Document Type
Article
Publication Date
11-14-2024
Abstract
The topic of quantitative imaging in radiation therapy was presented as a "Masterclass" at the 2023 annual meeting of the American Society of Radiation Oncology (ASTRO). Dual-energy computed tomography (CT) and single-positron computed tomography were reviewed in detail as the first portion of the meeting session, with data showing utility in many aspects of radiation oncology including treatment planning and dose response. Positron emission tomography/CT scans evaluating the functional volume of lung tissue so as to provide optimal avoidance of healthy lungs were presented second. Advanced brain imaging was then discussed in the context of different forms of magnetic resonance scanning methods as the third area noted with significant discussion of ongoing research programs. Quantitative image analysis was presented to provide clinical utility for the analysis of patients with head and neck cancer. Finally, quality assurance was reviewed for different forms of quantitative imaging given the critical nature of imaging when numerical valuation, not just relative contrast, plays a crucial role in clinical process and decision-making. Conclusions and thoughts are shared in the conclusion, noting strong data supporting the use of quantitative imaging in radiation therapy going forward and that more studies are needed to move the field forward.
Recommended Citation
Vinogradskiy, Yevgeniy; Bahig, Houda; Bucknell, Nicholas; Buchsbaum, Jeffrey; and Shu, Hui-Kuo George, "Conference Report: Review of Clinical Implementation of Advanced Quantitative Imaging Techniques for Personalized Radiotherapy" (2024). Department of Radiation Oncology Faculty Papers. Paper 201.
https://jdc.jefferson.edu/radoncfp/201
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
39590941
Language
English
Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Oncology Commons, Radiation Medicine Commons
Comments
This article is the author's final published version in Tomography, Volume 10, Issue 11, November 2024, Pages 1798 - 1813.
The published version is available at https://doi.org/10.3390/tomography10110132f.
Copyright © 2024 by the authors