(12 days)
A nuclear medicine image display and processing application suite that provides software applications used to process, analyze, and display medical images/data. The results obtained may be used as a tool, by a nuclear physician, in determining the diagnosis of patient disease conditions in various organs, tissues, and other anatomical structure. The data processed may be derived from any nuclear medicine camera. EBW NM 2.0 should only be operated by qualified healthcare professionals trained in the use of nuclear medicine equipment.
EBW NM 2.0 is a Windows®-based Nuclear Medicine suite of image display and processing applications for the Nuclear Medicine market segment. The software package is deployable on hardware platforms, which meet the minimum requirements needed to run the software. The comprehensive tools and features provided with this product, will allow the technologist and/or physician to perform image review, processing of source data, post processing, hardcopy production, interpretation, report generation and contains the utilities necessary to support the workflow and data management between those activities.
The provided document is a 510(k) summary for the Philips EBW NM 2.0 Image Processing System. It states that the device is "substantially equivalent" to predicate devices based on similar intended use, technological comparison, and system performance. However, it does not contain the specific details of performance studies, acceptance criteria, or ground truth establishment that you are requesting.
The 510(k) process primarily focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting detailed performance data against specific acceptance criteria. This document describes the device, its intended use, and its equivalence to two predicate devices (NM Application Suite K080961 and AutoSPECT K090403).
Therefore, based solely on the provided text:
- A table of acceptance criteria and the reported device performance: Not provided. The document states "system performance" but does not detail how this was measured against specific criteria.
- Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not provided.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience): Not provided.
- Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not provided.
- If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not indicated or described. The device is an "Image Processing System" and while it may assist human readers, a formal MRMC study is not mentioned as part of this submission.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not indicated or described.
- The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not provided.
- The sample size for the training set: Not provided.
- How the ground truth for the training set was established: Not provided.
In summary, this 510(k) summary confirms the regulatory clearance of the device but does not include the detailed study information or performance metrics you've asked for. Such information, if generated, would typically be found in detailed internal validation reports or potentially in a more comprehensive clinical study report, neither of which is part of this 510(k) "summary of safety and effectiveness."
§ 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).