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The Rectangular Corpectomy Cage is a vertebral body replacement system 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 vertebral body replacement in the thoracolumbar spine (from T1 to L5). The Rectangular Cage is intended for use with supplemental fixation cleared for use in the thoracolumbar spine and is to be used with autograft.

The Rectangular Corpectomy Cage consists of multiple components comprised of sterile, single-use implants fabricated from PEEK (ASTM F2026) with tantalum (ASTM F560) x-ray markers, or Titanium alloy (Ti6Al4V ELI, ASTM F136). The Rectangular Corpectomy Cage is used to replace a collapsed, damaged or unstable vertebral body resected or excised during total and partial vertebrectorny procedures due to tumor or trauma. They are designed to be used in conjunction with supplemental spinal fixation instrumentation.

The Rectangular Corpectomy Cage is comprised of implants designed to treat the thoracolumbar spine. The implants are available in a range of sizes and shapes to accommodate anterior. anterolateral, lateral and posterolateral surgical approaches and patient anatomy. Each cage has a hollow center to allow placement of autograft and/or allograft. Ridges on the superior and inferior surfaces of the device help to grip the endplates and prevent expulsion.

The provided document is a 510(k) premarket notification for a medical device (Rectangular Corpectomy Cage) and describes its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria in the context of an AI/algorithm-based medical device.

Therefore, most of the requested information regarding acceptance criteria, study design, expert involvement, and ground truth for an AI device is not available in these documents.

However, I can extract the information related to the performance testing that was conducted to demonstrate substantial equivalence, which serves a similar purpose in the context of this device.

Here's a breakdown of the available information:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state numerical acceptance criteria with corresponding performance results for these non-clinical tests. Instead, it states that "Design verification demonstrated the Subject Device is substantially equivalent to the predicate device." This implies that the performance of the Rectangular Corpectomy Cage met the standards demonstrated by the predicate devices, though specific values are not presented.

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

• Sample Size: The document mentions that testing was performed "on the worst case subject device." This implies that a limited number of physical devices were tested to represent the entire product line under the most challenging conditions. A specific numerical sample size is not provided, and for non-clinical mechanical testing, it's typically fewer units than for clinical trials.
• Data Provenance: The testing is non-clinical, meaning it's laboratory-based mechanical testing, not human subject data. Therefore, concepts like country of origin for data or retrospective/prospective do not apply.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable. For mechanical testing of a physical medical device, "ground truth" is defined by established engineering and biomechanical principles and standards (e.g., ASTM F2077). The "experts" involved would be the engineers and technicians performing and analyzing these tests.

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

This information is not applicable. Adjudication methods are relevant for human interpretation or clinical outcomes, not for objective mechanical performance tests.

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

This information is not applicable. An MRMC study is relevant for AI-assisted diagnostic or interpretive devices involving human readers. This document describes a physical implantable device.

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

This information is not applicable. This device is a physical implant, not an algorithm.

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

The "ground truth" for this type of non-clinical mechanical testing is established by the specified industry standards (e.g., ASTM F2077) and the physical properties and performance characteristics defined by sound engineering principles for intervertebral body fixation orthoses.

8. The sample size for the training set

This information is not applicable. There is no "training set" as this is not an AI/machine learning device.

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

This information is not applicable for the same reason as above.

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The Choice Spine Vertebral Body Replacement (VBR) System is intended for use in the thoracolumbar spine (T1-L5) to replace a collapsed, damaged, or unstable vertebral body due to tumor or trauma (i.e. fracture). The VBR device is intended for use with supplemental fixation & is to be used with autograft and/or allograft bone graft material.

The Choice Spine Vertebral Body Replacement (VBR) System devices have a basic oval shape with a hollow center for placement of bone graft. The superior & inferior surfaces have ridges, or 'teeth' for resisting migration. The devices are available in an assortment of heights & multiple angles of lordosis to accommodate different anatomic requirements.

This 510(k) summary describes a medical device called the "Choice Spine Vertebral Body Replacement (VBR) System," not an AI/ML powered medical device. Therefore, many of the requested categories for AI/ML performance studies are not applicable.

However, I can extract information related to the device's mechanical acceptance criteria and the study types performed to demonstrate substantial equivalence to predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size: This is a mechanical device, not an algorithm. The "sample size" refers to the number of devices or test specimens subjected to mechanical testing. The exact number of test specimens is not specified in the 510(k) summary but would be reported in the full test reports referenced by the ASTM standards.
• Data Provenance: The mechanical testing was performed in the context of demonstrating substantial equivalence for a medical device (spinal implant). The data provenance is from laboratory mechanical testing, not clinical data or human subjects.

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

• Not applicable. This is a mechanical device, and "ground truth" in the context of expert consensus or clinical outcomes is not relevant here. The "ground truth" for mechanical testing is established by engineering standards (e.g., ASTM F2267-04, ASTM F2077-03) and the quantitative measurements against those standards.

4. Adjudication method for the test set

• Not applicable. This is a mechanical device.

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 is a mechanical device, not an AI-powered diagnostic or assistive tool for human readers.

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

• Not applicable. This is a mechanical device, not an algorithm.

7. The type of ground truth used

• The "ground truth" for this device's performance relies on validated engineering standards and quantitative measurements of mechanical properties (e.g., load-bearing capacity, resistance to subsidence, resistance to expulsion, fatigue life). The acceptance criteria are typically defined as meeting or exceeding the performance of legally marketed predicate devices, as assessed by these standardized tests.

8. The sample size for the training set

• Not applicable. This is a mechanical device, not an AI algorithm requiring a training set.

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

• Not applicable. This is a mechanical device, not an AI algorithm.

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