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The Fluoroscan InSight is a Mini C-Arm Fluoroscopic Imaging System designed to provide the physicians with general fluoroscopic visualization of a patient, including, but not limited to surgical orthopedic and podiatry use, critical and emergency care procedures, and light anatomy imaging situations.

The Hologic® InSight-FD System, is a portable Mini C-Arm fluoroscopic imaging system with Flat Detector technology used by medical personnel in a variety of diagnostic, surgical and post-operative procedures for imaging extremities, including the hand, wrist, forearm, shoulder, foot, ankle and knee. The hardware enhancements for the InSight-FD System exist primarily within the detector assembly and collimation. The InSight-FD System offers CMOS Flat Detector technology which provides a rectangular viewing area in comparison t the circular view with the conventional image intensifier. For user convenience, additional buttons were added to the X-ray source assembly control panel from the available functions. The software enhancements for the InSight-FD System synchronize the rotation of the X-ray collimator with a manual rotation of +/-90 degrees. The synchronization enables the user to rotate the display image in a rectangular image as compared to the circular view of the image intensifier.

Here's an analysis of the provided text regarding the Hologic® InSight - FD Mini C-Arm Fluoroscopic Imaging System, focusing on the acceptance criteria and the study used to demonstrate conformance:

Summary of Device Performance Study

The provided 510(k) summary describes performance testing for the Hologic® InSight-FD System. The primary goal of the testing was to verify the incorporation and functionality of the flat panel detector technology and to ensure that accompanying software changes did not negatively impact functionality. The study also aimed to demonstrate that the device met its specific acceptance criteria and complied with applicable regulatory performance standards.

1. Table of Acceptance Criteria and Reported Device Performance

Note on Acceptance Criteria: The document does not explicitly state numerical or specific pass/fail acceptance criteria for most of these metrics. Instead, it broadly states that the device "meets specific acceptance criteria," "did not negatively impact functionality," "comparable to the prior system," and "complies with applicable regulatory performance standards." This is common in 510(k) summaries where detailed criteria are typically found in the full submission documents.

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

• Sample Size for Test Set: Not explicitly stated. The text mentions "Pairs of images were acquired" for radiographic and fluoroscopic parameters testing, but the number of pairs or the number of unique test subjects/phantoms is not provided.
• Data Provenance: Not specified. It's unclear if the data was generated in a specific country or if it was retrospective or prospective. Given the nature of a medical device submission, it would almost certainly be prospective testing conducted by the manufacturer.

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

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

4. Adjudication Method for the Test Set

• Adjudication Method: Not mentioned. There's no indication of any multi-reader review or consensus process for image assessment.

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

• Was it done?: No. The document does not describe an MRMC study comparing human reader performance with and without AI assistance. The testing described focuses on the device's technical performance characteristics.
• Effect Size: Not applicable, as no MRMC study was conducted.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance Study

• Was it done?: Yes, conceptually. The performance testing described, particularly for resolution, contrast, uniformity, motion, and compliance with radiation standards, assesses the device's intrinsic characteristics. While a human would naturally operate the system, the evaluation of these parameters focuses on the system's output and adherence to specifications, which is a form of standalone performance. However, this is not an AI-driven "algorithm only" study; it's a hardware/software system performance evaluation.

7. Type of Ground Truth Used

• Type of Ground Truth: The ground truth for this type of device (an imaging system) would primarily be measurement-based and comparative.
  • For radiographic/fluoroscopic parameters (resolution, contrast, uniformity, motion), the ground truth would be established through physical measurements using phantoms and standardized test objects, often compared against a "gold standard" or the performance of the predicate device (the prior image intensified system in this case).
  • For software functionality, the ground truth would be defined by pre-established functional requirements and design specifications.
  • For radiation protection standards, the ground truth is regulatory compliance as defined by 21 CFR 1020.30 and 1020.32.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This document describes the performance testing of an imaging system, not a machine learning or AI model that requires a "training set" in the conventional sense. The "software enhancements" mentioned are likely traditional programming changes, not machine learning algorithms.

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

• How Ground Truth for Training Set Was Established: Not applicable, as there is no apparent training set for an AI model. For the software itself, the "ground truth" for development and verification would be its functional design specifications and requirements.

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