Rapid ASPECTS (v3)

K232156

iSchemaView, Inc. · cleared 2024-01-19 · product code POK · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The Rapid platform is Software as a Medical Device (SaMD), which provides for the visualization and study of changes in tissue and vasculature using digital images captured by diagnostic imaging systems including CT (Computed Tomography), CTA (CT Angiography), MRI (Magnetic Resonance Imaging) and MRA (MR Angiography) as an aid to physician diagnosis.”
Algorithmmachine learning implementation; random forest machine learning technique; artificial intelligence algorithms
source quote (p.8)
“Rapid ASPECTS is a machine learning implementation. Rapid ASPECTS provides an automatic ASPECT score based on the case input file for the physician. The score includes which ASPECT regions are identified based on regional imaging features derived from non-contrast computed tomography (NCCT) brain image data based on the random forest machine learning technique.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.8)
“Rapid has been designed to meet cybersecurity requirements using design Vulnerability Assessments, SBOM's, and PEN Testing.”

Validation studies (2)

Standalone

n=88 cases

endpoints: percent agreement at ASPECTS region level; percent agreement at scan level

standards: ISO 14971:2019, IEC 62304:2015, IEC 62366:2015, NEMA PS 3.1 - 3.20

Reader study (MRMC)

n=102 cases

endpoints: reader scoring alignment with reference standard

standards: ISO 14971:2019, IEC 62304:2015, IEC 62366:2015, NEMA PS 3.1 - 3.20

Reported performance (3 observations)

agreement_kappaas written: “Percent agreement to reference (standalone)”82.8
source quote (p.9)
“The percent agreement of Rapid ASPECTS to the reference at the ASPECTS region level and at the scan level is 82.8%.”
agreement_kappaas written: “Percent agreement with assistance (excluding expert)”84
source quote (p.9)
“agreement increases from 82% without assistance to 84% with assistance excluding the expert”
agreement_kappaas written: “Average percent agreement with assistance (all readers)”83.3
source quote (p.9)
“the average agreement increases from 80.4% without assistance to 83.3% with assistance.”

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/K232156