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The EndoRotor® System is intended for use in airway procedures including removal of granulation tissue and endobronchial lesions.

The EndoRotor® Airway Microdebridement System is a powered resection tool consisting of a power Console with Foot Control, Specimen Trap with pre-loaded filter, and a singleuse Catheter with a cutting tool mounted on the distal end. The EndoRotor's flexible design allows it to be used within the working channel of flexible bronchoscopes in tortuous paths. The Console houses the control panel, drive motor, vacuum control valve, and peristaltic irrigation pump drive. The Catheter includes a debriding cutter and allows for aspiration from the resection site through the bronchoscope working channel to the Specimen Trap.

The provided text describes regulatory information for a medical device (EndoRotor Airway Microdebridement System) and its substantial equivalence determination by the FDA. It does not contain information about acceptance criteria and a study that proves a device meets acceptance criteria in the context of an AI/algorithm-based diagnostic or assistive device.

Instead, the document details:

• Device Identification: EndoRotor Console, Catheter, Specimen Trap, Filter Set, Roll Stand (K190715).
• Intended Use: Airway procedures including removal of granulation tissue and endobronchial lesions.
• Regulatory Classification: Class II, product code ERL (Ear, nose, and throat electric or pneumatic surgical drill).
• Comparison to Predicate Device: XPS 3000 System (Medtronic XOMED, K041413). It highlights similarities in principle of operation (mechanical resection using rotational movement) and differences such as access (flexible bronchoscope vs. rigid), and components (specimen trap).
• Non-Clinical Testing: Biocompatibility, sterilization validation, pyrogenicity, shelf-life, packaging, transport, and functional testing for the catheter; design verification, power-up/set-up, functional, electrical safety, and electromagnetic compatibility testing for the console; procedural testing for the specimen trap. These tests "Met established acceptance criteria." However, specific numerical acceptance criteria and reported performance values are not detailed.
• Clinical Testing: No new clinical study was conducted. Substantial equivalence was based on prior clearance for gastrointestinal use (K181127) where the device demonstrated safety and performance in regions with thin tissue walls, implying its suitability for airway applications.

Therefore, I cannot provide the requested information regarding acceptance criteria and performance data for an AI/algorithmic device based on the provided text, as this document pertains to a mechanical surgical device. The questions about sample size of test sets, data provenance, expert ground truth, MRMC studies, standalone performance, training sets, and how ground truth was established are all relevant to AI/algorithmic device validation, which is not what this document describes.

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The EndoRotor® is intended for use in endoscopic procedures by a trained gastroenterologist to resect and remove tissue, not intended for biopsy, of the gastrointestinal (GI) system including post-endoscopic mucosal resection (EMR) tissue persistence with a scarred base and residual tissue from the peripheral margins following EMR.

The EndoRotor®, with the design modifications and expanded indications for use described in the current 510(k) premarket notification, will continue to be marketed as the EndoRotor®. The new EndoRotor® will be referred to as the "modified EndoRotor" in this 510(k) Summary.

The overall device description remains unchanged since initial FDA clearance. Both the predicate and modified EndoRotor® are powered resection tools consisting of a power console, foot control, specimen trap with pre-loaded filter, and a single-use resection catheter that is inserted into the working channel of a compatible endoscope. The design modifications to the EndoRotor® described in the current 510(k) premarket notification include enhancements to improve the ease of use of the console and catheter components as well as provide flexibility to the gastroenterologist.

The provided text describes modifications to an existing device, the EndoRotor®, and does not present an AI/ML device or its associated performance studies. Therefore, I cannot extract information related to AI/ML specific acceptance criteria, and study details like sample size for test sets, data provenance, expert qualifications, adjudication methods, MRMC studies, standalone performance, training set details, or ground truth establishment.

Instead, the document details non-clinical and clinical performance testing conducted to support the substantial equivalence of the modified EndoRotor® to its predicate device (K170120) and to support expanded indications for use.

Here's the relevant information about the acceptance criteria and the studies that prove the device meets them:

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

The document doesn't explicitly list acceptance criteria in a quantitative table format with corresponding numerical performance for the modified device in the same way an AI/ML device submission might. Instead, it states that:

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

• Non-clinical (Animal Testing for Predicate Device, applicable to modified):

  • Sample Size: 6 porcine animals (4 recovery, 2 acute) for mucosal resections, totaling 124 mucosal resections. Additionally, 4 animals for design validation and usability assessment.
  • Data Provenance: Porcine animal model.

• Clinical (Investigator-led study in UK):

  • Sample Size: 19 patients.
  • Data Provenance: Retrospective, from Queens Alexandra Hospital in Portsmouth, United Kingdom.

• Clinical (Commercial procedures in Western Europe):

  • Sample Size: 78 patients.
  • Data Provenance: Real-world commercial procedures in Western Europe (Austria, Germany, The Netherlands, Switzerland, and the United Kingdom). The document implies this data is also retrospective "compiled data provides real world clinical evidence".

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

• Clinical (Investigator-led study in UK):
  • Number of Experts: Not explicitly stated, but the study was conducted by "Gastroenterologists" in Queens Alexandra Hospital.
  • Qualifications: "trained gastroenterologist" as per the Indications for Use. The study authors are listed as Khandiah K, Subramanian S, Thayalasekaran S, Chedgy F, and Bhandari P, implying multiple gastroenterologists were involved.
• Clinical (Commercial procedures in Western Europe):
  • Number of Experts: Not explicitly stated, but implies "Physicians" performing the procedures.
  • Qualifications: "trained gastroenterologist" as per the Indications for Use.

4. Adjudication method for the test set:

Not explicitly mentioned for the clinical studies. Decisions appear to have been made by the treating gastroenterologists.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done:

No, an MRMC comparative effectiveness study was not done. This is a medical device submission, not specifically an AI/ML device, and the studies performed focused on the safety and effectiveness of the device itself rather than human reader improvement with AI assistance.

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

Not applicable, as this is a medical device (EndoRotor®), not an algorithm. The device is always under the control of a trained physician.

7. The type of ground truth used:

• Non-clinical (Animal Testing): Histopathological assessment of tissue response (favorable and clinically acceptable tissue response).
• Clinical (Investigator-led study in UK & Commercial procedures): Physician assessment of lesion presence/scarring and procedure outcomes (disease eradication, luminal preservation, avoidance of surgery, no incidences of perforation or delayed bleeding). This can be considered expert consensus/clinical outcomes data.

8. The sample size for the training set:

Not applicable. This is not an AI/ML device; therefore, there isn't a "training set" in that context. The device's design improvements were based on feedback and engineering enhancements.

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

Not applicable for the same reason as above.

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