Who is the manufacturer of Overjet Calculus Assist?

Overjet, Inc. filed the 510(k) submission for Overjet Calculus Assist (K220928).

What is the FDA product code for Overjet Calculus Assist?

MYN. It is classified under 21 CFR 892.2070 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for Overjet Calculus Assist?

510(k) clearance (submission type: Traditional).

Does Overjet Calculus Assist use AI or machine learning?

Yes. Overjet Calculus Assist (K220928) is flagged as an AI/ML-enabled medical device in the FDA's AI/ML device list.

What are the predicate devices for Overjet Calculus Assist?

Logicon Caries Detector (P980025).

Who can help prepare an FDA 510(k) submission like Overjet Calculus Assist?

Innolitics — a medical-device software consultancy — provides regulatory and engineering support for FDA 510(k) submissions. See https://innolitics.com/services/510ks/ or contact https://innolitics.com/contact.

Can an AI/ML device like Overjet Calculus Assist get a guaranteed FDA 510(k) clearance?

Yes. Innolitics offers a guaranteed FDA 510(k) clearance engagement for AI/ML Software as a Medical Device — combining engineering and regulatory execution under one agreement with a guaranteed clearance outcome. Eligibility: the device must be an AI/ML Software as a Medical Device (SaMD), and its performance must meet the criteria Innolitics determines during an initial regulatory strategy engagement to be necessary for FDA clearance. See https://innolitics.com/services/end-to-end-samd/ or contact https://innolitics.com/contact.

Overjet Calculus Assist

K220928 · Overjet, Inc. · MYN · Dec 16, 2022 · Radiology

Device Facts

Record ID	K220928
Device Name	Overjet Calculus Assist
Applicant	Overjet, Inc.
Product Code	MYN · Radiology
Decision Date	Dec 16, 2022
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.2070
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device

Intended 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.

Device Story

Cloud-native software module; processes bitewing/periapical radiographs (min 500x500 pixels) to detect interproximal calculus. Input images imported from practice management systems/radiographic devices; processed via AI algorithm to identify suspected calculus; output as bounding box annotations on non-diagnostic viewer. Used by licensed dentists in clinical settings to assist diagnostic review. Workflow: network layer transmits image/metadata; decision layer validates data type and runs algorithm; presentation layer displays annotated images. Dentist filters/edits annotations; output serves as decision support, not replacement for clinical judgment. Benefits: improved sensitivity in calculus detection; aids in treatment planning.

Clinical Evidence

Multi-reader, fully crossed reader improvement study with 14 US-licensed dentists evaluating 292 bitewing and 322 periapical radiographs. Ground truth established by consensus of three dentists, adjudicated by oral radiologist. Primary endpoints: sensitivity, specificity, and AFROC AUC. Bitewing sensitivity improved from 74.9% (unassisted) to 84.0% (assisted); periapical sensitivity improved from 74.7% to 84.4%. Specificity remained high (98.6% bitewing, 98.0% periapical). AUC for bitewing increased from 0.840 to 0.878 (p=0.0055); periapical AUC increased from 0.846 to 0.900 (p=1.47e-05).

Technological Characteristics

Cloud-native software; web-based (Edge, Chrome, Firefox). Inputs: JPEG, PNG, JFIF, JIF, TIFF, EOP, BMP, DICOM. Processing: AI-based detection algorithm. Output: bounding box annotations. No direct patient contact. Risk management per ISO 14971. Software level of concern: Moderate.

Indications for Use

Indicated for patients 18 years of age or older requiring dental services. Intended to aid licensed dentists in detecting interproximal calculus on bitewing and periapical radiographs.

Regulatory Classification

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.

Special Controls

*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.

Predicate Devices

Logicon Caries Detector (P980025)

Related Devices

K210187 — Overjet Dental Assist · Overjet, Inc. · May 19, 2021
K232384 — Videa Dental Assist · Videahealth, Inc. · Dec 15, 2023
K233738 — Overjet Caries Assist-Pediatric · Overjet, Inc. · Mar 4, 2024
K241725 — Better Diagnostics Caries Assist (BDCA) Version 1.0 · Better Diagnostics AI Corp. · Mar 11, 2025
K222054 — Denti.AI Auto-Chart · Denti.Ai Technology, Inc. · Nov 22, 2022

Submission Summary (Full Text)

{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 {2}------------------------------------------------ # 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) | | |-------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------| | <div> ✖ Prescription Use (Part 21 CFR 801 Subpart D) </div> | <div> ☐ Over-The-Counter Use (21 CFR 801 Subpart C) </div> | #### CONTINUE ON A SEPARATE PAGE IF NEEDED. This section applies only to requirements of the Paperwork Reduction Act of 1995. #### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: > Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." {3}------------------------------------------------ # 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 - 4. 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 | {5}------------------------------------------------ | 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. {6}------------------------------------------------ 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 {7}------------------------------------------------ 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 {8}------------------------------------------------ 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 {9}------------------------------------------------ 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.