(260 days)
P980025
Not Found
Yes
The document explicitly mentions "overjet AI algorithm" multiple times in the "Mentions AI, DNN, or ML" and "Summary of Performance Studies" sections.
No
The device is described as radiological automated concurrent-read computer-assisted detection software intended to aid in the detection of interproximal calculus deposits on radiographs, providing information for diagnosis, not for treatment.
Yes
This device is intended to aid in the detection of interproximal calculus deposits, providing additional information for dentists to use in their diagnosis, which falls under the definition of a diagnostic device.
Yes
The device description explicitly states it is a "module within the Overjet Platform" and "software automatically detects interproximal calculus". The entire summary focuses on the performance and evaluation of the software algorithm and its impact on reader performance, with no mention of associated hardware components being part of the device itself.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- Device Function: The Overjet Calculus Assist (OCalA) software analyzes radiological images (bitewing and periapical radiographs). It does not analyze biological samples from the patient's body.
- Intended Use: The intended use is to aid in the detection of calculus deposits on radiographs, which are images, not biological specimens.
- Input: The input is imaging data, not biological sample data.
Therefore, because the device operates on medical images rather than biological samples, it falls under the category of a medical device, specifically a radiological computer-assisted detection software, and not an In Vitro Diagnostic.
No
The letter does not explicitly state that the FDA has reviewed, approved, or cleared a PCCP for this specific device.
Intended Use / Indications for Use
Overjet Calculus Assist (OCalA) is a radiological automated concurrent-read computer-assisted detection software intended to aid in the detection of interproximal calculus deposits on both bitewing and periapical radiographs. The Overjet Calculus Assist surrounds suspected calculus deposits with a bounding box. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of containing calculus deposits. 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 or patient history. The system is to be used by professionally trained and licensed dentists.
Product codes
MYN
Device Description
Overjet Calculus Assist is a module within the Overjet Platform. The Overjet Calculus Assist (OCalA) software automatically detects interproximal calculus on bitewing and periapical radiographs. It is intended to aid dentists in the detection of calculus. 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 professionally trained and licensed dentists.
Mentions image processing
The decision layer processes the image to ensure it is the correct data type, and then annotates it via the algorithm.
Mentions AI, DNN, or ML
Standalone performance of the overjet AI algorithm
Input Imaging Modality
bitewing and periapical radiographs
Anatomical Site
Tooth surface
Indicated Patient Age Range
18 years of age or older.
Intended User / Care Setting
professionally trained and licensed dentists.
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Standalone performance of the overjet AI algorithm for 296 bitewing radiographs and 322 periapical radiographs.
A total of 6,121 surfaces were available on bitewing radiographs, and 3,595 surfaces were available on periapical radiographs.
Overjet evaluated the Overjet Calculus Assist in a multi-reader, fully crossed reader improvement study. 14 US licensed dentists were asked to evaluate 292 bitewing radiographs (85 with calculus and 211 without calculus) and 322 periapical radiographs (89 with calculus and 233 without calculus). Ground truth was established by the consensus labels of three US-licensed dentists, and non-consensus labels were adjudicated by an oral radiologist.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Performance testing included standalone testing and a clinical reader evaluation. All testing demonstrated that Overjet Calculus Assist software met prespecified requirements.
Standalone Testing
- Sample Size: 296 bitewing radiographs and 322 periapical radiographs. A total of 6,121 surfaces were available on bitewing radiographs, and 3,595 surfaces were available on periapical radiographs.
- Overall standalone sensitivity: 74.1% (66.2%, 82.0%) for bitewing radiographs, and 72.9% (65.3%, 80.5%) for periapical radiographs.
- Overall standalone specificity: 99.4% (99.1%, 99.6%) for bitewing radiographs, and 99.6% (99.3%, 99.8%) for periapical radiographs.
- Subgroup Analyses: performed for age, gender, sensor, and clinical site. Results were generally similar across all subgroups, and any observed differences were not associated with increased risks.
- AFROC AUC: Bitewing 0.859 (0.823, 0.894), Periapical 0.867 (0.828, 0.903).
Clinical Evaluation - Reader Improvement
- Study Type: multi-reader, fully crossed reader improvement study.
- Sample Size: 14 US licensed dentists evaluated 292 bitewing radiographs (85 with calculus and 211 without calculus) and 322 periapical radiographs (89 with calculus and 233 without calculus).
- Ground Truth: Established by the consensus labels of three US-licensed dentists, and non-consensus labels were adjudicated by an oral radiologist.
- Key Results:
- Unassisted vs. Assisted Sensitivity:
- Bitewing radiographs: improved from 74.9% (68.3%, 80.2%) to 84.0% (78.8%, 88.2%).
- Periapical radiographs: improved from 74.7% (69.9%. 79.0%) to 84.4% (78.8%, 89.2%).
- Unassisted vs. Assisted Specificity:
- Bitewing radiographs: decreased slightly from 98.8% (98.7%, 99.0%) to 98.6% (98.4%, 98.9%).
- Periapical radiographs: decreased slightly from 98.1% (97.8%, 98.4%) to 98.0% (97.7%, 98.4%).
- AFROC AUC (Reader Avg):
- Bitewing: Unassisted 0.840 (0.800, 0.880), Assisted 0.878 (0.844, 0.913). p-value on AUC Difference 0.0055.
- Periapical: Unassisted 0.846 (0.808, 0.884), Assisted 0.900 (0.870, 0.929). p-value on AUC Difference 1.47e-05.
- Subgroup Analyses: performed for age, gender, sensor, clinical site, and reader experience. Reader improvement was observed in nearly all analyses. No observed differences were associated with increased risks.
- Unassisted vs. Assisted Sensitivity:
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Standalone Performance:
- Sensitivity: Overall 74.1% (66.2%, 82.0%) for bitewing radiographs, and 72.9% (65.3%, 80.5%) for periapical radiographs.
- Specificity: Overall 99.4% (99.1%, 99.6%) for bitewing radiographs, and 99.6% (99.3%, 99.8%) for periapical radiographs.
- AUC: Bitewing 0.859, Periapical 0.867.
Clinical Evaluation - Reader Improvement (reader performance):
- Sensitivity:
- Bitewing radiographs: Unassisted 74.9% (68.3%, 80.2%), Assisted 84.0% (78.8%, 88.2%).
- Periapical radiographs: Unassisted 74.7% (69.9%. 79.0%), Assisted 84.4% (78.8%, 89.2%).
- Specificity:
- Bitewing radiographs: Unassisted 98.8% (98.7%, 99.0%), Assisted 98.6% (98.4%, 98.9%).
- Periapical radiographs: Unassisted 98.1% (97.8%, 98.4%), Assisted 98.0% (97.7%, 98.4%).
- AUC of AFROC (Reader Avg):
- Bitewing: Unassisted 0.840, Assisted 0.878.
- Periapical: Unassisted 0.846, Assisted 0.900.
Predicate Device(s)
P980025
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2070 Medical image analyzer.
(a)
Identification. Medical image analyzers, including computer-assisted/aided detection (CADe) devices for mammography breast cancer, ultrasound breast lesions, radiograph lung nodules, and radiograph dental caries detection, is a prescription device that is intended to identify, mark, highlight, or in any other manner direct the clinicians' attention to portions of a radiology image that may reveal abnormalities during interpretation of patient radiology images by the clinicians. This device incorporates pattern recognition and data analysis capabilities and operates on previously acquired medical images. This device is not intended to replace the review by a qualified radiologist, and is not intended to be used for triage, or to recommend diagnosis.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the image analysis algorithms including a description of the algorithm inputs and outputs, each major component or block, and algorithm limitations.
(ii) A detailed description of pre-specified performance testing methods and dataset(s) used to assess whether the device will improve reader performance as intended and to characterize the standalone device performance. Performance testing includes one or more standalone tests, side-by-side comparisons, or a reader study, as applicable.
(iii) Results from performance testing that demonstrate that the device improves reader performance in the intended use population when used in accordance with the instructions for use. The performance assessment must be based on appropriate diagnostic accuracy measures (
e.g., receiver operator characteristic plot, sensitivity, specificity, predictive value, and diagnostic likelihood ratio). The test dataset must contain a sufficient number of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, concomitant diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals of the device for these individual subsets can be characterized for the intended use population and imaging equipment.(iv) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results; and cybersecurity).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use.
(ii) A detailed description of the intended reading protocol.
(iii) A detailed description of the intended user and user training that addresses appropriate reading protocols for the device.
(iv) A detailed description of the device inputs and outputs.
(v) A detailed description of compatible imaging hardware and imaging protocols.
(vi) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality or for certain subpopulations), as applicable.(vii) Device operating instructions.
(viii) A detailed summary of the performance testing, including: test methods, dataset characteristics, results, and a summary of sub-analyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
0
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
December 16, 2022
Overjet Inc. % Adam Odeh Director, Regulatory Affairs and Ouality Assurance 560 Harrison Ave., Unit 403 BOSTON, MA 02118
Re: K220928
Trade/Device Name: Overjet Calculus Assist Regulation Number: 21 CFR 892.2070 Regulation Name: Medical Image Analyzer Regulatory Class: Class II Product Code: MYN Dated: November 15, 2022 Received: November 17, 2022
Dear Adam Odeh:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal
1
statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
2022.12.16
14:56:46
-05'00'
Lu Jiang
Lu Jiang, Ph.D. Assistant Director Diagnostic X-ray Systems Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K220928
Device Name Overjet Calculus Assist
Indications for Use (Describe)
Overjet Calculus Assist (OCalA) is a radiological automated concurrent-read computer-assisted detection software intended to aid in the detection of interproximal calculus deposits on both bitewing and periapical radiographs. The Overjet Calculus Assist surrounds suspected calculus deposits with a bounding box. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of containing calculus deposits. 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 or patient history. The system is to be used by professionally trained and licensed dentists.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ✖ Prescription Use (Part 21 CFR 801 Subpart D) | ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
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510(k) Summary
(K220928)
This summary of 510(k) information is being submitted in accordance with the requirements of 21CFR Part 807.92
1. Date Prepared
November 15, 2022
2. Applicant
Overjet, Inc. 560 Harrison Ave Unit 403 Boston, MA 02118 Contact Person: Adam Odeh Email: adam.odeh@overjet.ai
3. Trade Name Overjet Calculus Assist
-
- Common Name Medical Image Analyzer
5. Classification 21 CFR 892.2070, Product code MYN, Class 2, Radiology
6. Device Description
Overjet Calculus Assist is a module within the Overjet Platform. The Overjet Calculus Assist (OCalA) software automatically detects interproximal calculus on bitewing and periapical radiographs. It is intended to aid dentists in the detection of calculus. 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 professionally trained and licensed dentists.
7. Indications for Use
Overjet Calculus Assist (OCalA) is a radiological automated concurrent-read computer-assisted detection software intended to aid in the detection of interproximal calculus deposits on both bitewing and periapical radiographs. The Overjet Calculus Assist surrounds suspected calculus deposits with a bounding box. The device provides additional information for the dentist to use in their diagnosis of a tooth surface suspected of containing calculus deposits. The device is not intended as a replacement for a complete dentist's review or their clinical judgment that
4
takes into account other relevant information from the image or patient history. The system is to be used by professionally trained and licensed dentists.
8. Predicate Device
Device: Logicon Caries Detector Manufacturer - Carestream Dental PMA:P980025 (down-classified to class 2 under 85 FR 3548, Jan. 22, 2020)
9. Substantial Equivalence
| Device | Carestream
Logicon
Caries Detector | Overjet Calculus Assist
(proposed) |
|--------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 510k | P980025 | K220928 |
| Regulation No /
Description | CFR 892.2070
Medical image analyzer | CFR 892.2070
Medical image analyzer |
| Intended Use | The Logicon Caries Detector is a
software device that is an aid in the
diagnosis of caries that have
penetrated into the dentin, on un-
restored proximal surfaces of
secondary dentition through
the statistical analysis of digital
intraoral radiographic imagery. The
device provides
additional information for the clinician
to use in his/her diagnosis of a tooth
surface suspected of being carious. It
is designed to work in conjunction
with an existing Carestream dental
RVG digital X-ray radiographic
system with dental imaging software
(dis) for Windows XP or higher. | Overjet's Calculus Assist (OCalA)
software automatically detects
interproximal calculus on bitewing and
periapical radiographs. It is intended to aid
dentists in the detection of calculus. 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 professionally trained and licensed
dentists. |
| Type of CAD | CADe | CADe |
| End User | Dentist | Dentist |
| Patient
Population | Patients requiring dental services, all
sexes, no
age restriction | Patients requiring dental services, all sexes,
18 years of age or older. |
| Platform | Windows PC | Web - Edge, Chrome, Firefox |
| OS | Microsoft Window 7, 8, 10 | Any |
| User Interface | Mouse, Keyboard | Mouse, Keyboard, Trackpad |
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| Image Input
Sources | Images can be scanned, loaded from
connected Carestream image solutions | Images imported from the radiographic
device, or from the practice management
system |
|----------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Image format | | JPEG, PNG, JFIF, JIF, TIFF, EOP, BMP,
DICOM |
| Processing
Architecture | The software provides graphical
representation of the density change in
a tooth, by looking for a
pattern of density dips starting at the
tooth surface, penetrating the enamel
and going into the dentin. Enamel is
represented by 10 green lines and
dentin by 5 blue lines. If a pattern
suggestive of caries exists, the dips are
highlighted with red dots to warn the
dentist. | Three layers:
1 - The Network layer works with the
practice PACS or EMR to transmit the
image and meta-data to Overjet.
2 - The decision layer processes the image
to ensure it is the correct data type, and
then annotates it via the algorithm
3 - The presentation layer displays the
annotated image in a non-diagnostic
viewer. The dentist can filter, display, hide,
create and edit the annotations presented. |
| Data Source | Bitewing radiographs acquired from
Carestream
dental RVG digital X-ray radiographic
system | Bitewing and periapical radiographs of at
least 500 x 500 pixels. |
| Output | • Outline of suspected region
• Tooth Density
• Lesion (caries) probability | Calculus detection on radiograph resulting
in bounding box outline of suspected
calculus |
| Performance
Testing | Increase in dentist's sensitivity of
approximately 20% | Superiority of aided reader versus unaided
reader performance |
| Level of
Concern | Moderate | Moderate |
Overjet Calculus Assist is determined to be substantially equivalent to the Carestream Logicon Caries Detector cleared as P980025. Both systems are software intended to support dental professionals in their diagnosis and treatment planning for their dental patients.
Both software systems automatically annotate suspected areas of interest for the dentist to review. The Logicon software displays suspected carious lesions as dips in annotated lines within the radiograph, green lines for the enamel and blue lines for the dentin. The Overjet Calculus Assist presents suspected calculus deposits as bounding boxes outlining the prediction. Both systems allow users to visualize the radiograph with the annotations, add their own annotations, and use the information as part of their diagnostic process.
Other similarities include both systems have no direct contact with the patient, both systems evaluate oral cavity radiographs, both systems utilize standard image types, and both systems connect to practice management systems. Logicon compatibility is limited to Carestream products.
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Some differences between the systems include the location of the software, the user interface, and the availability of additional features. A primary difference is the Carestream Logicon is a local software while Overjet Calculus Assist is a cloud native application. While Logicon and Overjet Calculus Assist have different user interfaces, both are accessed by computer and are intended for dental professionals to review annotations on dental radiographs. Overjet does not feel that the differences raise a concern of substantial equivalence and these differences do not interfere with the ability of the Overjet software to achieve its intended use.
10. Performance Testing
Overjet has conducted performance testing according to FDA's "Guidance for Industry and Food and Drug Administration Staff Computer-assisted Detection Devices Applied to Radiology Images and Radiology Device Data – Premarket Notification [510(k)] Submissions Document" issued on: Jul 3, 2012, as part of the development process of the calculus model. Performance testing included standalone testing and a clinical reader evaluation. All testing demonstrated that Overjet Calculus Assist software met prespecified requirements.
Standalone Testing
Standalone performance of the overjet AI algorithm for 296 bitewing radiographs and 322 periapical radiographs. Sensitivity and specificity were summarized based on surfaces, and 95% Cis were provided based on treating the subject as the basis of a cluster. A total of 6,121 surfaces were available on bitewing radiographs, and 3,595 surfaces were available on periapical radiographs.
Sensitivity
Overall standalone sensitivity was 74.1% (66.2%, 82.0%) for bitewing radiographs, and 72.9% (65.3%, 80.5%) for periapical radiographs.
Specificity
Overall standalone specificity was 99.4% (99.1%, 99.6%) for bitewing radiographs, and 99.6% (99.3%, 99.8%) for periapical radiographs.
Subgroup Analyses
Subgroup analyses were also performed for age, gender, sensor, and clinical site. Results were generally similar across all subgroups, and any observed differences were not associated with increased risks.
AFROC
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AFROC curves were derived using the polygon model scores associated with true positives and false positives for all areas identified on each image, which were used to generate and AFROC curve and associated AUC. Results are shown in the following table.
| Image Type | AUC | 95% CI1 |
|---|---|---|
| Bitewing | 0.859 | 0.823, 0.894 |
| Periapical | 0.867 | 0.828, 0.903 |
| 1 Based on m=10000 bootstrap samples. |
Clinical Evaluation - Reader Improvement
Overjet evaluated the Overjet Calculus Assist in a multi-reader, fully crossed reader improvement study. 14 US licensed dentists were asked to evaluate 292 bitewing radiographs (85 with calculus and 211 without calculus) and 322 periapical radiographs (89 with calculus and 233 without calculus). Ground truth was established by the consensus labels of three US-licensed dentists, and non-consensus labels were adjudicated by an oral radiologist. Half of the data set contained unannotated images, and the other half contained radiographs that had been processed through Overjet Calculus Assist. The radiographs were presented to the readers in alternating groups.
In Session 1, readers were asked to draw a box around suspected calculus, and to review predictions from the Overjet Calculus Assist model. Each reader was asked to provide a rating of 1-4 for their confidence in the label (1 - low confidence, 4 - high confidence). A 30-day washout period was utilized to limit recollection bias. Following the washout, the readers were presented the same data set but with alternate grouping. If a reader saw a radiograph in the unpredicted state in session 1, they were presented with the Overjet Calculus Assist predictions in session 2, and vice versa.
Results were compared against a consensus ground truth, and the sensitivity, specificity, and alternative free response receiver operating characteristic (AFROC) was evaluated to characterize the performance of the readers with and without viewing the model annotations.
Unassisted vs. Assisted Sensitivity
For bitewing radiographs, overall reader sensitivity improved from 74.9% (68.3%, 80.2%) to 84.0% (78.8%, 88.2%) unassisted vs assisted. For periapical radiographs, overall reader sensitivity improved from 74.7% (69.9%. 79.0%) to 84.4% (78.8%, 89.2%) unassisted vs assisted.
Unassisted vs. Assisted Specificity
For bitewing radiographs, overall reader specificity decreased slightly from 98.8% (98.7%, 99.0%) to 98.6% (98.4%, 98.9%) unassisted vs assisted. For periapical radiographs, overall
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reader specificity also decreased slightly from 98.1% (97.8%, 98.4%) to 98.0% (97.7%, 98.4%) unassisted vs assisted.
Subgroup Analyses
Subgroup analyses were performed for age, gender, sensor, clinical site, and reader experience. While some differences were observed for various factors and interactions, reader improvement (unassisted vs assisted) was observed in nearly all analyses. No observed differences were associated with increased risks.
AFROC
Readers provided confidence scores for any detected calculus, which were used to calculate AUC for weighted AFROC scores. For the average of all readers, AUC increased from 0.840 (0.800, 0.880) to 0.878 (0.844. 0.913) on bitewing radiographs, and from 0.846 (0.808. 0.884) to 0.900 (0.870, 0.929) on periapical radiographs. Both increases were statistically significant.
| Image
Type | Modality | Reader Avg
AUC of
AFROC | StdError | 95% CI | p-value
on AUC
Difference | Difference
in AUCs | StdErr of
Difference | 95% CI on
Difference |
|---------------|------------|-------------------------------|----------|--------------|---------------------------------|-----------------------|-------------------------|-------------------------|
| Bitewing | Assisted | 0.878 | 0.017 | 0.844, 0.913 | 0.0055 | 0.038 | 0.013 | 0.012, 0.065 |
| | Unassisted | 0.840 | 0.020 | 0.800, 0.880 | | | | |
| Periapical | Assisted | 0.900 | 0.015 | 0.870, 0.929 | 1.47e-05 | 0.054 | 0.011 | 0.032, 0.075 |
| | Unassisted | 0.846 | 0.019 | 0.808, 0.884 | | | | |
11. General Safety and Effectiveness Concerns
The device labeling contains instructions for use and any necessary cautions and warnings to provide for safe and effective use of this device. Risk management was conducted according to ISO 14971 which ensured, via a risk analysis, the identification and mitigation of potential hazards. Any potential hazards were controlled via software development and design, verification, and validation testing. In addition, general and special controls of the FD&C Act established for Radiological Computer Assisted Detection and Diagnosis Software are in place to further mitigate any safety and or effectiveness risks.
12. Assessment of Non-clinical Performance Data
Overjet Calculus Assist has been verified and validated according to Overiet's design control processes. All supporting documentation has been included in this 510(k) Premarket Notification. Verification activity included unit, integration, and system level testing. Validation testing included performing a pivotal reader study to compare the clinical performance of dentists using CAD detections from the Overjet Calculus Assist software when applied to dental radiographs to
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that of dentists not using Overjet Calculus Assist.
13. Conclusion
Overjet Calculus Assist is substantially equivalent to the predicate device, Carestream Logicon Caries Detector. Differences do not raise any concerns about the safety or efficacy of the device.