Literature DB >> 20821138

Visualization of treatment response in tumors by use of dynamic contrast-enhanced magnetic resonance imaging.

Shohei Miyazaki1, Kenya Murase, Yoshifumi Sugawara, Makoto Kajihara, Keiichi Kikuchi, Hitoshi Miki, Teruhito Mochizuki.   

Abstract

Our goal in this study was to present a method for generating functional parametric maps of hemodynamic parameters in tumors and a visualization method for assessing treatment response by use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 13 patients with musculoskeletal tumors were included in this study. First, tumor blood flow (F(T)) maps were generated from DCE-MRI data by use of deconvolution analysis, and K(1), k(2), and f were obtained from a two-compartment model, where K(1) and k(2) denote the rate constant for the transfer of contrast agent from blood to tissue and from tissue to blood, respectively, and f is the fraction of the blood volume. Images were generated by application of the linear least squares method pixel by pixel. Furthermore, the images of the distribution volume (V(d)) and permeability-surface area product (PS) were obtained from the relations V(d) = K(1)/k(2) and PS = -F(T) x ln(1 - K(1)/(F(T)), respectively. Second, two-dimensional (2D) plots were generated with V(d) and K(1) placed on the x- and y-axes, and three-dimensional (3D) plots were generated by the addition of PS on the z-axis. In the case of good responders whose biopsied specimens revealed tumor necrosis greater than 90%, both 2D and 3D plots gradually approached the origin after an increasing number of treatments. On the other hand, in the case of non-responders whose biopsied specimens showed little chemotherapeutic effect, large changes were not observed in either plot. In conclusion, our method will be promising for evaluating the treatment response in tumors visually.

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Year:  2008        PMID: 20821138     DOI: 10.1007/s12194-008-0019-0

Source DB:  PubMed          Journal:  Radiol Phys Technol        ISSN: 1865-0333


  10 in total

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7.  Measurement of tumor blood flow using dynamic contrast-enhanced magnetic resonance imaging and deconvolution analysis: a preliminary study in musculoskeletal tumors.

Authors:  Yoshifumi Sugawara; Kenya Murase; Keiichi Kikuchi; Kenshi Sakayama; Tatsuhiko Miyazaki; Makoto Kajihara; Hitoshi Miki; Teruhito Mochizuki
Journal:  J Comput Assist Tomogr       Date:  2006 Nov-Dec       Impact factor: 1.826

Review 8.  Functional tumor imaging with dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Peter L Choyke; Andrew J Dwyer; Michael V Knopp
Journal:  J Magn Reson Imaging       Date:  2003-05       Impact factor: 4.813

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Journal:  J Clin Oncol       Date:  1995-03       Impact factor: 44.544

10.  Tumor angiogenesis as a prognostic factor in cervical carcinoma.

Authors:  D L Wiggins; C O Granai; M M Steinhoff; P Calabresi
Journal:  Gynecol Oncol       Date:  1995-03       Impact factor: 5.482

  10 in total

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