Development of a synthetic phantom for the selection of optimal scanning parameters in CAD-CT colonography

The aim of this paper is to present the development of a synthetic phantom that can be used for the selection of optimal scanning parameters in computed tomography (CT) colonography. In this paper we attempt to evaluate the influence of the main scanning parameters including slice thickness, reconstruction interval, field of view, table speed and radiation dose on the overall performance of a computer aided detection (CAD)–CTC system. From these parameters the radiation dose received a special attention, as the major problem associated with CTC is the patient exposure to significant levels of ionising radiation. To examine the influence of the scanning parameters we performed 51 CT scans where the spread of scanning parameters was divided into seven different protocols. A large number of experimental tests were performed and the results analysed. The results show that automatic polyp detection is feasible even in cases when the CAD–CTC system was applied to low dose CT data acquired with the following protocol: 13 mAs/rotation with collimation of 1.5 mm × 16 mm, slice thickness of 3.0 mm, reconstruction interval of 1.5 mm, table speed of 30 mm per rotation. The CT phantom data acquired using this protocol was analysed by an automated CAD–CTC system and the experimental results indicate that our system identified all clinically significant polyps (i.e. larger than 5 mm)

A novel technique for reducing false positive detections in CAD-CTC

Computed tomography colonoscopy (CTC) is an emerging alternative to conventional colonoscopy for colorectal cancer screening. A series of computer assisted diagnosis (CAD) techniques have been developed for use in CTC. Although high levels of accuracy for polyp detection have been reported, the problem of excessive false positive detections still warrants attention. We present a CAD-CTC technique that has been developed specifically to reduce the number of false positive detections without compromising polyp detection accuracy. The technique incorporates a novel intermediate stage that restructures initial polyp candidates so that they conform more closely to the shape of actual polyps. The restructuring process causes false positives to expand to include more false positive characteristics, whereas, actual polyps retain their original polyp-like characteristics. An evaluation of the documented technique demonstrated that it can be successfully applied to the majority of polyp candidates, and that its use can reduce the number of false positive detections by up to 57.8%

Multicenter, randomized study to optimize bowel for colon capsule endoscopy

AIM To assess the cleansing efficacy and safety of a new Colon capsule endoscopy (CCE) bowel preparation regimen. METHODS This was a multicenter, prospective, randomized, controlled study comparing two CCE regimens. Subjects were asymptomatic and average risk for colorectal cancer. The second generation CCE system (PillCam® COLON 2; Medtronic, Yoqneam, Israel) was utilized. Preparation regimens differed in the 1st and 2nd boosts with the Study regimen using oral sulfate solution (89 mL) with diatrizoate meglumine and diatrizoate sodium solution (“diatrizoate solution”) (boost 1 = 60 mL, boost 2 = 30 mL) and the Control regimen oral sulfate solution (89 mL) alone. The primary outcome was overall and segmental colon cleansing. Secondary outcomes included safety, polyp detection, colonic transit, CCE completion and capsule excretion = 12 h. RESULTS Both regimens had similar cleansing efficacy for the whole colon (Adequate: Study = 75.9%, Control = 77.3%; P = 0.88) and individual segments. In the Study group, CCE completion was superior (Study = 90.9%, Control = 76.9%; P = 0.048) and colonic transit was more often \u3c 40 min (Study = 21.8%, Control = 4%; P = 0.0073). More Study regimen subjects experienced adverse events (Study = 19.4%, Control = 3.4%; P = 0.0061), and this difference did not appear related to diatrizoate solution. Adverse events were primarily gastrointestinal in nature and no serious adverse events related either to the bowel preparation regimen or the capsule were observed. There was a trend toward higher polyp detection with the Study regimen, but this did not achieve statistical significance for any size category. Mean transit time through the entire gastrointestinal tract, from ingestion to excretion, was shorter with the Study regimen while mean colonic transit times were similar for both study groups. CONCLUSION A CCE bowel preparation regimen using oral sulfate solution and diatrizoate solution as a boost agent is effective, safe, and achieved superior CCE completion. © The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved

An Efficient Approach for Polyps Detection in Endoscopic Videos Based on Faster R-CNN

Polyp has long been considered as one of the major etiologies to colorectal cancer which is a fatal disease around the world, thus early detection and recognition of polyps plays a crucial role in clinical routines. Accurate diagnoses of polyps through endoscopes operated by physicians becomes a challenging task not only due to the varying expertise of physicians, but also the inherent nature of endoscopic inspections. To facilitate this process, computer-aid techniques that emphasize fully-conventional image processing and novel machine learning enhanced approaches have been dedicatedly designed for polyp detection in endoscopic videos or images. Among all proposed algorithms, deep learning based methods take the lead in terms of multiple metrics in evolutions for algorithmic performance. In this work, a highly effective model, namely the faster region-based convolutional neural network (Faster R-CNN) is implemented for polyp detection. In comparison with the reported results of the state-of-the-art approaches on polyps detection, extensive experiments demonstrate that the Faster R-CNN achieves very competing results, and it is an efficient approach for clinical practice.Comment: 6 pages, 10 figures,2018 International Conference on Pattern Recognitio

A fully automatic CAD-CTC system based on curvature analysis for standard and low-dose CT data

Computed tomography colonography (CTC) is a rapidly evolving noninvasive medical investigation that is viewed by radiologists as a potential screening technique for the detection of colorectal polyps. Due to the technical advances in CT system design, the volume of data required to be processed by radiologists has increased significantly, and as a consequence the manual analysis of this information has become an increasingly time consuming process whose results can be affected by inter- and intrauser variability. The aim of this paper is to detail the implementation of a fully integrated CAD-CTC system that is able to robustly identify the clinically significant polyps in the CT data. The CAD-CTC system described in this paper is a multistage implementation whose main system components are: 1) automatic colon segmentation; 2) candidate surface extraction; 3) feature extraction; and 4) classification. Our CAD-CTC system performs at 100% sensitivity for polyps larger than 10 mm, 92% sensitivity for polyps in the range 5 to 10 mm, and 57.14% sensitivity for polyps smaller than 5 mm with an average of 3.38 false positives per dataset. The developed system has been evaluated on synthetic and real patient CT data acquired with standard and low-dose radiation levels

Endoscopic Polyp Segmentation Using a Hybrid 2D/3D CNN

Colonoscopy is the gold standard for early diagnosis and pre-emptive treatment of colorectal cancer by detecting and removing colonic polyps. Deep learning approaches to polyp detection have shown potential for enhancing polyp detection rates. However, the majority of these systems are developed and evaluated on static images from colonoscopies, whilst applied treatment is performed on a real-time video feed. Non-curated video data includes a high proportion of low-quality frames in comparison to selected images but also embeds temporal information that can be used for more stable predictions. To exploit this, a hybrid 2D/3D convolutional neural network architecture is presented. The network is used to improve polyp detection by encompassing spatial and temporal correlation of the predictions while preserving real-time detections. Extensive experiments show that the hybrid method outperforms a 2D baseline. The proposed architecture is validated on videos from 46 patients. The results show that real-world clinical implementations of automated polyp detection can benefit from the hybrid algorithm

Factors associated with the efficacy of polyp detection during routine flexible sigmoidoscopy

Objective: Flexible sigmoidoscopy reduces the incidence of colonic cancer through the detection and removal of premalignant adenomas. However, the efficacy of the procedure is variable. The aim of the present study was to examine factors associated with the efficacy of detecting polyps during flexible sigmoidoscopy. Design and patients: Retrospective observational cohort study of all individuals undergoing routine flexible sigmoidoscopy in NHS Greater Glasgow and Clyde from January 2013 to January 2016. Results: A total of 7713 patients were included. Median age was 52 years and 50% were male. Polyps were detected in 1172 (13%) patients. On multivariate analysis, increasing age (OR 1.020 (1.016–1.023) p<0.001), male sex (OR 1.23 (1.10–1.38) p<0.001) and the use of any bowel preparation (OR 3.55 (1.47–8.57) p<0.001) were associated with increasing numbers of polyps being detected. There was no significant difference in the number of polyps found in patients who had received an oral laxative preparation compared with an enema (OR 3.81 (1.57–9.22) vs 3.45 (1.43–8.34)), or in those who received sedation versus those who had not (OR 1.00 vs 1.04 (0.91–1.17) p=0.591). Furthermore, the highest number of polyps was found when the sigmoidoscope was inserted to the descending colon (OR 1.30 (1.04–1.63)). Conclusions: Increasing age, male sex and the utilisation of any bowel preparation were associated with an increased polyp detection rate. However, the use of sedation or oral laxative preparation appears to confer no additional benefit. In addition, the results indicate that insertion to the descending colon optimises the efficacy of flexible sigmoidoscopy polyp detection