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The SpineTune™ TL Spinal System is a posterior, noncervical pedicle fixation system indicated to provide immobilization and stabilization of spinal segments in skeletally-mature patients as an adjunct to fusion by autogenous bone graft in the treatment of the following acute and chronic instabilities or deformities of thoracic, lumbar and sacral spine:

• Spondylolisthesis (Grade 3 and 4) .
• Degenerative spondylolisthesis with objective evidence of neurological . impairment
• Trauma (i.e., fracture or dislocation) .
• Spinal stenosis .
• Deformities or curvatures (i.e., scoliosis, kyphosis, and/or lordosis) .
• . Tumor
• . Pseudoarthrosis
• Failed previous fusion .

The SpineTune™ TL Spinal System is a top-loading multiple fixation system which consists of pedicle screws, straight rods, curved cods, connectors and set which of polyaxial pedicle screw design and additional sizes of the straight and curved rods are an addition to the previously cleared SpineTune™ TL Spinal System (K100575).

The provided text describes a 510(k) summary for the LDR Spine SpineTune™ TL Spinal System. This document focuses on the mechanical testing of a physical medical device (spinal fixation system), not a software or AI-powered medical device. Therefore, the specific information requested about acceptance criteria, device performance, sample sizes for test/training sets, expert ground truth, MRMC studies, or standalone algorithm performance, as typically applied to AI/software for medical image analysis or similar diagnostic tools, is not present in the provided text.

The "study" described is non-clinical performance testing of the device's mechanical properties to demonstrate substantial equivalence to a predicate device, rather than a clinical study involving human subjects or an evaluation of an algorithm's diagnostic accuracy.

Here's a breakdown of what can be extracted and why other requested information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

Reasoning for table content: The document explicitly states: "The outcomes of non-clinical testing performed (static compression bending, static torsion, and axial compression fatigue testing) according to ASTM 1717 indicate that the cannulated polyaxial screw addition to the SpineTune™ Spinal System is substantially equivalent to the predicate device." The acceptance criterion is implicit in meeting the ASTM 1717 standards and demonstrating substantial equivalence.

Address for Missing Information:

The following requested information is not applicable or not present in the provided 510(k) summary because this document pertains to the mechanical testing of a physical implantable device, not an AI/software medical device:

• Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable for mechanical testing of a spinal system. The "test set" would be the number of screws/rods tested, but this detail is not provided.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for mechanical testing is based on engineering principles and ASTM standards, not expert medical opinion on images or diagnostics.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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 for AI/software in diagnostic settings.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): For mechanical testing, the "ground truth" is defined by the ASTM 1717 standard's pass/fail criteria for the physical properties of the materials and design.
• The sample size for the training set: Not applicable (no AI/ML model for training).
• How the ground truth for the training set was established: Not applicable.

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