Literature DB >> 24687746

Histogram analysis of apparent diffusion coefficient for the assessment of local aggressiveness of cervical cancer.

Huadan Xue1, Cui Ren, Jiaxin Yang, Zhaoyong Sun, Shuo Li, Zhengyu Jin, Keng Shen, Weixun Zhou.   

Abstract

PURPOSE: To retrospectively explore the value of apparent diffusion coefficient (ADC) histogram in assessing local aggressiveness of cervical cancer.
METHODS: 53 patients with cervical cancer, including 7 cases at stage IB1, 17 cases at stage IB2 and 29 cases at stage IIA, were subjected to preoperative MRI including diffusion-weighted imaging with b values of 0 and 800 s/mm(2). The average of mean ADC values (ADCmean), minimum ADC values (ADCmin) and the 5th to 85th percentile ADC values every 10 % (ADC5 %, ADC15 %, ADC85 %) were measured. ADC values were compared between subgroups according to pathologic subtype, histological differentiation, depth of cervical infiltration, and lymph node metastases.
RESULTS: ADCmean and ADCmin for adenocarcinoma were 1,170.3 ± 97.8 × 10(-6) and 748.7 ± 157.5 × 10(-6) mm(2) s(-1), respectively, significantly higher than that of squamous cell carcinoma (SCC) (1,053.8 ± 134.3 × 10(-6) and 615.6 ± 170.2 × 10(-6) mm(2) s(-1), respectively). ADCmean and ADC5 %-ADC85 % of well or moderately tumor were significantly higher than poorly differentiated tumor, but ADCmin was not significantly different among different differentiated cervical cancer. Only ADC5 %-ADC45 % could discriminate well or moderately differentiated SCC from poorly differentiated SCC. ADC5 % for distinguishing well/moderately from poorly differentiated cervical cancer had a largest AUC (0.83). There was no statistical difference in ADC value for different depth of cervical infiltration or lymph node metastases.
CONCLUSIONS: ADC values are helpful in assessing pathologic subtype and the differentiation of cervical cancer.

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Year:  2014        PMID: 24687746     DOI: 10.1007/s00404-014-3221-9

Source DB:  PubMed          Journal:  Arch Gynecol Obstet        ISSN: 0932-0067            Impact factor:   2.344


  19 in total

1.  ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study.

Authors:  Stefan Schob; Hans Jonas Meyer; Nikolaos Pazaitis; Dominik Schramm; Kristina Bremicker; Marc Exner; Anne Kathrin Höhn; Nikita Garnov; Alexey Surov
Journal:  Mol Imaging Biol       Date:  2017-12       Impact factor: 3.488

2.  Prognostic model based on magnetic resonance imaging, whole-tumour apparent diffusion coefficient values and HPV genotyping for stage IB-IV cervical cancer patients following chemoradiotherapy.

Authors:  Gigin Lin; Lan-Yan Yang; Yu-Chun Lin; Yu-Ting Huang; Feng-Yuan Liu; Chun-Chieh Wang; Hsin-Ying Lu; Hsin-Ju Chiang; Yu-Ruei Chen; Ren-Chin Wu; Koon-Kwan Ng; Ji-Hong Hong; Tzu-Chen Yen; Chyong-Huey Lai
Journal:  Eur Radiol       Date:  2018-07-26       Impact factor: 5.315

3.  Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer.

Authors:  Jiyeong Lee; Chan Kyo Kim; Sung Yoon Park
Journal:  MAGMA       Date:  2019-09-23       Impact factor: 2.310

4.  An analysis of Ki-67 expression in stage 1 invasive ductal breast carcinoma using apparent diffusion coefficient histograms.

Authors:  Maolin Xu; Qi Tang; Manxiu Li; Yulin Liu; Fang Li
Journal:  Quant Imaging Med Surg       Date:  2021-04

5.  Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Authors:  Jie Meng; Lijing Zhu; Li Zhu; Huanhuan Wang; Song Liu; Jing Yan; Baorui Liu; Yue Guan; Yun Ge; Jian He; Zhengyang Zhou; Xiaofeng Yang
Journal:  Radiat Oncol       Date:  2016-10-22       Impact factor: 3.481

6.  Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion.

Authors:  Naoko Tsuchiya; Mariko Doai; Katsuo Usuda; Hidetaka Uramoto; Hisao Tonami
Journal:  PLoS One       Date:  2017-02-16       Impact factor: 3.240

7.  Histological grades of rectal cancer: whole-volume histogram analysis of apparent diffusion coefficient based on reduced field-of-view diffusion-weighted imaging.

Authors:  Yang Peng; Hao Tang; Xiaoyan Meng; Yaqi Shen; Daoyu Hu; Ihab Kamel; Zhen Li
Journal:  Quant Imaging Med Surg       Date:  2020-01

8.  Volumetric ADC histogram analysis for preoperative evaluation of LVSI status in stage I endometrioid adenocarcinoma.

Authors:  Xiaoliang Ma; Xiaojun Ren; Minhua Shen; Fenghua Ma; Xiaojun Chen; Guofu Zhang; Jinwei Qiang
Journal:  Eur Radiol       Date:  2021-06-17       Impact factor: 5.315

9.  Simultaneous [18F]FDG-PET/MRI: Correlation of Apparent Diffusion Coefficient (ADC) and Standardized Uptake Value (SUV) in Primary and Recurrent Cervical Cancer.

Authors:  P Brandmaier; S Purz; K Bremicker; M Höckel; H Barthel; R Kluge; T Kahn; O Sabri; P Stumpp
Journal:  PLoS One       Date:  2015-11-09       Impact factor: 3.240

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

Authors:  Jie Meng; Lijing Zhu; Li Zhu; Li Xie; Huanhuan Wang; Song Liu; Jing Yan; Baorui Liu; Yue Guan; Jian He; Yun Ge; Zhengyang Zhou; Xiaofeng Yang
Journal:  Oncotarget       Date:  2017-09-28
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