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The Avenda Health Treatment System is indicated for use in surgical applications requiring the ablation, vaporization, excision, incision, and coagulation of soft tissue in areas of surgery including: cardiovascular thoracic surgery (excluding the heart and the vessels in the pericardial sac), dermatology, ear-nose-throat surgery, gastroenterology, general surgery, gynecology, head and neck surgery, neurosurgery, orthopedics, pulmonology, radiology, adiology, and urology, at a wavelength of 980nm.

The Avenda Health Treatment System ("Treatment System") is a thermal laser ablation system that causes coagulation necrosis of soft tissue. The Treatment System consists of the capital system Workstation and the single use Laser Applicator Kit. The Workstation contains core system hardware and software, provides the System's touchscreen user interface (UI), and serves as a "hub" to facilitate the connectivity of other System components. The Laser Applicator Kit consists of two patient-contacting disposable components, the Laser Catheter, and the Thermal-Optical Probe ("TOP"), which facilitate delivery of laser energy and monitoring of temperature, respectively. The Treatment Monitoring Software, which operates on the Workstation, provides the UI for controlling the device, displays previously generated patient and treatment plan information for the procedure, and actively monitors the treatment progress during a procedure by displaying output from the TOP.

The Treatment System is additionally used with an off-the-shelf accessory, the Tubing Set, which transports saline in a closed-loop system between the Workstation and Laser Catheter to provide cooling of the Laser Catheter. The Treatment System further includes an optional patient-contacting disposable accessory, the Multi-Channel Needle Guide ("MCG"), which may be used to attach an ultrasound probe to the Laser Catheter and TOP for enhanced visualization tracking, if desired.

The provided text describes a 510(k) premarket notification for the Avenda Health Treatment System, a laser ablation system for soft tissue coagulation. It focuses on demonstrating substantial equivalence to predicate devices rather than proving a new device meets specific acceptance criteria through clinical studies. Therefore, much of the requested information regarding "acceptance criteria" and "study that proves the device meets acceptance criteria" in the context of an AI/Machine Learning (ML) device is not directly applicable or available in this document.

The document states: "[807.92(b)(2)] Clinical Testing Summary: No clinical testing was conducted to support this 510(k) Premarket Notification." This means there was no human-in-the-loop study (MRMC) or standalone algorithm performance study performed for this submission to evaluate its effectiveness in a traditional clinical setting against a ground truth.

Instead, the submission relies on non-clinical bench testing to demonstrate that the device is as safe and effective as its predicate devices, focusing on the system's physical and technical performance.

Here's a breakdown of the requested information, highlighting what is available and what is not:

1. Table of acceptance criteria and the reported device performance:

Since no clinical efficacy acceptance criteria for an AI/ML component are presented, the "acceptance criteria" here refers to the performance of the physical device as demonstrated through non-clinical testing.

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

• Test set sample size: Not applicable/not specified for clinical testing, as no clinical testing was performed. For non-clinical bench testing, the sample sizes would refer to the number of physical devices or components tested, but these details are not provided in the summary.
• Data provenance: Not applicable for clinical data. For non-clinical testing, the data would originate from the manufacturer's internal testing facilities.

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

Not applicable, as no clinical ground truth was established due to the absence of clinical testing.

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

Not applicable, as no clinical testing requiring expert adjudication was performed.

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:

No, an MRMC comparative effectiveness study was not done. The document explicitly states, "No clinical testing was conducted to support this 510(k) Premarket Notification." The device is a laser ablation system, not an AI/ML diagnostic or assistive tool for human readers.

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

No, a standalone performance study was not done in the context of an AI/ML algorithm. The device is a physical laser system, and its performance was evaluated through non-clinical bench testing.

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

No clinical ground truth (expert consensus, pathology, outcomes data) was used or established, as no clinical testing was conducted. The "ground truth" for this submission are the established engineering and safety standards for medical devices and the performance characteristics of the predicate devices, against which the proposed device's physical and electrical performance was compared.

8. The sample size for the training set:

Not applicable, as there is no mention of an AI/ML component or a "training set" for such a component in the context of this 510(k) submission.

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

Not applicable, as there is no mention of an AI/ML component or a "training set" in the context of this 510(k) submission.

In summary, the provided document outlines a 510(k) submission for a physical medical device (a laser ablation system) that achieved clearance based on demonstrating substantial equivalence through non-clinical bench testing. It does not involve AI/ML components, clinical trials, or the establishment of ground truth for diagnostic or assistive accuracy.

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