Dataset Information

CT colonography: size reduction of submerged colorectal polyps due to electronic cleansing and CT-window settings.

ABSTRACT: OBJECTIVES:To assess whether electronic cleansing (EC) of tagged residue and different computed tomography (CT) windows influence the size of colorectal polyps in CT colonography (CTC). METHODS:A database of 894 colonoscopy-validated CTC datasets of a low-prevalence cohort was retrospectively reviewed to identify patients with polyps ?6 mm that were entirely submerged in tagged residue. Ten radiologists independently measured the largest diameter of each polyp, two-dimensionally, before and after EC in colon, bone, and soft-tissue-windows, in randomised order. Differences in size and polyp count before and after EC were calculated for size categories ?6 mm and ?10 mm. Statistical testing involved 95% confidence interval, intraclass correlation and mixed-model ANOVA. RESULTS:Thirty-seven patients with 48 polyps were included. Mean polyp size before EC was 9.8 mm in colon, 9.9 mm in bone and 8.2 mm in soft-tissue windows. After EC, the mean polyp size decreased significantly to 9.4 mm in colon, 9.1 mm in bone and 7.1 mm in soft-tissue windows. Compared to unsubtracted colon windows, EC, performed in colon, bone and soft-tissue windows, led to a shift of 6 (12,5%), 10 (20.8%) and 25 (52.1%) polyps ?6 mm into the next smaller size category, thus affecting patient risk stratification. CONCLUSIONS:EC and narrow CT windows significantly reduce the size of polyps submerged in tagged residue. Polyp measurements should be performed in unsubtracted colon windows. KEY POINTS:• EC significantly reduces the size of polyps submerged in tagged residue. • Abdominal CT-window settings significantly underestimate 2D sizes of submerged polyps. • Size reduction in EC is significantly greater in narrow than wide windows. • Underestimation of polyp size due to EC may lead to inadequate treatment. • Polyp measurements should be performed in unsubtracted images using a colon window.

SUBMITTER: Brauer C

PROVIDER: S-EPMC6182748 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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CT colonography: size reduction of submerged colorectal polyps due to electronic cleansing and CT-window settings.

Bräuer Christian C Lefere Philippe P Gryspeerdt Stefaan S Ringl Helmut H Al-Mukhtar Ali A Apfaltrer Paul P Berzaczy Dominik D Füger Barbara B Furtner Julia J Müller-Mang Christina C Pones Matthias M Scharitzer Martina M Woitek Ramona R Graser Anno A Weber Michael M Mang Thomas T

European radiology 20180514 11

<h4>Objectives</h4>To assess whether electronic cleansing (EC) of tagged residue and different computed tomography (CT) windows influence the size of colorectal polyps in CT colonography (CTC).<h4>Methods</h4>A database of 894 colonoscopy-validated CTC datasets of a low-prevalence cohort was retrospectively reviewed to identify patients with polyps ≥6 mm that were entirely submerged in tagged residue. Ten radiologists independently measured the largest diameter of each polyp, two-dimensionally, ...[more]

PMID: 29761359

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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: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 clinical relevance and in-vivo growth rates of small (6-9 mm) colorectal polyps are not well established. We aimed to assess the behaviour of such polyps with CT colonography assessments.In this longitudinal study, we enrolled asymptomatic adults undergoing routine colorectal cancer screening with CT colonography at two medical centres in the USA. Experienced investigators (PJP, DHK, JLH) measured volumes and maximum linear sizes of polyps in vivo with CT colonography scans at baseline and surveillance follow-up. We defined progression, stability, and regression on the basis of a 20% volumetric change per year from baseline (20% or more growth classed as progression, 20% growth to -20% reduction classed as stable, and -20% or more reduction classed as regression). We compared findings with histological subgroups confirmed after colonoscopy when indicated. This study is registered with ClinicalTrials.gov, number NCT00204867.Between April, 2004, and June, 2012, we screened 22,006 asymptomatic adults and included 243 adults (mean age 57·4 years [SD 7·1] and median age 56 years [IQR 52-61]; 106 [37%] women), with 306 small colorectal polyps. The mean surveillance interval was 2·3 years (SD 1·4; range 1-7 years; median 2·0 years [IQR 1·1-2·3]). 68 (22%) of 306 polyps progressed, 153 (50%) were stable, and 85 (28%) regressed, including an apparent resolution in 32 (10%) polyps. We established immediate histology in 131 lesions on colonoscopy after final CT colonography. 21 (91%) of 23 proven advanced adenomas progressed, compared with 31 (37%) of 84 proven non-advanced adenomas, and 15 (8%) of 198 other lesions (p<0·0001). The odds ratio for a growing polyp at CT colonography surveillance to become an advanced adenoma was 15·6 (95% CI 7·6-31·7) compared with 6-9 mm polyps detected and removed at initial CT colonography screening (without surveillance). Mean polyp volume change was a 77% increase per year for 23 proven advanced adenomas and a 16% increase per year for 84 proven non-advanced adenomas, but a 13% decrease per year for all proven non-neoplastic or unresected polyps (p<0·0001). An absolute polyp volume of more than 180 mm(3) at surveillance CT colonography identified proven advanced neoplasia (including one delayed cancer) with a sensitivity of 92% (22 of 24 polyps), specificity of 94% (266 of 282 polyps), positive-predictive value of 58% (22 of 38 polyps), and negative-predictive value of 99% (266 of 268 polyps). Only 16 (6%) of the 6-9 mm polyps exceeded 10 mm at follow-up.Volumetric growth assessment of small colorectal polyps could be a useful biomarker for determination of clinical importance. Advanced adenomas show more rapid growth than non-advanced adenomas, whereas most other small polyps remain stable or regress. Our findings might allow for less invasive surveillance strategies, reserving polypectomy for lesions that show substantial growth. Further research is needed to provide more information regarding the ultimate fate of unresected small polyps without significant growth.US National Institutes of Health, National Cancer Institute.

Project description:ObjectivesThe aim of this study was to compare the morphology, radiological stage, conspicuity, and computer-assisted detection (CAD) characteristics of colorectal cancers (CRC) detected by computed tomographic colonography (CTC) in screening and symptomatic populations.MethodsTwo radiologists independently analyzed CTC images from 133 patients diagnosed with CRC in (a) two randomized trials of symptomatic patients (35 patients with 36 tumours) and (b) a screening program using fecal occult blood testing (FOBt; 98 patients with 100 tumours), measuring tumour length, volume, morphology, radiological stage, and subjective conspicuity. A commercial CAD package was applied to both datasets. We compared CTC characteristics between screening and symptomatic populations with multivariable regression.ResultsScreen-detected CRC were significantly smaller (mean 3.0 vs 4.3 cm, p?<?0.001), of lower volume (median 9.1 vs 23.2 cm3, p?<?0.001) and more frequently polypoid (34/100, 34 % vs. 5/36, 13.9 %, p?=?0.02) than symptomatic CRC. They were of earlier stage than symptomatic tumours (OR?=?0.17, 95 %CI 0.07-0.41, p?<?0.001), and were judged as significantly less conspicuous (mean conspicuity 54.1/100 vs. 72.8/100, p?<?0.001). CAD detection was significantly lower for screen-detected (77.4 %; 95 %CI 67.9-84.7 %) than symptomatic CRC (96.9 %; 95 %CI 83.8-99.4 %, p?=?0.02).ConclusionsScreen-detected CRC are significantly smaller, more frequently polypoid, subjectively less conspicuous, and less likely to be identified by CAD than those in symptomatic patients.Key points• Screen-detected colorectal cancers (CRC) are significantly smaller than symptomatic CRC. • Screening cases are significantly less conspicuous to radiologists than symptomatic tumours. • Screen-detected CRC have different morphology compared to symptomatic tumours (more polypoid, fewer annular). • A commercial computer-aided detection (CAD) system was significantly less likely to note screen-detected CRC.

Dataset Information

CT colonography: size reduction of submerged colorectal polyps due to electronic cleansing and CT-window settings.

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CT colonography: size reduction of submerged colorectal polyps due to electronic cleansing and CT-window settings.

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