Tracer kinetic modelling of tumour angiogenesis based on dynamic contrast-enhanced CT and MRI measurements

被引:94
作者
Brix, Gunnar [1 ,2 ]
Griebel, Juergen [2 ]
Kiessling, Fabian [3 ]
Wenz, Frederik [4 ]
机构
[1] Bundesamt Strahlenschutz BfS, Abt Med & Beruflichen Strahlenschutz, D-85764 Oberschleissheim, Germany
[2] Fed Off Radiat Protect, Dept Med & Occupat Radiat Protect, Oberschleissheim, Germany
[3] Rhein Westfal TH Aachen, Dept Expt Mol Imaging, Aachen, Germany
[4] Heidelberg Univ, Dept Radiat Oncol, Univ Med Ctr Mannheim, D-6800 Mannheim, Germany
关键词
Contrast-enhanced dynamic imaging; Microcirculation; Microvasculature; Indicator dilution theory; Compartmental modelling; LOW-GRADE ASTROCYTOMAS; CEREBRAL-BLOOD-FLOW; PROSTATE-CANCER; PERFUSION CT; PHARMACOKINETIC ANALYSIS; NORMAL BRAIN; MAGNETIC-SUSCEPTIBILITY; OXYGENATION STATUS; RADIATION; TISSUE;
D O I
10.1007/s00259-010-1448-7
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Technical developments in both magnetic resonance imaging (MRI) and computed tomography (CT) have helped to reduce scan times and expedited the development of dynamic contrast-enhanced (DCE) imaging techniques. Since the temporal change of the image signal following the administration of a diffusible, extracellular contrast agent (CA) is related to the local blood supply and the extravasation of the CA into the interstitial space, DCE imaging can be used to assess tissue microvasculature and microcirculation. It is the aim of this review to summarize the biophysical and tracer kinetic principles underlying this emerging imaging technique offering great potential for non-invasive characterization of tumour angiogenesis. In the first part, the relevant contrast mechanisms are presented that form the basis to relate signal variations measured by serial CT and MRI to local tissue concentrations of the administered CA. In the second part, the concepts most widely used for tracer kinetic modelling of concentration-time courses derived from measured DCE image data sets are described in a consistent and unified manner to highlight their particular structure and assumptions as well as the relationships among them. Finally, the concepts presented are exemplified by the analysis of representative DCE data as well as discussed with respect to present and future applications in cancer diagnosis and therapy. Depending on the specific protocol used for the acquisition of DCE image data and the particular model applied for tracer kinetic analysis of the derived concentration-time courses, different aspects of tumour angiogenesis can be quantified in terms of well-defined physiological tissue parameters. DCE imaging offers promising prospects for improved tumour diagnosis, individualization of cancer treatment as well as the evaluation of novel therapeutic concepts in preclinical and early-stage clinical trials.
引用
收藏
页码:S30 / S51
页数:22
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