Diagnocat
K252934DGNCT, LLC · cleared 2026-01-15 · product code MYN · Radiology
Premarket evidence — what FDA accepted
Device typesamd
source quote (p.5)
“Diagnocat Software is a computer-assisted detection (CADe) software-only device intended to concurrently aid in the detection of periapical radiolucency areas.”
Algorithmdeep learning algorithms and artificial intelligence (AI)
source quote (p.5)
“The device is designed to facilitate the analysis and interpretation of previously obtained dental Cone Beam Computed Tomography (CBCT) scans, specifically in cases where a periapical radiolucency condition is suspected, leveraging deep learning algorithms and artificial intelligence (AI).”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.8)
“Software verification and validation testing, and cybersecurity testing per FDA guidance, “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions”, were conducted to ensure that the software meets its specifications and performs as intended.”
Validation studies (3)
Standalone
n=100 images
endpoints: Teeth Segmentation Mean DSC; Periapical Radiolucency Segmentation Mean DSC
Standalone
n=285 images
endpoints: Sensitivity; Specificity
Reader study (MRMC)
sample size not stated
endpoints: AUC
Reported performance (8 observations)
sensitivity0.854
source quote (p.9)
“Sensitivity 0.854”
specificity0.991
source quote (p.9)
“Specificity 0.991”
aurocas written: “auc”0.9213
source quote (p.9)
“Aided 0.9213”
diceas written: “Teeth Segmentation Mean DSC (Cohort 1)”0.955
source quote (p.8)
“Teeth Segmentation Cohort 1 0.955”
diceas written: “Teeth Segmentation Mean DSC (Cohort 2)”0.947
source quote (p.8)
“Teeth Segmentation Cohort 2 0.947”
diceas written: “Periapical Radiolucency Segmentation Mean DSC (Cohort 2)”0.804
source quote (p.8)
“Periapical Radiolucency Segmentation Cohort 2 0.804”
aurocas written: “Unaided AUC”0.894
source quote (p.9)
“Unaided 0.8940”
aurocas written: “AUC Difference”0.027
source quote (p.9)
“AUC Difference +0.027”
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
-100%
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). 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).