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MT-Bone is a piezoelectric ultrasonic device, consisting of handpieces and associated tip inserts, intended for:

• Bone cutting, osteotomy, osteoplasty and drilling in a variety of oral surgical procedures, including implantology, periodontal surgery, surgical orthodontic and surgical endodontic procedures;
• Scaling applications, including:
  Scaling: All general procedures for removal of supragingival and interdental calculus & plaque deposits:
  · Periodontology: Periodontal therapy and debridement for all types of periodontal diseases. including periodontal pocket irrigation and cleaning;
  · Endodontics: All treatments for root canal reaming, irrigation, filling, gutta-percha condensation and retrograde preparation;
  · Restorative and Prosthetics: Cavity preparation, removal of prostheses, amalgam condensation, finishing of crown preparations and inlay/onlay condensation.

MT-Bone is a piezoelectric ultrasonic device designed for oral bone surgery.
MT-Bone uses piezoelectric ultrasound technology to generate mechanical micro vibrations that can cut, drill or abrade through mineralized structures using appropriate inserts.
This allows an efficient and safe action which preserves the integrity of the osteotomized surfaces.
The micrometric, ultrasonic vibrations of the inserts provide greater precision and a selective action compared to traditional methods such as drills or oscillating saws (which act with macro vibrations), therefore minimizing traumatic effect on soft tissues. Depending by the Indication for use a lot of different type of inserts are available in Mectron portfolio.

The provided text describes the MT-Bone device and its substantial equivalence to a predicate device (PIEZOSURGERY TOUCH, K122322). However, it does not contain specific acceptance criteria, reported device performance metrics in a table, or details of a study proving the device meets said criteria in the way typically found for AI/ML-based medical devices.

The document primarily focuses on demonstrating substantial equivalence through a comparison of technological characteristics, indications for use, and general safety/performance testing. There is no mention of an algorithm, AI, or machine learning in the context of device function.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size) are not applicable or cannot be extracted from this document, as they pertain to a different type of device or evaluation method.

Here's a breakdown of what can be extracted based on the provided text, and where information is missing or not applicable:

1. Table of acceptance criteria and the reported device performance:

The document states that a series of non-clinical bench performance tests were conducted to evaluate the efficacy and safety of the device. The "acceptance criteria" are implied by the statement "All tests passed successfully" or "The testing showed that..." without quantitative metrics.

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

• Sample Size for Test Set: Not specified for any of the non-clinical tests. For the cadaver lab, it refers to "clinicians" but no number of cadavers or specific cases is given.
• Data Provenance: Not explicitly stated for any of the tests. It's internal testing by the manufacturer (Mectron S.p.A., Italy).

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):

• Number of Experts: For Usability Testing, it mentions "KOLs feedback and evaluations" (Key Opinion Leaders) but does not specify the number or their qualifications. For the Cadaver Lab, it states "clinicians" but again, no number or qualifications are provided.
• Qualifications of Experts: Not specified.

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

• Not applicable as the tests described are primarily bench, software, and usability/cadaver lab evaluations, not diagnostic accuracy studies requiring adjudication of ground truth by multiple experts.

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:

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The device described is a surgical instrument (piezoelectric ultrasonic device), not an imaging or diagnostic AI/ML device that assists human readers.

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

• Not applicable. The device is a surgical instrument requiring human operation. There is no mention of a standalone algorithm component that performs autonomously.

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

• For the non-clinical bench tests, "ground truth" is typically defined by engineering specifications, regulatory standards (e.g., IEC, ISO), and performance targets for the device's physical functions (e.g., amplitude, frequency, temperature, cutting efficacy).
• For Usability and Cadaver Lab tests, the "ground truth" or validation came from "KOLs feedback and evaluations" and "evaluation process conducted by clinicians," implying expert assessment of performance, safety, benefits, and usability.

8. The sample size for the training set:

• Not applicable. The document does not describe an AI/ML device that requires a training set.

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

• Not applicable. The document does not describe an AI/ML device that requires a training set.

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