(266 days)
Moldable Bone Void Filler and Moldable Bone Void Filler + CCC 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. Moldable Bone Void Filler and Moldable Bone Void Filler + CCC can be used with autogenous bone marrow. Moldable Bone Void Filler and Moldable Bone Void Filler + CCC resorbs and are replaced with bone during the healing process.
Moldable Bone Void Filler and Moldable Bone Void Filler + CCC are for single patient use only.
Moldable Bone Void Filler and Moldable Bone Void Filler + CCC are bone void fillers composed of processed demineralized bone matrix (DBM), a synthetic macromer hydrogel, and cortical cancellous bone chips (CCC) for Moldable Bone Void Filler + CCC only. Both are provided with an accessory kit containing pre-measured hydrating solution and a spatula to mix the components.
After the implant is hydrated, the resultant putty can then be handled and placed in the appropriate bone voids or gaps. Moldable Bone Void Filler and Moldable Bone Void Filler + CCC gradually resorb and are replaced with new bone during the healing process. At the 12 week timepoint, animal study data demonstrated new bone formation averages of 16.21% in the Optecure group, 13.8% in the Optecure + CCC group, 15.75% in the Exactech Optecure + CCC predicate group, and 12.08 % in the empty defect negative control group.
The provided text is a 510(k) summary for a medical device (Moldable Bone Void Filler and Moldable Bone Void Filler + CCC). This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving a device meets specific performance acceptance criteria for an AI/ML algorithm.
Therefore, most of the requested information regarding acceptance criteria, test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, training sets, and ground truth establishment for AI/ML algorithms is not applicable to this document.
However, I can extract information related to the device's performance data as presented in the context of demonstrating substantial equivalence.
Here's a breakdown of what can and cannot be answered based on the provided text:
What can be extracted:
- Acceptance Criteria (Implicitly based on Predicate Equivalence): The primary "acceptance criterion" for this 510(k) clearance is substantial equivalence to a predicate device. This is repeatedly stated throughout the document. The performance data presented (animal study results) are used to support this claim of equivalence, not to meet a pre-defined numerical performance threshold for a specific task like classification or detection.
- Reported Device Performance (Animal Study): The document provides quantitative results from an animal study regarding new bone formation.
What cannot be extracted (as it pertains to AI/ML acceptance criteria and studies):
- A table of explicit acceptance criteria for an AI/ML device.
- Sample size used for a test set (in the context of AI/ML).
- Data provenance for a test set.
- Number of experts and their qualifications used to establish ground truth for a test set.
- Adjudication method for a test set.
- Multi-reader multi-case (MRMC) comparative effectiveness study, its effect size, or human reader improvement with AI assistance.
- Standalone (algorithm only) performance.
- The type of ground truth used (expert consensus, pathology, outcomes data, etc.) for an AI/ML model.
- Sample size for a training set for an AI/ML model.
- How ground truth for a training set was established for an AI/ML model.
Information Extracted from the Provided Text:
1. A Table of Acceptance Criteria and the Reported Device Performance:
As this document is for a non-AI/ML medical device seeking 510(k) clearance, the "acceptance criteria" are intrinsically tied to demonstrating substantial equivalence to an existing predicate device. The performance data presented are used to support this claim, rather than meeting a specific numerical target for an AI/ML algorithm.
| Acceptance Criteria (Implicit for 510(k) Substantial Equivalence) | Reported Device Performance (Animal Study Data) |
|---|---|
| Devices are substantially equivalent to the predicate device with respect to indications for use, materials, biocompatibility, storage, and performance. This includes demonstrating comparable bone formation properties. | At the 12-week timepoint, animal study data demonstrated new bone formation averages of: |
- Optecure group (New Device): 16.21%
- Optecure + CCC group (New Device): 13.8%
- Exactech Optecure + CCC predicate group: 15.75%
- Empty defect negative control group: 12.08% |
| Device does not raise any safety and effectiveness concerns as compared to the predicate device. | Non-clinical testing performed to support substantial equivalence and demonstrate safety and effectiveness included: Chemical and physical properties, Biocompatibility, Sterility, Shelf Life, and Animal Study. |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
- The document refers to an "animal study" which contains performance data used to support substantial equivalence. It does not explicitly state the sample size (number of animals or defects) used in this animal study.
- The data provenance (country of origin, retrospective/prospective) for this animal study is not specified in the provided text.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. This is not an AI/ML device, and the ground truth for bone formation in an animal study would typically be established through histological analysis by trained pathologists or similar experts, but the number and qualifications are not provided.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
- Not applicable. This is not an AI/ML device study involving human reader interpretation 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
- No. This is not an AI/ML device and no MRMC study was conducted or is relevant to this submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This is a bone void filler, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- For the animal study: The ground truth for "new bone formation" would typically be established through histological analysis (a type of pathology) of tissue samples from the animal defects. The document mentions "animal study data demonstrated new bone formation averages."
8. The sample size for the training set
- Not applicable. This is not an AI/ML device that requires a training set.
9. How the ground truth for the training set was established
- Not applicable. This is not an AI/ML device that requires a training set.
§ 888.3045 Resorbable calcium salt bone void filler device.
(a)
Identification. A resorbable calcium salt bone void filler device is a resorbable implant intended to fill bony voids or gaps of the extremities, spine, and pelvis that are caused by trauma or surgery and are not intrinsic to the stability of the bony structure.(b)
Classification. Class II (special controls). The special control for this device is the FDA guidance document entitled “Class II Special Controls Guidance: Resorbable Calcium Salt Bone Void Filler Device; Guidance for Industry and FDA.” See § 888.1(e) of this chapter for the availability of this guidance.