K Number
K021929
Manufacturer
Date Cleared
2002-09-10

(90 days)

Product Code
Regulation Number
N/A
Reference & Predicate Devices
Predicate For
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Axya Model 100 Sonic Scalpel™ Ultrasonic Surgical System is indicated for use in endoscopic and open surgical procedures for the cutting and coagulation of soft tissue structures.

Device Description

The Sonic Scalpel™ Ultrasonic Surgical System consists of an Ultrasonic Generator / Co. Unit, a reusable handpiece that contains the ultrasonic transducer, and a family of disposable cutting / coagulation shears. The Sonic Scalpel™ shears are available with a range of shaft lengths, diameters and blade lengths as single-patient-use, sterile instruments. The shears are coupled to the reusable handpiece by means of a collar. The titanium instrument blade tip consists of one fixed blade and one movable blade. The tip may be rotated to facilitate the surgical approach. The shears are designed for cutting, coagulation and blunt dissection.

AI/ML Overview

The provided text describes the Axya Model 100 Sonic Scalpel™ Ultrasonic Surgical System and its substantial equivalence to predicate devices, but it does not contain specific acceptance criteria or a detailed study that proves the device meets such criteria in terms of performance metrics like accuracy, sensitivity, or specificity.

Instead, the submission focuses on:

  • Design and functional comparison: Demonstrating that the blade amplitude and temperature range are comparable to a predicate device.
  • In vitro and in vivo studies (summarized): Mentioning that in vitro studies evaluated blade excursion and temperature, and an in vivo study in laboratory animals evaluated efficacy, producing "similar results to the performance of typical electrosurgical systems."

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor can I fill in most of the requested details about a study focusing on meeting specific performance metrics with a test set, expert consensus, or comparative effectiveness.

Here’s what can be extracted from the provided text based on the categories you requested:


1. Table of Acceptance Criteria and the Reported Device Performance

Acceptance Criteria (Implied)Reported Device Performance
Blade excursion (amplitude) comparable to predicate device (Ultracision)Data presented demonstrate that the blade amplitude of the Axya Model 100 Sonic Scalpel Ultrasonic Surgical System is comparable to those parameters for the predicate Ultracision device.
Blade temperature comparable to predicate device (Ultracision)Data presented demonstrate that the blade temperature range of the Axya Model 100 Sonic Scalpel Ultrasonic Surgical System is comparable to those parameters for the predicate Ultracision device.
Efficacy in vivo comparable to typical electrosurgical systemsIn vivo study in laboratory animals indicates the system produces results similar to the performance of typical electrosurgical systems.

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

  • Sample Size: Not specified for any of the studies (in vitro or in vivo).
  • Data Provenance: The in vivo study was conducted in "laboratory animals." No country of origin is specified. The studies are by nature "retrospective" from the perspective of the FDA review, as they were completed prior to submission.

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

  • This information is not provided. The studies mentioned (in vitro and in vivo) likely involved technical measurements and observations by researchers, but "experts" establishing a ground truth in the context of diagnostic performance (e.g., radiologists for imaging) is not applicable here.

4. Adjudication method for the test set

  • Not applicable/not specified for the types of engineering and animal studies 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

  • No, an MRMC comparative effectiveness study was not done. This device is a surgical instrument, not an AI or diagnostic imaging device that would typically involve human readers.

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

  • Not applicable as this is a surgical instrument, not an algorithm or AI. The "standalone" performance would refer to the device's physical function, which was evaluated in the in vitro and in vivo studies.

7. The type of ground truth used

  • For the in vitro studies, the "ground truth" would be direct physical measurements (e.g., actual amplitude, actual temperature).
  • For the in vivo animal study, the "ground truth" would be the observed tissue responses (cutting, coagulation efficacy) as evaluated against the performance of "typical electrosurgical systems." No specific pathology or outcomes data is detailed.

8. The sample size for the training set

  • This concept (training set) typically applies to machine learning or AI models. It is not applicable to the development or testing of this physical surgical device.

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

  • Not applicable for the reasons mentioned in point 8.

Summary of Device Acceptance:

The device's acceptance was based on demonstrating substantial equivalence to existing legally marketed predicate devices (Ultracision Ultrasonic Scalpel and Olympus SonoSurg™ System). The studies presented were primarily to show that the Axya Model 100 Sonic Scalpel Ultrasonic Surgical System's fundamental operational characteristics (blade amplitude, temperature) and efficacy in animal models were comparable to these predicates, thus supporting its safety and effectiveness for the stated indications. The FDA's 510(k) clearance process focuses on this substantial equivalence rather than requiring extensive de novo clinical trials with specific acceptance criteria thresholds on performance metrics typically seen for diagnostic devices or novel treatments.

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