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510(k) Data Aggregation
(102 days)
Choice Spine Navigation System
The Choice Spine Navigation reusable instruments are intended to be used during preparation and placement of Choice Spine Lancer™ and Thunderbolt™ system screws during spinal surgery to assist the surgeon in precisely locating anatomical structures in either open or minimally invasive procedures. The Choice Spine Navigation reusable instruments are specifically designed for use with the Medtronic® 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 a skull, a long bone, or vertebra, can be identified relative to a CT or MR based model, fluoroscopy images, or digitized landmarks of the anatomy.
The Choice Spine Navigation instruments are non-sterile, reusable instruments designed to function with the Medtronic® StealthStation® System and SureTrak® II System. The Choice Spine Navigation instruments are for use with Choice Spine pedicle screw systems, specifically, the Lancer™ and Thunderbolt™ Pedicle Screw Systems. The instruments are manufactured from medical grade titanium and stainless steel.
The provided text describes a 510(k) premarket notification for the "Choice Spine Navigation System." This submission focuses on establishing substantial equivalence to a predicate device, rather than proving the device's absolute performance against a set of de novo acceptance criteria through extensive clinical studies, as might be required for a PMA or novel device.
The context of a 510(k) submission means the "device performance" and "acceptance criteria" are viewed through the lens of demonstrating equivalence to a legally marketed predicate. Therefore, the "study" proving it meets acceptance criteria is primarily an engineering and non-clinical performance assessment against a recognized standard (ASTM F2554-10).
Here's an analysis based on the provided text:
Acceptance Criteria and Reported Device Performance
The core acceptance criterion for a 510(k) is substantial equivalence to a predicate device. This is demonstrated by showing that the new device has "nearly identical technological characteristics" and that any minor differences "do not raise any new issues of safety and effectiveness."
The specific performance testing mentioned is for positional accuracy, as this is a critical function of a surgical navigation system.
Acceptance Criterion (Implicit for Substantial Equivalence via 510(k)) | Reported Device Performance |
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Overall Safety & Effectiveness | "The overall technology characteristics and performance data lead to the conclusion that the Navigation System is substantially equivalent to the predicate device." |
Technological Characteristics | "The subject and predicate devices have nearly identical technological characteristics and the minor differences do not raise any new issues of safety and effectiveness." (Specifically, identical Indications for Use, Principle of Operation, Technical Characteristics including Sterility, Interfacing, Sizes). |
Positional Accuracy (specific to navigation systems) | "The Navigation System has been tested per ASTM F2554-10, 'Standard Practice for Measurement of Positional Accuracy of Computer Assisted Surgical Systems.'" |
"The results of this non-clinical testing show that performance of the Navigation System is sufficient for its intended use and is substantially equivalent to legally marketed predicate devices." (No specific numerical accuracy values are provided in this summary document.) | |
Material Compatibility | The only difference cited is the use of additional materials (Radel, Ketaspire KT-820 CF30, Ti-6Al-4V per ASTM F136, and PTFE) in addition to stainless steel. The implication is that these materials are deemed safe and do not raise new safety concerns. |
Important Note: The provided text is a summarization for FDA submission. It generally does not include the detailed numerical results from performance tests; instead, it states the conclusion that the performance was "sufficient for its intended use" and "substantially equivalent." Full test reports would contain the exact measurements.
Additional Information on the Study (Based on 510(k) Context)
Given this is a 510(k) submission, the "study" proving the device meets acceptance criteria is primarily a non-clinical performance study and comparison to predicates.
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Sample sizes used for the test set and the data provenance:
- The document explicitly states "non-clinical testing" and references ASTM F2554-10. This standard typically involves laboratory-based measurements rather than human patient data.
- Therefore, the "test set" would consist of physical test setups or mock anatomy used to measure positional accuracy according to the ASTM standard.
- No specific sample size for "cases" is mentioned, as it's not a clinical study on patients. The "sample size" would relate to the number of measurements taken during the laboratory testing according to the standard.
- Data Provenance: The testing was conducted by Choice Spine, LP., based in the USA. It's non-clinical/bench testing, not retrospective or prospective patient data from specific countries.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- For non-clinical performance testing like positional accuracy per ASTM F2554-10, expert consensus in the form of physical measurement standards and calibrated equipment establishes the "ground truth." There are no human experts adjudicating clinical images or outcomes.
- The "experts" involved would be engineers and technicians trained in metrology and the use of the specified testing equipment (e.g., optical tracking systems, coordinate measuring machines) to perform the measurements according to the standard. Their qualifications would be in engineering and quality assurance/testing.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable in this context. Adjudication methods like 2+1 or 3+1 are used for human expert interpretation of clinical data (e.g., medical images) to establish a consensus ground truth.
- For non-clinical performance testing, the "ground truth" is derived from calibrated measurement devices and the precise execution of a standardized testing protocol (ASTM F2554-10). The results are quantitative measurements.
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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 conducted for this submission.
- This device is a surgical navigation system, not an AI-assisted diagnostic imaging device. Its function is to guide physical instruments in real-time during surgery, not to interpret images or assist "human readers" in a diagnostic context.
- Therefore, the concept of "human readers improve with AI vs without AI assistance" is not relevant to this device's intended use and assessment.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The device itself is standalone in its measurement capability, but its intended use is inherently human-in-the-loop, assisting a surgeon.
- The "performance" tested (positional accuracy) reflects the algorithm's ability to track and display positions accurately. This test is a standalone assessment of the system's mechanical and computational accuracy, independent of a specific surgical procedure or patient.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The ground truth for the positional accuracy testing is based on metrological standards and precise physical measurements obtained from calibrated equipment according to ASTM F2554-10.
- It is not expert consensus on clinical findings, pathology, or patient outcomes data.
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The sample size for the training set:
- Not applicable. This device is hardware and software for surgical navigation. It's not described as an AI/machine learning device that requires a "training set" of data in the typical sense (e.g., for image classification or prediction).
- Its functionality is based on established engineering principles (e.g., optical tracking, coordinate systems) and algorithms, not data-driven machine learning models that learn from a "training set."
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How the ground truth for the training set was established:
- Not applicable, as there is no "training set" in the context of machine learning for this device.
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