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The MatriStem UBM™ Pericardial Patch is intended for the reconstruction and repair of the pericardium.

The MatriStem UBM Pericardial Patch is a 4-layer multi-laminate device comprised of stacked urinary bladder matrix (UBM) sheets. The Pericardial Patch serves as a patch to reconstruct the pericardium and restore the native anatomy. The Pericardial Patch is available in three sizes: 7x10 cm, 7x15 cm, and 10x15 cm. Each device is packaged in a double peel-open pouch and an outer carton. The device is terminally sterilized using electron-beam irradiation.

This document describes the regulatory submission for the MatriStem UBM™ Pericardial Patch, a medical device intended for the reconstruction and repair of the pericardium. It is a 510(k) premarket notification, which means the manufacturer (ACell, Inc.) is seeking to demonstrate that their device is substantially equivalent to legally marketed predicate devices, and therefore does not require a full premarket approval (PMA).

The information provided covers bench testing and an animal study to support the substantial equivalence claim. However, it's important to note that this submission does not involve an AI/ML-based device and therefore the questions relating to AI-specific acceptance criteria, multi-reader multi-case studies, expert adjudication methods, and training/test set ground truth establishment for an AI algorithm are not applicable to this document. The device is a biological patch, not a diagnostic or prognostic AI tool.

Therefore, many of the requested items regarding AI/ML aspects will be answered as "Not Applicable" or "No" as the study described is for a physical medical device.

Here's the breakdown based on the provided text:

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

Since this is a physical medical device and not an AI model, the acceptance criteria are based on physical, chemical, and biological properties, and functionality in an in vivo model.

Note: Specific quantitative acceptance criteria for most bench tests are not provided in this public summary but are typically part of internal design control documentation and would have been submitted to the FDA. The document states "All acceptance criteria were met" for the animal study, indicating the successful completion of the pre-defined endpoints.

2. Sample sizes used for the test set and the data provenance

• Test Set Sample Size (Animal Study):

  • Total pigs: 12
  • Sham group (no repair): 2 pigs
  • ACell MatriStem UBM Pericardial Patch group: 5 pigs
  • Predicate CorMatrix Pericardial Patch group: 5 pigs

• Data Provenance: The study was a "90-day Good Laboratory Practices (GLP) animal study" performed in a porcine (pig) model. The country of origin is not specified but generally, GLP studies adhere to international standards. It is a prospective animal study designed to evaluate the device.

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

• Not Applicable (N/A) for an AI/ML context. This is a physical medical device.
• For the animal study, the ground truth was established through objective biological and physiological assessments:
  • Histology evaluation: Performed by pathologists.
  • Full necropsy examination: Performed by veterinary pathologists.
  • Echocardiography measurements: Performed by specialists in echocardiography (likely veterinary cardiologists or trained technicians).
  • The document implies that these assessments were performed by qualified personnel as part of a GLP study, but the specific number and qualifications of individuals are not detailed in this summary.

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

• N/A for an AI/ML context. This pertains to consensus among human readers for image interpretation, which is not relevant for this device.
• For the animal study, the "adjudication" of results would rely on standardized GLP protocols for sample collection, pathology, and data analysis to ensure consistency and objectivity. Any disagreements in interpretation (e.g., in histology slides) would typically be resolved by senior pathologists or consensus panels within the pathology group, but this is not an "adjudication method" in the AI sense.

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 study was not done. This is a study for a physical implantable medical device, not an AI diagnostic/assistance tool.
• The comparative effectiveness was demonstrated by comparing the subject device to a predicate device and a sham in an animal model based on biological and physiological outcomes, not human reader performance.

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

• N/A. This is a physical medical device, not an algorithm.

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

• Pathology and Outcomes Data (from an animal model).
  • Histology evaluation: Provides microscopic ground truth on tissue response, cellular infiltration, and remodeling.
  • Full necropsy examination: Provides macroscopic ground truth on device integration and tissue health.
  • Echocardiography measurements: Provides functional ground truth on cardiac performance.
  • The "ground truth" for the device's performance in vivo was established by these objective biological and physiological assessments in directly implanted animals.

8. The sample size for the training set

• N/A. This is a physical medical device. There is no "training set" in the context of machine learning.
• The development process for this device would involve extensive internal research and development, materials characterization, and process optimization, but this does not constitute a "training set" for an AI model.

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

• N/A. As there is no AI training set, this question is not applicable.

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Cytal® Wound Matrix 3-Layer is intended for the management of wounds including: partial and full-thickness wounds, pressure ulcers, venous ulcers, diabetic ulcers, chronic vascular ulcers, tunnel/undermined wounds, surgical wounds (donor sites/grafts, post-Mohs surgery, post-laser surgery, podiatric, wound dehiscence), trauma wounds (abrasions, lacerations, second-degree burns, and skin tears), and draining wounds. The device is intended for one-time use.

Cytal® Wound Matrix 3-Layer is composed of a resorbable, porcine-derived, extracellular matrix (ECM) scaffold containing epithelial basement membrane, specifically known as urinary bladder matrix (UBM). The devices are supplied in fenestrated sheet configurations up to 16 cm x 35 cm and packaged in double peel-open pouches. The devices are terminally sterilized using electron beam irradiation. Cytal Wound Matrix 3-Layer is pre-hydrated with sterile saline and applied to the wound. The device can be cut to different sizes. The device is intended for one time use.

The document provides information on the Cytal® Wound Matrix 3-Layer and its substantial equivalence to a predicate device. However, it does not describe acceptance criteria or a study proving that the device meets those criteria in the typical sense of a diagnostic or AI device performance study.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (ACell, Inc. Cytal® Wound Matrix (K152721)) for regulatory clearance. This involves showing that the new device has "the same intended uses and similar indications, technological characteristics, and principles of operation" and that minor differences "raise no new issues of safety or effectiveness."

Therefore, many of the requested categories for a diagnostic or AI device study are not applicable or not explicitly detailed in this type of submission.

Here's a breakdown based on the provided text, addressing your questions where information is available and noting where it is not:

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

The document does not explicitly state "acceptance criteria" for clinical performance in the way one might for a diagnostic device (e.g., sensitivity, specificity thresholds). Instead, the performance testing aimed to show that the device "met the clinically relevant user needs, design inputs, and specifications" and functioned "as intended," demonstrating substantial equivalence.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample size: Not specified. The document refers to "bench testing" and "design validation testing" (clinician feedback and simulated use) but does not provide specific sample sizes for these tests.
• Data provenance: Not applicable in the context of clinical data for performance; this was bench and simulated use testing.

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)

• The document mentions "clinician feedback" for design validation. The number and qualifications of these clinicians are not specified.

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

• None specified. The document briefly mentions "clinician feedback" but does not detail any adjudication method for potential discrepancies or consensus building.

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 study was NOT done. This type of study (comparative effectiveness, human readers, AI assistance) is relevant for diagnostic AI devices. The Cytal® Wound Matrix 3-Layer is a wound dressing, not an AI or diagnostic device, so this type of study is not applicable or performed in this context.

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

• Not applicable. As a wound matrix, there is no "algorithm only" performance to evaluate. The device's performance is inherent in its material properties and interaction with biological systems.

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

• For the technical performance aspects (suture retention, tensile, hydration, etc.), the "ground truth" would be established by engineering and material science standards and specifications.
• For "design validation" via clinician feedback and simulated use, the "ground truth" is implied to be clinician judgment regarding the device functioning as intended and meeting user needs. This is not equivalent to a clinical ground truth like pathology or patient outcomes.

8. The sample size for the training set

• Not applicable. Since this is not an AI/machine learning device, there is no "training set."

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

• Not applicable. There is no training set for this type of medical device.

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