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The Digital Lightbox is a system intended for the display of medical images. The software can transfer images to and from picture archiving and communication systems (PACS), file servers, or removable storage media. It includes functions for image manipulation, basic measurements and 3D visualization (reconstructions and volume rendering). Features for navigation planning include multi-modality image fusion as well as object and trajectory creation. It is not intended for primary image diagnosis or the review of mammographic images.

Digital Lightbox is a medical image viewing device consisting of two high-resolution monitors controlled through touch panels with an integrated PC. It features an Ethernet connection for retrieving medical images through a computer network. Further, the device can read images from CD, DVD or USB drives through external interfaces. The device software is compatible with the DICOM standard and allows basic image manipulation, 3D visualization (reconstructions and volume rendering), basic measurements, multi-modality image fusion and object and trajectory creation. Basic treatment plans can be exported to BrainLAB navigation systems. The device software integrates a web browser and remote access software.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the Digital Lightbox, structured as requested.

It's important to note that the provided text is a 510(k) summary and FDA clearance letter, which focuses on demonstrating substantial equivalence to predicate devices rather than detailing comprehensive performance studies with acceptance criteria. Therefore, some of the requested information (like specific acceptance criteria values, a detailed description of the study design including sample sizes for a test set, number and qualifications of experts for ground truth, adjudication methods, MRMC studies, or standalone performance metrics) is not explicitly present in this type of document. The document primarily attests to verification and validation activities performed according to the manufacturer's procedures.

Acceptance Criteria and Device Performance for Digital Lightbox (K093117)

1. Table of Acceptance Criteria and Reported Device Performance

As noted above, specific numerical acceptance criteria (e.g., minimum accuracy, sensitivity, specificity) and corresponding quantitative performance metrics for the Digital Lightbox are not detailed in this 510(k) summary. The document states that the device was verified and validated according to BrainLAB procedures for product design and development, and that the validation proves the safety and effectiveness of the system.

The primary "performance" reported is that the device is substantially equivalent to its predicate devices for its intended use, particularly for the new functionalities of 3D visualization and basic surgical planning.

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

The 510(k) summary does not specify a sample size for a "test set" in the context of comparative performance metrics (e.g., for accuracy or error rates). The validation mentioned is more likely related to internal testing against functional specifications and equivalence to predicate devices rather than a ground-truth-driven performance study with a defined test set.

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified. It's internal validation data, likely from BrainLAB's own testing procedures, but no details on country of origin or retrospective/prospective nature are provided.

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

This information is not provided in the 510(k) summary. The document does not describe a study involving expert-established ground truth for performance evaluation in the typical sense of diagnostic accuracy studies.

4. Adjudication Method for the Test Set

This information is not provided. As no expert-established ground truth study is detailed, an adjudication method is not described.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not described or indicated in the provided 510(k) summary. The focus is on demonstrating substantial equivalence based on technical characteristics and intended use, not on quantifying the improvement of human readers with or without AI assistance.

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

The Digital Lightbox is described as a medical image viewing device with image manipulation and visualization features, including "navigation planning." It is not directly analogous to a standalone AI algorithm providing a diagnostic output. While the software processes images and creates 3D models/trajectories, its performance isn't typically measured in terms of standalone diagnostic accuracy. The term "standalone performance" as commonly applied to AI algorithms in diagnostic imaging is not applicable or addressed in this document for the described device.

7. The Type of Ground Truth Used

The concept of "ground truth" (e.g., pathology, outcomes data) in the context of diagnostic accuracy is not explicitly mentioned or used in this 510(k) summary for evaluating the Digital Lightbox's performance. The validation relies on functional testing and demonstrating equivalence of features to predicate devices.

8. The Sample Size for the Training Set

The document does not refer to a "training set" as the Digital Lightbox is a software device for image viewing and manipulation, not an AI or machine learning model that would typically undergo a training phase.

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

Since the device is not described as an AI/ML model with a training phase, the concept of "ground truth for the training set" is not applicable to the information provided.

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The Digital Lightbox is a system intended for the retrieval and display of medical images from picture archiving and communication systems (PACS), file servers, or removable storage media. It includes functions for image manipulation, 3D reconstruction, basic measurements, and multi-modality image fusion. It is not intended for primary image diagnosis or the review of mammographic images.

Digital Lightbox is a medical image viewing device consisting of two high-resolution monitors controlled through touch panels with an integrated PC. It features an Ethernet connection for retrieving medical images through a computer network. Further, the device can read images from CD, DVD or USB drives through external interfaces. The device software is compatible with the DICOM standard and allows basic image manipulation, 3D reconstruction, basic measurements and multi-modality image fusion. The device software integrates a web browser and remote access software.

The provided text is a 510(k) summary for the Digital Lightbox. This document typically focuses on demonstrating substantial equivalence to predicate devices rather than presenting detailed clinical study results and acceptance criteria in the format requested for a medical AI device.

Given that the Digital Lightbox is described as a "medical image viewing device" and "not intended for primary image diagnosis," it is highly unlikely to involve acceptance criteria related to diagnostic accuracy (sensitivity, specificity, etc.) or comparative effectiveness studies with human readers assisted by AI. Its validation would primarily address functional performance, safety, and effectiveness as an image display and manipulation tool.

Therefore, the specific information requested in points 1-9 regarding diagnostic performance, sample sizes for test/training sets, expert ground truth, and MRMC studies is not available or applicable in the provided 510(k) summary for the Digital Lightbox.

However, I can extract information related to the device's validation and substantial equivalence claims:

Acceptance Criteria and Study for Digital Lightbox (Based on 510(k) Summary K080608)

While specific acceptance criteria in terms of diagnostic performance metrics (e.g., sensitivity, specificity, AUC) and detailed study designs (e.g., sample sizes, expert qualifications for ground truth) are not provided in this 510(k) summary, the document does state the general validation approach. The Digital Lightbox is a medical image viewing device, not an AI diagnostic algorithm, so its validation focuses on functional performance, safety, and equivalence to existing display systems.

1. Table of Acceptance Criteria and Reported Device Performance

• No specific quantitative acceptance criteria or reported device performance metrics (e.g., sensitivity, specificity, or image quality scores) related to diagnostic accuracy are provided or expected for this type of device.
• The document implies that the device met functional and safety criteria as part of BrainLAB's internal validation processes and demonstrated substantial equivalence to predicate devices.

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

• Not applicable/Not provided. This device is for image display and manipulation, not for diagnostic interpretation requiring a "test set" of patient data in the typical sense for AI diagnostic algorithms. Its validation would involve functional testing with various image types and formats, but not a "test set" with ground truth in the way a diagnostic algorithm would.

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

• Not applicable/Not provided. As stated above, this is not a diagnostic AI device requiring expert-established ground truth for a diagnostic test set.

4. Adjudication Method for the Test Set

• Not applicable/Not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of human readers improving with AI vs. without AI assistance

• No. This device is a display and manipulation tool, not an AI assistance system for human readers. Therefore, an MRMC study comparing human readers with and without "AI assistance" (from this device) is not relevant or reported.

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

• Not applicable. The Digital Lightbox is an interactive viewing device; its function inherently involves a human user. There is no "algorithm only" diagnostic performance to evaluate.

7. The type of ground truth used

• Not applicable. For a medical image viewing device, "ground truth" as pathology or outcome data is not relevant to its primary function. Its performance would be assessed against expected display fidelity, measurement accuracy, and functionality.

8. The Sample Size for the Training Set

• Not applicable/Not provided. As this is not an AI algorithm trained on patient data for diagnostic purposes, there is no "training set" in this context.

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

• Not applicable/Not provided.

Summary of Device Validation from the 510(k) Document:

The provided text states:

• "Digital Lightbox has been verified and validated according to BrainLAB procedures for product design and development. The validation proves the safety and effectiveness of the system." (Page 1, {1})
• "The information provided by BrainLAB in this 510 (k) application was found to be substantially equivalent with the predicate devices iPlan (K 053127), iPlan Hip Templating (K 042543) and DGSCOPE, RELEASE 1.0 (K 070397)." (Page 1, {1})

This indicates that BrainLAB conducted internal verification and validation activities to ensure the device met its design specifications and performed safely and effectively as an image viewing and manipulation system. The primary "study" for regulatory approval here is the demonstration of substantial equivalence to already legally marketed predicate devices, which implies that the Digital Lightbox meets similar performance and safety standards as those devices.

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