Paper Info
Title
Reference-tissue correction of T2-weighted signal intensity for prostate cancer detection
Abstract
The purpose of this study was to investigate whether correction with respect to reference tissue of T-2-weighted MR-image signal intensity (SI) improves its effectiveness for classification of regions of interest (ROIs) as prostate cancer (PCa) or normal prostatic tissue. Two image datasets collected retrospectively were used in this study: 71 cases acquired with GE scanners (dataset A), and 59 cases acquired with Philips scanners (dataset B). Through a consensus histology-MR correlation review, 175 PCa and 108 normal-tissue ROIs were identified and drawn manually. Reference-tissue ROIs were selected in each case from the levator ani muscle, urinary bladder, and pubic bone. T-2-weighted image SI was corrected as the ratio of the average T-2-weighted image SI within an ROI to that of a reference-tissue ROI. Area under the receiver operating characteristic curve (AUC) was used to evaluate the effectiveness of T-2-weighted image SIs for differentiation of PCa from normal-tissue ROIs. AUC (+/- standard error) for uncorrected T-2-weighted image SIs was 0.78 +/- 0.04 (datasets A) and 0.65 +/- 0.05 (datasets B). AUC for corrected T-2-weighted image SIs with respect to muscle, bladder, and bone reference was 0.77 +/- 0.04 (p=1.0), 0.77 +/- 0.04 (p=1.0), and 0.75 +/- 0.04 (p=0.8), respectively, for dataset A; and 0.81 +/- 0.04 (p=0.002), 0.78 +/- 0.04 (p<0.001), and 0.79 +/- 0.04 (p<0.001), respectively, for dataset B. Correction in reference to the levator ani muscle yielded the most consistent results between GE and Phillips images. Correction of T-2-weighted image SI in reference to three types of extra-prostatic tissue can improve its effectiveness for differentiation of PCa from normal-tissue ROIs, and correction in reference to the levator ani muscle produces consistent T-2-weighted image SIs between GE and Phillips MR images.
Year
DOI
Venue
2014
10.1117/12.2043585
Proceedings of SPIE
Keywords
Field
DocType
magnetic resonance (MR) imaging,prostate cancer,T-2-weighted imaging,reference tissue,correction
Nuclear medicine,Computer vision,Receiver operating characteristic,Correlation,Artificial intelligence,Prostate,Prostate cancer,Urinary bladder,Standard error,Principal component analysis,Magnetic resonance imaging,Physics
Conference
Volume
ISSN
Citations 
9035
0277-786X
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
yahui peng1198.60
Yulei Jiang2808.90
Aytekin Oto3596.59