Article

Three-dimensional MRI of the male urethrae with implanted artificial sphincters: initial results.

Department of Medical Physics and Bioengineering, University College London, Gower Street, London WC1E 6BT, UK.
British Journal of Radiology (impact factor: 1.31). 07/2006; 79(942):455-63. DOI:10.1259/bjr/56511504 pp.455-63
Source: PubMed

ABSTRACT The aim of this study was to develop a method for simultaneous 3D visualization of a new type of artificial urethral sphincter (AUS) and adjacent urinary structures. Serial MR tomograms were acquired from seven men after AUS implantation. 3D reconstruction was performed by thresholding original (positive) and inverted (negative) image intensity and by subsequently fusing positive and negative images. Results show that the bladder, cuff and balloons of the AUS of originally high intensity were imaged in 3D by thresholding the positive datasets. The urethrae and corpora cavernosa penis of originally low intensity were displayed in 3D by thresholding the negative datasets. Fusion of the positive and negative datasets allowed simultaneous visualization of the AUS complex and adjacent urinary structures. All the structures of interest were also clearly seen by interactive multiplanar reformatting. Coronal tomographic datasets provided better 3D and reformatted 2D images than sagittal and transverse datasets. This technique offers a simple means for evaluating the complex urethral anatomy and the AUS, and has potential for improved 3D visualization of many other complex morphological and pathological conditions.

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Keywords

3D reconstruction
 
3D visualization
 
adjacent urinary structures
 
artificial urethral sphincter
 
AUS implantation
 
complex morphological
 
Coronal tomographic datasets
 
corpora cavernosa penis
 
fusing positive
 
interactive multiplanar reformatting
 
low intensity
 
negative datasets
 
negative images
 
new type
 
positive datasets
 
reformatted 2D images
 
Serial MR tomograms
 
simultaneous 3D visualization
 
thresholding original
 
transverse datasets