ISIS Research Center, Georgetown University Medical Center
Washington D.C., District of Columbia, 20007, United States
NCT Number: NCT01261507
A new software product takes two chest radiographs, aligns them, and then subtracts one image from the other. The resulting image represents an image showing any differences between them. The study is to determine whether radiologists using this new software perform better with it than when they do not use it.
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Notify Me35 year–100 year
All sexes
Observational
Washington D.C., District of Columbia, 20007, United States
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
For Radiologists: American Board of Radiology Certification and live within the Baltimore, MD-Washington, DC Metropolitan areas
For chest radiographs, evidence of the presence or absence of lung nodule confirmed by expert panel; adequate image quality
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Exclusion criteria
Radiologists who assisted by providing cases for review
For chest radiographs: poor image quality
Time frame: 1 day
The area under the LROC curve will be compared for the chest radiograph interpretations done without the new software and those done with the new software. Improvement will be demonstrated if the improvement with the new software is statistically significant at the p=<0.05. There were 422 cases in the total study. 20 of these were inserted as "noise" cases, not to be analyzed. Thus there were 402 cases to be analyzed. There were 120 cases with nodules and 282 without a nodule. LROC is a method for measuring the success or failure of a method where there is a tradeoff between the detection of lung nodules that are there (true positives) and the detection that the radiologist considers to be a nodule where no nodule is present (false positive). It yields a single number that done not have a unit of measurement.
Time frame: 1 day
Sensitivity and specificity will be measured. If the radiologists using the new software have higher sensitivity, statistically significant at the p=< 0.05, the use of the new software will be considered to have resulted in improvement. A decrease in specificity is expected.
Time frame: 1 day
This is a comparison of the radiologists working without and with the software. The false positive rate is the percentage of cases in which the radiologists identified a lesions/location suspected of being cancer at a location where cancer was not present. . A false positive represents a location selected on a chest image without cancer and, also, a mark on a chest image where cancer was present, but a different location, one without cancer, was marked.The radiologists could mark up to five locations on an image and had to provide a confidence rating for each. This analysis is of the single mark with the highest confidence level.
Georgetown University
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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