AI Platform 2.2 (AIP002)

K260217

Exo Imaging · cleared 2026-02-24 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Exo AI Platform 2.2 (AIP 2.2) is a software as a medical device (SaMD)”
AlgorithmUltrasound image processing software implementing artificial intelligence, including non-adaptive machine learning algorithms trained with clinical data intended for non-invasive analysis of ultrasound data; Deep Convolutional Neural Networks for Segmentation, Landmark Detection and Classification
source quote (p.8)
“Ultrasound image processing software implementing artificial intelligence, including non-adaptive machine learning algorithms trained with clinical data intended for non-invasive analysis of ultrasound data Deep Convolutional Neural Networks for Segmentation, Landmark Detection and Classification”
Adaptive (vs locked)No
source quote (p.8)
“non-adaptive machine learning algorithms”
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act.”
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Retrospective clinical

n=184 patients

endpoints: overall agreement between the Quality AI and quality rated by the experienced sonographers

standards: ISO 14971, IEC 62304:2006/AC:2015, FDA's “Content of Premarket Submissions for Device Software Functions" Guidance for Industry and Food and Drug Administration Staff Document issued on June 14, 2023, FDA Guidance (June 2022) “Technical performance assessment of quantitative imaging in radiological device premarket submissions”

Reader study (MRMC)

n=186 scans

endpoints: percentage of clips rated as ACEP quality of 3 or above by expert readers that also received at least “Minimum criteria met for diagnosis" image quality by Clip Quality AI; percentage of scans that were considered as "Minimal criteria met for diagnosis" or "good" by Quality AI that were also deemed diagnostic by experts (ACEP score of 3 or higher)

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

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
3
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/K260217