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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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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 v1.3.0 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 an optional image display that allows the user to see through outer layers to increase the visibility of other models.
• . Update the imaging protocol to support overlapping slices.
• . Minor changes to the software were made to address user preferences and to fix minor anomalies.

The provided document is a 510(k) premarket notification summary for Medtronic's StealthStation Cranial Software v1.3.0. It describes the device, its intended use, and a comparison to a predicate device, along with performance testing.

Here's an analysis to address your specific questions:

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

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

The document does not specify a sample size (e.g., number of cases or images) for the performance testing. It states that the performance was determined "using anatomically representative phantoms and utilizing a subset of system components and features that represent the worst-case combinations of all potential system components."

Regarding data provenance, the testing was conducted in "laboratory and simulated use settings" using "anatomically representative phantoms." This indicates that the data was generated specifically for testing purposes, likely in a controlled environment, rather than being derived from real patient scans. The country of origin for the data is not specified, but the applicant company, Medtronic Navigation Inc., is based in Louisville, Colorado, USA. The testing appears to be prospective in nature, as it was specifically carried out to demonstrate equivalence.

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)

The document does not mention the involvement of human experts for establishing ground truth for the performance testing. The accuracy measurements (3D positional and trajectory angle) are typically derived from physical measurements against known ground truth (e.g., phantom dimensions, known instrument positions) in the context of navigation systems, not by expert consensus on image interpretation.

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

Not applicable. The performance testing described is objective measurement against physical phantoms, not subjective assessment by experts requiring adjudication.

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

No. The document explicitly states: "Clinical testing was not considered necessary prior to release as this is not new technology." This device is an image-guided surgery system software, not an AI-assisted diagnostic tool that would typically undergo MRMC studies. The changes in this version (v1.3.0) are described as "minor changes to the software were made to address user preferences and to fix minor anomalies" and "Addition of an optional image display that allows the user to see through outer layers," suggesting incremental updates rather than a fundamentally new AI algorithm.

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

Yes, the performance testing was effectively "standalone" in the sense that the system's accuracy was measured against a known physical ground truth (phantoms) rather than evaluating human performance with the system. The reported accuracy metrics describe the device's inherent precision in tracking and navigation, independent of user interaction during the measurement process itself.

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

The ground truth used was based on known physical properties of anatomically representative phantoms. This means that a physical phantom with precisely known dimensions and features was used, and the device's ability to accurately locate points and trajectories within that known physical structure was measured. This is a common and appropriate method for validating the accuracy of surgical navigation systems.

8. The sample size for the training set

Not applicable. This device, as described, is a software for image-guided surgery, not an AI/ML model that would typically have a "training set" in the context of deep learning. The changes are described as minor software updates and an optional display feature, not a new algorithm requiring a training phase from data.

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

Not applicable, as there is no mention of a training set for an AI/ML model in this submission.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

1. Table of Acceptance Criteria and Reported Device Performance

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

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

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

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

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

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

4. Adjudication Method for the Test Set

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

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

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

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

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

7. The Type of Ground Truth Used

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

8. The Sample Size for the Training Set

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

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

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

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The Visualase™ Therapy System is indicated for use to necrotize or coagulate soft tissue through interstitial irradiation or thermal therapy under magnetic resonance imaging (MRI) guidance in medicine and surgery in cardiovascular thoracic surgery (excluding the heart and the vericardial sac), dermatology, ear-nose-throat surgery, gastroenterology, general surgery, gynecology, head and neck surgery, plastic surgery, orthopedics, pulmonology, radiology, and urology, for wavelengths 800nm through 1064mm.

When therapy is performed under MRI guidance, and when data from compatible MRI sequences is available, the Visualase™ system can process images using proton resonance-frequency (PRF) shift analysis and image subtraction to relate changes in complex phase angle back to relative changes in tissue temperature during therapy. The image data may be manipulated and viewed in a number of different ways, and the values of data at certain selected points may be monitored and/or displayed over time.

The Visualase™ Thermal Therapy System is compatible with General Electric Medical Systems Signa model MR scanners and with Siemens Medical Solutions Magnetom Espree systems. When interpreted by a trained physician, this device provides information that may be useful in the determination or assessment of thermal therapy. Patient management decisions should not be made solely on the basis of Visualase™ analysis.

The Visualase Thermal Therapy System comprises of 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 document is a 510(k) summary for the Medtronic Visualase Thermal Therapy System. It describes labeling changes to the device manual and explicitly states that no new performance testing was required as there are no changes to the device itself. Therefore, the document does not contain information about studies specifically conducted to prove the device meets acceptance criteria for its current performance.

The document indicates that this 510(k) submission is for labeling changes only, primarily adding new warnings and information that were previously distributed via field corrective actions. It confirms that these changes do not affect the intended use or fundamental technology of the Visualase Thermal Therapy System.

Consequently, I cannot provide the requested information regarding acceptance criteria and a study to prove they are met because this 510(k) submission does not include such a study for the current device. The acceptance criteria and performance data would have been established and submitted during earlier 510(k) clearances for the device itself (e.g., K081656), not for this labeling update.

The request for information on multi-reader multi-case (MRMC) studies, effect sizes, standalone performance, training sets, and ground truth establishment are also not applicable to this specific submission, which focuses solely on labeling updates.

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