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The Anova Containment Device, in conjunction with traditional rigid fixation, is intended for use in spinal fusion procedures as a means to maintain the relative position of weak bony tissue such as allografts or autografts. The device is not intended for load bearing indications.

The Anova Containment Device is a flexible, synthetic composite implantable mesh. It includes a polyester mesh component connected by a mono-filament suture to a porous expanded polytetrafluoroethylene or "ePTFE" component. This ePTFE component is placed between the polyester mesh and the overlying soft tissues. The ePTFE component is not anchored to the disc. The Anova Containment Device is attached to the spine with four suture anchors (two fastened to the vertebra above and two fastened to the vertebra below the disc). The sutures from the anchors overlay the mesh and hold it against the vertebral body and to reinforce the mesh against pressure from the graft material.

Here's an analysis based on the provided text, outlining the acceptance criteria and the study details for the Anova Containment Device:

It's important to note that the provided text is a 510(k) summary, which is a regulatory document focused on demonstrating substantial equivalence to predicate devices, rather than a detailed scientific study report with specific performance metrics and acceptance criteria. Therefore, many of the requested points, especially those related to specific performance metrics, sample sizes for training/test sets, ground truth establishment, and expert involvement, are not explicitly stated in this type of document.

Acceptance Criteria and Device Performance

Based on the nature of a 510(k) submission, the primary "acceptance criteria" is demonstrating substantial equivalence to legally marketed predicate devices. The "reported device performance" is essentially that it functions similarly and addresses the same intended use.

Study Details

The provided document describes a regulatory submission (510(k)), not a clinical study in the typical sense with explicit test sets, training sets, and human reader performance measurements.

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

   • Sample Size: Not specified. The document states "evaluations based on data provided in this 510(k)," but does not detail a specific test set size or methodology for evaluating performance.
   • Data Provenance: Not specified. Given it's a premarket notification, it likely involved bench testing and potentially some animal or cadaveric studies (though not mentioned explicitly as "data provenance"). There is no mention of country of origin or whether it was retrospective or prospective in a clinical sense.

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

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified. The document does not describe a process for establishing "ground truth" by experts for a test set.

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

   • Adjudication Method: Not applicable/Not specified. This type of regulatory submission does not typically involve adjudication of a test set by multiple readers.

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:

   • MRMC Study: No. This device is a physical implant (surgical mesh), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study related to human reader performance with AI assistance is not applicable.

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

   • Standalone Performance: No. This is a physical medical device, not an algorithm. Therefore, "standalone algorithm performance" is not applicable.

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

   • Type of Ground Truth: Not explicitly defined in terms of a clinical "ground truth." For a device like this, the "ground truth" would likely be established through biomechanical testing, material characterization, and potentially animal model compatibility, demonstrating the device's ability to "maintain the relative position of weak bony tissue" and its physical properties. It's not a diagnostic device with pathology or outcomes as direct ground truth for a discrete "test set."

7. The sample size for the training set:

   • Sample Size: Not applicable/Not specified. This is a physical device, and the concept of a "training set" as understood in machine learning/AI does not apply. If "training set" refers to data used during the device's development and optimization, it is not detailed in this submission.

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

   • Ground Truth Establishment: Not applicable/Not specified, as the concept of a "training set" with ground truth in the AI context does not apply here. Development involved engineering principles, material science, and possibly pre-clinical testing, but not "ground truth" as typically defined for AI/diagnostic studies.

Summary of what the document does provide:

• Device Description: A flexible, synthetic composite implantable mesh with polyester and ePTFE components, designed to be attached to the spine with suture anchors.
• Intended Use: To maintain the relative position of weak bony tissue (allografts/autografts) in spinal fusion procedures, in conjunction with rigid fixation, and not for load-bearing.
• Regulatory Pathway: 510(k) premarket notification, demonstrating substantial equivalence to predicate devices (K041105, K014200, K070148).
• Conclusion: The device is considered "as safe and effective" as legally marketed devices and "substantially equivalent" to the cited predicates based on the provided evaluation data.

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