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The STarFix Designer Software is part of the WayPoint Stereotactic System. The WayPoint Stereotactic System is intended to be used with commercially available stereotactic system for neurological procedures which require the accurate positioning of microelectrodes, stimulating electrodes, or other instruments in the brain or nervous system.

FHC, Inc. STarFix™ Designer software is an advanced image-based neurosurgical planning software application designed for generating patient specific frames (FHC, Platform) primarily for Deep Brain Stimulation (DBS) Proedures and stereo-electroencephalography (SEEG) by means of the WayPoint™ Stereotactic platforms.

The STarFix™ Designer offers the following core features:

• Image import and registration
  • Open and manipulate CT and MR images for surgical planning
  • . Rigid registration between CT and MR images, with user-selected reference scan of either modality.
• Automatic localizer extraction
  • Extract localizers from preoperative CT manually or automatically
  • I Manually place localizers on MR scans
  • Manual refinement of localizer position
  • Patient specific 2D and 3D visualization of anatomical landmarks: AC, PC, MP
• Trajectory planning ●
  ●
• DBS STarFix™ Platform frame modeling ●
• . Multi-Oblique STarFix™ Platform frame modeling
• . Export and import planning data, including images, for transfer on another computer or to be saved for easy reference during the surgery
• Save the plan any time during the planning session

The STarFix™ Designer provides a modern design, built to ease user interaction, and allow fast and efficient planning for the WayPoint™ Platforms and ultimately, the implantation of DBS electrodes. With safety as a primary concern, all planning elements need to be verified and marked explicitly before a platform model can be built. The user interface is guiding the necessary planning steps, by using numbered menus and intuitive labeling, along with a minimum of application settings and common actions arranged in the form of a toolbar dedicated to either 2D or 3D operations.

The provided document, a 510(k) Summary for the STarFix Designer Software, describes the acceptance criteria and the study used to demonstrate that the device meets those criteria. However, it specifically states that the performance data for the STarFix Designer Software is documented in verification and validation reports, which are not included in this publicly available 510(k) summary. The summary itself only provides a high-level overview of the testing conducted.

Here's an attempt to extract the requested information based on the provided text, with explicit notes where information is not available from this document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "All major and minor software functions were tested iteratively" and refers to "software regression test protocol... based on the workflow established in the Usability specification of the predicate device." This suggests testing across a range of functionalities and scenarios, but no specific number of test cases or patient datasets used for validation is provided in this summary.
• Data Provenance: Not explicitly stated. For software testing, this would typically involve synthetic data, anonymized real patient data, or a combination. The document doesn't specify the origin or type of data used for testing.

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

• Number of Experts: Not mentioned.
• Qualifications of Experts: Not mentioned.

4. Adjudication Method for the Test Set

• Adjudication Method: Not mentioned. For software regression testing, adjudication is often performed by software quality assurance teams or subject matter experts comparing actual output to expected output. No specific method (e.g., 2+1 consensus) is described.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The performance data presented focuses on software regression testing to demonstrate substantial equivalence to a predicate device, rather than human performance with and without AI assistance.
• Effect Size of Human Readers Improvement with AI vs. without AI assistance: Not applicable, as no such study was performed or reported.

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

• Standalone Performance: The testing described is primarily focused on the standalone software's functionality and adherence to the established workflow of the predicate device. It confirms that "All major areas of software functionality were confirmed for the subject device" and that bug risks are acceptable. While not explicitly termed "standalone performance" in the typical AI/CAD context, the software regression testing inherently evaluates the algorithm's functions independent of real-time human interaction during a clinical procedure, verifying its computational accuracy and reliability in generating plans. However, it's crucial to note this is within the context of surgical planning software, where the output is used by a human, not a diagnostic AI system making a direct independent diagnosis.

7. The Type of Ground Truth Used

• Type of Ground Truth: For the software regression testing, the "ground truth" is largely defined by the "workflow established in the Usability specification of the predicate device" and expected system behavior based on these specifications. This would involve comparing the output of the STarFix Designer Software (e.g., image registration, localizer extraction, trajectory planning, platform modeling) against the expected output or behavior of the predicate device or a golden standard derived from the predicate's known performance. It is a functional and performance ground truth based on prior validated software.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is described as "advanced image-based neurosurgical planning software" that performs functions like "Image import and registration," "Automatic localizer extraction," and "Trajectory planning." It is a rule-based or algorithmic software, not a machine learning/AI model that typically requires a training set. The comparison is to older versions of planning software.

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

• Ground Truth for Training Set Establishment: Not applicable, as there is no mention of a training set for a machine learning model.

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The VFS1 Bipolar Electrosurgical Generator is indicated for use in micro, macro, and endoscopic bipolar irrigation, cutting and coagulating of tissue and the coagulation of blood vessels in all types of surgery.

The VFS1 Bipolar Electrosurgical Generator (referred to as generator or VFS1 Generator) is designed to cut and coagulate living human tissue during surgical procedures. The system provides 1 MHz Radio Frequency (RF) energy that is user/operator selectable based on the surgical procedure undertaken. The generator is configured for bipolar output and is earth isolated, to minimize leakage current, thus providing increased patient comfort and safety. The system will be provided with safety features that are continuously monitored and will provide warnings and/ or alerts when critical parameters exceed specified limits.

The VFS1 Generator is designed to cut and coagulate living tissue during surgical procedures. The system includes a bipedal footswitch. The generator is equipped with a tone generator to provide audible feedback each time cutting, or coagulation is performed. The generator incorporates a variable-rate irrigation pump to provide saline flow during procedures.

The VFS1 Generator is compatible with a variety of reusable bipolar products; i.e., insulated mirror finish bipolar forceps, disposable nonstick bipolar instruments as well as disposable bipolar cords and tubing products.

Items that are included in the system are:

• VFS1 generator -CO 840
• . Footpedal- CO 841

The provided text describes the 510(k) premarket notification for the "VFS1 Bipolar Electrosurgical Generator." This document outlines the device's technical specifications, intended use, and comparison to predicate devices, along with summaries of non-clinical performance testing.

However, the nature of this document (a 510(k) summary for an electrosurgical generator) means that the types of "acceptance criteria" and "study" details requested in your prompt (which relate to AI/Machine Learning models for diagnostic purposes, involving concepts like sample size for test/training sets, expert ground truth, MRMC studies, etc.) are not applicable to this medical device.

Electrosurgical generators are physical devices that perform cutting and coagulation using electrical energy. Their performance is evaluated through engineering tests, electrical safety standards compliance, and bench/ex vivo testing on tissue, rather than the statistical performance metrics used for AI diagnostic tools.

Therefore, I cannot extract the information you've requested about acceptance criteria and studies (as defined by your prompt's context) from this document.

For clarity, here's why each point in your request is not present or applicable:

1. Table of acceptance criteria and reported device performance: The document implicitly states that tests "met specifications" or were "acceptable." There isn't a table comparing a specific performance metric against a quantitative acceptance threshold in the way an AI diagnostic model would have (e.g., "sensitivity > 90%"). Instead, it confirms functional compliance.
2. Sample size for the test set and data provenance: Not applicable. The "test set" here refers to hardware components and ex vivo tissue samples, not patient data for an AI model.
3. Number of experts and their qualifications for ground truth: Not applicable. Ground truth for an electrosurgical device is about its physical effects on tissue, assessed typically by engineers and potentially surgeons, not by interpretation of images/data by multiple experts.
4. Adjudication method for the test set: Not applicable. There's no subjective interpretation requiring adjudication.
5. MRMC comparative effectiveness study: Not applicable. This is for evaluating changes in human reader performance with AI assistance, which is irrelevant for an electrosurgical generator.
6. Stand-alone (algorithm only) performance: Not applicable. This is a hardware device, not a standalone algorithm.
7. Type of ground truth used: Ex vivo testing on tissue samples to demonstrate cutting and coagulation effect. This is a physical outcome, not a diagnostic classification.
8. Sample size for the training set: Not applicable. There is no AI model being trained.
9. How ground truth for the training set was established: Not applicable for the same reason as above.

In summary, the provided document describes a traditional medical device (electrosurgical generator), and the requested information about acceptance criteria and studies are phrased in the context of AI/Machine Learning diagnostic devices. These frameworks are fundamentally different.

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The microTargeting™ Guideline 4000 5.0 System is intended to record and stimulate electrophysiological activity, as well as aid in the accurate placement of electrodes and other instruments.

The microTargeting™ Guideline 4000™ 5.0 System is an electrophysiological recording and stimulation system designed primarily for functional neurosurgery procedures. The system provides high quality and research-grade recordings on both microelectrodes and macroelectrodes, including low-frequency signals on externalized DBS leads, improved signal quality, decreased noise susceptibility, improved user experience with redesigned software, new intraoperative data analysis options, and an updated user interface to support touch screens and multiple high-resolution monitors. Additionally, it provides simultaneous constant-current and constant-voltage stimulation capabilities that include multiple weighted sources and return paths as well as complex and arbitrary stimulation waveforms. The software provides an intuitive patient management system, as well as advanced visualization and analysis methods for both single-unit recording and low-frequency signals (LFP, SEEG etc.). A fully configured system consists of a Core Module, a notebook PC, an 8-channel UE interface unit, a remote, an optional second 8-channel LF interface and an optional synchronization unit.

The provided document is a 510(k) Premarket Notification for the "microTargeting™ Guideline 4000 5.0 System." This document focuses on demonstrating substantial equivalence to a predicate device, as required for certain medical devices by the FDA. It does not include the information typically found in a study proving a device meets acceptance criteria for an AI/ML-driven diagnostic or assistive device (e.g., performance metrics like sensitivity, specificity, AUC, human-in-the-loop studies, ground truth establishment, or sample sizes for deep learning models).

The document is for an electrophysiological recording and stimulation system for neurosurgical procedures, not an AI/ML-driven device or an imaging diagnostic device. Therefore, the details requested (e.g., acceptance criteria for AI diagnostic performance, sample size for test sets, number of experts for ground truth, MRMC studies) are not applicable to the content of this specific submission.

The "acceptance criteria" discussed in the document are related to electrical safety, mechanical integrity, macro/micro stimulation accuracy, and software regression testing for an electrophysiological device, comparing its performance to that of a previous version of the device (the predicate device).

However, I will extract and present the information available that is conceptually similar to what your questions are asking for, but with the understanding that it pertains to a different type of device and different evaluation methodology than what your questions imply.

Here's an attempt to answer your questions based on the provided text, while making it clear where the information is not relevant or not present due to the nature of the device and submission:

Device: microTargeting™ Guideline 4000™ 5.0 System
Intended Use: To record and stimulate electrophysiological activity, as well as aid in the accurate placement of electrodes and other instruments during functional neurosurgical procedures.

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

The document describes nonclinical performance data for the device, and the "acceptance criteria" are implied by the "Results" section for each test, indicating that the device "met the acceptance criteria."

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

• Sample Size: Not specified in terms of "test set" samples (e.g., patient cases) as this is not a diagnostic AI/ML device. The tests described are device-level verification and validation (e.g., electrical safety, mechanical, stimulation accuracy) conducted on the physical device and its software. The number of units tested is not stated but standard V&V would involve a representative sample of manufactured units.
• Data Provenance: Not applicable in the context of patient data sets. The testing is based on internal protocols, external third-party testing (for electrical safety and mechanical strength), and comparison to a legally marketed predicate device (FHC, Inc.'s microTargeting™ Guideline 4000).

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

• Not Applicable. This is not a device that relies on expert interpretation of data (e.g., images, waveforms) to establish a "ground truth" for diagnostic accuracy in the way an AI/ML-driven device would. The "ground truth" for this device's performance is objectively measured against established engineering and safety standards (e.g., IEC 60601) and specifications for electrical outputs.

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

• Not Applicable. As there are no human interpretations of patient data involved in establishing "ground truth" for the tests described, no adjudication method is relevant.

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. This device is an electrophysiological recording and stimulation system, not an AI-assisted diagnostic tool. Therefore, MRMC studies involving human readers are not applicable to its evaluation.

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

• Not Applicable / Interpreted Differently. While the device itself operates "stand-alone" in its core functions (e.g., generating stimuli, recording signals), there is no 'algorithm-only' performance test in the diagnostic sense. The software functions were tested through "Software regression testing," which assesses the functionality and correctness of the software components. The device is intended for use by a neurosurgeon, neurologist, or clinical neurophysiologist, meaning there is always a human-in-the-loop controlling its operation and interpreting its outputs in a clinical context.

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

• The "ground truth" for evaluating this device's performance would be the expected engineering specifications and international safety standards. For example:
  • For electrical safety: Compliance with IEC 60601-1.
  • For mechanical integrity: Compliance with IEC 60601-1.
  • For stimulation accuracy: Output frequency, pulse duration, and amplitude within ±10% of the user interface set point, as measured by calibrated equipment (NIST traceable oscilloscope).
  • For software: Functionality confirmed against use-case specifications and risk assessment ensuring no unacceptable risks.

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML device that requires a "training set" of data for learning.

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

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

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The FHC microTargeting™ XL STar™ Drive System is intended to be used with commercially available stereotactic systems for neurosurgical procedures which require the accurate positioning of microelectrodes, stimulating electrodes, or other instruments in the brain or nervous system.

When used in conjunction with commonly available stereotactic systems, the microTargeting "M XL STar™ Drive System allows a neurosurgeon to precisely position intracranial microelectrodes, stimulating electrodes, lesion electrodes and other instruments during functional neurosurgical procedures.

microTargeting™ XL STar™ Drive System Components

• microTargeting™ XL STarTM Drive .
• insertion tubes
• verification probe ●
• sterilization case ●
• cleaning brushes .

Device Mounting Hardware and other Components
Additional components for device mounting include hardware specifically designed to interface between the microTargeting™ XL STar™ Drive system and other stereotactic frames or instruments, and also include optional components to increase utility.

• Adapters to fit Radionics and Leksell stereotactic systems .
• microTargeting controller firmware based on user specifications of drive travel.

This document is a 510(k) summary for the FHC microTargeting™ XL STar™ Drive System, a medical device. The purpose of this summary is to demonstrate substantial equivalence to a predicate device, not to present a comprehensive study proving the device meets specific acceptance criteria in the context of a typical AI/software performance study.

Therefore, many of the requested items (e.g., sample sizes for test/training sets, data provenance, expert ground truth, MRMC studies, standalone performance, specific acceptance criteria for a clinical study) are not applicable or not provided in this type of regulatory submission. The submission focuses on comparing the new device's technological characteristics and performance to a legally marketed predicate device to establish substantial equivalence.

Based on the provided text, here's what can be extracted and what cannot:

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

The document does not explicitly present a "table of acceptance criteria" in the format typically seen for algorithm performance studies with numerical metrics like sensitivity, specificity, or accuracy. Instead, it uses a "Comparison Table" to demonstrate substantial equivalence based on technological characteristics and states that performance testing documented in verification phases shows "equivalence or improvement" over the predicate.

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

This information is not provided in the document. As a 510(k) for a hardware device, the "performance testing" refers to engineering and design verification/validation directly on the device, not clinical data or patient data.

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

This information is not provided and is not applicable to this type of device submission. There is no clinical "ground truth" to establish in the context of this 510(k) summary, as it describes a mechanical stereotaxic instrument.

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

This information is not provided and is not applicable.

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

An MRMC study was not done and is not applicable. This is not an AI-assisted device for diagnostic interpretation.

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

This is not applicable. This is a hardware device, not an algorithm.

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

This is not applicable. The "performance testing" for this device likely involved engineering measurements and tests (e.g., measuring travel distance, repeatability, accuracy of positioning) against design specifications, rather than clinical ground truth from patient data.

8. The sample size for the training set

This is not applicable. This is a hardware device; there is no "training set" in the machine learning sense.

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

This is not applicable.

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The WayPoint™ Stercotactic System is intended to be used with commercially available stereotactic systems for neurosurgical procedures which require the accurate positioning of microclectrodes, stimulating electrodes, or other instruments in the brain or nervous system.

The WayPoint™ Stereotactic System. (WPS System) accurately locates and rigidly supports neurosurgical or other surgical instruments relative to specific anatomical structures or targets, thus facilitating microelectrode recording, stimulation, data collection, device implantation and other surgical procedures. The WPS System provides patient-customized stereotactic fixtures designed to be secured on skull-based anchor mounting sets to hold and align surgical instruments with patient anatomy and to allow selected targets to be reached with sub-millimeter accuracy. The WPS System consists of several components that work together to become a stereotactic system. These components are:

• 1. the WayPoint™ Stereotactic Anchor System:
• 2. the WayPoint™ Stereotactic Platform Adapter:
• 3. Device mounting hardware for the Platform; and,
• 4. WayPoint™ compatible Planning software such as:
• a. WayPoint™ Planner; or,
• b. VoXim®Planning software.
  The WayPoint™ Stereotactic Anchor/Locator System provides tools and components for the temporary implantation of anchors to be used as reference points and mounting sets for the surgical procedure. The WPS System software designs a Stereotactic Platform Adapter that will mount to the WayPoint™ Stereotactic Anchor System. For each surgical instrument or device to be mounted to the Stereotactic Platform Adapter, suitable hardware is provided to act as a secure interface and allow flexibility in targeting, if required. The two existing software components of the WPS System (WayPoint™ Planner and VoXim® microTargeting™ Planning software) provide tools to create a Stereotactic Platform Adapter from scanned patient images.

The provided document describes the WayPoint™ Stereotactic System and references performance data to support its substantial equivalence claim. However, it does not explicitly state acceptance criteria or provide a detailed study report that includes all the requested information for acceptance criteria and device performance in a structured format.

The document summarizes performance data rather than presenting it in detail.

Here's an attempt to extract the relevant information based only on the provided text, while also highlighting what is not available:

1. Table of Acceptance Criteria and Reported Device Performance

Missing from the table: Specific numerical acceptance criteria (e.g., "Accuracy must be within 0.5 mm") are not provided. The reported performance is qualitative ("submillimetric," "comparable").

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

• Sample Size (Test Set): Not specified. The document states "phantom- and imaging-based studies were conducted," but does not give the number of phantoms, images, or cases used in these studies.
• Data Provenance (Country of Origin, Retrospective/Prospective): Not specified.
  • The 510(k) submission is from FHC, Inc. in Bowdoin, Maine, USA.
  • It is not stated whether the studies were prospective or retrospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified.

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

• MRMC Study: Not explicitly stated or described. The document mentions "accuracies comparable to those of conventional frames" and "error measurements were comparable to those for the same procedure as described by other groups using a standard stereotactic frame," which implies a comparison, but it does not detail a formal MRMC study design comparing human readers with and without AI assistance to determine an "effect size." The device itself is a stereotactic system, not an AI for human reader assistance in diagnostic tasks.

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

• Standalone Performance: The description of the phantom-based study ("Stereotactic Platform Adapter produced by the WPS System is accurate to a submillimetric level") can be interpreted as a standalone performance assessment of the system's physical and software-driven accuracy in a controlled environment. The "imaging-based studies" comparing coordinates and error measurements also relate to the system's standalone performance in achieving target accuracy.

7. Type of Ground Truth Used

• For Phantom-based study: Likely the known physical dimensions and target locations of the phantom, measured with a high-precision reference system. This would be known physical truth.
• For Imaging-based studies:
  • Comparison of "intraoperative stereotactic coordinates of an implant to its position in postoperative CT images" suggests comparing the device's predicted/achieved coordinates with the actual, visible position on a postoperative imaging modality (CT), which serves as the ground truth for actual placement.
  • Comparison of "preoperative target selection and final placement verification based on CT images" also implies using CT images as the basis for both planning and verifying outcomes.

8. Sample Size for the Training Set

• Training Set Sample Size: Not specified. The document describes the system's performance but does not provide details on the development or training of any software components within the WPS System, nor does it refer to separate "training" and "test" sets in the context of machine learning model development. This device predates widespread explicit mention of training sets for AI in 510(k) summaries.

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

• Ground Truth for Training Set: Not specified, as training set details are absent.

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The FHC microTargeting™ STar Drive™ System is intended to be used with commercially available positioning systems for neurosurgical procedures which require the accurate positioning of microelectrodes, stimulating electrodes, or other instruments in the brain or nervous system.

When used in conjunction with commonly available stereotactic systems, the microTargeting™ STar Drive™ System allows a neurosurgeon to precisely position intracranial microelectrodes, stimulating electrodes, lesion electrodes and other instruments during functional neurosurgical procedures.

microTargeting™ STar Drive™ System Components

• microTargeting™ STar Drive™ .
• optional lower guide .
• lead holder with lead /lesion stop .
• . verification probe
• sterilization case .
• cleaning brushes

Device Mounting Hardware and other Components
Additional components for device mounting include hardware specifically designed to interface between the microTargeting TM STar Drive™ system and other stereotactic frames or instruments, and also include optional components to increase utility.

• Adapters to fit Radionics, Leksell, Leibinger RM, Leibinger ZD. . FHC MicroTargeting™ Platform and Medtronic-IGN NeXframe stereotactic systems
• ♥ single electrode insertion tube set
• . array electrode insertion tube set
• . lesion insertion kit and depth stops
• . custom microelectrode depth stops

The provided document, K092562, is a Special 510(k) Summary for the FHC microTargeting™ STar Drive™ System. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than presenting extensive de novo performance studies with detailed acceptance criteria and standalone algorithm performance.

Here's an analysis based on the provided text, addressing your questions to the best of its ability:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not provide specific, quantifiable acceptance criteria or a dedicated table for device performance in the way a de novo device might. Instead, it relies on demonstrating equivalence to a predicate device and states that performance testing documented in "verification and validation phases of design control" shows the device is "equivalent or improved" over the predicate.

The table in the document is a "Comparison Table" highlighting technological characteristics similarities, not acceptance criteria for performance.

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

The document does not specify a "test set" in the context of clinical or performance data for the purpose of establishing a new device's efficacy through primary studies. This is a 510(k) submission, specifically a Special 510(k), which streamlines the process for certain device modifications. The focus is on demonstrating equivalence to the predicate device (FHC microTargeting™ Drive System K003776).

The "Performance testing" mentioned refers to "verification and validation phases of design control" which would typically involve engineering tests, bench tests, and possibly simulated use, rather than a clinical human test set. Therefore, there is no mention of country of origin or whether data was retrospective or prospective in detail.

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

Not applicable. This type of submission for a mechanical stereotaxic instrument does not involve establishing ground truth through expert consensus on medical images or diagnoses, as would be the case for an AI/algorithm-based diagnostic device. The performance evaluation is based on engineering principles and comparison to a predicate.

4. Adjudication Method for the Test Set

Not applicable. As there is no "test set" in the sense of clinical cases requiring expert adjudication, no adjudication method is described.

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

Not applicable. The device is a mechanical stereotaxic instrument, not an AI or imaging diagnostic algorithm. Therefore, an MRMC study related to interpretation or AI assistance is not relevant to this submission.

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

Not applicable. The device is a mechanical system and does not involve a standalone algorithm.

7. The Type of Ground Truth Used

The "ground truth" for this device would be established through engineering specifications, measurements, and validation against known standards for mechanical accuracy, repeatability, and rigidity. For example, accuracy could be validated against a known target in a phantom. The document implies that such testing was performed during design control ("verification and validation phases"), but it does not detail the specific methodology or "ground truth" used for each aspect (e.g., "accuracy").

8. The Sample Size for the Training Set

Not applicable. This device is a mechanical instrument and does not involve a "training set" for an algorithm.

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

Not applicable. As there is no training set for an algorithm, the concept of establishing its ground truth is not relevant to this submission.

Summary of the K092562 document regarding acceptance criteria and studies:

The document primarily demonstrates substantial equivalence to an existing predicate device (K003776) by showing that the new device has the same intended use and similar technological characteristics, materials, and performance. The performance section broadly states that internal "verification and validation phases of design control" showed the device to be "equivalent or improved" in several mechanical and usability aspects (ease of manufacturing, mechanical and electrical quietness, ease of use, repeatability, accuracy, rigidity, and adaptability).

However, it does not provide:

• Specific, quantifiable acceptance criteria.
• Detailed reports of specific performance studies (e.g., a clinical trial, a detailed bench study with a specified number of samples).
• Any information regarding human-in-the-loop studies, multi-reader studies, AI performance, or data provenance in the context of clinical evaluation.

This is typical for a 510(k) submission for a non-AI, mechanical device that is substantially equivalent to a predicate, where the focus is on engineering verification/validation and comparison rather than new clinical efficacy trials or AI performance metrics.

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The microTargeting® Guideline 4000 system is intended to assist in functional neurosurgical procedures where recording from and stimulation of brain motor and sensory neurons will aid in the placement of depth electrodes.

The microTargeting® Guideline 4000 is designed for intraoperative electrophysiological microelectrode recording, stimulation, data collection, analysis and storage.

The provided document (K071364 FHC 510(k) Summary) describes a medical device, the microTargeting® Guideline System 4000, and its substantial equivalence to predicate devices, but it does not contain a study that proves the device meets specific acceptance criteria in the format requested.

This 510(k) summary is a premarket notification to the FDA, asserting that the new device is as safe and effective as a legally marketed predicate device. The primary method of demonstrating this is through comparison of technological characteristics and intended use, rather than a clinical trial with acceptance criteria and statistical performance measures.

Here's why and what information is available:

1. Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: The document does not explicitly list quantitative acceptance criteria (e.g., target sensitivity, specificity, or accuracy thresholds).
• Reported Device Performance: Instead of performance metrics, the document states:
  • "Specifications in every category are either the same, very similar, or improved [compared to predicate devices]."
  • "Non-clinical review of the device shows the device meets similar performance specifications as the predicate devices."

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

• Not applicable. No clinical test set data or study is described in this 510(k) summary. The demonstration of substantial equivalence relies on non-clinical engineering and design comparisons.

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

• Not applicable. No clinical test set.

4. Adjudication Method for the Test Set:

• Not applicable. No clinical test set.

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

• No. An MRMC study was not described. The document does not mention human reader performance or AI assistance.

6. Standalone Performance Study (Algorithm Only):

• Not applicable. This device is an intraoperative neurophysiological recording and stimulating device, not an AI algorithm. Standalone performance for an algorithm is not relevant here.

7. Type of Ground Truth Used:

• Not applicable. No clinical test data requiring a ground truth determination is presented. The "ground truth" for this 510(k) is the established safety and effectiveness of the predicate devices.

8. Sample Size for the Training Set:

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

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

• Not applicable.

Summary of what the document does provide regarding "proof" of meeting criteria:

The "proof" in this 510(k) summary is the assertion of "Substantial Equivalence" to legally marketed predicate devices. This means the FDA has determined that the microTargeting® Guideline System 4000 is as safe and effective as the predicate devices (Axon Instruments, Inc. Guideline System 3000 K970943; Alpha Omega Neurotrek Physiological Navigation System K993622).

The criteria for this substantial equivalence are outlined as:

• Similar design, construction, materials, intended use, and performance characteristics.
• No new technology, materials, or manufacturing methods introduced.
• Specifications are "the same, very similar, or improved."
• No new issues of safety or effectiveness are introduced.

The "study" or evidence for this is a "Non-clinical review of the device," which presumably involves engineering tests, bench testing, and comparison of technical specifications against the predicate devices. The document does not elaborate on the specific details of this non-clinical review or present quantitative results from it, as is typical for a 510(k) summary. The full 510(k) submission would contain more detailed information.

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The FHC microTargeting® Electrodes are intended for use in intra-operative recording of single unit neuronal activity or intra-operative stimulation of neural elements in the brain.

The FHC microTargeting® Electrode is for intra-operative single unit recording and stimulation during functional neurosurgery.

This document (K033173) is a 510(k) summary for a medical device called the microTargeting® Electrode. It's a premarket notification to the FDA to demonstrate substantial equivalence to legally marketed predicate devices, not a study proving the device meets specific acceptance criteria as you'd find in clinical trials for complex AI/machine learning devices.

Therefore, many of the requested categories (such as acceptance criteria, reported performance, sample size for test set, expert qualifications, adjudication method, MRMC study, standalone performance, ground truth types, training set size, and ground truth establishment for training set) are not applicable in this context.

This document describes a traditional medical device (an electrode) seeking clearance based on technological characteristics and intended use similar to existing products, rather than a device with an algorithm that requires performance metrics against a defined ground truth.

Here's what can be extracted from the provided text based on your request, with the understanding that the nature of the device and submission type means many fields will be "N/A":

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)

• N/A: This 510(k) submission does not present data from a clinical test set in the way an AI/ML device would. It relies on demonstrating substantial equivalence to predicate devices based on design, materials, manufacturing, and intended use, rather than specific performance metrics from a clinical study.

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)

• N/A: No ground truth establishment by experts for a test set is described or required for this type of 510(k) submission for a non-AI/ML device.

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

• N/A: No adjudication method is described as there is no test set for performance evaluation in this context.

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

• N/A: This is not an AI-assisted device. No MRMC study was performed.

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

• N/A: This is not an algorithm-based device. No standalone performance study was performed.

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

• N/A: No explicit "ground truth" as a reference standard for performance evaluation is mentioned or required for this device. The regulatory submission focuses on substantial equivalence to existing devices.

8. The sample size for the training set

• N/A: The device is a physical electrode. There is no concept of a "training set" as would be used for an AI/ML algorithm.

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

• N/A: As there is no training set, this is not applicable.

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The FHC microTargeting® Drive System is intended to be used with commercially available stereotactic systems for neurosurgical procedures which require the accurate positioning of microelectrodes, stimulating electrodes, DBS™ electrodes or other instruments in the brain or nervous system.

The microTargeting® Drive System with maTrix drive mount permits the accurate positioning of microelectrodes, stimulating electrodes, DBS electrodes, lesion positioning on thereficeroded, climataling aerous in the brain and nervous system and is adaptable to all major stereotactic systems.

microTargeting™ Drive System Components

• microTargeting™ drive
• maTrix™ drive mount and lower guide
• maTrix™ guide bushings
• DBS™ holder with DBS/lesion stop
• verification probe
• sterilization case
• cleaning brushes
• hex wrench

microTargeting™ Drive System Accessories

• Radionics adaptor
• Leksell adaptor
• BrainLab adaptor
• Leibinger RM adaptor
• Leibinger ZD adaptor
• Leibinger Ost-Reg™ (STarFix™) adaptor
• NeuroMate™ adaptor
• single electrode insertion tube set
• array electrode insertion tube set
• lesion insertion tube kit and depth stops
• custom microelectrode depth stops

I am sorry, but the provided text does not contain the information needed to answer the question about acceptance criteria and study details for the microTargeting® Drive System. The document is primarily a 510(k) summary for regulatory clearance, focusing on general device information, legal marketing, description, intended use, and substantial equivalence to predicate devices. It does not include specific performance data, study designs, or acceptance criteria.

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The FHC microTargeting® Drive System is intended to be used with commercially available stereotactic systems for neurosurgical procedures which require the accurate positioning of microelectrodes, stimulation electrodes, or other instruments in the brain or nervous system.

The microTargeting® Drive System with permits the accurate positioning of microelectrodes, stimulation electrodes, lesion electrodes, biopsy probes and other instruments in the brain and nervous system and is adaptable to all major stereotactic systems. The current microTargeting® Drive System allows the user to add position display capability or add power assist and position display capabilities.

This 510(k) summary (K011992) for the FHC microTargeting® Drive System describes a device for accurate positioning of instruments in neurosurgical procedures. However, it does not contain the level of detail regarding acceptance criteria or a specific study proving the device meets those criteria, as requested in the prompt.

Therefore, I cannot provide quantitative information for most of your questions. The document focuses on demonstrating substantial equivalence to a legally marketed predicate device (K003776), rather than presenting a performance study with detailed acceptance criteria and results.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Cannot be provided. The document does not specify quantitative acceptance criteria (e.g., accuracy thresholds, precision ranges) or present a table of reported device performance against such criteria. The substantial equivalence argument relies on the previous device's established performance without detailing it here.

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

• Cannot be provided. The document does not describe a "test set" in the context of device performance evaluation. It refers to "differences that exist between these devices, relating to technical specifications, physical appearance, and design," but does not mention specific testing data, sample sizes, or data provenance.

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)

• Cannot be provided. There is no mention of a "test set" requiring ground truth establishment by experts in this document.

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

• Cannot be provided. Not applicable as no test set or expert ground truth establishment is described.

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

• Cannot be provided. This device is a mechanical stereotactic drive system, not an AI-assisted diagnostic or therapeutic tool for human readers. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant or described.

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

• Cannot be provided. This is a mechanical device, not an algorithm. Standalone performance as typically understood for AI algorithms is not applicable.

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

• Cannot be provided. No ground truth establishment is described in the context of device performance.

8. The sample size for the training set

• Cannot be provided. No training set is mentioned as this is a mechanical device, not a machine learning algorithm.

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

• Cannot be provided. Not applicable as no training set or ground truth for it is mentioned.

Summary of available information related to the prompt:

• Device Name: microTargeting® Drive System
• Predicate Device: FHC, Inc microTargeting® Drive System (K003776), cleared Feb. 23, 2001.
• Demonstration of Effectiveness: The summary asserts that the device is "substantially equivalent" to its predicate. The phrase "Differences that exist between these devices, relating to technical specifications, physical appearance, and design do not affect the relative safety and effectiveness of the microTargeting® Drive System" implies that the company believes any changes do not negatively impact the device's performance, but no new studies are cited to prove this in a quantitative manner within this document. The effectiveness is assumed to be similar to the predicate based on technical and design comparisons, not new performance data.

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