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510(k) Data Aggregation
(271 days)
Smile Dx® is a computer-assisted detection (CADe) software designed to aid dentists in the review of digital files of bitewing and periapical radiographs of permanent teeth. It is intended to aid in the detection and segmentation of suspected dental findings which include: caries, periapical radiolucencies (PARL), restorations, and dental anatomy.
Smile Dx® is also intended to aid dentists in the measurement (in millimeter and percentage measurements) of mesial and distal bone levels associated with each tooth.
The device is not intended as a replacement for a complete dentist's review or their clinical judgment that takes into account other relevant information from the image, patient history, and actual in vivo clinical assessment.
Smile Dx® supports both digital and phosphor sensors.
Smile Dx® is a computer assisted detection (CADe) device indicated for use by licensed dentists as an aid in their assessment of bitewing and periapical radiographs of secondary dentition in adult patients. Smile Dx® utilizes machine learning to produce annotations for the following findings:
- Caries
- Periapical radiolucencies
- Bone level measurements (mesial and distal)
- Normal anatomy (enamel, dentin, pulp, and bone)
- Restorations
The provided FDA 510(k) Clearance Letter for Smile Dx® outlines the device's acceptance criteria and the studies conducted to prove it meets those criteria.
Acceptance Criteria and Device Performance
The acceptance criteria are implicitly defined by the performance metrics reported in the "Performance Testing" section. The device's performance is reported in terms of various metrics for both standalone and human-in-the-loop (MRMC) evaluations.
Here's a table summarizing the reported device performance against the implied acceptance criteria:
Table 1: Acceptance Criteria and Reported Device Performance
| Feature/Metric | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| Standalone Testing: | ||
| Caries Detection | High Dice, Sensitivity | Dice: 0.74 [0.72 0.76] |
| Sensitivity (overall): 88.3% [83.5%, 92.6%] | ||
| Periapical Radiolucency (PARL) Detection | High Dice, Sensitivity | Dice: 0.77 [0.74, 0.80] |
| Sensitivity: 86.1% [80.2%, 91.9%] | ||
| Bone Level Detection (Bitewing) | High Sensitivity, Specificity, Low MAE | Sensitivity: 95.5% [94.3%, 96.7%] |
| Specificity: 94.0% [91.1%, 96.6%] | ||
| MAE: 0.30 mm [0.29mm, 0.32mm] | ||
| Bone Level Detection (Periapical) | High Sensitivity, Specificity, Low MAE (percentage) | Sensitivity: 87.3% [85.4%, 89.2%] |
| Specificity: 92.1% [89.9%, 94.1%] | ||
| MAE: 2.6% [2.4%, 2.8%] | ||
| Normal Anatomy Detection | High Dice, Sensitivity, Specificity | Dice: 0.84 [0.83, 0.85] |
| Sensitivity (Pixel-level): 86.1% [85.4%, 86.8%] | ||
| Sensitivity (Contour-level): 95.2% [94.5%, 96%] | ||
| Specificity (Contour-level): 93.5% [91.6%, 95.8%] | ||
| Restorations Detection | High Dice, Sensitivity, Specificity | Dice: 0.87 [0.85, 0.90] |
| Sensitivity (Pixel-level): 83.1% [80.3%, 86.4%] | ||
| Sensitivity (Contour-level): 90.9% [88.2%, 93.9%] | ||
| Specificity (Contour-level): 99.6% [99.3%, 99.8%] | ||
| MRMC Clinical Evaluation - Reader Improvement: | ||
| Caries Detection (wAFROC Δθ) | Statistically significant improvement | +0.127 [0.081, 0.172] (p |
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(103 days)
Videa Perio Assist is a radiological semi-automated image processing software device intended to aid dental professionals in the measurements and visualization of mesial and distal bone levels associated with each tooth from bitewing and periapical radiographs. Measurements are made available as linear distances or relative percentages.
It should not be used in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. The system is to be used by trained professionals including, but not limited to, dentists and dental hygienists.
Videa Perio Assist (VPA) software is a cloud-based AI-powered medical device for the automatic measurement of tooth interproximal alveolar bone level in dental radiographs. The device itself is available as an API (Application Programming Interface) behind a firewalled network. The device returns 1) a series of points with connecting lines measuring the mesial and distal alveolar bone levels associated with each tooth 2) this distance expressed in millimeters and/or as a percentage of the root length.
Videa Perio Assist is accessed by the trained professional through their image viewer. From within the image viewer the user can upload a radiograph to Videa Perio Assist and then review the results. The device outputs a line to identify these points which calculate the interproximal bone level.
The device output will show all applicable measurements from one radiograph regardless of the number of teeth present. If no teeth are present the device outputs a clear indication that there are no identifiable teeth to calculate the interproximal bone level.
The intended users of Videa Perio Assist are trained professionals such as dentists and dental hygienists.
The intended patients of Videa Perio Assist are patients 12 years and above with permanent dentition undergoing routine dental visits or suspected of having interproximal bone level concerns. Videa Perio Assist may only be used with patients with permanent dentition present in the radiograph.
Here's a breakdown of the acceptance criteria and the study proving the device's performance, based on the provided FDA 510(k) summary for Videa Perio Assist:
1. Table of Acceptance Criteria & Reported Device Performance
Videa Perio Assist underwent two primary types of testing: Bench Testing (focused on algorithm precision/recall) and Clinical Testing (focused on algorithm sensitivity, specificity, and accuracy for clinical measurements).
Bench Testing Acceptance Criteria & Performance (Per Tooth Landmark Detection)
| Metric | Acceptance Criteria (Overall) | VPA Performance (Bitewing) | VPA Performance (Periapical - Overall) | VPA Performance (Periapical - CEJ-ABL subgroup) |
|---|---|---|---|---|
| Recall | > 82% | 94.4% | 91.9% | N/A (Not reported specifically for this subgroup for recall) |
| Precision | > 82% | 84.3% | N/A (Not reported overall for periapical) | 79.1% (Did not meet criteria for this subgroup) |
Note: The document notes that for the periapical CEJ-ABL subgroup, precision was 79.1%, meaning it did not meet the acceptance criteria of >82% precision for this specific subgroup, however, this was attributed to difficulty in estimating obscured points on overlapping teeth.
Clinical Testing Acceptance Criteria & Performance (Per Interproximal Bone Level Measurement)
| Metric | Acceptance Criteria (Overall) | VPA Performance (Bitewing) | VPA Performance (Periapical - All) | VPA Performance (Periapical - CEJ->ABL subgroup) | VPA Performance (Periapical - CEJ->RT subgroup) | VPA Performance (Periapical - ABL->RT subgroup) |
|---|---|---|---|---|---|---|
| Sensitivity | > 82% | 92.8% (Met) | 88.3% (Met) | Met | Met | Met |
| Specificity | > 81% | 89.4% (Met) | 87.0% (Met) | Did not meet (for this subgroup) | Met | Met |
| Mean Absolute Error |
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(273 days)
The Overjet Caries Assist (OCA) is a radiological, automated, concurrent read, computer-assisted detection software intended to aid in the detection and segmentation of caries on bitewing radiographs. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of being carious. The device is not intended as a replacement for a complete dentist's review or that takes into account other relevant information from the image, patient history, and actual in vivo clinical assessment.
Overjet Caries Assist (OCA) is a radiological automated concurrent read computer-assisted detection (CAD) software intended to aid in the detection and segmentation of caries on bitewing radiographs. The device provides additional information for the clinician to use in their diagnosis of a tooth surface suspected of being carious. The device is not intended as a replacement for a complete clinician's review or their clinical judgment that takes into account other relevant information from the image or patient history.
OCA is a software-only device which operates in three layers - a Network Layer, a Presentation Layer, and a Decision Layer (as shown in the data flow diagram below). Images are pulled in from a clinic/dental office, and the Machine Learning model creates predictions in the Decision Layer and results are pushed to the dashboard, which are in the Presentation Layer.
The Machine Learning System within the Decision Layer processes bitewing radiographs and annotates suspected carious lesions. It is comprised of four modules:
- Image Classifier The model evaluates the incoming radiograph and predicts the ● image type between Bitewing and Periapical Radiograph. This classification is used to support the data flow of the incoming radiograph. As part of the classification of the image type any non-radiographs are classified as "junk" and not processed. These include patient charting information, or other non-bitewing or periapical radiographs. OCA shares classifier and Tooth Number modules with the Overjet Dental Assist product cleared under K210187.
- . Tooth Number Assignment module - This module analyzes the processed image and determines what tooth numbers are present and provides a pixel wise segmentation mask for each tooth number.
- Caries module - This module outputs a pixel wise segmentation mask of all carious lesions using an ensemble of 3 U-Net based models. The shape and location of every carious lesion is contained in this mask as the carious lesions' predictions.
- Post Processing The overlap of tooth masks from the Tooth Number . Assignment Module and carious lesions from the Caries Module is used to assign specific carious lesions to a specific tooth. The Image Post Processor module annotates the original radiograph with the carious lesions' predictions.
Acceptance Criteria and Device Performance for Overjet Caries Assist
The Overjet Caries Assist (OCA) is a radiological, automated, concurrent read, computer-assisted detection software intended to aid in the detection and segmentation of caries on bitewing radiographs. The device's performance was evaluated through standalone testing of the AI algorithm and a clinical reader improvement study.
1. Table of Acceptance Criteria and Reported Device Performance
| Measure | Acceptance Criteria (Predicate Device Performance) | Reported Device Performance (Overjet Caries Assist) |
|---|---|---|
| Reader Improvement Study | ||
| Increase in dentist's sensitivity with AI assistance | Approximately 20% increase in sensitivity for the predicate device. For OCA, a greater than 15% increase in dentist's sensitivity was established as acceptance criteria. | Overall reader sensitivity improved from 57.9% to 76.2% (an increase of 18.3 percentage points, satisfying the >15% criterion). |
- Primary caries: 60.5% to 79.4% (18.9 pp improvement).
- Secondary caries: 49.8% to 63.0% (13.2 pp improvement). |
| Specificity with AI assistance | Not explicitly defined as an improvement criterion for the predicate, but overall specificity is a key measure. | Overall reader specificity decreased slightly from 99.3% to 98.4% (a decrease of less than 1%), deemed acceptable by the applicant as the benefit in sensitivity outweighs this slight decrease. |
| AFROC Score (Assisted) | The predicate did not explicitly state an AFROC criterion, but improving diagnostic accuracy is implicit. | AUC increased from 0.593 (unassisted) to 0.649 (assisted), for an increase of 0.057 (statistically significant, p
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