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The Reliance Lumbar IBF System is indicated for intervertebral body fusion of the spine in skeletally mature patients. The device systems are designed for use with autogenous bone graft to facilitate fusion. One device may be used per intervertebral space. The implants are intended to be used with legally cleared supplemental spinal fixation cleared for the implanted level.

The Reliance Lumbar IBF System, when used as an Intervertebral Body Fusion device is also intended for use at either one level or two contiguous levels in the lumbar spine, from L2 to S1, for the treatment of degenerative disease (DDD) with up to Grade 1 Spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. The lumbar device is to be used with patients who have had six months of non-operative treatment.

The Reliance Lumbar IBF System, originally cleared by FDA in K113540, is intended to be used as an intervertebral body fusion device. Reliance Lumbar IBF device is a spacer, which inserts between vertebral bodies in the anterior column of the thoracic and lumbar spine. The device is surgically implanted between vertebral bodies from an anterior, lateral, or posterior surgical approach. The Reliance Lumbar IBF device will be manufactured from PEEK. The PEEK device also contains Tantalum wires to aid in fluoroscopic visualization. The construct is not intended to be employed as a standalone device. The Reliance Lumbar IBF is to be used with supplemental fixation in all applications.

The provided text describes a 510(k) premarket notification for the "Reliance Lumbar IBF System" and does not contain information related to an AI/ML powered device, nor does it present acceptance criteria or a study proving device performance as typically expected for such devices.

The document is for an intervertebral body fusion device and outlines its indications for use, technological modifications (additional implant sizes and instruments), and claims substantial equivalence to a predicate device. The conclusion is based on a risk analysis and design verification testing, not on a clinical study evaluating diagnostic or prognostic performance of an AI/ML algorithm.

Therefore, I cannot extract the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth, or training set size, as this information is not present in the provided context.

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