PURPOSE: To evaluate semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measurements in predicting the response to radiotherapy in cervix cancer. METHODS AND MATERIALS: Patients with cervix cancer treated radically with chemoradiotherapy had DCE-MRI at three time points: before starting treatment, after 2 weeks of radiotherapy, and in the 5th week of radiotherapy. Semiquantitative measurements obtained from the signal intensity vs. time plots included arrival time of contrast, the slope and maximum slope of contrast uptake, time for peak enhancement, and the contrast enhancement ratio (CER). Pharmacokinetic modeling with a modeled vascular input function was used for the quantitative measurements volume transfer constant (K(trans)), rate constant (k(ep)), fraction plasma volume (fPV), and the initial area under gadolinium-time curve. The correlation of these measurements at each of the three time points with radiologic tumor response was investigated. RESULTS: Thirteen patients had a total of 38 scans. There was no correlation between the DCE-MRI measurements and the corresponding tumor volumes. A statistically significant correlation with percentage tumor regression was shown with the pretreatment DCE-MRI semiquantitative parameters of peak time (p = 0.046), slope (p = 0.025), maximum slope (p = 0.046), and CER (p = 0.025) and the quantitative parameters K(trans) (p = 0.043) and k(ep) (p = 0.022). Second and third scan measurements did not show any correlation. CONCLUSIONS: This is the first study to show that pretreatment DCE-MRI quantitative parameters predict the radiation response in cervix cancer. These measurements may allow a more meaningful comparison of DCE-MRI studies from different centers.
PURPOSE: To evaluate semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measurements in predicting the response to radiotherapy in cervix cancer. METHODS AND MATERIALS: Patients with cervix cancer treated radically with chemoradiotherapy had DCE-MRI at three time points: before starting treatment, after 2 weeks of radiotherapy, and in the 5th week of radiotherapy. Semiquantitative measurements obtained from the signal intensity vs. time plots included arrival time of contrast, the slope and maximum slope of contrast uptake, time for peak enhancement, and the contrast enhancement ratio (CER). Pharmacokinetic modeling with a modeled vascular input function was used for the quantitative measurements volume transfer constant (K(trans)), rate constant (k(ep)), fraction plasma volume (fPV), and the initial area under gadolinium-time curve. The correlation of these measurements at each of the three time points with radiologic tumor response was investigated. RESULTS: Thirteen patients had a total of 38 scans. There was no correlation between the DCE-MRI measurements and the corresponding tumor volumes. A statistically significant correlation with percentage tumor regression was shown with the pretreatment DCE-MRI semiquantitative parameters of peak time (p = 0.046), slope (p = 0.025), maximum slope (p = 0.046), and CER (p = 0.025) and the quantitative parameters K(trans) (p = 0.043) and k(ep) (p = 0.022). Second and third scan measurements did not show any correlation. CONCLUSIONS: This is the first study to show that pretreatment DCE-MRI quantitative parameters predict the radiation response in cervix cancer. These measurements may allow a more meaningful comparison of DCE-MRI studies from different centers.
Authors: Craig J Galbán; Stefanie Galbán; Marcian E Van Dort; Gary D Luker; Mahaveer S Bhojani; Alnawaz Rehemtulla; Brian D Ross Journal: Prog Mol Biol Transl Sci Date: 2010 Impact factor: 3.622
Authors: Hannah Bainbridge; Ahmed Salem; Rob H N Tijssen; Michael Dubec; Andreas Wetscherek; Corinne Van Es; Jose Belderbos; Corinne Faivre-Finn; Fiona McDonald Journal: Transl Lung Cancer Res Date: 2017-12
Authors: S B Donaldson; D L Buckley; J P O'Connor; S E Davidson; B M Carrington; A P Jones; C M L West Journal: Br J Cancer Date: 2009-11-17 Impact factor: 7.640