Related Experiment Video
Updated: Feb 4, 2026

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Individualized estimates of overall survival in radiation therapy plan optimization - A concept study
Arezoo Modiri1, Line Bjerregaard Stick2, Stephanie Renee Rice3
1School of Medicine, University of Maryland, Baltimore, MD, USA.
Purpose:
Current radiation therapy planning uses a set of defined dose-volume constraints to ensure a specified level of tumor coverage while constraining the dose distribution in the organs at risk. Such constraints are aggregated, population-based quantities that do not adequately consider patient-specific risk factors. Furthermore, these constraints are calculated for each organ independently and it is therefore not guaranteed that the optimal trade-off between organs is achieved. We introduce a novel radiotherapy planning approach where a patient-specific all-cause mortality risk is minimized using inverse plan optimization. As illustration of concept, our outcome risk model incorporates patient age, sex, cardiac risk factor (CRF), and smoking.
Methods And Materials:
We retrospectively analyzed a left-sided breast cancer case and a Hodgkin's lymphoma case, both clinically treated with three-dimensional conformal radiotherapy (3D-CRT). Our objective function for inverse plan optimization was an equally weighted summation of risk models for cancer recurrence and mortality from radiation-induced coronary heart disease and secondary lung and breast cancers incorporating patient age, sex, CRF, and smoking. We allowed the optimization algorithm to choose from a large set of gantry angles. The optimization task was to choose beams and optimize monitor units (MUs) so that overall survival was maximized (and the total risk of cancer recurrence and mortality from radiation-induced causes were minimized). The sensitivity analysis was performed in the lymphoma case by changing the tumor control probability model from using mean dose (Model 1) to using generalized equivalent uniform dose (Model 2).
Results:
For the breast case in this study, the 3D-CRT clinical plan used eight beams while the proposed 3D-CRT outcome-optimized plan used five beams, reducing the total risk - summation of the risks of recurrence and secondary disease mortality - from 3% to 2%. The mean doses to clinical target volume (CTV) and internal mammary nodes (IMN) were increased in the outcome-optimized plan by 1.9 and 1.8 Gy, respectively. For the Hodgkin's lymphoma case, the clinical 3D-CRT plan used two beams, while the proposed 3D-CRT outcome-optimized plan used three beams, reducing the total risk by 6% (from 16% to 10%). Using either of the two tumor control models for the lymphoma case resulted in outcome-optimized plans where tumor control was compensated at the cost of saving organs at risk. However, the impact of sensitivity to models was comparatively large. Using Model 1 resulted in a reduction in mean target dose by 15.2 vs 7.1 Gy for Model 2. In all cases, the chosen beams in outcome-optimized plans were different from clinically used beams.
Conclusions:
The proposed optimization strategy, supplanting dosimetric objectives with comprehensive individual risk estimates, has the potential to yield improved outcomes in terms of reduced mortality risk in cancer patients treated with radiotherapy. The approach is, however, currently limited by gaps in knowledge about the effect of compromising dose to part of the target, for example, in order to spare cardiac structures.
More Related Videos
Related Concept Videos
Biological Effects of Radiation
Self-Concept
Infancy and Emerging Recognition
During infancy, self-concept is virtually nonexistent. Babies do not distinguish themselves as separate entities and often mistake their...
Optimal Foraging
Concepts and Prototypes
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
Formula Mass and Mole Concepts of Compounds
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...

