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The TROKAMED MORCELLATOR is a motorized unit for morcellating and extracting tissue during laparoscopic procedures, in general surgery, gynecology including the removal of myomas and hysterectomy, and urology including nephrectomy.

The TROKAMED MORCELLATOR is comprised of a control unit, a grip module, two foot pedals, a power cord, a control cable and a flexible shaft, in addition to cutting modules, trocar sheaths, trocars, and forceps.

This document is a 510(k) summary, which is a premarket notification submitted to the FDA to demonstrate substantial equivalence to a legally marketed predicate device. It is not a detailed study report designed to present specific acceptance criteria and performance data for a novel device, nor an AI device. Therefore, much of the requested information regarding detailed acceptance criteria, study methodologies, and AI-specific metrics is not available in the provided text.

Based on the provided text, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance
This document does not specify quantitative acceptance criteria or detailed performance metrics against those criteria in a tabular format as would be found in a study report. Instead, it relies on demonstrating compliance with recognized consensus standards and substantial equivalence to predicate devices.

For "Performance Data," the document states:
"The device complies with applicable requirements of recognized consensus standards IEC 60601-1 (Electrical Safety), IEC 60601-1-2 (Electromagnetic Compatibility) and Medical Device Directive 93/42/EEC, and is manufactured at an ISO 13485 facility."

This indicates that the "acceptance criteria" are compliance with these listed standards. The "reported device performance" is that the device "complies" with these standards.

2. Sample size used for the test set and the data provenance
Not applicable. This is a medical device (morcellator), not an AI algorithm. The performance data refers to compliance with safety and compatibility standards, not a clinical test set with a specific sample size of data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This is a medical device, not an AI algorithm requiring expert-established ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This is a medical device, not an AI algorithm requiring adjudication for a test set.

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 a medical device (morcellator), not an AI-assisted device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a medical device (morcellator), not an AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. For this type of device, "ground truth" would be compliance with engineering and safety standards, and confirmation that its functional performance is similar to predicate devices, rather than a clinical ground truth for diagnostic accuracy.

8. The sample size for the training set
Not applicable. This is a medical device (morcellator), not an AI algorithm that uses a training set.

9. How the ground truth for the training set was established
Not applicable. This is a medical device (morcellator), not an AI algorithm.

Summary based on the document:

The Trokamed Morcellator is a motorized unit for tissue morcellation during laparoscopic procedures. Its "acceptance criteria" appear to be compliance with established international standards for electrical safety (IEC 60601-1), electromagnetic compatibility (IEC 60601-1-2), and the Medical Device Directive 93/42/EEC, along with manufacturing under ISO 13485. The "study" for these criteria is the testing performed to demonstrate compliance with these standards, the details of which are not provided in this summary but are implied to have been conducted by the manufacturer. The primary method of demonstrating its safety and effectiveness for FDA 510(k) clearance is by showing substantial equivalence to existing predicate devices (K993801, K061180, K041610, K960640), noting that "minor differences in design and dimensions have no effect on the performance, function or intended use of the device and do not raise any new issues of safety and effectiveness." There is no mention of AI or machine learning components in this device or its assessment.

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