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SurFuse™ Gel, SurFuse™ Putty, ExFuse™ Gel, ExFuse™ Putty products are indicated for bony voids or gaps that are not intrinsic to the stability of the bone structure. They are intended to be gently packed into bony voids or gaps of the skeletal system as a bone void filler in the extremities and pelvis. These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone. These products resorb and are replaced with bone during the healing process.

The submitted devices are resorbable bone void filler, combining Human Demineralized Bone Matrix (DBM) with cancellous bone powder and carboxymethylcellulose (CMC). The primary component of SurFuse™ and ExFuse™ is demineralized particle bone which is derived from human donor cortical bone. The additional bone powder in the ExFuse™ is derived from human donor cancellous bone. The CMC is added to enhance the cohesiveness of the composition. The submitted devices are provided in several volumes ranging from 0.3cc to 10 cc. The devices are supplied sterile for single patient use.

The provided text describes a 510(k) summary for medical devices (SurFuse™ Gel, SurFuse™ Putty, ExFuse™ Gel, ExFuse™ Putty), which are resorbable calcium salt bone void fillers. This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than detailed performance comparisons against acceptance criteria for an AI/software device.

Therefore, much of the requested information (acceptance criteria, sample sizes for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not applicable or not present in this document, as it pertains to a different type of device evaluation (e.g., AI/ML-based diagnostic software).

However, I can extract information related to the device's performance studies that were conducted to establish its substantial equivalence.

Here's the breakdown of what can be extracted from the document:

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

This document does not specify quantitative acceptance criteria in the manner an AI study would (e.g., sensitivity, specificity thresholds). Instead, the performance is demonstrated qualitatively through in vivo studies to show osteoconductive and osteoinductive potential, indicating equivalence to predicate devices.

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

• Rabbit unicortical defect model: The text states "in vivo rabbit unicortical defect model," but does not explicitly provide the number of rabbits or defects used.
• Athymic (nude) rat muscle pouch model: The text states "in vivo in the athymic (nude) rat muscle pouch model," but does not explicitly provide the number of rats used.
• Data Provenance: The in vivo animal studies are experimental, not retrospective or prospective human clinical data. The bone material itself is derived from human donors in the United States and screened.

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

Not applicable. These are in vivo animal studies (rabbit, rat) and in vitro assays, not studies requiring expert human interpretation of medical images or clinical outcomes. The "ground truth" would be the biological outcome observed and quantified in these animal models (e.g., new bone formation assessed histologically or radiographically by researchers).

4. Adjudication method for the test set

Not applicable. This is not a study involving human readers or clinical adjudication.

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

Not applicable. This document describes bone void filler devices, not AI-powered diagnostic software.

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

Not applicable. This is a medical device, not an algorithm. The in vitro BMP-2 ELISA assay is an in vitro test, which is a standalone lab test, but not an algorithm.

7. The type of ground truth used

• For Osteoconduction and Osteoinductive Potential: The "ground truth" is established through direct observation and measurement of biological outcomes (new bone formation) in animal models. This would typically involve histological analysis, imaging (e.g., X-ray, micro-CT) and potentially biochemical markers.

8. The sample size for the training set

Not applicable. These are in vivo and in vitro performance studies for a medical device, not an AI/ML algorithm requiring a training set in the computational sense. Each lot of the device will be evaluated using the in vitro assay, implying ongoing quality control rather than a training set for an algorithm.

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

Not applicable, as there is no training set for an AI/ML algorithm described.

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