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The PowerX Lipo System is intended for the removal of tissues or fluids from the body during general surgical procedures including suction lipoplasty for the purpose of aesthetic body contouring.

The PowerX Lipo System consists of three components: electronic controller with software, handpiece, and cannula. The handpiece is connected to the controller and to an independent aspiration source. The controller sends electronic signals to the handpiece and thereby controls the motion of the cannula that is fitted to the distal end of the handpiece.

The provided document is a 510(k) Pre-Market Notification for the PowerX Lipo System. It claims substantial equivalence to a predicate device, K110255, also named PowerX Lipo System.

This document describes a medical device (a suction lipoplasty system) rather than an AI/ML-driven diagnostic or prognostic device. Therefore, the typical acceptance criteria and study designs involving AI performance metrics (like sensitivity, specificity, AUC, human-in-the-loop studies, multi-reader multi-case studies, expert consensus for ground truth) as outlined in the prompt are not applicable to this submission.

The "acceptance criteria" for this device are based on its substantial equivalence to a predicate device, meaning it has the same intended use, similar technological characteristics, and safety and effectiveness profiles when tested against applicable non-clinical standards.

Here's how to interpret the provided information in the context of a 510(k) for a medical device:

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

The "acceptance criteria" here relate to the device meeting performance specifications and safety standards comparable to the predicate device. The document explicitly states:

And also lists compliance with electrical standards:

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

For this type of device, a "test set" in the AI/ML sense (e.g., a set of medical images) is not applicable. The testing here refers to engineering and bench testing to demonstrate compliance with performance and safety standards. The document does not specify sample sizes for these tests (e.g., how many cannulas were tested for deformation resistance), but often these are done on a representative sample to ensure manufacturing quality and design verification. Data provenance is not specified as it's not a clinical study on patient data.

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

Not applicable. "Ground truth" in this context is established by engineering specifications, international standards (IEC, ISO), and performance testing rather than expert medical interpretation of images.

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

Not applicable. This is not a study requiring adjudication of diagnostic findings.

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 is not an AI-assisted diagnostic device.

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

Not applicable. This is a physical medical device, not an algorithm.

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

The "ground truth" for this device's performance is established by engineering specifications, regulatory standards (e.g., IEC 60601-1, ISO 10079-1), and the performance characteristics of the predicate device. For example, a "ground truth" for suction vacuum might be a calibrated pressure gauge reading that matches the specified 20 inHg.

8. The sample size for the training set:

Not applicable. There is no AI/ML model for which a training set would be used.

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

Not applicable.

In summary: The provided document is a standard 510(k) submission for a traditional medical device (suction lipoplasty system). The "acceptance criteria" are met by demonstrating substantial equivalence to a legally marketed predicate device through engineering and non-clinical performance testing against established safety and performance standards. The questions related to AI/ML software performance are not relevant to this specific device submission.

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The Sound Surgical Technologies LLC PowerX Lipo System is intended for the removal of tissue or fluids from the body during general surgical procedures including suction lipoplasty for the purpose of aesthetic body contouring.

The Sound Surgical Technologies LLC (Sound) PowerX Lipo System (PowerX) consists of three major components: (1) an electronic Controller with software, (2) an electronic Handpiece, and (3) a reusable, sterilizable Cannula. The Handpiece is connected to the Controller and to an independent aspiration source. The Controller sends electronic signals to the Handpiece and thereby controls the motion of the cannula that is fitted to the distal end of the Handpiece. The Sound PowerX is a prescription device, and is intended for use by trained medical personnel.

The provided document is a 510(k) summary for the Sound Surgical Technologies LLC PowerX Lipo System. It describes the device, its intended use, and various performance tests conducted to demonstrate its safety and effectiveness. However, it does not include information about acceptance criteria and a study that proves the device meets those criteria in the context of diagnostic accuracy, which is typically what such a request implies.

The "Performance Testing" section states that "The Sound PowerX was tested for performance in accordance with its predetermined specifications as specified in Section 11, Device Description - Performance Specifications, of this submission. Test results indicate that the Sound PowerX complies with its predetermined specification." However, Section 11 is not provided in the snippet, so the specific performance specifications are unknown.

The document does provide information on acceptance criteria and testing for aspects like sterilization, biocompatibility, software validation, electrical safety, and electromagnetic compatibility. This is generally summarized as compliance with recognized standards.

Here's a breakdown of the information that can be extracted from the provided text, and significant gaps where information related to diagnostic accuracy would typically be found:

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, specific performance specifications for the device's primary function (tissue/fluid removal) are not detailed in the provided excerpt beyond a general statement of compliance. The other "performance" criteria relate to general medical device safety and functionality.

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

This information is not provided in the document for any of the performance tests. The document refers to "test results" but does not detail the nature of these tests in terms of sample size or data provenance that would be typical for a diagnostic accuracy study.

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)

This information is not applicable/not provided. The device is a "Suction lipoplasty system" meant for "removal of tissue or fluids," not a diagnostic device that relies on expert interpretation of output to establish ground truth.

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

This information is not applicable/not provided for the same reasons as point 3.

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

This information is not applicable/not provided. The device is not a diagnostic AI system, and therefore, MRMC studies and AI assistance metrics are not relevant to its evaluation as described.

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

This information is not applicable/not provided as it is not a diagnostic algorithm. The device itself is standalone in its mechanical/electronic function, but this question typically refers to the performance of a diagnostic algorithm in isolation.

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

This information is not applicable/not provided in the context of diagnostic "ground truth." The "ground truth" for the device's technical performance would be its ability to meet its engineering specifications (e.g., proper motor function, suction power, sterilization efficacy), which are implicitly based on established engineering principles and medical device standards.

8. The sample size for the training set

This information is not applicable/not provided. This question typically refers to the development of machine learning algorithms. The device's software is stated to be designed and developed "according to a robust software development process" and "rigorously verified and validated," implying standard software engineering practices rather than machine learning training sets.

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

This information is not applicable/not provided for the same reasons as point 8.

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