and highlight cases with suspected occlusion on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.9)
“iSchemaView uses the OWASP vulnerability risk process to identify and mitigate cybersecurity risks in conjunction with internal and external periodic assessments. iSchemaView maintains a compliance framework as annually certified by ISO 27001/27701 and conformance with UL-2900-1 through integrated development processes including: SBOM management, Penetration Testing, DAST and lifecycle monitoring.”

Validation studies (1)

Standalone

n=403 cases

endpoints: Sensitivity; Specificity; Time to notification

standards: EN ISO 14971:2019 (R2021), IEC 62304:2006 (R2015), IEC 62366:2015 (R2020), NEMA PS 3.1 - 3.20, UL 2900-1 (2017)

Reported performance (5 observations)

sensitivity0.921CI 95% CI: 0.880, 0.949
source quote (p.8)
“The primary endpoint analysis passed with Sensitivity 0.921 (95% CI: 0.880, 0.949) and Specificity 0.890 (95% CI: 0.832, 0.929) supporting the finding.”
specificity0.89CI 95% CI: 0.832, 0.929
source quote (p.8)
“The primary endpoint analysis passed with Sensitivity 0.921 (95% CI: 0.880, 0.949) and Specificity 0.890 (95% CI: 0.832, 0.929) supporting the finding.”
time_to_resultas written: “Time to notification”3.2CI min:1.92 min to 5.35min
source quote (p.8)
“A secondary endpoint analysis showed time to notification of 3.2 minutes, min:1.92 min to 5.35min.”
sensitivityas written: “Sensitivity (HGS cases)”0.874CI 95% CI:0.829-0.908
source quote (p.8)
“A sensitivity analysis with high grade stenosis (HGS) cases was included as a secondary analysis showing Se: 87.4% (95% CI:0.829-0.908) and Sp: 89.0% (95% CI: 0.832-0.929).”
specificityas written: “Specificity (HGS cases)”0.89CI 95% CI: 0.832-0.929
source quote (p.8)
“A sensitivity analysis with high grade stenosis (HGS) cases was included as a secondary analysis showing Se: 87.4% (95% CI:0.829-0.908) and Sp: 89.0% (95% CI: 0.832-0.929).”

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/K251151