Clinical–alimentary tractComputed Tomographic Virtual Colonoscopy Computer-Aided Polyp Detection in a Screening Population
Section snippets
Patient Population
The patient population consisted of 1253 asymptomatic adults between 40 and 79 years of age at 3 medical centers (institutions 1–3), of whom 1233 underwent complete same-day virtual and optical colonoscopy.4 Twenty of the 1253 patients were excluded because of incomplete optical colonoscopy, inadequate preparation, or failure of the CT colonographic system. The study was approved by the institutional review boards at all 3 centers. Written informed consent was obtained from all patients. This
Results
The patients were distributed into the training and test sets as shown in Table 1, with similar age and sex distributions, accounting for the 2:1 split. The polyp distributions are shown in Table 2.
The FROC curves are shown in Figure 1 for the 3 different classifiers trained to detect adenomatous polyps ≥10, ≥8, and ≥6 mm. These curves indicate that at a constant false-positive rate, sensitivity was higher for larger polyps. Sensitivity was also higher on the training set compared with the test
Discussion
CT virtual colonoscopy has progressed rapidly since its inception in 1994.29 Several large clinical trials have been reported.4, 6, 8, 30 Some of these trials have reported excellent sensitivity, but others have shown relatively poor sensitivity. The causes of poor sensitivities have been variously attributed to out-of-date CT scanner technology, absence of bowel opacification, inadequate interpretation software, improper interpretation approach (2-dimensional rather than 3-dimensional), or
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Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
2021, Computers in Biology and MedicineCitation Excerpt :This is not as undesirable as the converse of a high false negative rate, because the purpose of the computer-aided system is to focus the operator to attend to highlighted regions that may contain missed polyps [81]. While colonoscopy remains the gold-standard for investigating suspected CRC, CT virtual colonography is a relatively newer method for bowel cancer screening that offers non-invasive visualisation of the colon [82]. The flexibility of our model does not restrict usage to polyps in visible light and is equally applicable for polyp detection using CT colonography.
Imaging of Colorectal Cancer: Screening, Staging, and Surveillance
2021, Seminars in RoentgenologyCitation Excerpt :CT images are obtained both in supine and prone positions. Once data are acquired, image processing and reconstruction are performed on a computer using a variety of software packages.15 The data are then used to render multiplanar reformatted images (in coronal, sagittal, and axial planes), mucosal relief profiles, or hybrid surface-shaded or volume-rendered endoluminal perspectives.
Supine to prone colon registration and visualization based on optimal mass transport
2019, Graphical ModelsA comparison of computer-assisted detection (CAD) programs for the identification of colorectal polyps: performance and sensitivity analysis, current limitations and practical tips for radiologists
2018, Clinical RadiologyCitation Excerpt :This means that some small polyps identified on endoscopy and CAD may have been ignored by the radiologist. The majority of studies assessing the accuracy of CAD for detecting colorectal polyps are more in line with these studies and guidelines, using 5 or 6 mm as the cut-off.6,36,37,39–47 It is therefore not possible to draw reliable comparisons of this study with the results of other existing studies; however, this factor should not affect direct comparison between the two CAD systems in this study, which was its main purpose.
Imaging and Screening for Colorectal Cancer with CT Colonography
2017, Radiologic Clinics of North America
P.J.P.’s current affiliation is: Department of Radiology, University of Wisconsin Medical School, Madison, Wisconsin.
This research was supported by the Intramural Research Program of the National Institutes of Health, Warren G. Magnuson Clinical Center. Viatronix supplied the V3D Colon software free of charge. This study used the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health in Bethesda, Maryland (http://biowulf.nih.gov).