(52 days)
B-CAD is a computer-aided detection (CAD) software application designed to assist radiologists to analyze breast ultrasound images. B-CAD automatically segments and classifies shape and orientation characteristics of user-selected regions of interest (ROI).
The software allows the user to annotate, tag, measure, and automatically record selected views. The software automatically generates reports from user inputs annotated during the image analysis process. An output may be viewed and sent to standard film or paper printers or sent electronically to an intranet web server or other DICOM device. The software may retrieve archived reports from a web server or other DICOM device.
B-CAD includes the option to add annotations based on the ACR-BI-RADS® Breast Imaging Atlas. In addition, the report form has been designed to support compliance with the ACR-BI-RADS® Ultrasound Lexicon Classification Form.
When interpreted by a skilled physician, this device provides information that may be useful in screening and diagnosis. Patient management decisions should not be made solely on the results of B-CAD analysis. The ultrasound images displayed on B-CAD must not be used for primary diagnostic interpretation.
B-CAD is a computer-aided detection (CAD) software application, designed to assist radiologists to analyze breast ultrasound images. B-CAD automatically segments and classifies shape and orientation characteristics of user-selected regions of interest (ROI). The device uses multivariate pattern recognition methods to perform tissue segmentation and classification of images.
For breast ultrasound, these pattern recognition methods are used by a radiologist to analyze such features as shape and orientation [refer to American College of Radiology's (ACR) Breast Imaging Reporting and Data System (BI-RADS®) Breast Imaging Atlas and ACR-BI-RADS® Ultrasound lexicon].
The software application consists of proprietary software developed by The Medipattern Corporation. The software is a Windows 2000/XP, DICOMcompatible platform that may be installed on a standalone PC, PACS, or embedded in software applications cleared for use in medical imaging. The B-CAD user interface is designed to follow typical clinical workflow patterns to process, review, and analyze digital images.
The Medipattern software is designed to be compatible with any of the DICOM-compliant medical devices distributed by various OEM vendors.
To initiate B-CAD analysis and processing, images are acquired and pushed to the software application from an ultrasound imager for review and further analysis on a monitor. The user selects a ROI by clicking on a seed point and dragging the cursor to the selected boundary of the ROI. A circle appears, defining the region of interest. Once the ROI is selected, the B-CAD software initially displays a gallery of up to six segmented views on the monitor. The user may select any view for further analysis of anatomy and pathology. The software allows the user to annotate, tag, measure, and automatically record selected views. Results of the analysis are displayed on the monitor and may be selected by the user for automated reporting.
The software application automatically generates reports from user inputs annotated during the image analysis process. The user may select inputs for the report from various pull-down menus and toggle buttons and the user may direct the B-CAD software to prepopulate various fields contained in the report. All fields may be modified by the user at any time during the analysis and prior to archiving.
The provided 510(k) summary for the B-CAD System, Version 1.0, does not contain any information regarding specific acceptance criteria or a study proving that the device meets such criteria.
The document primarily focuses on describing the device, its intended use, and its substantial equivalence to predicate devices based on functions like image display, ROI quantification, and automated reporting. It mentions that "Software development for the B-CAD System follows documented processes for software design, verification and validation testing," and that a "risks assessment has been completed." However, it does not disclose the details of these verification and validation tests, including any performance metrics, target values, or the specific studies conducted to demonstrate clinical performance or accuracy.
Therefore, I cannot provide the requested information. The 510(k) summary does not include:
- A table of acceptance criteria and the reported device performance: No such criteria or performance data is presented.
- Sample size used for the test set and the data provenance: No test set or data provenance details are mentioned.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: No information on ground truth establishment or expert involvement is provided for any test set.
- Adjudication method for the test set: No adjudication method is described.
- If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, including effect size: No MRMC study is mentioned.
- If a standalone (algorithm only without human-in-the-loop performance) was done: The description focuses on assisting radiologists, but no standalone performance study is detailed.
- The type of ground truth used: No mention of ground truth type.
- The sample size for the training set: No information on training data is provided.
- How the ground truth for the training set was established: No information on training ground truth establishment.
The document states that "The System has been shown to be substantially equivalent to the predicate devices, and no new issues of safety or effectiveness are raised." This statement implies that the device's safety and effectiveness were assessed indirectly through comparison to previously cleared devices rather than a direct, quantitative performance study with explicit 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).