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The Kensey Nash Bone Void Filler is intended to be gently packed into the bony voids or gaps of the extremities and pelvis that are caused by trauma or surgery and are not intrinsic to the stability of the bony structure. These defects may be created from traumatic injury to the bone or surgically created osseous defects for the harvest of bone. The device provides a bone void filler that resorbs and is replaced with bone during the healing process. The device may be combined with sterile fluids such as saline or autogenous blood products such as blood or bone marrow aspirate. The addition of these autogenous blood products does not alter the performance of the device.

Kensey Nash Bone Void Filler is a mixture of beta tricalcium phosphate, polylactic acid and Type I bovine collagen. The product will be provided gamma sterilized for one-time use in a variety of shapes ranging from pre-formed cylinders, granules, cubes and blocks with sizes ranging up to 25 mm in diameter and up to 30 cc in volume.

The provided 510(k) summary for the Kensey Nash Bone Void Filler describes non-clinical testing performed to demonstrate substantial equivalence to predicate devices, focusing on safety and effectiveness. However, it does not provide explicit acceptance criteria or detailed study results with specific performance metrics such as accuracy, sensitivity, or specificity.

The document states: "Results of in vivo and in vitro comparison testing demonstrate that Kensey Nash BVF is substantially equivalent to PolyGraft™ BGS." This implies that the device's performance was compared to a predicate device, and the results were found to be comparable enough to satisfy the substantial equivalence requirements for 510(k) clearance.

Here's an attempt to answer your request based on the available information, highlighting where specific details are missing:

Acceptance Criteria and Device Performance

The 510(k) summary does not explicitly state quantitative acceptance criteria in terms of performance metrics (e.g., specific thresholds for biocompatibility, compressive strength, or bone healing rates). Instead, the "acceptance criteria" appear to be implicit in demonstrating "substantial equivalence" to a predicate device through various non-clinical tests.

The reported device performance is generally stated as achieving substantial equivalence.

Study Details

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

   • Sample Size (Test Set): Not specified in the provided summary. The summary mentions "an animal study" but does not give the number of animals or specific experimental groups.
   • Data Provenance: Not specified. The studies are non-clinical (biocompatibility, physical properties, compressive strength, in vitro, and animal study). The location where these studies were conducted or whether they are considered "retrospective" or "prospective" in a clinical sense is not applicable or stated for non-clinical testing.

2. 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 device is a bone void filler, and the testing described is non-clinical (in vitro, animal study). There is no mention of human expert-established ground truth for visual assessment or diagnosis that would typically be associated with medical imaging or diagnostic devices.

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

   • Not Applicable. As per point 2, this type of adjudication is not relevant for the non-clinical testing described.

4. 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. This is a medical device (bone void filler), not an AI-assisted diagnostic or imaging device. Therefore, a MRMC comparative effectiveness study involving human readers and AI assistance would not be applicable.

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

   • Not Applicable. This is a physical medical implant device, not an algorithm or software. "Standalone performance" in this context would refer to the device's inherent physical and biological performance, which was assessed through non-clinical testing.

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

   • Ground Truth for Non-Clinical Studies:
     • Biocompatibility: Likely assessed against ISO standards (e.g., ISO 10993 series) which define acceptable biological responses in various tests (cytotoxicity, sensitization, irritation, etc.). The "ground truth" would be compliance with these biological response criteria.
     • Physical Properties/Compressive Strength: Determined by engineering and materials science standards and measurements. The "ground truth" is the objective measurement of these properties.
     • In vivo (Animal Study): Likely involved histological analysis to assess bone formation, resorption rates, and tissue integration. The "ground truth" would be pathological assessment of tissue samples and potentially radiographic evaluation of bone healing in the animal models.

7. The sample size for the training set

   • Not Applicable. This is a physical medical device, not a machine learning or AI algorithm, so there is no concept of a "training set" in the context of data used to train an algorithm. "Training set" is typically used for AI/ML models.

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

   • Not Applicable. As per point 7, there is no "training set" for this type of medical device.

In summary, the provided 510(k) pertains to a physical bone void filler and demonstrates substantial equivalence through a series of non-clinical tests (biocompatibility, physical properties, compressive strength, in vitro, and an animal study). The document does not contain the detailed quantitative performance metrics or study designs typically associated with diagnostic or AI-powered devices, which would involve concepts like acceptance criteria for sensitivity/specificity, expert ground truth, or training/test sets.

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