Abstract
Objectives
The research focuses on the impact of radiation therapy (RT) on cardiac health, particularly by examining how advancements in RT technology and increased awareness of cardiotoxic risks have affected cardiac dose levels over time. The research examines the relationship between cardiac radiation doses, patient-specific factors, and long-term outcomes, including cardiovascular disease (CVD) and overall survival.
Methods
The studies analyzed data from a cohort of over 10,000 patients treated for various cancers (breast, lung, lymphoma, and esophageal) between 2009 and 2020. Artificial intelligence (AI) segmentation tools were used to delineate heart structures from CT scans and calculate dose metrics such as mean heart dose (MHD) and volumetric measures of these structures. The research also used statistical methods, including the Aalen-Johansen estimator and Cox proportional hazards, to assess the relationship between radiation doses, patient characteristics, and adverse outcomes collected from registry-based data.
Results
Study I found a significant decrease in cardiac doses over the study period, particularly in high-dose exposures. However, a recent increase in high-dose volumes for breast cancer treatments was noted. Study II revealed that patient-specific factors, such as pre-existing cardiac conditions and age, were stronger predictors of cardiovascular issues than radiation dose itself, with no clear dose-response relationship established with CVD.
Conclusions
Results highlight the potential of AI tools to generate individually
defined structures and calculate precise dose metrics, as well as the value of linking registry databases to obtain reliable results for a substantial retrospective cohort. We can conclude that advances in RT techniques and increased clinical awareness have generally led to improved heart sparing. It is still important to spare heart tissue, but tumor control should be prioritized. Additional analysis, such as substructure segmentation or so-called image-based "data mining techniques", seems to be a promising direction for further understanding of cardiotoxicity and individualization of radiation therapy.
The research focuses on the impact of radiation therapy (RT) on cardiac health, particularly by examining how advancements in RT technology and increased awareness of cardiotoxic risks have affected cardiac dose levels over time. The research examines the relationship between cardiac radiation doses, patient-specific factors, and long-term outcomes, including cardiovascular disease (CVD) and overall survival.
Methods
The studies analyzed data from a cohort of over 10,000 patients treated for various cancers (breast, lung, lymphoma, and esophageal) between 2009 and 2020. Artificial intelligence (AI) segmentation tools were used to delineate heart structures from CT scans and calculate dose metrics such as mean heart dose (MHD) and volumetric measures of these structures. The research also used statistical methods, including the Aalen-Johansen estimator and Cox proportional hazards, to assess the relationship between radiation doses, patient characteristics, and adverse outcomes collected from registry-based data.
Results
Study I found a significant decrease in cardiac doses over the study period, particularly in high-dose exposures. However, a recent increase in high-dose volumes for breast cancer treatments was noted. Study II revealed that patient-specific factors, such as pre-existing cardiac conditions and age, were stronger predictors of cardiovascular issues than radiation dose itself, with no clear dose-response relationship established with CVD.
Conclusions
Results highlight the potential of AI tools to generate individually
defined structures and calculate precise dose metrics, as well as the value of linking registry databases to obtain reliable results for a substantial retrospective cohort. We can conclude that advances in RT techniques and increased clinical awareness have generally led to improved heart sparing. It is still important to spare heart tissue, but tumor control should be prioritized. Additional analysis, such as substructure segmentation or so-called image-based "data mining techniques", seems to be a promising direction for further understanding of cardiotoxicity and individualization of radiation therapy.
| Originalsprog | Engelsk |
|---|---|
| Udgiver | |
| Status | Udgivet - 2024 |