A review of diffusion-weighted magnetic resonance imaging in head and neck cancer patients for treatment evaluation and prediction of radiation-induced xerostomia

被引:0
作者
Tai Ermongkonchai
Richard Khor
Morikatsu Wada
Eddie Lau
Daniel Tao Xing
Sweet Ping Ng
机构
[1] Austin Health,Department of Radiation Oncology, Olivia
[2] Austin Health,Newton John Cancer and Wellness Centre
[3] Austin Health,Department of Radiology
[4] The University of Melbourne,Department of Molecular Imaging and Therapy
来源
Radiation Oncology | / 18卷
关键词
Diffusion magnetic resonance imaging; Head and neck cancer; Magnetic resonance imaging; Radiotherapy; Xerostomia;
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摘要
The incidence of head and neck cancers (HNC) is rising worldwide especially with HPV-related oropharynx squamous cell carcinoma. The standard of care for the majority of patients with locally advanced pharyngeal disease is curative-intent radiotherapy (RT) with or without concurrent chemotherapy. RT-related toxicities remain a concern due to the close proximity of critical structures to the tumour, with xerostomia inflicting the most quality-of-life burden. Thus, there is a paradigm shift towards research exploring the use of imaging biomarkers in predicting treatment outcomes. Diffusion-weighted imaging (DWI) is a functional MRI feature of interest, as it quantifies cellular changes through computation of apparent diffusion coefficient (ADC) values. DWI has been used in differentiating HNC lesions from benign tissues, and ADC analyses can be done to evaluate tumour responses to RT. It is also useful in healthy tissues to identify the heterogeneity and physiological changes of salivary glands to better understand the inter-individual differences in xerostomia severity. Additionally, DWI is utilised in irradiated salivary glands to produce ADC changes that correlate to clinical xerostomia. The implementation of DWI into multi-modal imaging can help form prognostic models that identify patients at risk of severe xerostomia, and thus guide timely interventions to mitigate these toxicities.
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