UltraSight AI Guidance

K223347

UltraSight Inc. · cleared 2023-07-24 · product code QJU · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“UltraSight AI Guidance is a mobile application based on machine learning that uses artificial intelligence (AI) to provide dynamic real-time guidance on the position and orientation of the transducer to help non-expert users acquire diagnostic-quality tomographic views of the heart.”
Algorithmmachine learning, artificial intelligence, deep learning-based algorithm
source quote (p.4)
“UltraSight AI Guidance is a mobile application based on machine learning that uses artificial intelligence (AI) to provide dynamic real-time guidance on the position and orientation of the transducer to help non-expert users acquire diagnostic-quality tomographic views of the heart.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedNo

Validation studies (6)

Bench

sample size not stated

endpoints: All user tasks associated with the device were evaluated and critical tasks were identified for usability evaluation, where if performed incorrectly or not performed at all would or could cause serious harm. All participants successfully completed the testing sessions and performed the critical task identified in the study without any use errors, close calls, or other issues.

standards: FDA Guidance Document, "Applying Human Factors and Usability Engineering to Medical Devices" (2016)

Standalone

n=312 images

endpoints: classification performance between “diagnosable” and “non diagnosable" clips of each view.

Standalone

n=2,300,000 images

endpoints: classification performance for the classification tasks of "Hold position" vs. "Navigate" and "Hold position" vs. "No heart".

Standalone

n=2,300,000 images

endpoints: frame level accuracy of each guidance cue prediction.

Reader study (MRMC)

n=61 patients · 1 site(s)

endpoints: qualitative visual assessment of left ventricular (LV) size, LV function, right ventricular (RV) size, and the presence of nontrivial pericardial effusion; qualitative assessment of RV function; left atrium size; structural assessment of the aortic, mitral, and tricuspid valves; qualitative assessment of IVC size

Reader study (MRMC)

n=240 patients

endpoints: qualitative visual assessment of left ventricular (LV) size, LV function, right ventricular (RV) size, and the presence of nontrivial pericardial effusion; qualitative assessment of RV function; left atrium size; structural assessment of the aortic, mitral, and tricuspid valves; qualitative assessment of IVC size

Reported performance (4 observations)

aurocas written: “auc”0.86CI [0.85, 0.87]
source quote (p.11)
“The mean AUC was 0.86 with 95% CI [0.85, 0.87] showing good classification performance, relative to the success criteria of AUC > 0.8.”
ppvas written: “PPV”0.93CI [0.92, 0.94]
source quote (p.11)
“The mean PPV was 0.93 with 95% CI [0.92, 0.94] relative to the success criteria of PPV > 0.75, showing good classification performance.”
aurocas written: “AUC (View Detection)”0.988CI [0.985, 0.990]
source quote (p.11)
“The mean AUC was 0.988 with 95% CI [0.985, 0.990] showing good classification performance, relative to the success criteria of AUC > 0.8.”
aurocas written: “AUC (Probe Guidance)”0.821CI [0.813, 0.827]
source quote (p.11)
“The mean AUC was 0.821 with 95% CI [0.813, 0.827] showing good classification performance, relative to the success criteria of AUC > 0.8.”

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
1
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K251416 (decision 2025-12-17) from Ultrasight , Ltd. for a matching device line ("UltraSight Guidance") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K251416

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/K223347