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Stealth™ Spine Clamps

When used with Medtronic computer assisted surgery systems, defined as including the Stealth™ System, the following indications of use are applicable:

• The spine referencing devices are intended to provide rigid fixation between patient and patient reference frame for the duration of the surgery. The devices are intended to be reusable.
• The navigated instruments are specifically designed for use with Medtronic computer-assisted surgery systems, which are indicated for any medical condition in which the use of stereotactic surgery may be appropriate or vertebra can be identified relative to a CT or MR based model, fluoroscopy images, or digitized landmarks of the anatomy.
• The Stealth™ spine clamps are indicated for skeletally mature patients.

ModuLeX™ Shank Mounts

When used with Medtronic computer assisted surgery systems, defined as including the Stealth™ System, the following indications of use are applicable:

• The spine referencing devices are intended to provide rigid fixation between patient and patient reference frame for the duration of the surgery. The devices are intended to be reusable.
• The navigated instruments are specifically designed for use with Medtronic computer assisted surgery systems, which are indicated for any medical condition in which the use of stereotactic surgery may be appropriate or vertebra can be identified relative to a CT or MR based model, fluoroscopy images, or digitized landmarks of the anatomy.
• The ModuLeX™ shank mounts are indicated to be used with the CD Horizon™ ModuLeX™ Spinal System during surgery.
• The ModuLeX™ shank mounts are indicated for skeletally mature patients.

The Stealth™ Spine Clamps are intended to provide rigid attachment between the patient and patient reference frame for the duration of the surgery. The subject devices are designed for use with the Stealth™ System and are intended to be reusable.

The ModuLeX™ Shank Mounts are intended to provide rigid attachment between the patient and patient reference frame for the duration of the surgery. The subject devices are designed for use with the Stealth™ System and are intended to be reusable.

This document, an FDA 510(k) Clearance Letter, does not contain the specific details about acceptance criteria and study data that would be found in a full submission. 510(k) summary documents typically provide a high-level overview.

Based on the provided text, here's what can be extracted and what information is not available:

Information from the document:

• Device Type: Stealth™ Spine Clamps and ModuLeX™ Shank Mounts, which are orthopedic stereotaxic instruments used with computer-assisted surgery systems (specifically the Medtronic Stealth™ System).
• Purpose: To provide rigid fixation between the patient and a patient reference frame for the duration of spine surgery, and to serve as navigated instruments for surgical guidance.
• Predicate Devices:
  • Stealth™ Spine Clamps: StealthStation™ Spinous Process Clamps (K211442)
  • ModuLeX™ Shank Mounts: Rod Clamps (K131425)
• Testing Summary (XI. Discussion of the Performance Testing):
  • Mechanical Robustness and Navigation Accuracy
  • Functional Verification
  • Useful Life Testing
  • Packaging Verification
  • Design Validation
  • Summative Usability
  • Biocompatibility (non-cytotoxic, non-sensitizing, non-irritating, non-toxic, non-pyrogenic)

Information NOT available in the provided document (and why):

This 510(k) summary describes physical medical devices (clamps and mounts) used in conjunction with a computer-assisted surgery system, but it does not describe an AI/software device whose performance is measured in terms of accuracy, sensitivity, or specificity for diagnostic or guidance purposes. Therefore, many of the requested points related to AI performance, ground truth, and reader studies are not applicable or not detailed in this type of submission.

Specifically, the document does not contain:

1. A table of acceptance criteria and reported device performance (with specific numerical metrics for "Navigation Accuracy"): While "Navigation Accuracy" is listed as a test conducted, the actual acceptance criteria (e.g., "accuracy must be within X mm") and the quantitative results are not provided in this summary. This would typically be in a detailed test report within the full 510(k) submission.
2. Sample sizes used for the test set and data provenance: No information on the number of units tested, or if any patient data was used for "Navigation Accuracy" (it's likely bench testing).
3. Number of experts used to establish ground truth and their qualifications: Not applicable as this is a mechanical device submission, not an AI diagnostic submission. Ground truth for mechanical accuracy would be established by precise measurement tools, not human experts in this context.
4. Adjudication method for the test set: Not applicable for mechanical/functional testing.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study: Not mentioned or applicable. This type of study is for evaluating human performance (e.g., radiologists interpreting images) with and without AI assistance.
6. Stand-alone (algorithm only) performance: Not applicable; this is not an algorithm for diagnosis or image analysis.
7. Type of ground truth used (expert consensus, pathology, outcomes data, etc.): For "Navigation Accuracy," the ground truth would be based on highly precise measurement systems (e.g., optical tracking validation) in a lab setting, not clinical outcomes or expert consensus.
8. Sample size for the training set: Not applicable; there is no "training set" as this is not a machine learning model.
9. How the ground truth for the training set was established: Not applicable.

Summary of what is known concerning acceptance criteria and proof of adherence:

• Acceptance Criteria/Proof (General): The document states that "Testing conducted to demonstrate equivalency of the subject device to the predicate is summarized as follows: Mechanical Robustness and Navigation Accuracy, Functional Verification, Useful Life Testing, Packaging Verification, Design Validation, Summative Usability, Biocompatibility."
• Implied Acceptance: The FDA's clearance (K242464) indicates that Medtronic successfully demonstrated that the new devices are "substantially equivalent" to predicate devices based on the submitted testing. This means the performance met the FDA's expectations for safety and effectiveness, likely by demonstrating equivalent or better performance against the predicates in the specified tests (e.g., meeting established benchmarks for sterility, material strength, and precision when interfaced with the navigation system). However, the specific numerical criteria for "Navigation Accuracy" are not disclosed in this summary letter.

Conclusion based on the provided text:

This 510(k) summary is for a Class II mechanical stereotaxic instrument and, as such, focuses on demonstrating mechanical, functional, and biocompatibility equivalency to predicate devices. It does not contain the detailed performance metrics, ground truth establishment methods, or human reader study results that would be pertinent to an AI/software medical device submission.

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The Visualase V2 ™ MRI-Guided Laser Ablation System is a neurosurgical tool and is indicated for use to ablate, necrotize, or coagulate intracranial soft tissue including brain structures (for example, brain tumor, radiation necrosis, and epileptic foci as identified by non-invasive and invasive neurodiagnostic testing, including imaging) through interstitial irradiation or thermal therapy in pediatrics and adults with 980 nm lasers. The intended patients are adults and pediatric patients from the age of 2 years and older.

The Visualase MRI-Guided Laser Ablation System comprises hardware and software components used in combination with three MR-compatible (conditional), sterile, single-use, saline-cooled laser applicators with proprietary diffusing tips that deliver controlled energy to the tissue of interest. The system consists of:

• a diode laser (energy source)
• a coolant pump to circulate saline through the laser application
• Visualase workstation which interfaces with MRI scanner's host computer
• Visualase software which provides the system's ability to visualize and monitor relative changes in tissue temperature during ablation procedures, set temperature limits and control the laser output; one monitors to display all system imaging and laser ablation via a graphical user interface and peripherals for interconnections

The provided FDA 510(k) clearance letter for the Visualase V2 MRI-Guided Laser Ablation System does not contain the detailed information necessary to fully address all aspects of the request. Specifically, the document focuses on regulatory compliance, substantial equivalence to predicate devices, and general testing summaries (software V&V, system V&V, electrical safety). It does not include specific acceptance criteria with performance metrics, details of a clinical study (like sample sizes, ground truth establishment, expert qualifications, or MRMC studies), or direct data proving the device met specific performance criteria.

The letter explicitly states: "A clinical trial was not required to establish substantial equivalence. Clinical evidence provided in a literature summary format supports the safe use of the Visualase V2 System in the intended patient population." This indicates that a prospective clinical performance study, often associated with detailed acceptance criteria and reported performance, was not the primary method for demonstrating substantial equivalence for this particular submission.

Therefore, many sections of your request cannot be fulfilled based on the provided document. I will fill in the information that is present and explicitly state where information is not available.

Acceptance Criteria and Device Performance for Visualase V2 MRI-Guided Laser Ablation System

Based on the provided FDA 510(k) clearance letter (K250307), the device's acceptance criteria and proven performance are primarily demonstrated through verification and validation activities for its software and system, and compliance with electrical safety standards. A formal clinical trial with quantitative performance metrics against specific acceptance criteria (e.g., sensitivity, specificity, accuracy) was not required for this submission to establish substantial equivalence, but rather clinical evidence was provided via a literature summary.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of this 510(k) for the Visualase V2 System as described in the document, performance acceptance criteria are focused on safety, functionality, and equivalence to predicate devices, rather than clinical efficacy metrics typically found in AI/diagnostic device submissions.

2. Sample Size for the Test Set and Data Provenance

The document explicitly states: "A clinical trial was not required to establish substantial equivalence. Clinical evidence provided in a literature summary format supports the safe use of the Visualase V2 System in the intended patient population."

Therefore, no specific "test set" sample size for a clinical performance study is reported in this document. The "testing summary" refers to internal verification and validation against design controls and standards, not a clinical data set for performance evaluation of an AI algorithm.

Data Provenance: Not applicable for a clinical test set in this context, as a clinical performance study was not the basis for substantial equivalence for this upgrade. The clinical evidence was a literature summary.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable, as a specific clinical test set for performance evaluation (e.g., for an AI algorithm's diagnostic accuracy which would require ground truth labeling) was not conducted as part of this 510(k) as described. The "ground truth" for the device's functionality and safety was established via engineering verification, validation, and regulatory compliance.

4. Adjudication Method for the Test Set

Not applicable, as a clinical test set requiring adjudication was not reported as part of this 510(k) as described.

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

No, a MRMC comparative effectiveness study was not reported in this 510(k) clearance letter. The submission focused on establishing substantial equivalence through other means (software/system V&V, safety testing, literature review) rather than demonstrating AI assistance performance improvement.

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

The Visualase V2 System is a medical device system that includes hardware and software for MRI-guided laser ablation, with software providing monitoring and control capabilities related to temperature and thermal damage estimation. It is not an AI diagnostic algorithm for which a standalone performance evaluation (e.g., AUC, sensitivity/specificity) would typically be required or reported in this format. The software's performance is intrinsically linked to the system's function and user interaction.

Therefore, a "standalone algorithm only" performance study in the sense of a diagnostic AI product is not applicable and not reported.

7. The Type of Ground Truth Used

For the system's functional and safety validation, the "ground truth" would be engineering specifications, design requirements, and established medical and electrical safety standards (e.g., IEC standards, 21 CFR 820.30 Design Controls).

For any inferred clinical claims from the "literature summary," the ground truth would originate from the clinical data reported in the summarized peer-reviewed literature, which could involve histological confirmation, long-term patient outcomes, or expert clinical diagnosis, but these details are not provided in the 510(k) letter itself.

8. The Sample Size for the Training Set

Not applicable. The document describes a medical device system update, not an AI algorithm developed using a specific training dataset in the machine learning sense. The "training" for the system's software would derive from its design and programming, verified through the V&V processes.

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

Not applicable, as this is not an AI algorithm developed through data-driven training in the machine learning sense. The "ground truth" for the device's design and engineering would be based on scientific and engineering principles, preclinical testing, and existing medical knowledge, as per design control procedures.

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The O-arm™ O2 Imaging System is a mobile x-ray system, designed for 2D and 3D imaging for adult and pediatric patients weighing 60 lbs or greater and having an abdominal thickness greater than 16 cm, and is intended to be used where a physician benefits from 2D and 3D information of anatomic structures and objects with high x-ray attenuation such as bony anatomy and metallic objects. The O-arm™ O2 Imaging System is compatible with certain image guided surgery systems.

The O-arm™ O2 Imaging System is a mobile x-ray system that provides 3D and 2D imaging. The O-arm™ O2 Imaging System consists of two main assemblies that are used together: The Image Acquisition System (IAS) and The Mobile View Station (MVS). The two units are interconnected by a single cable that provides power and signal data. The IAS has an internal battery pack that provides power for motorized transportation and gantry positioning. In addition, the battery pack is used to power the X-ray tank. The MVS has an internal UPS to support its function when mains power is disconnected. The O-arm™ O2 Imaging System operates off standard line voltage within the following voltages: VAC 100, 120 or 240, Frequency 60Hz or 50Hz, Power Requirements 1440 VA.

The Medtronic O-arm™ O2 Imaging System with 4.3.0 software introduces three new features: Medtronic Implant Resolution (MIR) (referred to as KCMAR in the document), 3D Long Scan (3DLS), and Spine Smart Dose (SSD). The device's performance was evaluated through various studies to ensure substantial equivalence to the predicate device (O-arm™ O2 Imaging System 4.2.0 software) and to verify that the new features function as intended without raising new safety or effectiveness concerns.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

• Spine Smart Dose (SSD) Clinical Equivalence:
  • Sample Size: 100 clinical image pairs.
  • Data Provenance: "Clinical" images, suggesting retrospective or prospective clinical data. No specific country of origin is mentioned.
• KCMAR Clinical Equivalence:
  • Sample Size:
    • Initial study: 40 image pairs from four cadavers (small, medium, large, and extra-large habitus).
    • Subsequent study: 33 image pairs from two cadavers (small and extra-large habitus).
  • Data Provenance: Cadavers (ex-vivo data). No country of origin specified.
• 3D Long Scan (3DLS) Clinical Utility:
  • Sample Size: 45 paired samples from acquisitions of three cadavers (small, medium, and extra-large habitus). Two cadavers were instrumented with pedicle screw hardware.
  • Data Provenance: Cadavers (ex-vivo data). No country of origin specified.

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

• Spine Smart Dose (SSD) Clinical Equivalence: "board-certified neuroradiologist" (singular, implied one, but could be more based on typical study designs not explicitly stated as count of 1). The document mentions "board-certified neuroradiologist involving 100 clinical image pairs".
• KCMAR Clinical Equivalence: "Board-certified radiologists" (plural).
• 3D Long Scan (3DLS) Clinical Utility: "Board-certified radiologists" (plural).

4. Adjudication Method for the Test Set

The document does not explicitly state an adjudication method (e.g., 2+1, 3+1). It describes a "blinded review" for SSD and "clinical utility scores (1-5 scale)" for KCMAR and 3DLS, implying individual assessments that were then potentially aggregated or statistically compared.

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

The studies for SSD, KCMAR, and 3DLS involved multiple readers (board-certified radiologists/neuroradiologists) evaluating images.

• SSD: Compared "O-arm™ O2 Imaging System 4.3.0 SSD images" to "O-arm™ O2 Imaging System 4.2.x Standard and Predicate High-Definition modes." The outcome was clinical equivalence, not an improvement in human reader performance with AI assistance. It states the SSD leverages Machine Learning technology to reduce noise.
• KCMAR: Compared images reconstructed "without KCMAR feature" to images "with KCMAR feature." The outcome was "statistically better" clinical value for KCMAR. This indicates that the feature itself (which uses an algorithm for metal artifact reduction) resulted in better images, which would indirectly benefit the reader, but it doesn't quantify an improvement in human reader performance directly.
• 3DLS: Compared "Standard 3DLS and SSD 3DLS" to "corresponding Standard acquisition mode." The outcome was "statistically equivalent clinical utility." This specifically relates to the utility of the scan modes, not an AI-assisted interpretation by readers.

Therefore, while MRMC-like studies were conducted to assess the performance of the features, the focus was on the characteristics of the images produced by the device (clinical equivalence/utility/better value) rather than quantifying an effect size of how much human readers improve with AI versus without AI assistance in their diagnostic accuracy or efficiency.

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

Yes, aspects of standalone performance were evaluated through bench testing.

• SSD Bench Testing: Evaluated image quality parameters (3D Line pair, Contrast, MTF, Uniformity, Geometric accuracy) and navigational accuracy.
• KCMAR Bench Testing: Qualitatively compared metal artifact reduction and quantitatively assessed implant location accuracy.
• 3DLS Bench Testing: Verified system-level requirements for image quality (3D Line pair, Contrast, MTF, Geometric accuracy) and navigational accuracy.

These bench tests assess the algorithmic output directly against defined performance metrics, independent of human interpretation.

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

• Clinical Equivalence/Utility for SSD, KCMAR, 3DLS: Ground truth was established by expert assessment/consensus from board-certified neuroradiologists/radiologists providing clinical utility scores and making equivalence/superiority judgments.
• Bench Testing: Ground truth was based on phantom measurements and objective system-level requirements for image quality, geometric accuracy, and navigational accuracy.

8. The Sample Size for the Training Set

The document states that the Spine Smart Dose (SSD) feature "leverages Machine Learning technology with existing O-arm™ images to achieve reduction in dose..." However, it does not specify the sample size of the training set used for this Machine Learning model.

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

For the Spine Smart Dose (SSD) feature, which uses Machine Learning, the document mentions "existing O-arm™ images." It does not explicitly state how the ground truth for these training images was established. Typically, for such denoising or image enhancement tasks, the "ground truth" might be considered the higher-dose, higher-quality images, with the ML model learning to reconstruct a similar quality image from lower-dose acquisitions. The document implies that the model's output (low-dose reconstruction) was then validated against expert opinion for clinical equivalence.

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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 furnished document is a 510(k) premarket notification for the StealthStation Cranial Software, version 3.1.5. It details the device's indications for use, technological characteristics, and substantiates its equivalence to a predicate device through performance testing.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions "System accuracy validation testing" was conducted. However, it does not specify the sample size for this test set (e.g., number of cases, images, or measurements).

Regarding data provenance, the document does not explicitly state the country of origin of the data nor whether the data used for accuracy testing was retrospective or prospective. The study focuses on demonstrating substantial equivalence through testing against predefined accuracy thresholds rather than utilizing patient-specific clinical data.

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

The document does not provide information on the number of experts used to establish ground truth for the system accuracy validation testing, nor their specific qualifications. It mentions "User exploratory testing to explore clinical workflows, including standard and unusual clinically relevant workflows. This testing will include subject matter experts, internal and field support personnel," but this refers to a different type of testing (usability/workflow exploration) rather than objective ground truth establishment for accuracy measurements.

4. Adjudication Method for the Test Set:

The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for establishing ground truth for the system accuracy validation testing. The accuracy measurements appear to be objective, derived from controlled testing environments rather than subjective expert interpretations requiring adjudication.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted as part of this submission. The testing described is focused on the standalone performance of the device's accuracy in a controlled environment, not on how human readers perform with or without AI assistance.

6. Standalone Performance (Algorithm Only without Human-in-the-loop Performance):

Yes, standalone performance testing was done. The "System accuracy validation testing" directly assesses the algorithm's performance in achieving specific positional and angular accuracy. The reported "Positional Error - 0.824 mm" and "Trajectory Error - 0.615 degrees" are metrics of the standalone algorithm's accuracy without direct human intervention in the measurement process itself, although the device is ultimately used by humans in a clinical context.

7. Type of Ground Truth Used:

The ground truth for the system accuracy validation testing appears to be based on objective, controlled measurements within a testing environment, likely involving phantom models or precise physical setups where the true position and orientation are known or can be measured with high precision. This is implied by the nature of "3D positional accuracy" and "trajectory angle accuracy" measurements, which are typically determined against a known, precise reference. It is not expert consensus, pathology, or outcomes data.

8. Sample Size for the Training Set:

The document does not provide any information regarding the sample size for a training set. This is because the StealthStation Cranial Software is a navigation system that uses image processing and registration algorithms, rather than a machine learning model that requires a distinct training dataset in the traditional sense. The software's development likely involves engineering principles and rigorous testing against design specifications, not iterative learning from data.

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

As the device does not appear to be an AI/ML model that undergoes a machine learning "training" phase with a labeled dataset in the conventional understanding for medical imaging analysis, the concept of establishing ground truth for a training set is not applicable in this context. The software's functionality is based on established algorithms for image registration and instrument tracking, which are then validated through performance testing against pre-defined accuracy thresholds.

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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 Visualase MRI-Guided Laser Ablation System is a neurosurgical tool and is indicated for use to ablate, necrotize, or coagulate intracranial soft tissue including brain structures (for example, brain tumor, radiation necrosis and epileptic foci as identified by non-invasive and invasive neurodiagnostic testing, including imaging) through interstitial irradiation or thermal therapy in medicine and surgery in the discipline of neurosurgery with 800nm through 1064mm lasers.

The Visualase MRI-Guided Laser Ablation System comprises hardware and software components used in combination with three MR-compatible (conditional), sterile, single-use, saline-cooled laser applicators with proprietary diffusing tips that deliver controlled energy to the tissue of interest. The system consists of: a diode laser (energy source) a coolant pump to circulate saline through the laser application Visualase workstation which interfaces with MRI scanner's host computer Visualase software which provides the system's ability to visualize and monitor relative changes in tissue temperature during ablation procedures, set temperature limits and control the laser output; two monitors to display all system imaging and laser ablation via a graphical user interface and peripherals for interconnections Remote Presence software provides a non-clinical utility application for use by Medtronic only and is not accessible by the user

The provided text describes specific details about the Visualase MRI-Guided Laser Ablation System (SW 3.4) and its comparison to predicate devices, but it does not contain a table of acceptance criteria or a detailed study description with performance metrics in the format requested.

The "Testing Summary" section mentions in vivo testing to demonstrate accuracy and performance of MR Thermometry and Thermal Damage Estimate, as well as software and system verification and validation. However, it does not provide:

• Specific acceptance criteria values (e.g., "accuracy must be within X degrees Celsius").
• Reported device performance values against these criteria.
• Sample sizes for the test set.
• Data provenance.
• Details about expert involvement or adjudication.
• Information on MRMC studies or standalone AI performance.
• Details about the training set.

Therefore, most of the requested information cannot be extracted from the given text.

Here's a breakdown of what can be extracted and what is missing based on your request:

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

• Acceptance Criteria: Not explicitly stated with numeric values in the document. The general statement is "Testing demonstrated the accuracy and precision of the Visualase MRI-Guided Ablation System's Thermal Damage Estimate and MR Thermometry for its intended use."
• Reported Device Performance: Not provided (e.g., no specific accuracy values, precision values, or success rates are given).

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

• Sample Size: Not specified.
• Data Provenance: The testing was "In vivo testing conducted 1.5T and 3.0T (in accordance with 21 CFR 58)". 21 CFR Part 58 refers to Good Laboratory Practice for nonclinical laboratory studies, which implies prospective in vivo studies, but does not specify the origin of the data (e.g., country).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not specified.

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

• Not specified.

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

• The document implies the device is a tool used by a neurosurgeon. It does not describe a comparative effectiveness study involving human readers with or without AI assistance, or any effect size for such a study.

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

• The document states the system "provides the system's ability to visualize and monitor relative changes in tissue temperature during ablation procedures, set temperature limits and control the laser output." It is an MRI-guided system implying human-in-the-loop operation. No standalone algorithm-only performance is described.

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

• Given it's "in vivo testing" for "Thermal Damage Estimate" and "MR Thermometry," the ground truth likely involved a direct measurement method for temperature or thermal damage in the tissue, possibly through implanted probes or post-ablation pathological assessment, but the specific method is not detailed.

8. The sample size for the training set

• Not applicable as this document describes performance of a medical device (laser ablation system with software), not a machine learning model explicitly detailing training data. The software components are verified and validated, but no "training set" in the context of AI/ML is mentioned.

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

• Not applicable for the reasons stated above.

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The StealthStation System, with StealthStation Cranial software, is intended as an aid for locating anatomical structures in either open or percutaneous neurosurgical procedures. Their use 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 the skull, 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):

• Tumor resections
• General ventricular catheter placement
• Pediatric ventricular catheter placement
• Depth electrode, lead, and probe placement
• Cranial biopsies

The StealthStation™ Cranial Software v2.0 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. During surgery, positions of specialized surgical instruments are continuously updated on these images either by optical tracking or electromagnetic tracking.

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 changes to the currently cleared StealthStation™ S8 Cranial Software are as follows:

• Addition of white matter tractography (WMT) fiber tract creation for the brain referred to as diffusion Magnetic Resonance Imaging (dMRI) tractography. dMRI tractography will process diffusion-weighted MRI data into 3D fiber tract models that represent whitematter tracts. This will be marketed as a software option called Stealth™ Tractography.
• Addition of the Medtronic SenSight™ directional DBS lead to the existing list of view overlays.
• Minor changes to the software were made to address user preferences and to fix minor anomalies.

The provided text describes the performance testing and acceptance criteria for the Medtronic Navigation StealthStation S8 Cranial v2.0 software, particularly focusing on the new white matter tractography (WMT) feature.

Here's a breakdown of the requested information:

1. Table of acceptance criteria and the reported device performance:

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

• Test Set Sample Size: The document does not specify a numerical sample size for the "datasets" used in summative usability validation and clinical expert evaluation. It states "datasets not used for development, composed of normal and abnormal brains in both pediatric and adult populations."
• Data Provenance: Not explicitly stated, but the mention of "datasets not used for development" suggests a separate, possibly curated, test set. There is no information on the country of origin or whether the data was 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: The document refers to "clinical experts" (plural) but does not specify the exact number.
• Qualifications of Experts: Not explicitly stated (e.g., "radiologist with 10 years of experience"). It only identifies them as "representative users" and "clinical experts."

4. Adjudication method for the test set:

• The document does not describe a formal adjudication method (e.g., 2+1, 3+1). It states that "Clinical expert evaluations included white matter tract generation and editing," implying direct assessment by these experts.

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 MRMC comparative effectiveness study is mentioned. The study focuses on the device's performance and validation through usability and clinical expert evaluation of the tractography feature, not on human reader performance improvement with AI assistance. The device functions as an aid for locating anatomical structures and displays information; it doesn't appear to be an AI that assists human interpretation in a comparative effectiveness sense.

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

• Yes, a standalone performance test was done for the "System Accuracy" related to 3D positional accuracy and trajectory angle accuracy. This 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 assessment of the system's ability to achieve these accuracy metrics independently of human interaction during the measurement. The "correct creation and rendering of dMRI tracts" also implies an algorithm-only assessment of the output.

7. The type of ground truth used:

• For System Accuracy (Positional and Trajectory): "Anatomically representative phantoms" were used. The ground truth would be the known, precisely measured dimensions and positions within these phantoms.
• For Software Functionality (dMRI tractography): The ground truth appears to be based on whether the software correctly creates and renders the dMRI tracts as per established specifications and expectations, as assessed by performance testing. Clinical experts further evaluated the quality and clinical utility of these rendered tracts in relation to other structures.
• For Usability and Clinical Expert Evaluation: The ground truth is effectively the consensus or expert judgment of the "representative users" and "clinical experts" regarding the safety, effectiveness, and clinical utility of the software and its new tractography feature. This is a form of expert consensus or clinical judgment. No mention of pathology or outcomes data for establishing ground truth is made in this context.

8. The sample size for the training set:

• The document does not provide any information about a training set since this is a regulatory submission for a software device, not an AI model that requires a distinct training phase. The new feature, dMRI tractography, processes diffusion-weighted MRI data into 3D fiber models. While the underlying algorithms would have been developed and "trained" (in a broader development sense), this document does not refer to a dedicated "training set" in the context of the device's clearance.

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

• Not applicable, as a "training set" distinct for an AI model is not described in this regulatory submission. The development and verification of the tractography algorithms would have involved internal processes and known physics/mathematics of dMRI data processing.

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The navigated instruments are specifically designed for use with the 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.

When used with a Medtronic StealthStation™ Navigation System, the Spine Referencing fixation devices are intended to provide rigid attachment between patient and patient reference frame for the duration of the surgery.

The Spinous Process Clamps are intended to provide rigid attachment between patient and patient reference frame for the duration of the surgery. The subject devices are designed for use with the StealthStation™ System and are intended to be reusable.

The provided text describes a 510(k) premarket notification for a medical device, the StealthStation™ Spinous Process Clamps. This document outlines the device's characteristics, intended use, and a comparison to a predicate device, along with a summary of performance testing.

However, the document does not describe an AI/ML-driven device or a study involving "human readers" improving with "AI vs without AI assistance." It pertains to a physical stereotaxic instrument used in spinal surgery for rigid attachment to a patient's anatomy for navigation.

Therefore, many of the specifics requested in your prompt (e.g., sample size for test/training sets, data provenance, number of experts for ground truth, adjudication method, MRMC studies, standalone performance, type of ground truth for AI, training set details) are not applicable to this type of medical device submission.

The document discusses performance testing relevant to a mechanical device, such as functional verification, useful life testing, navigation accuracy testing, and packaging verification, as well as biological endpoint testing. These tests are to ensure the device's safety and effectiveness as a physical surgical tool and reference system, not as an AI diagnostic or assistive tool.

To answer your prompt, I will extract the information that is present and explicitly state when information is not applicable given the nature of the device.

Acceptance Criteria and Device Performance for Medtronic StealthStation™ Spinous Process Clamps

The device in question, the StealthStation™ Spinous Process Clamps, is a physical stereotaxic instrument, not an AI/ML-driven device. Therefore, the "acceptance criteria" and "study" described in the provided text relate to the mechanical and biological performance of this instrument, not to the performance of an AI algorithm or its impact on human reader performance.

The "studies" are performance tests designed to demonstrate the device's substantial equivalence to a predicate device and its safety and effectiveness for its intended use as a surgical instrument.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a formal table of quantitative acceptance criteria with corresponding performance metrics like those typically seen for AI/ML device validations (e.g., sensitivity, specificity, AUC thresholds). Instead, the performance testing described is qualitative or refers to compliance with established standards for mechanical and biological safety.

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

• Test Set Sample Size: Not explicitly stated as a "sample size" in the context of patient data or algorithm testing. The performance testing likely involved a limited number of physical devices (e.g., clamps) for mechanical and biological evaluations. This is not a data-driven AI model.
• Data Provenance: Not applicable. The "data" comes from physical testing of the device, not from patient medical records or imaging scans. The testing would have occurred in a laboratory or manufacturing environment.
• Retrospective/Prospective: Not applicable. The testing is a controlled, experimental assessment of the device's physical properties and performance, not a study on historical or future patient data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Not applicable. This section is relevant for AI/ML applications where expert labeling is used to create ground truth for image classification, segmentation, etc. For a mechanical device, "ground truth" relates to engineering specifications, physical measurements, and compliance with industry standards, which are evaluated by engineers and technical specialists, not typically "experts" in the context of medical image interpretation.

4. Adjudication Method for the Test Set

• Not applicable. Adjudication methods (e.g., 2+1, 3+1 consensus) are used in studies involving human interpretation of complex medical data, especially for establishing ground truth in AI model development. This device's testing involves objective engineering and biological assessments.

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

• No. An MRMC study is specific to evaluating the impact of an AI algorithm on human reader performance, usually in diagnostics. This device is a physical surgical instrument, not an AI diagnostic tool.

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

• No, not applicable. This concept pertains to the performance of an AI algorithm by itself. The StealthStation™ Spinous Process Clamps are physical devices that are used with a navigation system and by a human surgeon. Their performance is inherently related to their physical interaction and functionality for surgical navigation.

7. The Type of Ground Truth Used

• Engineering Specifications and Standardized Test Methods: For functional verification, useful life, packaging, and navigational accuracy, the "ground truth" would be the pre-defined engineering specifications, design requirements, and objective measurements obtained using established test methodologies (e.g., ASTM, ISTA, internal quality standards).
• ISO 10993-1:2018 Standards: For biocompatibility, the ground truth is established by the accepted biological safety endpoints and testing protocols outlined in the ISO 10993 series of standards.

8. The Sample Size for the Training Set

• Not applicable. This device is not an AI/ML algorithm that requires a "training set" of data.

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

• Not applicable. As there is no training set for an AI/ML algorithm, the concept of establishing ground truth for it does not apply.

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The StealthStation System, with StealthStation Cranial Software, is intended as an aid for locating anatomical structures in either open or percutaneous neurosurgical procedures. Their use 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 the skull, 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):

• Tumor resections
• General ventricular catheter placement
• Pediatric ventricular catheter placement
• Depth electrode, lead, and probe placement
• Cranial biopsies

The StealthStation™ Cranial Software v1.3.2 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. During surgery, positions of specialized surgical instruments are continuously updated on these images either by optical tracking or electromagnetic tracking.

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 acceptance criteria for the StealthStation™ Cranial Software v1.3.2 are not explicitly detailed in the provided document beyond the general statement of "System Accuracy Requirements" being "Identical" to the predicate device. The performance characteristics of the predicate device, StealthStation™ Cranial Software v1.3.0, are stated as the benchmark for system accuracy.

Here's the information extracted from the document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• The document states that "Software verification testing for each requirement specification" was conducted and "Design verification was performed using the StealthStation™ System with Station™ Cranial Software v1.3.2 in laboratory."
• No specific sample size for a test set is mentioned. The testing described is software verification and design verification, not a clinical study on patient data for performance evaluation in the typical sense of AI/ML devices.
• Data provenance is not applicable or not disclosed as the document indicates "Clinical testing was not considered necessary prior to release as this is not new technology."

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

• Not applicable. The testing described is software and design verification rather than a clinical performance study requiring expert ground truth establishment from patient data.

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

• Not applicable. This information is relevant for clinical studies involving multiple reviewers adjudicating findings, which was not performed.

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 performed. The device is a navigation system and not an AI-assisted diagnostic tool that would typically involve human readers.

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

• No. The device is a surgical navigation system, which is inherently a human-in-the-loop tool. The performance evaluation focuses on its accuracy specifications within that use case during design verification.

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

• Not applicable. For the system accuracy, the ground truth would be precise measurements taken in a laboratory setting for the navigational accuracy, rather than clinical ground truth from patient data like pathology or outcomes.

8. The sample size for the training set:

• Not applicable. The document describes a software update for a stereotaxic instrument, not an AI/ML device that undergoes model training with a dataset.

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

• Not applicable. As the device is not described as an AI/ML system requiring a training set, the establishment of ground truth for such a set is not relevant.

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The StealthStation FlexENT™ System, with the StealthStation™ ENT Software, is intended as an aid for precisely locating anatomical structures in either open or percutaneous ENT procedures. Their use 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 the skull, can be identified relative to images of the anatomy.

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

• Functional Endoscopic Sinus Surgery (FESS)
• Endoscopic Skull Base procedures
• Lateral Skull Base procedures

The Medtronic SteathStation FlexENT™ computer-assisted surgery system and its associated applications are intended as an aid for precisely locating anatomical structures in either open or percutaneous ENT procedures. Their use 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 the skull, can be identified relative to images of the anatomy.

The StealthStation FlexENT™ is an electromagnetic based surgical guidance platform that supports use of special application software (StealthStation™ S8 ENT Software 1.3 and associated instruments.

The StealthStation™ S8 ENT Software 1.3 helps guide surgeons during ENT procedures such as functional endoscopic sinus surgery (FESS), endoscopic skull base procedures, and lateral skull base procedures. StealthStation™ S8 ENT Software 1.3 functionality is described in terms of its feature sets which are categorized as imaging modalities, registration, planning, and views. Feature sets include functionality that contributes to clinical decision making and are necessary to achieve system performance.

Patient images can be displayed by the StealthStation™ S8 ENT Software 1.3 from a variety of perspectives (axial, sagittal, coronal, oblique) and 3dimensional (3D) renderings of anatomical structures can also be displayed. During navigation, the system identifies the tip location and traiectory of the tracked instrument on images and models the user has selected to display. The surgeon may also create and store one or more surgical plan trajectories before surgery and simulate progression along these trajectories. During surgery, the software can display how the actual instrument tip position and trajectory relate to the plan, helping to guide the surgeon along the planned trajectory. While the surgeon's judgment remains the ultimate authority, realtime positional information obtained through the StealthStation™ System can serve to validate this judgment as well as guide. The StealthStation™ S8 ENT v1.3 Software can be run on both the StealthStation FlexENT™ and StealthStation™ S8 Platforms.

The StealthStation™ System is an Image Guided System (IGS), comprised of a platform (StealthStation FlexENT™ or StealthStation™ S8), clinical software, surgical instruments, and a referencing system (which includes patient and instrument trackers). The IGS tracks the position of instruments in relation to the surgical anatomy, known as localization, and then identifies this position on preoperative or intraoperative images of a patient.

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document states that "Testing was performed under the representative worst-case configuration... utilizing a subset of system components and features that represent the worst-case combinations of all potential system components." It does not specify a numerical sample size for the test set (e.g., number of phantoms or trials).

The data provenance is not explicitly stated in terms of country of origin. The test appears to be a prospective bench study conducted by the manufacturer, Medtronic Navigation, Inc.

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

The document does not mention the use of experts to establish ground truth for this accuracy testing. The ground truth for positional and trajectory accuracy would typically be established by precise measurements on the anatomically representative phantoms using highly accurate measurement systems, not by expert consensus.

4. Adjudication Method for the Test Set:

Not applicable, as this was a bench accuracy test with directly measurable metrics, not a subjective assessment requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

No, an MRMC comparative effectiveness study was not conducted. The study focuses on the standalone accuracy of the device.

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

Yes, a standalone performance study was done. The accuracy testing described ("3D positional accuracy" and "trajectory angle accuracy") measures the device's inherent accuracy in locating anatomical structures and guiding trajectories, independent of human interaction during the measurement process. The system tracks instruments and displays their position and trajectory on images without direct human interpretation being part of the measurement for these accuracy metrics.

7. The Type of Ground Truth Used:

The ground truth used for this accuracy study was derived from precise physical measurements taken on "anatomically representative phantoms." This implies that the true position and trajectory were known and used as reference points against which the device's reports were compared.

8. The Sample Size for the Training Set:

The document does not provide information about a training set since the study described is a performance validation of a medical device's accuracy, not a machine learning model that would require a dedicated training set. The software likely undergoes extensive internal development and testing, but separate "training set" details are not provided in this context.

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

Not applicable, as no training set information is provided or relevant for this type of accuracy study.

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