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The Myosure Hysteroscopic Tissue Removal System is intended for hysteroscopic intrauterine procedures by a trained gynecologist to resect and remove tissue including submucous myomas and endometrial polyps.

The modified Myosure Hysteroscopic Tissue Removal System consists of the following procedural components which are identical to those found in the predicate Myosure System:

• . Myosure Control Unit
• . Myosure Tissue Removal Device
• Myosure Foot Pedal .
  The Myosure Control Unit contains an electric motor and software controller that drives the Myosure Tissue Removal Device. The Control Unit motor is activated and deactivated by the Myosure Foot Pedal. The Myosure Tissue Removal Device is a tissue morcellator that is connected to the Control Unit via a flexible drive cable. The morcellator's cutter blade is controlled by a drive system that enables simultaneous rotation and reciprocation of the cutter. The cutter is also connected to a vacuum source which aspirates resected tissue through a side-facing cutting window in the device's outer tube. Distension fluid and resected tissue are transported from the Myosure Tissue Removal Device to a tissue trap and vacuum canister via a tube protruding from the proximal end of the Tissue Removal Device. The Myosure Hysteroscopic Tissue Removal System is compatible with commercially available fluid management systems and may be used with hysteroscopes that have a straight 4 mm working channel.

The provided text describes a 510(k) summary for the Hologic MyoSure Tissue Removal Device. This submission is for a modified version of an existing device, and therefore the performance testing focuses on demonstrating equivalence to the predicate device, rather than establishing novel performance metrics.

Here's an analysis of the provided information against your requested criteria:

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

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: Not explicitly stated. The document mentions "performance verification testing" and "test interval" but does not quantify the number of devices, tests, or tissue samples used.
• Data Provenance: Not explicitly stated. It refers to "the same methodology as was used in support of the predicate MyoSure System 510(k) submission (K122498)." This suggests in-house lab testing rather than human clinical data. No country of origin is mentioned. The testing appears to be prospective lab testing.

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 is a device equivalence study based on functional performance, not an AI or diagnostic tool where expert ground truth is typically established. Therefore, this question is not applicable in the context of this 510(k) submission.

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

Not applicable. This is a device performance study, not a study where human reader adjudication of results is relevant.

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 device equivalence study for a hysteroscopic tissue removal system, not an AI or diagnostic tool.

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

Not applicable. This is a medical device, not an algorithm, and its performance is evaluated in direct comparison to a predicate device's functional characteristics.

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

The "ground truth" in this context is the established performance and specifications of the predicate MyoSure Hysteroscopic Tissue Removal System (K122498). The study aims to prove that the modified device's performance aligns with these established benchmarks.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. As above, this is not an AI/machine learning device.

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