Literature DB >> 28256151

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective.

Kee H Wong1,2, Rafal Panek1,2, Shreerang A Bhide1,2, Christopher M Nutting1,2, Kevin J Harrington1,2, Katie L Newbold1,2.   

Abstract

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

Entities:  

Mesh:

Year:  2017        PMID: 28256151      PMCID: PMC5601510          DOI: 10.1259/bjr.20160768

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  82 in total

1.  Evaluation of the larynx for tumour recurrence by diffusion-weighted MRI after radiotherapy: initial experience in four cases.

Authors:  V Vandecaveye; F de Keyzer; V Vander Poorten; K Deraedt; H Alaerts; W Landuyt; S Nuyts; R Hermans
Journal:  Br J Radiol       Date:  2006-04-26       Impact factor: 3.039

2.  Microvessel density of invasive breast cancer assessed by dynamic Gd-DTPA enhanced MRI.

Authors:  D L Buckley; P J Drew; S Mussurakis; J R Monson; A Horsman
Journal:  J Magn Reson Imaging       Date:  1997 May-Jun       Impact factor: 4.813

3.  Clinical outcomes of adaptive radiotherapy in head and neck cancers.

Authors:  Tejinder Kataria; Deepak Gupta; Shikha Goyal; Shyam S Bisht; Trinanjan Basu; Ashu Abhishek; Kushal Narang; Susovan Banerjee; Shahida Nasreen; Sasikumar Sambasivam; Aruj Dhyani
Journal:  Br J Radiol       Date:  2016-03-17       Impact factor: 3.039

Review 4.  The promise and pitfalls of positron emission tomography and single-photon emission computed tomography molecular imaging-guided radiation therapy.

Authors:  Richard L Wahl; Joseph M Herman; Eric Ford
Journal:  Semin Radiat Oncol       Date:  2011-04       Impact factor: 5.934

5.  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

6.  Comparative dosimetry of three-phase adaptive and non-adaptive dose-painting IMRT for head-and-neck cancer.

Authors:  Luiza A M Olteanu; Dieter Berwouts; Indira Madani; Werner De Gersem; Tom Vercauteren; Fréderic Duprez; Wilfried De Neve
Journal:  Radiother Oncol       Date:  2014-04-17       Impact factor: 6.280

7.  Assessment of serial multi-parametric functional MRI (diffusion-weighted imaging and R2*) with (18)F-FDG-PET in patients with head and neck cancer treated with radiation therapy.

Authors:  Myo Min; Mark T Lee; Peter Lin; Lois Holloway; Dj Wijesekera; Dinesh Gooneratne; Robba Rai; Wei Xuan; Allan Fowler; Dion Forstner; Gary Liney
Journal:  Br J Radiol       Date:  2015-12-09       Impact factor: 3.039

8.  Metastatic retropharyngeal lymph nodes: comparison of CT and MR imaging for diagnostic accuracy.

Authors:  Hiroki Kato; Masayuki Kanematsu; Haruo Watanabe; Keisuke Mizuta; Mitsuhiro Aoki
Journal:  Eur J Radiol       Date:  2014-03-29       Impact factor: 3.528

9.  Intensity-modulated radiotherapy in the treatment of oropharyngeal cancer: clinical outcomes and patterns of failure.

Authors:  Megan E Daly; Quynh-Thu Le; Peter G Maxim; Billy W Loo; Michael J Kaplan; Nancy J Fischbein; Harlan Pinto; Daniel T Chang
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-06-18       Impact factor: 7.038

10.  Diffusion weighted MRI in head-and-neck cancer: geometrical accuracy.

Authors:  Tim Schakel; Johannes M Hoogduin; Chris H J Terhaard; Marielle E P Philippens
Journal:  Radiother Oncol       Date:  2013-10-31       Impact factor: 6.280

View more
  13 in total

1.  The quantitative impact of joint peer review with a specialist radiologist in head and neck cancer radiotherapy planning.

Authors:  Kevin Chiu; Peter Hoskin; Amit Gupta; Roeum Butt; Samsara Terparia; Louise Codd; Yatman Tsang; Jyotsna Bhudia; Helen Killen; Clare Kane; Subhadip Ghoshray; Catherine Lemon; Daniel Megias
Journal:  Br J Radiol       Date:  2021-12-21       Impact factor: 3.039

2.  A pilot study of highly accelerated 3D MRI in the head and neck position verification for MR-guided radiotherapy.

Authors:  Yihang Zhou; Oi Lei Wong; Kin Yin Cheung; Siu Ki Yu; Jing Yuan
Journal:  Quant Imaging Med Surg       Date:  2019-07

3.  Cross-modality deep learning: Contouring of MRI data from annotated CT data only.

Authors:  Jennifer P Kieselmann; Clifton D Fuller; Oliver J Gurney-Champion; Uwe Oelfke
Journal:  Med Phys       Date:  2020-12-13       Impact factor: 4.071

4.  Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

Authors:  Xinyuan Chen; Jianrong Dai
Journal:  J Appl Clin Med Phys       Date:  2018-03-24       Impact factor: 2.102

5.  MR-Guided Radiotherapy for Head and Neck Cancer: Current Developments, Perspectives, and Challenges.

Authors:  Simon Boeke; David Mönnich; Janita E van Timmeren; Panagiotis Balermpas
Journal:  Front Oncol       Date:  2021-03-19       Impact factor: 6.244

Review 6.  Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.

Authors:  Amita Shukla-Dave; Nancy A Obuchowski; Thomas L Chenevert; Sachin Jambawalikar; Lawrence H Schwartz; Dariya Malyarenko; Wei Huang; Susan M Noworolski; Robert J Young; Mark S Shiroishi; Harrison Kim; Catherine Coolens; Hendrik Laue; Caroline Chung; Mark Rosen; Michael Boss; Edward F Jackson
Journal:  J Magn Reson Imaging       Date:  2018-11-19       Impact factor: 5.119

7.  Diffusion-kurtosis imaging predicts early radiotherapy response in nasopharyngeal carcinoma patients.

Authors:  Gang Wu; Meng-Meng Li; Feng Chen; Shao-Ming Lin; Kai Yang; Ying-Man Zhao; Xiao-Lei Zhu; Wei-Yuan Huang; Jian-Jun Li
Journal:  Oncotarget       Date:  2017-08-02

Review 8.  The Promise of Novel Biomarkers for Head and Neck Cancer from an Imaging Perspective.

Authors:  Loredana G Marcu; Paul Reid; Eva Bezak
Journal:  Int J Mol Sci       Date:  2018-08-24       Impact factor: 5.923

9.  Radiation-induced parotid changes in oropharyngeal cancer patients: the role of early functional imaging and patient-/treatment-related factors.

Authors:  Simona Marzi; Alessia Farneti; Antonello Vidiri; Francesca Di Giuliano; Laura Marucci; Filomena Spasiano; Irene Terrenato; Giuseppe Sanguineti
Journal:  Radiat Oncol       Date:  2018-10-01       Impact factor: 3.481

10.  Impact of CT slice thickness on volume and dose evaluation during thoracic cancer radiotherapy.

Authors:  Huanli Luo; Yanan He; Fu Jin; Dingyi Yang; Xianfeng Liu; Xueqi Ran; Ying Wang
Journal:  Cancer Manag Res       Date:  2018-09-20       Impact factor: 3.989

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.