CT colonography: optimisation, diagnostic performance and patient acceptability of reduced-laxative regimens using barium-based faecal tagging.
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ABSTRACT:
SUBMITTER: Taylor SA
PROVIDER: S-EPMC2220024 | biostudies-other | 2008 Jan
REPOSITORIES: biostudies-other
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Project description:The purpose of this study is to determine whether Barium or BariumFerumoxsil is better for fecal tagging in MR colonography. Patients referred to colonoscopy are offered MR colonography before colonoscopy. Two days before colonography, patients ingest either a contrast agent A (200 ml Barium sulphate solution 1g/ml)) four times a day or a 200 ml contrast agent B (Barium sulfate(25%) and Ferumoxil(75%)) four times a day, which will render fecal masses "invisible" on the following MR colonography. The patients are randomised to either contrast agent A or B. The examinations are evaluated by two independent blinded readers, who will rate the tagging quality of the contrast agents. The quality of tagging will be rated by a Visual Analog Scale (VAS) and Relative contrast (ReCon = Iwall - Ilumen/ Iwall + Ilumen).
| 2029447 | ecrin-mdr-crc
Project description:Electronic cleansing (EC) is an emerging technique for the removal of tagged fecal materials at fecal-tagging computed tomographic (CT) colonography. However, existing EC methods may generate various types of artifacts that severely impair the quality of the cleansed CT colonographic images. Dual-energy fecal-tagging CT colonography is regarded as a next-generation imaging modality. EC that makes use of dual-energy fecal-tagging CT colonographic images promises to be effective in reducing cleansing artifacts by means of applying the material decomposition capability of dual-energy CT. The dual-energy index (DEI), which is calculated from the relative change in the attenuation values of a material at two different photon energies, is a reliable and effective indicator for differentiating tagged fecal materials from various types of tissues on fecal-tagging CT colonographic images. A DEI-based dual-energy EC scheme uses the DEI to help differentiate the colonic lumen-including the luminal air, tagged fecal materials, and air-tagging mixture-from the colonic soft-tissue structures, and then segments the entire colonic lumen for cleansing of the tagged fecal materials. As a result, dual-energy EC can help identify partial-volume effects in the air-tagging mixture and inhomogeneous tagging in residual fecal materials, the major causes of EC artifacts. This technique has the potential to significantly improve the quality of EC and promises to provide images of a cleansed colon that are free of the artifacts commonly observed with conventional single-energy EC methods.
| S-EPMC3654226 | biostudies-other
Project description:To assess the variation in diagnostic performance among radiologists at screening computed tomographic (CT) colonography.In this HIPAA-compliant, institutional review board-approved study, 6866 asymptomatic adults underwent first-time CT colonographic screening at a single center between January 2005 and November 2011. Results of examinations were interpreted by one of eight board-certified abdominal radiologists (mean number of CT colonographic studies per reader, 858; range, 131-2202). Findings at CT colonography and subsequent colonoscopy were recorded, and key measures of diagnostic performance, including adenoma and advanced neoplasia detection rate, were compared among the radiologists.The overall prevalence of histopathologically confirmed advanced neoplasia was 3.6% and did not differ significantly among radiologists (range, 2.4%-4.4%; P = .067; P = .395 when one outlier was excluded). Overall, 19.5% of polyps detected at CT colonography proved to be advanced neoplasia and did not differ significantly among radiologists (range, 14.4%-23.2%; P = .223). The overall per-polyp endoscopic confirmation rate was 93.5%, ranging from 80.0% to 97.6% among radiologists (P = .585). The overall percentage of nondiagnostic CT colonographic examinations was 0.7% and was consistent among radiologists (range, 0.3%-1.1%; P = .509).Consistent performance for adenoma and advanced neoplasia detection, as well as other clinically relevant end points, were observed among radiologists at CT colonographic screening.
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Project description:To ascertain which of four combinations of low residue diet, reduced laxative dose and oral contrast agent is best tolerated by patients and optimally prepares the colon prior ro CT colonography
| 2020435 | ecrin-mdr-crc
Project description:PurposeTo prospectively compare adequacy of colonic cleansing, adequacy of solid stool and fluid tagging, and patient acceptance by using reduced-volume, 2-L polyethylene glycol (PEG) versus magnesium citrate bowel preparations for CT colonography.Materials and methodsThis study was approved by the institutional Committee on Human Research and was compliant with HIPAA; all patients provided written consent. In this randomized, investigator-blinded study, 50 patients underwent oral preparation with either a 2-L PEG or a magnesium citrate solution, tagging with oral contrast agents, and subsequent CT colonography and segmentally unblinded colonoscopy. The residual stool (score 0 [best] to 3 [worst]) and fluid (score 0 [best] to 4 [worst]) burden and tagging adequacy were qualitatively assessed. Residual fluid attenuation was recorded as a quantitative measure of tagging adequacy. Patients completed a tolerance questionnaire within 2 weeks of scanning. Preparations were compared for residual stool and fluid by using generalized estimating equations; the Mann-Whitney test was used to compare the qualitative tagging score, mean residual fluid attenuation, and adverse effects assessed on the patient experience questionnaire.ResultsThe mean residual stool (0.90 of three) and fluid burden (1.05 of four) scores for PEG were similar to those for magnesium citrate (0.96 [P = .58] and 0.98 [P = .48], respectively). However, the mean fecal and fluid tagging scores were significantly better for PEG (0.48 and 0.28, respectively) than for magnesium citrate (1.52 [P < .01] and 1.28 [P < .01], respectively). Mean residual fluid attenuation was higher for PEG (765 HU) than for magnesium citrate (443 HU, P = .01), and mean interpretation time was shorter for PEG (14.8 minutes) than for magnesium citrate (18.0 minutes, P = .04). Tolerance ratings were not significantly different between preparations.ConclusionReduced-volume PEG and magnesium citrate bowel preparations demonstrated adequate cleansing effectiveness for CT colonography, with better tagging and shorter interpretation time observed in the PEG group. Adequate polyp detection was maintained but requires further validation because of the small number of clinically important polyps.
| S-EPMC3176421 | biostudies-literature
Project description:PurposeTo evaluate the ability of additional analysis of computed tomographic (CT) colonography images to provide a comprehensive osteoporosis assessment.Materials and methodsThis Health Insurance Portability and Accountability Act-compliant study was approved by our institutional review board with a waiver of informed consent. Diagnosis of osteoporosis and assessment of fracture risk were compared between biomechanical CT analysis and dual-energy x-ray absorptiometry (DXA) in 136 women (age range, 43-92 years), each of whom underwent CT colonography and DXA within a 6-month period (between January 2008 and April 2010). Blinded to the DXA data, biomechanical CT analysis was retrospectively applied to CT images by using phantomless calibration and finite element analysis to measure bone mineral density and bone strength at the hip and spine. Regression, Bland-Altman, and reclassification analyses and paired t tests were used to compare results.ResultsFor bone mineral density T scores at the femoral neck, biomechanical CT analysis was highly correlated (R(2) = 0.84) with DXA, did not differ from DXA (P = .15, paired t test), and was able to identify osteoporosis (as defined by DXA), with 100% sensitivity in eight of eight patients (95% confidence interval [CI]: 67.6%, 100%) and 98.4% specificity in 126 of 128 patients (95% CI: 94.5%, 99.6%). Considering both the hip and spine, the classification of patients at high risk for fracture by biomechanical CT analysis--those with osteoporosis or "fragile bone strength"--agreed well against classifications for clinical osteoporosis by DXA (T score ?-2.5 at the hip or spine), with 82.8% sensitivity in 24 of 29 patients (95% CI: 65.4%, 92.4%) and 85.7% specificity in 66 of 77 patients (95% CI: 76.2%, 91.8%).ConclusionRetrospective biomechanical CT analysis of CT colonography for colorectal cancer screening provides a comprehensive osteoporosis assessment without requiring changes in imaging protocols.
| S-EPMC4699492 | biostudies-literature
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.
| S-EPMC5101282 | biostudies-literature
Project description:PurposeTo compare the Medicare population cost of colorectal cancer (CRC) screening of average risk individuals by CT colonography (CTC) vs. optical colonoscopy (OC).MethodsThe authors used Medicare claims data, fee schedules, established protocols, and other sources to estimate CTC and OC per-screen costs, including the costs of OC referrals for a subset of CTC patients. They then modeled and compared the Medicare costs of patients who complied with CTC and OC screening recommendations and tested alternative scenarios.ResultsCTC is 29% less expensive than OC for the Medicare population in the base scenario. Although the CTC cost advantage is increased or reduced under alternative scenarios, it is always positive.ConclusionCTC is a cost-effective CRC screening option for the Medicare population and will likely reduce Medicare expenditures for CRC screening.
| S-EPMC4628615 | biostudies-literature
Project description:Purpose. The purpose of this study was to evaluate the technical and diagnostic performance of sub-milliSievert ultralow-dose (ULD) CT colonograpy (CTC) in the detection of colonic and extracolonic lesions. Materials and Methods. CTC with standard dose (SD) and ULD acquisitions of 64 matched patients, half of them with colonic findings, were reconstructed with filtered back projection (FBP), hybrid (HIR) and iterative model reconstruction techniques (IMR). Image noise in six colonic segments, in the left psoas muscle and aorta were measured. Image quality of the left adrenal gland and of the colon in the endoscopic and 2D view was rated on a five point Likert scale by two observers, who also completed the reading of CTC for colonic and extracolonic findings. Results. The mean radiation dose estimate was 4.1 ± 1.4 mSv for SD and 0.86 ± 0.17 mSv for ULD for both positions (p < 0.0001). In ULD-IMR, SD-IMR and SD-HIR, the endoluminal noise was decreased in all colonic segments compared to SD-FBP (p < 0.001). There were 27 small (6-9 mm) and 17 large (≥10 mm) colonic lesions that were classified as sessile polyps (n = 38), flat lesions (n = 3), or as a mass (n = 3). Per patient sensitivity and specificity were 0.82 and 0.93 for ULD-FBP, 0.97 and 0.97 for ULD-HIR, 0.97 and 1.0 for ULD-IMR. Per polyp sensitivity was 0.84 for ULD-FBP, 0.98 for ULD-HIR, 0.98 for ULD-IMR. Significantly less extracolonic findings were detected in ULD-FBP and ULD-HIR, but in the E4 category by C-RADS (potentially important findings), the detection was similar. Conclusion. Both HIR and IMR are suitable for sub-milliSievert ULD CTC without sacrificing diagnostic performance of the study.
| S-EPMC4824919 | biostudies-literature
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.
| S-EPMC9213389 | biostudies-literature