Testing of Computer Aided Detection Software for Riverain Medical Group
This is a clinical trial using retrospective data of two different software devices developed by Riverain Medical Group: Softview and OnGuard 5.0. The two studies will be run concurrently. Riverain Medical Group's computer systems are designed to assist radiologists in their identification of lung cancer on chest radiographs. The current machine received FDA Pre-Market Approval. This is to test two new software approaches.
|Official Title:||Testing of Computer Aided Detection Software for Riverain Medical Group|
- Improvement in Cancer Detection as Measured by Localized Receiver Operating Characteristic) LROC Changes Under the LROC Curve. [ Time Frame: Three days of experiment over 3-5 months, varied by participant ] [ Designated as safety issue: No ]
Standard methods for LROC methodology and statistical analysis were used. We are testing two different types of software using different cases, but the same radiologists to control for radiologist differences. LROC is Localized Receiver Operating Characteristic. LROC measures the trade-offs between sensitivity and specificity as radiologists use different levels of suspicion of disease. This analysis is for the software that decreases the visibility of the ribs and clavicles while preserving (and potentially enhancing) the visibility of the lungs and lung diseases. In this case, the level of suspicion recorded was for the radiologist's concern that a finding did or did not represent cancer. Please note that the FDA approved indications for use is to detected nodules that may represent cancer, but in our study scoring for a true finding was based on whether or not the nodule did represent cancer.
A larger number, if statistically significant, indicates that that method is better.
- Sensitivity and Specificity Using SoftView Software [ Time Frame: Three days of experiment over 3-5 months, varied by participant ] [ Designated as safety issue: No ]Sensitivity and specificity were calculated using the radiologists' responses of recommendations for follow-up with CT or biopsy. Truth was whether or not the nodule identified was found to be cancer. Sensitivity is the percentage of correct identification of a positive case (a case with cancer). Specificity is the percentage of negative cases (those without cancer) that were correctly identified as not having cancer. The mean values of 15 radiologists are used.
- Difference in the Area Under the LROC Curve Comparing OnGuard 1.0 and OnGuard 5.1 [ Time Frame: 5 months ] [ Designated as safety issue: No ]This reports the comparison of the detection of lung nodules that were proven to represent lung cancers. It compares the results of two versions of computer-aided detection software: OnGuard 1.0 from 2001 and OnGuard 5.1 from 2009. The results represent the responses of radiologists when they use one or the other types of software. To compare radiologists' results with the two types of software, the measurement analyzed was the difference in the areas under the localized receiver operating characteristic curve (LROC). The results from the 15 participating radiologists were averaged (mean value). The area under the LROC curve is a measure of the trade-offs between sensitivity and 1-specificity that occurs as the level of certainty of a positive finding changes. It is normally reported as a decimal without units. In this study dsign, a lower number indicates that the new method (OnGuard 5.1), if statistically significant, if better.
|Study Start Date:||May 2009|
|Study Completion Date:||June 2010|
|Primary Completion Date:||June 2010 (Final data collection date for primary outcome measure)|
Radiologists who have certification by the American Board of Radiology
This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, both SoftView (TM) OnGuard (TM) CADe Software with be tested
In 2000, data was presented to the FDA to demonstrate that a new system for computer analysis could assist radiologists in the detection of small lung cancers on chest radiographs. Radiologists using the system showed a statistically significant improvement in lung cancer detection rate when they used the system, compared to their interpretation of chest radiographs when they did not use the computer system. This study, along with other supporting data, resulted in the FDA giving Pre-Market Approval for the system.
The system has undergone several improvements in software and hardware, and it is now intended to test two different software systems to determine whether radiologists using the systems can improve their detection of lung cancer on chest radiographs.
One of these systems processes the chest radiograph to decrease the emphasis given to the shadow of the ribs and thereby enhances the ability of radiologists to detect disease in the lungs. The second system performs a series of evaluations on chest radiographs and, based on a complex system of analysis, points to locations on the chest radiograph that contain solitary pulmonary nodules having the characteristics of primary lung cancer or solitary metastases of cancer to the lungs.
This will be a test of radiologists to determine the degree of improvement, if any, that results when they interpret chest radiographs that may or may not have cancer, first interpreted without the computer and, second, with the images output by the software.
Please refer to this study by its ClinicalTrials.gov identifier: NCT00906789
|United States, District of Columbia|
|ISIS Imaging Science Research Center, Georgetown University|
|Washington, District of Columbia, United States, 20057|
|Principal Investigator:||Matthew T. Freedman, MD, MBA||Georgetown University|
|Study Director:||Ben Lo, Ph.D.||Georgetown University|