Uncomplicated and Cancer-Free Control Probability (UCFCP): A new integral approach to treatment plan optimization in photon radiation therapy

IS2aR, a computational tool to transform voxelized reference phantoms into patient-specific whole-body virtual CTs for peripheral dose estimation

BACKGROUND

The risk of radiogenic cancer induction due to radiotherapy depends on the dose received by the patient's organs. Knowing the position of all organs is needed to assess this dose in a personalized way. However, radiotherapy planning computed tomography (pCT) scans contain truncated patient anatomy, limiting personalized dose evaluation.

PURPOSE

To develop a simple and freely available computational tool that adapts an ICRP reference computational phantom to generate a patient-specific whole-body CT for peripheral dose computations.

METHODS

Various bone-segmentation methods were explored onto fifteen pCTs, and the one with the highest Sørensen-Dice coefficient was implemented. The reference phantom is registered to the pCT, obtaining a registration transform matrix, which is then applied to create the whole-body virtual CT. Additional validation involved a comparison of absorbed doses to organs delineated on both the pCT and the virtual CT.

RESULTS

A dedicated graphical user interface was designed and implemented to house the developed functions for i) selecting a registration region on which automatic bone segmentation and rigid registration will occur, ii) displaying the results of these processes under selectable views, and iii) exporting the final patient-specific whole-body CT. This software was termed IS2aR. The tested whole-body virtual CT generated by IS2aR fulfilled our requirements.

CONCLUSIONS

IS2aR is a user-friendly computational software to create a personalized whole-body CT containing the original structures in the reference phantom. The personalized dose deposited in peripheral organs can be estimated further to assess second cancer induction risk in epidemiological studies.

A simple analytical model for a fast 3D assessment of peripheral photon dose during coplanar isocentric photon radiotherapy

Considering that cancer survival rates have been growing and that nearly two-thirds of those survivors were exposed to clinical radiation during its treatment, the study of long-term radiation effects, especially secondary cancer induction, has become increasingly important. To correctly assess this risk, knowing the dose to out-of-field organs is essential. As it has been reported, commercial treatment planning systems do not accurately calculate the dose far away from the border of the field; analytical dose estimation models may help this purpose. In this work, the development and validation of a new three-dimensional (3D) analytical model to assess the photon peripheral dose during radiotherapy is presented. It needs only two treatment-specific input parameter values, plus information about the linac-specific leakage, when available. It is easy to use and generates 3D whole-body dose distributions and, particularly, the dose to out-of-field organs (as dose–volume histograms) outside the 5% isodose for any isocentric treatment using coplanar beams [including intensity modulated radiotherapy and volumetric modulated arc therapy (VMAT)]. The model was configured with the corresponding Monte Carlo simulation of the peripheral absorbed dose for a 6 MV abdomen treatment on the International Comission on Radiological Protection (ICRP) 110 computational phantom. It was then validated with experimental measurements using thermoluminescent dosimeters in the male ATOM anthropomorphic phantom irradiated with a VMAT treatment for prostate cancer. Additionally, its performance was challenged by applying it to a lung radiotherapy treatment very different from the one used for training. The model agreed well with measurements and simulated dose values. A graphical user interface was developed as a first step to making this work more approachable to a daily clinical application.

Determining Out-of-Field Doses and Second Cancer Risk From Proton Therapy in Young Patients—An Overview

Proton therapy has the potential to provide survival and tumor control outcomes comparable and frequently superior to photon therapy. This has led to a significant concern in the medical physics community on the risk for the induction of second cancers in all patients and especially in younger patients, as they are considered more radiosensitive than adults and have an even longer expected lifetime after treatment. Thus, our purpose is to present an overview of the research carried out on the evaluation of out-of-field doses linked to second cancer induction and the prediction of this risk. Most investigations consisted of Monte Carlo simulations in passive beam facilities for clinical scenarios. These works established that equivalent doses in organs could be up to 200 mSv or 900 mSv for a brain or a craniospinal treatment, respectively. The major contribution to this dose comes from the secondary neutrons produced in the beam line elements. Few works focused on scanned-beam facilities, but available data show that, for these facilities, equivalent doses could be between 2 and 50 times lower. Patient age is a relevant factor in the dose level, especially for younger patients (by means of the size of the body) and, in addition, in the predicted risk by models (due to the age dependence of the radiosensitivity). For risks, the sex of the patient also plays an important role, as female patients show higher sensitivity to radiation. Thus, predicted risks of craniospinal irradiation can range from 8% for a 15-year-old male patient to 58% for a 2-year-old female patient, using a risk model from a radiological protection field. These values must be taken with caution due to uncertainties in risk models, and then dosimetric evaluation of stray radiation becomes mandatory in order to complement epidemiological studies and be able to model appropriate dose–response functions for this dose range. In this sense, analytical models represent a useful tool and some models have been implemented to be used for young patients. Research carried out so far confirmed that proton beam therapy reduces the out-of-field doses and second cancer risk. However, further investigations may be required in scanned-beam delivery systems.

Estimating cancer risks due to whole lungs low dose radiotherapy with different techniques for treating COVID-19 pneumonia

BACKGROUND

Low dose radiotherapy (LDRT) of whole lungs with photon beams is a novel method for treating COVID-19 pneumonia. This study aimed to estimate cancer risks induced by lung LDRT for different radiotherapy delivery techniques.

METHOD

Four different radiotherapy techniques, including 3D-conformal with anterior and posterior fields (3D-CRT AP-PA), 3D-conformal with 8 coplanar fields (3D-CRT 8 fields), eight fields intensity-modulated radiotherapy (IMRT), and volumetric modulated arc therapy using 2 full arcs (VMAT) were planned on the CT images of 32 COVID-19 patients with the prescribed dose of 1 Gy to the lungs. Organ average and maximum doses, and PTV dose distribution indexes were compared between different techniques. The radiation-induced cancer incidence and cancer-specific mortality, and cardiac heart disease risks were estimated for the assessed techniques.

RESULTS

In IMRT and VMAT techniques, heart (mean and max), breast (mean, and max), and stomach (mean) doses and also maximum dose in the body were significantly lower than the 3D-CRT techniques. The calculated conformity indexes were similar in all the techniques. However, the homogeneity indexes were lower (i.e., better) in intensity-modulated techniques (P < 0.03) with no significant differences between IMRT and VMAT plans. Lung cancer incident risks for all the delivery techniques were similar (P > 0.4). Cancer incidence and mortality risks for organs located closer to lungs like breast and stomach were higher in 3D-CRT techniques than IMRT or VMAT techniques (excess solid tumor cancer incidence risks for a 30 years man: 1.94 ± 0.22% Vs. 1.68 ± 0.17%; and women: 6.66 ± 0.81% Vs. 4.60 ± 0.43%: cancer mortality risks for 30 years men: 1.63 ± 0.19% Vs. 1.45 ± 0.15%; and women: 3.63 ± 0.44% Vs. 2.94 ± 0.23%).

CONCLUSION

All the radiotherapy techniques had low cancer risks. However, the overall estimated risks induced by IMRT and VMAT radiotherapy techniques were lower than the 3D-CRT techniques and can be used clinically in younger patients or patients having greater concerns about radiation induced cancers.

Generalized approach for radiotherapy treatment planning by optimizing projected health outcome: preliminary results for prostate radiotherapy patients

Research in cancer care increasingly focuses on survivorship issues, e.g. managing disease- and treatment-related morbidity and mortality occurring during and after treatment. This necessitates innovative approaches that consider treatment side effects in addition to tumor cure. Current treatment-planning methods rely on constrained iterative optimization of dose distributions as a surrogate for health outcomes. The goal of this study was to develop a generally applicable method to directly optimize projected health outcomes. We developed an outcome-based objective function to guide selection of the number, angle, and relative fluence weight of photon and proton radiotherapy beams in a sample of ten prostate-cancer patients by optimizing the projected health outcome. We tested whether outcome-optimized radiotherapy (OORT) improved the projected longitudinal outcome compared to dose-optimized radiotherapy (DORT) first for a statistically significant majority of patients, then for each individual patient. We assessed whether the results were influenced by the selection of treatment modality, late-risk model, or host factors. The results of this study revealed that OORT was superior to DORT. Namely, OORT maintained or improved the projected health outcome of photon- and proton-therapy treatment plans for all ten patients compared to DORT. Furthermore, the results were qualitatively similar across three treatment modalities, six late-risk models, and 10 patients. The major finding of this work was that it is feasible to directly optimize the longitudinal (i.e. long- and short-term) health outcomes associated with the total (i.e. therapeutic and stray) absorbed dose in all of the tissues (i.e. healthy and diseased) in individual patients. This approach enables consideration of arbitrary treatment factors, host factors, health endpoints, and times of relevance to cancer survivorship. It also provides a simpler, more direct approach to realizing the full beneficial potential of cancer radiotherapy.

Low dose radiation therapy for COVID-19: Effective dose and estimation of cancer risk

BACKGROUND AND PURPOSE

The objective of this work is to evaluate the risk of carcinogenesis of low dose ionizing radiation therapy (LDRT), for treatment of immune-related pneumonia following COVID-19 infection, through the estimation of effective dose and the lifetime attributable risk of cancer (LAR).

MATERIAL AND METHODS

LDRT treatment was planned in male and female computational phantoms. Equivalent doses in organs were estimated using both treatment planning system calculations and a peripheral dose model (based on ionization chamber measurements). Skin dose was estimated using radiochromic films. Later, effective dose and LAR were calculated following radiation protection procedures.

RESULTS

Equivalent doses to organs per unit of prescription dose range from 10 mSv/cGy to 0.0051 mSv/cGy. Effective doses range from 204 mSv to 426 mSv, for prescription doses ranging from 50 cGy to 100 cGy. Total LAR for a prescription dose of 50 cGy ranges from 1.7 to 0.29% for male and from 4.9 to 0.54% for female, for ages ranging from 20 to 80 years old.

CONCLUSIONS

The organs that mainly contribute to risk are lung and breast. Risk for out-of-field organs is low, less than 0.06 cases per 10000. Female LAR is on average 2.2 times that of a male of the same age. Effective doses are of the same order of magnitude as the higher-dose interventional radiology techniques. For a 60 year-old male, LAR is 8 times that from a cardiac CT, when prescription dose is 50 cGy.

Justification and optimization of radiation exposures: a new framework to aggregate arbitrary detriments and benefits

Myriad radiation effects, including benefits and detriments, complicate justifying and optimizing radiation exposures. The purpose of this study was to develop a comprehensive conceptual framework and corresponding quantitative methods to aggregate the detriments and benefits of radiation exposures to individuals, groups, and populations. In this study, concepts from the ICRP for low dose were integrated with clinical techniques focused on high dose to develop a comprehensive figure of merit (FOM) that takes into account arbitrary host- and exposure-related factors, endpoints, and time points. The study built on existing methods with three new capabilities: application to individuals, groups, and populations; extension to arbitrary numbers and types of endpoints; and inclusion of limitation, where relevant. The FOM was applied to three illustrative exposure situations: emergency response, diagnostic imaging, and cancer radiotherapy, to evaluate its utility in diverse settings. The example application to radiation protection revealed the FOM's utility in optimizing the benefits and risks to a population while keeping individual exposures below applicable regulatory limits. Examples in diagnostic imaging and cancer radiotherapy demonstrated the FOM's utility for guiding population- and patient-specific decisions in medical applications. The major finding of this work is that it is possible to quantitatively combine the benefits and detriments of any radiation exposure situation involving an individual or population to perform cost-effectiveness analyses using the ICRP key principles of radiation protection. This FOM fills a chronic gap in the application of radiation-protection theory, i.e., limitations of generalized frameworks to algorithmically justify and optimize radiation exposures. This new framework potentially enhances objective optimization and justification, especially in complex exposure situations.

Biological optimization for mediastinal lymphoma radiotherapy - a preliminary study

Purpose: In current radiotherapy (RT) planning and delivery, population-based dose-volume constraints are used to limit the risk of toxicity from incidental irradiation of organs at risks (OARs). However, weighing tradeoffs between target coverage and doses to OARs (or prioritizing different OARs) in a quantitative way for each patient is challenging. We introduce a novel RT planning approach for patients with mediastinal Hodgkin lymphoma (HL) that aims to maximize overall outcome for each patient by optimizing on tumor control and mortality from late effects simultaneously.Material and Methods: We retrospectively analyzed 34 HL patients treated with conformal RT (3DCRT). We used published data to model recurrence and radiation-induced mortality from coronary heart disease and secondary lung and breast cancers. Patient-specific doses to the heart, lung, breast, and target were incorporated in the models as well as age, sex, and cardiac risk factors (CRFs). A preliminary plan of candidate beams was created for each patient in a commercial treatment planning system. From these candidate beams, outcome-optimized (O-OPT) plans for each patient were created with an in-house optimization code that minimized the individual risk of recurrence and mortality from late effects. O-OPT plans were compared to VMAT plans and clinical 3DCRT plans.Results: O-OPT plans generally had the lowest risk, followed by the clinical 3DCRT plans, then the VMAT plans with the highest risk with median (maximum) total risk values of 4.9 (11.1), 5.1 (17.7), and 7.6 (20.3)%, respectively (no CRFs). Compared to clinical 3DCRT plans, O-OPT planning reduced the total risk by at least 1% for 9/34 cases assuming no CRFs and 11/34 cases assuming presence of CRFs.Conclusions: We developed an individualized, outcome-optimized planning technique for HL. Some of the resulting plans were substantially different from clinical plans. The results varied depending on how risk models were defined or prioritized.

Study of out-of-field dose in photon radiotherapy: A commercial treatment planning system versus measurements and Monte Carlo simulations

Purpose

An accurate assessment of out‐of‐field dose is necessary to estimate the risk of second cancer after radiotherapy and the damage to the organs at risk surrounding the planning target volume. Although treatment planning systems (TPSs) calculate dose distributions outside the treatment field, little is known about the accuracy of these calculations. The aim of this work is to thoroughly compare the out‐of‐field dose distributions given by two algorithms implemented in the Monaco TPS, with measurements and full Monte Carlo simulations.

Methods

Out‐of‐field dose distributions predicted by the collapsed cone convolution (CCC) and Monte Carlo (MC_Monaco) algorithms, built into the commercially available Monaco version 5.11 TPS, are compared with measurements carried out on an Elekta Axesse linear accelerator. For the measurements, ion chambers, thermoluminescent dosimeters, and EBT3 film are used. The BEAMnrc code, built on the EGSnrc system, is used to create a model of the Elekta Axesse with the Agility collimation system, and the space phase file generated is scored by DOSXYZnrc to generate the dose distributions (MC_EGSnrc). Three different irradiation scenarios are considered: (a) a 10 × 10 cm² field, (b) an IMRT prostate plan, and (c) a three‐field lung plan. Monaco's calculations, experimental measurements, and Monte Carlo simulations are carried out in water and/or in an ICRP110 phantom.

Results

For the 10 × 10 cm² field case, CCC underestimated the dose, compared to ion chamber measurements, by 13% (differences relative to the algorithm) on average between the 5% and the ≈2% isodoses. MC_Monaco underestimated the dose only from approximately the 2% isodose for this case. Qualitatively similar results were observed for the studied IMRT case when compared to film dosimetry. For the three‐field lung plan, dose underestimations of up to ≈90% for MC_Monaco and ≈60% for CCC, relative to MC_EGSnrc simulations, were observed in mean dose to organs located beyond the 2% isodose.

Conclusions

This work shows that Monaco underestimates out‐of‐field doses in almost all the cases considered. Thus, it does not describe dose distribution beyond the border of the field accurately. This is in agreement with previously published works reporting similar results for other TPSs. Analytical models for out‐of‐field dose assessment, MC simulations or experimental measurements may be an adequate alternative for this purpose.