Search Results

ABCcolla® Bone Graft is an implant intended to fill bony voids or gaps of the skeletal system (i.e., extremities and pelvis). These osseous defects are surgically created or the result of traumatic injury to the bone and are not intrinsic to the stability of the bony structure. ABCcolla® Bone Graft resorbs and is replaced with bone during the healing process.

ABCcolla® Bone Graft is a bone mineral matrix of porcine origin. ABCcolla® Bone Graft is physically and chemically comparable to the mineralized matrix of human bone.

The provided text describes a 510(k) premarket notification for the "ABCcolla® Bone Graft" device, which is a resorbable calcium salt bone void filler. Here's an analysis of the acceptance criteria and study information, focusing on the lack of specific details regarding a "study that proves the device meets acceptance criteria" as would be expected for an AI/ML device:

Important Note: The provided document is a 510(k) summary for a bone graft medical device, not an AI/ML powered device. As such, concepts like "test set," "human readers," "AI assistance," "ground truth establishment for training set," and "adjudication method" are not applicable in their typical AI/ML context. The document describes traditional medical device testing for substantial equivalence, focusing on biocompatibility, physical properties, and pre-clinical animal performance.

Therefore, many of the requested fields will be marked as "Not Applicable" or "Not Provided" in the context of an AI/ML device. I will extract the relevant information from the document as it pertains to a traditional medical device's testing and acceptance.

Acceptance Criteria and Reported Device Performance

The acceptance criteria for the ABCcolla® Bone Graft are implicitly set by demonstrating "substantial equivalence" to predicate devices and meeting established medical device standards. The "performance" in this context refers to its physical, chemical, and biological properties, as well as its ability to facilitate bone formation in animal models.

Study Details (Interpreted for a non-AI/ML medical device)

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

   • Test Set Sample Size:
     • For chemical, physical, and in vitro biological tests: Not explicitly stated in terms of sample count (e.g., number of batches, units). These would typically involve multiple samples to establish consistency.
     • For pre-clinical animal performance testing: A "critical-size bone defect model" was performed. The number of animals used is not specified.
   • Data Provenance: The studies were performed by ACRO Biomedical Co., Ltd. (Taiwan). The document does not specify if the studies were retrospective or prospective, but animal studies are typically prospective by nature.

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

   • Not Applicable / Not Provided. For a bone graft device, "ground truth" is established through standardized laboratory analyses (e.g., chemical assays, physical measurements) and histological examination of animal tissue, performed by qualified scientists and pathologists, rather than expert clinicians rendering a diagnostic opinion. The number of such specialists is not specified.

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

   • Not Applicable. Adjudication methods like 2+1 are relevant for interpreting ambiguous diagnostic images or clinical scenarios, typically in studies involving human readers or AI. For the described medical device testing, results are derived from objective measurements, biochemical analyses, and histological assessments in animal models.

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:

   • Not Applicable. This device is a bone graft, not an AI-powered diagnostic tool. Therefore, no MRMC study or AI assistance comparison would be performed.

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

   • Not Applicable. This is a physical medical implant, not an algorithm.

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

   • For chemical and physical properties: Analytical measurements against established standards (e.g., hydroxyapatite content, porosity).
   • For biocompatibility: Adherence to ISO 10993 series standards, which involves evaluating cellular responses, systemic toxicity, etc.
   • For pre-clinical animal performance: Histological evidence of new bone formation and healing in the critical-size bone defect model, likely compared to control groups or expected healing patterns. This would involve pathology and quantitative analysis of bone growth.

7. The sample size for the training set:

   • Not Applicable. This is a physical medical device, not an AI/ML model, so there is no "training set."

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

   • Not Applicable. As there is no training set for an AI/ML model, this question is irrelevant for this device.

Ask a specific question about this device