(70 days)
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.
| Acceptance Criterion (Implied) | Reported Device Performance |
|---|---|
| Safety and Effectiveness | Verified and validated according to BrainLAB procedures. |
| Compliance with Intended Use | System is intended for display of medical images, image manipulation, basic measurements, 3D visualization, and navigation planning features (multi-modality image fusion, object/trajectory creation). Its features for navigation planning and 3D visualization are equivalent to predicate device iPlan (K053127). |
| DICOM Standard Conformance | Conforms to the DICOM standard. |
| Substantial Equivalence to Predicate Devices | Found to be substantially equivalent to iPlan (K053127) and Digital Lightbox (K080608) for its stated indications for use (including new functionalities). |
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.
§ 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).