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The REMI™ Robotic Navigation System is intended for use as an aid for precisely locating anatomical structures and for the spatial positioning and orientation of a tool holder or guide tube to be used by surgeons for navigating and/or guiding compatible surgical instruments in open or percutaneous spinal procedures in reference to rigid patient anatomy and fiducials that can be identified on a 3D imaging scan. The REMI™ Robotic Navigation System is indicated for assisting the surgeon in placing pedicle screws in the posterior lumbar region (LI-S1). The system is designed for lumbar pedicle screw placement with the prone position and is compatible with the Accelus LineSider® Spinal System.

The Remi Robotic Navigation System (Remi) is an image guided system primarily comprised of a computer workstation, software, a trajectory system, including a targeting platform, a camera, and various image guided instruments intended for assisting the surgeon in placing screws in the pedicles of the lumbar spine. The system operates in a similar manner to other optical-based image y systems.

The provided text outlines the FDA 510(k) clearance for the REMI Robotic Navigation System, focusing on its substantial equivalence to a predicate device. However, it does not contain a detailed study report or explicit acceptance criteria with reported device performance metrics in the format requested.

The document primarily focuses on demonstrating that the updated REMI system, with additional compatible 3D imaging systems, is substantially equivalent to its predicate. The "Performance Testing - Bench" section mentions tests conducted but does not provide specific numerical acceptance criteria or performance results.

Therefore, much of the requested information cannot be extracted directly from the provided text. I will indicate where information is missing or inferred.

Acceptance Criteria and Device Performance

Study Details from the provided text:

1. Sample size used for the test set and the data provenance:

   • The document mentions "Performance Testing - Bench" and "Verification and validation testing" but does not specify the sample size for any test set or the data provenance (e.g., country of origin, retrospective/prospective). It suggests bench testing was primarily used for equivalence.

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

   • No information provided. The "performance testing" described appears to be technical validation against specified equivalence factors rather than expert review of clinical outcomes or images.

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

   • No information provided.

4. 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:

   • No, an MRMC study was not described. This device is a robotic navigation system for spinal surgery, not an AI-assisted diagnostic imaging interpretation tool that would typically involve human readers. Its purpose is to aid surgeons in pedicle screw placement.

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

   • The document does not explicitly describe a "standalone" algorithmic performance test in the context of an AI-only system. The device is a navigation system that guides a human surgeon. Its performance metrics, like accuracy, are inherently tied to the system's ability to guide to a planned trajectory, which can be measured quantitatively in bench tests. The bench testing mentioned covers aspects like "Accuracy," "Image Quality," "Image Transfer Speed," and "Image Registration Speed."

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

   • Based on the description of "Performance Testing - Bench" and "Accuracy verification on anatomical landmarks" (for the predicate), the ground truth for accuracy testing would typically involve precisely measured physical points or targets on a phantom or model, measured by a highly accurate reference system (e.g., CMM). For image quality, transfer, and registration speed, the ground truth would be objectively defined technical specifications or measurements.

7. The sample size for the training set:

   • No information provided about a "training set." The REMI system is a robotic navigation system, not described as a deep learning or machine learning-based algorithm that typically requires a large training dataset for model development. The system uses pre-programmed logic, image processing, and control algorithms.

8. How the ground truth for the training set was established:

   • Not applicable, as no training set for an AI/ML model is mentioned.

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Integrity Implants Navigated Instruments are intended to be used during the preparation and placement of Integrity Implants spinal implants during spinal surgery to assist the surgeon in precisely locating anatomical structures in either open or minimally invasive procedures.

Integrity Implants Navigated Instruments are specifically designed for use with Medtronic's StealthStation System, which is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as vertebra, can be identified relative to a CT or MR-based model, finages, or digitized landmarks of the anatomy.

The Integrity Implants Navigated Instruments include non-sterile screw drivers, cannulated and solid taps (4.0 - 10.5 mm), probes, and awls designed to function with the Medtronic StealthStation® System and NavLock® Tracker. The subject devices are for use with the Integrity Implants LineSider® Spinal System (K190360 and K203367). The instruments are manufactured from stainless steel and Radel.

The provided text is a 510(k) summary for the Integrity Implants Navigated Instruments. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study to prove the device meets specific acceptance criteria for performance as an AI/ML-driven diagnostic or prognostic device.

However, I can extract information related to performance testing and acceptance criteria as much as possible from the provided text, while acknowledging that it's not a typical study report for acceptance criteria in the sense of accuracy, sensitivity, or specificity for AI/ML.

Here's a breakdown of the information based on your request, with limitations due to the nature of the document:

1. Table of Acceptance Criteria and Reported Device Performance

Limitations: The document does not provide specific quantitative acceptance criteria (e.g., "positional accuracy must be within X mm") or specific quantitative results for each test. It states that tests were "completed to ensure" functionality and compatibility and that the devices are "as safe and effective" as the predicate, implying that acceptance criteria were met, but without detailing them.

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

The document does not specify a "test set sample size" or "data provenance" in the context of typical AI/ML performance studies (e.g., number of images, patient demographics). The performance data cited refers to:

• Accuracy testing: Performed in accordance with ASTM F2554-18. This standard likely dictates the setup and number of measurements, but the specific details (e.g., number of physical instruments tested, number of measurement points per instrument) are not provided.
• Registration testing: Details on the sample size (e.g., number of instruments registered, number of registration attempts) are not provided.
• Dimensional analysis: This likely involved comparing instrument dimensions, but the "sample size" here refers to the number of device types/models evaluated, which can be inferred from Section IV and the comparison table.
• Cleaning and sterilization validation data: Leveraged from a previous 510(k) (K190360). This implies prior validation studies were conducted, but their specific sample sizes are not detailed in this document.

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

This information is not applicable and not provided in the document. This device is a surgical instrument intended for use with a navigation system, not a diagnostic or prognostic AI/ML device that generates clinical findings requiring expert ground truth for a test set. The "ground truth" for its performance would be engineering measurements and physical tests.

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

Not applicable, as this is not an AI/ML diagnostic/prognostic device relying on human expert review for ground truth.

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 not an AI-assisted diagnostic or prognostic device that involves human readers interpreting output. It's a navigated surgical instrument.

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

This concept is somewhat applicable in the sense that the navigational system's accuracy and the instrument's compatibility with it can be tested independently of a surgeon's clinical use. The "accuracy testing in accordance with ASTM F2554-18" and "registration testing" would fall under this category of standalone performance assessment of the instrument's interaction with the navigation system. The document does not, however, detail specific performance metrics or results from these standalone tests beyond stating they were performed.

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

For the type of device described, the "ground truth" would be established through:

• Physical measurements and engineering standards: For accuracy (e.g., comparing navigated position to physically measured position in a test setup per ASTM F2554-18).
• Functional tests: To confirm proper registration and compatibility with the StealthStation system.
• Dimensional specifications: For dimensional analysis.

It is not based on expert consensus, pathology, or outcomes data in the clinical diagnostic sense.

8. The sample size for the training set

Not applicable. This device is not an AI/ML model that undergoes a "training set" process.

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

Not applicable, as there is no "training set" for this type of device.

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LineSider™ Spinal System, with or without MIS instrumentation, is intended for posterior, non-cervical fixation in skeletally mature patients as an adjunct to fusion for the following indications: degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies); spondylolisthesis; trauma (i.e. fracture or dislocation); spinal stenosis; curvatures (i.e., scoliosis and/or lordosis); tumor; pseudarthrosis; and/or failed previous fusion.

When used for posterior non-cervical pedicle screw fixation in pediatric patients, LineSider™ Spinal System implants are indicated as an adjunct to fusion to treat progressive spinal deformities (i.e., scoliosis) including idiopathic scoliosis, neuromuscular scoliosis, and congental scoliosis. Additionally, LineSider™ is intended to treat pediatric patients diagnosed with the following conditions: spondylolysis; fracture caused by tumor and/or trauma. LineSider™ Spinal System is intended to be used with autograft. Pediatric pedicle screw fixation is limited to a posterior approach.

The LineSider™ Spinal System is a thoracolumbosacral pedicle screw system containing metallic implants intended to provide immobilization of spinal segments. The system consists of a variety of screws, hooks, rods, set screws, crosslink connectors, rod-to-rod connectors, iliac connectors, and associated instruments. Components are offered in various shapes and sizes to meet the requirements of the individual patient anatomy. The LineSider™ Spinal System subject to this 510(k) adds non-modular screws to the line offered under K190360.

This document is a 510(k) summary for the LineSider™ Spinal System, which is a thoracolumbosacral pedicle screw system. It describes an expansion of an already cleared device to include non-modular screws.

Based on the provided text, the device itself is a spinal implant system, not an AI or imaging device with performance metrics like accuracy, sensitivity, or specificity. Therefore, many of the requested categories for AI/imaging device studies (like sample size for test/training sets, ground truth establishment, expert qualifications, MRMC studies) are not applicable.

The "acceptance criteria" and "device performance" instead refer to mechanical strength and substantial equivalence to predicate devices, rather than diagnostic accuracy.

Here's a breakdown of the applicable information:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Test Set Sample Size: Not applicable. This refers to mechanical testing of physical parts, not a data-driven test set for an algorithm. The testing involves physical samples of the spinal system components.
• Data Provenance: Not applicable in the context of clinical or image data. The data provenance is from laboratory mechanical testing performed by Empirical Testing Corp. (Colorado Springs, Colorado).

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)

• Not applicable. Ground truth in this context refers to the physical properties of the spinal implants, which are assessed through standardized mechanical testing according to ASTM F1717. The "ground truth" is adherence to established engineering standards rather than expert clinical consensus.

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

• Not applicable. Adjudication methods are typically for reconciling discrepancies in human expert evaluations. Mechanical testing results are objective measurements.

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 medical device (spinal implant) clearance, not an AI diagnostic or assistance tool.

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

• Not applicable. This is for a physical medical device, not an algorithm.

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

• Type of Ground Truth: The "ground truth" for this device's performance is compliance with pre-defined mechanical performance standards (ASTM F1717), which ensure the device's structural integrity and equivalence to predicate devices under specified loads and conditions.

8. The sample size for the training set

• Not applicable. There is no "training set" in the context of mechanical testing for a spinal implant.

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

• Not applicable. There is no "training set" for this type of device submission.

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