LVivo Software Application

K243862

DiA Imaging Analysis Ltd. · cleared 2025-03-17 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The LVivo platform is a software system for automated analysis of ultrasound examinations. Automated analysis of echocardiographic examinations is done using DICOM movies.”
Algorithmmachine learning algorithm
source quote (p.8)
“Yes. Based on the same machine learning algorithm, multiple rocessing steps were added and the calculated features revised”
Adaptive (vs locked)No
source quote (p.8)
“Yes. Based on the same machine learning algorithm, multiple rocessing steps were added and the calculated features revised”
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.8)
“Risk control measures are identified by the threat models and incorporated into the risk analysis process and SW design. The verification and validation testing including 3rd party libraries vulnerability assessment of the SW (SBOM) to ensure that cybersecurity related design requirement are implemented successfully. The company has defined a Cybersecurity plan for ongoing cybersecurity maintenance.”

Validation studies (2)

Retrospective clinical

n=170 cases · 3 site(s)

endpoints: Specificity; Sensitivity; Accuracy; Pearson correlation coefficient; ICC

standards: IEC 62304:2006+A1:2015 CSV, IEC 62366-1 Medical devices - Part 1: Application of usability engineering to medical devices, 2015 + AMD 2020, IEC/TR80002-1:2009, Medical device software - Part 1: Guidance on the application of ISO 14971 to medical device software systems, software, and services information

Retrospective clinical

n=101 patients · 1 site(s)

endpoints: Specificity; Sensitivity; Accuracy; Pearson correlation

Reported performance (7 observations)

sensitivity0.82
source quote (p.9)
“The Specificity and sensitivity of WMSI were 79% and 82% respectively and the accuracy was found to be 82%.”
specificity0.79
source quote (p.9)
“The Specificity and sensitivity of WMSI were 79% and 82% respectively and the accuracy was found to be 82%.”
accuracyas written: “Accuracy (Study 1)”0.82
source quote (p.9)
“The Specificity and sensitivity of WMSI were 79% and 82% respectively and the accuracy was found to be 82%.”
agreement_kappaas written: “ICC (GT vs LVivo SWM) (Study 1)”0.85
source quote (p.9)
“ICC calculated between GT and LVivo SWM, and between each pair of experts.”
specificityas written: “Specificity (Study 2)”0.82
source quote (p.10)
“Specificity 82%”
sensitivityas written: “Sensitivity (Study 2)”0.82
source quote (p.10)
“Sensitivity 82%”
accuracyas written: “Accuracy (Study 2)”0.82
source quote (p.10)
“Accuracy 82%”

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/K243862