Adravision Perio

K232440

Adra Corporation · cleared 2023-12-05 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“Adravision Perio is a Software as a Medical Device (SaMD) intended to aid dentists in the measurement of mesial and distal bone levels associated with each tooth on bitewing and periapical dental radiographs of permanent teeth in patients 22 years of age or older.”
Algorithmmachine learning technologies
source quote (p.6)
“Both devices utilize machine learning technologies to measure interproximal bone levels in dental radiographs and allow users to visualize the radiographs with annotations, add their own annotations and use the information as part of their diagnostic decision.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

n=340 images

endpoints: Precision; Recall

standards: FDA's Guidance for Industry and FDA Staff, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices"

Bench

n=78 images

endpoints: Sensitivity; Specificity; Mean Absolute Error

standards: FDA's Guidance for Industry and FDA Staff, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices"

Reported performance (6 observations)

ppvas written: “Precision (Bitewing)”91
source quote (p.8)
“Precision 91.0%”
ppvas written: “Precision (Periapical)”84.8
source quote (p.8)
“Precision 84.8%”
sensitivityas written: “Recall (Bitewing)”94
source quote (p.8)
“Recall 94.0%”
sensitivityas written: “Recall (Periapical)”89.3
source quote (p.8)
“Recall 89.3%”
accuracyas written: “Overall tooth number classification accuracy (OKS study)”91.8
source quote (p.8)
“Adravision Perio also obtained an overall tooth number classification accuracy of 91.8% in the OKS study”
accuracyas written: “Overall tooth number classification accuracy (Length Assessment)”93.2
source quote (p.8)
“and 93.2% in the Length Assessment”

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/K232440