Title :
Quantitative Analysis of Bladder Wall Thickness for Magnetic Resonance Cystoscopy
Author :
Xi Zhang ; Yang Liu ; Zengyue Yang ; Qiang Tian ; Guopeng Zhang ; Dan Xiao ; Guangbin Cui ; Hongbing Lu
Author_Institution :
Dept. of Biomed. Eng., Fourth Mil. Med. Univ., Xi´an, China
Abstract :
Objective: To find an effective way for quantitative evaluation on wall thickness variation of human bladder with/without bladder tumor, a novel pipeline of thickness measurement and analysis for magnetic resonance (MR) cystography is proposed. Methods: After the acquisition of volumetric bladder images with a high-resolution T2-weighted 3-D sequence, the inner and outer borders of the bladder wall were segmented simultaneously by a coupled directional level-set method. Then, the bladder wall thickness (BWT) was estimated using the Laplacian method. To reducing the influence of individual variation and urine filling on wall thickness, a thickness normalization using Z-score is performed. Finally, a parametric surface mapping strategy was applied to map thickness distribution onto a unified sphere surface, for quantitative intra- and intersubject comparison between bladders of different shapes. Results: The proposed pipeline was tested with a database composed of MR bladder images acquired from 20 volunteers and 20 patients with bladder cancer. The results indicate that the thickness normalization step using Z-score makes the quantitative comparison of wall thickness quite possible and there is a significant difference on BWT between patients and volunteers. Using the proposed pipeline, we established a thickness template for a normal bladder wall based on dataset of all volunteers. Conclusion: As a first attempt to establish a general pipeline for bladder wall analysis, the presented work provides an effective way to achieve the goal of evaluating the entire bladder wall for detection and diagnosis of abnormality. In addition, it can be easily extended to quantitative analyses of other bladder features, such as, intensity-based or texture features.
Keywords :
biomedical MRI; cancer; edge detection; feature extraction; image resolution; image segmentation; image sequences; image texture; kidney; medical image processing; numerical analysis; thickness measurement; tumours; Laplacian method; bladder cancer; bladder tumor; bladder wall thickness measurement; coupled directional level-set method; high-resolution T2-weighted 3D sequence; intensity-based features; magnetic resonance cystoscopy; parametric surface mapping strategy; texture features; urine filling; volumetric bladder image acquisition; volumetric bladder image segmentation; Bladder; Cancer; Filling; Laplace equations; Pipelines; Shape; Three-dimensional displays; 3-D bladder template; 3D bladder template; Bladder cancer; T2-weighted MRI; T2-weighted magnetic resonance image (MRI); bladder cancer; bladder wall segmentation; bladder wall thickness; bladder wall thickness (BWT); shape mapping;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2015.2429612