(406 days)
uWS-CT is a software solution intended to be used for viewing, manipulation, and storage of medical images. It supports interpretation and evaluation of examinations within healthcare institutions. It has the following additional indications:
The CT Oncology application is intended to support fast-tracking routine diagnostic oncology, staging, and follow-up, by providing a tool for the user to perform the segmentation of suspicious lesions in lung or liver. The CT Colon Analysis application is intended to provide the user a tool to enable easy visualization and efficient evaluation of CT volume data sets of the colon.
The CT Dental application is intended to provide the user a tool to reconstruct panoramic and paraxial views of jaw. The CT Lung Density application is intended to provide the user a number of density parameters and structure information for evaluating tomogram scans of the lung.
The CT Lung Nodule application is intended to provide the user a tool for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies.
The CT Vessel Analysis application is intended to provide a tool for viewing, manipulating CT vascular images.
The Inner view application is intended to perform a virtual camera view through hollow structures (cavities), such as vessels.
uWS-CT is a comprehensive software solution designed to process, review and analyze CT studies. It can transfer images in DICOM 3.0 format over a medical imaging network or import images from external storage devices such as CD/DVDs or flash drives. These images can be functional data, as well as anatomical datasets. It can be at one or more time-points or include one or more time-frames. Multiple display formats including MIP and volume rendering and multiple statistical analysis including mean, maximum and minimum over a user-defined region is supported. A trained, licensed physician can interpret these displayed images as well as the statistics as per standard practice.
The provided document is a 510(k) Premarket Notification from Shanghai United Imaging Healthcare Co., Ltd. for their device uWS-CT. This document outlines the device's indications for use, technological characteristics, and comparison to predicate devices, but it does not contain a detailed study demonstrating that the device meets specific acceptance criteria based on human-in-the-loop or standalone performance.
Instead, the document primarily focuses on demonstrating substantial equivalence to predicate devices based on similar functionality and intended use, supported by software verification and validation testing, hazard analysis, and performance evaluations for various CT applications. It explicitly states that "No clinical study was required." and "No animal study was required." for this submission.
Therefore, I cannot provide the detailed information requested in the prompt's format (acceptance criteria table, sample size, expert ground truth, MRMC study, etc.) because these types of studies were not conducted or reported in this 510(k) submission.
The "Performance Data" section (Page 11) lists "Performance Evaluation Report For CT Lung Nodule," "Performance Evaluation Report For CT Oncology," etc., but these are internal reports that are not detailed in this public document. They likely refer to internal testing that verifies the software's functions perform as designed, rather than robust clinical performance studies against specific quantitative acceptance criteria with human readers or well-defined ground truth beyond internal validation.
What is present in the document regarding "performance" is:
- Software Verification and Validation: This typically involves testing that the software functions as designed, is free of bugs, and meets its specified requirements. The document mentions "hazard analysis," "software requirements specification (SRS)," "software architecture description," "software development environment description," "software verification and validation," and "cyber security documents."
- Performance Evaluation Reports for specific applications: These are listed but not detailed (e.g., CT Lung Nodule, CT Oncology). It's implied these show the software functions correctly for those applications.
In summary, based on the provided text, there is no information about:
- A table of acceptance criteria with reported device performance in the context of clinical accuracy or diagnostic performance.
- Sample sizes used for a test set in a clinical performance study.
- Data provenance for a clinical test set.
- Number of experts or their qualifications for establishing clinical ground truth.
- Adjudication methods for a clinical test set.
- Multi-Reader Multi-Case (MRMC) comparative effectiveness studies.
- Standalone (algorithm-only) performance studies against clinical ground truth.
- Type of clinical ground truth used (pathology, outcomes data, expert consensus from an external panel).
- Sample size for a training set (as no AI/ML model requiring a training set is explicitly discussed in terms of its performance data; the device is described as "CT Image Post-Processing Software" with various applications.)
- How ground truth for a training set was established.
The closest the document comes to "acceptance criteria" and "performance" are discussions of functional equivalence to predicate devices and general software validation, stating that the proposed device performs in a "similar manner" and has a "safety and effectiveness profile that is similar to the predicate device."
§ 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).