aprevo® Digital Segmentation

K231955

Carlsmed, Inc. · cleared 2023-11-03 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“aprevo® Digital Segmentation software is intended to be used by trained, medically knowledgeable design personnel to perform digital image segmentation of the spine, primarily lumbar anatomy. The device inputs DICOM images and outputs a 3-D model of the spine.”
AlgorithmAI-based algorithm
source quote (p.4)
“Upon removal of soft tissue and identification of spine structure, the software will utilize an AI-based algorithm to segment the structure and render a 3D model as an output.”
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)

Bench

sample size not stated

endpoints: IOU (intersection over union) score for segmentation; accuracy of vertebral body labeling; sensitivity; specificity

standards: FDA guidance document Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.

Reported performance (4 observations)

sensitivity0.8CI >
source quote (p.5)
“with sensitivity and specificity exceeding 80% each.”
specificity0.8CI >
source quote (p.5)
“with sensitivity and specificity exceeding 80% each.”
iouas written: “IOU score”0.8CI >
source quote (p.5)
“The software performance was evaluated using an IOU (intersection over union) score for segmentation which exceeded the acceptance criteria of 80%.”
accuracyas written: “Accuracy”0.9CI >
source quote (p.5)
“It was also evaluated for accuracy of vertebral body labeling which exceeded the acceptance criteria of 90% overall, with sensitivity and specificity exceeding 80% each.”

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/K231955