A novel semi-automatic segmentation method for volumetric assessment of the colon based on magnetic resonance imaging

PurposeTo develop a novel semi-automatic segmentation method for quantification of the colon from magnetic resonance imaging (MRI).MethodsFourteen abdominal T2-weighted and dual-echo Dixon-type water-only MRI scans were obtained from four healthy subjects. Regions of interest containing the colon were outlined manually on the T2-weighted images. Segmentation of the colon and feces was obtained using k-means clustering and image registration. Regional colonic and fecal volumes were obtained. Inter-observer agreement between two observers was assessed using the Dice similarity coefficient as measure of overlap.ResultsColonic segmentations showed wide variation in volume and morphology between subjects. Colon volumes of the four healthy subjects for both observers were (median [interquartile range]) ascending colon 200 mL [169.5–260], transverse 200.5 mL [113.5–242.5], descending 148 mL [121.5–178.5], sigmoid-rectum 277 mL [192–345], and total 819 mL [687–898.5]. Overlap agreement for the total colon segmentation between the two observers was high with a Dice similarity coefficient of 0.91 [0.84–0.94]. The colon volume to feces volume ratio was on average 0.7.ConclusionRegional colon volumes were comparable to previous findings using fully manual segmentation. The method showed good agreement between observers and may be used in future studies of gastrointestinal disorders to assess colon and fecal volume and colon morphology. Novel insight into morphology and quantitative assessment of the colon using this method may provide new biomarkers for constipation and abdominal pain compared to radiography which suffers from poor reliability.

[1]  K. Garsed,et al.  Stimulation of colonic motility by oral PEG electrolyte bowel preparation assessed by MRI: comparison of split vs single dose , 2014, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[2]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[3]  Bostjan Likar,et al.  A Review of Methods for Correction of Intensity Inhomogeneity in MRI , 2007, IEEE Transactions on Medical Imaging.

[4]  S. Laurberg,et al.  Cortical evoked potentials in response to rapid balloon distension of the rectum and anal canal , 2014, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[5]  C. Lam,et al.  Differential Effects of FODMAPs (Fermentable Oligo-, Di-, Mono-Saccharides and Polyols) on Small and Large Intestinal Contents in Healthy Subjects Shown by MRI , 2013, The American Journal of Gastroenterology.

[6]  Lixu Gu,et al.  An Automatic and Fast Centerline Extraction Algorithm for Virtual Colonoscopy , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[7]  R. Kavlock,et al.  Ambulatory 24-Hour Colonic Manometry in Slow-Transit Constipation , 2004, American Journal of Gastroenterology.

[8]  Jingfei Ma,et al.  Breath‐hold water and fat imaging using a dual‐echo two‐point dixon technique with an efficient and robust phase‐correction algorithm , 2004, Magnetic resonance in medicine.

[9]  Erlend Hodneland,et al.  Semi-automated segmentation of the sigmoid and descending colon for radiotherapy planning using the fast marching method , 2010, Physics in medicine and biology.

[10]  J. Bartko Measurement and reliability: statistical thinking considerations. , 1991, Schizophrenia bulletin.

[11]  David H. Kim,et al.  Colorectal anatomy in adults at computed tomography colonography: normal distribution and the effect of age, sex, and body mass index , 2009, Endoscopy.

[12]  Lin Lu,et al.  An improved method of automatic colon segmentation for virtual colon unfolding , 2013, Comput. Methods Programs Biomed..

[13]  Stefan Klein,et al.  Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease , 2013, Front. Neuroinform..

[14]  Benoit M. Dawant,et al.  Morphometric analysis of white matter lesions in MR images: method and validation , 1994, IEEE Trans. Medical Imaging.

[15]  Yaorong Ge,et al.  Segmentation in virtual colonoscopy using a geometric deformable model , 2006, Comput. Medical Imaging Graph..

[16]  J. Armstrong,et al.  Are abdominal x-rays a reliable way to assess for constipation? , 2010, The Journal of urology.

[17]  K. Garsed,et al.  Effect of experimental stress on the small bowel and colon in healthy humans , 2015, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[18]  D J Vining,et al.  Automatic segmentation of the colon for virtual colonoscopy. , 2000, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[19]  Mark Mandelkern,et al.  An automatic method for colon segmentation in CT colonography , 2009, Comput. Medical Imaging Graph..

[20]  Ronald M. Summers,et al.  Hybrid segmentation of colon filled with air and opacified fluid for CT colonography , 2006, IEEE Transactions on Medical Imaging.

[21]  G. Kiss,et al.  Computer-aided detection for CT colonography: update 2007 , 2007, Abdominal Imaging.

[22]  Max A. Viergever,et al.  elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.

[23]  S. Steele,et al.  Constipation and obstructed defecation. , 2007, Clinics in colon and rectal surgery.

[24]  James Kozloski,et al.  Self-referential forces are sufficient to explain different dendritic morphologies , 2013, Front. Neuroinform..

[25]  C L Hoad,et al.  Fasting and postprandial volumes of the undisturbed colon: normal values and changes in diarrhea-predominant irritable bowel syndrome measured using serial MRI , 2013, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[26]  A. Ahmadian,et al.  An Efficient Colon Segmentation method for Oral Contrast-Enhanced CT Colonography , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[27]  L. R. Dice Measures of the Amount of Ecologic Association Between Species , 1945 .

[28]  Jaap Stoker,et al.  A computer-assisted model for detection of MRI signs of Crohn’s disease activity: future or fiction? , 2011, Abdominal Imaging.

[29]  S. Preston,et al.  Bowel preparation affects the amplitude and spatiotemporal organization of colonic propagating sequences , 2010, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[30]  Bin Li,et al.  A novel approach to extract colon lumen from CT images for virtual colonoscopy , 2000, IEEE Transactions on Medical Imaging.

[31]  Jeih-San Liow,et al.  Qualitative and Quantitative Evaluation of Six Algorithms for Correcting Intensity Nonuniformity Effects , 2001, NeuroImage.