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The ROI-T Implant is indicated for use to replace a vertebral body that has been resected or excised due to tumor or trauma/fracture. The device is intended for use as a partial vertebral body replacement in the thoracolumbar spine (from T1 to L5) and is intended for use with supplemental internal fixation. The ROI-T may be implanted singularly or in pairs. Supplemental internal fixation is required to properly utilize this system.

The ROI-T Implants are crescent shaped blocks in a variety heights and lordosis angles. The shape of the ROI-T offers more options to the surgeon to adapt to the patient' anatomy.

The ROI-T Implant features a closed graft space and offers superior vascularization of that space. The inferior and superior surfaces of the devices have a pattern of teeth to provide increased stability and inhibit movement of the implants.

This device, the LDR Spine ROI-T Implant, is a medical device and not an AI/ML-driven diagnostic tool. Therefore, the questions related to AI/ML specific acceptance criteria, studies, ground truth, and expert involvement are not applicable in this context.

Acceptance Criteria and Device Performance:

The primary acceptance criteria for medical devices like the LDR Spine ROI-T Implant, especially for 510(k) submissions, revolve around demonstrating substantial equivalence to a legally marketed predicate device. This typically involves non-clinical performance data (e.g., mechanical testing, biocompatibility) rather than clinical studies with human readers or AI performance metrics.

Study Proving Device Meets Acceptance Criteria:

The study proving the device meets the acceptance criteria is a non-clinical performance study focused on mechanical properties.

1. Table of Acceptance Criteria and Reported Device Performance:

   Acceptance Criteria (Implied)	Reported Device Performance
   Substantial equivalence to predicate device (ROI-T System) for mechanical properties.	"Finite Element Analysis results demonstrated that the proposed ROI-T Implant is substantially equivalent to the predicate device."

2. Sample Size used for the test set and the data provenance:

   • Sample Size: Not applicable in the context of Finite Element Analysis (FEA). FEA is a computer-based simulation, not a traditional test set with a sample size of physical units.
   • Data Provenance: Not applicable. FEA is a computational method.

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

   • Not applicable. FEA uses engineering principles and material properties as its "ground truth" or input data, not expert consensus in a medical diagnostic sense. Engineers or biomechanical experts would design and validate the FEA model.

4. Adjudication method for the test set:

   • Not applicable. FEA results are analyzed and validated against engineering standards or established methods, not through an adjudication process.

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.

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

   • No. This is not an AI/ML device.

7. The type of ground truth used:

   • The "ground truth" for non-clinical performance data like FEA is based on:
     • Material properties: Established scientific and engineering data for the materials used (e.g., titanium alloys).
     • Biomechanical principles: Accepted biomechanical models and principles related to spinal load-bearing and stability.
     • Predicate device performance: The known mechanical performance characteristics of the legally marketed predicate device, against which the new device's FEA results are compared.

8. The sample size for the training set:

   • Not applicable. This is not an AI/ML device. FEA involves defining geometries, material properties, and boundary conditions, not a data training set.

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

   • Not applicable. This is not an AI/ML device.

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