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The TenZing System is a combination of the SpineAssist System and C-InSight System, allowing the C-InSight application to run on the SpineAssist Workstation: The SpineAssist™ System is indicated for precise positioning of surgical instruments or implants during general spinal surgery. The SpineAssist™ System may be used in either open or percutaneous procedures.

The C-InSight software provides 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 particularly in orthopedic applications.

The TenZing system is a device modification of the SpineAssist system, designed to incorporate both the original SpineAssist system and the C-InSight system in one workstation. The TenZing console is identical to the SpineAssist console. The system is intended to be used in a variety of hospital locations (e.g., OR, trauma unit, etc.). The main components of the TenZing System include:

A. Workstation

B. SpineAssist accessories:

Surgical Accessories Kit .

Setup Kit .

C. SpineAssist Device

D. C-InSight accessories:

Spine Target Kit .

Extremities Target Kit .

E. Image Adaptor

F. Spine Assist Disposable kits

G. C-InSight Sterile Sheath Disposable kits

Here's an analysis of the provided text regarding the TenZing System's acceptance criteria and studies, organized by your requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document (K102130) does not explicitly state specific quantitative acceptance criteria (e.g., accuracy thresholds, precision targets) for the Tenzing System. It focuses on demonstrating substantial equivalence to predicate devices and software validation rather than specific performance metrics against pre-defined criteria.

Therefore, a table of acceptance criteria and reported device performance cannot be generated from this document. The document states:

• "There are no performance standards under the Federal Food, Drug and Cosmetic Act, for the TenZing device." (Section 7)
• "The TenZing System software was subject to software validation testing in accordance with the FDA Guidance for the Premarket Submissions for Software Contained in Medical Devices (January 11, 2002)." (Section 8)
• "The technological characteristics, e.g., overall design, materials, mechanism of action, mode of operation, performance characteristics, etc., and the intended use of the TenZing device are substantially equivalent to the predicate device cited above." (Section 9)

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

The document does not provide details on sample sizes for test sets used in performance evaluation, nor does it specify the provenance (country of origin, retrospective/prospective) of data used for any testing. The testing described is "software validation testing," which typically involves internal verification and validation against requirements rather than clinical performance testing with patient data detailed in this type of submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

This information is not provided in the document. Software validation testing usually involves internal testing teams and engineers, not external clinical experts for ground truth establishment in the way described for AI/diagnostic devices.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Human Readers Improving with AI vs. Without AI Assistance

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed or reported in this document. The TenZing System is a surgical navigation and 3D imaging system, not a diagnostic AI system intended to improve human reader performance in interpreting images. Its purpose is to guide surgeons and provide 3D imagery from 2D fluoroscopy.

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

The document describes "software validation testing" (Section 8). This constitutes a form of standalone testing of the algorithm and software components against their specifications and functional requirements. However, specific performance metrics (e.g., accuracy of 3D reconstruction, precision of navigation guidance) from such standalone testing are not detailed in this submission. The "substantial equivalence" argument (Section 9) implies that its standalone performance characteristic is comparable to its predicates.

7. The Type of Ground Truth Used

For the "software validation testing," the ground truth would typically be defined by the system's functional and technical specifications, and the accuracy of its outputs (e.g., 3D reconstruction from 2D, positioning accuracy) would be verified against known inputs and expected computations. It is not based on expert consensus, pathology, or outcomes data in the clinical sense for this type of device.

8. The Sample Size for the Training Set

The document does not mention a training set, as the TenZing System is not described as an AI/machine learning device that requires a training set in the conventional sense. It's a system that combines existing technologies (SpineAssist, C-InSight) and associated software.

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

As no training set is mentioned or implied for an AI/ML model, this information is not applicable and therefore not provided.

Summary of Device and Approval Context:

The TenZing System (K102130) is a combination device integrating features of two previously cleared Mazor Surgical Technologies systems: SpineAssist (K073467) and C-InSight (K081672). It acts as a workstation to run both applications.

• SpineAssist: Indicated for precise positioning of surgical instruments or implants during general spinal surgery (open or percutaneous procedures).
• C-InSight: Provides processing and conversion of 2D fluoroscopic projections from standard C-Arms into volumetric 3D images, for high contrast objects in orthopedic applications.

The approval is based on substantial equivalence to these predicate devices. The primary performance testing mentioned is software validation to FDA guidance. This type of 510(k) submission generally relies on demonstrating that the new device does not raise new questions of safety or effectiveness compared to legally marketed predicates, rather than presenting novel clinical performance data or extensive studies like those required for de novo AI devices.

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The C-InSight software provides 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 particularly for orthopedic applications.

C-InSight is a software based product, which converts a sequence of Two-dimensional fluoroscopy images into a 3D volume, intraoperatively. The C-InSight is an add-on to commercially available mobile x-ray systems.

Here's an analysis of the acceptance criteria and study information for the C-InSight System, based on the provided text:

Key Takeaways Before Diving In:

• This device, the C-InSight System, is a software-based product that converts 2D fluoroscopy images into 3D volumes intraoperatively.
• No clinical performance data (human studies) are provided or stated as applicable. The evaluation relies entirely on non-clinical performance tests.
• The primary purpose of these tests is to establish substantial equivalence to predicate devices.
• The acceptance criteria are implicitly tied to meeting design and performance specifications as demonstrated by a series of non-clinical tests.

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria with corresponding performance metrics. Instead, it lists the types of non-clinical performance tests conducted and then concludes that these tests demonstrate the system "meets its design and performance specifications."

Implicit Acceptance Criteria and Reported Performance (Derived from the text):

Study Information

1. Sample Size Used for the Test Set and Data Provenance:

   • Test Set Sample Size: Not explicitly stated as a number of "cases" or "patients." For the "C-InSight accuracy vs. CT (cadaver tests)," the sample size would refer to the number of cadavers used, but this number is not provided. For synthetic and spine accuracy tests, the "sample size" would likely refer to the number of simulated or phantom test runs, which is also not specified.
   • Data Provenance:
     • Country of Origin: Not specified in the provided text.
     • Retrospective or Prospective: Not applicable, as no human clinical data was used. The tests seem to be controlled, laboratory-based non-clinical assessments.

2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

   • Not applicable (N/A). The document describes non-clinical tests, not human-read clinical studies requiring expert ground truth establishment for a diagnostic output. For accuracy tests (synthetic, spine, cadaver vs. CT), "ground truth" would likely be established by known physical parameters of the phantom/cadaver or high-resolution CT scans, not human expert consensus on images generated by the C-InSight system.

3. Adjudication Method for the Test Set:

   • Not applicable (N/A). No human readers are performing diagnoses or evaluations of the device output that would require adjudication. The accuracy tests likely compare the C-InSight's 3D reconstructions against known physical measurements or higher-resolution imaging (like CT).

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. The document explicitly states "Clinical Performance Data: Not Applicable." Therefore, no MRMC study involving human readers was conducted or reported.

5. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

   • Yes, this appears to be the primary focus of the performance evaluation. The "Non-Clinical Performance Data" section describes tests of the C-InSight system's intrinsic capabilities (e.g., accuracy, image quality, software validation) as a standalone software product. The device is a "3-D Reconstruction Tool," and its performance is evaluated based on how well it generates these reconstructions.

6. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.):

   • For the accuracy tests (synthetic, spine, cadaver vs. CT): The ground truth would presumably be the known physical reality or a higher-fidelity imaging modality's output.
     • For "synthetic accuracy," it likely refers to a simulated environment with known parameters.
     • For "spine accuracy," it could involve phantoms with precisely known anatomical dimensions.
     • For "accuracy vs. CT (cadaver tests)," the ground truth would be the 3D anatomical information obtained from high-resolution CT scans of the cadavers, against which the C-InSight's reconstructions are compared.
   • For software validation, image quality, and radiation dose: Ground truth would be defined by pre-established engineering specifications, industry standards, or regulatory guidelines.

7. The Sample Size for the Training Set:

   • Not provided. The document describes a ready-to-use software product and its validation tests, not a machine learning model that requires a "training set." While the software likely uses algorithms developed using data, the specifics of such development data (if any) are not discussed in this 510(k) summary.

8. How the Ground Truth for the Training Set Was Established:

   • Not provided, as the document does not mention a training set in the context of device validation.

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The SpineAssist™ System is indicated for precise positioning of surgical instruments or implants during general spinal surgery. The SpineAssist™ System may be used in either open or percutaneous procedures.

The SpineAssist™ system is a computer controlled miniature medical image-guided surgery (IGS) system, which serves as a technological platform for solutions that provide unprecedented levels of accuracy, precision and accessibility in performing orthopedic procedures. The SpineAssist™ is designed to assist surgeons in precisely guiding handheld surgical tools in line with a computerized, image-based pre-operative plan along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the SpineAssist device, which positions its articulating arm and tool guide. Using a special bone attachment component (i.e., a clamp and bridge, the Hover-T / Bi-lateral Hover-T bridge, the Bed Mount Hover-T or the Cervical Kit) the SpineAssist device attaches to the bone in the area where the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools according to the computerized, image-based, pre-operative plan.

The main components of the SpineAssist™ system include:
A. SpineAssist™ device
B. Workstation
C. Accessories including the Clamp Kit for less invasive procedures, the MIS platforms: Hover-T, Bi-lateral Hover-T, Bed Mount Hover-T and the Cervical Kit, the last one intended for less invasive procedures.

Here's an analysis of the provided text regarding the SpineAssist™ System's acceptance criteria and studies:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states that the performance tests "demonstrate that SpineAssist system meets its design and performance specifications." However, it does not provide specific quantitative acceptance criteria or detailed results for each test (e.g., "accuracy within X mm"). It only indicates that these tests were performed to validate stability and accuracy for the extended intended use.

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

• Test Set Sample Size: Not explicitly stated as a numerical sample size. The document mentions tests were performed "on cadavers to simulate real clinical procedures." The number of cadavers used is not specified.
• Data Provenance: The cadaver tests were described as simulating clinical procedures, but the origin of the cadavers (e.g., country) is not mentioned. These were non-clinical tests. The study is prospective as it involved performing tests to gather data for the submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• This information is not provided in the given text. The tests were "stability and accuracy tests... performed on cadavers," implying a technical assessment rather than a human expert consensus for "ground truth" related to device performance metrics.

4. Adjudication Method for the Test Set

• This information is not applicable and not provided. The performance tests described (stability, accuracy) are typically measured objectively by technical instrumentation rather than requiring a human adjudication process like in a diagnostic study.

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

• No, an MRMC comparative effectiveness study was not done. This submission is for a surgical navigation system, not an AI-assisted diagnostic tool. There is no mention of human readers or AI assistance in a diagnostic context.

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

• Yes, standalone (algorithm/device only) performance tests were done. The "Non-Clinical Performance Data" section describes various stability and accuracy tests performed on the SpineAssist™ system itself (e.g., "Bed Mount Hover-T Stability Test," "Cervical Accuracy C1-C6 Test"). These tests evaluate the device's technical specifications without necessarily involving human surgical performance in a comparative study. The software validation is also a standalone assessment of the algorithmic components.

7. The Type of Ground Truth Used

• For the accuracy and stability tests, the ground truth would likely be established through pre-defined anatomical landmarks or precise measurements taken by a high-precision measurement system (e.g., optical tracking, CMM). For example, in an "accuracy" test, the deviation of the navigated tool from a known target trajectory or point would be measured against a gold standard reference. The text doesn't explicitly state the methodology for establishing this ground truth but implies it's based on physical measurements and engineering specifications.

8. The Sample Size for the Training Set

• This information is not applicable and not provided. The SpineAssist™ system is described as a "computer controlled miniature medical image-guided surgery (IGS) system" that processes images and exports coordinates. While it uses "proprietary algorithms," it is not described as a machine learning or AI system that requires a distinct "training set" to develop its core functionality in the sense that a diagnostic AI model would. Its software validation focuses on compliance with standards rather than a machine learning training paradigm.

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

• This information is not applicable and not provided for the reasons stated in point 8.

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The SpineAssist™ System is indicated for precise positioning of surgical instruments or implants during thoracic and lumbar spinal surgery. The SpineAssist™ system may be used in either open or percutaneous procedures.

The SpineAssist™ system is a computer controlled miniature medical image-guided surgery (IGS) system which serves as a technological platform for solutions that provide unprecedented levels of accuracy, precision and accessibility in performing orthopedic procedures. The SpineAssist™ is designed to assist surgeons in precisely guiding handheld surgical tools or implants in line with a computerized, image-based pre-operative plan along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the SpineAssist device, which positions its articulating arm and tool guide. Using a special bone attachment component (i.e., a clamp and bridge or the Hover-T bridge) the SpineAssist device attaches to the bone in the area where the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools or implants according to the computerized, image-based, preoperative plan.

The main components of the SpineAssist™ system include:

• A. SpineAssist™ device
• B. Workstation
• A. Accessories including clamp, bridge, Hover-T bridge, targets, prism, wedge, etc.

The provided text does not contain detailed acceptance criteria or a comprehensive study report with the specific information requested in the prompt (e.g., specific quantitative benchmarks for acceptance, detailed performance metrics with numerical results, sample sizes for test and training sets, expert qualifications, or adjudication methods).

However, based on the summary of non-clinical performance data and conclusions, I can infer the general acceptance criteria and report the mentioned performance.

Here's an analysis of what can be extracted from the document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in a table format. However, it implicitly suggests that the system's performance for "accuracy" and "safety and effectiveness" during "general spinal surgical procedures" were the key criteria.

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

The document mentions "non-clinical performance data" and lists several "case studies" and "accuracy tests." It does not specify the sample size (e.g., number of cases, number of measurements) for any of these tests.

The data provenance is not explicitly stated. However, given the nature of "non-clinical performance data" for a surgical device involving "accuracy tests" and "case studies," it is highly likely that these were conducted in a controlled laboratory or cadaveric setting, rather than on human patients (since "Clinical Performance Data" is marked as "Not Applicable"). It is likely prospective for the specific tests conducted for this submission. The company is based in Israel, so the studies were likely conducted there or in a partnered facility.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

The document does not provide any information regarding the number of experts, their qualifications, or how ground truth was established for the "accuracy tests" or "case studies."

4. Adjudication Method for the Test Set

The document does not provide any information regarding adjudication methods.

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

No, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not done or reported in this summary. The device is a surgical navigation system, not an AI diagnostic tool that assists human readers in interpreting medical images. "Clinical Performance Data" is explicitly stated as "Not Applicable," further reinforcing that human reader studies are outside the scope of this submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the "Non-Clinical Performance Data" listed are all standalone algorithm/system performance tests. The device itself is designed to guide surgical tools based on algorithmic processing of imaging data, and the tests like "General Spinal Accuracy Test," "Hover-T Accuracy Test," and "New Imaging and Lateral to 30 degree Accuracy Test" directly assess the system's performance in this standalone capacity. The lack of "Clinical Performance Data" and MRMC studies further supports that the reported performance reflects the algorithm/system without human-in-the-loop performance for this specific submission.

7. The Type of Ground Truth Used

While not explicitly stated, for "accuracy tests" in a surgical navigation system, the ground truth would typically be established by:

• Precise measurements using highly accurate calibration tools or coordinate measuring machines in a controlled environment (e.g., phantom, cadaveric models).
• Known physical dimensions or fiducial markers on phantoms or cadavers which the system is attempting to target or guide to.
• For "case studies" (e.g., Osteoid Osteoma, Thoracic Hover-T), the "ground truth" might refer to the actual anatomical position or intended trajectory as confirmed by intra-operative imaging or post-operative assessment against the surgical plan.

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size for the training set.

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

The document does not provide any information regarding how the ground truth for the training set was established.

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The SpineAssist System is indicated for precise positioning of surgical instruments during spinal stabilization surgery. The device enables pre-operative planning of the surgical procedure and subsequent spatial positioning and orientation of the surgical tool during intra-operative procedures.

The Hover-T Bridge accessory used in conjunction with the SpineAssist device for minimally invasive surgical procedures, is intended for use for lumbar spinal fusion stabilization surgery.

The SpineAssist device developed by Mazor Surgical Technologies is an accurate imageguided positioning system that extends surgical capability in terms of precision, miniaturization and accessibility. The SpineAssist surgical positioning system assists the surgeon in the operating room to accurately position hand held surgical tools according to a computerized image-based pre-operative plan and to accurately guide surgical tools along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the SpineAssist Device, which positions its articulating arm and tool guide. Using the Hover-T kit, a special bone attachment component, the SpineAssist device attaches to the bone on which the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools in line with the computerized, image-based, pre-operative plan.

The provided text describes the SpineAssist System and its clearance as a medical device, but it does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study proving device performance.

Specifically, the document is a 510(k) premarket notification approval. While it confirms the device's intended use and substantial equivalence to a predicate device, it does not include a dedicated section detailing specific acceptance criteria for performance, nor does it outline the methodology, results, and detailed characteristics of a study designed to prove the device meets such criteria.

Therefore, I can only provide information based on what is available in the document.

Here's an attempt to answer your questions to the best of my ability with the provided text, while also explicitly stating what information is not available:

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

This information is not provided in the given document. The 510(k) summary focuses on substantial equivalence to a predicate device rather than presenting a performance study against specific acceptance criteria.

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

This information is not provided in the given document. The document refers to the device's "precision" and "accuracy" as part of its technological characteristics, but it does not detail any specific test set, its sample size, or its provenance.

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 in the given document. As no specific performance study with a test set is detailed, information about ground truth establishment or experts is absent.

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

This information is not provided in the given document.

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

This information is not provided in the given document. The device assists surgeons in positioning tools; it's not described as an AI diagnostic or interpretive tool where "human readers" would be a relevant metric for improvement with AI assistance.

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

This information is not explicitly detailed in the given document. The description states the device "assists the surgeon" and "guides surgical tools," implying a human-in-the-loop system. While it has proprietary algorithms for image processing and coordinate export, a standalone performance evaluation of the algorithms completely independent of human interaction is not described.

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

This information is not provided in the given document.

8. The sample size for the training set

This information is not provided in the given document. The document mentions "proprietary algorithms" and processing of images but does not delve into the development or training of these algorithms.

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

This information is not provided in the given document.

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The SpineAssist is indicated for precise positioning of surgical instruments during spinal fusion stabilization surgery. The device enables pre-operative planning of the surgical procedure and subsequent spatial positioning and orientation of the surgical tool during intra-operative procedures.

The SpineAssist device is a computer controlled miniature medical image-guided surgery (IGS) system which serves as a technological platform for solutions that provide unprecedented levels of accuracy, precision and accessibility in performing orthopedic procedures. The SpineAssist is designed to assist surgeons in precisely guiding handheld surgical tools in line with a computerized, image-based preoperative plan along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the MSG, which positions its articulating arm and tool guide. Through the bone-attaching procedure, the SpineAssist device attaches to the bone on which the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools in line with the computerized, image-based, pre-operative plan.

The main components of the SpineAssist device include:

• A. Planning System;
• B. Workstation; and
• C. Miniature Surgical Guidance System MSG

The provided text describes the SpineAssist Device, a surgical navigation system, and its 510(k) clearance. However, it does not contain specific acceptance criteria, detailed study designs with sample sizes for test sets, expert qualifications, adjudication methods, or quantitative performance metrics regarding accuracy or clinical outcomes directly. The content focuses on regulatory compliance, intended use, and comparison to predicate devices, rather than a detailed performance study report.

Therefore, many of the requested details cannot be extracted directly from the provided text. I will provide what can be inferred or explicitly stated.

Description of the Acceptance Criteria and Device Performance

The document indicates that testing was performed to assure compliance with various standards and to validate the accuracy and repeatability of the device. However, specific numerical acceptance criteria for accuracy and repeatability are not provided in the text, nor are the detailed reported device performance values against such criteria.

The acceptance criteria implied are primarily related to:

• Electrical Safety: Compliance with EN 60601-1.
• Electromagnetic Compatibility: Compliance with EN 60601-1-2.
• Software Validation: Compliance with IEC 60601-1-4 and FDA Guidance for Software in Medical Devices.
• Accuracy and Repeatability: These were "performed to validate," but no specific quantitative thresholds or results are given.

Since no specific performance data or acceptance criteria are listed, the table below will reflect the general statements made in the document.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states that "Additional device performance tests were performed to validate the accuracy and repeatability of the device." However, the sample size used for these tests (e.g., number of procedures, patients, or data points) and the data provenance (e.g., country of origin, retrospective/prospective) are not mentioned in the provided text.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

This information is not provided in the text. The document describes a technical device for surgical guidance but does not detail studies involving human-expert-established ground truth for a test set.

4. Adjudication Method for the Test Set

This information is not provided in the text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study is mentioned in the provided text. The document does not describe human readers using or not using the AI to assess an outcome, nor does it discuss an effect size for human improvement. The device is purely a surgical guidance system, not an AI for image interpretation that would typically require MRMC studies.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop Performance)

The document mentions that "Tests were also carried out to satisfy the requirements... Additional device performance tests were performed to validate the accuracy and repeatability of the device." This implies standalone technical performance testing of the device's accuracy and repeatability, separate from human performance. However, specific metrics and results of this standalone performance are not quantitatively detailed.

7. Type of Ground Truth Used

Given that the performance tests mentioned are for "accuracy and repeatability," the ground truth for these tests would likely involve physical measurements and engineering tolerances rather than expert consensus, pathology, or outcomes data in a clinical sense. For example, accuracy could be measured against a known physical target, and repeatability by measuring multiple attempts to reach the same target. However, the exact nature of the ground truth is not explicitly stated.

8. Sample Size for the Training Set

This information is not provided in the text. The document does not describe a machine learning model requiring a training set in the conventional sense. The "proprietary algorithms" process fluoroscopic and CT images, but the specifics of their development and training data are not disclosed.

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

Since there is no information on a specific training set or a machine learning model detailed for, this information is not provided in the text.

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