Literature DB >> 21816291

Assessment of tumor radioresponsiveness and metastatic potential by dynamic contrast-enhanced magnetic resonance imaging.

Kirsti Marie Øvrebø1, Kristine Gulliksrud, Berit Mathiesen, Einar K Rofstad.   

Abstract

PURPOSE: It has been suggested that gadolinium diethylene-triamine penta-acetic acid (Gd-DTPA)-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide clinically useful biomarkers for personalized cancer treatment. In this preclinical study, we investigated the potential of DCE-MRI as a noninvasive method for assessing the radioresponsiveness and metastatic potential of tumors. METHODS AND MATERIALS: R-18 melanoma xenografts growing in BALB/c nu/nu mice were used as experimental tumor models. Fifty tumors were subjected to DCE-MRI, and parametric images of Ktrans (the volume transfer constant of Gd-DTPA) and ve (the fractional distribution volume of Gd-DTPA) were produced by pharmacokinetic analysis of the DCE-MRI series. The tumors were irradiated after the DCE-MRI, either with a single dose of 10 Gy for detection of radiobiological hypoxia (30 tumors) or with five fractions of 4 Gy in 48 h for assessment of radioresponsiveness (20 tumors). The host mice were then euthanized and examined for lymph node metastases, and the primary tumors were resected for measurement of cell survival in vitro.
RESULTS: Tumors with hypoxic cells showed significantly lower Ktrans values than tumors without significant hypoxia (p<0.0001, n=30), and Ktrans decreased with increasing cell surviving fraction for tumors given fractionated radiation treatment (p<0.0001, n=20). Tumors in metastasis-positive mice had significantly lower Ktrans values than tumors in metastasis-negative mice (p<0.0001, n=50). Significant correlations between ve and tumor hypoxia, radioresponsiveness, or metastatic potential could not be detected.
CONCLUSIONS: R-18 tumors with low Ktrans values are likely to be resistant to radiation treatment and have a high probability of developing lymph node metastases. The general validity of these observations should be investigated further by studying preclinical tumor models with biological properties different from those of the R-18 tumors.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21816291     DOI: 10.1016/j.ijrobp.2011.04.008

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  12 in total

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2.  Automation of pattern recognition analysis of dynamic contrast-enhanced MRI data to characterize intratumoral vascular heterogeneity.

Authors:  SoHyun Han; Radka Stoyanova; Hansol Lee; Sean D Carlin; Jason A Koutcher; HyungJoon Cho; Ellen Ackerstaff
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3.  Mapping Tumor Hypoxia In Vivo Using Pattern Recognition of Dynamic Contrast-enhanced MRI Data.

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4.  A diffusion-compensated model for the analysis of DCE-MRI data: theory, simulations and experimental results.

Authors:  Jacob U Fluckiger; Mary E Loveless; Stephanie L Barnes; Martin Lepage; Thomas E Yankeelov
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5.  Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer.

Authors:  Stephanie L Barnes; Anna G Sorace; Mary E Loveless; Jennifer G Whisenant; Thomas E Yankeelov
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Authors:  Jason Chia-Hsien Cheng; Ang Yuan; Jyh-Horng Chen; Yi-Chien Lu; Kuan-Hung Cho; Jian-Kuen Wu; Chien-Jang Wu; Yeun-Chung Chang; Pan-Chyr Yang
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8.  Oxygen-Sensitive MRI: A Predictive Imaging Biomarker for Tumor Radiation Response?

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Journal:  Int J Radiat Oncol Biol Phys       Date:  2021-03-26       Impact factor: 8.013

9.  DW-MRI in assessment of the hypoxic fraction, interstitial fluid pressure, and metastatic propensity of melanoma xenografts.

Authors:  Tord Hompland; Christine Ellingsen; Kanthi Galappathi; Einar K Rofstad
Journal:  BMC Cancer       Date:  2014-02-15       Impact factor: 4.430

10.  Pretreatment Dynamic Contrast-Enhanced MRI Improves Prediction of Early Distant Metastases in Patients With Nasopharyngeal Carcinoma.

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Journal:  Medicine (Baltimore)       Date:  2016-02       Impact factor: 1.817

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