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Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT

PURPOSE: To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). METHODS: 36 women with pathologically confirmed advanced cervical squamous c...

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Autores principales: Meng, Jie, Zhu, Lijing, Zhu, Li, Xie, Li, Wang, Huanhuan, Liu, Song, Yan, Jing, Liu, Baorui, Guan, Yue, He, Jian, Ge, Yun, Zhou, Zhengyang, Yang, Xiaofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696195/
https://www.ncbi.nlm.nih.gov/pubmed/29190929
http://dx.doi.org/10.18632/oncotarget.21374
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author Meng, Jie
Zhu, Lijing
Zhu, Li
Xie, Li
Wang, Huanhuan
Liu, Song
Yan, Jing
Liu, Baorui
Guan, Yue
He, Jian
Ge, Yun
Zhou, Zhengyang
Yang, Xiaofeng
author_facet Meng, Jie
Zhu, Lijing
Zhu, Li
Xie, Li
Wang, Huanhuan
Liu, Song
Yan, Jing
Liu, Baorui
Guan, Yue
He, Jian
Ge, Yun
Zhou, Zhengyang
Yang, Xiaofeng
author_sort Meng, Jie
collection PubMed
description PURPOSE: To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). METHODS: 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm(2)) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. RESULTS: With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC(mean), 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). CONCLUSIONS: Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.
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spelling pubmed-56961952017-11-29 Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT Meng, Jie Zhu, Lijing Zhu, Li Xie, Li Wang, Huanhuan Liu, Song Yan, Jing Liu, Baorui Guan, Yue He, Jian Ge, Yun Zhou, Zhengyang Yang, Xiaofeng Oncotarget Research Paper PURPOSE: To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). METHODS: 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm(2)) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. RESULTS: With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC(mean), 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). CONCLUSIONS: Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT. Impact Journals LLC 2017-09-28 /pmc/articles/PMC5696195/ /pubmed/29190929 http://dx.doi.org/10.18632/oncotarget.21374 Text en Copyright: © 2017 Meng et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Paper
Meng, Jie
Zhu, Lijing
Zhu, Li
Xie, Li
Wang, Huanhuan
Liu, Song
Yan, Jing
Liu, Baorui
Guan, Yue
He, Jian
Ge, Yun
Zhou, Zhengyang
Yang, Xiaofeng
Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title_full Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title_fullStr Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title_full_unstemmed Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title_short Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
title_sort whole-lesion adc histogram and texture analysis in predicting recurrence of cervical cancer treated with ccrt
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696195/
https://www.ncbi.nlm.nih.gov/pubmed/29190929
http://dx.doi.org/10.18632/oncotarget.21374
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