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Rodo Abutment System is intended to be used in conjunction with compatible implant systems in the maxillary or mandibular arch to provide support for crowns, bridges or overdentures.

The Rodo Abutment System includes the Rodo Abutment, Smileloc Sleeve, Titanium Coping, Temporary Cap, abutment screws, the Smileloc Activator (or Smileloc Remover) (all cleared under K160786) and Smilekey (cleared under K180609). The Smileloc Sleeve is used to lock and unlock the Titanium Coping for final restoration to or from the abutment. This makes the prosthesis removable. The Rodo Abutment System eliminates the need for an access hole on the occlusal surface of a screw-retained restoration and also eliminates the possibility of prosthetic screw loosening. The Smilekey is an induction heating device for dental prosthesis removal of the Smileloc Sleeve in the Rodo Abutment System. The Smilekey was cleared as an accessory to the Abutment System in K180609, and there have been no changes to the Smilekey since this clearance.

The Rodo Abutment is provided in five series designs (100 F, 200 P, 300 S, 400 M, 500 D) with the 200 P and 500 D series having angled abutments (17°, 30°), for a total of nine designs. The 300 S series is designed for limited occlusal space and the 400 M series is designed for large interproximal spaces. Abutments are available in sizes ranging from 3.0 mm to 6.0 mm depending on the compatible implant system in use. Designs are available with engaging and non-engaging implant-abutment interfaces.

The provided text describes a 510(k) premarket notification for the Rodo Abutment System, focusing on adding compatibility with new implant lines. However, it does not contain the detailed information typically found in a study proving a device meets specific performance acceptance criteria for an AI/ML medical device.

The Rodo Abutment System is a hardware dental device, not an AI/ML software device. The "performance data" section discusses non-clinical testing such as dimensional analysis, reverse engineering, and fatigue testing according to ISO 14801. It does not refer to AI/ML model performance metrics, ground truth establishment, or human reader studies.

Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, or multi-reader multi-case studies, as the provided document pertains to the clearance of a mechanical dental device and not an AI/ML-driven diagnostic tool.

Specifically, the document does NOT contain information on:

• A table of acceptance criteria and reported device performance for an AI/ML model (e.g., sensitivity, specificity, AUC).
• Any sample sizes used for a test set in the context of AI/ML performance.
• Data provenance for AI/ML data (country of origin, retrospective/prospective).
• Number of experts used to establish ground truth for an AI/ML model.
• Adjudication method for an AI/ML test set.
• Multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone (algorithm-only) performance of an AI/ML model.
• Type of ground truth used (pathology, outcomes data, etc.) for an AI/ML model.
• Sample size for a training set in the context of AI/ML.
• How ground truth for a training set was established for an AI/ML model.

The document's "Performance Data" section solely refers to non-clinical bench testing for a mechanical device.

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The Rodo Smilekey is intended to be used with the Rodo Abutment System for removing prostheses compatible with Smileloc Sleeve by using induction heating.

The Smilekey is an additional remover device intended for use with the predicate Rodo Abutment System (K160786). It is used to deliver induction energy to the Smileloc Sleeve. The Smilekey consists of a tip and handle that uses induction (alternating electromagnetic field) to deliver precise energy to the Smileloc. Only the end of the tip is inserted inside the patient's mouth while the handle is hand-held by the operator. The Smilekey is powered by a rechargeable lithium battery inside the handle. The handle also contains an electronic control board that regulates the entire operation, including LED indicators that let the operator know when energy is being applied to the Smileloc Sleeve and when the unlocking procedure has been completed.

The given text describes the Rodo Smilekey, a dental device intended for removing prostheses compatible with the Smileloc Sleeve using induction heating. The document focuses on demonstrating the substantial equivalence of the Rodo Smilekey to a predicate device, the Smileloc Activator, rather than establishing distinct acceptance criteria with specific performance thresholds for a novel diagnostic or treatment outcome.

Instead of traditional accuracy, sensitivity, or specificity metrics often seen in AI/ML performance studies, the performance data provided focuses on safety and functional performance compared to established standards and the predicate device.

Here's an attempt to structure the information based on your request, acknowledging that the nature of the device (a tool for heating/removing dental prostheses) means some of your requested categories may not have direct equivalents:

1. A table of acceptance criteria and the reported device performance

Since this is a 510(k) submission for a Class II medical device, the "acceptance criteria" are primarily related to safety, functional performance, and substantial equivalence to a predicate device, rather than diagnostic accuracy. No explicit numerical acceptance criteria are provided, but the document states compliance with relevant standards and demonstrates that performance meets safe limits and is equivalent to the predicate.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document primarily describes bench testing (e.g., electrical safety, EMC, biocompatibility, cleaning, software V&V, battery, usability, thermal safety). These types of tests typically do not involve "test sets" of patient data in the way a diagnostic AI would.

• Sample size for test set: Not applicable in the context of patient data for diagnostic/prognostic evaluation. For bench tests, "samples" would refer to the number of devices or materials tested. This specific number is not provided, but the statement implies sufficient units were tested to meet the requirements of the standards.
• Data provenance: Not applicable. These are laboratory-based bench tests, not clinical data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. The "ground truth" for these types of engineering and safety tests is adherence to established international standards (e.g., ISO, IEC, AAMI/ANSI) and regulatory guidance. Expert clinical opinion for ground truth in a diagnostic sense is not relevant for this device's performance claims.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable, as there is no "test set" of clinical cases requiring expert adjudication.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This device is a tool for removing dental prostheses, not a diagnostic AI system assisting human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This refers to the inherent performance of the device itself (e.g., its ability to heat the Sleeve safely and effectively). The entire "Performance Data" section describes standalone testing of the Rodo Smilekey. It functions as an algorithm itself in the sense of regulating energy delivery and time, and its performance was evaluated independently through bench testing.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

The "ground truth" for the device's acceptable performance is defined by:

• Compliance with internationally recognized engineering and safety standards (e.g., AAMI/ANSI ES60601-1, IEC 60601-1-2, ISO 10993-1, ISO 10993-5, IEC 62133, IEC 60601-1-6).
• Adherence to FDA guidance documents (e.g., for reprocessing, software validation).
• Demonstrating that thermal output (maximum implant/abutment temperature) remains below established safety limits determined by physiological studies (e.g., Eriksson, AR et al.).
• Substantial equivalence to a legally marketed predicate device (Rodo Abutment System K160786) based on similar intended use and demonstration that technological differences do not raise new safety or effectiveness concerns.

8. The sample size for the training set

Not applicable. This device is not an AI/ML algorithm that requires a training set of data. Its function is based on principles of induction heating and electronics, not learned patterns from data.

9. How the ground truth for the training set was established

Not applicable, as no training set is used.

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Rodo Abutment System is intended to be used in conjunction with compatible implant systems in the maxillary or mandibular arch to provide support for crowns, bridges or overdentures.

The Rodo Abutment System includes the Rodo Abutment, Smileloc Sleeve, Silicone Seal, Titanium Coping, Temporary Cap, abutment screws, and Smileloc Activator (or Smileloc Remover). The Smileloc Sleeve is used to lock and unlock the Titanium Coping for final restoration to or from the abutment. This makes the prosthesis removable.

Rodo Abutment is provided in five series designs (100 F. 200 P. 300 S. 400 M. 500 D) with the 200 P and 500 D series having angled abutments (17°, 30°), for a total of nine designs. The 200 P and 500 D series are designed for multi-unit restorations only, the 300 S series is designed for limited occlusal space, and the 400 M series is designed for large interproximal spaces. Abutments are available in sizes ranging from 0 3.0 mm depending on the compatible implant system in use. Designs are available with engaging and non-engaging implant-abutment interfaces.

The provided document is a 510(k) summary for the Rodo Abutment System, a dental device. It outlines the device's indications for use, its classification, and a comparison to predicate devices, but does not contain information about acceptance criteria or a study designed to prove the device meets specific performance criteria in terms of algorithm-based metrics (like sensitivity, specificity, or AUC) as would be typical for an AI/ML device.

The closest information available that might relate to "acceptance criteria" for a medical device (not specifically an AI/ML device) typically involves demonstrating substantial equivalence to a legally marketed predicate device through various tests and comparisons.

Here's an analysis based on the provided document, addressing the requested points:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) submission for a physical dental abutment system and not an AI/ML device, there are no specific performance metrics like sensitivity, specificity, or accuracy mentioned as "acceptance criteria" for an algorithm. Instead, the "performance" is demonstrated through various non-clinical and clinical tests to show safety and effectiveness and substantial equivalence to predicate devices.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size (Clinical Trial): 34 subjects were enrolled, 32 subjects received Rodo Abutments and restorations. Out of these, 3 subjects received 4 abutments each as part of full arch treatment, resulting in a total of 41 Rodo Abutments placed and restored.
• Data Provenance: The document states, "A prospective multi-center clinical trial... was conducted under an Investigational Device Exemption study according to FDA guidelines." This indicates it's prospective data. The document does not explicitly state the country of origin, but given the FDA submission context, it's presumed to be a US-based study or at least data acceptable for US regulatory purposes.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. For a physical device like a dental abutment, "ground truth" might refer to clinical outcomes assessed by trained dental professionals, but the study description does not detail the number or qualifications of experts involved in assessing device performance or generating the "ground truth" of safety and effectiveness outcomes beyond the medical staff conducting the trial.

4. Adjudication Method for the Test Set

This information is not provided in the document. Adjudication methods (like 2+1 or 3+1) are typically relevant for studies where multiple readers interpret data and discrepancies need to be resolved, which is common in imaging studies for AI/ML devices. For a clinical trial of a physical implant, such a method for "test set" adjudication is not typically described in this manner.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No, an MRMC comparative effectiveness study was not done. This type of study is specific to evaluating diagnostic performance, often of AI/ML systems or diagnostic tests, comparing multiple readers' interpretations of cases. The Rodo Abutment System is a physical dental device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No, a standalone algorithm performance study was not done. The Rodo Abutment System is a physical dental device, not an algorithm or AI system.

7. The Type of Ground Truth Used

For the clinical study, the "ground truth" for evaluating the Rodo Abutment System's safety and effectiveness was based on clinical outcomes data from human subjects who received the device. This included:

• Observation of adverse events (e.g., abutment screw loosening, crown separation, non-device related events).
• The overall clinical assessment that the system "provides an appropriate method of attaching prosthetic restorations to dental implant abutments" and "if necessary, it allows repeated removal of the restoration."

For non-clinical tests, the "ground truth" was based on engineering standards and direct measurement/testing results (e.g., SAL for sterility, acceptable ranges for biocompatibility, mechanical strength, corrosion resistance).

8. The Sample Size for the Training Set

This product is a physical medical device, not an AI/ML algorithm. Therefore, there is no "training set" in the context of machine learning. The clinical and non-clinical data collected serve as validation for the device's design and manufacturing rather than training an algorithm.

9. How the Ground Truth for the Training Set Was Established

As there is no training set for an AI/ML algorithm, this question is not applicable.

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