(42 days)
Receive and process electronic images of patients. The REGIUS CS-2000/CS-3000 is NOT intended for use with digital mammography system.
REGIUS CONSOLE CS-2000 and CS-3000 are KONICAMINOLTA CR CONSOLE. REGIUS CONSOLE CS-2000 and CS-3000 control and manage the direct type CR such as INDICD CONCOLL OD 2000 and Sb connected to the Control Unit and the cassette type CR such as REGIUS MODEL 170 and 190 that is connected via the network. On such as REGION INCES-3000 have the hard disk for storing the digital images. REGIUS CONSOLE CS-2000 and CS-3000 consist of a console with the touch panel function, a keyboard and a mouse for input, and a barcode scanner. It can be connected to up multiple direct type CR and multiple cassette type CR, the image read by any reader in the system will be displayed on the REGIUS CONSOLE CS-2000 and CS-3000 by which the objective cassette was registered. The image read by each reader will OD bood by in real time in synchronization with the reader operation. REGIUS CONSOLE CS-2000 and CS-3000 process the images received from the reader INDOND OD DONDOID OD 2006 and OSSS of unction, etc., and send them to the connected devices, such as the host computer or the CR printer.
The provided text is a 510(k) summary for the REGIUS CONSOLE CS-2000 and CS-3000, which are medical image processing workstations. It states that the device is "not intended for use with digital mammography systems" and should be used by a radiographer, not for diagnosis. The documentation focuses on demonstrating substantial equivalence to a predicate device (Fuji CR Console Plus, K041990) rather than presenting a study with specific acceptance criteria and performance metrics in the way a clinical trial might for a new diagnostic algorithm.
Therefore, the information requested in your prompt regarding acceptance criteria, performance studies, sample sizes, expert ground truth, and MRMC studies is not explicitly present in the provided 510(k) summary. The summary highlights the device's functions and compares its features to the predicate device to establish substantial equivalence for regulatory approval.
Here's a breakdown based on the information that is available:
1. Table of Acceptance Criteria and Reported Device Performance
This 510(k) summary does not include a table of acceptance criteria or explicitly reported device performance metrics in the sense of accuracy, sensitivity, or specificity. The submission aims to demonstrate substantial equivalence to a predicate device by comparing features and safety, not by meeting specific performance thresholds for diagnostic accuracy.
The comparison table provided in the document focuses on hardware features and image processing functions between the applicant's device (REGIUS CONSOLE CS-2000/CS-3000) and the predicate device (Fuji Flash Plus IIP). It doesn't define acceptance criteria or report performance against them.
2. Sample Size Used for the Test Set and Data Provenance
Not applicable. The document does not describe a test set or clinical study of this nature. The approval is based on demonstrating substantial equivalence to a predicate device.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
Not applicable. There is no mention of a test set or ground truth established by experts for performance evaluation.
4. Adjudication Method for the Test Set
Not applicable. There is no mention of a test set or adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not described in this 510(k) summary. The document does not mention human reader performance with or without AI assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
No, a standalone algorithm performance study was not described. The device is a "Medical Image Processing Workstation" intended for use by a radiographer and explicitly states it is "never used for a diagnosis purpose." Its functions are for image processing and management, not standalone diagnosis.
7. The Type of Ground Truth Used
Not applicable. The document does not describe a clinical evaluation requiring ground truth such as pathology or outcomes data. The regulatory approach is substantial equivalence.
8. The Sample Size for the Training Set
Not applicable. There is no mention of a training set for an AI or machine learning algorithm. The device is an image processing workstation.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as no training set is mentioned for this device.
Summary of Device Purpose as per 510(k):
The REGIUS CONSOLE CS-2000 and CS-3000 are medical image processing workstations designed to "Receive and process electronic images of patients." They are intended for use by radiographers to control CR systems, manage patient information, display images, and perform various image processing functions (e.g., contrast adjustment, F-processing, E-processing, H-processing, masking, rotating/flipping, re-sampling/resizing, stitching, grid suppression). Crucially, the document states: "Console is designed in the purpose that the radiographer uses and is never used for a diagnosis purpose." This clarifies that the device's function is image manipulation and management for a radiographer, not automated diagnostic interpretation.
The 510(k) approval is based on demonstrating substantial equivalence to a predicate device (Fuji CR Console Plus, K041990) by comparing hardware and software features, functionalities, and safety aspects, rather than through clinical performance studies against specific diagnostic acceptance criteria.
§ 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).