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The NuVasive® MLX™ - Medial Lateral Expandable Lumbar Interbody System is indicated for intervertebral body fusion of the spine in skeletally mature patients. The System is designed for use with autogenous bone graft to facilitate fusion. The MLX – Medial Lateral Expandable Lumbar Interbody System is intended for use at either one level or two contiguous levels in the lumbar spine, from L2 to S1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. Patients must have undergone a regimen of at least six (6) months of non-operative treatment prior to being treated with the MLX - Medial Lateral Expandable Lumbar Interbody System. The MLX -Medial Lateral Expandable Lumbar Interbody System is intended to be used with supplemental internal spinal fixation systems that are cleared by the FDA for use in the lumbar spine.

The NuVasive MLX – Medial Lateral Expandable Lumbar Interbody System is manufactured from Ti-6Al-4V ELI conforming to ASTM F136 and ISO 5832-3, Ti-6Al-4V conforming to ASTM 1472, and Nitinol SE508 conforming to ASTM F2063. The implants are available in a variety of different shapes and sizes to suit the individual pathology and anatomical conditions of the patient. This 510(k) covers design changes to MLX - Medial Lateral Expandable Lumbar Interbody System (K140770).

This document is a 510(k) premarket notification for a medical device, the NuVasive® MLX™-Medial Lateral Expandable Lumbar Interbody System. It details the device's indications for use, technological characteristics, and performance data to demonstrate substantial equivalence to previously cleared predicate devices.

Here's an analysis based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document only describes nonclinical testing and Finite Element Analysis (FEA) for the device. Clinical data (human subject testing) for a "test set" in the context of device performance in patients (e.g., efficacy, safety) is not mentioned in this 510(k) summary. The testing described is pre-market, bench-top lab testing for mechanical properties and computational analysis.

Therefore, the concepts of "sample size for the test set" and "data provenance (country of origin, retrospective/prospective)" as they relate to human patient data are not applicable to the data presented in this particular 510(k) summary.

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

This information is not applicable as the data presented is from nonclinical (bench and computational) testing, not clinical studies requiring expert ground truth for patient outcomes. The "ground truth" here would be the established ASTM standards and engineering principles for mechanical testing and FEA. Product engineers and test lab personnel with relevant expertise would interpret these results.

4. Adjudication Method for the Test Set

This is not applicable as the document describes nonclinical mechanical and computational testing, not clinical studies that typically involve adjudication of patient outcomes or diagnostic interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size.

This is not applicable. This 510(k) pertains to a physical medical implant (intervertebral body fusion device), not an AI/software device that would typically undergo MRMC studies for diagnostic accuracy or physician assistance.

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

This is not applicable. The device is a physical implant, not a software algorithm.

7. The Type of Ground Truth Used

For the nonclinical performance data, the "ground truth" is based on:

• Established ASTM standards (e.g., F2077, F2063, F136, F1472) for material properties and mechanical testing.
• Engineering principles and Finite Element Analysis (FEA) models for assessing structural integrity and predicting performance under various loads.

8. The Sample Size for the Training Set

This is not applicable. There is no mention of a "training set" in the context of machine learning or AI. The testing described focuses on evaluating the physical properties and performance of the manufactured device and its design changes.

9. How the Ground Truth for the Training Set was Established

This is not applicable for the reasons stated in point 8.

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