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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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