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Synergy Cranial v2.2.9:
The StealthStation System, with Synergy Cranial software, is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The system is indicated for any medical condition in which reference to a rigid anatomical structure can be identified relative to images of the anatomy. This can include, but is not limited to, the following cranial procedures:

• Cranial Biopsies
• Tumor Resections
• Craniotomies/Craniectomies
• Skull Base Procedures
• Transsphenoidal Procedures
• Thalamotomies/Pallidotomies
• Pituitary Tumor Removal
• CSF Leak Repair
• Pediatric Catheter Shunt Placement
• General Catheter Shunt Placement

StealthStation Cranial Software v3.1.4:
The StealthStation System, with StealthStation Cranial software, is intended to aid in precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The system is indicated for any medical condition in which reference to a rigid anatomical structure can be identified relative to images of the anatomy. This can include, but is not limited to, the following cranial procedures (including stereotactic frame-based and stereotactic frame alternatives-based procedures):

• Cranial biopsies (including stereotactic)
• Deep brain stimulation (DBS) lead placement
• Depth electrode placement
• Tumor resections
• Craniotomies/Craniectomies
• Skull Base Procedures
• Transsphenoidal Procedures
• Thalamotomies/Pallidotomies
• Pituitary Tumor Removal
• CSF leak repair
• Pediatric Ventricular Catheter Placement
• General Ventricular Catheter Placement

The StealthStation System, with StealthStation Cranial software helps guide surgeons during cranial surgical procedures such as biopsies, tumor resections, and shunt and lead placements. The StealthStation Cranial software works in conjunction with an Image Guided System (IGS) which consists of clinical software, surgical instruments, a referencing system and platform/computer hardware. Image guidance, also called navigation, tracks the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of the patient. StealthStation Cranial software functionality is described in terms of its feature sets which are categorized as imaging modalities, registration, planning, interfaces with medical devices, and views. Feature sets include functionality that contributes to clinical decision making and are necessary to achieve system performance.

The Medtronic Navigation, Inc. StealthStation Cranial Software (v3.1.4) and Synergy Cranial Software (v2.2.9) are image-guided surgery (IGS) systems intended to aid in precisely locating anatomical structures during neurosurgical procedures.

Here's an analysis of the acceptance criteria and study that proves the device meets them, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The primary acceptance criteria for both software versions are related to system accuracy in 3D positional and trajectory angle measurements.

Note: The document refers to "StealthStation Cranial v3.1.3" and also "StealthStation Cranial v3.0 Software" in the testing section for the newer version's accuracy. Assuming v3.1.3 is the subject device and v3.0 is a close predecessor or the system version used for the test. The "v3.1.4" in the 510(k) letter is likely a minor update from v3.1.3, and the reported performance for v3.1.3 is considered representative.

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

The document does not explicitly state the sample size (number of patients or phantom configurations) used for the quantitative accuracy testing (test set). It mentions:

• "Under representative worst-case configuration"
• "utilizing a subset of system components and features that represent the worst-case combinations of all potential system components."
• "Test configurations included CT images with slice spacing and thickness ranging between 0.6 mm to 1.25 mm and T1-weighted MR images with slice spacing and thickness ranging between 1.0 mm to 3.0 mm."

Data Provenance: The data appears to be prospective as it was generated through laboratory and simulated use settings with "anatomically representative phantoms." The country of origin is not explicitly stated, but given Medtronic Navigation, Inc. is located in Louisville, Colorado, USA, it's highly probable the testing was conducted in the USA.

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

The document indicates that the accuracy was determined using "anatomically representative phantoms." This implies that the ground truth for positional and angular accuracy was engineered and precisely measured within a controlled phantom environment, rather than established by human experts interpreting clinical data. Therefore, human experts were likely involved in designing and validating the phantom setup and measurement methodologies, but not in directly establishing ground truth from patient data. The qualifications of these individuals are not specified but would typically be engineers, physicists, or metrology specialists.

4. Adjudication Method for the Test Set

Given that the ground truth was established through a designed phantom and precise measurements, an adjudication method for human interpretation is not applicable here. The measurements are objective and quantitative.

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

No MRMC comparative effectiveness study was mentioned for human readers improving with AI vs. without AI assistance. The device is a surgical navigation system, aiding in real-time guidance, not an AI-assisted diagnostic tool that would typically undergo MRMC studies.

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

Yes, a standalone performance was done for the system's accuracy. The reported positional and trajectory angle errors are measures of the system's inherent accuracy, independent of a specific human-in-the-loop scenario. The study describes "Design verification and validation was performed using the StealthStation Cranial software in laboratory and simulated use settings."

7. The Type of Ground Truth Used

The ground truth used was engineered truth derived from precisely measured anatomical phantoms. This is a highly controlled and quantitative method, suitable for measuring the accuracy of a navigation system.

8. The Sample Size for the Training Set

The document does not describe a "training set" in the context of an AI/machine learning model. The device is referred to as "software" for an Image Guided System (IGS), which typically relies on established algorithms for image processing, registration, and tracking, rather than deep learning models that require large training datasets with ground truth labels in the conventional sense. The "training" for such a system would involve rigorous formal verification and validation of these algorithms.

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

As noted above, the concept of a "training set" and its associated ground truth, as typically applied to AI/machine learning, does not appear to be directly applicable to the description of this device's development as presented in the 510(k) summary. The development involved "Software verification and validation testing for each requirement specification" and "System integration performance testing for cranial surgical procedures using anatomical phantoms," suggesting traditional software engineering and testing methodologies rather than machine learning training.

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The Synergy® Cranial software is surgical navigation software that, when used with the StealthStation® System as a planning and intraoperative guidance system, is intended to aid in precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The system is indicated for any medical condition in which reference to a rigid anatomical structure can be identified relative to images of the anatomy.

This can include, but is not limited to, the following cranial procedures:

• Cranial Biopsies
• Tumor Resections
• Craniotomies/Craniectomies
• Skull Base Procedures
• Transsphenoidal Procedures
• Thalamotomies/Pallidotomies
• Pituitary Tumor Removal
• CSF Leak Repair
• Pediatric Catheter Shunt Placement
• General Catheter Shunt Placement

The StealthStation® System, with StealthStation® Cranial software, is intended to aid in precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The system is indicated for any medical condition in which reference to a rigid anatomical structure can be identified relative to images of the anatomy.

This can include, but is not limited to, the following cranial procedures (including stereotactic frame-based and stereotactic frame alternatives-based procedures):

• Cranial biopsies (including stereotactic)
• Deep brain stimulation (DBS) lead placement
• Depth electrode placement
• Tumor resections
• Craniotomies/Craniectomies
• Skull Base Procedures
• Transsphenoidal Procedures
• Thalamotomies/Pallidotomies
• Pituitary Tumor Removal
• CSF leak repair
• Pediatric Ventricular Catheter Placement
• General Ventricular Catheter Placement

The StealthStation® System, with StealthStation Cranial software helps guide surgeons during cranial surgical procedures such as biopsies, tumor resections, and shunt and lead placements. The StealthStation® Cranial software works in conjunction with an Image Guided System (IGS) which consists of clinical software, surgical instruments, a referencing system and platform/computer hardware. Image guidance, also called navigation, tracks the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of the patient. StealthStation® Cranial software functionality is described in terms of its feature sets which are categorized as imaging modalities, registration, planning, interfaces with medical devices, and views. Feature sets include functionality that contributes to clinical decision making and are necessary to achieve system performance.

The provided document is a 510(k) Premarket Notification from Medtronic Navigation Inc. to the FDA for their StealthStation Synergy Cranial S7 Software v.2.2.8 and StealthStation Cranial Software v3.1.1. The document primarily discusses the substantial equivalence of these devices to previously cleared predicate devices.

While it mentions system accuracy requirements and some aspects of testing, it does NOT contain the detailed information typically found in a study proving a device meets acceptance criteria for an AI/ML medical device, especially regarding clinical performance, expert ground truth, multi-reader studies, or large-scale data sets.

The document describes a surgical navigation software, which is a different category from an AI/ML diagnostic or predictive device. The "performance testing" described focuses on 3D positional and trajectory accuracy of the surgical navigation system itself, not on the performance of an AI algorithm in interpreting medical images or making clinical assessments.

Therefore, many of the requested sections about AI/ML device performance (e.g., ground truth methods, sample sizes for training/test sets in the context of AI, expert adjudication, MRMC studies) are not applicable or not provided in this document.

Here's what can be extracted and inferred from the text regarding the device's acceptance criteria and the study that "proves" it meets them, framed within the context of a surgical navigation system:

Device: StealthStation® Synergy Cranial S7 Software v2.2.8 and StealthStation® Cranial Software v3.1.1 (used with the StealthStation® System)

Function: Surgical navigation software intended to aid in precisely locating anatomical structures in neurosurgical procedures.

Nature of Device's "Performance": The performance here refers to the accuracy of the navigation system in guiding surgical instruments, not an AI's ability to interpret images or predict outcomes.

1. Table of Acceptance Criteria and Reported Device Performance

This information is presented within the "Summary of the Technological Characteristics" section, specifically under the "System Accuracy Requirement" for both software versions.

Conclusion: Both subject devices (v2.2.8 and v3.1.1) demonstrate positional and trajectory accuracy values better than or equal to the specified acceptance criteria (which are based on the predicate devices' performance).

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

• Sample Size for Test Set: Not explicitly stated as a numerical 'sample size' of cases or images in the typical AI/ML sense. The document states: "This performance was determined using anatomically representative phantoms and utilizing a subset of system components and features that represent the worst-case combinations of all potential system components." This implies testing was done on physical phantoms rather than patient data.
• Data Provenance: Not applicable in the sense of patient data origin (e.g., country of origin, retrospective/prospective). The testing used "anatomically representative phantoms."

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

• Number of Experts/Qualifications: Not applicable. The "ground truth" for a surgical navigation system's accuracy is typically established by direct physical measurements against known values on precise phantoms, not by expert human interpretation of images for diagnosis or outcomes.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. As the "ground truth" is established by physical measurement on phantoms, or engineering validation, there is no need for expert adjudication.

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

• MRMC Study Done?: No. This type of study is relevant for AI systems that assist human readers in tasks like image interpretation or diagnosis. This document pertains to a surgical navigation system, where the 'device performance' is its physical accuracy, not its interpretative assistance to a human reader.

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

• Standalone Performance: Yes, implicitly. The "System Accuracy" testing is a standalone test of the device's accuracy in a controlled, "worst-case configuration" using phantoms. This measures the device's inherent precision and accuracy independent of direct human-in-the-loop performance during an actual surgery. However, this is not an AI algorithm's standalone performance in a diagnostic sense, but rather an engineering performance metric.

7. The Type of Ground Truth Used

• Type of Ground Truth: Engineering measurements / Physical reference standard. The document states the performance was determined using "anatomically representative phantoms." The ground truth for positional and trajectory accuracy would be the known, precisely measured positions and angles on these phantoms.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable / Not provided. This device is a software for surgical navigation, not an AI/ML model trained on a large dataset of patient images to perform diagnostic or predictive tasks. The software's functionality is based on algorithms that process imaging data (CT, MR) for registration and guidance, not on a machine learning training paradigm.

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

• How Ground Truth for Training Established: Not applicable. As there's no evident "training set" in the AI/ML sense, this question is not relevant. The software's functionality is based on established physics, geometry, and image processing algorithms.

Ask a specific question about this device

The StealthStation System, with Synergy® Cranial software, is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The system is indicated for any medical condition in which reference to a rigid anatomical structure can be identified relative to images of the anatomy.

This can include, but is not limited to, the following cranial procedures:

• Cranial Biopsies
• Tumor Resections
• Craniotomies/Craniectomies
• Skull Base Procedures
• Transsphenoidal Procedures
• Thalamotomies/Pallidotomies
• Pituitary Tumor Removal
• CSF Leak Repair
• Pediatric Catheter Shunt Placement
• General Catheter Shunt Placement

The StealthStation System, with Synergy Cranial v2.2.7 software helps guide surqeons during cranial surgical procedures such as biopsies, tumor resections, and shunt placements. The Synergy Cranial v2.2.7 software works in conjunction with an Image Guided System (IGS) which consists of clinical software, surqical instruments, a referencing system and platform/computer hardware. Image quidance, also called navigation, tracks the position of instruments in relation to the surgical anatomy and identifies this position on diagnostic or intraoperative images of the patient. Synergy Cranial v2.2.7 software functionality is described in terms of its feature sets which are categorized as imaging modalities, registration, planning, interfaces with medical devices, and views. Feature sets include functionality that contributes to clinical decision making and are necessary to achieve system performance.

Here's a breakdown of the acceptance criteria and study information for the StealthStation System with Synergy Cranial Software, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a numerical "sample size" for the test set in terms of cases or patients. Instead, it describes:

• Test Setup: "an anatomically representative phantom." This suggests a single or very limited number of phantoms were used to test accuracy.
• Data Provenance: The testing was conducted "in laboratory and simulated use settings." This indicates a retrospective and simulated provenance, not based on real patient data from a specific country.

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

The document does not mention the use of experts to establish ground truth for the test set. The ground truth for accuracy testing on a phantom would typically be established by the precise design and known dimensions of the phantom itself, and the accurate measurement tools used during the test.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method. Since the performance testing was based on an anatomically representative phantom and direct measurements of positional and angular error, adjudication by human experts (as would be typical for image interpretation tasks) was not applicable or performed.

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

No, an MRMC comparative effectiveness study was not done. The document does not describe any human reader studies or a comparison of human reader performance with and without AI assistance. The testing focuses solely on the device's inherent accuracy in a simulated environment.

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

Yes, a standalone performance evaluation was conducted. The document states that the testing demonstrated the system's "performance in 3D positional accuracy" and "trajectory angle accuracy." These are measurements of the algorithm/system's precision in guiding instruments, independent of a human's interpretation or decision-making. The device, an Image Guided System (IGS), inherently functions as a standalone guidance system, providing objective measurements to the surgeon.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The ground truth used for the performance testing was based on the known physical properties and precise measurements of an anatomically representative phantom. This is a form of engineered or objective ground truth, not derived from subjective expert consensus, pathology, or patient outcomes.

8. The Sample Size for the Training Set

The document does not provide any information about the sample size used for a training set. This is typical for a medical device cleared via 510(k) where the focus is on substantial equivalence to a predicate device and performance validation, rather than the development and training of a novel AI algorithm from a large dataset. The Synergy Cranial software is likely a refined version or update to existing navigation software, rather than a de-novo AI model requiring extensive training data.

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

As no training set is described, there is no information on how its ground truth would have been established.

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