(289 days)
AXIR-CX is a software package used with general purpose computing hardware to receive, store, distribute and display chest X-ray images and associated data for patient diagnosis. AXIR-CX is a software application that enable the DICOM-compliant chest X-ray image [14 x 17 or 17 x 17 inch size] from DR and CR, and after image displaying the user adds the annotation regarding the diagnosis and print out the patient information or send to another PACS system. AXIR-CX is intended to be used by trained medical professionals including physicians, radiologists, and medical technicians. This device is not indicated for use in mammography.
The AXIR software is designed for use by radiologists and radiology technicians for annotation in the Chest X-ray images. The AXIR software is developed to use Radisen Flat Panel DR Detector and Radisen Image Viewer. The purpose of AXIR software is for the doctor to annotate Chest X-ray images and then to print out with patient information or sent to another PACS system.
A client user needs to install AXIR-CX first in the recommended PC environment. After installation, the client user chooses a DICOM format in the uploaded patient list to be annotated, and then annotation is written by user after reviewing of image chosen. After annotation has completed it can be printed out, saved or sent to another PACS system.
This submission, K213520 for AXIR-CX, does not contain the information requested regarding acceptance criteria and performance studies that prove the device meets those criteria.
The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device (ExamVue PACS, K162868). It highlights similarities and differences in intended use, performance standards, operating system requirements, and specific functionalities like image archiving, display, patient search, and annotation.
Crucially, this document does not describe a study that validates the performance of AXIR-CX against predefined acceptance criteria for AI/ML-driven diagnostic tasks. The "Performance Standard" mentioned (21 CFR 892.2050) refers to the regulation for Medical image management and processing systems, not specific performance metrics for AI. The "Safety, EMC and Performance Data" section only states that "Safety testing and documentation was performed in accordance with IEEE 1012-2012, Standard for System and Software Verification and Validation," which is a general software engineering standard and does not provide details on specific clinical or AI performance evaluation.
Therefore, I cannot extract the requested information from this document. The device, AXIR-CX, appears to be an image management and processing system (PACS-like) with annotation capabilities, rather than an AI-driven diagnostic tool that would require the rigorous performance study details you've outlined. The differences noted, such as the absence of specific measurement tools, window/level adjustment, and zoom/magnify functions in AXIR-CX compared to the predicate, further suggest it's a foundational image display and management system.
§ 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).