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510(k) Data Aggregation
(24 days)
MYOSURE CONTROL UNIT
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 3 mm working channel.
Here's an analysis of the provided text regarding the MyoSure Hysteroscopic Tissue Removal System, extracting the requested information about acceptance criteria and the supporting study:
The provided text (K120593 Premarket Notification) describes a modification to an existing device, the MyoSure Hysteroscopic Tissue Removal System. The modification specifically concerns the motor within the control unit, which now rotates bidirectionally. The submission aims to demonstrate substantial equivalence to the predicate device (K100559).
Acceptance Criteria and Device Performance
The core of the performance testing is to demonstrate equivalence to the predicate device. The acceptance criteria are implicitly tied to the performance characteristics of the predicate device, K100559. The study's outcome is that the modified device meets or is equivalent to these established characteristics.
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria (Implicit from Predicate Device) | Reported Device Performance (MyoSure K120593) |
---|---|
Fibroid cutting performance equivalent to predicate | Modified MyoSure System's fibroid cutting performance is equivalent to that of the predicate device. |
Cutter durability over time equivalent to predicate | Cutter durability over time is equivalent for the modified and predicate MyoSure Systems. |
Heat generation over time equivalent to predicate | Heat generation over time is equivalent for the modified and predicate MyoSure Systems. |
Meets predicate's functional specifications | Modified MyoSure System meets the same functional and performance specifications as the predicate MyoSure System. |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not explicitly state the specific sample sizes (e.g., number of fibroids tested, number of cutting cycles, duration of heat generation tests) used for the performance verification testing.
- Sample Size: Not explicitly stated. The testing methodology used was the same as for the predicate device (K100559), implying similar rigor but not detailing specific numbers.
- Data Provenance: Not explicitly stated, but it would have been generated internally by Hologic, Inc. as part of product development and regulatory submission. The study is described as "Performance verification testing" and "Verification/validation testing," which are typically prospective tests conducted on the modified device under controlled laboratory or simulated conditions. There is no mention of retrospective patient data.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
This type of information is not applicable to this submission. The tests described are engineering performance tests of a mechanical device (cutting efficacy, durability, heat generation), not clinical studies requiring expert interpretation of medical images or patient outcomes. The "ground truth" here is objective physical measurement or operational equivalence.
4. Adjudication Method for the Test Set:
This is not applicable. As mentioned above, the testing involves objective engineering measurements and comparisons, not subjective interpretations requiring adjudication among experts.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:
No, an MRMC comparative effectiveness study was not done. The submission focuses on the device's mechanical and functional performance, not the diagnostic or interpretative performance of human readers, with or without AI assistance. The device is a surgical tool, not an AI diagnostic system.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done:
Not applicable in the context of AI. This device is hardware with an embedded software controller for its motor. The "standalone" performance here refers to the device operating according to its design specifications. The testing performed is essentially "standalone performance" in the sense that the device's cutting, durability, and heat generation were tested independently to ensure they met the established benchmarks (i.e., equivalence to the predicate).
7. The Type of Ground Truth Used:
The "ground truth" for this engineering study is based on:
- Objective Engineering Measurements: Direct measurements of cutting performance (e.g., speed, efficacy on tissue simulants), durability (e.g., number of cycles before failure), and heat generation (e.g., temperature readings).
- Functional Equivalence to Predicate Device: The established performance characteristics and specifications of the legally marketed predicate device (K100559) serve as the benchmark for comparison.
8. The Sample Size for the Training Set:
Not applicable. This device does not involve machine learning or AI that would require a "training set" in the conventional sense. The "training" for such a device would be its engineering design and manufacturing processes.
9. How the Ground Truth for the Training Set was Established:
Not applicable for the same reason as point 8.
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