Full text

Turn on search term navigation

© 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Imaging plays a fundamental role in all aspects of the cancer management pathway. However, conventional imaging techniques are largely reliant on morphological and size descriptors that have well-known limitations, particularly when considering targeted-therapy response monitoring. Thus, new imaging methods have been developed to characterise cancer and are now routinely implemented, such as diffusion-weighted imaging, dynamic contrast enhancement, positron emission technology (PET) and magnetic resonance spectroscopy. However, despite the improvement these techniques have enabled, limitations still remain. Novel imaging methods are now emerging, intent on further interrogating cancers. These techniques are at different stages of maturity along the biomarker pathway and aim to further evaluate the cancer microstructure (vascular, extracellular and restricted diffusion for cytometry in tumours) magnetic resonance imaging (MRI), luminal water fraction imaging] as well as the metabolic alterations associated with cancers (novel PET tracers, hyperpolarised MRI). Finally, the use of machine learning has shown powerful potential applications. By using prostate cancer as an exemplar, this Review aims to showcase these potentially potent imaging techniques and what stage we are at in their application to conventional clinical practice.

Details

Title
Emerging methods for prostate cancer imaging: evaluating cancer structure and metabolic alterations more clearly
Author
Retter, Adam 1 ; Gong, Fiona 1 ; Syer, Tom 1 ; Singh, Saurabh 1 ; Sola Adeleke 1 ; Punwani, Shonit 1   VIAFID ORCID Logo 

 UCL Centre for Medical Imaging, London, UK 
Pages
2565-2579
Section
Reviews
Publication year
2021
Publication date
Oct 2021
Publisher
John Wiley & Sons, Inc.
ISSN
15747891
e-ISSN
18780261
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2578243430
Copyright
© 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.