(44 days)
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.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).