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The Cezanne II Interbody Fusion System is indicated for intervertebral body fusion of the lumbar spine, from L2 to SI, in skeletally mature patients who have had six months of non-operative treatment. The device is intended for use at either one level or two contiguous levels for the treatment of degenerative disc disease (DDD) with up to Grade l spondylolisthesis or retrolisthesis at the involved level(s). DOD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. The device system is designed for use with supplemental fixation and with autograft to facilitate fusion.

The Cezanne II Interbody Fusion System will be offered in various device configurations based on surgical approach and patient anatomy. The Cezanne II System consists of XLIF, TLIF and ALIF implants.

The System implant components are made of polyether ether ketone (PEEK Optima LT1) that conforms to ASTM F2026. Additionally, the devices contain tantalum markers (ASTM F560) to assist the surgeon with proper placement of the device.

The System is implanted using a combination of device specific and universal class I instruments manufactured from stainless steel materials that conform to ASTM F899.

Note: The provided text describes a 510(k) premarket notification for a medical device, the "Accel Spine Cezanne II Interbody Fusion System." This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, primarily through non-clinical testing (mechanical tests). It does not involve clinical studies or AI algorithm performance, which are the typical contexts for the acceptance criteria and study design questions you've posed.

Therefore, many of the requested fields are not applicable to the information provided in this 510(k) summary. I will answer based only on the information present in the document.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable. The study involved non-clinical mechanical testing of the device, not a test set of data such as images or patient records.
• Data Provenance: Not applicable. The "data" comes from engineering tests performed according to specific ASTM standards in a lab setting, not from patients or a specific country of origin. The tests were "non-clinical."

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

• Not applicable. Ground truth, in the context of expert review, is not relevant for this type of non-clinical mechanical testing. The "ground truth" for these tests is defined by the objective physical properties and performance measured according to the specified ASTM standards.

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

• Not applicable. Adjudication methods are used in studies involving expert review or subjective interpretation of data, which is not the case here.

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 510(k) submission for an interbody fusion system, not an AI-powered diagnostic device. No MRMC study was conducted.

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

• Not applicable. This is a physical medical device (interbody fusion system), not an algorithm or AI.

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

• The "ground truth" for the non-clinical testing is defined by the objective measurements and pass/fail criteria established by the specific ASTM standards (F2077-11, F2267-04, F-04.25.02.02, F2026, F560, F899). It is a form of empirical measurement against established engineering standards.

8. The sample size for the training set

• Not applicable. This is a physical medical device, not an AI model requiring a training set.

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

• Not applicable. This is a physical medical device, not an AI model requiring a training set.

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