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The mcompass Biofeedback Anorectal Manometry System is a manometry system for the measurement of anorectal pressures. It provides visual feedback (biofeedback) of the muscle action allowing the patient to modulate the activity of the anorectal muscles, thereby reeducating the pelvic floor muscles. It is used in a clinical setting and consists of a non-sterile disposable catheter (2-channel or 5-channel), a previously cleared reusable RMD FOB (and related battery charger), and software that resides on a tablet PC and that collects, records and displays the pressure data. Air-charged balloons are used to measure contractile pressures of the anorectal canal and simulate a range of bowel fullness levels, in addition to measuring locational pressure at the distal tip of the catheter. During the clinical procedure, the distal end of the catheter is inserted in the anus/rectum of the patient. The proximal end of the catheter is connected via an integrated cable to the handheld RMD FOB which transmits real-time pressure data wirelessly to the mcompass software on the PC

AI/ML Overview

The provided text describes a 510(k) premarket notification for the mcompass Biofeedback Anorectal Manometry System (K143031). It focuses on demonstrating substantial equivalence to a predicate device (mcompass Anorectal Manometry System, K120088) rather than detailing specific acceptance criteria and a study to prove they are met in the same way one might for a novel AI device.

Therefore, the requested information, particularly regarding AI-specific criteria, sample sizes for test/training sets, expert adjudication methods, and MRMC studies, is not present in this document. This document pertains to the regulatory clearance of a physical medical device.

However, I can extract the information that is present regarding performance data and validation:

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

Since this is a 510(k) submission for substantial equivalence to an existing device, a direct "acceptance criteria" table with numerical performance targets similar to a novel AI algorithm's sensitivity/specificity is not explicitly stated. Instead, the "performance data" section focuses on demonstrating that the new device meets various safety and functional standards, and that its technological differences do not raise new questions of safety or effectiveness compared to the predicate.

Category	Acceptance Criteria (Implied by Standards)	Reported Device Performance
Biocompatibility	Complies with ISO 10993-5 (Cytotoxicity), ISO 10993-11 (Systemic Toxicity), ISO 10993-10 (Intracutaneous Injection Test, Sensitivity) for surface-contacting devices (<24 hours mucosal exposure).	Meets the specified ISO 10993 standards for Cytotoxicity (Elution Test & Neutral Red Uptake), Systemic Toxicity, Intracutaneous Injection Test (Irritation), and Kligman Maximization Test (Sensitivity).
Mechanical Testing	Meets standards for physical characteristics, system leak pressure, and burst pressure.	• Physical characteristics• System leak pressure• Burst pressure(All implicitly met as "Performance data" is listed and no deficiencies are noted.)
Electrical Safety and EMC	Complies with current standards for electrical safety and Electromagnetic Compatibility (EMC).	Meets current standards for electrical safety and EMC.
Software Verification and Validation	Complies with FDA's "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 2005).	Software verification and validation testing were conducted, and documentation was provided as recommended by the FDA guidance.

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. The submission focuses on device engineering, safety, and software validation rather than a clinical performance study with a test set of patient data.

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 provided in the document. As mentioned, the submission doesn't detail a clinical performance study with a test set requiring expert-established ground truth.

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

This information is not provided in the document.

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 provided in the document. The device is not an AI-assisted diagnostic tool, but rather a system for anorectal manometry and biofeedback.

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

This information is not applicable as the device is not an algorithm performing a diagnostic task. It is a physical system with software for data collection, recording, and display. The software's performance was validated, but not as a "standalone algorithm" in the typical sense of AI product evaluation.

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

For the software verification and validation, the "ground truth" would be defined by the software requirements and design specifications, with correctness verified through testing against expected outputs. For the device components, the ground truth is adherence to the specified engineering standards (e.g., ISO, electrical safety norms) and mechanical properties. There is no biological "ground truth" mentioned in the context of a clinical study in this document.

8. The sample size for the training set

This information is not provided in the document. This is not an AI device that would typically have a "training set" of patient data.

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

This information is not provided in the document, as it is not applicable to this type of device submission.

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