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Cited by in CrossRef
For: Cai G, Xu Y, Zhu J, Gu WL, Zhang S, Ma XJ, Cai SJ, Zhang Z. Diffusion-weighted magnetic resonance imaging for predicting the response of rectal cancer to neoadjuvant concurrent chemoradiation. World J Gastroenterol 2013; 19(33): 5520-5527 [PMID: 24023496 DOI: 10.3748/wjg.v19.i33.5520]
URL: https://www.wjgnet.com/1948-5204/full/v19/i33/5520.htm
Number Citing Articles
1
S Nougaret, F Castan, H Forges, H A Vargas, B Gallix, S Gourgou, P Rouanet, E Rullier, B Lelong, P Maingon, J-J Tuech, D Pezet, M Rivoire, B Meunier, J Loriau, A Valverde, J-M Fabre, M Prudhomme, E Cotte, G Portier, L Quero, B Gallix, C Lemanski, M Ychou, F Bibeau. Early MRI predictors of disease-free survival in locally advanced rectal cancer from the GRECCAR 4 trialBritish Journal of Surgery 2019; 106(11): 1530 doi: 10.1002/bjs.11233
2
F. De Felice, A.L. Magnante, D. Musio, M. Ciolina, C.N. De Cecco, M. Rengo, A. Laghi, V. Tombolini. Diffusion-weighted magnetic resonance imaging in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapyEuropean Journal of Surgical Oncology (EJSO) 2017; 43(7): 1324 doi: 10.1016/j.ejso.2017.03.010
3
Jianxing Qiu, Jing Liu, Zhongxu Bi, Xiaowei Sun, Xin Wang, Junling Zhang, Chengwen Liu, Jinxia Zhu, Naishan Qin. Integrated slice-specific dynamic shimming diffusion weighted imaging (DWI) for rectal Cancer detection and characterizationCancer Imaging 2021; 21(1) doi: 10.1186/s40644-021-00403-9
4
Paul B. Romesser, Neelam Tyagi, Christopher H. Crane. Magnetic Resonance Imaging-Guided Adaptive Radiotherapy for Colorectal Liver MetastasesCancers 2021; 13(7): 1636 doi: 10.3390/cancers13071636
5
Piet Dirix, Karin Haustermans, Vincent Vandecaveye. The Value of Magnetic Resonance Imaging for Radiotherapy PlanningSeminars in Radiation Oncology 2014; 24(3): 151 doi: 10.1016/j.semradonc.2014.02.003
6
Narek Shaverdian, Yingli Yang, Peng Hu, Steven Hart, Ke Sheng, James Lamb, Minsong Cao, Nzhde Agazaryan, David Thomas, Michael Steinberg, Daniel A Low, Percy Lee. Feasibility evaluation of diffusion-weighted imaging using an integrated MRI-radiotherapy system for response assessment to neoadjuvant therapy in rectal cancerThe British Journal of Radiology 2017; 90(1071): 20160739 doi: 10.1259/bjr.20160739
7
Alexey Surov, Hans Jonas Meyer, Anne-Kathrin Höhn, Curd Behrmann, Andreas Wienke, Rolf Peter Spielmann, Nikita Garnov. Correlations between intravoxel incoherent motion (IVIM) parameters and histological findings in rectal cancer: preliminary resultsOncotarget 2017; 8(13): 21974 doi: 10.18632/oncotarget.15753
8
Andreas M. Hötker, Julio Garcia-Aguilar, Marc J. Gollub. Multiparametric MRI of Rectal Cancer in the Assessment of Response to TherapyDiseases of the Colon & Rectum 2014; 57(6): 790 doi: 10.1097/DCR.0000000000000127
9
Hai-Bin Zhu, Xiao-Yan Zhang, Xiao-Hong Zhou, Xiao-Ting Li, Yu-Liang Liu, Shuai Wang, Ying-Shi Sun. Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: A prospective single-center studyJournal of Magnetic Resonance Imaging 2017; 46(1): 175 doi: 10.1002/jmri.25567
10
Ulrike I. Attenberger, Ralf D. Hofheinz, Barbara D. Wichtmann. MRT-basierte Chirurgie des Rektumkarzinoms2020; : 95 doi: 10.1007/978-3-662-58159-9_9
11
Guillermo P. Sangster, David H. Ballard, Miguel Nazar, Richard Tsai, Maren Donato, Horacio B. D'Agostino. Multimodality Imaging Review of Anorectal and Perirectal Diseases With Histological, Endoscopic, and Operative Correlation, Part I: Anatomy and NeoplasmsCurrent Problems in Diagnostic Radiology 2019; 48(5): 494 doi: 10.1067/j.cpradiol.2018.07.015
12
Pilar Adriana Torres-Mesa, Ricardo Oliveros, Jorge Mesa, Natalia Olaya, Ricardo Sánchez. Desenlaces del manejo no quirúrgico posterior a neoadyuvancia del cáncer localmente avanzado de rectoRevista Colombiana de Cancerología 2014; 18(3): 109 doi: 10.1016/j.rccan.2014.05.003
13
Rania A. Marouf, Mary Y. Tadros, Tarek Y. Ahmed. Value of diffusion-weighted MR imaging in assessing response of neoadjuvant chemo and radiation therapy in locally advanced rectal cancerThe Egyptian Journal of Radiology and Nuclear Medicine 2015; 46(3): 553 doi: 10.1016/j.ejrnm.2015.03.005
14
Maria Napoletano, Daniele Mazzucca, Enrico Prosperi, Maria Cristina Aisa, Marco Lupattelli, Cynthia Aristei, Michele Scialpi. Locally advanced rectal cancer: qualitative and quantitative evaluation of diffusion-weighted magnetic resonance imaging in restaging after neoadjuvant chemo-radiotherapyAbdominal Radiology 2019; 44(11): 3664 doi: 10.1007/s00261-019-02012-4
15
Barbara D. Wichtmann, Steffen Albert, Wenzhao Zhao, Angelika Maurer, Claus Rödel, Ralf-Dieter Hofheinz, Jürgen Hesser, Frank G. Zöllner, Ulrike I. Attenberger. Are We There Yet? The Value of Deep Learning in a Multicenter Setting for Response Prediction of Locally Advanced Rectal Cancer to Neoadjuvant ChemoradiotherapyDiagnostics 2022; 12(7): 1601 doi: 10.3390/diagnostics12071601
16
Luís Curvo-Semedo. Usefulness of diffusion-weighted MRI in the characterization and assessment of response to neoadjuvant therapy in rectal cancerImaging in Medicine 2014; 6(1): 75 doi: 10.2217/iim.13.72
17
Kumar Sandrasegaran. Functional MR Imaging of the AbdomenRadiologic Clinics of North America 2014; 52(4): 883 doi: 10.1016/j.rcl.2014.02.018
18
Adam Gladwish, Kathy Han. Increasing the Therapeutic Ratio of RadiotherapyCancer Drug Discovery and Development 2017; : 203 doi: 10.1007/978-3-319-40854-5_9
19
Haiting Xie, Tao Sun, Ming Chen, Hao Wang, Xin Zhou, Yunkai Zhang, Huanhong Zeng, Jilian Wang, Wei Fu. Effectiveness of the Apparent Diffusion Coefficient for Predicting the Response to Chemoradiation Therapy in Locally Advanced Rectal CancerMedicine 2015; 94(6): e517 doi: 10.1097/MD.0000000000000517
20
Niels W. Schurink, Doenja M.J. Lambregts, Regina G.H. Beets-Tan. Diffusion-weighted imaging in rectal cancer: current applications and future perspectivesThe British Journal of Radiology 2019; 92(1096): 20180655 doi: 10.1259/bjr.20180655
21
Nathan Hearn, Alexandria Leppien, Patrick O’Connor, Katelyn Cahill, Daisy Atwell, Dinesh Vignarajah, Myo Min. Radiotherapy dose escalation using pre-treatment diffusion-weighted imaging in locally advanced rectal cancer: a planning studyBJR|Open 2023; 6(1) doi: 10.1093/bjro/tzad001
22
Roberta Fusco, Vincenza Granata, Mario Sansone, Robert Grimm, Paolo Delrio, Daniela Rega, Fabiana Tatangelo, Antonio Avallone, Nicola Raiano, Giuseppe Totaro, Vincenzo Cerciello, Biagio Pecori, Antonella Petrillo. Intravoxel Incoherent Motion Model of Diffusion Weighted Imaging and Diffusion Kurtosis Imaging in Differentiating of Local Colorectal Cancer Recurrence from Scar/Fibrosis Tissue by Multivariate Logistic Regression AnalysisApplied Sciences 2020; 10(23): 8609 doi: 10.3390/app10238609
23
Sergio Grosu, Arnd-Oliver Schäfer, Tobias Baumann, Philipp Manegold, Mathias Langer, Axel Gerstmair. Differentiating locally recurrent rectal cancer from scar tissue: Value of diffusion-weighted MRIEuropean Journal of Radiology 2016; 85(7): 1265 doi: 10.1016/j.ejrad.2016.04.006
24
Lotte Jacobs, Martijn Intven, Niels van Lelyveld, Marielle Philippens, Maarten Burbach, Kees Seldenrijk, Maartje Los, Onne Reerink. Diffusion-weighted MRI for Early Prediction of Treatment Response on Preoperative Chemoradiotherapy for Patients With Locally Advanced Rectal CancerAnnals of Surgery 2016; 263(3): 522 doi: 10.1097/SLA.0000000000001311
25
Jia Wang, Xuejun Liu, Bin Hu, Yuanxiang Gao, Jingjing Chen, Jie Li. Development and validation of an MRI-based radiomic nomogram to distinguish between good and poor responders in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapyAbdominal Radiology 2021; 46(5): 1805 doi: 10.1007/s00261-020-02846-3
26
Ke Nie, Liming Shi, Qin Chen, Xi Hu, Salma K. Jabbour, Ning Yue, Tianye Niu, Xiaonan Sun. Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRIClinical Cancer Research 2016; 22(21): 5256 doi: 10.1158/1078-0432.CCR-15-2997
27
Trang T Pham, Gary P Liney, Karen Wong, Michael B Barton. Functional MRI for quantitative treatment response prediction in locally advanced rectal cancerThe British Journal of Radiology 2017; 90(1072): 20151078 doi: 10.1259/bjr.20151078
28
François Lallemand, Natacha Leroi, Silvia Blacher, Mohamed Ali Bahri, Evelyne Balteau, Philippe Coucke, Agnès Noël, Alain Plenevaux, Philippe Martinive. Tumor Microenvironment Modifications Recorded With IVIM Perfusion Analysis and DCE-MRI After Neoadjuvant Radiotherapy: A Preclinical StudyFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.784437
29
Lawrence F. Lau, David S. Williams, Sze Ting Lee, Andrew M. Scott, Christopher Christophi, Vijayaragavan Muralidharan. Metabolic Response to Preoperative Chemotherapy Predicts Prognosis for Patients Undergoing Surgical Resection of Colorectal Cancer Metastatic to the LiverAnnals of Surgical Oncology 2014; 21(7): 2420 doi: 10.1245/s10434-014-3590-0
30
Ines Joye, Piet Dirix. MRI for Radiotherapy2019; : 95 doi: 10.1007/978-3-030-14442-5_6
31
A.M. Maffione, S. Chondrogiannis, C. Capirci, F. Galeotti, A. Fornasiero, G. Crepaldi, G. Grassetto, L. Rampin, M.C. Marzola, D. Rubello. Early prediction of response by 18F-FDG PET/CT during preoperative therapy in locally advanced rectal cancer: A systematic reviewEuropean Journal of Surgical Oncology (EJSO) 2014; 40(10): 1186 doi: 10.1016/j.ejso.2014.06.005
32
Trang T. Pham, Timothy Stait-Gardner, Cheok Soon Lee, Michael Barton, Petra L. Graham, Gary Liney, Karen Wong, William S. Price. Correlation of ultra-high field MRI with histopathology for evaluation of rectal cancer heterogeneityScientific Reports 2019; 9(1) doi: 10.1038/s41598-019-45450-2
33
Sofie Rahbek, Faisal Mahmood, Michal R Tomaszewski, Lars G Hanson, Kristoffer H Madsen. Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRIPhysics in Medicine & Biology 2023; 68(2): 025006 doi: 10.1088/1361-6560/acaa85
34
Hai-Dong Xu, Yu-Qin Zhang, Wei-Yu Shen, Zheng-Chun Mao. Diffusion-weighted imaging in evaluating the efficacy of concurrent chemoradiotherapy in the treatment of non-small cell lung cancerTumori Journal 2018; 104(3): 188 doi: 10.5301/tj.5000612
35
HIROSHI DOI, NAOHITO BEPPU, TAKASHI KATO, MASASHI NODA, HIDENORI YANAGI, NAOHIRO TOMITA, NORIHIKO KAMIKONYA, SHOZO HIROTA. Diffusion-weighted magnetic resonance imaging for prediction of tumor response to neoadjuvant chemoradiotherapy using irinotecan plus S-1 for rectal cancerMolecular and Clinical Oncology 2015; 3(5): 1129 doi: 10.3892/mco.2015.604
36
Angelina Marina Di Re, Yu Sun, Purnima Sundaresan, Eric Hau, James Wei Tatt Toh, Harriet Gee, Michelle Or, Annette Haworth. MRI radiomics in the prediction of therapeutic response to neoadjuvant therapy for locoregionally advanced rectal cancer: a systematic reviewExpert Review of Anticancer Therapy 2021; 21(4): 425 doi: 10.1080/14737140.2021.1860762
37
Petra J. van Houdt, Yingli Yang, Uulke A. van der Heide. Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive RadiotherapyFrontiers in Oncology 2021; 10 doi: 10.3389/fonc.2020.615643
38
Andrea Delli Pizzi, Roberta Cianci, Domenico Genovesi, Gianluigi Esposito, Mauro Timpani, Alessandra Tavoletta, Pierluigi Pulsone, Raffaella Basilico, Daniela Gabrielli, Consuelo Rosa, Luciana Caravatta, Monica Di Tommaso, Massimo Caulo, Antonella Filippone. Performance of diffusion-weighted magnetic resonance imaging at 3.0T for early assessment of tumor response in locally advanced rectal cancer treated with preoperative chemoradiation therapyAbdominal Radiology 2018; 43(9): 2221 doi: 10.1007/s00261-018-1457-8