AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Sonicision™ Cordless Ultrasonic Dissection Device is indicated for soft tissue incisions when bleeding control and minimal thermal injury are desired. The device can be used as an adjunct to or substitute for electrosurgery, lasers, and steel scalpels in general, plastic, pediatric, gynecologic, urologic, exposure to orthopedic structures (such as spine and joint space) and other open and endoscopic procedures. The Sonicision Cordless Ultrasonic Dissection Device can be used to coagulate isolated vessels up to 5 mm in diameter.

Device Description

The Sonicision™ Cordless Ultrasonic Dissection Device is a hand-held surgical device consisting of three interdependent components that, when assembled, enable ultra high-frequency mechanical motion (ultrasonic energy) to transect, dissect, and coagulate tissue. The Sonicision device is designed to be both ergonomic and intuitive for the user. It can coagulate vessels up to and including 5 mm in diameter and is designed to be inserted and extracted through a compatible 5 mm trocar, when used endoscopically/laparoscopically. A unique characteristic of the device is that it functions without the need for external power cords and transducer cables. Sonicision generators and batteries are prepared by the facility and attached to the dissector (disposable component). When assembled, electrical power supplied by the battery pack is available to be converted to ultrasonic energy in the generator. The clinical intended use is achieved by the surgeon when pressure is applied to tissue placed between the clamping jaw and the exposed portion of the probe while activating ultrasonic energy through the use of a two-stage button. The system is comprised of single-use and reusable components.

AI/ML Overview

The provided text describes the 510(k) summary for the Sonicision™ Cordless Ultrasonic Dissection Device. It details the device's description, intended use, and technological/performance characteristics, along with a summary of non-clinical/preclinical performance. However, it does not contain specific acceptance criteria tables nor comparative study results with human readers or standalone algorithm performance as requested in the prompt. The information provided is primarily for demonstrating substantial equivalence to predicate devices, focusing on design features and non-clinical testing.

Therefore, many of the requested details cannot be extracted from the provided document.

Here's a summary of what can be extracted and what cannot:

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

The document describes various performance aspects that were evaluated to demonstrate substantial equivalence, but it does not present them in a formal table with specific acceptance criteria (e.g., "burst pressure > X mmHg") and corresponding reported values. Instead, it states that the device "performs at least as well as (not inferior to) the predicate ultrasonic device."

  • Evaluated areas: Active blade displacement, frequency, grasping and pulling force, shaft deflection, distal seal leakage, button activation force, jaw clamping force, temperature, isolated vessel burst pressures/hemostasis, coagulation and dissection speed, qualitative ratings of sealed tissue, thermal spread, and enterotomy formation speed and hemostasis.
  • Performance Outcome: "performs at least as well as (not inferior to) the predicate ultrasonic device (Harmonic ACE36E)"

2. Sample sized 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 for individual tests. The preclinical studies used "porcine" models.
  • Data Provenance: Porcine (animal) studies for preclinical evaluations. The document does not specify a country of origin for the studies.
  • Retrospective or Prospective: These were primarily prospective preclinical studies using animal models.

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. The "ground truth" here is based on objective measurements and observations in bench and animal studies (e.g., vessel burst pressure, tissue integrity), not on expert interpretations of medical images or data.

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

Not applicable. This type of adjudication method is used for establishing ground truth in expert-based studies, which is not what was performed here.

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, not an AI diagnostic tool. No MRMC study or AI assistance evaluation was performed.

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

Not applicable. This is a physical surgical device, not an algorithm. Performance was evaluated in non-clinical, preclinical (bench/animal), and usability studies, which involve the device in operation.

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

The "ground truth" in this context was established through:

  • Objective measurements in non-clinical (electrical/mechanical/functional) testing: e.g., direct measurements of active blade displacement, frequency, forces, leakage.
  • Preclinical (bench tissue/animal) evaluations: using direct observation, measurement, and histological assessment of tissue effects (e.g., isolated vessel burst pressures, coagulation speed, thermal spread, enterotomy formation).

8. The sample size for the training set:

Not applicable. The device is not an AI algorithm that requires a training set. Its development and validation are based on engineering design, material science, and physical testing.

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

Not applicable, as there is no training set for an AI algorithm.

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