Assessment of the Early Predictive Power of Quantitative Magnetic Resonance Imaging Parameters During Neoadjuvant Chemotherapy for Uterine Cervical Cancer

2014 ◽  
Vol 24 (4) ◽  
pp. 751-757 ◽  
Author(s):  
Yuki Himoto ◽  
Koji Fujimoto ◽  
Aki Kido ◽  
Noriomi Matsumura ◽  
Tsukasa Baba ◽  
...  

ObjectivesThe purpose of this study was to quantitatively evaluate 3 types of magnetic resonance imaging (MRI) parameters in parallel for the early prediction of neoadjuvant chemotherapy (NACT) effectiveness in cervical cancer—tumor volume parameters, diffusion parameters, and perfusion parameters.Materials and MethodsWe prospectively evaluated 13 patients with International Federation of Gynecology and Obstetrics stage IB to IIB cervical squamous cell carcinoma who underwent 3 serial MRI studies, that is, pretreatment, post–first course NACT, and post–second course NACT followed by radical hysterectomy. We obtained tumor volume parameters, diffusion parameters, and dynamic contrast material–enhanced perfusion parameters quantitatively from pretreatment MRI and post–first course MRI. The correlation of these parameters and the eventual tumor volume regression rate (TVRR) obtained from pretreatment MRI and post–second course MRI before surgery were investigated, statistically based on the Pearson correlation coefficient.ResultsThirteen patients had a total of 39 scans. Early TVRR (r= 0.844;P< 0.001), the fractional volume of the tissue extracellular extravascular space (Ve,r= 0.648;P< 0.05), and the change of Ve during the first course of NACT (r= −0.638;P< 0.05) correlated with eventual TVRR.ConclusionsEarly TVRR, Ve, and the change of Ve could be useful predictors for the treatment effectiveness of NACT. These parameters could help to modify strategy in the early stage of NACT and to choose individualized treatment to avoid the delay of radical treatment, even when NACT is ineffective.

2018 ◽  
Vol 60 (5) ◽  
pp. 670-676
Author(s):  
Ji Zhang ◽  
Weizhong Tian ◽  
Xinhua Bu ◽  
Xiulan Wang ◽  
Fangzheng Tian ◽  
...  

Background Patients with uterine cervical cancer suffer high mortality. Accurate detection of a residual tumor by magnetic resonance imaging (MRI) during and after directed brachytherapy (BCT) is crucial for the success of cancer treatment and is a significant predictor of patient survival. Purpose To determine the diagnostic significance of MRI in detecting residual tumor tissue after BCT. Material and Methods The Web of Knowledge, Cochrane Library, and PubMed were systematically searched (January 1997 to December 2016) for post-brachytherapy MRI studies that measured residual tumors in patients with uterine cervical cancer. All data were analyzed using the Meta-Disc 1.4 program. Results Four clinical studies consisting of 163 patients (147 of whom were included in the present analysis) who were diagnosed with uterine cervical cancer according to the International Federation of Gynecology and Obstetrics (FIGO) staging system were included in the study. All the patients received BCT and underwent MRI detection of residual tumors tissue. In studies where the accuracy of MRI detection was confirmed by histological tests or gynecological tests, the summary estimates of specificity, sensitivity, positive predictive value, negative predictive value, and accuracy were 88.5%, 83.5%, 53.5%, 97.1%, and 84.3%, respectively. Conclusion MRI-directed BCT is commonly used for cervical cancer patients. Based on our investigation of four independent studies, MRI showed better prediction of positive results than negative results in patients with cervical cancer after BCT. However, more data on the greater numbers of patients are needed to establish the accuracy of MRI detection of cervical cancer after BCT.


2003 ◽  
Vol 26 (5) ◽  
pp. e163-e168 ◽  
Author(s):  
Kailash Narayan ◽  
Allan McKenzie ◽  
Richard Fisher ◽  
Beatrice Susil ◽  
Tom Jobling ◽  
...  

2019 ◽  
Vol 7_2019 ◽  
pp. 85-91
Author(s):  
Ovodenko D.L. Ovodenko ◽  
Bychenko V.G. Bychenko ◽  
Khabas G.N. Khabas ◽  
Akinfiev D.M. Akinfiev D ◽  
Makarova A.S. Makarova ◽  
...  

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