DV. Target

K202928

Deepvoxel INC · cleared 2021-04-02 · product code QKB · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“DV.Target is a software application that enables the routing of DICOM-compliant data (CT Images) to automatic image processing workflows, using machine learning-based algorithms to automatically delineate organs-at-risk (OARs).”
Algorithmmachine learning-based algorithms, deep learning processing
source quote (p.3)
“DV.Target is a software application that enables the routing of DICOM-compliant data (CT Images) to automatic image processing workflows, using machine learning-based algorithms to automatically delineate organs-at-risk (OARs). DV.Target should be installed on a specialized server supporting deep learning processing. Algorithm: Machine learning-based”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (3)

Retrospective clinical

sample size not stated

endpoints: auto-contouring accuracy; Dice-Sørensen coefficients (DICE score)

Retrospective clinical

sample size not stated · 1 site(s)

endpoints: auto-contouring accuracy; Dice-Sørensen coefficients (DICE score)

Retrospective clinical

sample size not stated

endpoints: auto-contouring accuracy; Dice-Sørensen coefficients (DICE score)

Reported performance (1 observation)

diceas written: “Dice-Sørensen coefficients (DICE score)”stated without value
source quote (p.10)
“The Dice-Sørensen coefficients (DICE score) were calculated and used to evaluate contouring accuracies by comparing device-generated contours with ground truth contours. The confidence interval of performance differences between the proposed and the predicate/reference devices are within the non-inferiority margin for all compared OARs.”

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
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/K202928