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The Piezosurgery MEDICAL is an ultrasonic surgical system consisting of handpieces and associated tips for cutting bone, osteotomy, osteoplasty and drilling in variety of surgical procedures, including but not limited to otolaryngological, oral/maxillofacial, hand, foot, neurosurgical, spine, and plastic/reconstructive surgery. It may also be used with endoscopic visual assistance to perform the above listed procedures.

The Piezosurgery® Medical device is an ultrasonic surgical system consisting of a central console with two integral peristaltic irrigation pumps, and two detachable handpieces. Each handpiece is connected to the console electrically, and each is also connected to one of the irrigation pumps via an irrigation tubing kit. The handpieces contain the ultrasonic transducers. A separate electricallyoperated footswitch is provided with the device, which also attaches to the central console. The irrigation tubing kits and insert tips are supplied sterile and are intended for single-use. A range of optionally available handpiece tips provides the surgeon with a wide variety of options for drilling, cutting and sawing.

The console has a touch-screen display and contains general control system circuits and two ultrasonic generators which drive the handpiece functions. The irrigation tubing kit is fed with physiological saline solution during the surgical procedure from saline bags (not supplied) which hang from drip stands that attach to the rear of the central console.

The user may activate either of the two handpieces by the selection from the LCD touch-screen and by pressing the footswitch.

This looks like a 510(k) premarket notification for a medical device called Piezosurgery Medical. It's a submission to show substantial equivalence to already marketed devices, not a study demonstrating performance based on acceptance criteria in the way you've described for an AI/ML device.

Therefore, many of the specific questions about acceptance criteria, study design, sample sizes, ground truth, experts, and AI performance cannot be directly answered from the provided text. This document is focused on regulatory clearance based on equivalence, not a clinical performance study with specific metrics and acceptance criteria for a new algorithmic device.

However, I can extract what is provided related to "performance data" which, in this context, refers to the device's operational characteristics rather than clinical outcomes measured against statistical targets.

Here's an attempt to address your request based only on the provided text, highlighting where information is not applicable or missing for this type of submission:

1. Table of acceptance criteria and the reported device performance

This document does not present "acceptance criteria" in the context of specific quantitative efficacy or diagnostic performance targets, nor does it provide a direct "reported device performance" against such criteria. The "Performance Data" section describes the device's operational capabilities.

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 applicable. This submission is for regulatory clearance based on substantial equivalence to predicate devices, not a clinical trial with a test set of patient data.
• Data Provenance: Not applicable for a clinical test set. The manufacturer is Mectron Spa, Italy, and the 510(k) owner is Piezosurgery SRL, Italy.

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

• Not applicable. There is no mention of a test set requiring expert-established ground truth for performance evaluation in this 510(k) submission.

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

• Not applicable. No test set requiring adjudication is mentioned.

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 surgical instrument (Piezosurgery Medical), not an AI/ML diagnostic or assistive tool for human readers (e.g., radiologists). Therefore, an MRMC study comparing human reader performance with and without AI assistance is irrelevant to this device.

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

• Not applicable. The Piezosurgery Medical is an ultrasonic surgical system, a physical instrument operated by a surgeon ("human-in-the-loop" by design), not a standalone algorithm.

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

• Not applicable. The submission focuses on the device's functional and technological characteristics and its intended use, demonstrating equivalence to predicate devices. It does not present a clinical performance study that would require a defined "ground truth" in the context of diagnostic accuracy or treatment success.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device where a "training set" would be used.

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

• Not applicable. As above, there is no training set for this type of device.

Summary of what is provided regarding performance and regulatory rationale:

The "Performance Data" section describes the device's operational flexibility (four cutting modalities, five irrigation levels, seven power levels) and its inherent technological features like ultrasonic frequency modulation and automatic tuning to achieve the desired surgical effect (a "hammering effect" for cutting action).

The conclusion of the 510(k) submission states that: "Based on the information contained within this submission, it is concluded that the Piezosurgery Medical device is substantially equivalent to the predicate devices already in interstate commerce within the USA." This statement, along with the FDA's clearance letter, indicates that the device met the regulatory standard of substantial equivalence, which is the primary "acceptance criterion" for a 510(k) submission – meaning it is as safe and effective as a legally marketed predicate device. The information supporting this includes the device description, intended use, and technological characteristics, as well as the operational "performance data" detailed above.

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The Piezosurgery® device is intended for use in the following dental applications:

• Bone cutting for use in oral surgery (K043408) -
• Removing supra and subgingival calculus deposits and stains from teeth -
• Periodontal pocket lavage with simultaneous ultrasonic tip movement -
• Scaling and root planing -
• Retrograde preparation of root canals

The Piezosurgery® device uses piezoelectric ultrasonic technology to generate mechanical microvibrations for bone cutting and ultrasonic scaling, with minimal trauma to soft tissue. The device is supplied with sharp, smoothing and blunt insert tips for use in oral surgery, including implantology, periodontal surgery, endodontic surgery and surgical orthodontics.

The provided text is a 510(k) summary for the Piezosurgery® device. This document focuses on demonstrating substantial equivalence to a predicate device for regulatory approval, rather than providing a detailed study report with specific acceptance criteria and performance data as one might find for a novel AI/ML medical device.

Therefore, many of the requested categories for AI/ML device studies are not applicable to this submission, as it describes a traditional medical device (an ultrasonic scaler) and its performance evaluation for established indications.

Here's an analysis based on the provided text, addressing the points where information is available and indicating where it's not applicable:

1. Table of acceptance criteria and the reported device performance

• Removing supra and subgingival calculus deposits and stains
• Periodontal pocket lavage with simultaneous ultrasonic tip movement
• Scaling and root planing
• Retrograde preparation of root canals | Technical, clinical, and histologic comparisons supported a finding of substantial equivalence to the predicate device. |
  | For Bone Cutting: Substantial equivalence to a predicate device (K043408, though the specific predicate for bone cutting is only referenced by K-number, not name) for bone cutting in oral surgery. | Performance and safety evaluations demonstrated:
• Precisely delineated tissue cutting
• Reduced risk of adjacent tissue damage
• Needed limited pressure on the handpiece to achieve desired cutting action
• Improved surgical control
• Reduced possibility of trauma to soft tissue |

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 in the provided text. The submission mentions "clinical data," but no numbers are given for patient or case count.
• Data Provenance: Not specified. It's unclear if the data was retrospective or prospective, or its country of origin.

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

• Number of Experts/Qualifications: Not specified. The summary refers to "clinical data" and "histologic comparisons" but does not detail how these assessments were conducted or by whom.

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

• Adjudication Method: Not specified.

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

• MRMC Study: Not applicable. This is a traditional medical device, not an AI/ML diagnostic tool, so an MRMC study is not relevant.

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

• Standalone Performance: Not applicable. This is a traditional medical device that requires human operation; it is not an algorithm.

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

• Type of Ground Truth: The performance evaluations were based on "clinical data on the characteristics of the inserts in vibration, cutting precision, and on the risk of adjacent tissue damage." It also mentions "histologic comparisons." These suggest a combination of clinical observation, physical measurements of device performance (vibration, cutting), tissue damage assessment, and potentially histopathological analysis to confirm tissue effects.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This is a traditional medical device, not an AI/ML model, so there is no "training set."

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

• Ground Truth for Training Set Establishment: Not applicable. (See #8)

Summary of Key Findings from the Document:

The Piezosurgery® device achieved 510(k) clearance by demonstrating "substantial equivalence" to existing predicate devices (EMS Piezon® Master 600 for ultrasonic scaling and K043408 for bone cutting). This equivalence was supported by "technical, clinical and histologic comparisons." The performance evaluations specifically highlighted precise cutting, reduced risk of adjacent tissue damage, and improved surgical control with limited pressure. The document, being a 510(k) summary, does not provide detailed study methodologies, sample sizes, or expert qualifications as typically found in comprehensive clinical trial reports.

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The Piezosurgery device is a bone cutting instrument intended for use in oral surgery.

The Piezosurgery® device uses piezoelectric ultrasonic technology to generate mechanical The riezdsurgery done cutting, with minimal trauma to soft tissue. The device is supplied mith sharp, smoothing and blunt insert tips for use in oral surgery, including implantology, periodontal surgery and surgical orthodontics.

The Piezosurgery device, indicated as a bone cutting instrument for oral surgery, underwent performance evaluations primarily based on clinical and histologic data.

Here's an analysis of the provided information in the requested format:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated. The document refers to "clinical and histologic data," implying a study involving patients or tissue samples, but no specific numbers are provided for either human subjects or tissue samples.
• Data Provenance: Not explicitly stated. The clinical and histologic data are likely retrospective, as no prospective study design is mentioned. The country of origin is not specified, but the submitter and contact person are associated with Italy, suggesting the data could be from Italy or Europe, though this is not confirmed.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. There is no mention of a formal adjudication process (e.g., 2+1, 3+1).

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

• MRMC Study: No, an MRMC comparative effectiveness study was not explicitly mentioned. The evaluation focuses on the device's intrinsic performance characteristics rather than comparing human reader performance with and without AI assistance. This device is a surgical tool, not an AI diagnostic system.

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

• Standalone Performance: Not applicable. This device is a manual surgical instrument, not an algorithm or AI system. Its performance inherently involves a human operator.

7. The Type of Ground Truth Used

• Ground Truth Type: Clinical observations and histologic findings. These are considered direct evidence of the device's effects on tissue and surgical outcomes.

8. The Sample Size for the Training Set

• Sample Size: Not applicable. As this is a medical device and not an AI or machine learning model, there is no "training set" in the conventional sense. The "training" for such devices typically involves design, engineering, and iterative testing, sometimes using preclinical or basic science data, and ultimately clinical data serves as validation.

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

• Ground Truth Establishment: Not applicable, as there is no training set mentioned for an algorithm. The development of the device would have relied on engineering principles, material science, and possibly cadaveric or animal studies to refine its design and operational parameters.

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