Title
Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approach.
Abstract
Magnetic resonance imaging (MRI) is often used in clinical practice to stage patients with bladder cancer to help plan treatment. However, qualitative assessment of MR images is prone to inaccuracies, adversely affecting patient outcomes. In this paper, T2-weighted MR image-based quantitative features were extracted from the bladder wall in 65 patients with bladder cancer to classify them into two primary tumor (T) stage groups: group 1 - T stage <= T2, with primary tumor locally confined to the bladder, and group 2 -T stage > T2, with primary tumor locally extending beyond the bladder. The bladder was divided into 8 sectors in the axial plane, where each sector has a corresponding reference standard T stage that is based on expert radiology qualitative MR image review and histopathologic results. The performance of the classification for correct assignment of T stage grouping was then evaluated at both the patient level and the sector level. Each bladder sector was divided into 3 shells (inner, middle, and outer), and 15,834 features including intensity features and texture features from local binary pattern and gray-level co-occurrence matrix were extracted from the 3 shells of each sector. An optimal feature set was selected from all features using an optimal biomarker approach. Nine optimal biomarker features were derived based on texture properties from the middle shell, with an area under the ROC curve of AUC value at the sector and patient level of 0.813 and 0.806, respectively.
Year
DOI
Venue
2018
10.1117/12.2294550
Proceedings of SPIE
Keywords
DocType
Volume
Optimal biomarker approach,feature extraction,bladder cancer staging,magnetic resonance imaging (MRI)
Conference
10575
ISSN
Citations 
PageRank 
0277-786X
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
chuang wang1167.40
Jayaram K. Udupa22481322.29
Yubing Tong39322.73
Jerry Chen401.35
Sriram Venigalla500.34
Dewey Odhner633943.49
Thomas J. Guzzo700.34
John Christodouleas800.34
D. A. Torigian98121.68