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The Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II are indicated for precise positioning of surgical instruments or spinal implants during general spine surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative guidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagery. Example procedures include: Posterior-approach spinal implant procedures, such as pedicle screw placement, with the lumbar region.

The subject devices, Image calibrator-21F and Image calibrator-31F are designed for use with Anatase Spine Surgery Navigation System (K230783) and Remex Spine Surgery Navigation System II (K233513). The subject devices are modified from previously cleared devices to be compatible with the 21 cm/ 31 cm flat panel C-arm for CT image position and calibration.

The software upgrade is due to these newly added Image calibrators and one added function of auto-labeling for CT/C-arm image registration.

This 510(k) clearance letter and summary discuss the Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II. However, the provided document does not contain the detailed acceptance criteria and the specific study data proving the device meets these criteria in the format requested.

The document states:

• "Verification and validation activities have been completed to provide sufficient assurance that the subject device meets the performance requirements under its indications for use conditions."
• "The test methods are the same as the previously cleared 510(k), K233513."
• "All the results are passed."

This indicates that performance testing was conducted and passed, but the specific metrics, criteria, and the results themselves are not enumerated in this public summary. This level of detail is typically found in the full 510(k) submission, which is not publicly released in its entirety.

Therefore, I cannot extract the information needed to fill out the requested table and answer the specific questions about the study design, sample sizes, expert qualifications, and ground truth establishment from the provided text.

Based on the provided text, here's what can be inferred or explicitly stated regarding performance testing, but not the detailed acceptance criteria or results:

• Type of device: Spine Surgery Navigation System. These systems are typically evaluated based on their accuracy in guiding surgical instruments or implants relative to anatomical structures.
• Performance Data Section: The document mentions "Verification and validation activities have been completed" for the subject device.
• Test Descriptions mentioned:
  • Software: Verified and validated in accordance with FDA guidance for software in medical devices and IEC 62304.
  • Risk Assessment: Effectiveness of risk control measures verified in accordance with ISO 14971.
  • Design Verification: Design output fulfills design input requirements.
• Comparison to Predicate: "The intended use and fundamental technology of the subject device are identical to the predicate devices and could share the same testing methods as the predicate devices. All the results are passed." This implies that the performance was at least as good as the predicate device (K233513).
• Nature of changes: The current 510(k) is for a modification to the device, including compatibility with new Image Calibrators (21F and 31F for flat panel C-arm CT imaging) and an auto-labeling function for CT/C-arm image registration. Performance testing would have focused on verifying these changes do not adversely affect safety and effectiveness, and that the existing fundamental performance (e.g., accuracy of navigation) is maintained.

Conclusion: The provided text confirms that performance testing was conducted and passed, but does not provide the specific acceptance criteria or the reported performance data in a quantifiable manner. The document acts as a summary and approval letter, not a detailed study report.

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The Remex Spine Surgery Navigation instrument is designed for use with Anatase Spine Surgery Navigation System(K230783) and Remex Spine Surgery Navigation System II(K233513). The Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II are indicated for precise positioning of surgical instruments or spinal implants during general spine surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative guidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagery. Example procedures include: Posterior-approach spinal implant procedures, such as pedicle screw placement, with the lumbar region.

The Remex Spine Surgery Navigation Instrument is designed for use with Anatase Spine Surgery Navigation System (K230783) and Remex Spine Surgery Navigation System II (K233513).
The Remex Spine Surgery Navigation Instrument consists of the Nav Awl, Nav Drill Guide, Nav Tap, Nav Screwdriver and Nav Handle.

1. Nav Awl: The subject device is intended to support the surgeon to create an entry point before implanting the screw.
2. Nav Drill Guide: The subject device is intended to assist in drilling holes to a desired depth and ensuring proper orientation.
3. Nav Tap: The subject device is intended to create screw threads.
4. Nav Screwdriver: The subject device is intended to driver the screw into the vertebra.
   Nav Handle: The subject device is intended to connected with Nav Awl, Nav Tap or Nav Screwdriver for navigation tracking purpose.

This document is focused on the Remex Spine Surgery Navigation Instrument and its substantial equivalence to predicate devices (K233513, K230783). It primarily addresses the design and functional aspects of the instrument itself, rather than presenting a performance study of an AI-powered diagnostic device or a navigation system that relies on sophisticated algorithms validated with clinical outcomes.

Therefore, the provided text does not contain the detailed information required to answer many of the specific questions regarding acceptance criteria and a study proving device performance as typically understood for an AI/ML-driven diagnostic or image analysis device. The "Performance Data" section discusses general design verification, software verification (in accordance with general FDA guidance and IEC 62304), risk assessment (ISO 14971), and biocompatibility (ISO 10993). It states that "[a]ll the results are passed" but doesn't provide specific numerical acceptance criteria or performance metrics related to diagnostic accuracy, sensitivity, specificity, or reader improvement.

Based on the provided text, I can extract the following limited information:

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

The document doesn't provide specific numerical acceptance criteria in the format of a table with quantitative performance metrics for a diagnostic device (e.g., accuracy, sensitivity, specificity). Instead, it lists general verification and validation activities designed to demonstrate that the instrument performs safely and effectively.

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

• Sample Size: Not specified. The document refers to "verification and validation activities" and "performance tests" but does not detail the sample size (e.g., number of instruments tested, number of patients/cases used for a clinical performance study if one were relevant to this specific instrument).
• Data Provenance: Not specified. (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: Not applicable/not specified. The testing described is primarily engineering and materials verification for a physical medical instrument, not a study requiring expert readers to establish ground truth for image interpretation or diagnosis.
• Qualifications of Experts: Not applicable/not specified.

4. Adjudication method for the test set:

• Adjudication Method: Not applicable/not specified. This type of detailed adjudication process (e.g., 2+1, 3+1) is typically relevant to studies involving human reading of medical images where ground truth is established by consensus, which is not the subject of this 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:

• MRMC Study: No, an MRMC comparative effectiveness study was not done, or at least not described in this document. This document pertains to a physical surgical instrument, not an AI-assisted diagnostic or image analysis system that would typically undergo such a study.

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

• Standalone Performance: Not applicable. This document describes a surgical instrument. While it works with navigation systems (K230783, K233513) that likely have software components, the focus here is the physical instrument itself, not an AI algorithm whose standalone performance needs to be measured.

7. The type of ground truth used:

• Type of Ground Truth: Not applicable in the conventional sense of clinical ground truth (pathology, outcomes data, expert consensus). For a surgical instrument, "ground truth" would relate to engineering specifications, material properties, and functional performance (e.g., precision of fit, sterility, tracking accuracy within the navigation system). Measurements and observations against these pre-defined specifications serve as the "ground truth" for verification.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. This document describes a physical medical device (surgical instrument), not an AI/ML algorithm that would undergo training on a data set.

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

• Ground Truth Establishment for Training Set: Not applicable. There is no mention of an AI/ML training set in this document.

In summary: The provided document is an FDA 510(k) clearance letter and synopsis for a medical instrument (Remex Spine Surgery Navigation Instrument), which is a physical device used with existing navigation systems. It is not a submission for an AI/ML-driven diagnostic or image analysis device. Therefore, the detailed performance study and acceptance criteria questions related to artificial intelligence and clinical diagnostic performance are largely not applicable to the content provided. The "performance data" section focuses on standard engineering and biocompatibility testing to ensure the instrument's safety and effectiveness.

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The Anatase Navi Disposable Instrument is designed for use with Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II. The Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II. are indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative quidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagerv. Example procedures include : Posterior-approach spinal implant procedures, such as pedicle screw placement, within the lumbar region.

The Anatase Navi Disposable Instrument is designed for use with Anatase Spine Surgery Navigation System and Remex Spine Surgery Navigation System II. The Guiding awl is intended to support the surgeon to create an entry point before implanting the screw. The Spine pin with DRF-D and MIS LOC with DRF are both intended to fix the DRF on the vertebra by boned pins or the clamp. Once the DRF is fixed on the vertebra, the system can track the position of the patient's vertebra and instruments.

This document is a 510(k) summary for the Anatase Navi Disposable Instrument. It primarily focuses on demonstrating substantial equivalence to a predicate device by addressing changes in material, packaging, and sterilization due to a change from repeat-use to single-use. The acceptance criteria and performance data provided are related to these specific changes, rather than clinical performance metrics of an AI/algorithm-based device.

Therefore, many of the requested details regarding AI/algorithm performance (e.g., sample size for the test set, data provenance, number of experts for ground truth, MRMC studies, standalone performance, training set details) are not applicable to this submission as it describes a physical medical instrument, not a software or AI device.

Here's a breakdown of the available information based on your request, highlighting where information is not present in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria listed here are primarily for the changes related to the device being single-use and sterilized, rather than clinical performance of an AI/algorithm.

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

This document describes a physical instrument and its manufacturing/sterilization validation. It does not involve a clinical "test set" in the context of an AI/algorithm performance study. Therefore, this information is not applicable.

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 is not applicable as the submission is for a physical medical instrument, not an AI/algorithm requiring expert ground truth in a clinical context.

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

This is not applicable as there is no clinical "test set" and no need for expert adjudication.

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 is not applicable as the device is a physical instrument, not an AI or software device.

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

This is not applicable as the device is a physical instrument, not an AI or software device.

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

For the physical and process validation tests (package, sterilization, biocompatibility, risk assessment, design verification), the "ground truth" would be established by relevant scientific and engineering standards and validated laboratory test results, rather than clinical outcomes or expert consensus on medical images.

8. The sample size for the training set

This is not applicable as the device is a physical instrument and does not involve AI model training.

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

This is not applicable as the device is a physical instrument and does not involve AI model training or a "training set" in that context.

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The Remex Spine Surgery Navigation System II, is indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative quidance system to enable open or percutaneous image quided surgery by means of registering intraoperative 2D fluoroscopic projections to preoperative 3D CT imagery.

Example procedures include:

Posterior-approach spinal implant procedures, such as pedicle screw placement, within the lumbar region.

The Remex Spine Surgery Navigation System II, also known as an Image Guided System, is comprised of a platform, clinical software, surgical instruments, and a referencing system. The system uses wireless optical tracking technology to track the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of a patient. The system helps guide surgeons during spine procedures such as spinal fusion. The software functionality in terms of its feature sets are categorized as imaging modalities, registration, planning, interfaces with medical devices, and views.

Apologies, but the provided text from the FDA 510(k) clearance letter and the associated 510(k) summary for the "Remex Spine Surgery Navigation System II" does not contain the detailed information required to fulfill the request regarding acceptance criteria and the study that proves the device meets the acceptance criteria.

Specifically, the document states that "Performance Data Verification and validation activities have been completed to provide sufficient assurance that the subject device meets the performance requirements under its indications for use conditions. Below is a summary of all performance tests which should carried out on the subject device to demonstrated that the subject device performs as safely and effectively as the predicate device."

It then lists several tests:

• Software
• Electrical Safety
• Electromagnetic Compatibility
• Accuracy
• Risk Assessment
• Design Verification

While "Accuracy" is listed, the document does not provide the acceptance criteria for this accuracy test (e.g., "positional accuracy must be within X mm") nor does it report the actual device performance results against these criteria. It simply states that accuracy was "evaluated in accordance with ASTM F2554-18."

Therefore, I cannot generate the requested information based solely on the text provided. The document outlines what types of tests were performed to demonstrate substantial equivalence, but not the specific quantitative acceptance criteria or the measured performance of the device against those criteria.

To answer your prompt, I would need a document that includes sections detailing:

1. Specific, quantitative acceptance criteria for performance metrics (e.g., accuracy, precision).
2. Reported performance results of the device against those criteria.
3. Details about the study design for accuracy (e.g., sample size, data provenance, ground truth establishment, expert qualifications, etc.).

Without that missing information, I cannot complete the table or provide the requested details about the study.

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The Anatase Spine Surgery Navigation System is indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative guidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagery.

Example procedures include but are not limited to:

Posterior-approach spinal implant procedures, such as pedicle screw placement, within the lumbar region.

The Anatase Spine Surgery Navigation System, also known as an Image Guided System, is comprised of a platform, clinical software, surgical instruments, and a referencing system. The system uses wireless optical tracking technology to track the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of a patient. The system helps guide surgeons during spine procedures such as spinal fusion. The software functionality in terms of its feature sets are categorized as imaging modalities, registration, planning, interfaces with medical devices, and views.

The provided text describes the Anatase Spine Surgery Navigation System and its 510(k) submission to the FDA. The document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone study with detailed clinical performance data, acceptance criteria, and ground truth establishment for a specific AI-driven diagnostic or prognostic task.

However, based on the Accuracy section under "Performance Data Verification and validation activities," we can infer the acceptance criteria and the nature of the study for positional accuracy.

Here's an analysis based on the provided text, while acknowledging limitations due to the nature of the document (a 510(k) summary for device clearance):

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that the positional accuracy of the system is evaluated in accordance with ASTM F2554-18. While the specific numerical acceptance criteria and the reported performance values are not provided in this summary document, the fact that it passed verification and validation implies that it met predefined criteria based on this standard.

To get the specific values, one would need to consult a more detailed technical report or the full 510(k) submission, which is not fully available here.

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

The document does not specify the sample size used for the positional accuracy test set nor the data provenance (e.g., country of origin, retrospective/prospective). This information is typically found in detailed test reports, not a 510(k) summary.

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

The document does not mention the use of experts to establish ground truth for the positional accuracy testing. Positional accuracy testing typically relies on metrology equipment and precise physical measurements, not expert human evaluation.

4. Adjudication Method for the Test Set:

Not applicable, as ground truth for positional accuracy is established by metrological methods, not human adjudication.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or described. The document states "The Anatase Spine Surgery Navigation System is indicated for precise positioning of surgical instruments or spinal implants..." suggesting it is a tool for surgeons rather than an AI diagnostic device that assists human readers in interpreting images.

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

Yes, a standalone performance evaluation regarding positional accuracy was conducted for the device. The text states, "Accuracy: Positional accuracy of the system is evaluated in accordance with ASTM F2554-18." This refers to the objective measurement of the system's tracking and navigation capabilities.

7. Type of Ground Truth Used:

For positional accuracy, the ground truth would be established through metrological measurements using calibrated instruments and reference standards, as dictated by ASTM F2554-18. It is not expert consensus, pathology, or outcomes data in this context.

8. Sample Size for the Training Set:

The document does not mention a "training set" in the context of machine learning or AI. This device is a navigation system that uses optical tracking and image registration, implying a more traditional engineering validation process rather than a deep learning model requiring a large training dataset for a diagnostic task.

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

Not applicable, as there is no mention of a training set for an AI/machine learning model to establish ground truth.

Summary of Device Performance Study Information based on the provided text:

The information primarily focuses on regulatory conformity and substantial equivalence. For specific performance studies, the key takeaway is:

• Study Type for Accuracy: Evaluation of positional accuracy.
• Standard Used: ASTM F2554-18.
• Ground Truth for Accuracy: Metrological measurements (implied by the standard).
• Result: The device met performance requirements, indicating it passed the accuracy criteria.

The document does not provide the detailed numerical results, sample sizes, or specifics of the test setup beyond referencing the standard.

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The Anatase Spine Surgery Navigation System is indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative guidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagery.

Example procedures include but are not limited to:

Posterior-approach spinal implant procedures, such as pedicle screw placement, within the lumbar region.

The Anatase Spine Surgery Navigation System, also known as an Image Guided System, is comprised of a platform, clinical software, surgical instruments, and a referencing system. The system uses optical tracking technology to track the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of a patient. The system helps guide surgeons during spine procedures such as spinal fusion. The software functionality in terms of its feature sets is categorized as imaging modalities, registration, planning, interfaces with medical devices, and views.

The modified Anatase Spine Surgery Navigation System, the subject of these 510(k) applications, introduces software, hardware and instruments modifications to the original Surgery Navigation System cleared in 510(k) K180523.

The Anatase Spine Surgery Navigation System, Model number: SNS-Spine2-S and SNS-Spine2-V, is indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery.

Here's a breakdown of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The provided document does not specify sample sizes for any test sets nor the data provenance (e.g., country of origin, retrospective/prospective). The studies are non-clinical, meaning they did not involve patient data.

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

This information is not provided in the document as these were non-clinical tests.

4. Adjudication method for the test set:

This information is not provided in the document as these were non-clinical tests.

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 clinical testing, including MRMC studies, was conducted. The document explicitly states: "No clinical testing has been conducted."

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

The provided information focuses on the entire system's performance, which is an image-guided navigation system that would inherently involve human interaction (a surgeon). While software verification and validation were performed, the document does not distinguish between human-in-the-loop and algorithm-only performance for a standalone assessment in a manner that would typically be seen for an AI diagnostic device. The "Accuracy" test implies an assessment of the system's ability to track and display positions, which is a standalone performance metric for the navigation component, but it's not described as an AI-specific algorithm performance.

7. The type of ground truth used:

For the accuracy testing, the ground truth would likely be established through precise physical measurements to determine the true positional accuracy of the system against a known standard. However, the document does not specify the exact methodology for establishing the ground truth beyond referencing ASTM F2554-18. For other tests like electrical safety, EMC, and sterilization, the "ground truth" is defined by compliance with the referenced standards.

8. The sample size for the training set:

As this is a navigation system and not explicitly an AI diagnostic device in the context of machine learning model training, the concept of a "training set" in that sense is not directly applicable or discussed in the document. Software verification and validation were performed, but details on data used for these processes are not provided.

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

Same as above, the concept of a "training set" with established ground truth as typically understood in AI/machine learning is not applicable here. Software verification and validation would use various testing methods to ensure the software performs as designed and meets requirements.

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