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Sonic Surgeon 310L, Sonic Surgeon 600L and Sonic Surgeon 800L are piezoelectric devices for surgery that enable mechanical ultrasound treatment, osteotomy and osteoplasty techniques to be applied in dental use.

Sonic Surgeon 310L. Sonic Surgeon 600L and Sonic Surgeon 800L are ultrasonic surgical units intended for mechanical ultrasound treatment in prophylaxis, periodontics. The normal mode is tooth scaling applications, and the Boost Mode of Sonic Surgeon 310L. Sonic Surgeon 600L and Sonic Surgeon 800L can be used for surgical procedures, including osteotomy, osteoplasty, periodontal surgery and implantation.

The tips can easily be changed during the treatment and must also be cleaned and autoclaved.

This document is a 510(k) Summary for the Sonic Surgeon 310L, 600L, and 800L devices, seeking to demonstrate substantial equivalence to predicate devices, not an AI/ML device. Therefore, it does not contain the information requested in the prompt, such as acceptance criteria for AI performance, details of a study proving a device meets such criteria, sample sizes for test/training sets in an AI context, expert ground truth establishment, adjudication methods, or MRMC studies.

The document focuses on the technological characteristics and performance parameters comparing the new devices to existing predicate devices (Sonic Surgeon 300 and UBS ultrasonic bone surgery/UDD ultrasonic debridement device) to assert substantial equivalence.

Here's an analysis of the available information in relation to the prompt:

1. Table of acceptance criteria and the reported device performance:
   The document does not present "acceptance criteria" in the sense of predefined thresholds for performance to be met by the device itself beyond functional equivalence to predicates. Instead, it compares specific technological characteristics and performance parameters to predicate devices. These comparisons serve as the basis for claiming substantial equivalence.

   Characteristic/Parameter	Predicate Device (Sonic Surgeon 300 - K110881)	Predicate Device (UBS/UDD - K080220)	Proposed Devices (310L, 600L, 800L)
   Intended Use	Ultrasonic Surgical Unit for osteotomy & osteoplasty in dental use	Bone cutting instruments for oral surgery	Piezoelectric devices for mechanical ultrasound treatment, osteotomy, and osteoplasty in dental use
   Sterilization Method	Same as Proposed Devices (implied, not explicitly detailed for predicate)	Same as Proposed Devices (implied, not explicitly detailed for predicate)	Autoclaved (for tips)
   Materials Used	Enclosure: PC, ABS; Hose/Seals: Silicone; Hand Piece: PES; Tips: TrimRite stainless; Tip Coating: ZrN, ZrN+Diamond	Not detailed	Enclosure: PC, ABS; Hose/Seals: Silicone; Hand Piece: PPSU; Tips: TrimRite stainless; Tip Coating: ZrN, ZrN+Diamond
   Electrical Input Power	AC 95-115V, AC 210-240V	AC 230V±10%	AC 100-240V
   Auto Scanning Freq.	26 ± 3 kHz	26 kHz ± 10%	Automatic scanning, 26 ± 3 kHz
   Power Output (Normal Mode)	(Not specified for 300)	(Not specified for UBS/UDD Normal)	310L: 15-17W (L1), 17-21W (L2), 21-27W (L3)

600L: 15-17W (L1), 17-21W (L2), 21-27W (L3)
800L: 15-17W (L1), 17-21W (L2), 21-27W (L3) |
| Power Output (Boost Mode) | (Not specified for 300) | 90 W (overall power mentioned) | 310L: 30-50W
600L: 50-70W
800L: 70-90W |
| Water Flow (approx. ml/min) | Level 1: 10; Level 2: 30; Level 3: 50; Level 4: 70; Level 5: 90 | Not detailed | Level 1: 7-13; Level 2: 15-40; Level 3: 40-60; Level 4: 60-80; Level 5: 80-110 |
| LED Brightness (lux, at 20mm)| X | Not detailed | 310L: 1900-2600
600L: 2000-2800
800L: 2000-2800 (across 3 levels) |
| Foot Switch IP Class | IPX1 | Not detailed | IPX8 |

The "acceptance criteria" here are implicitly that the proposed devices must demonstrate similar performance and safety characteristics to the legally marketed predicate devices, supporting the claim of substantial equivalence. For example, the maximum output power of the Sonic Surgeon 800L (70-90W) is compared to the predicate UBS device (90W) to establish equivalence in this aspect.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
This document describes a medical device, not an AI/ML product. The "test set" in this context refers to standard engineering and electrical safety tests, and potentially material biocompatibility tests. It does not involve a "test set" of clinical data for algorithmic performance evaluation. No information regarding sample size or data provenance in the context of clinical studies for performance metrics is provided. The tests mentioned are for compliance with IEC standards.

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. Ground truth and expert adjudication are concepts relevant to AI/ML performance evaluation, which is not the subject of this 510(k) submission. The "ground truth" for this device would be established by physical measurements and compliance with engineering and safety standards.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
   Not applicable. This is not an AI/ML filing.

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 is not an AI/ML filing; no human-in-the-loop performance or reader studies are mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable. This is not an AI/ML filing.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
   Not applicable in the context of AI/ML. The "ground truth" for this device's performance would be derived from physical measurements (e.g., power output, frequency, LED brightness, water flow) and compliance with established engineering and safety standards (IEC 60601-1, IEC 60601-1-2).

8. The sample size for the training set:
   Not applicable. This is not an AI/ML filing. There is no concept of a "training set" for this type of device.

9. How the ground truth for the training set was established:
   Not applicable. This is not an AI/ML filing.

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Ultrasonic Surgical Unit is a piczoelectric device for bone surgery that enables ostcotomy and ostcoplasty techniques to be applied to in dental use.

Sonic Surgeon 300 is an ultrasound generator for use in dental surgery. And this device is used for surgical procedures, including osteonal surgery and in device your and implantation. Boost Mode can be used for mechanical ultrasound treatment in prophylaxis, periodontics or endodontics. The tips can easily be changed during the treatment and can also be cleaned and autoclaved. The Ultrasonic Surgical Unit transforms generated ultrasonic (26±3kHz) energy to the kinetic energy and transmits it to the tip. The generator of the Ultrasonic Surgical Unit performs automatic tuning of the operating frequency, the efficiency of the piezoelectric transducer in the handpiece.

This document describes the safety and effectiveness information of the Sonic Surgeon 300 / Ultrasonic Surgical Unit.

Here's an analysis of the provided text in relation to acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide specific numerical acceptance criteria for performance benchmarks like accuracy, precision, or sensitivity. Instead, it focuses on demonstrating substantial equivalence to a predicate device and adherence to safety standards.

"The performance tests demonstrated that Ultrasonic Surgical Unit performs in a substantially equivalent manner to the predicate device." |
| Intended Use Conformity: The device performs its stated "Indications for Use." | The device is described as "a piezoelectric device for bone surgery that enables osteotomy and osteoplasty techniques to be applied to in dental use." This intended use is consistent with the general description of its function. |

2. Sample size used for the test set and the data provenance:

The document does not specify a sample size or test set in the context of a formal clinical or performance study involving patients or a dataset for evaluating an AI model. The "performance tests" mentioned are likely technical evaluations against standards rather than a study on a specific number of cases/patients.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not applicable or provided. The document describes a device for surgical use and its technical compliance, not an AI or diagnostic tool that requires ground truth established by experts.

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

This information is not applicable or provided. The "performance tests" likely refer to engineering and electrical safety testing, not clinical performance evaluation with 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:

This information is not applicable or provided. The device is an ultrasonic surgical unit, not an AI-assisted diagnostic tool. Therefore, a multi-reader multi-case study evaluating human reader improvement with AI assistance would not be relevant.

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

This information is not applicable or provided. The device is a physical surgical instrument, not an algorithm.

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

This information is not applicable or explicitly stated as ground truth is typically associated with diagnostic or AI performance evaluation. The "ground truth" in this context would be the specifications and requirements of the safety standards (IEC 60601-1, IEC 60601-1-2) and the operational characteristics of the predicate device (Piezosurgery, K043408). The device's performance is measured against these established technical specifications and the functionality of the predicate.

8. The sample size for the training set:

This information is not applicable or provided. The document describes a physical medical device, not an AI model that requires a training set.

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

This information is not applicable or provided for the same reasons as above.

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