The Use of Imaging in the Prediction and Assessment of Cancer Treatment Toxicity

Abstract

Multimodal imaging is commonly used in the management of patients with cancer. Imaging plays pivotal roles in the diagnosis, initial staging, treatment response assessment, restaging after treatment and the prognosis of many cancers. Indeed, it is difficult to imagine modern precision cancer care without the use of multimodal molecular imaging, which is advancing at a rapid pace with innovative developments in imaging sciences and an improved understanding of the complex biology of cancer. Cancer therapy often leads to undesirable toxicity, which can range from an asymptomatic subclinical state to severe end organ damage and even death. Imaging is helpful in the portrayal of the unwanted effects of cancer therapy and may assist with optimal clinical decision-making, clinical management, and overall improvements in the outcomes and quality of life for patients.

A Score-Based Approach to 18F-FDG PET Images as a Tool to Describe Metabolic Predictors of Myocardial Doxorubicin Susceptibility

“…This phenomenon is attributable to both secondary malignancies and late cardiotoxicity [ 2 , 3 , 4 ] and can considerably impair life expectancy in younger patients. Moreover, the occurrence of cardiac injury can decisively affect both overall performance status as well as quality of life, particularly in elderly subjects, in patients with cardiovascular comorbidities, or in those in which additional thoracic irradiation is indicated [ 4 , 5 , 6 , 7 ]. In these regards, dose-dependent anthracycline-induced cardiomyopathy is one of the most acknowledged and well-studied clinical models of cardiovascular toxicity by chemotherapy.…”

Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer

“…This highlights the importance of discovering and validating biomarkers that are both sensitive to treatment effects and predict outcomes following combination cancer therapies [ 2 ], enabling patient risk stratification for individualized treatment techniques. Risk stratification studies have focused on early detection and cancerous nodules classification [ 3 , 4 , 5 ], histologic subtype classification [ 6 ], prognosis after radiation therapy or surgery [ 7 ], prediction of lung toxicity after radiation therapy [ 8 , 9 ], and prediction of response to chemoradiation or immunotherapy [ 10 , 11 , 12 ], utilizing a variety of survival prediction modeling [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ].…”