ABSTRACT: To determine whether the display of computer-aided detection (CAD) marks on individual polyps on both the supine and prone scans leads to improved polyp detection by radiologists compared to the display of CAD marks on individual polyps on either the supine or the prone scan, but not both.
The acquisition of patient data for this study was approved by the Institutional Review Board and was Health Insurance Portability and Accountability Act-compliant. Subsequently, the use of the data was declared exempt from further institutional review board review. Four radiologists interpreted 33 computed tomography colonography cases, 21 of which had one adenoma 6-9 mm in size, with the assistance of a CAD system in the first reader mode (ie, the radiologists reviewed only the CAD marks). The radiologists were shown each case twice, with different sets of CAD marks for each of the two readings. In one reading, a true-positive CAD mark for the same polyp was displayed on both the supine and prone scans (a double-mark reading). In the other reading, a true-positive CAD mark was displayed either on the supine or prone scan, but not both (a single-mark reading). True-positive marks were randomized between readings and there was at least a 1-month delay between readings to minimize recall bias. Sensitivity and specificity were determined and receiver operating characteristic (ROC) and multiple-reader multiple-case analyses were performed.
The average per polyp sensitivities were 60% (38%-81%) versus 71% (52%-91%) (P = .03) for single-mark and double-mark readings, respectively. The areas (95% confidence intervals) under the ROC curves were 0.76 (0.62-0.88) and 0.79 (0.58-0.96), respectively (P = NS). Specificities were similar for the single-mark compared with the double-mark readings.
The display of CAD marks on a polyp on both the supine and prone scans led to more frequent detection of polyps by radiologists without adversely affecting specificity for detecting 6-9 mm adenomas.
Academic radiology 08/2010; 17(8):948-59. · 2.09 Impact Factor