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Analyzing the curvature of the colon in different patient positions
Author(s): Jacob Laframboise; Tamas Ungi; Andras Lasso; Mark Asselin; Matthew S. Holden; Pearl Tan; Lawrence Hookey; Gabor Fichtinger
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Paper Abstract

Purpose: Colonoscopy is a complex procedure with considerable variation among patients, requiring years of experience to become proficient. Understanding the curvature of colons could enable practitioners to be more effective. The purpose of this research is to develop methods to analyze the curvature of patients’ colons, and compare key segments of colons between supine and prone positions. Methods: The colon lumen in CT scans of ten patients are segmented. The following steps are automated by Python scripts in the 3D Slicer application: a set of center points along the colon are generated, and a curve is fit to these points. By identifying local maximums and local minimums in curvature, curves can be defined between two local curvature minimums. The angle of each curve is calculated over the distance of curves. Results: This automated process was used to identify and quantitatively analyze curves on the colon centerline in different patient positions. On average, there are 4.6 ± 3.8 more curves in supine position than prone. In the descending colon, there are more curves in the supine position, but curves in the prone position are larger. Conclusion: This process can quantify the curvature of colons, and can be adapted to consider other patient groups. Descriptive statistics indicate supine position has more curves in the descending colon, and prone has sharper curves in the descending colon. These preliminary results motivate further work with a larger sample size, which may reveal additional significant differences.

Paper Details

Date Published: 8 March 2019
PDF: 8 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109512F (8 March 2019); doi: 10.1117/12.2512455
Show Author Affiliations
Jacob Laframboise, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Tamas Ungi, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Andras Lasso, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Mark Asselin, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Matthew S. Holden, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)
Pearl Tan, Gastrointestinal Disease Research Unit, Queen's Univ. (Canada)
Lawrence Hookey, Gastrointestinal Disease Research Unit, Queen's Univ. (Canada)
Gabor Fichtinger, Lab. for Percutaneous Surgery, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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