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The software displays medical images and data. It also includes functions for image review, image manipulation, basic measurements and 3D visualization.

Device Description

Viewer is a software for viewing DICOM data, such as native slices generated with medical imaging devices, axial, coronal and sagittal reconstructions, and data specific volume rendered views (e.g., skin, vessels, bone). Viewer supports basic manipulation such as windowing, reconstructions or alignment and it provides basic measurement functionality for distances and angles. Viewer is not intended for diagnosis nor for treatment planning. The Subject Device (Viewer) for which we are seeking clearance consists of the following software modules.

· Viewer 5.4 (General Viewing)
· Universal Atlas Performer 6.0
Universal Atlas Transfer Performer 6.0
Universal Atlas Performer: Software for analyzing and processing medical image data with Universal Atlas to create different output results for further use by Brainlab applications
Universal Atlas Transfer Performer: Software that provides medical image data autoseqmentation information to Brainlab applications
When installed on a server, Viewer can be used on mobile devices like tablets. No specific application or user interface is provided for mobile devices. In mixed reality, the data and the views are selected and opened via desktop PC. The views are then rendered on the connected stereoscopic head-mounted display. Multiple users in the same room can connect to the Viewer session and view/review the data (such as already saved surgical plans) on their mixed reality glasses.

AI/ML Overview

The Brainlab AG Viewer (5.4) and associated products (Elements Viewer, Mixed Reality Viewer, Smart Layout, Elements Viewer Smart Layout) are a medical image management and processing system. The device displays medical images and data, and includes functions for image review, manipulation, basic measurements, and 3D visualization.

Here's an analysis of the acceptance criteria and supporting studies based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text details various tests performed to ensure the device's performance, particularly focusing on the mixed reality aspects and measurement accuracy. However, specific numerical "acceptance criteria" (e.g., "accuracy must be >95%") and corresponding reported performance values are not explicitly stated in a detailed quantitative manner in the summary. Instead, the document describes the types of tests conducted and generally states that they were successful or ensured certain qualities.

Test Category	Acceptance Criteria (Implied/General)	Reported Device Performance (General)
Software Verification & Validation	Successful implementation of product specifications, incremental testing for different release candidates, testing of risk control measures, compatibility testing, cybersecurity tests.	Documentation provided as recommended by FDA guidance. Successful implementation, testing of risk controls, compatibility, and cybersecurity acknowledged for an enhanced level.
Ambient Light	Sufficient visualization in a variety of ambient lighting conditions with Magic Leap 2.	Test conducted to determine Magic Leap 2 display quality for sufficient visualization in a variety of ambient lighting conditions. (Implied successful)
Hospital Environment	Compatibility with various hardware platforms and compatible software.	Test conducted to test compatibility of the Subject Device with various hardware platforms and compatible software. (Implied successful)
Display Quality	Seamless integration of real and virtual content; maintenance of high visibility and image quality (optical transmittance, luminance non-uniformity, Michelson contrast).	Tests carried out to measure and compare optical transmittance, luminance non-uniformity, and Michelson contrast of the head-mounted display to ensure seamless integration of real and virtual content and maintenance of high visibility and image quality, both with and without segmented dimming. (Implied successful)
Measurement Accuracy	Accurate 3D measurement placement using Mixed Reality user interface (Magic Leap control), comparable to mouse and touch input.	Tests performed to evaluate the accuracy of 3D measurement placement using a Mixed Reality user interface (Magic Leap control) in relation to mouse and touch as input methods. (Implied successful, and supports equivalence to predicate's measurement capabilities, with added 3D functionality in MR)

2. Sample Size for the Test Set and Data Provenance

The document does not explicitly state the sample sizes used for any of the described tests (Ambient Light, Hospital Environment, Display Quality, Measurement Accuracy).

Regarding data provenance, the document does not specify the country of origin for any data, nor whether the data used in testing was retrospective or prospective.

3. Number of Experts and Qualifications for Ground Truth

The document does not provide information on the number of experts used to establish ground truth for any of the described tests, nor their qualifications.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) used for the test set.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The study is focused on the device's technical performance and accuracy, not on human reader improvement with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

The document describes the "Viewer" as software for displaying and manipulating medical images. While it's a software-only device, the tests described (e.g., display quality, measurement accuracy) inherently assess the algorithm's performance in its intended functions without direct human-in-the-loop impact on the results being measured during those specific tests. However, it's not explicitly framed as an "algorithm-only" performance study in contrast to human performance, but rather as instrumental performance validation. The Mixed Reality functionality, while requiring a human operator, still has its underlying software/hardware performance (e.g., accuracy of 3D measurement placement) evaluated.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for any of the tests. For "Measurement accuracy test," it can be inferred that a known, precisely measured physical or digital standard would have been used as ground truth for comparison. For other tests like display quality or compatibility, the ground truth would be conformance to established technical specifications or standards for optical properties and functional compatibility, respectively.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This is consistent with the device being primarily a viewing, manipulation, and measurement tool rather than an AI/ML diagnostic algorithm that requires a "training set" in the conventional sense. The "Universal Atlas Performer" and "Universal Atlas Transfer Performer" modules do involve "analyzing and processing medical image data with Universal Atlas to create different output results" and "provides medical image data autosegmentation information," which might imply some form of algorithmic learning or rule-based processing. However, no details on training sets for these specific components are included.

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

As no training set is mentioned or detailed, there is no information on how its ground truth might have been established.

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