Aining Zhang1, Jiacheng Song1, Zhanlong Ma2, Ting Chen1. 1. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, China. 2. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300, Guangzhou Road, Nanjing, 210029, China. mzlwzcdyx@163.com.
Abstract
PURPOSE: To explore the value of histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters and apparent diffusion coefficient (ADC) values in predicting the neoadjuvant chemotherapy (NACT) response for cervical cancers. METHODS: Sixty-three patients with pathologically proved stage IB2-IIA2 cervical cancer from March 2013 to January 2017 were retrospectively analyzed. They were divided into two groups on the basis of therapeutic response: the significant response (SR) group, which contains complete response patients and partial response patients, and nonsignificant response (non-SR) group, which contains progressive diseases and stable diseases. Clinical characteristics, DCE-MRI parameters (Ktrans, Kep, Ve), and ADC values before NACT were analyzed and compared between the two groups. RESULTS: SR group and non-SR group were documented in 35 and 28 patients. The mean Ktrans value, 90th percentile Ktrans value, maximal Ktrans value, and 90th percentile ADC value of tumors in SR were significantly higher than those in non-SR group (P = 0.012, P = 0.022, P = 0.005, P = 0.033, respectively), and the mean Ve value and 10th percentile Ve value of tumors were significantly lower in SR group (P = 0.041, P = 0.033, respectively). Kep values did not significantly differ between SR and non-SR. The 90th percentile Ktrans value combined with the 90th percentile ADC value had the highest area under the curve at 0.740 (P = 0.003) to predict NACT effectiveness. CONCLUSION: Histogram analysis of DCE-MRI multi-parameters combined with ADC values may serve as sensitive indicators for predicting NACT effectiveness in cervical cancers.
PURPOSE: To explore the value of histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters and apparent diffusion coefficient (ADC) values in predicting the neoadjuvant chemotherapy (NACT) response for cervical cancers. METHODS: Sixty-three patients with pathologically proved stage IB2-IIA2 cervical cancer from March 2013 to January 2017 were retrospectively analyzed. They were divided into two groups on the basis of therapeutic response: the significant response (SR) group, which contains complete response patients and partial response patients, and nonsignificant response (non-SR) group, which contains progressive diseases and stable diseases. Clinical characteristics, DCE-MRI parameters (Ktrans, Kep, Ve), and ADC values before NACT were analyzed and compared between the two groups. RESULTS: SR group and non-SR group were documented in 35 and 28 patients. The mean Ktrans value, 90th percentile Ktrans value, maximal Ktrans value, and 90th percentile ADC value of tumors in SR were significantly higher than those in non-SR group (P = 0.012, P = 0.022, P = 0.005, P = 0.033, respectively), and the mean Ve value and 10th percentile Ve value of tumors were significantly lower in SR group (P = 0.041, P = 0.033, respectively). Kep values did not significantly differ between SR and non-SR. The 90th percentile Ktrans value combined with the 90th percentile ADC value had the highest area under the curve at 0.740 (P = 0.003) to predict NACT effectiveness. CONCLUSION: Histogram analysis of DCE-MRI multi-parameters combined with ADC values may serve as sensitive indicators for predicting NACT effectiveness in cervical cancers.
Authors: Vincenza Granata; Roberta Fusco; Simona Salati; Antonella Petrillo; Elio Di Bernardo; Roberta Grassi; Raffaele Palaia; Ginevra Danti; Michelearcangelo La Porta; Matteo Cadossi; Gorana Gašljević; Gregor Sersa; Francesco Izzo Journal: Int J Environ Res Public Health Date: 2021-05-24 Impact factor: 3.390
Authors: Vincenza Granata; Roberta Grassi; Roberta Fusco; Andrea Belli; Carmen Cutolo; Silvia Pradella; Giulia Grazzini; Michelearcangelo La Porta; Maria Chiara Brunese; Federica De Muzio; Alessandro Ottaiano; Antonio Avallone; Francesco Izzo; Antonella Petrillo Journal: Infect Agent Cancer Date: 2021-07-19 Impact factor: 2.965