CT colonography: clinical evaluation of a method for automatic coregistration of polyps at follow-up surveillance studies.

PURPOSE: To evaluate the accuracy of a method of automatic coregistration of the endoluminal surfaces at computed tomographic (CT) colonography performed on separate occasions to facilitate identification of polyps in patients undergoing polyp surveillance. MATERIALS AND METHODS: Institutional review board and HIPAA approval were obtained. A registration algorithm that was designed to coregister the coordinates of endoluminal colonic surfaces on images from prone and supine CT colonographic acquisitions was used to match polyps in sequential studies in patients undergoing polyp surveillance. Initial and follow-up CT colonographic examinations in 26 patients (35 polyps) were selected and the algorithm was tested by means of two methods, the longitudinal method (polyp coordinates from the initial prone and supine acquisitions were used to identify the expected polyp location automatically at follow-up CT colonography) and the consistency method (polyp coordinates from the initial supine acquisition were used to identify polyp location on images from the initial prone acquisition, then on those for follow-up prone and follow-up supine acquisitions). Two observers measured the Euclidean distance between true and expected polyp locations, and mean per-patient registration accuracy was calculated. Segments with and without collapse were compared by using the Kruskal-Wallace test, and the relationship between registration error and temporal separation was investigated by using the Pearson correlation. RESULTS: Coregistration was achieved for all 35 polyps by using both longitudinal and consistency methods. Mean ± standard deviation Euclidean registration error for the longitudinal method was 17.4 mm ± 12.1 and for the consistency method, 26.9 mm ± 20.8. There was no significant difference between these results and the registration error when prone and supine acquisitions in the same study were compared (16.9 mm ± 17.6; P = .451). CONCLUSION: Automatic endoluminal coregistration by using an algorithm at initial CT colonography allowed prediction of endoluminal polyp location at subsequent CT colonography, thereby facilitating detection of known polyps in patients undergoing CT colonographic surveillance.

Registration of the endoluminal surfaces of the colon derived from prone and supine CT colonography.

PURPOSE: Computed tomographic (CT) colonography is a relatively new technique for detecting bowel cancer or potentially precancerous polyps. CT scanning is combined with three-dimensional (3D) image reconstruction to produce a virtual endoluminal representation similar to optical colonoscopy. Because retained fluid and stool can mimic pathology, CT data are acquired with the bowel cleansed and insufflated with gas and patient in both prone and supine positions. Radiologists then match visually endoluminal locations between the two acquisitions in order to determine whether apparent pathology is real or not. This process is hindered by the fact that the colon, essentially a long tube, can undergo considerable deformation between acquisitions. The authors present a novel approach to automatically establish spatial correspondence between prone and supine endoluminal colonic surfaces after surface parameterization, even in the case of local colon collapse. METHODS: The complexity of the registration task was reduced from a 3D to a 2D problem by mapping the surfaces extracted from prone and supine CT colonography onto a cylindrical parameterization. A nonrigid cylindrical registration was then performed to align the full colonic surfaces. The curvature information from the original 3D surfaces was used to determine correspondence. The method can also be applied to cases with regions of local colonic collapse by ignoring the collapsed regions during the registration. RESULTS: Using a development set, suitable parameters were found to constrain the cylindrical registration method. Then, the same registration parameters were applied to a different set of 13 validation cases, consisting of 8 fully distended cases and 5 cases exhibiting multiple colonic collapses. All polyps present were well aligned, with a mean (+/- std. dev.) registration error of 5.7 (+/- 3.4) mm. An additional set of 1175 reference points on haustral folds spread over the full endoluminal colon surfaces resulted in an error of 7.7 (+/- 7.4) mm. Here, 82% of folds were aligned correctly after registration with a further 15% misregistered by just onefold. CONCLUSIONS: The proposed method reduces the 3D registration task to a cylindrical registration representing the endoluminal surface of the colon. Our algorithm uses surface curvature information as a similarity measure to drive registration to compensate for the large colorectal deformations that occur between prone and supine data acquisitions. The method has the potential to both enhance polyp detection and decrease the radiologist's interpretation time.