Literature DB >> 15323399

Evaluation of tumor angiogenesis using dynamic enhanced magnetic resonance imaging: comparison of plasma vascular endothelial growth factor, hemodynamic, and pharmacokinetic parameters.

O Ikeda1, R Nishimura, H Miyayama, T Yasunaga, Y Ozaki, A Tuji, Y Yamashita.   

Abstract

PURPOSE: To assess whether tumor angiogenesis of breast cancers can be predicted on the basis of dynamic magnetic resonance imaging (MRI).
MATERIAL AND METHODS: Seventy-one patients with 71 breast cancers underwent Gd-DTPA enhanced dynamic MRI. Two regions of interest measurements were obtained in the periphery and in the center of the breast cancers. Hemodynamic parameters obtained by dynamic MRI included peak time, contrast enhancement ratio (CE ratio), and washout ratio. The triexponential concentration curve of Gd-DTPA was fitted to a theoretical model based on compartmental analysis. The transfer constant (or permeability surface product per unit volume of compartment "k") was obtained using this method. Tumor angiogenesis was assessed by plasma vascular endothelial growth factor (P-VEGF).
RESULTS: The P-VEGF was positive in 28 of 71 tumors (39%). The CE ratio, washout ratio, and k in the periphery in P-VEGF positive breast cancers (mean 178%, 18%, and 1.5 x 10(-2) (s(-1)) were significantly greater (P<0.01, P<0.05, and P<0.03)) than those for P-VEGF negative breast cancers (mean: 151%, 14%, and 1.1 x 10(-2) (s(-1)). The peak time in the periphery in P-VEGF positive breast cancers was more marked than for P-VEGF negative breast cancers, but this difference was not significant.
CONCLUSION: The hemodynamic and pharmacokinetic analysis of MRI provides valuable information about angiogenesis of breast cancers.

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Year:  2004        PMID: 15323399     DOI: 10.1080/02841850410005372

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  4 in total

1.  Real-time electrical impedance variations in women with and without breast cancer.

Authors:  Ryan J Halter; Alex Hartov; Steven P Poplack; Roberta diFlorio-Alexander; Wendy A Wells; Kari M Rosenkranz; Richard J Barth; Peter A Kaufman; Keith D Paulsen
Journal:  IEEE Trans Med Imaging       Date:  2014-07-24       Impact factor: 10.048

2.  Computer aided diagnosis system for breast cancer based on color Doppler flow imaging.

Authors:  Yan Liu; H D Cheng; J H Huang; Y T Zhang; X L Tang; J W Tian; Y Wang
Journal:  J Med Syst       Date:  2012-07-13       Impact factor: 4.460

3.  Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves?

Authors:  Matthias Dietzel; Stephan Ellmann; Rüdiger Schulz-Wendtland; Paola Clauser; Evelyn Wenkel; Michael Uder; Pascal A T Baltzer
Journal:  Eur Radiol       Date:  2019-07-29       Impact factor: 5.315

4.  Diagnosis of Breast Cancer Using Radiomics Models Built Based on Dynamic Contrast Enhanced MRI Combined With Mammography.

Authors:  You-Fan Zhao; Zhongwei Chen; Yang Zhang; Jiejie Zhou; Jeon-Hor Chen; Kyoung Eun Lee; Freddie J Combs; Ritesh Parajuli; Rita S Mehta; Meihao Wang; Min-Ying Su
Journal:  Front Oncol       Date:  2021-11-17       Impact factor: 6.244

  4 in total

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