Search Results

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.

Ask a specific question about this device