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PliaFX® Flo is indicated for bony voids or gaps that are not intrinsic to the bony structure. It is indicated to be placed into the bony voids or gaps of the skeletal system (e.g., the extremities, spine and pelvis). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. This product provides a bone void filler that remodels into the recipient's skeletal system.

PliaFX® Flo Flowable Demineralized Fibers is a sterile, freeze-dried, human bone allograft product consisting of demineralized bone matrix fibers combined with USP grade glycerol/glycerin. The subject device is pre-filled in a 3cc or 14cc delivery syringe based on product volume. The 3cc syringe configuration also includes an optional female luer cap.

This appears to be a 510(k) summary for a medical device called PliaFX Flo, a resorbable calcium salt bone void filler. The document focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study to prove performance against specific acceptance criteria.

The provided text does not contain information about acceptance criteria or a study that proves the device meets those criteria in the way typically found for software-based medical devices or diagnostic tools.

Instead, the summary focuses on non-clinical performance testing to demonstrate that the delivery syringe (a change from the predicate device) is capable of storing and delivering the bone void filler and does not raise different questions of safety or effectiveness.

Therefore, I cannot fulfill all parts of your request with the provided input. However, I can extract the relevant information regarding the non-clinical testing performed and the conclusions drawn:

Information available from the provided text:

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

The document doesn't explicitly define acceptance criteria in a table format with corresponding performance results in the context of a clinical or functional performance study for the bone void filler itself. Instead, it describes general non-clinical performance testing for the delivery syringe.

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

This information is not provided in the document. The document refers to "non-clinical performance testing" but does not detail the sample sizes or the origin of any data used for these tests.

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

This information is not applicable and therefore not provided. The document describes non-clinical engineering/mechanical testing of a delivery system, not a study requiring expert-established ground truth for clinical or diagnostic performance.

4. Adjudication method for the test set:

This information is not applicable and therefore not provided. Adjudication methods are relevant for studies involving human interpretation or subjective assessments, which is not the case for the described non-clinical testing.

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 applicable and therefore not provided. This device is a bone void filler and delivery system, not an AI-assisted diagnostic tool.

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

This information is not applicable and therefore not provided. This device is not an algorithm.

7. The type of ground truth used:

This information is not applicable in the usual sense of clinical ground truth (e.g., pathology, expert consensus). The "ground truth" for the described non-clinical tests would be defined by engineering specifications and physical measurements for mechanical properties (e.g., proper extrusion force, no leaks, correct delivered volume).

8. The sample size for the training set:

This information is not applicable and therefore not provided. There is no mention of a training set as this is not an AI/machine learning device.

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

This information is not applicable and therefore not provided. See point 8.

In summary: The provided document is a 510(k) summary focused on demonstrating substantial equivalence. The "study" mentioned is "non-clinical performance testing" of the device's delivery system (the syringe) to ensure it stores and delivers the bone void filler safely and effectively, and does not relate to the performance of the bone void filler itself in a clinical setting against specific acceptance criteria.

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The Allograft MIS Delivery System is intended to be used for the delivery of hydrated allograft bone graft material to an orthopedic surgical site.

The Allograft MIS Delivery System is a sterile, single-use, disposable graft delivery device intended for the delivery of hydrated allograft bone graft material to an orthopedic surgical site. The delivery system consists of: a cannula for containing and delivering the allograft material to the surgical site; a plunger to express the allograft material from the cannula; a dispenser to advance the plunger down the length of the cannula; and two end caps to retain the allograft material in the cannula prior to system assembly.

The cannula component is a 5 cc straight, open bore tube with a double threaded interface that mates with two end caps which are removed prior to cannula attachment to the dispenser. The dispenser is designed for single-hand, incremental delivery of graft materials and may be used to dispense multiple cannulas for a single patient.

This FDA 510(k) summary is for a medical device (Allograft MIS Delivery System), not an AI algorithm. Therefore, many of the requested criteria related to AI performance, ground truth, experts, and training sets are not applicable.

However, I can extract the acceptance criteria and the study type conducted to demonstrate substantial equivalence for this device.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: The document does not specify the exact sample sizes used for each of the performance tests. It generally states that "Testing was performed on samples that represented the finished device."
• Data Provenance: Not applicable. This is a physical device, and the testing involves laboratory and simulated use rather than clinical data from a specific country or retrospective/prospective studies.

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):

• Not applicable. This document describes the testing of a physical medical device. Ground truth as typically defined for AI algorithms (e.g., expert consensus on image interpretation) is not relevant here. The acceptance criteria are based on engineering and performance standards, likely evaluated by engineers, technicians, and quality control professionals.

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

• Not applicable. Adjudication methods are typically relevant for human interpretation tasks or clinical trials, not for direct performance testing of a physical device against predefined engineering standards.

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 versus without AI assistance:

• Not applicable. This is not an AI device.

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

• Not applicable. This is not an AI device.

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

• Ground Truth (for device performance): The "ground truth" in this context refers to established engineering specifications, regulatory standards, and intended functional outputs for the device. For example, the device must extrude material within certain force limits, fit together correctly, and maintain sterility. These are objective measures rather than subjective interpretations.

8. The sample size for the training set:

• Not applicable. This is not an AI device, so there is no training set in the context of machine learning.

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

• Not applicable. This is not an AI device.

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The MatrACELL™ Decellularized Pulmonary Artery Patch Allograft is indicated for repair of the right ventricular outflow tract.

derived from human pulmonary artery tissue and subsequently decellularized. The product is provided in multiple sizes for clinical use.

This document is a 510(k) summary for the MatrACELL™ Decellularized Pulmonary Artery Patch Allograft. It describes the device, its intended use, and its substantial equivalence to predicate devices. It does not present any specific acceptance criteria or a study proving the device meets acceptance criteria in the way typically found for AI/ML medical devices (e.g., performance metrics like sensitivity, specificity, or AUC).

Instead, this document focuses on demonstrating substantial equivalence to existing legally marketed devices, which is the primary pathway for 510(k) clearance. The "performance data" mentioned is not about meeting specific numerical thresholds for diagnostic accuracy, but rather about showing that the device is as safe and effective as its predicates.

Here's a breakdown of the information that can be extracted, and where the requested AI/ML specific information is not available from this document:

1. Table of Acceptance Criteria and Reported Device Performance

Missing from the document: Specific numerical acceptance criteria (e.g., minimum sensitivity, specificity, or precision) for diagnostic/classification performance, as this is not an AI/ML diagnostic device being cleared.

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

• Sample Size for Test Set: Not applicable in the context of an AI/ML device. The "test set" here refers to the data used in bench and animal testing. The document mentions a "female juvenile sheep model" for animal testing, but does not specify the number of animals or the specific details of the bench tests.
• Data Provenance: The animal study was conducted using a "female juvenile sheep model." The location of this study (e.g., country of origin) is not specified. It is a prospective study as it involves new animal testing.

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

• Not applicable / Not stated: Ground truth in the context of this device (a tissue allograft) would likely relate to histological analysis, tissue integration, mechanical properties, and functional outcomes in the animal model. The document does not specify the number or qualifications of experts involved in analyzing the results of the bench and animal tests.

4. Adjudication Method for the Test Set

• Not applicable / Not stated: Adjudication methods are typically used to resolve discrepancies among experts when establishing ground truth for diagnostic AI/ML models. This type of formal adjudication process is not described for the evaluation of this tissue allograft.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, not performed: An MRMC comparative effectiveness study is used to assess human reader performance with and without AI assistance. This device is a tissue allograft, not an AI/ML diagnostic or assistive device, so such a study would not be relevant.

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

• No, not applicable: This device is a tissue allograft, not an algorithm. Therefore, "standalone" algorithm performance is not a relevant concept for this submission.

7. The Type of Ground Truth Used

• The implicit "ground truth" for demonstrating substantial equivalence for this device would likely be:
  • Histology/Pathology: Assessment of tissue integration, cellular infiltration, inflammation, and degradation in the animal model.
  • Mechanical Properties: Bench testing to ensure the patch's physical properties (e.g., tensile strength, flexibility) are suitable and comparable to native tissue or predicate devices.
  • Functional Outcomes Data: In the animal model, this would involve assessing the long-term patency, remodeling, and hemodynamic performance of the patched right ventricular outflow tract.
  • Safety Data: Assessment of adverse events, host immune response, and complications in the animal model.

8. The Sample Size for the Training Set

• Not applicable: This device is not an AI/ML model that requires a training set. The "development" of the decellularization process might involve various experimental runs, but this is distinct from an AI/ML training set.

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

• Not applicable: As there is no AI/ML training set, the concept of establishing ground truth for it does not apply. The development of the decellularization process would be based on established scientific principles and experimental results to achieve the desired tissue properties.

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