Computed tomography colonography compared with conventional colonoscopy for the detection of colorectal polyps

2007 ◽  
Vol 30 (7) ◽  
pp. 375-380 ◽  
Author(s):  
María Chaparro Sánchez ◽  
Lourdes del Campo Val ◽  
José Maté Jiménez ◽  
José Cantero Perona ◽  
Antonio Barbosa ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Colorectal Polyps ◽  
Conventional Colonoscopy ◽  
Computed Tomography Colonography

Machine Learning for Automated Polyp Detection in Computed Tomography Colonography

2012 ◽  
pp. 830-850
Author(s):  
Abhilash Alexander Miranda ◽  
Olivier Caelen ◽  
Gianluca Bontempi
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
False Positive ◽  
False Positive Rate ◽  
Learning Algorithms ◽  
Colorectal Polyps ◽  
Machine Learning Algorithms ◽  
Computed Tomography Colonography ◽  
Positive Rate ◽  
Independent Features

This chapter presents a comprehensive scheme for automated detection of colorectal polyps in computed tomography colonography (CTC) with particular emphasis on robust learning algorithms that differentiate polyps from non-polyp shapes. The authors’ automated CTC scheme introduces two orientation independent features which encode the shape characteristics that aid in classification of polyps and non-polyps with high accuracy, low false positive rate, and low computations making the scheme suitable for colorectal cancer screening initiatives. Experiments using state-of-the-art machine learning algorithms viz., lazy learning, support vector machines, and naïve Bayes classifiers reveal the robustness of the two features in detecting polyps at 100% sensitivity for polyps with diameter greater than 10 mm while attaining total low false positive rates, respectively, of 3.05, 3.47 and 0.71 per CTC dataset at specificities above 99% when tested on 58 CTC datasets. The results were validated using colonoscopy reports provided by expert radiologists.

scholarly journals Performance of multidetector computed tomography colonography compared with conventional colonoscopy

Gut ◽  
2002 ◽  
Vol 51 (2) ◽  
pp. 207-211 ◽  
Author(s):  
T. Gluecker ◽  
G Dorta ◽  
W Keller ◽  
P Jornod ◽  
R Meuli ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Multidetector Computed Tomography ◽  
Conventional Colonoscopy ◽  
Computed Tomography Colonography

Diagnostic performance of computed tomography colonography and colonoscopy: a prospective and validated analysis of 231 paired examinations

2007 ◽  
Vol 48 (8) ◽  
pp. 831-837 ◽  
Author(s):  
R. B. Arnesen ◽  
E. von Benzon ◽  
S. Adamsen ◽  
L. B. Svendsen ◽  
H. O. Raaschou ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Diagnostic Performance ◽  
Helical Ct ◽  
Cost Effective ◽  
Colorectal Polyps ◽  
Low Grade ◽  
Ct Scanner ◽  
Computed Tomography Colonography ◽  
First Choice ◽  
Effective Use

Background: Detection of colorectal tumors with computed tomography colonography (CTC) is an alternative to conventional colonoscopy (CC), and clarification of the diagnostic performance is essential for cost-effective use of both technologies. Purpose: To evaluate the diagnostic performance of CTC compared with CC. Material and Methods: 231 consecutive CTCs were performed prior to same-day scheduled CC. The radiologist and endoscopists were blinded to each other's findings. Patients underwent a polyethylene glycol bowel preparation, and were scanned in prone and supine positions using a single-detector helical CT scanner and commercially available software for image analysis. Findings were validated (matched) in an unblinded comparison with video-recordings of the CCs and re-CCs in cases of doubt. Results: For patients with polyps ⩾5 mm and ⩾10 mm, the sensitivity was 69% (95% CI 58–80%) and 81% (68–94%), and the specificity was 91% (84–98%) and 98% (93–100%), respectively. For detection of polyps ⩾5 mm and ⩾10 mm, the sensitivity was 66% (57–75%) and 77% (65–89%). A flat, elevated low-grade carcinoma was missed by CTC. One cancer relapse was missed by CC, and a cecal cancer was missed by an incomplete CC and follow-up double-contrast barium enema. Conclusion: CC was superior to CTC and should remain first choice for the diagnosis of colorectal polyps. However, for diagnosis of lesions ⩾10 mm, CTC and CC should be considered as complementary methods.

Machine Learning for Automated Polyp Detection in Computed Tomography Colonography

2010 ◽  
pp. 54-77
Author(s):  
Abhilash Alexander Miranda ◽  
Olivier Caelen ◽  
Gianluca Bontempi
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
False Positive ◽  
False Positive Rate ◽  
Learning Algorithms ◽  
Colorectal Polyps ◽  
Machine Learning Algorithms ◽  
Computed Tomography Colonography ◽  
Positive Rate ◽  
Independent Features

This chapter presents a comprehensive scheme for automated detection of colorectal polyps in computed tomography colonography (CTC) with particular emphasis on robust learning algorithms that differentiate polyps from non-polyp shapes. The authors’ automated CTC scheme introduces two orientation independent features which encode the shape characteristics that aid in classification of polyps and non-polyps with high accuracy, low false positive rate, and low computations making the scheme suitable for colorectal cancer screening initiatives. Experiments using state-of-the-art machine learning algorithms viz., lazy learning, support vector machines, and naïve Bayes classifiers reveal the robustness of the two features in detecting polyps at 100% sensitivity for polyps with diameter greater than 10 mm while attaining total low false positive rates, respectively, of 3.05, 3.47 and 0.71 per CTC dataset at specificities above 99% when tested on 58 CTC datasets. The results were validated using colonoscopy reports provided by expert radiologists.

scholarly journals Single-center study comparing computed tomography colonography with conventional colonoscopy

2008 ◽  
Vol 14 (3) ◽  
pp. 469 ◽  
Author(s):  
Ian C Roberts-Thomson ◽  
Graeme R Tucker ◽  
Peter J Hewett ◽  
Peter Cheung ◽  
Ruben A Sebben ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Conventional Colonoscopy ◽  
Single Center ◽  
Computed Tomography Colonography ◽  
Single Center Study ◽  
Center Study

scholarly journals Computed Tomography Colonography as a Sensible Option for Colorectal Cancer Screening: Evidence Based on Metanalysis

2021 ◽  
Vol 41 (01) ◽  
pp. 087-095
Author(s):  
Ingrid Chaves de Souza Borges ◽  
Natália Costa Resende Cunha ◽  
Amanda Marsiaj Rassi ◽  
Marcela Garcia de Oliveira ◽  
Jacqueline Andréia Bernardes Leão-Cordeiro ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Computed Tomography ◽  
Cancer Screening ◽  
Literature Search ◽  
Web Of Science ◽  
Screening Method ◽  
Colorectal Polyp ◽  
Evidence Based ◽  
Polyp Detection ◽  
Computed Tomography Colonography

Abstract Objective This metanalysis aimed to evaluate the sensitivity and specificity of computed tomography colonography in colorectal polyp detection. Methods A literature search was performed in the PubMed and Web of Science databases. Results A total of 1,872 patients (males 57.2%, females 42.8%) aged 49 to 82 years old (mean age 59.7 ± 5.3 years) were included in this metanalysis. The estimated sensitivity of computed tomography colonography was 88.4% (46.3–95.7%, coefficient of variation [CV] = 28.5%) and the estimated specificity was 73.6% (47.4–100.0%, CV = 37.5%). For lesions up to 9 mm, the sensitivity was 82.5% (62.0–99.9%, CV = 25.1%) and the specificity was 79.2% (32.0–98.0%, CV = 22.9%). For lesions > 9 mm, the sensitivity was 90.2% (64.0–100.0%, CV = 7.4%) and the specificity was 94.7% (80.0–100.0%, CV = 6.2%). No statistically significant differences in sensitivity according to the size of the lesion were found (p = 0.0958); however, the specificity was higher for lesions > 9 mm (p < 0.0001). Conclusions Most of the studies analyzed in the present work were conducted before 2010, which is about a decade after computed tomography colonography started being indicated as a screening method by European and American guidelines. Therefore, more studies aimed at analyzing the technique after further technological advancements are necessary, which could lead to the development of more modern devices.

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