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The Stealth AXIS Surgical System, with the Stealth AXIS Cranial clinical application, is intended for precise positioning of surgical instruments and as an aid for locating anatomical structures in open, minimally invasive, and 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 Stealth AXIS Cranial clinical application works in conjunction with the Stealth AXIS Surgical System. The Stealth AXIS Cranial clinical application helps guide surgeons during cranial procedures such as biopsies, tumor resections, shunt placements and depth electrode and probe placement. The system tracks the position of instruments in relation to surgical anatomy and identifies this position on diagnostic or intraoperative images of the patient.

Patient images are transferred to the system, and the Stealth AXIS Cranial clinical application displays the image of the patient anatomy from a variety of perspectives (axial, sagittal, coronal, oblique) and 3-dimensional (3D) renderings of anatomical structures. During navigation, the Stealth AXIS Surgical System identifies the tip location and trajectory of the tracked instrument on images and models the user has selected to display on the monitor. The surgeon may also create and store one or more surgical plan trajectories before surgery and simulate progression along these trajectories. During surgery, the Stealth AXIS Cranial clinical application can display how the actual instrument tip position and trajectory relate to the pre-surgical plan, helping to guide the surgeon along the planned trajectory.

The provided FDA 510(k) clearance letter and summary for the Stealth AXiS Cranial clinical application offers surprisingly limited detail on the specific acceptance criteria and the study that proves the device meets them, especially concerning the AI/ML components. However, I will extract and infer as much as possible from the provided text to answer your questions.

It's important to note that the clearance letter itself doesn't present the full study details, but rather summarizes the findings that Medtronic provided to the FDA. Many of the specific details you requested (like exact sample sizes for test sets, data provenance, number and qualifications of experts, and adjudication methods for ground truth) are not explicitly stated in this public document. I will highlight what is present and what is missing.

Acceptance Criteria and Device Performance Study for Stealth AXiS Cranial Clinical Application

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on overall system accuracy requirements and general software validation. For the AI-enabled "Autotracts" feature, the acceptance criteria are less formally quantified in the provided text.

2. Sample Size for the Test Set and Data Provenance

• Test Set Sample Size: Not explicitly stated in the document for either the general system accuracy or the AI Autotracts feature. The document only mentions "withheld datasets" for validation of the AI model.
• Data Provenance:
  • For System Accuracy: "representative worst-case configuration" implies laboratory testing, not patient data in this context.
  • For AI Autotracts: "hundreds of images from internal studies and public datasets, spanning normal and pathological cases." The country of origin and whether the data was retrospective or prospective are not specified.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not explicitly stated. The document mentions "expert-reviewed gold standard annotations" for the training/validation of the Autotracts and "expert review" to assess performance.
• Qualifications of Experts: Not explicitly stated. It is implied that these are experts in brain anatomy, neuroimaging, and neuronavigation, but specific qualifications (e.g., "Radiologist with 10 years of experience") are not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. For the expert-reviewed ground truth, it is unknown if a single expert provided the ground truth, if consensus was reached among multiple experts (e.g., 2+1, 3+1), or if there was no formal adjudication process described beyond "expert-reviewed."

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

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was explicitly NOT performed. The document states, "No clinical testing was performed." The usability validation was done by "representative users," but this is distinct from a clinical MRMC study designed to measure the effect size of AI assistance on human reader performance.
• Effect Size of AI vs. Without AI Assistance: Since no clinical testing or MRMC study was performed, there is no reported effect size of how much human readers improve with AI vs. without AI assistance in this document.

6. Standalone (Algorithm Only) Performance

• Standalone Performance: For the AI-enabled "Autotracts" feature, the description of "Performance was assessed leveraging expert review to ensure reliability" suggests some form of standalone evaluation against expert-derived ground truth. However, specific quantitative standalone metrics (e.g., sensitivity, Dice coefficient for segmentation, average distance error for tractography) are not provided. The phrase "Users retain control by adjusting tract appearance... and ultimately verifying tracts before proceeding" also highlights that the AI's output is intended for human-in-the-loop verification, not necessarily as a standalone diagnostic or planning output without review.

7. Type of Ground Truth Used

• For System Accuracy: Physical measurements against known standards in a "worst-case configuration."
• For AI Autotracts: "expert-reviewed gold standard annotations" for training and validation, and "expert review" for performance assessment. This implies expert consensus on the definition of white matter tracts based on diffusion MRI images. It does not mention pathology or outcomes data for ground truth for this specific AI feature.

8. Sample Size for the Training Set

• Training Set Sample Size: Not explicitly stated. The document mentions "Training and validation used hundreds of images from internal studies and public datasets." It does not separate the exact number for training versus validation.

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

• Ground Truth Establishment for Training Set: The ground truth for the AI Autotracts training set was established through "expert-reviewed gold standard annotations." This indicates that human experts manually identified or delineated the white matter tracts on the diffusion MRI images, and their work was considered the "gold standard" for the AI model to learn from.

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The Stealth AXiS™ Surgical System, with the Stealth AXiS™ ENT clinical application, is intended for precise positioning of surgical instruments and as an aid for locating anatomical structures in open, minimally invasive, and 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 Stealth AXiS ENT Clinical Application works in conjunction with the Stealth AXiS Surgical System, which consists of clinical software, surgical instruments, a referencing system, and platform/computer hardware. The Stealth AXiS™ ENT Clinical Application helps guide surgeons during ENT procedures such as functional endoscopic sinus surgery (FESS), endoscopic skull base procedures, and lateral skull base procedures. The system 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.

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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 1064nm lasers.

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 Cooled Laser Applicator System (VCLAS) is an MR-compatible (conditional), sterile, single-use, saline-cooled laser applicator with proprietary diffusing tips that deliver controlled energy to targeted tissue when connected to the Visualase Systems.

The VCLAS is an accessory to both cleared versions of the Visualase Cooled Laser Ablation Systems - Visualase MRI-guided Laser Ablation System (V1 System, K211269) and Visualase V2 MRI-guided Laser Ablation System (V2 System, K250307). The V1 and V2 systems are not subjects of this submission.

This change encompasses changes to the Visualase Cooled Laser Applicator System (VCLAS) pump tubing set, extension tubing and inlet/outlet ports to ensure compatibility with both cleared Visualase Systems (K211269 and K250307) and accompanying information to inform safe and effective use. The device modifications include material changes and there are no changes to Visualase Systems (V1 and V2 system)' hardware or software.

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The Stealth AXiS™ Surgical System is intended for precise positioning of surgical instruments and as an aid for precisely locating anatomical structures in open, minimally invasive, and percutaneous procedures. The Stealth AXiS™ Surgical System is indicated for medical conditions in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a CT or MR based model, fluoroscopy images, or digitized landmarks of the anatomy.

The Stealth AXiS™ Surgical System is indicated for precise robotic positioning of surgical instruments or implants during orthopedic or neurosurgery. It may be used in open, minimally invasive, and percutaneous procedures.

The Stealth AXiS™ Surgical System, with the Stealth AXiS™ Spine clinical application, is intended for precise positioning of surgical instruments and as an aid for precisely locating anatomical structures in open, minimally invasive, and percutaneous procedures. Their use is indicated for medical conditions in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as the spine or pelvis, can be identified relative to images of the anatomy.

This can include procedures in adult patients, such as:
• Interbody device placement
• Pedicle screw placement
• Iliosacral screw placement

This can include the following spinal implant procedure in skeletally mature pediatric (adolescent) patients:
• Pedicle screw placement

The Stealth AXiS™ Surgical System is a computer-assisted surgery system that is composed of a platform, clinical application, surgical instruments, and a referencing system (which includes patient and instrument trackers). The system 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. The Stealth AXiS™ Surgical System supports both optical and electromagnetic (EM) localization. Localization is also called navigation.

The Stealth AXiS™ Spine clinical application helps guide surgeons during spine procedures. Patient images can be displayed by the Spine clinical application from a variety of perspectives (axial, sagittal, coronal, oblique) and 3-dimensional (3D) renderings of anatomical structures can also be displayed. During navigation, the system identifies the tip location and trajectory 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 clinical application displays 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, real-time positional information obtained through the Stealth AXiS™ Surgical System can serve to guide this judgment.

With the addition of the Stealth AXiS™ Autopilot to the Stealth AXiS™ Core, the Stealth AXiS™ Surgical System becomes a robotic-assisted surgery system.

Here's an analysis of the acceptance criteria and study information for the Stealth AXiS™ Surgical System with Stealth AXiS™ Spine clinical application, based on the provided 510(k) clearance letter:

Acceptance Criteria and Device Performance

Study Information

1. Sample sized used for the test set and the data provenance:

• AI-enabled Automatic Planning: Test data was strictly separated from training data by site and included scans stratified by surgical approach and vertebra. Specific sample size is not provided in the document.
• AI-enabled Automatic Spine Segmentation: Test data was separated from training data. Specific sample size is not provided in the document.
• General System Accuracy: "Under representative worst-case configuration..." Specific sample size (e.g., number of measurements, cadavers) and data provenance (e.g., country of origin, retrospective or prospective) are not provided in the document.
• Clinical Testing: A retrospective clinical evaluation of published literature was performed. Specific details on the number of studies or patients are not provided.

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

• AI-enabled Automatic Planning: The model compared candidate screw placements to "expert standards" and identified solutions aligned with "expert decisions." These expert placements were from "Surgical Support Technicians." The number of experts or specific qualifications are not explicitly stated beyond "Surgical Support Technicians."
• AI-enabled Automatic Spine Segmentation: Ground truth was "clinician-reviewed." The number of clinicians or their specific qualifications (e.g., radiologist with X years of experience) are not provided.
• General System Accuracy: Not applicable as ground truth for "accuracy" typically refers to physical measurements against a known standard.

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

• AI-enabled Automatic Planning: Decision-making relies on the AI model identifying solutions similar to "expert decisions," with clinical users having full control to review, modify, or override. This implies an expert review step but does not specify a formal adjudication method like N+1.
• AI-enabled Automatic Spine Segmentation: Ground truth was "clinician-reviewed." This implies review, but a formal adjudication method (e.g., majority vote, consensus) is not specified.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• A formal MRMC comparative effectiveness study comparing human readers with AI assistance versus without AI assistance is not explicitly mentioned for either AI feature. The AI features are described as aids where the human user retains ultimate control. The document focuses on the standalone performance of the AI components and system accuracy rather than direct human performance improvement.

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

• AI-enabled Automatic Planning: The model outputs screw placement recommendations. While clinical users can modify these, the performance evaluation likely assesses the accuracy of the AI’s initial recommendations against expert standards, suggesting a standalone component to its evaluation.
• AI-enabled Automatic Spine Segmentation: Model performance was evaluated by comparing "AI-generated segmentations to clinician-reviewed ground truth," which indicates a standalone evaluation of the algorithm's segmentation output.
• General System Accuracy: Yes, the "3D positional accuracy" and "trajectory angle accuracy" are standalone performance metrics for the device.

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

• AI-enabled Automatic Planning: "Expert standards" and "expert decisions" from "Surgical Support Technicians." This indicates expert consensus or labeled data from experts.
• AI-enabled Automatic Spine Segmentation: "Clinician-reviewed ground truth." This implies expert review or consensus.
• General System Accuracy: Ground truth for physical accuracy studies is typically established through high-precision metrology or physical measurements against a known standard, often in a lab setting, but not explicitly stated here.

7. The sample size for the training set:

• AI-enabled Automatic Planning: "expert screw placements from Surgical Support Technicians." Specific sample size is not provided.
• AI-enabled Automatic Spine Segmentation: "internal and public datasets." Specific sample size is not provided.

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

• AI-enabled Automatic Planning: Ground truth was established from "expert screw placements from Surgical Support Technicians," implying that these technicians provided the optimal screw placements used to train the model.
• AI-enabled Automatic Spine Segmentation: Ground truth was established using "internal and public datasets," with the implication that these datasets contained accurately segmented vertebrae, likely performed by clinicians or experts. The statement "clinician-reviewed ground truth" for validation suggests a similar approach for training data.

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The StealthStation™ System, with StealthStation™ Spine Software, is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical and orthopedic procedures in adult and skeletally mature pediatric (adolescent) patients. 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 spine or pelvis, can be identified relative to images of the anatomy.

This can include the following spinal implant procedures in adult patients, such as:

• Pedicle Screw Placement
• Iliosacral Screw Placement
• Interbody Device Placement

This can include the following spinal implant procedures in skeletally mature pediatric (adolescent) patients:

• Pedicle Screw Placement

StealthStation S8 Spine Software helps guide surgeons during spine surgical procedures. The subject software works in conjunction with a navigation system, surgical instruments, a referencing system, and computer hardware. Navigation tracks the position of instruments in relation to the surgical anatomy and identifies this position on pre-operative or intraoperative images of the patient. The mouse, keyboard, touchscreen monitor, and footswitch of the StealthStation platforms are used to move through the software workflow. Patient images are displayed by the software from a variety of perspectives (axial, sagittal, coronal, oblique) and 3-dimensional (3D) renderings. During navigation, the system identifies the tip location and trajectory of the tracked instrument on images and models the user has selected to display on the monitor. The surgeon may also create and store one or more surgical plan trajectories before and during 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.

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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 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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