Ermongkonchai, Tai, Khor, Richard, Wada, Morikatsu, Lau, Eddie, Xing, Daniel, and Ng, Sweet Ping (2023) A review of diffusion-weighted magnetic resonance imaging in head and neck cancer patients for treatment evaluation and prediction of radiation-induced xerostomia. Radiation Oncology, 18 (1). 20.

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Abstract

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.

Item ID:	81974
Item Type:	Article (Research - C1)
ISSN:	1748-717X
Copyright Information:	© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Date Deposited:	20 Feb 2024 00:35
FoR Codes:	32 BIOMEDICAL AND CLINICAL SCIENCES > 3211 Oncology and carcinogenesis > 321110 Radiation therapy @ 100%
SEO Codes:	20 HEALTH > 2001 Clinical health > 200105 Treatment of human diseases and conditions @ 100%
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