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The PneumoLiner device is intended for use as a multiple instrument port and tissue containment system during minimally invasive gynecologic laparoscopic surgery to enable the isolation and containment of tissue, considered benign, resected during single-port or multi- site laparoscopic surgery during power morcellation and removal. When used in women with fibroids, the PneumoLiner is for women who are pre-menopausal and under age 50. The PneumoLiner is compatible with bipolar or electromechanical laparoscopic power morcellators that are between 15mm and 18mm in shaft outer diameter and 135mm and 180mm in shaft working length and which have an external component that allows for the proper orientation of the laparoscope to perform a contained morcellation.

The ASC PneumoLiner is an inflated morcellation containment system that allows for containment of gynecological tissue, cells and fluids during power morcellation and removal. It is a sterile single use device and requires the surgeon to successfully complete a validated training program before use. The ASC PneumoLiner is for clinical use in a hospital or surgical center operating room. The device consists of the following components: the Retractor Introducer, Boot Assembly, the PneumoLiner Introducer and the PneumoLiner. The first three components (Retractor, Retractor Introducer and Boot Assembly) are used to retract an incision in the abdominal wall and to allow for the introduction of laparoscopic instruments and the PneumoLiner Bag while under pneumoperitoneum and with vision from a laparoscope. The PneumoLiner Bag is introduced via the PneumoLiner introducer and the large valve on the Boot Assembly. The PneumoLiner is intended for use in gynecological power morcellation. It is intended to form a complete containment barrier from the spillage of liquids, cells and tissue from the time the tissue or organ is excised and encapsulated in the PneumoLiner bag, throughout the morcellation procedure and withdrawal of the containment bag with accompanying liquids and debris.

Based on the provided text, the device in question (PneumoLiner) is a medical device for contained morcellation, not an AI/ML powered device. Therefore, the information requested about acceptance criteria and studies proving the device meets them, especially those pertaining to AI/ML device performance (like MRMC studies, standalone algorithm performance, number of experts for ground truth, training set size and ground truth establishment), is largely not applicable to this document.

The document describes a 510(k) submission for a revision to the labeling (indications for use and contraindications) of an existing device, and some non-clinical performance testing related to packaging and shelf-life. There are no mentions of AI/ML or a "study that proves the device meets the acceptance criteria" in terms of an AI/ML algorithm's clinical performance.

However, I can extract the relevant information regarding the changes made and the supporting information for those specific changes, which are primarily based on clinical literature reviews rather than a new clinical study of the device itself.

Since the request is about acceptance criteria and a study proving the device meets them, and this document describes a labeling change for a physical medical device, I will reframe the answer based on the information available:

Acceptance Criteria and Study for PneumoLiner (K192898 Labeling Revision)

The provided document (K192898 510(k) clearance letter) describes a submission primarily for a revision to the Indications for Use and contraindications of an existing medical device, the PneumoLiner. It also includes updated non-clinical performance data for shelf-life and packaging. It does not describe a clinical study of the device's efficacy or safety as an AI/ML system.

Therefore, many of the requested points related to AI/ML device performance are not applicable. I will address the relevant points based on the information provided in the document.

1. Table of Acceptance Criteria and Reported Device Performance

For this specific 510(k), the "acceptance criteria" appear to be related to the justification of the labeling changes and the non-clinical performance of packaging and shelf-life. The "performance" is demonstrated through literature review for the labeling changes and specific testing for packaging/shelf-life.

• JMIG Special Article, "Morcellation during Uterine Tissue Extraction: An Update by the Tissue Extraction Task Force Members" (2018).
• FDA Updated Assessment of the Use of Laparoscopic Power Morcellators to Treat Uterine Fibroids (December 2017).
• Seidhoff et al. (2017) meta-analysis.
  These sources stratify the risk of occult leiomyosarcoma (LMS) by age. |
  | Non-Clinical Performance (Shelf-Life & Packaging) | Sterilization validity. | Sterilization validated to ISO 11137-1:2006 and ISO 11137-2:2013. |
  | | Shelf-life validity (updated from 1 year to 3 years). | Tested on samples accelerated aged which underwent simulated shipping, including:
• Sterile Barrier Integrity testing
• Visual inspection per ASTM F1996:2009 (2013)
• Bubble leak testing per ASTM F2096:2011
• Seal strength per ASTM F88:2009.
• Device functionality (leak testing, bond/material strength testing). |

2. Sample Size Used for the Test Set and Data Provenance

This is not applicable for a clinical performance test of an AI/ML algorithm. The "test set" for the labeling changes was the existing body of clinical literature. The provenance is explicitly cited as published academic journals and FDA assessments.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This is not applicable as an AI/ML algorithm was not being evaluated. The "ground truth" for the labeling changes was derived from peer-reviewed clinical literature and FDA assessments, which represent the consensus or findings of multiple medical experts and researchers in the field. The specific number of individual experts directly involved in "establishing ground truth" for this submission is not quantified in the document, as it relied on previously established and published data.

4. Adjudication Method for the Test Set

This is not applicable as an AI/ML algorithm was not being evaluated. The "adjudication" for the literature review was implicitly handled through the peer-review process of the cited publications and the FDA's own assessment methodologies.

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. This type of study is relevant for evaluating the impact of AI assistance on human performance, which is not the subject of this 510(k) submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No, a standalone algorithm performance study was not done. This submission is not for an AI-powered device.

7. The Type of Ground Truth Used

For the labeling changes, the "ground truth" was derived from published clinical literature, meta-analyses, and FDA assessments regarding the risk stratification of occult leiomyosarcoma (LMS) by age in women with presumed fibroids. This effectively represents:

• Expert Consensus (via peer-reviewed publications): The conclusions drawn in the cited articles reflect the collaborative findings and consensus (or significant findings) of experts in gynecology and oncology.
• Outcomes Data (clinical studies summarized in literature): The literature reviewed is based on real-world clinical outcomes and patient data that informed the risk stratification.

8. The Sample Size for the Training Set

This is not applicable as there was no AI/ML algorithm to train.

9. How the Ground Truth for the Training Set Was Established

This is not applicable as there was no AI/ML algorithm to train.

In summary, the provided document describes a regulatory submission for a physical medical device (PneumoLiner) that involves labeling revisions and non-clinical performance testing for shelf-life and packaging. It is crucial to note that this is not an AI/ML-powered device and therefore, most of the questions related to AI/ML study methodologies are not relevant to this specific 510(k) clearance letter. The justification for labeling changes was based on existing clinical literature and expert-driven assessments.

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The PneumoLiner device is intended for use as a multiple instrument port and tissue containment system during minimally invasive gynecologic laparoscopic surgery to enable the isolation and containment of tissue considered benign, resected during single-port or multi-site laparoscopic surgery during power morcellation and removal. The PneumoLiner is compatible with bipolar or electromechanical laparoscopic power morcellators that are between 15 mm and 18 mm in shaft outer diameter and 135 mm and 180 mm in shaft working length and which have an external component that allows for the proper orientation of the laparoscope to perform a contained morcellation.

The PneumoLiner System consists of two main components:

• A laparoscopic multi-instrument port
• Tissue pouch (PneumoLiner) intended to provide a separately contained space within the abdomen for the safe morcellation of tissue

As depicted in Figure 1 below, the laparoscopic multi-instrument port consists of the Retractor, Retractor Introducer and the Boot Assembly.

The provided text describes the acceptance criteria and performance of the PNEUMOLINER system, but it does not include a study that directly compares human readers with and without AI assistance (a multi-reader multi-case comparative effectiveness study). The device itself is a medical containment system, not an AI-powered diagnostic or assistive tool. Therefore, some of the requested information regarding AI-specific studies will not be present.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document details extensive performance testing. Here, we compile a table based on the "Design Verification" section, which includes quantitative acceptance criteria, and other key performance tests.

Note: (b) (4) indicates redacted information, typically quantitative values or specific methods.

2. Sample Size Used for the Test Set and Data Provenance

• Barrier Testing (Filter Test):
  • Accelerated Aged: 32 test samples (plus 1 control).
  • Provenance: Bench testing, in-vitro.
• Barrier Testing (Immersion Test):
  • Initial Group: 22 test samples (from an initial 35, with 6 excluded for initial leaks and 4 for aberrant bacteria).
  • Additional Group: 10 test samples (from an initial 24, with 3 excluded for initial leaks and 6 for contamination).
  • Total for Analysis: 32 samples (plus controls).
  • Provenance: Bench testing, using TSB (Tryptone Soya Broth) and B. diminuta.
• Bench Testing (Preliminary):
  • Laparoscope Puncture: 30 test samples.
  • Tenaculum Damage: 30 material samples per each of 5 different tenacula.
  • Pressure/Burst Testing: 30 PneumoLiner System samples.
  • Obstruction Testing: 30 samples.
  • Provenance: Bench testing, in-vitro.
• Design Verification (Table 1): Over 30 device samples per test. (Specific counts not always provided but stated as "30 or more").
  • Provenance: Bench testing, in-vitro.
• Clinical Simulation of Morcellation: 34 PneumoLiner pouches and 5 PneumoLiner System boot assembly and retractors.
  • Provenance: Simulated use in a surgical simulation test rig (SSTR) using animal tissue (lamb heart, beef tongue).
• Training Validation: 34 participants, each using at least 3 PneumoLiner Systems. A total of 102 PneumoLiner Systems were used.
  • Provenance: Porcine model (animal study, in-vivo simulation).
• Design Validation: 31 participants, each using one PneumoLiner System.
  • Provenance: Porcine model (animal study, in-vivo simulation).

No Human Data: All listed studies are non-clinical (bench or animal models). Therefore, there is no country of origin for human data, as no human data was used directly to support device performance. The studies are prospective in design.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

This device is not an AI diagnostic device. Therefore, the concept of "experts establishing ground truth" in the traditional sense of medical image interpretation (e.g., radiologists reviewing images) does not directly apply here.

However, for the Training Validation and Design Validation studies, participants included "surgeons with advanced training in laparoscopic techniques," with varying levels of experience (categorized as "Experienced" and "Inexperienced"). These are the "users" of the device, whose ability to correctly use the device and avoid damage established a form of "ground truth" for usability and safety in a simulated clinical scenario.

• Training Validation: 34 participants (experts/users).
• Design Validation: 31 participants (experts/users).

Their qualifications are described as participants with a "range of experience in laparoscopic procedures," with the device being intended for "surgeons with advanced training in laparoscopic techniques."

4. Adjudication Method for the Test Set

Adjudication methods (like 2+1, 3+1) are typically used for establishing consensus on ground truth in studies involving expert review of data (e.g., radiology reads). As this is a study about the physical performance and usability of a medical device, such an adjudication method is not applicable.

Instead, the "ground truth" for the performance tests was based on:

• Pre-defined objective criteria (e.g., absence of bacterial growth, lack of leaks, force thresholds, time limits, visual inspection for defects).
• For the simulated use studies (Training and Design Validation), the "ground truth" on successful device use and absence of leaks was assessed by a "test coordinator" or the test team against clearly defined pass/fail criteria (e.g., visual inspection for leaks after a water test).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done.

MRMC studies typically compare multiple human readers' diagnostic performance on multiple cases, often to evaluate the impact of an AI algorithm on reader accuracy or efficiency. The PNEUMOLINER is a physical medical device, not an AI diagnostic tool, so this type of study is not relevant to its assessment.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No, a standalone performance study in the context of an AI algorithm was not done.

This terminology applies to AI algorithms. The PNEUMOLINER is a physical device that requires human operation. Its "standalone" performance is measured through bench testing and simulated use, where the device itself is tested against physical parameters (e.g., impermeability, strength, ability to contain tissue). These tests were conducted without human interaction beyond operating the test equipment or, in simulations, the device itself.

7. The Type of Ground Truth Used

The ground truth used for the various performance tests includes:

• Objective Physical Measurements: Force thresholds, pressure levels, time metrics, visual inspection for damage, dimensional accuracy.
• Biological Impermeability: Absence of bacterial growth (B. diminuta) after challenge.
• Integrity Assessment: Absence of leaks after water filling and visual inspection.
• Usability/Safety: Successful setup and operation of the device by trained users, and absence of device compromise (damage/leakage) in simulated clinical scenarios (porcine models). This is based on observation by test coordinators against predefined success/failure criteria.

8. The Sample Size for the Training Set

The concept of a "training set" typically refers to data used to train machine learning models. As the PNEUMOLINER is a physical medical device and not an AI algorithm, there is no "training set" in this sense.

However, if we interpret "training set" as the data used to inform the design and development of the device (before formal verification/validation), or the data used for the training program for users, then:

• Device Development Data: The document mentions "preliminary tests intended to generate acceptance criteria for their design verification tests as well as to validate the surgical simulator and training rig." These tests (e.g., Laparoscope puncture (30 samples), Tenaculum damage (150 samples), Powered Morcellation (5 samples), Pressure/Burst (30 samples), Obstruction Testing (30 samples)) could be considered analogous to data used in the formative stages.
• User Training Program Data: The "Training Validation" study itself involved 34 participants using a total of 102 PneumoLiner Systems in a porcine model. This study validated the effectiveness of the user training program, which is crucial for the device's safe and effective use.

9. How the Ground Truth for the Training Set Was Established

Again, applying the AI model analogy, there is no "ground truth" for an AI training set here.

If referring to the "Training Validation" study for users:

• The ground truth was established by objective observation of user performance by a study coordinator against predefined criteria for successful setup, use, and removal of the device, as well as post-procedure leak testing of the PneumoLiner pouch. The Instructions for Use (IFU) served as the standard against which user performance was evaluated. The outcome was binary: successful execution of steps and no leaks.

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