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Author Notes:

Correspondence: Jian He; email: hjxueren@126.com or Xiaofeng Yang; email: Xiaofeng.yang@emory.edu or Zhengyang Zhou; email: zyzhou@nju.edu.cn

Author Contributions: Jie Meng and Shunli Liu contributed equally to this work

J.M. and S.L.L. collected data, carried out the data analysis and drafted the manuscript; X.F.Y. and Y.G. carried out the quality control of data and algorithms; H.H.W. and L.Z. had significant roles in the data acquisition; L.J.Z. and L.X. were the oncologists responsible for all oncological support; J.H., X.F.Y. and Z.Y.Z. had significant roles in the study design and manuscript review; X.F.Y. and Z.Y.Z. formulated the research question, supervised the research program and edited the manuscript.

All authors read and approved the final manuscript.

Disclosures: The authors declare no competing interests.

Subjects:

Research Funding:

This work was supported by the National Natural Science Foundation of China (ID: 81371516, 81501441, 81671751), Social Development Foundation of Jiangsu Province (BE2015605), Foundation of National Health and Family Planning Commission of China (W201306), the Natural Science Foundation of Jiangsu Province (ID: BK20150109, BK20150102), Jiangsu Province Health and Family Planning Commission Youth Scientific Research Project (ID: Q201508), Six Talent Peaks Project of Jiangsu Province (ID: 2015-WSN-079) and Key Project supported by Medical Science and technology development Foundation, Nanjing Department of Health (YKK15067).

The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources.

Keywords:

  • Science & Technology
  • Multidisciplinary Sciences
  • Science & Technology - Other Topics
  • TUMOR HETEROGENEITY
  • MAGNETIC-RESONANCE
  • NEOADJUVANT CHEMORADIOTHERAPY
  • CONCURRENT CHEMORADIOTHERAPY
  • PROSTATE-CANCER
  • RECTAL-CANCER
  • F-18-FDG PET
  • FEATURES
  • GLIOBLASTOMA
  • CHEMOTHERAPY

Texture Analysis as Imaging Biomarker for recurrence in advanced cervical cancer treated with CCRT

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Journal Title:

Scientific Reports

Volume:

Volume 8, Number 1

Publisher:

, Pages 11399-11399

Type of Work:

Article | Final Publisher PDF

Abstract:

This prospective study explored the application of texture features extracted from T2WI and apparent diffusion coefficient (ADC) maps in predicting recurrence of advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). We included 34 patients with advanced cervical cancer who underwent pelvic MR imaging before, during and after CCRT. Radiomic feature extraction was performed by using software at T2WI and ADC maps. The performance of texture parameters in predicting recurrence was evaluated. After a median follow-up of 31 months, eleven patients (32.4%) had recurrence. At four weeks after CCRT initiated, the most textural parameters (four T2 textural parameters and two ADC textural parameters) showed significant difference between the recurrence and nonrecurrence group (P values range, 0.002~0.046). Among them, RunLengthNonuniformity (RLN) from T2 and energy from ADC maps were the best selected predictors and together yield an AUC of 0.885. The support vector machine (SVM) classifier using ADC textural parameters performed best in predicting recurrence, while combining T2 textural parameters may add little value in prognosis. T2 and ADC textural parameters have potential as non-invasive imaging biomarkers in early predicting recurrence in advanced cervical cancer treated with CCRT.

Copyright information:

© 2018, The Author(s)

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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