DTX Studio Assist

K252086

Nobel Biocare C/O Medicim NV · cleared 2025-11-17 · product code MYN · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“DTX Studio Assist is a Software Development Kit (SDK) designed to integrate with medical device software that displays two-dimensional dental radiographs.”

AlgorithmSupervised machine learning algorithms

source quote (p.6)

“DTX Studio Assist and primary predicate device (DTX Studio Clinic 4.0 - K231898) share the following characteristics: - Supervised machine learning algorithms”

Adaptive (vs locked)FDA source did not state this

PCCPNo

Cybersecurity addressedNo

Validation studies (3)

Standalone

n=1,530 images

endpoints: identifying and segmenting eight types of dental restorations in intraoral radiographs (IORs)

standards: ISO 13485:2016, IEC 62304:2006/Amd 1 :2015, ISO 14971 :2019

Standalone

n=274 images · 30 site(s)

endpoints: identifying anatomical landmarks and calculating mesial and distal ABL measurements in intraoral radiographs (IORs)

standards: ISO 13485:2016, IEC 62304:2006/Amd 1 :2015, ISO 14971 :2019

Standalone

n=220 images

endpoints: identifying and segmenting key anatomical structures in intraoral radiograph images (Enamel, Dentine, Pulp , Jaw bone, artificial)

standards: ISO 13485:2016, IEC 62304:2006/Amd 1 :2015, ISO 14971 :2019

Reported performance (5 observations)

sensitivity0.888

source quote (p.7)

“The algorithm achieved an overall sensitivity of 88.8% and specificity of 96.6%, with segmentation accuracy confirmed by a mean Dice score of 86.5%, closely matching inter-expert agreement”

specificity0.966

source quote (p.7)

“The algorithm achieved an overall sensitivity of 88.8% and specificity of 96.6%, with segmentation accuracy confirmed by a mean Dice score of 86.5%, closely matching inter-expert agreement”

sensitivityas written: “Alveolar Bone Level (ABL) Measurement Algorithm Sensitivity”0.932

source quote (p.7)

“The algorithm achieved a sensitivity of 93.2% and specificity of 88.6% for ABL line segment matching.”

specificityas written: “Alveolar Bone Level (ABL) Measurement Algorithm Specificity”0.886

source quote (p.7)

“The algorithm achieved a sensitivity of 93.2% and specificity of 88.6% for ABL line segment matching.”

diceas written: “Restoration Detection Algorithm Mean Dice Score”0.865

source quote (p.7)

“The algorithm achieved an overall sensitivity of 88.8% and specificity of 96.6%, with segmentation accuracy confirmed by a mean Dice score of 86.5%, closely matching inter-expert agreement”

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

recalls in product code, 24mo

MAUDE reports in code, 12mo

-100%

vs code's own 3-yr baseline

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).