Bladder AI (AIBV01)

K230497

Exo Inc · cleared 2023-06-22 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
Bladder AI is a standalone software as a medical device (SaMD) that helps qualified users with image-based assessment of bladder ultrasound images in patients aged 2 or older.
AlgorithmML-based semi-automatic landmark placements; Image segmentation for border detection
source quote (p.5)
Key features of the software are ML-based semi-automatic landmark placements
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=122 patients

endpoints: Intraclass correlation coefficient (ICC); Bladder Volume error

standards: IEC 62304:2006/AC:2015 - Medical device software – Software life cycle processes, FDA Guidance (May 2005), “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices”, FDA Guidance (June 2022) “Technical performance assessment of quantitative imaging in radiological device premarket submissions"

Reported performance (2 observations)

agreement_kappaas written: “Intraclass correlation coefficient (ICC) - Dual-View0.98
source quote (p.8)
Bladder volume, Dual-View¹ 0.98
agreement_kappaas written: “Intraclass correlation coefficient (ICC) - Single-View0.97
source quote (p.8)
Bladder volume, Single-View² 0.97

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/K230497