Tumor Growth Estimation via Registration of DCE-MRI Derived Tumor Specific Descriptors

被引:0
|
作者
Roque, Thais [1 ]
Papiez, Bartlomiej W. [1 ]
Kersemans, Veerle [2 ]
Smart, Sean [2 ]
Allen, Danny [2 ]
Chappell, Michael [1 ]
Schnabel, Julia A. [1 ,3 ]
机构
[1] Univ Oxford, Dept Engn Sci, Inst Biomed Engn, Oxford OX1 2JD, England
[2] Univ Oxford, Dept Oncol, Preclin Imaging Grp, Oxford OX1 2JD, England
[3] Kings Coll London, Div Imaging Sci & Biomed Engn, Dept Biomed Engn, London WC2R 2LS, England
基金
英国工程与自然科学研究理事会;
关键词
IMAGE REGISTRATION; MOTION CORRECTION; SEGMENTATION; DECOMPOSITION; MODELS;
D O I
10.1109/CVPRW.2016.70
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides information on changes occurring during tumor growth in the tumor micro-environment and vasculature. In the present paper, tumor voxel-wise estimates of tumor descriptors including total cell number, proliferative cell number, hypoxic cell number, necrotic cell number and oxygen level derived from DCE-MRI data are used to guide the deformable registration of subsequent time points over the tumor growth cycle, evaluating their predictive value for tumor growth. The analysis of three preclinical colon carcinoma longitudinal cases shows that using physiologically meaningful measures of tumor as guidance information can improve non-rigid registration of longitudinal tumor imaging data when compared to a state-of-the-art local correlation coefficient Demons approach. Moreover, using the determinant of the Jacobian of the estimated displacement field as an indicator of volume change allows us to observe a correlation between the tumor descriptor values and tumor growth, especially when maps of hypoxic cells and level of oxygen were used to aid registration. To the best of our knowledge, this work demonstrates for the first time the feasibility of using biologically meaningful tumor descriptors (total cell number, proliferative cell number, hypoxic cell number, necrotic cell number and oxygen level) derived from DCE-MRI to aid non-rigid registration of longitudinal tumor data as well as to estimate tumor growth.
引用
收藏
页码:507 / 515
页数:9
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