title: Quantitative assessment of colorectal morphology: Implications for robotic colonoscopy.
abstract: This paper presents a method of characterizing the distribution of colorectal morphometrics. It uses three-dimensional region growing and topological thinning algorithms to determine and visualize the luminal volume and centreline of the colon, respectively. Total and segmental lengths, diameters, volumes, and tortuosity angles were then quantified. The effects of body orientations on these parameters were also examined. Variations in total length were predominately due to differences in the transverse colon and sigmoid segments, and did not significantly differ between body orientations. The diameter of the proximal colon was significantly larger than the distal colon, with the largest value at the ascending and cecum segments. The volume of the transverse colon was significantly the largest, while those of the descending colon and rectum were the smallest. The prone position showed a higher frequency of high angles and consequently found to be more torturous than the supine position. This study yielded a method for complete segmental measurements of healthy colorectal anatomy and its tortuosity. The transverse and sigmoid colons were the major determinant in tortuosity and morphometrics between body orientations. Quantitative understanding of these parameters may potentially help to facilitate colonoscopy techniques, accuracy of polyp spatial distribution detection, and design of novel endoscopic devices.
authors.affiliation: Institute of Functional Surfaces (iFS), School of Mechanical Engineering, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK. Electronic address: a.alazmani@leeds.ac.uk.
authors.forename: A
authors.initials: A
authors.lastname: Alazmani
authors.affiliation: Academic Surgical Unit, St. James's University Hospital, Leeds LS9 7TF, UK.
authors.forename: A
authors.initials: A
authors.lastname: Hood
authors.affiliation: Academic Surgical Unit, St. James's University Hospital, Leeds LS9 7TF, UK.
authors.forename: D
authors.initials: D
authors.lastname: Jayne
authors.affiliation: Institute of Functional Surfaces (iFS), School of Mechanical Engineering, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK.
authors.forename: A
authors.initials: A
authors.lastname: Neville
authors.affiliation: Institute of Engineering Systems and Design, School of Mechanical Engineering, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK.
authors.forename: P
authors.initials: P
authors.lastname: Culmer
mesh_terms: D058070:Asymptomatic Diseases; D003106:Colon / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D003113:Colonoscopy / Q000295:instrumentation*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D016684:Prone Position; D012007:Rectum; D012371:Robotics; D016683:Supine Position; D014057:Tomography, X-Ray Computed
keywords: Colon; Colorectal cancer; Large intestine; Robotic colonoscopy