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The device is intended for the spatial positioning and orientation of instrument holders or tool guides to be used by surgeons to guide standard neurosurgical instruments during spine surgery. Guidance is based on an intra-operative plan developed with three dimensional imaging software provided that the required markers and rigid patient anatomy can be identified on 3D CT scans. The device is indicated for the placement of pedicle serews in lumbar vertebrae with a posterior approach

ROSA Spine is a computer controlled electromechanical arm providing guidance of neurosurgical instruments during spinal surgery.

ROSA Spine assists the surgeon in planning the position of instruments relative to intraoperative images.

Adequate position of the instrument holder is obtained from three-dimensional calculations performed from desired surgical planning parameters and registration of spatial position of the patient.

ROSA Spine provides a stable, accurate and reproducible mechanical guidance of neurosurgical instruments in accordance with an intraoperative planning.

While the provided document is a 510(k) premarket notification for the ROSA Spine device, it primarily focuses on establishing substantial equivalence to predicate devices rather than detailing a specific clinical study with detailed acceptance criteria and ground truth establishment for a diagnostic or AI-driven medical device. The ROSA Spine is described as a computer-controlled electromechanical arm for surgical guidance, not a device that makes diagnoses or predictions based on medical images in the way an AI algorithm might.

Therefore, many of the requested details, particularly those related to "AI improvement," "multi-reader multi-case studies," "ground truth establishment," and "training sets" are not applicable or explicitly stated for this type of surgical guidance system's 510(k) submission.

However, I can extract the relevant performance data and address the questions to the best of my ability based on the provided text, making it clear where the information is not present or not applicable.

Here's an attempt to answer your questions based on the provided document:

Device: ROSA Spine (a computer-controlled electromechanical arm for spinal surgical guidance)

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present these as "acceptance criteria" in a formal table with pre-defined thresholds the way an AI or diagnostic device might. However, it does provide performance metrics tested and reported for the device and its predicates. I will interpret "acceptance criteria" as the performance levels achieved that demonstrate equivalence and safety/effectiveness for this type of device.

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

• Sample Size for Device Performance Testing: "Testing were conducted on cadaveric specimens" - The exact number of cadaveric specimens is not specified.
• Data Provenance: The document does not explicitly state the country of origin for the cadaveric specimens or if the studies were retrospective or prospective. Given it's a 510(k) for a French company, it's plausible testing occurred in Europe or the US, but this is not stated. The context implies these were laboratory/simulated clinical environment tests.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Not applicable in the sense of typical AI ground truth for image interpretation. For a surgical guidance robot, "ground truth" relates to physical accuracy. The device's accuracy was verified against physical measurements. The document does not specify if "experts" were involved in setting up or verifying the cadaveric tests beyond standard engineering and clinical personnel.

4. Adjudication Method for the Test Set

• Not applicable as it's not an AI model requiring human consensus for interpretation. The performance metrics are objectively measured.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

• No, an MRMC study was NOT done. This type of study is typically performed for diagnostic devices, especially those involving human interpretation of medical images with or without AI assistance. The ROSA Spine is a robotic surgical guidance system, not a diagnostic imaging device.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• The "Performance Data" section describes "Device performance tests were performed to validate the absolute accuracy and repeatability of the robot arm, the application accuracy of the device, and the navigation accuracy according to ASTM F2554-10." This is essentially the standalone performance of the robot's mechanical and navigation capabilities, independent of a specific surgeon's skill in using it for the final instrument placement, although it is designed to guide human actions. It's not an "algorithm only" in the AI sense, but rather the robot's physical performance.

7. The Type of Ground Truth Used

• For the performance tests related to accuracy and repeatability, the ground truth was physical measurement against known standards or reference points (e.g., as per ASTM F2554-10) on cadaveric specimens. This is an objective measurement of the robot's mechanical and guidance precision.

8. The Sample Size for the Training Set

• Not applicable. This device is a robotic system; it is not an AI model that learns from a "training set" of data in the common machine learning sense. Its programming and algorithms are deterministic, based on physics and geometry.

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

• Not applicable, as there is no "training set" in the machine learning sense. The device's functionality is based on engineering principles and pre-programmed algorithms rather than data-driven learning.

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