Biological mechanisms of normal tissue damage: importance for the design of NTCP models

Parameters of the Lyman Model for Calculation of Normal-Tissue Complication Probability: A Systematic Literature Review

PURPOSE

The Lyman model is one of the most used radiobiological models for calculation of normal-tissue complication probability (NTCP). Since its introduction in 1985, many authors have published parameter values for the model based on clinical data of different radiotherapeutic situations. This study attempted to collect the entirety of radiobiological parameter sets published to date and provide an overview of the data basis for different variations of the model. Furthermore, it sought to compare the parameter values and calculated NTCPs for selected endpoints with sufficient data available.

METHODS AND MATERIALS

A systematic literature analysis was performed, searching for publications that provided parameters for the different variations of the Lyman model in the Medline database using PubMed. Parameter sets were grouped into 13 toxicity-related endpoint groups. For 3 selected endpoint groups (≤25% reduction of saliva 12 months after irradiation of the parotid, symptomatic pneumonitis after irradiation of the lung, and bleeding of grade 2 or less after irradiation of the rectum), parameter values were compared and differences in calculated NTCP values were analyzed.

RESULTS

A total of 509 parameter sets from 130 publications were identified. Considerable heterogeneities were detected regarding the number of parameters available for different radio-oncological situations. Furthermore, for the 3 selected endpoints, large differences in published parameter values were found. These translated into great variations of calculated NTCPs, with maximum ranges of 35.2% to 93.4% for the saliva endpoint, of 39.4% to 90.4% for the pneumonitis endpoint, and of 5.4% to 99.3% for the rectal bleeding endpoint.

CONCLUSIONS

The detected heterogeneity of the data as well as the large variations of published radiobiological parameters underline the necessity for careful interpretation when using such parameters for NTCP calculations. Appropriate selection of parameters and validation of values are essential when using the Lyman model.

Predictive modelling for late rectal and urinary toxicities after prostate radiotherapy using planned and delivered dose

Background and purpose

Normal tissue complication probability (NTCP) parameters derived from traditional 3D plans may not be ideal in defining toxicity outcomes for modern radiotherapy techniques. This study aimed to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively scored clinical data for late gastrointestinal (GI) and genitourinary (GU) toxicities for high-risk prostate cancer patients treated using volumetric-modulated-arc-therapy (VMAT). Dose-volume-histograms (DVH) extracted from planned (D_P) and accumulated dose (D_A) were used.

Material and methods

D_P and D_A obtained from the DVH of 150 prostate cancer patients with pelvic-lymph-nodes irradiation treated using VMAT were used to generate LKB-NTCP parameters using maximum likelihood estimations. Defined GI and GU toxicities were recorded up to 3-years post RT follow-up. Model performance was measured using Hosmer-Lemeshow goodness of fit test and the mean area under the receiver operating characteristics curve (AUC). Bootstrapping method was used for internal validation.

Results

For mild-severe (Grade ≥1) GI toxicity, the model generated similar parameters based on D_A and D_P DVH data (D_A-D₅₀:71.6 Gy vs D_P-D₅₀:73.4; D_A-m:0.17 vs D_P-m:0.19 and D_A/P-n 0.04). The 95% CI for D_A-D₅₀ was narrower and achieved an AUC of >0.6. For moderate-severe (Grade ≥2) GI toxicity, D_A-D₅₀ parameter was higher and had a narrower 95% CI (D_A-D₅₀:77.9 Gy, 95% CI:76.4-79.6 Gy vs D_P-D₅₀:74.6, 95% CI:69.1-85.4 Gy) with good model performance (AUC>0.7). For Grade ≥1 late GU toxicity, D₅₀ and n parameters for D_A and D_P were similar (D_A-D₅₀: 58.8 Gy vs D_P-D₅₀: 59.5 Gy; D_A-n: 0.21 vs D_P-n: 0.19) with a low AUC of<0.6. For Grade ≥2 late GU toxicity, similar NTCP parameters were attained from D_A and D_P DVH data (D_A-D₅₀:81.7 Gy vs D_P-D₅₀:81.9 Gy; D_A-n:0.12 vs D_P-n:0.14) with an acceptable AUCs of >0.6.

Conclusions

The achieved NTCP parameters using modern RT techniques and accounting for organ motion differs from QUANTEC reported parameters. D_A-D₅₀ of 77.9 Gy for GI and D_A/D_P-D₅₀ of 81.7-81.9 Gy for GU demonstrated good predictability in determining the risk of Grade ≥2 toxicities especially for GI derived D₅₀ and are recommended to incorporate as part of the DV planning constraints to guide dose escalation strategies while minimising the risk of toxicity.

Involvement of tissue changes induced by neoadjuvant treatment in total mesorectal excision (TME): novel suggestions for determining TME quality

BACKGROUND

Few studies to date have investigated morphological changes after neoadjuvant treatment (NAT) and their implications in total mesorectal excision (TME). This study was primarily designed to evaluate whether tissue changes associated with NAT affected the quality of TME and additionally to suggest a more objective method evaluating TME quality.

METHODS

This study enrolled 1322 consecutive patients who underwent curative robot-assisted surgery for rectal cancer. Patients who did and did not receive NAT were subjected to propensity-score matching, yielding 402 patients in each group.

RESULTS

NAT independently reduced complete achievement of TME [odds ratio (OR) = 2.056, p = 0.017]. Intraoperative evaluation identified seven tissue changes significantly associated with NAT, including tumor perforation, mucin pool, necrosis, fibrosis, fat degeneration, and rectal or perirectal edema NAT (p < 0.001-0.05). Tumor perforation (OR = 5.299, p = 0.001) and mucin pool (OR = 14.053, p = 0.002) were independently associated with inappropriate (near-complete + incomplete) TME. Complete TME resulted in significantly reduced local recurrence (4.3% vs 15.3%, p = 0.003) and increased 5-year DFS rate (80.6% vs 67.6%, p = 0.047) compared with inappropriate one. By contrast, two tiers of complete and near-complete TMEs vs incomplete TME did not. Notably, among patients with complete TME, those who received NAT had a lower 5-year DFS than those who did not (77.8% vs 83.3%, p = 0.048).

CONCLUSIONS

NAT-associated tissue changes, somewhat interrupting complete TME, may provide unsolved clue to the relative inability of NAT to improve overall survival. The conventional three-tier grading of TME seems to be simplified into two tiers as complete and inappropriate.

A clinical trial to compare a 3D-printed bolus with a conventional bolus with the aim of reducing cardiopulmonary exposure in postmastectomy patients with volumetric modulated arc therapy

BACKGROUND

We compared the dosimetry, application, and acute toxicity of a 3D-printed and a conventional bolus for postmastectomy radiotherapy (PMRT) with volumetric modulated arc therapy (VMAT). Materials and Methods Eligible patients (n = 75) with PMRT breast cancer were randomly selected to receive VMAT with a conventional bolus or a 3D-printed bolus. The primary endpoint was a 10% decrease in the mean heart dose to left-sided breast cancer patients. The secondary endpoint was a 5% decrease in the mean ipsilateral lung dose to all patients. A comparative analysis was carried out of the dosimetry, normal tissue complication probability (NTCP), acute skin toxicity, and radiation pneumonitis.

RESULTS

Compared to a conventional bolus, the mean heart dose in left-sided breast cancer was reduced by an average of 0.8 Gy (5.5 ± 1.3 Gy vs. 4.7 ± 0.8 Gy, p = 0.035) and the mean dose to the ipsilateral lung was also reduced by an average of 0.8 Gy (12.4 ± 1.0 Gy vs. 11.6 ± 0.8 Gy, p < 0.001). The values for V_50Gy of the PTV of the chest wall for the 3D-printed and conventional boluses were 95.4 ± 0.6% and 94.8 ± 0.8% (p = 0.026) and the values for the CI of the entire PTV were 0.83 ± 0.02 and 0.80 ± 0.03 (p < 0.001), respectively. The NTCP for the 3D-printed bolus was also reduced to an average of 0.14% (0.32 ± 0.19% vs. 0.18 ± 0.11%, p = 0.017) for the heart and 0.45% (3.70 ± 0.67% vs. 3.25 ± 0.18%, p < 0.001) for the ipsilateral lung. Grade 2 and Grade 1 radiation pneumonitis were 0.0% versus 7.5% and 14.3% versus 20.0%, respectively (p = 0.184).

CONCLUSIONS

The 3D-printed bolus may reduce cardiopulmonary exposure in postmastectomy patients with volumetric modulated arc therapy.

Models for Translational Proton Radiobiology-From Bench to Bedside and Back

The number of proton therapy centers worldwide are increasing steadily, with more than two million cancer patients treated so far. Despite this development, pending questions on proton radiobiology still call for basic and translational preclinical research. Open issues are the on-going discussion on an energy-dependent varying proton RBE (relative biological effectiveness), a better characterization of normal tissue side effects and combination treatments with drugs originally developed for photon therapy. At the same time, novel possibilities arise, such as radioimmunotherapy, and new proton therapy schemata, such as FLASH irradiation and proton mini-beams. The study of those aspects demands for radiobiological models at different stages along the translational chain, allowing the investigation of mechanisms from the molecular level to whole organisms. Focusing on the challenges and specifics of proton research, this review summarizes the different available models, ranging from in vitro systems to animal studies of increasing complexity as well as complementing in silico approaches.

Radiation-Induced Dyspnea in Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy

Simple Summary

Dyspnea is a common symptomatic side-effect of thoracic radiation therapy. The aim of this study is to build a predictive model of any-grade radiation-induced dyspnea within six months after stereotactic body radiation therapy in patients treated for non-small cell lung cancer. The occurrence of pre-treatment chronic obstructive pulmonary disease and higher relative lungs volume receiving more than 15 Gy as well as heart volume were shown to be risk factors for dyspnea. The obtained results encourage further studies on the topic, which could validate the present organ-based findings and explore the voxel-based landscape of radiation dose sensitivity in the development of dyspnea.

Abstract

In this study, we investigated the prognostic factors for radiation-induced dyspnea after hypo-fractionated radiation therapy (RT) in 106 patients treated with Stereotactic Body RT for Non-Small-Cell Lung Cancer (NSCLC). The median prescription dose was 50 Gy (range: 40–54 Gy), delivered in a median of four fractions (range: 3–12). Dyspnea within six months after SBRT was scored according to CTCAE v.4.0. Biologically Effective Dose (α/β = 3 Gy) volume histograms for lungs and heart were extracted. Dosimetric parameters along with patient-specific and treatment-related factors were analyzed, multivariable logistic regression method with Leave-One-Out (LOO) internal validation applied. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and calibration plot parameters. Fifty-seven patients (53.8%) out of 106 developed dyspnea of any grade after SBRT (25/57 grade ≥ 2 cases). A three-variable predictive model including patient comorbidity (COPD), heart volume and the relative lungs volume receiving more than 15 Gy was selected. The model displays an encouraging performance given by a training ROC-AUC = 0.71 [95%CI 0.61–0.80] and a LOO-ROC-AUC = 0.64 [95%CI 0.53–0.74]. Further modeling efforts are needed for dyspnea prediction in hypo-fractionated treatments in order to identify patients at high risk for developing lung toxicity more accurately.

Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations

For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose distribution, and potentially its correlation with anatomy, can provide more robust associations with toxicity and seed more general NTCP models. Such approaches are culminating in the application of computationally intensive processes such as machine learning and the application of neural networks. The opportunities these approaches have for individualising treatment, predicting toxicity and expanding the solution space for radiation therapy are substantial and have clearly widespread and disruptive potential. Impediments to reaching that potential include issues associated with data collection, model generalisation and validation. This review examines the role of spatial models of complication and summarises relevant published studies. Sources of data for these studies, appropriate statistical methodology frameworks for processing spatial dose information and extracting relevant features are described. Spatial complication modelling is consolidated as a pathway to guiding future developments towards effective, complication-free radiotherapy treatment.

Association of Breast Cancer Irradiation With Cardiac Toxic Effects: A Narrative Review

IMPORTANCE

To promptly recognize and manage cardiovascular (CV) risk factors before, during, and after cancer treatment, decreasing the risk of cancer therapy-related cardiac dysfunction is crucial. After recent advances in breast cancer treatment, mortality rates from cancer have decreased, and the prevalence of survivors with a potentially higher CV disease risk has increased. Cardiovascular risks might be associated with the multimodal approach, including systemic therapies and breast radiotherapy (RT).

OBSERVATIONS

The heart disease risk seems to be higher in patients with tumors in the left breast, when other classic CV risk factors are present, and when adjunctive anthracycline-based chemotherapy is administered, suggesting a synergistic association. Respiratory control as well as modern RT techniques and their possible further refinement may decrease the prevalence and severity of radiation-induced heart disease. Several pharmacological cardioprevention strategies for decreasing cardiac toxic effects have been identified in several guidelines. However, further research is needed to ascertain the feasibility of these strategies in routine practice.

CONCLUSIONS AND RELEVANCE

This review found that evidence-based recommendations are lacking on the modalities for and intensity of heart disease screening, surveillance of patients after RT, and treatment of these patients. A multidisciplinary and multimodal approach is crucial to guide optimal management.

Genomics models in radiotherapy: From mechanistic to machine learning

Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.

Voxel-based analysis in radiation oncology: A methodological cookbook

Recently, 2D or 3D methods for dose distribution analysis have been proposed as evolutions of the Dose Volume Histogram (DVH) approaches. Those methods, collectively referred to as pixel- or voxel-based (VB) methods, evaluate local dose response patterns and go beyond the organ-based philosophy of Normal Tissue Complication Probability (NTCP) modelling. VB methods have been introduced in the context of radiation oncology in the very last years following the virtuous example of neuroimaging experience. In radiation oncology setting, dose mapping is a suitable scheme to compare spatial patterns of local dose distributions between patients who develop toxicity and who do not. In this critical review, we present the methods that include spatial dose distribution information for evaluating different toxicity endpoints after radiation therapy. The review addresses two main topics. First, the critical aspects in dose map building, namely the spatial normalization of the dose distributions from different patients. Then, the issues related to the actual dose map comparison, i.e. the viable options for a robust VB statistical analysis and the potential pitfalls related to the adopted solutions. To elucidate the different theoretical and technical issues, the covered topics are illustrated in relation to practical applications found in the existing literature. We conclude the overview on the VB philosophy in radiation oncology by introducing new phenomenological approaches to NTCP modelling that accounts for inhomogeneous organ radiosensitivity.

Radiation-Induced Hypothyroidism After Radical Intensity Modulated Radiation Therapy for Oropharyngeal Carcinoma

PURPOSE

To evaluate 2 published normal tissue complication probability models for radiation-induced hypothyroidism (RHT) on a large cohort of oropharyngeal carcinoma (OPC) patients who were treated with intensity-modulated radiation therapy (IMRT).

METHODS AND MATERIALS

OPC patients treated with retrievable IMRT Digital Imaging and Communications in Medicine (DICOMs) data and available baseline and follow-up thyroid function tests were included. Mean dose (Dmean) to the thyroid gland (TG) and its volume were calculated. The study outcome was clinical HT at least 6 months after radiation therapy, which was defined as grade ≥2 HT per Common Terminology Criteria for Adverse Events grading system (symptomatic hypothyroidism that required thyroid replacement therapy). Regression analyses and Wilcoxon rank-sum test were used. Receiver operating characteristic curves and area under the curve for the fitted model were calculated.

RESULTS

In the study, 360 OPC patients were included. The median age was 58 years. Most tumors (51%) originated from the base of tongue. IMRT-split field was used in 95%, and median radiation therapy dose was 69.96 Gy. In the study, 233 patients (65%) developed clinical RHT that required thyroid replacement therapy. On multivariate analysis higher Dmean and smaller TG volume maintained the statistically significant association with the risk of clinical RHT (P < .0001). Dmean was significantly higher in patients with clinical RHT versus those without (50 vs 42 Gy, P < .0001). Patients with RHT had smaller TG volume compared with those without (11.8 compared with 12.8 mL, P < .0001). AUC of 0.72 and 0.66 were identified for fitted model versus for the applied Boomsma et al and Cella et al models, respectively.

CONCLUSIONS

Volume and Dmean of the TG are important predictors of clinical RHT and shall be integrated into normal tissue complication probability models for RHT. Dmean and thyroid volume should be considered during the IMRT plan optimization in OPC patients.

PACE: A Probabilistic Atlas for Normal Tissue Complication Estimation in Radiation Oncology

In radiation oncology, the need for a modern Normal Tissue Complication Probability (NTCP) philosophy to include voxel-based evidence on organ radio-sensitivity (RS) has been acknowledged. Here a new formalism (Probabilistic Atlas for Complication Estimation, PACE) to predict radiation-induced morbidity (RIM) is presented. The adopted strategy basically consists in keeping the structure of a classical, phenomenological NTCP model, such as the Lyman-Kutcher-Burman (LKB), and replacing the dose distribution with a collection of RIM odds, including also significant non-dosimetric covariates, as input of the model framework. The theory was first demonstrated in silico on synthetic dose maps, classified according to synthetic outcomes. PACE was then applied to a clinical dataset of thoracic cancer patients classified for lung fibrosis. LKB models were trained for comparison. Overall, the obtained learning curves showed that the PACE model outperformed the LKB and predicted synthetic outcomes with an accuracy >0.8. On the real patients, PACE performance, evaluated by both discrimination and calibration, was significantly higher than LKB. This trend was confirmed by cross-validation. Furthermore, the capability to infer the spatial pattern of underlying RS map for the analyzed RIM was successfully demonstrated, thus paving the way to new perspectives of NTCP models as learning tools.

Distinct vascular genomic response of proton and gamma radiation-A pilot investigation

The cardiovascular biology of proton radiotherapy is not well understood. We aimed to compare the genomic dose-response to proton and gamma radiation of the mouse aorta to assess whether their vascular effects may diverge. We performed comparative RNA sequencing of the aorta following (4 hrs) total-body proton and gamma irradiation (0.5–200 cGy whole body dose, 10 dose levels) of conscious mice. A trend analysis identified genes that showed a dose response. While fewer genes were dose-responsive to proton than gamma radiation (29 vs. 194 genes; q-value ≤ 0.1), the magnitude of the effect was greater. Highly responsive genes were enriched for radiation response pathways (DNA damage, apoptosis, cellular stress and inflammation; p-value ≤ 0.01). Gamma, but not proton radiation induced additionally genes in vasculature specific pathways. Genes responsive to both radiation types showed almost perfectly superimposable dose-response relationships. Despite the activation of canonical radiation response pathways by both radiation types, we detected marked differences in the genomic response of the murine aorta. Models of cardiovascular risk based on photon radiation may not accurately predict the risk associated with proton radiation.

Early Detection of Cardiovascular Changes After Radiotherapy for Breast Cancer: Protocol for a European Multicenter Prospective Cohort Study (MEDIRAD EARLY HEART Study)

Background

Breast cancer is the most common cancer among women, and radiotherapy plays a major role in its treatment. However, breast cancer radiotherapy can lead to incidental irradiation of the heart, resulting in an increased risk for a variety of heart diseases arising many years after radiotherapy. Therefore, identifying breast cancer patients at the highest risk for radiation-induced cardiac complications is crucial for developing strategies for primary and secondary prevention, which may contribute to healthy aging. There is still a need for precise knowledge on the relationship between radiation dose to specific cardiac structures and early subclinical cardiac changes and their occurrence over time that could finally lead to cardiac complications.

Objective

The MEDIRAD EARLY HEART study aims to identify and validate new cardiac imaging and circulating biomarkers of radiation-induced cardiovascular changes arising within first 2 years of breast cancer radiotherapy and to develop risk models integrating these biomarkers combined with precise dose metrics of cardiac structures based on three-dimensional dosimetry.

Methods

The EARLY HEART study is a multicenter, prospective cohort study in which 250 women treated for breast cancer and followed for 2 years after radiotherapy will be included. Women treated with radiotherapy without chemotherapy for a unilateral breast cancer and aged 40-75 years meet the inclusion criteria. Baseline and follow-up data include cardiac measurements based on two-dimensional speckle-tracking echocardiography, computed tomography coronary angiography, cardiac magnetic resonance imaging, and a wide panel of circulating biomarkers of cardiac injury. The absorbed dose will be evaluated globally for the heart and different substructures. Furthermore, the dose-response relationship will allow modeling the radiation-induced occurrence and evolution of subclinical cardiac lesions and biomarkers to develop prediction models.

Results

This study details the protocol of the MEDIRAD EARLY HEART study and presents the main limits and advantages of this international project. The inclusion of patients began in 2017. Preliminary results are expected to be published in 2019, and complete analysis should be published in 2021.

Conclusions

The MEDIRAD EARLY HEART study will allow identifying the main cardiac imaging and blood-based determinants of radiation-induced cardiac injuries to better propose primary and secondary preventive measures in order to contribute to enhanced patient care and quality of life.

Trial Registration

ClinicalTrials.gov NCT03297346; https://clinicaltrials.gov/ct2/show/NCT03297346 (Archived by WebCite at http://www.webcitation.org/72KS7MIUU)

Registered Report Identifier

RR1-10.2196/9906

Relationships among patient characteristics, irradiation treatment planning parameters, and treatment toxicity of acute radiation dermatitis after breast hybrid intensity modulation radiation therapy

To evaluate the relationships among patient characteristics, irradiation treatment planning parameters, and treatment toxicity of acute radiation dermatitis (RD) after breast hybrid intensity modulation radiation therapy (IMRT). The study cohort consisted of 95 breast cancer patients treated with hybrid IMRT. RD grade ≥2 (2⁺) toxicity was defined as clinically significant. Patient characteristics and the irradiation treatment planning parameters were used as the initial candidate factors. Prognostic factors were identified using the least absolute shrinkage and selection operator (LASSO)-based normal tissue complication probability (NTCP) model. A univariate cut-off dose NTCP model was developed to find the dose-volume limitation. Fifty-two (54.7%) of ninety-five patients experienced acute RD grade 2⁺ toxicity. The volume of skin receiving a dose >35 Gy (V₃₅) was the most significant dosimetric predictor associated with RD grade 2⁺ toxicity. The NTCP model parameters for V_35Gy were TV₅₀ = 85.7 mL and γ₅₀ = 0.77, where TV₅₀ was defined as the volume corresponding to a 50% incidence of complications, and γ₅₀ was the normalized slope of the volume-response curve. Additional potential predictive patient characteristics were energy and surgery, but the results were not statistically significant.

To ensure a better quality of life and compliance for breast hybrid IMRT patients, the skin volume receiving a dose >35 Gy should be limited to <85.7 mL to keep the incidence of RD grade 2⁺ toxicities below 50%. To avoid RD toxicity, the volume of skin receiving a dose >35 Gy should follow sparing tolerance and the inherent patient characteristics should be considered.

Changes in the retreatment radiation tolerance of the spinal cord with time after the initial treatment

PURPOSE

To estimate, from experimental data, the retreatment radiation 'tolerances' of the spinal cord at different times after initial treatment.

MATERIALS AND METHODS

A model was developed to show the relationship between the biological effective doses (BEDs) for two separate courses of treatment with the BED of each course being expressed as a percentage of the designated 'retreatment tolerance' BED value, denoted [Formula: see text] and [Formula: see text]. The primate data of Ang et al. ( 2001 ) were used to determine the fitted parameters. However, based on rodent data, recovery was assumed to commence 70 days after the first course was complete, and with a non-linear relationship to the magnitude of the initial BED (BED_init).

RESULTS

The model, taking into account the above processes, provides estimates of the retreatment tolerance dose after different times. Extrapolations from the experimental data can provide conservative estimates for the clinic, with a lower acceptable myelopathy incidence. Care must be taken to convert the predicted [Formula: see text] value into a formal BED value and then a practical dose fractionation schedule.

CONCLUSIONS

Used with caution, the proposed model allows estimations of retreatment doses with elapsed times ranging from 70 days up to three years after the initial course of treatment.

Normal tissue damage: its importance, history and challenges for the future

Sir Oliver Scott, a philanthropist and radiation biologist and, therefore, the epitome of a gentleman and a scholar, was an early Director of the BECC Radiobiology Research Unit at Mount Vernon. His tenure preceded that of Jack Fowler, with both contributing to basic, translational and clinical thought and application in radiation across the globe. With respect to this review, Fowler's name in particular has remained synonymous with the use of models, both animal and mathematical, that assess and quantify the biological mechanisms that underlie radiation-associated normal tissue toxicities. An understanding of these effects is critical to the optimal use of radiation therapy in the clinic; however, the role that basic sciences play in clinical practice has been undergoing considerable change in recent years, particularly in the USA, where there has been a growing emphasis on engineering and imaging to improve radiation delivery, with empirical observations of clinical outcome taking the place of models underpinned by evidence from basic science experiments. In honour of Scott and Fowler's work, we have taken this opportunity to review how our respective fields of radiation biology and radiation physics have intertwined over the years, affecting the clinical use of radiation with respect to normal tissue outcomes. We discuss the past and current achievements, with the hope of encouraging a revived interest in physics and biology as they relate to radiation oncology practice, since, like Scott and Fowler, we share the goal of improving the future outlook for cancer patients.

Early Effects of Ionizing Radiation on the Collagen Hierarchical Structure of Bladder and Rectum Visualized by Atomic Force Microscopy

Radiation therapy, widely used in the treatment of a variety of malignancies in the pelvic area, is associated with inevitable damage to the surrounding healthy tissues. We have applied atomic force microscopy (AFM) to track the early damaging effects of ionizing radiation on the collagen structures in the experimental animals' bladder and rectum. The first signs of the low-dose radiation (2 Gy) effect were detected by AFM as early as 1 week postirradiation. The observed changes were consistent with initial radiation destruction of the protein matrix. The alterations in the collagen fibers' packing 1 month postirradiation were indicative of the onset of fibrotic processes. The destructive effect of higher radiation doses was probed 1 day posttreatment. The severity of the radiation damage was proportional to the dose, from relatively minor changes in the collagen packing at 8 Gy to the growing collagen matrix destruction at higher doses and complete three-dimensional collagen network restructuring towards fibrotic-type architecture at the dose of 22 Gy. The AFM study appeared superior to the optical microscopy-based studies in its sensitivity to early radiation damage of tissues, providing valuable additional information on the onset and development of the collagen matrix destruction and remodeling.

A Co-culture Method to Investigate the Crosstalk Between X-ray Irradiated Caco-2 Cells and PBMC

The protocol adopted in this work aims at unraveling how X-rays perturb the functioning of the intestinal barrier, focusing on the interplay between colorectal tumor cells and the immune system. Colorectal carcinoma is among the most common type of cancer, typically treated by surgery, chemotherapy, and radiotherapy. Advantages of radiotherapy in targeting the tumor are well known. However, even limited exposures of healthy tissues are of great concern, particularly regarding the effects on the intestinal barrier and the immune system. The adopted setup allows to study the interplay between two cell populations in a condition more similar to the physiological one, when compared to normal cell cultures. For this purpose, we resort to different techniques and we used an in vitro co-culture model, based on Caco-2 cells differentiated as a monolayer and PBMC, sharing the same culture medium. This protocol has been developed to focus on both macroscopic effects, i.e. cell viability and Trans-Epithelial Electrical Resistance (TEER), and, through western blot, molecular alterations, i.e. the activation of inflammatory pathway in immune cells and the tight junction protein expression in Caco-2 cells. Initial evaluation of radiation effects on Caco-2 cell viability was assessed via the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and Trypan blue assays, while TEER was measured at fixed time intervals through an ohmmeter specifically designed for co-culture systems. In this way, the effects due to radiation, the presence of Peripheral Blood Mononuclear Cells (PBMC), and eventually their synergistic effect, can be demonstrated. Through these complementary techniques, we observed a high radio-resistance of Caco-2 within the range of 2 - 10 Gy of X-rays and an increased Caco-2 monolayer permeability when PBMCs were added. In particular, PBMC presence was found to be associated with the variation in the tight junction scaffold proteins expression.

Special radiobiological features of second cancer risk after particle radiotherapy

In absolute terms: second cancer risks from radiotherapy of first cancers in adults are small compared to the benefits from radiotherapy but this is not so for radiotherapy of childhood cancers. Moreover, the radiation dose dependence of cancer induction differs between organs and tissues. The organ-specific dose dependence of second cancer risks may indicate the existence of different radiobiological mechanisms. As an inevitable consequence of the age dependence of organ sensitivity to second cancer induction, the organ/tissue weighting factors which have been proposed by ICRP for calculating effective dose (the dose unit Sv) and for risk estimation in the general population should not be used in medical radiation exposures. In adult cancer radiotherapy, the most common unwanted effect is local tumour recurrence whereas both, severe late normal tissue damage and radiation-induced second cancers are rare, around 1% of locally controlled cancer patients. In childhood cancers, local failures are rare (<10% in some cancers) yet second cancers are more common than uncontrolled primaries. The main reason for considering particle radiotherapy for childhood cancers is the possibility to exploit their physical characteristics to reduce the radiation exposure to organs and tissues close to and distant from the primary cancer which is to be targeted. However, the relative biological effectiveness of the radiation doses within the proton beam is not a constant and the relative biological effectiveness of the neutrons is not known as far as the mechanisms of late normal tissue damage and second cancer risk are concerned. In view of the highly charged discussions of the potential risks of treatment-induced seecond cancers from the neutron contamination of exposure doses in out-of-PTV critical organs a comprehensive European project called ANDANTE was performed which integrated the disciplines of radiation physics, molecular biology, systems biology modelling and epidemiology in order to investigate the RBE of induction of cancer from exposure to neutrons compared to photons. Since out-of-field "effective" neutron doses from proton therapy are smaller than the photon stray doses whichever reasonable RBE is chosen for comparison, and since the absolute risk of radiation-induced second cancer rates are in the order of 1% in the cohorts of adult patients who have been treated in the past with methods which caused relatively high out-of-field doses to large body volumes, it is highly unlikely that such patients treated in future with highly conformal particle therapy are at a higher radiation-induced second cancer risk than those patients treated with photons and described before. Still, the potential risks of second cancers from scattered proton radiotherapy for childhood cancers may cause concern. Yet, the overall risk of undesired consequences of radiation exposure of children which are more complex and manifold than in adult patients (including developmental, neurocognitive, hormonal and growth impairment effects) are likely to be very much reduced by the better focussing of the radiation dose in the target offered by particle radioherapy. This benefit may far outweigh the still hypothetical second cancer risk from particle radiotherapy in pediatric radiotherapy.

The Interplay between Radioresistant Caco-2 Cells and the Immune System Increases Epithelial Layer Permeability and Alters Signaling Protein Spectrum

Colorectal cancer is one of the most frequent type of cancer, with a higher incidence in the developed countries. Colorectal cancer is usually managed with both surgeries, chemotherapy and radiotherapy. Radiotherapy has the well-known advantage of targeting the tumor, minimizing normal tissue exposure. Nevertheless, during radiation treatment, exposure of healthy tissues is of great concern, in particular because of the effects on the intestinal barrier functions and on cells belonging to the immune system. The functional role of intestinal barrier in avoiding paracellular trafficking and controlling bacterial spread from gut it is well known and it is due to the presence of tight junction complexes. However, intestinal barrier is fundamental in participating to the interplay with immune system, especially considering the gut-associated lymphoid tissue. Until few years ago, radiotherapy was considered to bear only a depressive action on the immune system. However, it is now recognized that the release of pro-inflammatory signals and phenotypic changes in tumoral cells due to ionizing radiation could trigger the immune system against the tumor. In this work, we address how intestinal barrier functions are perturbed by X-ray doses in the range 0–10 Gy, focusing on the interplay between tumoral cells and the immune system. To this aim, we adopted a coculture model in which Caco-2 cells can be grown in presence/absence of peripheral blood mononuclear cells (PBMC). We focused our attention on changes in the proliferation, trans-epithelial electrical resistance (TEER), cytokine release, and proteins of the junctional complexes. Our results indicate a high radioresistance of Caco-2 in the investigated dose range, and an increased permeability of the tumoral cell layer due to the presence of PBMC. This is found to be correlated with activation of PBMC, inhibiting the apoptotic pathway, with the enhancement of cytokine release and with variation of tight junction scaffold protein expression levels, assumed to be related to IFN-γ- and TNF-α-mediated signaling.

Why RBE must be a variable and not a constant in proton therapy

OBJECTIVE

This article considered why the proton therapy (PT) relative biological effect (RBE) should be a variable rather than a constant.

METHODS

The reasons for a variable proton RBE are enumerated, with qualitative and quantitative arguments. The heterogeneous data sets collated by Paganetti et al (2002) and the more homogeneous data of Britten et al (2013) are further analyzed using linear regression fitting and RBE-inclusive adaptations of the linear-quadratic (LQ) radiation model.

RESULTS

The in vitro data show RBE increasing as dose per fraction is lowered. In the Paganetti et al (2002) data sets, the differences between observed and expected effects are smaller when the LQ model is used, but with such data heterogeneity, firm statistical conclusions cannot be obtained. The more homogeneous data set shows an unequivocal variation in RBE with dose per faction. The in vivo data are inappropriate for assessments of late normal tissue effects in radiotherapy. Also, if there is the same degree of uncertainty in an RBE of 1.1 or in an RBE of 2-3 for C ions, the fractional and biological effective doses can vary considerably and be greater in the proton case. So, errors in RBE assignment are important for protons, just as with C ions.

CONCLUSION

Further experimental programmes are proposed, including late normal tissue end points. Better RBE allocations might further improve PT outcomes.

ADVANCES IN KNOWLEDGE

This study provides a rigorous critique of the 1.1 RBE used for protons, from theoretical and practical standpoints. Data analysis shows that the LQ model is more appropriate than simple linear regression. Comprehensive research programmes are suggested.

Early detection and prediction of cardiotoxicity after radiation therapy for breast cancer: the BACCARAT prospective cohort study

Background

Radiotherapy (RT) for breast cancer presents a benefit in terms of reducing local recurrence and deaths resulting from breast cancer but it can lead to secondary effects due to the presence of neighboring cardiac normal tissues within the irradiation field. Breast RT has been shown to be associated with long-term increased risk of heart failure, coronary artery disease, myocardial infarction and finally cardiovascular death more than 10 years after RT. However, there is still a lack of knowledge for early cardiotoxicity induced by breast RT that can appear long before the onset of clinically significant cardiac events. Based on a 2-year follow-up prospective cohort of patients treated with breast RT, the BACCARAT (BreAst Cancer and CArdiotoxicity Induced by RAdioTherapy) study aims to enhance knowledge on detection and prediction of early subclinical cardiac dysfunction and lesions induced by breast RT and on biological mechanisms potentially involved, based on functional and anatomical cardiac imaging combined with simultaneous assessment of multiple circulating biomarkers and accurate heart dosimetry.

Methods/Design

BACCARAT study consists in a monocentric prospective cohort study that will finally include 120 women treated with adjuvant 3D CRT for breast cancer, and followed for 2 years after RT. Women aged 50 to 70 years, treated for breast cancer and for whom adjuvant 3D CRT is indicated, without chemotherapy are eligible for the study. Baseline (before RT) and follow-up data include measurements of functional myocardial dysfunction including strain and strain rate based on 2D-speckle tracking echocardiography, anatomical coronary lesions including description of plaques in segments of coronary arteries based on Coronary computed tomography angiography, and a wide panel of circulating biomarkers. The absorbed dose is evaluated for the whole heart and its substructures, in particular the coronary arteries. Analysis on occurrence and evolution of subclinical cardiac lesions and biomarkers will be performed and completed with dose-response relationship. Multivariate model of normal tissue complication probability (NTCP) will also be proposed.

Discussion

Tools and results developed in the BACCARAT study should allow improving prediction and prevention of potential lesions to cardiac normal tissues surrounding tumors and ultimately enhance patients’ care and quality of life.

Trial registration

ClinicalTrials.gov: NCT02605512

Outcome modeling techniques for prostate cancer radiotherapy: Data, models, and validation

Prostate cancer is a frequently diagnosed malignancy worldwide and radiation therapy is a first-line approach in treating localized as well as locally advanced cases. The limiting factor in modern radiotherapy regimens is dose to normal structures, an excess of which can lead to aberrant radiation-induced toxicities. Conversely, dose reduction to spare adjacent normal structures risks underdosing target volumes and compromising local control. As a result, efforts aimed at predicting the effects of radiotherapy could invaluably optimize patient treatments by mitigating such toxicities and simultaneously maximizing biochemical control. In this work, we review the types of data, frameworks and techniques used for prostate radiotherapy outcome modeling. Consideration is given to clinical and dose-volume metrics, such as those amassed by the QUANTEC initiative, and also to newer methods for the integration of biological and genetic factors to improve prediction performance. We furthermore highlight trends in machine learning that may help to elucidate the complex pathophysiological mechanisms of tumor control and radiation-induced normal tissue side effects.

Recent advancements in toxicity prediction following prostate cancer radiotherapy

In external beam radiotherapy for prostate cancer limiting toxicities for dose escalation are bladder and rectum toxicities. Normal tissue complication probability models aim at quantifying the risk of developping adverse events following radiotherapy. These models, originally proposed in the context of uniform irradiation, have evolved to implementations based on the state-of-the-art classification methods which are trained using empirical data. Recently, the use of image processing techniques combined with population analysis methods has led to a new generation of models to understand the risk of normal tissue complications following radiotherapy. This paper overviews those methods in the case of prostate cancer radiation therapy and propose some lines of future research.

A new parameter computed with independent component analysis to predict rectal toxicity following prostate cancer radiotherapy

The main challenge in prostate cancer radiotherapy is to deliver the prescribed dose to the clinical target while minimizing the dose to the neighboring organs at risk and thus avoiding subsequent toxicity-related events. With the aim of improving toxicity prediction following prostate cancer radiotherapy, the goal of our work is to propose a new predictive variable computed with independent component analysis to predict late rectal toxicity, and to compare its performance to other models (logistic regression, normal tissue complication probability model and recent principal component analysis approach). Clinical data and dose-volume histograms were collected from 216 patients having received 3D conformal radiation for prostate cancer with at least two years of follow-up. Independent component analysis was trained to predict the risk of 3-year rectal bleeding Grade ≥ 2. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve. Clinical parameters combined with the new variable were found to be predictors of rectal bleeding. The mean area under the receiving operating curve for our proposed approach was 0:75. The AUC values for the logistic regression, the Lyman-Kutcher-Burman model and the recent principal component analysis approach were 0:62, 0:53 and 0:62, respectively. Our proposed new variable may be an useful new tool in predicting late rectal toxicity. It appears as a strong predictive variable to improve classical models.

Revisiting Biomarkers of Total-Body and Partial-Body Exposure in a Baboon Model of Irradiation

In case of a mass casualty radiation event, there is a need to distinguish total-body irradiation (TBI) and partial-body irradiation (PBI) to concentrate overwhelmed medical resources to the individuals that would develop an acute radiation syndrome (ARS) and need hematologic support (i.e., mostly TBI victims). To improve the identification and medical care of TBI versus PBI individuals, reliable biomarkers of exposure could be very useful. To investigate this issue, pairs of baboons (n = 18) were exposed to different situations of TBI and PBI corresponding to an equivalent of either 5 Gy ⁶⁰Co gamma irradiation (5 Gy TBI; 7.5 Gy left hemibody/2.5 right hemibody TBI; 5.55 Gy 90% PBI; 6.25 Gy 80% PBI; 10 Gy 50% PBI, 15 Gy 30% PBI) or 2.5 Gy (2.5 Gy TBI; 5 Gy 50% PBI). More than fifty parameters were evaluated before and after irradiation at several time points up to 200 days. A partial least square discriminant analysis showed a good distinction of TBI from PBI situations that were equivalent to 5 Gy. Furthermore, all the animals were pooled in two groups, TBI (n = 6) and PBI (n = 12), for comparison using a logistic regression and a non parametric statistical test. Nine plasmatic biochemical markers and most of hematological parameters turned out to discriminate between TBI and PBI animals during the prodromal phase and the manifest illness phase. The most significant biomarkers were aspartate aminotransferase, creatine kinase, lactico dehydrogenase, urea, Flt3-ligand, iron, C-reactive protein, absolute neutrophil count and neutrophil-to-lymphocyte ratio for the early period, and Flt3-ligand, iron, platelet count, hemoglobin, monocyte count, absolute neutrophil count and neutrophil-to-lymphocyte ratio for the ARS phase. These results suggest that heterogeneity could be distinguished within a range of 2.5 to 5 Gy TBI.

Contrasting analytical and data-driven frameworks for radiogenomic modeling of normal tissue toxicities in prostate cancer

BACKGROUND AND PURPOSE

We explore analytical and data-driven approaches to investigate the integration of genetic variations (single nucleotide polymorphisms [SNPs] and copy number variations [CNVs]) with dosimetric and clinical variables in modeling radiation-induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients.

MATERIALS AND METHODS

Sixty-two patients who underwent curative hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 and 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Fifty-four patients had full dosimetric profiles. Two parallel modeling approaches were compared to assess the risk of severe RB (Grade⩾3) and ED (Grade⩾1); Maximum likelihood estimated generalized Lyman-Kutcher-Burman (LKB) and logistic regression. Statistical resampling based on cross-validation was used to evaluate model predictive power and generalizability to unseen data.

RESULTS

Integration of biological variables xrcc1 CNV and SNP improved the fit of the RB and ED analytical and data-driven models. Cross-validation of the generalized LKB models yielded increases in classification performance of 27.4% for RB and 14.6% for ED when xrcc1 CNV and SNP were included, respectively. Biological variables added to logistic regression modeling improved classification performance over standard dosimetric models by 33.5% for RB and 21.2% for ED models.

CONCLUSION

As a proof-of-concept, we demonstrated that the combination of genetic and dosimetric variables can provide significant improvement in NTCP prediction using analytical and data-driven approaches. The improvement in prediction performance was more pronounced in the data driven approaches. Moreover, we have shown that CNVs, in addition to SNPs, may be useful structural genetic variants in predicting radiation toxicities.

Effects of gamma irradiation on collagen damage and remodeling

PURPOSE

To evaluate the dose-time dependences of structural changes occurring in collagen within 24 hours to three months after gamma-irradiation at doses from 2-40 Gy in vivo.

MATERIALS AND METHODS

Rat's tail tendon was chosen as in vivo model, with its highly ordered collagen structure allowing the changes to be interpreted unambiguously. Macromolecular level (I) was investigated by differential scanning calorimetry (DSC); fibers and bundles level (II) by laser scanning microscopy (LSM), and bulk tissue microstructural level (III) by cross-polarization optical coherence tomography (CP-OCT).

RESULTS

For (I), the formation of molecular cross-links and breaks appeared to be a principal mechanism of collagen remodeling, with the cross-links number dependent on radiation dose. Changes on level (II) involved primary, secondary and tertiary bundles splitting in a day and a week after irradiation. Bulk collagen microstructure (III) demonstrated early widening of the interference fringes on CP-OCT images observed to occur in the tendon as result of this splitting. At all three levels, the observed collagen changes demonstrated complete remodeling within ∼ a month following irradiation.

CONCLUSION

The time course and dose dependencies of the observed collagen changes at different levels of its hierarchy further contribute to elucidating the role of connective tissue in the radiotherapy process.

Radiotherapy-induced mesorectum alterations: histological evaluation of 90 consecutive cases

OBJECTIVE

In order to identify the radiotherapy-induced histological modifications in the mesorectum, we reviewed the surgical specimens of 90 rectal resections comprehensive of the total mesorectal excision (23 cases radiologically classified as cT2N0M0 and 67 as cT3N0M0). All patients were preoperative treated with radiotherapy: 20 with 50 Gy, 20 with 20 Gy and 50 Gy irradiation associated to FOLFOX scheme chemotherapy.

MATERIAL AND METHODS

Routine hematoxylin and eosin stained serial slides at 5 mm of intervals were obtained from surgical specimens and included the tumor site and the adjacent irradiated mucosa, the submucosa and the muscular layers of the rectal wall and the mesorectal adipose tissue, completely removed until to the mesorectal fascia. Ten subjects (eight cT2N0M0 and two cT3N0M0), who did not received preoperative oncological treatments were adopted as controls.

RESULTS

Histologically, examination revealed fibrosis of the adipose tissue in 86 cases (95%), vascular damage including vasculities and fibrotic thickening wall of arteries and veins in 46 cases (51%), sclero-hyalinosis of lymph nodes with pericapsular fibrosis in 22 cases (23%) and perineural deposition of fibrosis in 12 (13%). These findings were ubiquitously observed in the whole mesorectum. Fibrosis of the adipose tissue and vasculitis were mainly associated to the combination of 50 Gy radiations plus chemotherapy (p < 0.05).

CONCLUSION

The detection of histopathological alterations in the mesorectum can give reason of the well-known postoperative complications and long-term sequels.

Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?

Purpose

The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation.

Methods

All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were included (n = 90). All patients were treated with three-dimensional conformal radiotherapy with a median total dose of 32 Gy. The cardiac toxicity profile was available for each patient. Heart and lung dose-volume histograms (DVHs) were extracted and both organs were considered for Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) NTCP model fitting using maximum likelihood estimation. Bootstrap refitting was used to test the robustness of the model fit. Model performance was estimated using the area under the receiver operating characteristic curve (AUC).

Results

Using only heart-DVHs, parameter estimates were, for the LKB model: D₅₀ = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D₅₀ = 32.4 Gy, s = 0.99 and γ = 0.42. AUC values were 0.67 for LKB and 0.66 for RS, respectively. Similar performance was obtained for models using only lung-DVHs (LKB: D₅₀ = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D₅₀ = 24.4 Gy, s = 0.99, γ = 2.12, AUC = 0.66). Bootstrap result showed that the parameter fits for lung-LKB were extremely robust. A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70). However, the best performance was obtained using the previously determined multivariate regression model including maximum heart dose with increasing risk for larger heart and smaller lung volumes (AUC = 0.82).

Conclusions

The risk of radiation induced valvular disease cannot be modeled using NTCP models only based on heart dose-volume distribution. A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.

Random forests to predict rectal toxicity following prostate cancer radiation therapy

PURPOSE

To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models.

METHODS AND MATERIALS

Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression model was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC).

RESULTS

The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69.

CONCLUSIONS

The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.

Chemokine treatment rescues profound T-lineage progenitor homing defect after bone marrow transplant conditioning in mice

Development of T cells in the thymus requires continuous importation of T-lineage progenitors from the bone marrow via the circulation. Following bone marrow transplant, recovery of a normal peripheral T-cell pool depends on production of naïve T cells in the thymus; however, delivery of progenitors to the thymus limits T-lineage reconstitution. Here, we examine homing of intravenously delivered progenitors to the thymus following irradiation and bone marrow reconstitution. Surprisingly, following host conditioning by irradiation, we find that homing of lymphoid-primed multipotent progenitors and common lymphoid progenitors to the thymus decreases more than 10-fold relative to unirradiated mice. The reduction in thymic homing in irradiated mice is accompanied by a significant reduction in CCL25, an important chemokine ligand for thymic homing. We show that pretreatment of bone marrow progenitors with CCL25 and CCL21 corrects the defect in thymic homing after irradiation and promotes thymic reconstitution. These data suggest new therapeutic approaches to promote T-cell regeneration.

A prospective study comparing the predictions of doctors versus models for treatment outcome of lung cancer patients: a step toward individualized care and shared decision making

BACKGROUND

Decision Support Systems, based on statistical prediction models, have the potential to change the way medicine is being practiced, but their application is currently hampered by the astonishing lack of impact studies. Showing the theoretical benefit of using these models could stimulate conductance of such studies. In addition, it would pave the way for developing more advanced models, based on genomics, proteomics and imaging information, to further improve the performance of the models.

PURPOSE

In this prospective single-center study, previously developed and validated statistical models were used to predict the two-year survival (2yrS), dyspnea (DPN), and dysphagia (DPH) outcomes for lung cancer patients treated with chemo radiation. These predictions were compared to probabilities provided by doctors and guideline-based recommendations currently used. We hypothesized that model predictions would significantly outperform predictions from doctors.

MATERIALS AND METHODS

Experienced radiation oncologists (ROs) predicted all outcomes at two timepoints: (1) after the first consultation of the patient, and (2) after the radiation treatment plan was made. Differences in the performances of doctors and models were assessed using Area Under the Curve (AUC) analysis.

RESULTS

A total number of 155 patients were included. At timepoint #1 the differences in AUCs between the ROs and the models were 0.15, 0.17, and 0.20 (for 2yrS, DPN, and DPH, respectively), with p-values of 0.02, 0.07, and 0.03. Comparable differences at timepoint #2 were not statistically significant due to the limited number of patients. Comparison to guideline-based recommendations also favored the models.

CONCLUSION

The models substantially outperformed ROs' predictions and guideline-based recommendations currently used in clinical practice. Identification of risk groups on the basis of the models facilitates individualized treatment, and should be further investigated in clinical impact studies.

Acta Oncologica Lecture. Gastrointestinal consequences of cancer treatment and the wider context: a bad gut feeling

BACKGROUND

The percentage of people living with a diagnosis of cancer is rising globally. Between 20% and 25% of people treated for cancer experience a consequence of cancer which has an adverse impact on the quality of their life. Gastrointestinal (GI) symptoms are the most common of all consequences of cancer treatment and have the greatest impact on daily activity. PATHOPHYSIOLOGY OF LONG-TERM BOWEL DAMAGE AFTER PELVIC RADIOTHERAPY: Long-term damage to the bowel after radiotherapy is mediated by ischaemic changes and fibrosis. Each fraction of radiotherapy causes a series of repetitive injuries to the intestinal tissue resulting in an altered healing process, which affects the integrity of the repair and changes the architecture of the bowel wall. THE NATURE OF GI SYMPTOMS THAT DEVELOP: Patient-reported outcome measures show that diarrhoea, urgency, increased bowel frequency, tenesmus and flatulence are the five most prevalent GI symptoms with a moderate or severe impact on patients' daily lives after treatment with pelvic radiotherapy. Many patients also experience fatigue, urinary problems and have sexual concerns. SYSTEMATIC ASSESSMENT AND MANAGEMENT: The complex nature of those symptoms warrants systematic assessment and management. The use of a tested algorithm can assist in achieving this. The most common contributing factors to ongoing bowel problems after pelvic radiotherapy are small intestinal bacterial overgrowth, bile acid malabsorption, pancreatic insufficiency, rectal bleeding and its impact on bone health.

THE WIDER CONTEXT

Symptom burden, socio-psychosocial impact, memory and cognitive function, fatigue, urinary problems and sexual concerns need to be taken into account when thinking about consequences of cancer treatment.

CONCLUSION

As our understanding of consequences of cancer treatments continues to emerge and encompass a wide variety of specialties, a holistic, multifaceted and multidisciplinary approach is required to manage those consequences long-term.

Dose/volume-response relations for rectal morbidity using planned and simulated motion-inclusive dose distributions

BACKGROUND AND PURPOSE

Many dose-limiting normal tissues in radiotherapy (RT) display considerable internal motion between fractions over a course of treatment, potentially reducing the appropriateness of using planned dose distributions to predict morbidity. Accounting explicitly for rectal motion could improve the predictive power of modelling rectal morbidity. To test this, we simulated the effect of motion in two cohorts.

MATERIALS AND METHODS

The included patients (232 and 159 cases) received RT for prostate cancer to 70 and 74 Gy. Motion-inclusive dose distributions were introduced as simulations of random or systematic motion to the planned dose distributions. Six rectal morbidity endpoints were analysed. A probit model using the QUANTEC recommended parameters was also applied to the cohorts.

RESULTS

The differences in associations using the planned over the motion-inclusive dose distributions were modest. Statistically significant associations were obtained with four of the endpoints, mainly at high doses (55-70 Gy), using both the planned and the motion-inclusive dose distributions, primarily when simulating random motion. The strongest associations were observed for GI toxicity and rectal bleeding (Rs=0.12-0.21; Rs=0.11-0.20). Applying the probit model, significant associations were found for tenesmus and rectal bleeding (Rs=0.13, p=0.02).

CONCLUSION

Equally strong associations with rectal morbidity were observed at high doses (>55 Gy), for the planned and the simulated dose distributions including in particular random rectal motion. Future studies should explore patient-specific descriptions of rectal motion to achieve improved predictive power.

Multivariate normal tissue complication probability modeling of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancer

Background

The risk of radio-induced gastrointestinal (GI) complications is affected by several factors other than the dose to the rectum such as patient characteristics, hormonal or antihypertensive therapy, and acute rectal toxicity. Purpose of this work is to study clinical and dosimetric parameters impacting on late GI toxicity after prostate external beam radiotherapy (RT) and to establish multivariate normal tissue complication probability (NTCP) model for radiation-induced GI complications.

Methods

A total of 57 men who had undergone definitive RT for prostate cancer were evaluated for GI events classified using the RTOG/EORTC scoring system. Their median age was 73 years (range 53–85). The patients were assessed for GI toxicity before, during, and periodically after RT completion. Several clinical variables along with rectum dose-volume parameters (Vx) were collected and their correlation to GI toxicity was analyzed by Spearman’s rank correlation coefficient (Rs). Multivariate logistic regression method using resampling techniques was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC).

Results

At a median follow-up of 30 months, 37% (21/57) patients developed G1-2 acute GI events while 33% (19/57) were diagnosed with G1-2 late GI events. An NTCP model for late mild/moderate GI toxicity based on three variables including V65 (OR = 1.03), antihypertensive and/or anticoagulant (AH/AC) drugs (OR = 0.24), and acute GI toxicity (OR = 4.3) was selected as the most predictive model (Rs = 0.47, p < 0.001; AUC = 0.79). This three-variable model outperforms the logistic model based on V65 only (Rs = 0.28, p < 0.001; AUC = 0.69).

Conclusions

We propose a logistic NTCP model for late GI toxicity considering not only rectal irradiation dose but also clinical patient-specific factors. Accordingly, the risk of G1-2 late GI increases as V65 increases, it is higher for patients experiencing previous acute toxicity and it is lower for patients who take AH/AC drugs. The developed NTCP model could represent a potentially useful tool to be used in prospective trial and for comparison among different RT techniques.

Hypothyroidism after primary radiotherapy for head and neck squamous cell carcinoma: normal tissue complication probability modeling with latent time correction

BACKGROUND AND PURPOSE

To develop a normal tissue complication probability (NTCP) model of radiation-induced biochemical hypothyroidism (HT) after primary radiotherapy for head and neck squamous cell carcinoma (HNSCC) with adjustment for latency and clinical risk factors.

PATIENTS AND METHODS

Patients with HNSCC receiving definitive radiotherapy with 66-68Gy without surgery were followed up with serial post-treatment thyrotropin (TSH) assessment. HT was defined as TSH >4.0mU/l. Data were analyzed with both a logistic and a mixture model (correcting for latency) to determine risk factors for HT and develop an NTCP model based on mean thyroid dose (MTD) and thyroid volume.

RESULTS

203 patients were included. Median follow-up: 25.1months. Five-year estimated risk of HT was 25.6%. In the mixture model, the only independent risk factors for HT were thyroid volume (cm(3)) (OR=0.75 [95% CI: 0.64-0.85], p<0.001) and MTD (Gy) (OR=1.12 [95% CI: 1.07-1.20], p<0.001). From the mixture NTCP-model individual dose constraints for a 25% risk of HT were 26, 38, 48 and 61Gy for thyroid volumes of 10, 15, 20 and 25cm(3), respectively.

CONCLUSIONS

Comparing the logistic and mixture models demonstrates the importance of latent-time correction in NTCP-modeling. Thyroid dose constraints in treatment planning should be individualized based on thyroid volume.

Multivariate normal tissue complication probability modeling of heart valve dysfunction in Hodgkin lymphoma survivors

PURPOSE

To establish a multivariate normal tissue complication probability (NTCP) model for radiation-induced asymptomatic heart valvular defects (RVD).

METHODS AND MATERIALS

Fifty-six patients treated with sequential chemoradiation therapy for Hodgkin lymphoma (HL) were retrospectively reviewed for RVD events. Clinical information along with whole heart, cardiac chambers, and lung dose distribution parameters was collected, and the correlations to RVD were analyzed by means of Spearman's rank correlation coefficient (Rs). For the selection of the model order and parameters for NTCP modeling, a multivariate logistic regression method using resampling techniques (bootstrapping) was applied. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

When we analyzed the whole heart, a 3-variable NTCP model including the maximum dose, whole heart volume, and lung volume was shown to be the optimal predictive model for RVD (Rs = 0.573, P<.001, AUC = 0.83). When we analyzed the cardiac chambers individually, for the left atrium and for the left ventricle, an NTCP model based on 3 variables including the percentage volume exceeding 30 Gy (V30), cardiac chamber volume, and lung volume was selected as the most predictive model (Rs = 0.539, P<.001, AUC = 0.83; and Rs = 0.557, P<.001, AUC = 0.82, respectively). The NTCP values increase as heart maximum dose or cardiac chambers V30 increase. They also increase with larger volumes of the heart or cardiac chambers and decrease when lung volume is larger.

CONCLUSIONS

We propose logistic NTCP models for RVD considering not only heart irradiation dose but also the combined effects of lung and heart volumes. Our study establishes the statistical evidence of the indirect effect of lung size on radio-induced heart toxicity.

Spinal cord tolerance to single-session uniform irradiation in pigs: implications for a dose-volume effect

BACKGROUND AND PURPOSE

This study was performed to test the hypothesis that spinal cord radiosensitivity is significantly modified by uniform versus laterally non-uniform dose distributions.

MATERIALS AND METHODS

A uniform dose distribution was delivered to a 4.5-7.0 cm length of cervical spinal cord in 22 mature Yucatan minipigs for comparison with a companion study in which a laterally non-uniform dose was given [1]. Pigs were allocated into four dose groups with mean maximum spinal cord doses of 17.5 ± 0.1 Gy (n=7), 19.5 ± 0.2 Gy (n=6), 22.0 ± 0.1 Gy (n=5), and 24.1 ± 0.2 Gy (n=4). The study endpoint was motor neurologic deficit determined by a change in gait within one year. Spinal cord sections were stained with a Luxol fast blue/periodic acid Schiff combination.

RESULTS

Dose-response curves for uniform versus non-uniform spinal cord irradiation were nearly identical with ED(50)'s (95% confidence interval) of 20.2 Gy (19.1-25.8) and 20.0 Gy (18.3-21.7), respectively. No neurologic change was observed for either dose distribution when the maximum spinal cord dose was ≤ 17.8 Gy while all animals experienced deficits at doses ≥ 21.8 Gy.

CONCLUSION

No dose-volume effect was observed in pigs for the dose distributions studied and the endpoint of motor neurologic deficit; however, partial spinal cord irradiation resulted in less debilitating neurologic morbidity and histopathology.

Development of multivariate NTCP models for radiation-induced hypothyroidism: a comparative analysis

BACKGROUND

Hypothyroidism is a frequent late side effect of radiation therapy of the cervical region. Purpose of this work is to develop multivariate normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RHT) and to compare them with already existing NTCP models for RHT.

METHODS

Fifty-three patients treated with sequential chemo-radiotherapy for Hodgkin's lymphoma (HL) were retrospectively reviewed for RHT events. Clinical information along with thyroid gland dose distribution parameters were collected and their correlation to RHT was analyzed by Spearman's rank correlation coefficient (Rs). Multivariate logistic regression method using resampling methods (bootstrapping) was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). Models were tested against external published data on RHT and compared with other published NTCP models.

RESULTS

If we express the thyroid volume exceeding X Gy as a percentage (Vx(%)), a two-variable NTCP model including V30(%) and gender resulted to be the optimal predictive model for RHT (Rs = 0.615, p < 0.001. AUC = 0.87). Conversely, if absolute thyroid volume exceeding X Gy (Vx(cc)) was analyzed, an NTCP model based on 3 variables including V30(cc), thyroid gland volume and gender was selected as the most predictive model (Rs = 0.630, p < 0.001. AUC = 0.85). The three-variable model performs better when tested on an external cohort characterized by large inter-individuals variation in thyroid volumes (AUC = 0.914, 95% CI 0.760-0.984). A comparable performance was found between our model and that proposed in the literature based on thyroid gland mean dose and volume (p = 0.264).

CONCLUSIONS

The absolute volume of thyroid gland exceeding 30 Gy in combination with thyroid gland volume and gender provide an NTCP model for RHT with improved prediction capability not only within our patient population but also in an external cohort.