Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy

Chen "Systematic review and meta-analysis of tumor biomarkers in predicting prognosis in esophageal cancer" BMC Cancer (2013) 10.1186/1471-2407-13-539

[2]

Li "Value of sequential 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in prediction of the overall survival of esophageal cancer patients treated with chemoradiotherapy" Int J Clin Exp Med (2015)

[3]

Atsumi "Prediction of outcome with FDG-PET in definitive chemoradiotherapy for esophageal cancer" J Radiat Res (2013) 10.1093/jrr/rrt021

[4]

Lindner "PET/CT predicts survival in patients undergoing primary surgery for esophageal cancer" Langenbecks Arch Surg (2015) 10.1007/s00423-014-1264-9

[5]

Myslivecek Czechoslovakia (2012)

[6]

Primary Esophageal Cancer: Heterogeneity as Potential Prognostic Biomarker in Patients Treated with Definitive Chemotherapy and Radiation Therapy

Connie Yip, David Landau, Robert Kozarski et al.

Radiology 2014 10.1148/radiol.13122869

[7]

Beukinga "Predicting response to neoadjuvant chemoradiotherapy in esophageal cancer with textural features derived from pretreatment (18)F-FDG PET/CT imaging" J Nucl Med (2017) 10.2967/jnumed.116.180299

[8]

Hou "Radiomic analysis in contrast-enhanced CT: predict treatment response to chemoradiotherapy in esophageal carcinoma" Oncotarget (2017) 10.18632/oncotarget.22304

[9]

Ganeshan "Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage" Cancer Imaging (2010) 10.1102/1470-7330.2010.0021

[10]

Ganeshan "Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival" Clin Radiol (2012) 10.1016/j.crad.2011.08.012

[11]

Gatenby "Quantitative imaging in cancer evolution and ecology" Radiology (2013) 10.1148/radiol.13122697

[12]

Wu "Intratumoral spatial heterogeneity at perfusion MR imaging predicts recurrence-free survival in locally advanced breast cancer treated with neoadjuvant chemotherapy" Radiology (2018) 10.1148/radiol.2018172462

[13]

Wu "Robust Intratumor partitioning to identify high-risk subregions in lung cancer: a pilot study" Int J Radiat Oncol Biol Phys (2016) 10.1016/j.ijrobp.2016.03.018

[14]

Xia "Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data-a preliminary study" Phys Med Biol (2018) 10.1088/1361-6560/aaa609

[15]

Liu "Understanding and enhancement of internal clustering validation measures" IEEE Trans Cybern (2013) 10.1109/tsmcb.2012.2220543

[16]

Larue "Influence of gray level discretization on radiomic feature stability for different CT scanners, tube currents and slice thicknesses: a comprehensive phantom study" Acta Oncol (2017) 10.1080/0284186x.2017.1351624

[17]

Vallieres "El Naqa I. a radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities" Phys Med Biol (2015) 10.1088/0031-9155/60/14/5471

[18]

Parada "Accuracy and reliability of a simple calculation for measuring glenoid bone loss on 3-dimensional computed tomography scans" Arthroscopy (2018) 10.1016/j.arthro.2017.07.032

[19]

Huang "Radiomics signature: a potential biomarker for the prediction of disease-free survival in early-stage (I or II) non-small cell lung cancer" Radiology (2016) 10.1148/radiol.2016152234

[20]

Liang "Novel nomogram for preoperative prediction of early recurrence in intrahepatic cholangiocarcinoma" Front Oncol (2018) 10.3389/fonc.2018.00360

[21]

Park "Radiomics signature on magnetic resonance imaging: association with disease-free survival in patients with invasive breast cancer" Clin Cancer Res (2018) 10.1158/1078-0432.ccr-17-3783

[22]

Hu "A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules" Eur Radiol (2019) 10.1007/s00330-018-5539-3

[23]

Wu "Survival prediction in high-grade osteosarcoma using radiomics of diagnostic computed tomography" EBioMedicine (2018) 10.1016/j.ebiom.2018.07.006

[24]

Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin

Bioinformatics 2009 10.1093/bioinformatics/btp324

[25]

cn.MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate

Günter Klambauer, Karin Schwarzbauer, Andreas Mayr et al.

Nucleic Acids Research 2012 10.1093/nar/gks003

[26]

Wald "Future directions in esophageal cancer therapy" Ann Cardiothorac Surg (2017) 10.21037/acs.2017.02.01

[27]

Abdo "Targeted” chemotherapy for esophageal cancer" Front Oncol (2017) 10.3389/fonc.2017.00063

[28]

Bolm "Multimodal anti-tumor approaches combined with immunotherapy to overcome tumor resistance in esophageal and gastric cancer" Anticancer Res (2018) 10.21873/anticanres.12588

[29]

Segal "Decoding global gene expression programs in liver cancer by noninvasive imaging" Nat Biotechnol (2007) 10.1038/nbt1306

[30]

Aerts "Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach" Nat Commun (2014) 10.1038/ncomms5006

[31]

Grossmann "Defining the biological basis of radiomic phenotypes in lung cancer" eLife (2017)

[32]

Wilson "Radiomics of pulmonary nodules and lung cancer" Transl Lung Cancer Res (2017) 10.21037/tlcr.2017.01.04

[33]

Puli "Staging accuracy of esophageal cancer by endoscopic ultrasound: a meta-analysis and systematic review" World J Gastroenterol (2008) 10.3748/wjg.14.1479

[34]

Thosani "Diagnostic accuracy of EUS in differentiating mucosal versus submucosal invasion of superficial esophageal cancers: a systematic review and meta-analysis" Gastrointest Endosc (2012) 10.1016/j.gie.2011.09.016

[35]

Wang "Copy number alterations detected by whole-exome and whole-genome sequencing of esophageal adenocarcinoma" Hum Genomics (2015) 10.1186/s40246-015-0044-0

[36]

Wu "Randomised phase III trial of concurrent chemoradiotherapy with extended nodal irradiation and erlotinib in patients with inoperable oesophageal squamous cell cancer" Eur J Cancer (2018) 10.1016/j.ejca.2018.01.085

Cited By

151

Radiomics-based prediction of recurrence for head and neck cancer patients using data imbalanced correction

Hiroki Oka, Daisuke Kawahara · 2024

Computers in Biology and Medicine

Microfluidic biosensors for biomarker detection in body fluids: a key approach for early cancer diagnosis

Yingyu Zhou, Jia Lu · 2024

Biomarker Research

Metrics

151

Citations

36

References

Details

Published: Jun 01, 2019
Vol/Issue: 44
Pages: 289-297
License: View

Authors

Hebei Medical University

Z

Zhao Jing

International Laboratory for High‐Resolution Earth System Model and Prediction (iHESP) Texas A&M University College Station TX USA; Laboratory for Ocean Dynamics and Climate Qingdao Pilot National Laboratory for Marine Science and Technology Qingdao China; Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES)/College of Oceanic and Atmospheric Sciences Ocean University of China Qingdao China

H

Hongfang Zhang

Ministry of Education Key Laboratory of Synthetic and Natural Functional Molecular Chemistry, College of Chemistry & Materials Science, Shaanxi Provincial Key Laboratory of Electroanalytical Chemistry, Northwest University, Xi’an 710127, China

Funding

National Natural Science Foundation of China

Cite This Article

Congying Xie, Pengfei Yang, Xuebang Zhang, et al. (2019). Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy. EBioMedicine, 44, 289-297. https://doi.org/10.1016/j.ebiom.2019.05.023

Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy

You May Also Like