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The VCFix Spinal System is indicated for use in the reduction of vertebral compression fractures that may result from osteoporosis or trauma (fracture types A according to Magerl/AO Spine classification) with or without posterior instrumental fixation, and compression fractures that result from malignant lesions (myeloma or osteolytic metastasis). The VCFix Spinal System is intended to be used in combination with Teknimed F20 bone cement, and to be placed, using a transpedicular approach, in a fractured vertebra from level T9 to L5.

The VCFix Spinal System is a cannulated screw-shaped implant with an expandable plate structure and is available in multiple sizes to accommodate varying patient anatomy. A pair of implants are inserted into the pedicles and manipulated with the toolset, resulting in the expansion of the device to restore the vertebral height. The implant is made of titanium alloy (Ti6Al4V ELI). During the procedure, the surgeon inserts the implants bilaterally through each pedicle of the fractured vertebra and adjusts the height and angle of the device (to correct local kyphosis) based on the unique vertebral fracture of the patient.
The VCFix Spinal System includes sterile, single-use implantation kits and a preparation kit. The kits include a pair of implants and all tools necessary for preparing the implant site and vertebral body expansion. The positioning and expansion of the implant must imperatively be followed by the injection of Teknimed F20 bone cement (K103433) to fixate the restored vertebral body. The bone cement and its delivery system are sold separately.

The provided text is a 510(k) clearance letter and summary for a medical device (VCFix Spinal System). It focuses on demonstrating substantial equivalence to predicate devices based on indications for use, technological characteristics, and performance testing.

Crucially, this document describes performance testing for a medical implant (a physical device), not an AI/ML medical device. The questions you've asked are specific to AI/ML device studies, particularly concerning acceptance criteria based on metrics like sensitivity, specificity, or F1 score, and elements like ground truth establishment and expert adjudication.

Because the VCFix Spinal System is a physical implant and not an AI/ML device, the detailed information requested about AI/ML specific study design (e.g., sample size for test set/training set, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth for AI) is not applicable and therefore not present in this document.

The "Performance Testing Summary" section describes the mechanical and functional testing conducted for the implant. These tests are designed to ensure the physical device meets its engineering specifications and safety requirements, not to evaluate the diagnostic or predictive performance of an AI algorithm.

Here's a breakdown of the relevant information provided and an explanation of why other requested information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a physical implant, "acceptance criteria" here refers to engineering specifications and mechanical performance standards, not statistical performance metrics for an AI algorithm. The document states that "All necessary testing has been performed for the worst-case configuration of the VCFix Spinal System to assure substantial equivalence to its predicates and to demonstrate the subject devices perform as intended."

Information Not Applicable / Not Available for this Type of Device (Physical Implant):

The following points are specific to AI/ML device studies and are not found in this document because the VCFix Spinal System is a physical implant, not an AI/ML software device.

2. Sample size used for the test set and the data provenance: Not applicable. Performance testing for implants involves physical specimens or in-vitro/in-vivo models, not image or clinical text data sets.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for AI/ML typically refers to expert labels on data. For an implant, "ground truth" relates to objective measurements from mechanical tests or clinical outcomes from trials (which are not detailed here beyond safety and equivalence).
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This refers to how expert disagreements are resolved for data labeling in AI/ML studies.
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. MRMC studies are for evaluating AI's impact on human diagnostic performance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This refers to the performance of an AI algorithm on its own.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable in the AI/ML sense. The "ground truth" for this device's performance would be the objective results of the specified mechanical and biological tests, demonstrating it meets engineering specifications and safety requirements.
8. The sample size for the training set: Not applicable. This device is not an AI/ML model that undergoes "training."
9. How the ground truth for the training set was established: Not applicable.

In summary, the provided FDA 510(k) pertains to a physical medical device (spinal implant) and its clearances are based on comprehensive engineering, mechanical, and biological testing, demonstrating substantial equivalence to existing predicate devices. Therefore, the specific details and study design elements common to AI/ML medical device evaluations are not present in this documentation.

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