Arterys MICA

K203744

Arterys Inc. · cleared 2022-03-14 · product code QIH · Radiology

FDA 510(k) summary for Arterys MICA (K203744)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
2
Cited predicates
1
Performance observations
2
Product code
QIH
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“Arterys MICA software is a medical diagnostic application that displays, processes, stores, and transfers DICOM and non-DICOM medical data.”
Algorithmdeep learning algorithms
source quote (p.7)
“Arterys MICA uses many deep learning algorithms to reduce many tedious, time-consuming manual steps, such as segmentation, landmark identification, etc.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.9)
“The software verification and validation activities were performed as per IEC 62304:2006/AC:2015- Medical device software – Software life cycle processes and ISO 14971:2019 Medical devices -- Application of risk management to medical devices, in addition to the FDA Guidance documents Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices and Content of Premarket Submission for Management of Cybersecurity in Medical Devices.”

Validation studies (2)

Bench

sample size not stated

endpoints: difference between calculated and expected T1 and T2 values were within predefined accuracy requirements (i.e., 30 ms and 4 ms for T1 and T2 values, respectively)

standards: IEC 62304:2006/AC:2015- Medical device software – Software life cycle processes, ISO 14971:2019 Medical devices -- Application of risk management to medical devices, FDA Guidance documents Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices, Content of Premarket Submission for Management of Cybersecurity in Medical Devices

Standalone

n=90 scans

endpoints: device performed as intended compared to ground-truth contours

Reported performance (2 observations)

accuracyas written: “T1 value accuracy”stated without valueCI within predefined accuracy requirements (i.e., 30 ms)
source quote (p.9)
“The results showed that the difference between calculated and expected T1 and T2 values were within predefined accuracy requirements (i.e., 30 ms and 4 ms for T1 and T2 values, respectively).”
accuracyas written: “T2 value accuracy”stated without valueCI within predefined accuracy requirements (i.e., 4 ms)
source quote (p.9)
“The results showed that the difference between calculated and expected T1 and T2 values were within predefined accuracy requirements (i.e., 30 ms and 4 ms for T1 and T2 values, respectively).”

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

1
recalls in product code, 24mo
4
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
1
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code QIH (PIE Medical Imaging B.V., initiated 2026-05-07): "User measurement value reported by diagnostic bioimaging software intended to measure/visualize cardiovascular structures may be larger (0.8% to 34.4%) than the actual anatomical d" Recalling firm is another firm in the same product code.

    first seen 2026-08-26 · recall res_event_number:98930

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 2026-08-26.

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.

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Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K203744