A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: approach

Point-of-care ultrasound as the first imaging strategy in young infants aged under 90 days presenting with gastrointestinal manifestations at the emergency department

This study compared the emergency department (ED) flow of young infants under 90 days old presenting with gastrointestinal symptoms who underwent point-of-care ultrasound (POCUS) versus X-ray (XR) as their primary imaging test. The study retrospectively enrolled infants under 90 days old with gastrointestinal (GI) symptoms who visited a tertiary university-affiliated hospital ED from January 2019 to September 2022. The patients were divided into 2 groups based on whether they received XR or POCUS as their first imaging test. Out of 440 patients, 352 (80%) were enrolled in the XR-first group and 88 (20%) in the POCUS-first group. No significant differences exist in demographics, clinical characteristics, or the prevalence of surgical abdomen between the groups. The time-to-disposition and ED length of stay (EDLOS) were significantly shorter in the POCUS-first group as compared to those in the XR-first group (86 min vs 127 min, P = .013; 121 min vs 157 min, P = .049; respectively). In the POCUS-first group, only 30.7% of the cases required an additional XR. The performance of POCUS in screening for surgical abdomen showed a sensitivity and specificity of 95.8% and 95.3%, respectively. In young infants under 90 days presenting with GI symptoms at the ED, using POCUS as the first imaging test instead of XR can shorten time-to-disposition and EDLOS, improving ED flow with acceptable screening performance for surgical emergencies.

Utilizing patient data: A tutorial on predicting second cancer with machine learning models

BACKGROUND

The article explores the potential risk of secondary cancer (SC) due to radiation therapy (RT) and highlights the necessity for new modeling techniques to mitigate this risk.

METHODS

By employing machine learning (ML) models, specifically decision trees, in the research process, a practical framework is established for forecasting the occurrence of SC using patient data.

RESULTS & DISCUSSION

This framework aids in categorizing patients into high-risk or low-risk groups, thereby enabling personalized treatment plans and interventions. The paper also underscores the many factors that contribute to the likelihood of SC, such as radiation dosage, patient age, and genetic predisposition, while emphasizing the limitations of current models in encompassing all relevant parameters. These limitations arise from the non-linear dependencies between variables and the failure to consider factors such as genetics, hormones, lifestyle, radiation from secondary particles, and imaging dosage. To instruct and assess ML models for predicting the occurrence of SC based on patient data, the paper utilizes a dataset consisting of instances and attributes.

CONCLUSION

The practical implications of this research lie in enhancing our understanding and prediction of SC following RT, facilitating personalized treatment approaches, and establishing a framework for leveraging patient data within the realm of ML models.

Calculation of Organ Dose Distribution (in-field and Out-of-field) in Breast Cancer Radiotherapy on RANDO Phantom Using GEANT4 Application for Tomographic Emission (Gate) Monte Carlo Simulation

Introduction

Organ dose distribution calculation in radiotherapy and knowledge about its side effects in cancer etiology is the most concern for medical physicists. Calculation of organ dose distribution for breast cancer treatment plans with Monte Carlo (MC) simulation is the main goal of this study.

Materials and Methods

Elekta Precise linear accelerator (LINAC) photon mode was simulated and verified using the GEANT4 application for tomographic emission. Eight different radiotherapy treatment plans on RANDO's phantom left breast were produced with the ISOgray treatment planning system (TPS). The simulated plans verified photon dose distribution in clinical tumor volume (CTV) with TPS dose volume histogram (DVH) and gamma index tools. To verify photon dose distribution in out-of-field organs, the point dose measurement results were compared with the same point doses in the MC simulation. Eventually, the DVHs for out-of-field organs that were extracted from the TPS and MC simulation were compared.

Results

Based on the implementation of gamma index tools with 2%/2 mm criteria, the simulated LINAC output demonstrated high agreement with the experimental measurements. Plan simulation for in-field and out-of-field organs had an acceptable agreement with TPS and experimental measurement, respectively. There was a difference between DVHs extracted from the TPS and MC simulation for out-of-field organs in low-dose parts. This difference is due to the inability of the TPS to calculate dose distribution in out-of-field organs.

Conclusion and Discussion

Based on the results, it was concluded that the treatment plans with the MC simulation have a high accuracy for the calculation of out-of-field dose distribution and could play a significant role in evaluating the important role of dose distribution for second primary cancer estimation.

Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

PURPOSE

In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

METHODS AND MATERIALS

The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

RESULTS

Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

CONCLUSIONS

Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases.

Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

BACKGROUND

In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data.

METHODS

We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability.

RESULTS

There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability.

CONCLUSIONS

Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

Out-of-field effects: lessons learned from partial body exposure

Partial body exposure and inhomogeneous dose delivery are features of the majority of medical and occupational exposure situations. However, mounting evidence indicates that the effects of partial body exposure are not limited to the irradiated area but also have systemic effects that are propagated outside the irradiated field. It was the aim of the "Partial body exposure" session within the MELODI workshop 2020 to discuss recent developments and insights into this field by covering clinical, epidemiological, dosimetric as well as mechanistic aspects. Especially the impact of out-of-field effects on dysfunctions of immune cells, cardiovascular diseases and effects on the brain were debated. The presentations at the workshop acknowledged the relevance of out-of-field effects as components of the cellular and organismal radiation response. Furthermore, their importance for the understanding of radiation-induced pathologies, for the discovery of early disease biomarkers and for the identification of high-risk organs after inhomogeneous exposure was emphasized. With the rapid advancement of clinical treatment modalities, including new dose rates and distributions a better understanding of individual health risk is urgently needed. To achieve this, a deeper mechanistic understanding of out-of-field effects in close connection to improved modelling was suggested as priorities for future research. This will support the amelioration of risk models and the personalization of risk assessments for cancer and non-cancer effects after partial body irradiation.

Novel Implications of Nanoparticle-Enhanced Radiotherapy and Brachytherapy: Z-Effect and Tumor Hypoxia

Radiotherapy and internal radioisotope therapy (brachytherapy) induce tumor cell death through different molecular signaling pathways. However, these therapies in cancer patients are constrained by dose-related adverse effects and local discomfort due to the prolonged exposure to the surrounding tissues. Technological advancements in nanotechnology have resulted in synthesis of high atomic elements such as nanomaterials, which can be used as radiosensitizers due to their photoelectric characteristics. The aim of this review is to elucidate the effects of novel nanomaterials in the field of radiation oncology to ameliorate dose-related toxicity through the application of ideal nanoparticle-based radiosensitizers such as Au (gold), Bi (bismuth), and Lu (Lutetium-177) for enhancing cytotoxic effects of radiotherapy via the high-Z effect. In addition, we discuss the role of nanoparticle-enhanced radiotherapy in alleviating tumor hypoxia through the nanodelivery of genes/drugs and other functional anticancer molecules. The implications of engineered nanoparticles in preclinical and clinical studies still need to be studied in order to explore potential mechanisms for radiosensitization by minimizing tumor hypoxia, operational/logistic complications and by overcoming tumor heterogeneity in radiotherapy/brachytherapy.

Biophysical Modeling of the Ionizing Radiation Influence on Cells Using the Stochastic (Monte Carlo) and Deterministic (Analytical) Approaches

This review article describes our simplified biophysical model for the response of a group of cells to ionizing radiation. The model, which is a product of 10 years of studies, acts as (a) a comprehensive stochastic approach based on the Monte Carlo simulation with a probability tree and (b) the thereof derived detailed deterministic models describing the selected biophysical and radiobiological phenomena in an analytical manner. Specifically, the presented model describes effects such as the risk of neoplastic transformation of cells relative to the absorbed radiation dose, the dynamics of tumor development, the priming dose effect (also called the Raper-Yonezawa effect) based on the introduced adaptive response approach, and the bystander effect. The model is also modifiable depending on users' potential needs.

The risk of cancer following high, and very high, doses of ionising radiation

It is established that moderate-to-high doses of ionising radiation increase the risk of subsequent cancer in the exposed individual, but the question arises as to the risk of cancer from higher doses, such as those delivered during radiotherapy, accidents, or deliberate acts of malice. In general, the cumulative dose received during a course of radiation treatment is sufficiently high that it would kill a person if delivered as a single dose to the whole body, but therapeutic doses are carefully fractionated and high/very high doses are generally limited to a small tissue volume under controlled conditions. The very high cumulative doses delivered as fractions during radiation treatment are designed to inactivate diseased cells, but inevitably some healthy cells will also receive high/very high doses. How the doses (ranging from <1 Gy to tens of Gy) received by healthy tissues during radiotherapy affect the risk of second primary cancer is an increasingly important issue to address as more cancer patients survive the disease. Studies show that, except for a turndown for thyroid cancer, a linear dose-response for second primary solid cancers seems to exist over a cumulative gamma radiation dose range of tens of gray, but with a gradient of excess relative risk per Gy that varies with the type of second cancer, and which is notably shallower than that found in the Japanese atomic bomb survivors receiving a single moderate-to-high acute dose. The risk of second primary cancer consequent to high/very high doses of radiation is likely to be due to repopulation of heavily irradiated tissues by surviving stem cells, some of which will have been malignantly transformed by radiation exposure, although the exact mechanism is not known, and various models have been proposed. It is important to understand the mechanisms that lead to the raised risk of second primary cancers consequent to the receipt of high/very high doses, in particular so that the risks associated with novel radiation treatment regimens-for example, intensity modulated radiotherapy and volumetric modulated arc therapy that deliver high doses to the target volume while exposing relatively large volumes of healthy tissue to low/moderate doses, and treatments using protons or heavy ions rather than photons-may be properly assessed.

Tumour volume distribution can yield information on tumour growth and tumour control

BACKGROUND

It is shown that tumour volume distributions can yield information on two aspects of cancer research: tumour induction and tumour control.

MATERIALS AND METHODS

From the hypothesis that the intrinsic distribution of breast cancer volumes follows an exponential distribution, firstly the probability density function of tumour growth time was deduced via a mathematical transformation of the probability density functions of tumour volumes. In a second step, the distribution of tumour volumes was used to model the variation of the clonogenic cell number between patients in order to determine tumour control probabilities for radiotherapy patients.

RESULTS

Distribution of lag times, i.e. the time from the appearance of the first fully malignant cell until a clinically observable cancer, can be used to deduce the probability of tumour induction as a function of patient age. The integration of the volume variation with a Poisson-TCP model results in a logistic function which explains population-averaged survival data of radiotherapy patients.

CONCLUSIONS

The inclusion of tumour volume distributions into the TCP formalism enables a direct link to be deduced between a cohort TCP model (logistic) and a TCP model for individual patients (Poisson). The TCP model can be applied to non-uniform tumour dose distributions.

Estimating long-term health risks after breast cancer radiotherapy: merging evidence from low and high doses

In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy-Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose-response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose-response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients.

Pediatric craniospinal irradiation with a short partial-arc VMAT technique for medulloblastoma tumors in dosimetric comparison

Background

This study aimed to contrast four different irradiation methods for pediatric medulloblastoma tumors in a dosimetric comparison regarding planning target volume (PTV) coverage and sparing of organs at risk (OARs).

Methods

In sum 24 treatment plans for 6 pediatric patients were realized. Besides the clinical standard of a 3D-conformal radiotherapy (3D-CRT) treatment plan taken as a reference, volumetric modulated arc therapy (VMAT) treatment plans (“VMAT_AVD” vs. “noAVD” vs. “FullArc”) were optimized and calculated for each patient. For the thoracic and abdominal region, the short partial-arc VMAT_AVD technique uses an arc setup with reduced arc-length by 100°, using posterior and lateral beam entries. The noAVD uses a half 180° (posterior to lateral directions) and the FullArc uses a full 360° arc setup arrangement. The prescription dose was set to 35.2 Gy.

Results

We identified a more conformal dose coverage for PTVs and a better sparing of OARs with used VMAT methods. For VMAT_AVD mean dose reductions in organs at risk can be realized, from 16 to 6.6 Gy, from 27.1 to 8.7 Gy and from 8.0 to 1.9 Gy for the heart, the thyroid and the gonads respectively, compared to the 3D-CRT treatment method. In addition we have found out a superiority of VMAT_AVD compared to the noAVD and FullArc trials with lower exposure to low-dose radiation to the lungs and breasts.

Conclusions

With the short partial-arc VMAT_AVD technique, dose exposures to radiosensitive OARS like the heart, the thyroid or the gonads can be reduced and therefore, maybe the occurrence of late sequelae is less likely. Furthermore the PTV conformity is increased. The advantages of the VMAT_AVD have to be weighed against the potentially risks induced by an increased low dose exposure compared to the 3D-CRT method.

Estimation of secondary cancer risk after radiotherapy in high-risk prostate cancer patients with pelvic irradiation

We aimed to estimate the risk of secondary cancer after radiotherapy (RT) in high‐risk prostate cancer (HRPC) patients with pelvic irradiation. Computed tomography data of five biopsy‐proven HRPC patients were selected for this study. Two different planning target volumes (PTV₁ and PTV₂) were contoured for each patient. The PTV₁ included the prostate, seminal vesicles, and pelvic lymphatics, while the PTV₂ included only the prostate and seminal vesicles. The prescribed dose was 54 Gy for the PTV₁ with a sequential boost (24 Gy for the PTV₂). Intensity‐modulated RT (IMRT) and volumetric modulated arc therapy (VMAT) techniques were used to generate treatment plans with 6 and 10 MV photon energies with the flattening filter (FF) or flattening filter‐free (FFF) irradiation mode. The excess absolute risks (EARs) were calculated and compared for the bladder, rectum, pelvic bone, and soft tissue based on the linear‐exponential, plateau, full mechanistic, and specific mechanistic sarcoma dose‐response model. According to the models, all treatment plans resulted in similar risks of secondary bladder or rectal cancer and pelvic bone or soft tissue sarcoma except for the estimated risk of the bladder according to the full mechanistic model using IMRT_(6MV;FF) technique compared with VMAT techniques with FFF options. The overall estimation of EAR indicated that the radiation‐induced cancer risk due to RT in HRPC was lower for bladder than the rectum. EAR values ranged from 1.47 to 5.82 for bladder and 6.36 to 7.94 for rectum, depending on the dose–response models used. The absolute risks of the secondary pelvic bone and soft tissue sarcoma were small for the plans examined. We theoretically predicted the radiation‐induced secondary cancer risk in HRPC patients with pelvic irradiation. Nevertheless, prospective clinical trials, with larger patient cohorts with a long‐term follow‐up, are needed to validate these model predictions.

10-MV SBRT FFF IRRADIATION TECHNIQUE IS ASSOCIATED TO THE LOWEST PERIPHERAL DOSE: THE OUTCOME OF 142 TREATMENT PLANS FOR THE 10 MOST COMMON TUMOUR LOCATIONS

There is a growing interest in the combined use of Stereotactic Body Radiation Therapy (SBRT) with Flattening Filter Free (FFF) due to the high local control rates and reduced treatment times, compared to conventionally fractionated treatments. It has been suggested that they may also provide a better radiation protection to radiotherapy patients as a consequence of the expected decrease in peripheral doses. This work aims to determine this reduction in unattended out-of-field regions, where no CT information is available but an important percentage of second primary cancers occur. For that purpose, ten different cases suitable for SBRT were chosen. Thus, 142 different treatment plans including SBRT, as well as 3D-CRT, IMRT and VMAT (with standard fractionation) in low and high energies for Varian (FF and FFF), Siemens and Elekta machines were created. Then, photon and neutron peripheral dose in 14 organs were assessed and compared using two analytical models. For the prostate case, uncomplicated and cancer free control probability estimation was also carried out. As a general behavior, SBRT plans led to the lowest peripheral doses followed by 3D-CRT, VMAT and IMRT, in this order. Unflattened beams proved to be the most effective in reducing peripheral doses, especially for 10 MV. The obtained results suggest that FFF beams for SBRT with 10 MV represent the best compromise between dose delivery efficiency and peripheral dose reduction.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

Hypo-fractionated boost in locally advanced non-small cell lung cancer: temporal distribution of boost fractions

To propose new schemas for radiation boosting of primary tumors, in locally advanced non-small cell lung cancers (NSCLC), in conjunction with standard chemoradiotherapy. To investigate the effect of temporal distributions of the boost fractions on tumor control. NSCLC cases, previously treated with 60 Gy in 30 fractions, were retrospectively planned by adding a radiation boost (25 Gy in 5 fractions) to the primary tumor. Several integrated and sequential boosting schedules were considered. Biological doses were calculated for targets and organs at risk (OAR). Tumor control probabilities (TCP) were calculated using an empirical model and a stochastic model that accounts more systematically for tumor growth kinetics and cell kill. For heterogeneous patient populations, the TCPs for different boost schedules ranged from 82% to 84% and from 73% to 74% for integrated and sequential boosting respectively. For individual tumors with specific growth parameters, the TCP varied by up to 19% between the different schedules. The TCP for sequential boosting was expected to be up to 67% lower than front integrated boosting. The gap in TCP between schedules was higher for tumors with higher clonogenic cell numbers, lower radio-sensitivity, shorter doubling times and lower cell loss. The proposed boosting schemas are dosimetrically feasible and biologically effective. We suggest that the boosts are most effective when given during the first week of treatment and least effective when given sequentially after the end of treatment. The effect of boost scheduling and the effectiveness of front boosting are expected to be most significant for tumors with high clonogenic cell numbers, fast growing rates, low cell loss and low radio-sensitivity. Ultimately, animal studies and clinical trials, guided by biology modeling as presented in the present work, will be needed to verify the effectiveness of fine tuning temporal distributions of radiotherapy fractions.

Volume effects of radiotherapy on the risk of second primary cancers: A systematic review of clinical and epidemiological studies

As modern radiotherapy, including intensity-modulated techniques, is associated with high dose gradients to normal tissues and large low-to-moderate dose volumes, the assessment of second primary cancer (SPC) risks requires quantification of dose-volume effects. We conducted a systematic review of clinical and epidemiological studies investigating the effect of the irradiated volume or dose-volume distribution to the remaining volume at risk (RVR) on SPC incidence. We identified eighteen studies comparing SPC risks according to the irradiated volume (i.e., in most studies, the size or number of fields used), and four studies reporting risk estimates according to the dose distribution to the RVR (after whole-body dose reconstruction). An increased risk of SPCs (mainly breast and lung cancers) with extended radiotherapy was observed among patients treated for Hodgkin lymphoma or childhood cancers. However, normal tissue dose distribution was not estimated, limiting the interpretation of those results in terms of volume effects on organs at risk. Studies considering whole-body exposures quantified dose-response relationships for point dose estimates, without accounting for dose-volume distributions. Therefore, they disregarded possible tissue effects (e.g. bystander and abscopal effects, stem cell repopulation) which may play a role in the induction of SPCs. Currently, there is no clinical or epidemiological information about a possible role of high dose gradients in surrounding organs, or increasing volumes of distant tissues exposed to low doses, in the risk of SPCs. Opportunities for future research nevertheless now exist, since methods and tools for estimating individual whole-body dose-volume distributions in large patient populations have been developed.

Tailoring protocols for chest CT applications: when and how?

In the medical era of early detection of diseases and tailored therapies, an accurate characterization and staging of the disease is pivotal for treatment planning. The widespread use of computed tomography (CT)-often with the use of contrast material (CM)-probably represents the most important advance in diagnostic radiology. The result is a marked increase in radiation exposure of the population for medical purposes, with its intrinsic carcinogenic potential, and CM affecting kidney function. The radiologists should aim to minimize patient's risk by reducing radiation exposure and CM amount, while maintaining the highest image quality. To achieve this goal, it is necessary to perform "patient-centric imaging". The purpose of this review is to provide radiologists with "tips and tricks" to control radiation dose at CT, summarizing technical artifices in order to reduce image noise and increase image contrast. Also chest CT tailored protocols are supplied, with particular attention to three most common thoracic CT protocols: aortic/cardiac CT angiography (CTA), pulmonary CTA, and routine chest CT.

Intensity-modulated radiation therapy and volumetric modulated arc therapy versus conventional conformal techniques at high energy: Dose assessment and impact on second primary cancer in the out-of-field region

The aim of this work was to estimate peripheral neutron and photon doses associated with the conventional 3D conformal radiotherapy techniques in comparison to modern ones such as Intensity modulated radiation therapy and volumetric modulated arc therapy. Assessment in terms of second cancer incidence ought to peripheral doses was also considered. For that, a dosimetric methodology proposed by the authors has been applied beyond the region where there is no CT information and, thus, treatment planning systems do not calculate and where, nonetheless, about one third of second primary cancers occurs.

Predicting Organ-Specific Risk Interactions between Radiation and Chemotherapy in Secondary Cancer Survivors

Several studies have shown that pediatric patients have an increased risk of developing a secondary malignancy several decades after treatment with radiotherapy and chemotherapy. In this work, we use a biologically motivated mathematical formalism to estimate the relative risks of breast, lung and thyroid cancers in childhood cancer survivors due to concurrent therapy regimen. This model specifically includes possible organ-specific interaction between radiotherapy and chemotherapy. The model predicts relative risks for developing secondary cancers after chemotherapy in breast, lung and thyroid tissues, and compared with the epidemiological data. For a concurrent therapy protocol, our model predicted relative risks of 3.2, 9.3, 4.5 as compared to the clinical data, i.e., 1.4, 8.0, 2.3 for secondary breast, lung and thyroid cancer risks, respectively. The extracted chemotherapy mutation induction rates for breast, lung and thyroid are 10⁻⁹, 0.5 × 10⁻⁶, 0.9 × 10⁻⁷ respectively. We found that there exists no synergistic interaction between radiation and chemotherapy for neither mutation induction nor cell kill in lung tissue, but there is an interaction in cell kill for the breast and thyroid organs. These findings help understand the risks of current clinical protocols and might provide rational guidance to develop future multi-modality treatment protocols to minimize secondary cancer risks.

A review of dosimetric and toxicity modeling of proton versus photon craniospinal irradiation for pediatrics medulloblastoma

BACKGROUND

Craniospinal irradiation (CSI) is the standard radiation therapy treatment for medulloblastoma. Conventional CSI photon therapy (Photon-CSI) delivers significant dose to surrounding normal tissue (NT). Research into pediatric CSI with proton therapy (Proton-CSI) has increased, with the aim of exploiting the potential to reduce NT dose and associated post-treatment complications. This review aims to compare treatment outcomes of pediatric medulloblastoma patients between Proton- and Photon-CSI treatments.

MATERIAL AND METHODS

A search and review of studies published between 1990 and 2016 comparing pediatric (2-18 years) medulloblastoma Proton- and Photon-CSI in three aspects - normal organ sparing and target coverage; normal organ dysfunction and second malignancy risks - was completed.

RESULTS

Fifteen studies were selected for review and the results were directly compared. Proton-CSI reported improved out-of-field organ sparing while target coverage improvements were inconsistent. Normal organ dysfunction risks were predicted to be lower following Proton-CSI. Secondary malignancy risks (SMRs) were generally lower with Proton-CSI based on several different risk models.

CONCLUSIONS

Proton-CSI conferred better treatment outcomes than Photon-CSI for pediatric medulloblastoma patients. This review serves to compare the current literature in the absence of long-term data from prospective studies.

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

PURPOSE

Biological treatment plan evaluation does not currently consider second cancer induction from peripheral doses associated to photon radiotherapy. The aim is to propose a methodology to characterize the therapeutic window by means of an integral radiobiological approach, which considers not only Tumour Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) but also Secondary Cancer Probability (SCP).

METHODS

Uncomplicated and Cancer-Free Control Probability (UCFCP) function has been proposed assuming a statistically uncorrelated response for tumour and normal tissues. The Poisson's and Lyman's models were chosen for TCP and NTCP calculations, respectively. SCP was modelled as the summation of risks associated to photon and neutron irradiation of radiosensitive organs. For the medium (>4Gy) and low dose regions, mechanistic and linear secondary cancer risks models were used, respectively. Two conformal and intensity-modulated prostate plans at 15MV (same prescription dose) were selected to illustrate the UCFCP features.

RESULTS

UCFCP exhibits a bell-shaped behaviour with its maximum inside the therapeutic window. SCP values were not different for the plans analysed (∼2.4%) and agreed with published epidemiological results. Therefore, main differences in UCFCP came from differences in rectal NTCP (18% vs 9% for 3D-CRT and IMRT, respectively). According to UCFCP values, the evaluated IMRT plan ranked first.

CONCLUSIONS

The level of SCP was found to be similar to that of NTCP complications which reinforces the importance of considering second cancer risks as part of the possible late sequelae due to treatment. Previous concerns about the effect of peripheral radiation, especially neutrons, in the induction of secondary cancers can be evaluated by quantifying the UCFCP.

Characteristic patterns of cancer incidence: Epidemiological data, biological theories, and multistage models

We investigate and classify several patterns in cancer incidence and relative risk data which persist across different countries and multiple published studies. We then explore biological hypotheses as well as many mathematical models in the literature that attempt to explain these patterns. A general modeling framework is presented which is general enough to model most of observed behaviors. It is our belief that this model has sufficient flexibility to be adapted to new information as it is discovered. As one application of this framework, we give a model for the effect of aging on the process of carcinogenesis.

Risk estimation of second primary cancers after breast radiotherapy

AIMS

There is evidence towards the induction of second primary cancers (SPCs) after breast radiotherapy (RT). Organs, such as the lungs and the esophagus, have been identified as common sites for SPC formation. As a result, the current study investigated the risk of secondary carcinogenesis associated with particular RT techniques for breast cancer; including whole breast, segmented breast, partial breast and mammosite brachytherapy.

METHODS

In this study, seven breast cancer patients had all major organs contoured on their planning computed tomography (CT) images. Whole breast, segmented breast, accelerated partial breast irradiation (APBI) and mammosite boost treatment plans were generated for each patient using Pinnacle3 treatment planning system. Differential dose-volume histograms were generated for a number of critical structures: bladder, brain and central nervous system (CNS), breast, colon, liver, lung, mouth and pharynx, esophagus, ovary, salivary gland, small intestine, stomach, and uterus. The lifetime attributed risk (LAR) of cancer induction was estimated using the Schneider et al. excess absolute risk models and dose-volume histograms for the above organs.

RESULTS

The sites with the highest LAR estimates were the ipsilateral and contralateral lungs, and contralateral breast for all treatment techniques. For all sites, the LAR estimates for the segmented breast and mammosite treatments were lower than those for the whole breast and APBI treatments. For right-sided target volumes the liver also resulted in high LAR estimates, with all techniques having a LAR greater than 20 per 10 000 person-years (PY), except for mammosite with a mean LAR estimate of 13.2 per 10 000 PY. For left-sided target volumes the stomach also resulted in high LAR estimates, with both whole breast and APBI having a LAR greater than 20 per 10 000 PY, and mammosite the lowest with a LAR of 8.3 per 10 000 PY.

CONCLUSION

It is concluded that the lungs and contralateral breast showed high LAR estimates.

Comparative Risk Predictions of Second Cancers After Carbon-Ion Therapy Versus Proton Therapy

PURPOSE

This work proposes a theoretical framework that enables comparative risk predictions for second cancer incidence after particle beam therapy for different ion species for individual patients, accounting for differences in relative biological effectiveness (RBE) for the competing processes of tumor initiation and cell inactivation. Our working hypothesis was that use of carbon-ion therapy instead of proton therapy would show a difference in the predicted risk of second cancer incidence in the breast for a sample of Hodgkin lymphoma (HL) patients.

METHODS AND MATERIALS

We generated biologic treatment plans and calculated relative predicted risks of second cancer in the breast by using two proposed methods: a full model derived from the linear quadratic model and a simpler linear-no-threshold model.

RESULTS

For our reference calculation, we found the predicted risk of breast cancer incidence for carbon-ion plans-to-proton plan ratio, <Rc/Rp>, to be 0.75 ± 0.07 but not significantly smaller than 1 (P=.180).

CONCLUSIONS

Our findings suggest that second cancer risks are, on average, comparable between proton therapy and carbon-ion therapy.

Open-Source Radiation Exposure Extraction Engine (RE3) with Patient-Specific Outlier Detection

We present an open-source, picture archiving and communication system (PACS)-integrated radiation exposure extraction engine (RE3) that provides study-, series-, and slice-specific data for automated monitoring of computed tomography (CT) radiation exposure. RE3 was built using open-source components and seamlessly integrates with the PACS. RE3 calculations of dose length product (DLP) from the Digital imaging and communications in medicine (DICOM) headers showed high agreement (R (2) = 0.99) with the vendor dose pages. For study-specific outlier detection, RE3 constructs robust, automatically updating multivariable regression models to predict DLP in the context of patient gender and age, scan length, water-equivalent diameter (D w), and scanned body volume (SBV). As proof of concept, the model was trained on 811 CT chest, abdomen + pelvis (CAP) exams and 29 outliers were detected. The continuous variables used in the outlier detection model were scan length (R (2)  = 0.45), D w (R (2) = 0.70), SBV (R (2) = 0.80), and age (R (2) = 0.01). The categorical variables were gender (male average 1182.7 ± 26.3 and female 1047.1 ± 26.9 mGy cm) and pediatric status (pediatric average 710.7 ± 73.6 mGy cm and adult 1134.5 ± 19.3 mGy cm).

Concepts and challenges in cancer risk prediction for the space radiation environment

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

Risk-optimized proton therapy to minimize radiogenic second cancers

Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimizes the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment planning utilized a combination of a commercial treatment planning system and an in-house risk-optimization algorithm. When normal-tissue dose constraints were incorporated in treatment planning, the risk model that incorporated the effects of fractionation, initiation, inactivation, repopulation and promotion selected a combination of anterior and lateral beams, which lowered the relative risk by 21% for the bladder and 30% for the rectum compared to the lateral-opposed beam arrangement. Other results were found for other risk models.

Visualization of risk of radiogenic second cancer in the organs and tissues of the human body

BACKGROUND

Radiogenic second cancer is a common late effect in long term cancer survivors. Currently there are few methods or tools available to visually evaluate the spatial distribution of risks of radiogenic late effects in the human body. We developed a risk visualization method and demonstrated it for radiogenic second cancers in tissues and organs of one patient treated with photon volumetric modulated arc therapy and one patient treated with proton craniospinal irradiation.

METHODS

Treatment plans were generated using radiotherapy treatment planning systems (TPS) and dose information was obtained from TPS. Linear non-threshold risk coefficients for organs at risk of second cancer incidence were taken from the Biological Effects of Ionization Radiation VII report. Alternative risk models including linear exponential model and linear plateau model were also examined. The predicted absolute lifetime risk distributions were visualized together with images of the patient anatomy.

RESULTS

The risk distributions of second cancer for the two patients were visually presented. The risk distributions varied with tissue, dose, dose-risk model used, and the risk distribution could be similar to or very different from the dose distribution.

CONCLUSIONS

Our method provides a convenient way to directly visualize and evaluate the risks of radiogenic second cancer in organs and tissues of the human body. In the future, visual assessment of risk distribution could be an influential determinant for treatment plan scoring.

Modeling age-dependent radiation-induced second cancer risks and estimation of mutation rate: an evolutionary approach

Although the survival rate of cancer patients has significantly increased due to advances in anti-cancer therapeutics, one of the major side effects of these therapies, particularly radiotherapy, is the potential manifestation of radiation-induced secondary malignancies. In this work, a novel evolutionary stochastic model is introduced that couples short-term formalism (during radiotherapy) and long-term formalism (post-treatment). This framework is used to estimate the risks of second cancer as a function of spontaneous background and radiation-induced mutation rates of normal and pre-malignant cells. By fitting the model to available clinical data for spontaneous background risk together with data of Hodgkin's lymphoma survivors (for various organs), the second cancer mutation rate is estimated. The model predicts a significant increase in mutation rate for some cancer types, which may be a sign of genomic instability. Finally, it is shown that the model results are in agreement with the measured results for excess relative risk (ERR) as a function of exposure age and that the model predicts a negative correlation of ERR with increase in attained age. This novel approach can be used to analyze several radiotherapy protocols in current clinical practice and to forecast the second cancer risks over time for individual patients.

Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

PURPOSE

Theoretical dose-response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients.

METHODS

A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities.

RESULTS

Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry.

CONCLUSIONS

The uncertainty in the dose-response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio of absolute risks between two modalities is less sensitive to the uncertainties in the risk model and can provide statistically significant estimates.

Minimizing second cancer risk following radiotherapy: current perspectives

Secondary cancer risk following radiotherapy is an increasingly important topic in clinical oncology with impact on treatment decision making and on patient management. Much of the evidence that underlies our understanding of secondary cancer risks and our risk estimates are derived from large epidemiologic studies and predictive models of earlier decades with large uncertainties. The modern era is characterized by more conformal radiotherapy technologies, molecular and genetic marker approaches, genome-wide studies and risk stratifications, and sophisticated biologically based predictive models of the carcinogenesis process. Four key areas that have strong evidence toward affecting secondary cancer risks are 1) the patient age at time of radiation treatment, 2) genetic risk factors, 3) the organ and tissue site receiving radiation, and 4) the dose and volume of tissue being irradiated by a particular radiation technology. This review attempts to summarize our current understanding on the impact on secondary cancer risks for each of these known risk factors. We review the recent advances in genetic studies and carcinogenesis models that are providing insight into the biologic processes that occur from tissue irradiation to the development of a secondary malignancy. Finally, we discuss current approaches toward minimizing the risk of radiation-associated secondary malignancies, an important goal of clinical radiation oncology.

Etiology and treatment of hematological neoplasms: stochastic mathematical models

Leukemias are driven by stemlike cancer cells (SLCC), whose initiation, growth, response to treatment, and posttreatment behavior are often "stochastic", i.e., differ substantially even among very similar patients for reasons not observable with present techniques. We review the probabilistic mathematical methods used to analyze stochastics and give two specific examples. The first example concerns a treatment protocol, e.g., for acute myeloid leukemia (AML), where intermittent cytotoxic drug dosing (e.g., once each weekday) is used with intent to cure. We argue mathematically that, if independent SLCC are growing stochastically during prolonged treatment, then, other things being equal, front-loading doses are more effective for tumor eradication than back loading. We also argue that the interacting SLCC dynamics during treatment is often best modeled by considering SLCC in microenvironmental niches, with SLCC-SLCC interactions occurring only among SLCC within the same niche, and we present a stochastic dynamics formalism, involving "Poissonization," applicable in such situations. Interactions at a distance due to partial control of total cell numbers are also considered. The second half of this chapter concerns chromosomal aberrations, lesions known to cause some leukemias. A specific example is the induction of a Philadelphia chromosome by ionizing radiation, subsequent development of chronic myeloid leukemia (CML), CML treatment, and treatment outcome. This time evolution involves a coordinated sequence of > 10 steps, each stochastic in its own way, at the subatomic, molecular, macromolecular, cellular, tissue, and population scales, with corresponding time scales ranging from picoseconds to decades. We discuss models of these steps and progress in integrating models across scales.

A comparative study on the risks of radiogenic second cancers and cardiac mortality in a set of pediatric medulloblastoma patients treated with photon or proton craniospinal irradiation

PURPOSE

To compare the risks of radiogenic second cancers and cardiac mortality in 17 pediatric medulloblastoma patients treated with passively scattered proton or field-in-field photon craniospinal irradiation (CSI).

MATERIAL/METHODS

Standard of care photon or proton CSI treatment plans were created for all 17 patients in a commercial treatment planning system (TPS) (Eclipse version 8.9; Varian Medical Systems, Palo Alto, CA) and prescription dose was 23.4 or 23.4 Gy (RBE) to the age specific target volume at 1.8 Gy/fraction. The therapeutic doses from proton and photon CSI plans were estimated from TPS. Stray radiation doses were determined from Monte Carlo simulations for proton CSI and from measurements and TPS for photon CSI. The Biological Effects of Ionization Radiation VII report and a linear model based on childhood cancer survivor data were used for risk predictions of second cancer and cardiac mortality, respectively.

RESULTS

The ratios of lifetime attributable risk (RLARs) (proton/photon) ranged from 0.10 to 0.22 for second cancer incidence and ranged from 0.20 to 0.53 for second cancer mortality, respectively. The ratio of relative risk (RRR) (proton/photon) of cardiac mortality ranged from 0.12 to 0.24. The RLARs of both cancer incidence and mortality decreased with patient's age at exposure (e), while the RRRs of cardiac mortality increased with e. Girls had a significantly higher RLAR of cancer mortality than boys.

CONCLUSION

Passively scattered proton CSI provides superior predicted outcomes by conferring lower predicted risks of second cancer and cardiac mortality than field-in-field photon CSI for all medulloblastoma patients in a large clinically representative sample in the United States, but the magnitude of superiority depends strongly on the patients' anatomical development status.

Repopulation of interacting tumor cells during fractionated radiotherapy: stochastic modeling of the tumor control probability

PURPOSE

Optimal treatment planning for fractionated external beam radiation therapy requires inputs from radiobiology based on recent thinking about the "five Rs" (repopulation, radiosensitivity, reoxygenation, redistribution, and repair). The need is especially acute for the newer, often individualized, protocols made feasible by progress in image guided radiation therapy and dose conformity. Current stochastic tumor control probability (TCP) models incorporating tumor repopulation effects consider "stem-like cancer cells" (SLCC) to be independent, but the authors here propose that SLCC-SLCC interactions may be significant. The authors present a new stochastic TCP model for repopulating SLCC interacting within microenvironmental niches. Our approach is meant mainly for comparing similar protocols. It aims at practical generalizations of previous mathematical models.

METHODS

The authors consider protocols with complete sublethal damage repair between fractions. The authors use customized open-source software and recent mathematical approaches from stochastic process theory for calculating the time-dependent SLCC number and thereby estimating SLCC eradication probabilities. As specific numerical examples, the authors consider predicted TCP results for a 2 Gy per fraction, 60 Gy protocol compared to 64 Gy protocols involving early or late boosts in a limited volume to some fractions.

RESULTS

In sample calculations with linear quadratic parameters α = 0.3 per Gy, α∕β = 10 Gy, boosting is predicted to raise TCP from a dismal 14.5% observed in some older protocols for advanced NSCLC to above 70%. This prediction is robust as regards: (a) the assumed values of parameters other than α and (b) the choice of models for intraniche SLCC-SLCC interactions. However, α = 0.03 per Gy leads to a prediction of almost no improvement when boosting.

CONCLUSIONS

The predicted efficacy of moderate boosts depends sensitively on α. Presumably, the larger values of α are the ones appropriate for individualized treatment protocols, with the smaller values relevant only to protocols for a heterogeneous patient population. On that assumption, boosting is predicted to be highly effective. Front boosting, apart from practical advantages and a possible advantage as regards iatrogenic second cancers, also probably gives a slightly higher TCP than back boosting. If the total number of SLCC at the start of treatment can be measured even roughly, it will provide a highly sensitive way of discriminating between various models and parameter choices. Updated mathematical methods for calculating repopulation allow credible generalizations of earlier results.

Second primary cancers after radiation for prostate cancer: a review of data from planning studies

A review of planning studies was undertaken to evaluate estimated risks of radiation induced second primary cancers (RISPC) associated with different prostate radiotherapy techniques for localised prostate cancer. A total of 83 publications were identified which employed a variety of methods to estimate RISPC risk. Of these, the 16 planning studies which specifically addressed absolute or relative second cancer risk using dose-response models were selected for inclusion within this review. There are uncertainties and limitations related to all the different methods for estimating RISPC risk. Whether or not dose models include the effects of the primary radiation beam, as well as out-of-field regions, influences estimated risks. Regarding the impact of IMRT compared to 3D-CRT, at equivalent energies, several studies suggest an increase in risk related to increased leakage contributing to out-of-field RISPC risk, although in absolute terms this increase in risk may be very small. IMRT also results in increased low dose normal tissue irradiation, but the extent to which this has been estimated to contribute to RISPC risk is variable, and may also be very small. IMRT is often delivered using 6MV photons while conventional radiotherapy often requires higher energies to achieve adequate tissue penetration, and so comparisons between IMRT and older techniques should not be restricted to equivalent energies. Proton and brachytherapy planning studies suggest very low RISPC risks associated with these techniques. Until there is sufficient clinical evidence regarding RISPC risks associated with modern irradiation techniques, the data produced from planning studies is relevant when considering which patients to irradiate, and which technique to employ.

Hodgkin's lymphoma emerging radiation treatment techniques: trade-offs between late radio-induced toxicities and secondary malignant neoplasms

BACKGROUND

Purpose of this study is to explore the trade-offs between radio-induced toxicities and second malignant neoplasm (SMN) induction risk of different emerging radiotherapy techniques for Hodgkin's lymphoma (HL) through a comprehensive dosimetric analysis on a representative clinical model.

METHODS

Three different planning target volume (PTVi) scenarios of a female patient with supradiaphragmatic HL were used as models for the purpose of this study. Five treatment radiation techniques were simulated: an anterior-posterior parallel-opposed (AP-PA), a forward intensity modulated (FIMRT), an inverse intensity modulated (IMRT), a Tomotherapy (TOMO), a proton (PRO) technique. A radiation dose of 30 Gy or CGE was prescribed. Dose-volume histograms of PTVs and organs-at-risk (OARs) were calculated and related to available dose-volume constraints. SMN risk for breasts, thyroid, and lungs was estimated through the Organ Equivalent Dose model considering cell repopulation and inhomogeneous organ doses.

RESULTS

With similar level of PTVi coverage, IMRT, TOMO and PRO plans generally reduced the OARs' dose and accordingly the related radio-induced toxicities. However, only TOMO and PRO plans were compliant with all constraints in all scenarios. For the IMRT and TOMO plans an increased risk of development of breast, and lung SMN compared with AP-PA and FIMRT techniques was estimated. Only PRO plans seemed to reduce the risk of predicted SMN compared with AP-PA technique.

CONCLUSIONS

Our model-based study supports the use of advanced RT techniques to successfully spare OARs and to reduce the risk of radio-induced toxicities in HL patients. However, the estimated increase of SMNs' risk inherent to TOMO and IMRT techniques should be carefully considered in the evaluation of a risk-adapted therapeutic strategy.

Age and space irradiation modulate tumor progression: implications for carcinogenesis risk

Age plays a major role in tumor incidence and is an important consideration when modeling the carcinogenesis process or estimating cancer risks. Epidemiological data show that from adolescence through middle age, cancer incidence increases with age. This effect is commonly attributed to a lifetime accumulation of cellular, particularly DNA, damage. However, during middle age the incidence begins to decelerate and, for many tumor sites, it actually decreases at sufficiently advanced ages. We investigated if the observed deceleration and potential decrease in incidence could be attributed to a decreased capacity of older hosts to support tumor progression, and whether HZE [high atomic number (Z), high energy (E)] radiation differentially modulates tumor progression in young vs. middle-age hosts, issues that are relevant to estimating carcinogenesis risk for astronauts. Lewis lung carcinoma (LLC) cells were injected into syngeneic mice (143 and 551 days old), which were then subject to whole-body (56)Fe irradiation (1 GeV/amu). Three findings emerged: (1) among unirradiated animals, substantial inhibition of tumor progression and significantly decreased tumor growth rates were seen for middle-aged mice compared to young mice, (2) whole-body (56)Fe irradiation inhibited tumor progression in both young and middle-aged mice (with greater suppression seen in case of young animals), with little effect on tumor growth rates, and (3) (56)Fe irradiation suppressed tumor progression in young mice to a degree that was not significantly different than transiting from young to middle-aged. Thus, (56)Fe irradiation acted similar to aging with respect to tumor progression. We further investigated the molecular underpinnings driving the radiation modulation of tumor dynamics in young and middle-aged mice. Through global gene expression analysis, the key players, FASN, AKT1 and the CXCL12/CXCR4 complex, were determined to be contributory. In sum, these findings demonstrated a reduced capacity of middle-aged hosts to support the progression phase of carcinogenesis and identify molecular factors that contribute to HZE radiation modulation of tumor progression as a function of age.

Model of accelerated carcinogenesis based on proliferative stress and inflammation for doses relevant to radiotherapy

Recent findings demonstrate that accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks in cells, which escaped apoptosis due to proliferative stress. In this work, proliferative stress and inflammation-based carcinogenesis at large dose were included in a cancer induction model considering fractionation. At large dose, tissue injury due to irradiation could be so severe that under the regenerative proliferative stress induced by cell loss, the genomic unstable cells generated during irradiation and/or inflammation escape senescence or apoptosis and reenter the cell cycle, triggering enhanced carcinogenesis. This acceleration-modeled to be proportional to the number of repopulated cells-is only significant, however, when tissue injury is severe and thus proportional to the cell loss in the tissue. The general solutions to the resulting differential equations for carcinoma induction were computed. In case of full repopulation or acute low-dose irradiation, the acceleration term disappears from the equation describing cancer induction. The acceleration term is affecting the dose-response curve for carcinogenesis only at large doses. An example for bladder cancer is shown. An existing model for cancer induction after fractionated radiotherapy which is based on cell mutations was extended here by including the effects of inflammation and proliferative stress, and an additional model parameter was established which describes acceleration. The new acceleration parameter affects the dose-response model only at large dose and is only effective when the tissue is not capable of fully repopulating between dose fractions.