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The Mazor X is indicated for precise positioning of spinal implants during general spinal and brain surgery. It may be used in open or minimally invasive or percutaneous procedures.

Mazor X 3D imaging capabilities provide a processing and conversion of 2D fluoroscopic projections from standard C-Arms into volumetric 3D image. It is intended to be used whenever the clinician and/or patient benefits from generated 3D imaging of high contrast objects.

The Mazor X navigation tracks the position of instruments, during spinal surgery, in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of a patient.

The Mazor X System integrates a new Navigation feature, which enables tracking compatible spine instruments. The previously cleared Mazor X System enables mechanical positioning of a tool or instrument and determining its orientation and trajectory. The new Navigation feature tracks the position of compatible surgical instruments in or on the patient anatomy during surgery and continuously updates the instrument position on the image of the patient's anatomy. The modified Mazor X System can operate with or without the Navigation feature.

This document describes the FDA's clearance of the Mazor X System (Mazor X Stealth Edition) and the supporting performance testing. It focuses on demonstrating substantial equivalence to predicate devices, particularly regarding a new navigation feature.

Here's an analysis of the provided text in response to your request, identifying what information is available and what is not:

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

The document does not provide a specific table of acceptance criteria with corresponding performance metrics like a clinical trial report would. Instead, it globally states that the "overall accuracy under worst-case scenario navigation tool positioning calculated the position and trajectory errors" and that the "software changes did not affect the previously cleared robotic guidance trajectory accuracy (i.e. < 1.5mm)".

However, we can infer a key performance target related to accuracy:

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 for Test Set: The document mentions "Cadaver validation activities (GC17021, TP-GC17021)", but the number of cadavers or specific test samples (e.g., number of anatomical targets or measurements) for the navigation accuracy testing is not specified.
• Data Provenance: The cadaver studies likely used ex-vivo data. The country of origin for this data is not specified. It's implied to be a pre-clinical, prospective evaluation based on the nature of the testing.

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 provided. The document details engineering and software validation tests rather than clinical evaluations involving human expert readers for ground truth establishment.

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

This information is not provided. The performance testing described is technical validation of system accuracy, not a study requiring adjudication of human reader interpretations.

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

There is no indication that an MRMC study was performed or that the device (Mazor X Stealth Edition) involves "AI assistance" in the sense of an algorithm interpreting images for human readers. The device is described as a robotic guidance and navigation system.

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

The primary performance test described is "navigation accuracy testing," which evaluates the system's ability to accurately track instruments and guide trajectories. This is essentially a "standalone" or "device-only" performance assessment in a controlled (cadaver) environment, measuring the inherent accuracy of the system. The "robotic guidance trajectory accuracy (i.e. < 1.5mm)" is a key standalone accuracy parameter.

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

For the navigation accuracy testing, the ground truth would likely be established through precise metrological methods (e.g., coordinate measuring systems, high-resolution imaging with known fiducial markers) that can independently verify the true position and trajectory, against which the device's measurements are compared. The document mentions "Overall accuracy under worst-case scenario navigation tool positioning calculated the position and trajectory errors," implying a quantitative comparison to a known true value, but the specific method of establishing this precise ground truth is not detailed. It is not expert consensus, pathology, or outcomes data in the clinical sense.

8. The sample size for the training set

The document does not describe a training set in the context of a machine learning model, as the device is a robotic guidance system, not an AI diagnostic algorithm. Therefore, this information is not applicable/provided.

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

As there's no mention of a traditional machine learning training set, this information is not applicable/provided.

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