LVivo Software Application

K200232

DiA Imaging Analysis Ltd · cleared 2020-06-23 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“Automated Radiological Image Processing Software- classified as Class 2 QIH”
AlgorithmImage segmentation for border detection. For the RV- Deep Learning Technology, the algorithm combines image processing and Deep Learning Neural Network (NN) for RV analysis, identifying endocardial boundaries and tricuspid valve location by NN model, enhanced and tracked using image processing. For bladder, it uses machine learning and active contour for segmenting bladder contours.
source quote (p.7)
“Image segmentation for border detection For the RV- Deep Learning Technology. The Algorithm combines image processing and Deep Learning Neural Network (NN) for the RV analysis. The endocardial boundaries and the location of the anulus of the tricuspid valve are identified by the NN model. These boundaries are further enhanced and tracked using image processing methods that are already established in other approved modules of the LVivo Platform. This application automatically measures bladder volume by segmenting bladder contours from sagittal and transverse ultrasound views using a combination of machine learning and active contour”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Retrospective clinical

sample size not stated · 1 site(s)

endpoints: compare LVivoRV measurement of FAC to manual FAC measurement; compare LVivoRV measurements to the manual measurements of EDA, ESA, TAPSE, S' and FREE WALL STRAIN; compare RV function by visual assessment to the categorized result from FAC, TAPSE, S' and STRAIN; evaluate inter and intra observer variability

standards: ASE guidelines

Retrospective clinical

n=113 patients · 1 site(s)

endpoints: compare LVivo Bladder measurement of bladder volume to bladder volume by manual tracing; evaluate whether the residual volume is lower or higher than this 200ml threshold

Reported performance (6 observations)

sensitivity100
source quote (p.12)
“high sensitivity and specificity (100 and 80 respectively)”
specificity80
source quote (p.12)
“high sensitivity and specificity (100 and 80 respectively)”
agreement_kappaas written: “Inter-observer reliability (EDA)”0.85
source quote (p.10)
“Inter-observer reliability between sonographers for EDA, ESA and FAC was 0.85, 0.9 and 0.77 respectively (p<0.0001).”
agreement_kappaas written: “Inter-observer reliability (ESA)”0.9
source quote (p.10)
“Inter-observer reliability between sonographers for EDA, ESA and FAC was 0.85, 0.9 and 0.77 respectively (p<0.0001).”
agreement_kappaas written: “Inter-observer reliability (FAC)”0.77
source quote (p.10)
“Inter-observer reliability between sonographers for EDA, ESA and FAC was 0.85, 0.9 and 0.77 respectively (p<0.0001).”
agreement_kappaas written: “Kappa (Bladder)”0.84
source quote (p.12)
“with excellent Kappa of 0.84”

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
4
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243862 (decision 2025-03-17) from DiA Imaging Analysis Ltd. for a matching device line ("LVivo Software Application") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243862

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243235 (decision 2025-03-03) from DiA Imaging Analysis Ltd. for a matching device line ("LVivo Software Application") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243235

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K240553 (decision 2024-10-04) from DiA Imaging Analysis Ltd. for a matching device line ("LVivo Software Application") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K240553

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K210053 (decision 2021-02-05) from DiA Imaging Analysis Ltd for a matching device line ("LVivo Software Application") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K210053

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/K200232