Literature DB >> 29423223

Meta-analysis of diffusion-weighted imaging for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma.

Qiming Zhou1,2, Fangfang Zeng3, Yao Ding4, Clifton D Fuller4, Jihong Wang2.   

Abstract

The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma (HNSCC). A comprehensive search was conducted through the EMBASE, PubMed and Cochrane Library databases for relevant publications. Stata software was used to calculate the pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratios, and to construct a summary receiver operating characteristics (sROC) curve for DWI. A total of 9 studies comprising 421 patients were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 0.82 [95% confidence interval (CI): 0.72-0.88], 0.70 (95% CI: 0.62-0.77), 2.7 (95% CI: 2.1-3.6), 0.26 (95% CI: 0.17-0.41), and 10.48 (95% CI: 5.35-20.53), respectively. The area under the sROC curve was 0.84 (95% CI: 0.81-0.87). Therefore, DWI appears to be a promising imaging modality for predicting local failure of chemoradiotherapy in patients with HNSCC.

Entities:  

Keywords:  chemoradiotherapy; diffusion-weighted imaging; head and neck squamous cell carcinoma; locoregional failure

Year:  2017        PMID: 29423223      PMCID: PMC5772961          DOI: 10.3892/mco.2017.1504

Source DB:  PubMed          Journal:  Mol Clin Oncol        ISSN: 2049-9450


  26 in total

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Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-09-09       Impact factor: 7.038

2.  Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for head and neck squamous cell carcinoma.

Authors:  Vincent Vandecaveye; Piet Dirix; Frederik De Keyzer; Katya Op de Beeck; Vincent Vander Poorten; I Roebben; Sandra Nuyts; Robert Hermans
Journal:  Eur Radiol       Date:  2010-02-24       Impact factor: 5.315

3.  Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy.

Authors:  Elisa Scalco; Simona Marzi; Giuseppe Sanguineti; Antonello Vidiri; Giovanna Rizzo
Journal:  Phys Med       Date:  2016-09-14       Impact factor: 2.685

4.  Is there a benefit in using magnetic resonance imaging in the prediction of preoperative neoadjuvant therapy response in locally advanced rectal cancer?

Authors:  Lian-Ming Wu; Jiong Zhu; Jiani Hu; Yan Yin; Hai-Yan Gu; Jia Hua; Jie Chen; Jian-Rong Xu
Journal:  Int J Colorectal Dis       Date:  2013-03-21       Impact factor: 2.571

5.  Value of magnetic resonance diffusion-weighted imaging for the prediction of radiosensitivity in nasopharyngeal carcinoma.

Authors:  Jinsheng Hong; Yiqi Yao; Yu Zhang; Tianlan Tang; Hao Zhang; Daoliang Bao; Yunbin Chen; Jianji Pan
Journal:  Otolaryngol Head Neck Surg       Date:  2013-07-24       Impact factor: 3.497

6.  Induction chemotherapy followed by radiotherapy for larynx preservation in advanced laryngeal and hypopharyngeal cancer: Outcome prediction after one cycle induction chemotherapy by a score based on clinical evaluation, computed tomography-based volumetry and 18F-FDG-PET/CT.

Authors:  Gunnar Wichmann; Anne Krüger; Andreas Boehm; Marlen Kolb; Mathias Hofer; Milos Fischer; Stefan Müller; Sandra Purz; Patrick Stumpp; Osama Sabri; Andreas Dietz; Regine Kluge
Journal:  Eur J Cancer       Date:  2016-12-26       Impact factor: 9.162

7.  Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck.

Authors:  Sungheon Kim; Laurie Loevner; Harry Quon; Eric Sherman; Gregory Weinstein; Alex Kilger; Harish Poptani
Journal:  Clin Cancer Res       Date:  2009-02-01       Impact factor: 12.531

8.  Diffusion magnetic resonance imaging: an imaging treatment response biomarker to chemoradiotherapy in a mouse model of squamous cell cancer of the head and neck.

Authors:  Daniel A Hamstra; Kuei C Lee; Bradford A Moffat; Thomas L Chenevert; Alnawaz Rehemtulla; Brian D Ross
Journal:  Transl Oncol       Date:  2008-12       Impact factor: 4.243

9.  Diffusion-weighted MR imaging in laryngeal and hypopharyngeal carcinoma: association between apparent diffusion coefficient and histologic findings.

Authors:  Juliette P Driessen; Joana Caldas-Magalhaes; Luuk M Janssen; Frank A Pameijer; Nina Kooij; Chris H J Terhaard; Wilko Grolman; Marielle E P Philippens
Journal:  Radiology       Date:  2014-04-17       Impact factor: 11.105

Review 10.  Magnetic resonance imaging versus computed tomography for detection of acute vascular lesions in patients presenting with stroke symptoms.

Authors:  Miriam Brazzelli; Peter Ag Sandercock; Francesca M Chappell; Maria Grazia Celani; Enrico Righetti; Nicholas Arestis; Joanna M Wardlaw; Jonathan J Deeks
Journal:  Cochrane Database Syst Rev       Date:  2009-10-07
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  2 in total

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Authors:  Daniela Alterio; Lorenzo Preda; Stefania Volpe; Caterina Giannitto; Giulia Riva; Frank Arthur Kamga Pounou; Murat Atac; Gioacchino Giugliano; Roberto Bruschini; Annamaria Ferrari; Giulia Marvaso; Maria Cossu Rocca; Elena Verri; Duccio Rossi; Massimo Bellomi; Barbara Alicja Jereczek-Fossa; Roberto Orecchia; Mohssen Ansarin
Journal:  Acta Otorhinolaryngol Ital       Date:  2020-02       Impact factor: 2.124

2.  Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group.

Authors:  Petra J van Houdt; Hina Saeed; Daniela Thorwarth; Clifton D Fuller; William A Hall; Brigid A McDonald; Amita Shukla-Dave; Ernst S Kooreman; Marielle E P Philippens; Astrid L H M W van Lier; Rick Keesman; Faisal Mahmood; Catherine Coolens; Teodor Stanescu; Jihong Wang; Neelam Tyagi; Andreas Wetscherek; Uulke A van der Heide
Journal:  Eur J Cancer       Date:  2021-06-15       Impact factor: 10.002

  2 in total

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