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NovoGro Putty is intended for use as a bone void filler for gaps and voids that are not intrinsic to the stability of the bony structure. NovoGro Putty is intended to be hydrated with sterile water and 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. NovoGro Putty provides a bone void filler that resorbs and is replaced by bone during the healing process.

NovoGro Putty is provided to the end-user as two components (dry powder and aqueous solution) that must be mixed intra-operatively prior to implantation using the supplied mixing system to form a moldable cohesive putty-like graft. The dry powder component of NovoGro Putty contains spherical beads that are composed primarily of a co-precipitate of dicalcium phosphate anhydrite Imonetite. CaHPO4], magnesium phosphate trihydrate [newberyite, Mg(PO2OH)+3(H2O)] and sodium hydrogen phosphate [NaH2PO4]. Small amounts of silica (SiO2) and magnesium oxide (MgO) are combined with this co-precipitate during manufacturing. These spherical beads are mixed heterogeneously with dry sodium carboxymethyl cellulose (CMC) powder to enhance the handling properties of the final mixed graft. The aqueous component of NovoGro is ultrapure reverse osmosis deionized water (DI H2O). NovoGro Putty is provided sterile for single use in volumes ranging from 1 cc to 20 cc. NovoGro Putty is provided in a kit with a mixing system, a vial of ultrapure water for mixing, and a graduated syringe to measure the correct volume of the supplied ultrapure water to add to the dry component.

This document is a 510(k) premarket notification for a medical device called NovoGro, a resorbable calcium salt bone void filler device. It is not an AI/ML device, therefore, the information requested in the prompt related to acceptance criteria for an AI/ML device and its validation study (e.g., sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not applicable.

However, based on the document, I can extract information about the device's performance criteria and the study that supported its substantial equivalence to a predicate device.

Here's a summary of the requested information, adjusted for a non-AI/ML medical device:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is not an AI/ML device, the "acceptance criteria" are not framed in terms of performance metrics like sensitivity or specificity. Instead, acceptance is based on demonstrating substantial equivalence to a legally marketed predicate device through various tests. The performance of the subject device (NovoGro) was deemed equivalent to the predicate (Actifuse ABX).

2. Sample Size Used for the Test Set and Data Provenance

• Test Set (Animal Study): Not explicitly stated how many animals were in the "rabbit distal femoral condyle critical-sized defect model." The document mentions "baseline (time 0) animals" and "empty (unfilled) defects (negative control) evaluated at 6 weeks and 12 weeks," implying multiple animals within each group and time point, but the exact number isn't provided.
• Data Provenance: The animal study was conducted as pre-clinical testing, but the country of origin is not specified. It is a prospective study designed to compare the subject device against the predicate.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Ground Truth Establishment: For the animal study, the "ground truth" or evaluative endpoints were based on objective scientific analyses.
  • Evaluators: The document mentions "high-resolution radiography, micro-computed tomography (micro-CT) imaging, undecalcified histologic evaluation, and histomorphometric analysis." Histology sections were also "graded according to AAMI/ANSI/ISO 10993-6 (Annex E)."
  • Number and Qualifications of Experts: Not specified. It can be inferred that these evaluations were performed by qualified personnel (e.g., veterinary radiologists, histopathologists, scientists trained in histomorphometry), but the specific number or their credentials are not detailed in this document.

4. Adjudication Method for the Test Set

• Given the objective nature of the evaluations (radiography, micro-CT, histology, histomorphometry, and grading against a standard), a formal "adjudication method" in the sense of expert consensus for subjective findings is less relevant here. The analyses rely on scientific methods and specified standards (e.g., AAMI/ANSI/ISO 10993-6). Any discrepancies would likely be resolved through re-evaluation or adherence to established protocols. The document does not describe a specific adjudication method.

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 MRMC study was done. This is not an AI/ML device meant to assist human readers. The study performed was a comparative animal study of the device itself.

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

• Not applicable. This refers to AI/ML algorithms. The device is a physical bone void filler.

7. The type of ground truth used

• For the animal study: The ground truth was established through a combination of radiographic imaging, micro-CT imaging, undecalcified histologic evaluation, and histomorphometric analysis. These are objective scientific measurements and observations of tissue response and bone formation in an in-vivo model. Histology sections were also graded against a standard (AAMI/ANSI/ISO 10993-6 Annex E).

8. The sample size for the training set

• Not applicable. This device is not an AI/ML algorithm that requires a training set. The "training" for this type of device would refer to its development and refinement through pre-clinical testing, but not in the context of a "training set" for AI.

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

• Not applicable, as there is no AI/ML training set for this device.

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