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Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection.

ABSTRACT: To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm.An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided doses over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm.The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan.An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.

SUBMITTER: Linguraru MG

PROVIDER: S-EPMC3254579 | biostudies-other | 2011 Dec

REPOSITORIES: biostudies-other

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Project description:Purpose To report the prevalence and characteristics of serrated polyps identified in a large, average-risk population undergoing screening computed tomographic (CT) colonography. Materials and Methods This HIPAA-compliant retrospective study was approved by the institutional review board of the University of Wisconsin School of Medicine and Public Health. The need for informed consent was waived. Nine thousand six hundred examinations from 8289 patients were enrolled in a single-institution CT colonography-based screening program (from 2004 to 2011) and were evaluated for the presence of nondiminutive serrated lesions and advanced adenomas. The prevalence and characteristics of these lesions were tabulated. Generalized estimating equation regressions of polyp characteristics that may contribute to visualization of serrated lesions were investigated, including polyp size, location, and morphologic appearance; histologic findings; and presence or absence of contrast material tagging. Results Nondiminutive serrated lesions (?6 mm) were seen at CT colonography-based screening with a prevalence of 3.1% (254 of 8289 patients). Sessile serrated adenomas (SSAs) and traditional serrated adenomas (TSAs) constituted 36.8% (137 of 372) and 4.3% (16 of 372) of serrated lesions, respectively; hyperplastic polyps (HPs) accounted for 58.9% (219 of 372 lesions). SSA and TSA tended to be large (mean size, 10.6 mm and 14.1 mm, respectively), with size categories and polyp subgroups significantly associated (P < .0001). SSA tended to be proximal in location (91.2%, 125 of 137 lesions) and flat in morphologic appearance (39.4%, 54 of 137 lesions) compared with TSA and HP. The presence of high-grade dysplasia in serrated lesions was uncommon when compared with advanced adenomas (one of 372 lesions vs 22 of 395 lesions, respectively; P < .0001). Multivariate analysis showed that contrast material tagging markedly improved serrated polyp detection with an odds ratio of 40.4 (95% confidence interval: 10.1, 161.4). Conclusion Serrated lesions are seen at CT colonography-based screening with a nondiminutive prevalence of 3.1%. These lesions tend to be large, flat, and proximal in location. Adherent contrast material coating on these polyps aids in their detection, despite an often flat morphologic appearance. (©) RSNA, 2016 Online supplemental material is available for this article.

Project description:The purpose of this work was to develop and validate a computer-aided method for the 3D segmentation of lymph nodes in CT images. The proposed method can be utilized to facilitate applications like biopsy planning, image guided radiation treatment, or assessment of response to therapy.An optimal surface finding based lymph node segmentation method was developed. Based on the approximate center point of a lymph node of interest, a graph is generated, which represents the local neighborhood around the lymph node at discrete locations (graph nodes). A cost function is calculated based on a weighted edge and region homogeneity term. By means of optimization, a surface-based segmentation of the lymph node is derived. In addition, an interactive segmentation refinement algorithm was developed, which allows the user to quickly correct segmentation errors, if needed. For assessment of segmentation accuracy, 111 lymph nodes of mediastinum, abdomen, head/neck, and axillary regions from 35 volumetric CT scans were utilized. For accuracy analysis, lymph nodes were divided into three test sets based on lymph node size and spatial resolution of the CT scan. The average lymph node size for test set I, II, and III was 1056, 1621, and 501 mm(3), respectively. Spatial resolution of test set II was lower than for test sets I and III. To generate an independent reference standard for comparison, all 111 lymph nodes were segmented by an expert with a live wire approach.All test sets were segmented with the proposed approach. Out of the 111 lymph nodes, 40 cases (36%) required computer-aided refinement of initial segmentation results. The refinement typically required 10 s per lymph node. The mean and standard deviation of the Dice coefficient for final segmentations was 0.847 ± 0.061, 0.836 ± 0.058, and 0.809 ± 0.070 for test sets I, II, and II, respectively. The average signed surface distance error was 0.023 ± 0.171, 0.394 ± 0.189, and 0.001 ± 0.146 mm for test sets I, II, and II, respectively. The time required for locating the approximate center point of a target lymph node in a scan, generating an initial OSF segmentation, and refining the segmentation, if needed, is typically less than one minute.Segmentation of lymph nodes in volumetric CT images is a challenging task due to partial volume effects, nearby strong edges, neighboring structures with similar intensity profiles and potentially inhomogeneous density of lymph nodes. The presented approach addresses many of these obstacles. In the majority of cases investigated, the initial segmentation method delivered results that did not require further processing. In addition, the computer-aided segmentation refinement framework was found to be effective in dealing with potentially occurring segmentation errors.

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Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection.

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