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Serrated Polyps at CT Colonography: Prevalence and Characteristics of the Serrated Polyp Spectrum.

ABSTRACT: 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.

SUBMITTER: Kim DH

PROVIDER: S-EPMC5510740 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning.MethodsIn this retrospective analysis of an average risk colorectal cancer screening sample, polyps of all size categories and morphologies were manually segmented on supine and prone CT colonography images and classified as premalignant (adenoma) or benign (hyperplastic polyp or regular mucosa) according to histopathology. Two deep learning models SEG and noSEG were trained on 3D CT colonography image subvolumes to predict polyp class, and model SEG was additionally trained with polyp segmentation masks. Diagnostic performance was validated in an independent external multicentre test sample. Predictions were analysed with the visualisation technique Grad-CAM++.ResultsThe training set consisted of 107 colorectal polyps in 63 patients (mean age: 63 ± 8 years, 40 men) comprising 169 polyp segmentations. The external test set included 77 polyps in 59 patients comprising 118 polyp segmentations. Model SEG achieved a ROC-AUC of 0.83 and 80% sensitivity at 69% specificity for differentiating premalignant from benign polyps. Model noSEG yielded a ROC-AUC of 0.75, 80% sensitivity at 44% specificity, and an average Grad-CAM++ heatmap score of ≥ 0.25 in 90% of polyp tissue.ConclusionsIn this proof-of-concept study, deep learning enabled the differentiation of premalignant from benign colorectal polyps detected with CT colonography and the visualisation of image regions important for predictions. The approach did not require polyp segmentation and thus has the potential to facilitate the identification of high-risk polyps as an automated second reader.Key points• Non-invasive deep learning image analysis may differentiate premalignant from benign colorectal polyps found in CT colonography scans. • Deep learning autonomously learned to focus on polyp tissue for predictions without the need for prior polyp segmentation by experts. • Deep learning potentially improves the diagnostic accuracy of CT colonography in colorectal cancer screening by allowing for a more precise selection of patients who would benefit from endoscopic polypectomy, especially for patients with polyps of 6-9 mm size.

Project description:Background & aimsSessile serrated polyps (SSPs) could account for a substantial proportion of colorectal cancers. We aimed to increase clarity on SSP prevalence and clinical features.MethodsWe performed a systematic review of MEDLINE, Web of Science, Embase, and Cochrane databases for original studies published in English since 2000. We included studies of different populations (United States general or similar), interventions (colonoscopy, autopsy), comparisons (world regions, alternative polyp definitions, adenoma), outcomes (prevalence, clinical features), and study designs (cross-sectional). Random-effects regression was used for meta-analysis where possible.ResultsWe identified 74 relevant colonoscopy studies. SSP prevalence varied by world region, from 2.6% in Asia (95% confidence interval [CI], 0-5.9) to 10.5% in Australia (95% CI, 2.8-18.2). Prevalence values did not differ significantly between the United States and Europe (P = .51); the pooled prevalence was 4.6% (95% CI, 3.4-5.8), and SSPs accounted for 9.4% of polyps with malignant potential (95% CI, 6.6-12.3). The mean prevalence was higher when assessed through high-performance examinations (9.1%; 95% CI, 4.0-14.2; P = .04) and with an alternative definition of clinically relevant serrated polyps (12.3%; 95% CI, 9.3-15.4; P < .001). Increases in prevalence with age were not statistically significant, and prevalence did not differ significantly by sex. Compared with adenomas, a higher proportion of SSPs were solitary (69.0%; 95% CI, 45.9-92.1; P = .08), with diameters of 10 mm or more (19.3%; 95% CI, 12.4-26.2; P = .13) and were proximal (71.5%; 95% CI, 63.5-79.5; P = .008). The mean ages for detection of SSP without dysplasia, with any or low-grade dysplasia, and with high-grade dysplasia were 60.8 years, 65.6 years, and 70.2 years, respectively. The range for proportions of SSPs with dysplasia was 3.7%-42.9% across studies, possibly reflecting different study populations.ConclusionsIn a systematic review, we found that SSPs are relatively uncommon compared with adenoma. More research is needed on appropriate diagnostic criteria, variations in detection, and long-term risk.

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Serrated Polyps at CT Colonography: Prevalence and Characteristics of the Serrated Polyp Spectrum.

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