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Calcigen™-S Bone Void Filler is indicated to fill bony voids or gaps of the skeletal system (i.e. the extremities, spine and pelvis). These defects may be surgically created osseous defects or osseous defects created from a traumatic injury to the bone. Calcigen™-S Bone Void Filler is indicated only for bony voids or gaps that are not intrinsic to the stability of the bony structure.

Calcigen™-S Bone Void Filler is a bone filler that resorbs and is replaced with bone during the healing process. The product is available in two forms, paste and granuales.

The provided text is a 510(k) premarket notification for the Calcigen™-S Bone Void Filler. This document describes a medical device, its intended use, and its substantial equivalence to previously marketed devices. However, it does not contain any information about a clinical study with acceptance criteria and reported device performance related to diagnostic accuracy or clinical outcomes as would be expected for a diagnostic or AI-powered device.

Instead, the submission focuses on:

• Non-Clinical Testing: Material properties (set time, exothermic temperature, purity, porosity, mass/volume ratio), biocompatibility (non-toxic, non-mutagenic, non-hemolytic, non-cytotoxic, non-pyrogenic), and comparative testing with a predicate device for dissolution rate and surface pH.
• Animal Testing: Demonstrated equivalence with the predicate device in an in vivo situation (histologically and mechanically).
• A statement explicitly saying: "Clinical Testing: none provided".

Therefore, I cannot fulfill the request to describe acceptance criteria and a study proving device performance in the context of diagnostic accuracy, AI involvement, or human reader improvement, as this information is not present in the provided text.

Based on the available information, here is what can and cannot be answered:

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

• Not Applicable / Not Provided: The document does not present acceptance criteria or reported performance for clinical accuracy or diagnostic capabilities. The non-clinical and animal testing results (e.g., set time, dissolution rate, biocompatibility, histological equivalence) are presented to demonstrate substantial equivalence to a predicate device, not to meet specific clinical performance metrics.

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

• Not Applicable / Not Provided: No clinical test set involving human data is mentioned. Animal testing was conducted, but specific sample sizes and provenance are not detailed beyond "an in vivo situation."

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 / Not Provided: No human test set or ground truth establishment by experts is described as there was no clinical testing provided.

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

• Not Applicable / Not Provided: No human test set requiring adjudication is mentioned.

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: No MRMC study was done, and no AI component is described.

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

• No: No standalone algorithm performance is described, as the device is a bone void filler, not an AI or diagnostic algorithm.

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

• Not Applicable / Not Provided: For the non-clinical and animal testing, "ground truth" would be established by standard analytical methods for material properties and histological/mechanical assessments in animal models. No human ground truth is referred to.

8. The sample size for the training set

• Not Applicable / Not Provided: There is no training set mentioned, as this is a physical medical device, not a machine learning model.

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

• Not Applicable / Not Provided: As there is no training set, this question is not applicable.

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