Parascript® AccuDetect® Computer-Aided Detection (CAD) software helps radiologists read digital mammograms. Using several complementary algorithms and a patented voting method to achieve high sensitivity and low false-positive rates, AccuDetect identifies areas suspicious for breast cancer for further review. AccuDetect improves the performance of radiologists in discriminating between malignant and nonmalignant cases.
Examining the Results
According to the retrospective comparative study, “Malignant Lesions on Mammography: Accuracy of Two Different Computer-Aided Detection Systems,” (Lobbes et al., Clinical Imaging 37 (2013) 283-288), the previous version of the AccuDetect CAD system (AccuDetect Galileo version 4.0.1) showed better overall performance when compared to iCAD’s Second Look (version 7.2) in detecting masses, microcalcifications, and all cancer types, especially in extremely dense breasts. When compared to Second Look in extremely dense breasts (ACR 4), AccuDetect demonstrated 15.4 percent increase in detection of both masses and calcifications with similar operating points for both CAD systems. Most importantly, for total cancer cases in extremely dense breasts, the percentage of cancers correctly identified by AccuDetect was 14.6 percent higher than that of Second Look, again with similar operating points.
These differences can be directly related to the mechanism that each system uses in detecting lesions. Second Look detects culprit lesions on mammograms using image processing, pattern recognition, and artificial intelligence techniques based on the knowledge from thousands of mammograms. In addition to these well-known approaches, AccuDetect system uses multiple independent cancer detection algorithms and unique patented voting methodology (“Voting in Mammography Processing.” US Patent 8,311,296.) to combine its findings. Comparing the results of the multiple image recognition processes allows for the mitigation of the inherent faults of the recognition processes, thus leading to reduced false-positive and false-negative rates.
Find out more about how Parascript® AccuDetect® works:
- Download the AccuDetect brochure
- Download the Company Overview brochure
- Clinical Imaging, “Malignant lesions on mammography: accuracy of two different computer-aided detection systems” research article
- Learn about lowering false-positive rates through voting
- Find out about improvement in ROC curves of Readers with the next generation mammography CAD – ECR Scientific Paper
- Find out about improvement in both sensitivity and specificity of readers with next generation of mammography CAD – ECR Scientific Paper
- Read the retrospective study comparison of Arcadia Lab’s Galileo and Parascript® AccuDetect® CAD systems
- Read about How FDA Approves AccuDetect® 7.0 Expanding Parascript’s Reach
- Read about the FDA granting Parascript approval for mammography CAD in 2013
The Digital Imaging and Communications in Medicine (DICOM) standard facilitates interoperability of medical equipment. Below is Parascript’s DICOM Conformance Statement for Parascript AccuDetect Computer Aided Detection (CAD) software.
SUPERIOR CAD WORKFLOW PERFORMANCE
- Fast processing time – 11 seconds per image,
45 seconds per 4-view study.
(Compared to: iCAD’s SecondLook: 30 seconds per image, 120 seconds per 4-view study; and Hologic’s R2: 30 seconds per image, 120 seconds per 4-view study.)
(P. Tchou et al., “Interpretation Time of Computer-aided Detection at Screening Mammography.” Radiology. October 2010.)
- Priority queuing of preferred devices for important or urgent studies.
- CAD server supports up to four FFDM systems.
DETECTION OF MICROCALCIFICATIONS
- Detects calcification clusters consisting of several calcifications with size between 0.1mm and 0.8mm. in diameter within 2cm2 area.
- Results for calcifications: 90% sensitivity with 0.75 false positives per four-view study.
AccuDetect 7.0 includes a Windows 7, multi-vendor CAD server that provides consistency across all digital mammography systems. Please see the ACCUDETECT BROCHURE for details.