Share Email Print

Proceedings Paper

A Ktrans deep characterization to measure clinical significance regions on prostate cancer
Author(s): Yesid Gutiérrez; John Arevalo; Fabio Martínez
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Magnetic resonance imaging (MRI) plays a valuable role in many task related with characterization of prostate cancer lesions. Recently, the DCE-MRI (Dynamic contrast Enhanced) has allowed to visualize and localize potential tumor regions. Specifically, Ktrans, from DCR-MRI, has shown to be a powerful pharmacokinetic parameter that allows to characterize tumor biology and to detect treatment responses from reconstructed coefficient maps of capillary permeability. Nevertheless, even expert-based analysis of Ktrans sequences are subject to a large false positive findings (FPF). In much of such cases, the prostate angiogenesis, or benign prostatic hyperplasia (BPH) regions are misclassified as cancer findings. This work introduces a robust deep convolutional strategy that characterizes Ktrans regions and allows an automatic prediction of cancer findings. The proposed strategy was validated over the SPIE-AAPM-NCI PROSTATEx public dataset with 320 multimodal images on peripheral, transitional and anterior fibromuscular stroma regions. The best configuration of proposal strategy achieved an area under the ROC curve (AUC) of 0.74. Additionally, the proposed strategy achieved a proper characterization by using mainly Ktrans information that together with T2-MRI-transaxial overcome baseline strategies that use additional modalities of MRI.

Paper Details

Date Published: 3 January 2020
PDF: 9 pages
Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 113300C (3 January 2020); doi: 10.1117/12.2542606
Show Author Affiliations
Yesid Gutiérrez, Univ. Industrial de Santander (Colombia)
John Arevalo, Univ. Industrial de Santander (Colombia)
Fabio Martínez, Univ. Industrial de Santander (Colombia)

Published in SPIE Proceedings Vol. 11330:
15th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?