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OSTEOSET® DBM Pellets are indicated only for bony voids or gaps that are not intrinsic to the stability of the bony structure. OSTEOSET® DBM Pellets are intended to be gently packed into 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 traumatic injury to the bone.

OSTEOSET® DBM Pellets are a bone graft material. OSTEOSET® DBM Pellets combine the effects of DBM and OSTEOSET® Pellets. The DBM used in OSTEOSET® DBM Pellets is tested to confirm the osteoinductivity of each DBM lot.

OSTEOSET® DBM Pellets are provided as preformed 3.0 mm or 4.8 mm pellets. The biodegradable, radiopaque pellets are used to fill bone voids and are resorbed in approximately 30-60 days when used according to labeling. This product is supplied sterile for single patient use.

The provided text describes a 510(k) summary for the OSTEOSET® DBM Pellets, a bone void filler. This document is a premarket notification for a medical device and, as such, focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study demonstrating achievement of specific acceptance criteria in the way a new, high-risk device might.

Here's an analysis of the provided text in relation to your request:

1. Table of acceptance criteria and the reported device performance:

The document does not explicitly state quantitative "acceptance criteria" for the OSTEOSET® DBM Pellets in terms of clinical performance (e.g., bone healing rates, reduction in pain). Instead, it describes performance related to the materials and manufacturing processes that support its substantial equivalence claim.

1. in vitro assay (human bone forming cells) correlated to athymic rat model and clinical results.
2. in vitro assay for native protein (BMP-2) correlated to athymic rat model. |
   | Viral Inactivation Potential (of DBM processing) | Processing method evaluated with a panel of model human viruses, showing "suitable viral inactivation potential". |
   | Resorption Rate | Resorbed in approximately 30-60 days. |

Important Note: The document explicitly states: "The osteoinductivity of this combination of DBM and calcium sulfate (OSTEOSET® Pellets) has not been established; therefore, it is unknown to what extent the formulation components may alter the osteoinductive character of the DBM. Additionally, it is unknown how osteoinductivity of the DBM component, measured via either in vitro assay, will correlate with human clinical performance of OSTEOSET® DBM Pellets." This highlights that the "performance" described is largely at the component/material level rather than full device clinical performance.

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

• Test Set Sample Size: Not applicable in the context of device clinical performance testing. The "tests" mentioned are for raw material (DBM) and processing methods.
  • For Osteoinductivity Potential Testing: The "test set" refers to each lot of DBM. The actual sample size of cells or rats used in these assays is not specified, but the methods refer to established models (in vitro human bone forming cells, athymic rat model).
  • For Viral Inactivation Potential: A "panel of model potential human viruses" was used. The number of viruses in the panel is not specified.
• Data Provenance: Not explicitly stated for all references.
  • Reference 1 (Wilkins, 1999) on DBM effectiveness: likely retrospective analysis on human cell culture and athymic rat model correlations.
  • Reference 2 (Lindholm TS, Urist MR, 1980) on bone formation analysis: an animal study (bone marrow and bone matrix grafts).
  • Reference 3: "Data on file at Wright Medical Technology, Inc." (manufacturer's internal data), likely derived from laboratory testing of DBM batches.
• Retrospective or Prospective: The viral inactivation and osteoinductivity assays are prospective tests performed on each batch of materials. The referenced studies that correlate these assays to clinical/animal outcomes could be retrospective analyses of existing data.

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 as the submission does not detail human-read imaging or diagnostic performance where expert consensus would be required to establish ground truth. The "ground truth" for the osteoinductivity assays would be the biological response observed (e.g., bone formation in rats, cell differentiation), and for viral inactivation, it would be the reduction in viral titer. These are laboratory-based measurements, not expert interpretations.

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

Not applicable. There is no mention of adjudication, as this typically applies to image interpretation or clinical outcome assessment, which are not detailed in this 510(k) summary.

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 device is a bone void filler, a physical implant. The submission does not involve AI or imaging interpretation, so MRMC studies are irrelevant.

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

Not applicable. The device is a physical product, not an algorithm.

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

• For Osteoinductivity Potential: The "ground truth" for the assays is the correlation to the athymic rat model (a biological model for bone formation) and clinical results of DBM (outcomes data). The in vitro assays themselves are surrogates for this biological activity.
• For Viral Inactivation Potential: The "ground truth" is the reduction in viral infectivity/titer directly measured in laboratory experiments with model viruses.

8. The sample size for the training set:

Not applicable. This summary does not describe an AI/machine learning device, so there is no concept of a "training set" in this context. The manufacturing processes and material testing are based on established scientific methods and assays, not iterative learning from data.

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

Not applicable. As there is no training set mentioned, this question is not relevant.

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OSTEOSET® DBM Pellets are indicated only for bony voids or gaps that are not intrinsic to the stability of the bony structure. OSTEOSET® DBM Pellets are intended to be gently packed into 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 traumatic injury to the bone.

OSTEOSET® DBM Pellets are made of surgical grade calcium sulfate incorporating Human Demineralized Bone Matrix (DBM) and stearic acid as a tableting aid. OSTEOSET® DBM Pellets are provided as preformed 3.0 mm or 4.8 mm pellets. The biodegradable, radiopaque pellets are used to fill bone voids and are resorbed in approximately 30-60 days when used according to labeling. This product is supplied sterile for single patient use.

The provided text describes a 510(k) premarket notification for a medical device called OSTEOSET® DBM Pellets. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than undergoing a full clinical efficacy trial with specific acceptance criteria as might be seen for novel drug or high-risk device approvals.

Therefore, the concept of "acceptance criteria" in the context of this 510(k) is primarily tied to demonstrating that the new device performs similarly to the predicate device, not necessarily against pre-defined numerical thresholds for a specific clinical outcome. The study described focuses on establishing this equivalence.

Here's an analysis based on the information provided, addressing your points where possible:

Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) submission based on substantial equivalence, the "acceptance criteria" are implicitly met by demonstrating that the new device is as safe and effective as the predicate device. The study's "performance" is the lack of difference when compared to the predicate in relevant metrics.

Study Information

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

   • Test Set Sample Size: The primary performance testing was conducted in a canine model. The specific number of animals is not provided in the summary.
   • Data Provenance: Animal model (canine), prospective study design (comparing the new device to a predicate). The in-vitro DBM osteoinductivity bioassay and athymic rat model data are also mentioned, along with human clinical correlation data from prior studies (presumably retrospective, as they are used to validate the bioassay's predictive power for DBM generally, not directly for this specific device).

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

   • The document does not specify the use of human experts or ground truth establishment in the traditional sense for the animal model study. Performance was evaluated via "radiographic, mechanical, histological and quantification of new bone formation." These are objective measurements typically conducted by trained laboratory personnel or pathology specialists, rather than clinical experts providing a subjective "ground truth."

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

   • Not applicable / None specified. The animal study relied on objective measurements rather than subjective assessments requiring adjudication.

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:

   • No, an MRMC comparative effectiveness study was not done. This type of study is relevant for imaging devices or decision-support tools where human reader performance is a key outcome. The OSTEOSET® DBM Pellets are a bone void filler, not an imaging or AI diagnostic device.

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

   • No, this is not applicable. The device is a physical implant, not an algorithm.

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

   • For the canine model, the "ground truth" for performance was based on objective measures: radiographic imaging, mechanical testing, histological analysis, and quantitative assessment of new bone formation. These are direct biological and physical measurements, rather than human expert interpretation or consensus.
   • For the DBM osteoinductivity, the in-vitro bioassay was correlated with in-vivo bone formation in an athymic rat muscle model (pathology) and prior human clinical healing rates (outcomes data) from different studies to demonstrate its predictive power for the DBM component generally.

7. The sample size for the training set:

   • Not applicable. This device is not an AI/ML algorithm that requires a training set. The DBM bioassay mentions having been correlated with past studies, which could be considered historical data sets, but there's no "training set" in the context of the device itself.

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

   • Not applicable. As the device is not an AI/ML algorithm, there is no training set or associated ground truth establishment for a training set. The bioassay's predictive power was established by correlating its results with in vivo new bone formation in rats and human clinical healing rates from previously published work.

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