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Drive unit with a piezoceramic oscillating system, which moves the tip in a linear oscillation.

The drive unit is used for the removal of supragival calculus and subgingival concretions and for endodontic application and preparation of tooth enamel.

The Proxeo ULTRA is a drive unit including handpieces with a piezoceramic oscillating system, which moves the tip in a linear oscillation.

The drive unit is used for the removal of supragingival calculus and subgingival concretions and for endodontic application and preparation of tooth enamel.

The medical device consists of the following components that are also included in the scope of delivery:

• Control unit (PB-510, PB-520, and PB-530)
• Handpiece (PB-5 L, PB-5 L, S, and PB-5 L Q)
• Foot control (wired, wireless)
• A Power supply, instruction for use and other accessories

The scaler tips are moved with a piezo-scaler handpiece by converting electrical energy into mechanical vibration. The coolant (water) is directed to the treatment site via a solenoid valve and a control unit via the tip. The scaler tips are re-usable [diamond-coated tips are single use only] and delivered non-sterile. Tips for use with Piezo Scaler for the following dental applications:

• Scaling-tips
• Periodontic-tips
• Implant-cleaning-tips
• Endodontic-tips
• Tips for restoration and prosthetics

With the foot control, corresponding device functions can be operated with the foot. These functions include, for example, program selection (button), operation of coolant function (button), motor direction of rotation selection (button), motor speed level (variable with pedal), power piezo handpiece (variable with pedal).

Bluetooth Low Energy technology is used in the wireless foot controls (C-NW) to make this possible wirelessly as well. The foot controls are powered internally by a rechargeable battery (C-NW) or an external power source (C-NF).

This document is a marketing clearance (510(k)) for a dental device, the Proxeo ULTRA. It details the device's characteristics and its equivalence to previously cleared predicate devices. Since this is a 510(k) summary for a physical medical device (ultrasonic scaler), not a diagnostic or AI-powered software, the typical acceptance criteria and study designs that involve metrics like sensitivity, specificity, or reader studies with AI assistance are not applicable in the same way they would be for an AI/ML medical device.

The document focuses on demonstrating substantial equivalence to predicate devices through technical characteristics, performance data (bench testing, biocompatibility, electrical safety, reprocessing validation), and adherence to relevant standards. It does not contain information on "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of clinical performance metrics for diagnostic or AI-based devices.

Therefore, I cannot extract the requested information regarding acceptance criteria, sample sizes for test sets, expert involvement, adjudication methods, MRMC studies, standalone performance, or ground truth types, as these are not relevant or reported for this type of device clearance.

Instead, the "acceptance criteria" for a device like the Proxeo ULTRA are primarily met by demonstrating that it performs as intended (as shown by bench testing) and is as safe and effective as existing legally marketed devices.

Here's how the information would typically be presented if it were an AI/ML device, alongside an explanation of why it's not applicable here:

Based on the provided FDA 510(k) summary for the Proxeo ULTRA (an ultrasonic dental scaler), the requested information regarding acceptance criteria and study designs for AI/ML performance metrics is NOT applicable.

This document is for a physical medical device and demonstrates substantial equivalence through:

• Technical Characteristics Comparison: Showing similar design, operating principles, and materials to predicate devices.
• Performance Data: This primarily involves non-clinical testing to ensure the device functions as intended and meets safety standards, rather than diagnostic accuracy or clinical outcome studies in the context of AI.

Therefore, the following specific information cannot be extracted from this document:

1. A table of acceptance criteria and the reported device performance (in terms of AI/diagnostic metrics): Not applicable. The "performance" is demonstrated through bench testing, biocompatibility, electrical safety, and reprocessing validation, ensuring the device operates as specified and is safe.
2. Sample sizes used for the test set and the data provenance: Not applicable. There isn't a "test set" of clinical data for diagnostic performance. Bench testing is mentioned, but specific sample sizes for its components are not detailed in this summary.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for diagnostic purposes is not established for an ultrasonic scaler.
4. Adjudication method for the test set: Not applicable.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable. This type of study is for evaluating human performance with and without AI assistance for diagnostic tasks.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. There is no AI algorithm.
7. The type of ground truth used: Not applicable.
8. The sample size for the training set: Not applicable. There is no AI model requiring a training set.
9. How the ground truth for the training set was established: Not applicable.

Instead, for this device, the "acceptance criteria" are implied by the demonstration of substantial equivalence, which includes:

• Manufacturing and Safety Standards Compliance: The device complies with relevant IEC standards (IEC 60601-1, IEC 80601-2-60, IEC 60601-1-2) for electrical safety and EMC.
• Biocompatibility: Evaluation according to ISO 10993 series.
• Reprocessing Validation: Validation per FDA Guidance for Medical Devices.
• Bench Testing: Functional testing (application, settings, features) per device specifications.
• Software Verification: Compliance with IEC 62304 and FDA guidance for software, given its moderate level of concern.

The "study that proves the device meets the acceptance criteria" refers to the non-clinical testing (bench, biocompatibility, electrical safety, reprocessing, software verification) that demonstrates the device performs as intended and is as safe and effective as its predicate devices. The document explicitly states: "Non-clinical testing has been performed showing that the device performs as intended and are substantially equivalent to the predicate device... and the reference device..."

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The PIEZON® 707 BIK and PIEZON® BIK LED is intended for use for the following indications:

Scaling

• Removal of supragingival calculus
• Removal of stains

Endo

• Preparation, cleaning and irrigation of root canals
• Condensing gutta-percha
• Removal of crowns, bridges and restorations

Restorative

• Preparation of cavities
• Cementation of restorations
• Condensing of amalgams

Periodontics

• Scaling and root planing
• Periodontal therapy

The PIEZON® 707 BIK and PIEZON® BIK LED is an ultrasonic scaling unit consisting of an ultrasonic generator supplied with a Piezon Handpiece and scaling instruments. The PIEZON® 707 BIK and PIEZON® BIK LED are supplied with the Piezon Handpiece EN-061 and Piezon Handpiece LED EN-060, respectively. The PIEZON® 707 BIK and PIEZON® BIK LED ultrasonic generator is designed for installation into a dental chair.

The ultrasonic generator produces piezo-electric vibrations (ultrasonics) for water or dry work instruments. The appropriate instrument for a particular application is screwed onto the handpiece supplied with the scaling unit prior to beginning the procedure. The power control is handled via the potentiometer or the chair main control. The water control is handled via the handpiece or the chair main control. The treatment is carried out by placing the instrument tip onto the tooth surface according to the Operating Instruction for the instrument selected.

The provided text describes the regulatory clearance for the PIEZON® 707 BIK and PIEZON® BIK LED ultrasonic scaler. It states that no clinical testing was conducted to support this submission, and therefore, an AI/algorithm-specific acceptance criteria and study proving its meeting of those criteria in a MRMC or standalone manner are not applicable.

The submission focuses on demonstrating substantial equivalence to a predicate device (Satelec SP Newtron Module, K033764) through non-clinical performance testing.

Here's the information parsed from the document based on your request, with an emphasis on what is not applicable due to the nature of the submission (device, not AI/ML):

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

The document does not explicitly state "acceptance criteria" in a quantitative, threshold-based manner typical for AI/ML performance. Instead, it indicates that "all design inputs... were satisfied by the design outputs" and that "the device met the predetermined acceptance criteria" based on non-clinical tests.

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

Not applicable. This was non-clinical performance and safety testing of a physical device, not an AI/ML algorithm's performance on a data test set. The testing was performed on the device itself, integrated with a dental chair and handpiece.

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 as typically defined for AI/ML performance evaluation (e.g., derived from expert consensus on medical images) is not relevant here. The "ground truth" for this device's performance would be engineering specifications and safety standards.

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

Not applicable. No expert adjudication process for a data test set was described.

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. No clinical testing, and specifically no MRMC comparative effectiveness study was performed or described. This device is an ultrasonic scaler, not an AI-assisted diagnostic tool. The submission explicitly states: "No clinical testing was conducted to support this submission."

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

Not applicable. This device is a physical medical device (ultrasonic scaler), not an AI algorithm. Its performance is measured by its physical operation and adherence to engineering and safety standards, not as a standalone algorithm.

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

For the non-clinical performance testing of the ultrasonic scaler, the "ground truth" was based on:

• Engineering specifications: The design inputs and predetermined performance specifications for the device's electrical, mechanical, and functional characteristics.
• International standards: Compliance with standards like IEC 60601-1 (electrical safety) and IEC 60601-1-2 (electromagnetic compatibility).

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no concept of a "training set" for an algorithm.

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

Not applicable. As there is no training set, this question is not relevant.

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