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The Bio2 CLM•BG Bioactive Scaffold is intended for use as a bone void filler for bony voids or gaps that are not intrinsic to the stability of the bony structure. Bioactive Scaffold is indicated to be gently packed into bony voids or gaps of the skeletal system (i.e. extremities and pelvis). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone.

The product provides a bone void filler that resorbs and is replaced with bone during the healing process.

The Bio2 Technologies implants are bone void fillers in the shape of cylinders, blocks and wedges. The devices are osteoconductive, bioactive, bone void fillers. The implants are made from a fiber based bioactive glass. The material can be drilled and tapped, and screws can be placed through it. The device structure allows tissue infiltration between the bioactive glass fibers. The fibers then are slowly absorbed and replaced by new bone tissue during the healing process. The cylinders, blocks and wedges are provided sterile and are intended for single use.

The provided text is a 510(k) summary for the Bio2 CLM.BG Bioactive Scaffold, a bone void filler device. It describes the device, its intended use, and compares it to predicate devices to establish substantial equivalence. However, it does not contain the specific details required to fulfill all sections of your request regarding acceptance criteria and a study proving those criteria are met for a device that uses AI or reports performance metrics like sensitivity, specificity, or AUC.

The document focuses on:

• Substantial Equivalence: Comparing the device's characteristics (e.g., osteoconductive, bioactive, resorbable bioactive glass, radiopaque) and performance to existing predicate devices (Bio2 CLM.BG Bioactive Scaffold K142463, Synthes chronOS K013072, Norian Drillable Bone Void Filler and Norian Drillable Fast Set Putty K073303).
• Biocompatibility Testing: Stating compliance with ISO-10993.
• In Vitro Bioactivity Testing: Mentioning compliance with ISO 23317:2012 and the material forming a surface apatite layer when submerged in simulated body fluid.
• In Vivo Animal Studies: Stating that the device achieves bony healing in a critical defect model, confirmed with radiographs, histology, and histomorphometry.

Based on the provided text, I can answer some of your questions, but many will be missing as the document does not describe the kind of performance study you are asking for (e.g., related to AI-driven diagnostics with metrics like sensitivity and specificity).

Here's the breakdown of what can and cannot be answered:

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

Not available in the provided text in the requested format. The document describes compliance with standards and equivalence to predicates, not specific numerical acceptance criteria with corresponding performance metrics like sensitivity or specificity.

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 for the test set: Not explicitly stated for the in vivo animal studies. It mentions "critical size defects were filled" and rabbit femurs were evaluated, suggesting an animal model, but not the number of animals or defects.
• Data provenance: For the in vivo animal studies, "rabbit femurs" are mentioned, indicating an animal model study, not human data. Country of origin is not specified.
• Retrospective or prospective: The animal studies would typically be prospective, but this is not explicitly stated.

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 or not mentioned. The ground truth for the animal study appears to be based on objective scientific methods like X-ray, histology, histomorphometry, SEM, and EDX, rather than human expert interpretation of images for diagnosis.

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

Not applicable or not mentioned. This typically relates to expert consensus for ground truth establishment in diagnostic studies, which is not what is described here.

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. This is not an AI-based diagnostic device. The study described is an animal model for bone healing, not a human reader study.

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

No. This is not an algorithmic device.

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

For the in vivo animal studies: Radiographs, histology, histomorphometry, SEM (Scanning Electron Microscopy), and EDX (Energy Dispersive X-ray Spectroscopy). This constitutes a combination of imaging, microscopic evaluation, and elemental analysis of the bone tissue.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. This is not an AI/machine learning device.

In summary, the provided document details a substantial equivalence claim for a physical medical device (bone void filler) based on material properties, in vitro testing, and in vivo animal studies. It does not provide the type of performance metrics, study designs, or ground truth establishment relevant to an AI/ML-driven diagnostic device.

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The Bio2 CLM-BG Bioactive Scaffold is intended for use as a bone void filler for bony voids or gaps that are not intrinsic to the stability of the bony structure. Bio2 CL.M+BG Bioacive Scaffold is indicated to be gently packed into bony voids or gaps of the skeletal system (i.e. extremitics and pelvis). These defects may be surgically created osseous defects or osseous defects created from traumatic injury to the bone.

The product provides a bone void filler that resorbs and is replaced with bone during the healing process.

The Bio2 Technologies implants are bone void fillers in the shape of cylinders, blocks and wedges. The devices are osteoconductive, bioactive, bone void fillers. The implants are made from a fiber based bioactive glass. The device structure allows tissue infiltration between the bioactive glass fibers. The fibers then are slowly absorbed and replaced by new bone tissue during the healing process. The cylinders, blocks and wedges are provided sterile and are intended for single use.

The provided document describes the Bio2 CLM.BG Bioactive Scaffold, a bone void filler device, and its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria with detailed performance metrics. Therefore, many of the requested details, such as specific acceptance criteria for diagnostic performance, sample sizes for test sets, expert qualifications, and detailed statistical analysis, are not present.

However, based on the information provided, here's a best effort to address the questions:

1. Table of Acceptance Criteria and the Reported Device Performance

The acceptance criteria are implied by the comparison to predicate devices and the successful outcomes of in vitro and in vivo studies, generally demonstrating that the Bio2 CLM.BG Bioactive Scaffold is as safe and effective as the control material and predicate devices. No specific quantitative acceptance criteria (e.g., minimum sensitivity or specificity values) are explicitly stated for diagnostic performance, as this is a bone void filler, not a diagnostic device.

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

• Test Set Sample Size: The document mentions "critical size defects were filled with Bio2 CLM.BG Bioactive Scaffold and the control material" in a rabbit model. However, the specific number of animals or defects in this in vivo study is not provided.
• Data Provenance: The in vivo study was an animal study (rabbit model), making it prospective pre-clinical data. The country of origin is not specified but assumed to be where Bio2 Technologies (Woburn, Massachusetts, USA based) conducted its research.

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

This information is not provided. The assessment of the animal study results involved "x-ray, histology, histomorphometry, SEM and EDX," which would typically be evaluated by experts in those fields (e.g., veterinary radiologists, histopathologists), but their number and qualifications are not detailed.

4. Adjudication method for the test set

This information is not provided. For animal studies involving multiple assessment methods, adjudication among experts might occur, but no specific method (e.g., 2+1, 3+1) is described.

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

A multi-reader, multi-case (MRMC) comparative effectiveness study is not applicable here. This document describes a medical device (bone void filler) and its substantial equivalence, not an AI-powered diagnostic or assistive tool for human readers. Therefore, there's no mention of human reader improvement with or without AI assistance.

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

This question is not applicable as the device is a physical bone void filler, not an algorithm.

7. The type of ground truth used

The ground truth for the in vivo animal study comprised:

• Radiographs (x-ray): Imaging assessment of bone formation.
• Histology: Microscopic examination of tissue.
• Histomorphometry: Quantitative analysis of tissue structure (e.g., amount of new bone, scaffold resorption).
• SEM (Scanning Electron Microscopy) and EDX (Energy-Dispersive X-ray Spectroscopy): Advanced imaging and elemental analysis of material integration and new bone formation.

For the in vitro studies, the ground truth for apatite layer formation in SBF was measured via established scientific methods.

8. The sample size for the training set

This information is not provided and is generally not applicable in the context of a physical medical device (bone void filler) which typically undergoes pre-clinical and clinical testing, not "training" in the machine learning sense.

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

This information is not provided and is not applicable for this type of medical device as outlined in point 8.

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