Inclusion of clinical risk factors into NTCP modelling of late rectal toxicity after high dose radiotherapy for prostate cancer

NRG Oncology White Paper on the Relative Biological Effectiveness in Proton Therapy

This position paper, led by the NRG Oncology Particle Therapy Work Group, focuses on the concept of relative biologic effect (RBE) in clinical proton therapy (PT), with the goal of providing recommendations for the next-generation clinical trials with PT on the best practice of investigating and using RBE, which could deviate from the current standard proton RBE value of 1.1 relative to photons. In part 1, current clinical utilization and practice are reviewed, giving the context and history of RBE. Evidence for variation in RBE is presented along with the concept of linear energy transfer (LET). The intertwined nature of tumor radiobiology, normal tissue constraints, and treatment planning with LET and RBE considerations is then reviewed. Part 2 summarizes current and past clinical data and then suggests the next steps to explore and employ tools for improved dynamic models for RBE. In part 3, approaches and methods for the next generation of prospective clinical trials are explored, with the goal of optimizing RBE to be both more reflective of clinical reality and also deployable in trials to allow clinical validation and interpatient comparisons. These concepts provide the foundation for personalized biologic treatments reviewed in part 4. Finally, we conclude with a summary including short- and long-term scientific focus points for clinical PT. The practicalities and capacity to use RBE in treatment planning are reviewed and considered with more biological data in hand. The intermediate step of LET optimization is summarized and proposed as a potential bridge to the ultimate goal of case-specific RBE planning that can be achieved as a hypothesis-generating tool in near-term proton trials.

Comparison of volumetric modulated arc therapy and helical tomotherapy for prostate cancer using Pareto fronts

BACKGROUND

Studies comparing different radiotherapy treatment techniques-such as volumetric modulated arc therapy (VMAT) and helical tomotherapy (HT)-typically compare one treatment plan per technique. Often, some dose metrics favor one plan and others favor the other, so the final plan decision involves subjective preferences. Pareto front comparisons provide a more objective framework for comparing different treatment techniques. A Pareto front is the set of all treatment plans where improvement in one criterion is possible only by worsening another criterion. However, different Pareto fronts can be obtained depending on the chosen machine settings.

PURPOSE

To compare VMAT and HT using Pareto fronts and blind expert evaluation, to explain the observed differences, and to illustrate limitations of using Pareto fronts.

METHODS

We generated Pareto fronts for twenty-four prostate cancer patients treated at our clinic for VMAT and HT techniques using an in-house script that controlled a commercial treatment planning system. We varied the PTV under-coverage (100% - V95%) and the rectum mean dose, and fixed the mean doses to the bladder and femoral heads. In order to ensure a fair comparison, those fixed mean doses were the same for the two treatment techniques and the sets of objective functions were chosen so that the conformity indexes of the two treatment techniques were also the same. We used the same machine settings as are used in our clinic. Then, we compared the VMAT and HT Pareto fronts using a specific metric (clinical distance measure) and validated the comparison using a blinded expert evaluation of treatment plans on these fronts for all patients in the cohort. Furthermore, we investigated the observed differences between VMAT and HT and pointed out limitations of using Pareto fronts.

RESULTS

Both clinical distance and blind treatment plan comparison showed that VMAT Pareto fronts were better than HT fronts. VMAT fronts for 10 and 6 MV beam energy were almost identical. HT fronts improved with different machine settings, but were still inferior to VMAT fronts.

CONCLUSIONS

That VMAT Pareto fronts are better than HT fronts may be explained by the fact that the linear accelerator can rapidly vary the dose rate. This is an advantage in simple geometries that might vanish in more complex geometries. Furthermore, one should be cautious when speaking about Pareto optimal plans as the best possible plans, as their calculation depends on many parameters.

Influence of optimisation parameters on directly deliverable Pareto fronts explored for prostate cancer

PURPOSE

In inverse radiotherapy treatment planning, the Pareto front is the set of optimal solutions to the multi-criteria problem of adequately irradiating the planning target volume (PTV) while reducing dose to organs at risk (OAR). The Pareto front depends on the chosen optimisation parameters whose influence (clinically relevant versus not clinically relevant) is investigated in this paper.

METHODS

Thirty-one prostate cancer patients treated at our clinic were randomly selected. We developed an in-house Python script that controlled the commercial treatment planning system RayStation to calculate directly deliverable Pareto fronts. We calculated reference Pareto fronts for a given set of objective functions, varying the PTV coverage and the mean dose of the primary OAR (rectum) and fixing the mean doses of the secondary OARs (bladder and femoral heads). We calculated the fronts for different sets of objective functions and different mean doses to secondary OARs. We compared all fronts using a specific metric (clinical distance measure).

RESULTS

The in-house script was validated for directly deliverable Pareto front calculations in two and three dimensions. The Pareto fronts depended on the choice of objective functions and fixed mean doses to secondary OARs, whereas the parameters most influencing the front and leading to clinically relevant differences were the dose gradient around the PTV, the weight of the PTV objective function, and the bladder mean dose.

CONCLUSIONS

Our study suggests that for multi-criteria optimisation of prostate treatments using external therapy, dose gradient around the PTV and bladder mean dose are the most influencial parameters.

Dependence of the AUC of NTCP models on the observational dose-range highlights cautions in comparison of discriminative performance

BACKGROUND

Normal tissue complication probability (NTCP) models are probabilistic models that describe the risk of radio-induced toxicity in tissues or organs. In the field of radiotherapy, the area under the ROC curve (AUC) is widely used to estimate the performance in risk prediction of NTCP models.

METHODS

In this work, we derived an analytical expression of the AUC for the logistic NTCP model in the case of both symmetrical and asymmetrical dose (to the normal tissue) windows around D50. Using numerical simulations, we studied the behavior of the AUC in general clinical settings, enforcing non-logistic NTCP models (Lyman-Kutcher-Burman and LogEUD) and including risk factors beyond the dose. We validated our findings using real-world radiotherapy data sets of prostate cancer patients.

RESULTS

Our analytical expression of the AUC made explicit the dependence on both the steepness of the logistic curve (β) and the dose window width (w), showing that an increase of w pushes AUC towards higher values. Increasing values of the AUC with increasing values of w were consistently observed across simulated data sets with diverse clinical settings from published studies and real clinical data sets.

CONCLUSION

Our results reveal that the AUC of NTCP models inherits intrinsic characteristics from the clinical setting of the data set on which the models are developed, and warn against the use of the AUC to compare the performance of models constructed upon data from trials in which substantially different dose ranges were administered or accounting for different risk factors beyond the dose.

Prediction of toxicity outcomes following radiotherapy using deep learning-based models: A systematic review

PURPOSE

This study aims to perform a comprehensive systematic review of deep learning (DL) models in predicting RT-induced toxicity.

MATERIALS AND METHODS

A literature review was performed following the PRISMA guidelines. Systematic searches were performed in PubMed, Scopus, Cochrane and Embase databases from the earliest record up to September 2022. Related studies on deep learning models for radiotherapy toxicity prediction were selected based on predefined PICOS criteria.

RESULTS

Fourteen studies of radiotherapy-treated patients on different types of cancer [prostate (n=2), HNC (n=4), liver (n=2), lung (n=4), cervical (n=1), and oesophagus (n=1)] were eligible for inclusion in the systematic review. Information regarding patient characteristics and model development was summarized. Several approaches, such as ensemble learning, data augmentation, and transfer learning, that were utilized by selected studies were discussed.

CONCLUSION

Deep learning techniques are able to produce a consistent performance for toxicity prediction. Future research using large and diverse datasets and standardization of the study methodologies are required to improve the consistency of the research output.

Technical note: Investigation of dose and LETd effect to rectum and bladder by using non-straight laterals in prostate cancer receiving proton therapy

BACKGROUND

Parallel-opposed lateral beams are the conventional beam arrangements in proton therapy for prostate cancer. However, when considering linear energy transfer (LET) and RBE effects, alternative beam arrangements should be investigated.

PURPOSE

To investigate the dose and dose averaged LET (LET_d ) impact of using new beam arrangements rotating beams 5°-15° posteriorly to the laterals in prostate cancer treated with pencil-beam-scanning (PBS) proton therapy.

METHODS

Twenty patients with localized prostate cancer were included in this study. Four proton treatment plans for each patient were generated utilizing 0°, 5°, 10°, and 15° posterior oblique beam pairs relative to parallel-opposed lateral beams. Dose-volume histograms (DVHs) from posterior oblique beams were analyzed. Dose-LET_d -volume histogram (DLVH) was employed to study the difference in dose and LET_d with each beam arrangement. DLVH indices, V ( d , l ) $V( {d,l} )$ , defined as the cumulative absolute volume that has a dose of at least d (Gy[RBE]) and a LET_d of at least l (keV/µm), were calculated for both the rectum and bladder to the whole group of patients and two-sub groups with and without hydrogel spacer. These metrics were tested using Wilcoxon signed-rank test.

RESULTS

Rotating beam angles from laterals to slightly posterior by 5°-15° reduced high LET_d volumes while it increased the dose volume in the rectum and increased LET_d in bladders. Beam angles rotated five degrees posteriorly from laterals (i.e., gantry in 95° and 265°) are proposed since they achieved the optimal balance of better LET_d sparing and minimal dose increase in the rectum. A reduction of V(50 Gy[RBE], 2.6 keV/µm) from 7.41 to 3.96 cc (p < 0.01), and a slight increase of V(50 Gy[RBE], 0 keV/µm) from 20.1 to 21.6 cc (p < 0.01) were observed for the group without hydrogel spacer. The LET_d sparing was less effective for the group with hydrogel spacer, which achieved the reduction of V(50 Gy[RBE], 2.6 keV/µm) from 4.28 to 2.10 cc (p < 0.01).

CONCLUSIONS

Posterior oblique angle plans improved LET_d sparing of the rectum while sacrificing LET_d sparing in the bladder in the treatment of prostate cancer with PBS. Beam angle modification from laterals to slightly posterior may be a strategy to redistribute LET_d and perhaps reduce rectal toxicity risks in prostate cancer patients treated with PBS. However, the effect is reduced for patients with hydrogel spacer.

Postoperative adjuvant radiation for cervix cancer: reflections on the evidence and a peep into the future

Early stage cervical cancer, stages IB1–2 and IIA1, can be treated with (chemo)radiation and brachytherapy or radical hysterectomy with or without further adjuvant (chemo)radiation. In a carefully selected cohort for surgery, traditionally a small proportion of patients would need adjuvant (chemo)radiation so that the therapeutic ratio is maximized. However, advances in radiation technology, specifically intensity modulated radiotherapy, have led to a reduction in treatment related adverse events. Also, recent developments in risk stratification suggest using a lower threshold to offer adjuvant treatment to minimize pelvic relapse. These developments together present opportunities of not only re-examining the therapeutic ratio but also of further evolving postoperative risk stratification. This review article summarizes the current evidence on adjuvant treatment strategies and summarizes the key areas where research should be focused.

Normal tissue complication probability models for prospectively scored late rectal and urinary morbidity after proton therapy of prostate cancer

Background and purpose

Photons and protons have fundamentally different properties, i.e. protons have a reduced dose bath but a higher relative biological effectiveness. Photon-based normal tissue complication probability (NTCP) models may therefore not immediately be applicable to proton therapy (PT). The aim was to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively recorded late morbidity data from PT, focusing on rectal morbidity and prostate cancer.

Materials and methods

Prospectively collected data were available for 1151 prostate cancer patients treated with passive scattering PT and prescribed target doses of 78–82 Gy (RBE = 1.1) in 2 Gy fractions. Morbidity data (CTCAE v3.0) consisted of two alternative late grade 2 rectal bleeding endpoints: Medical Grade2A (GR2A) and procedural Grade2B (GR2B), as well as late grade 3 + urinary morbidity. GR2A + 2B were observed in 156/1047 patients (15%), GR2B in 45/1047 patients (4%), and urinary grade 3 + in 51/1151 patients (4%). LKB NTCP model parameters (D50, m, and n) were derived by maximum likelihood estimation.

Results

For the rectum/rectal wall the volume parameter n was low (0.07–0.14) for both GR2A + 2B and GR2B, as was the m parameter (range: 0.16–0.20). For the bladder/bladder wall both parameters were high (n-range: 0.20–0.36; m-range: 0.32–0.36). D50 parameters were higher for GR2B of the rectum/rectal wall (95.9–98.0 Gy) and bladder/bladder wall (118.1–119.9 Gy), but lower for GR2A2B (71.7–73.6 Gy).

Conclusion

PT specific LKB NTCP model parameters were derived from a population of more than 1000 patients. The D50 parameter differed for all structures and endpoints and deviated from typical photon-based LKB model values.

Modelling Radiation-Induced Salivary Dysfunction during IMRT and Chemotherapy for Nasopharyngeal Cancer Patients

BACKGROUND

Radiation-induced xerostomia is one of the most prevalent adverse effects of head and neck cancer treatment, and it could seriously affect patients' qualities of life. It results primarily from damage to the salivary glands, but its onset and severity may also be influenced by other patient-, tumour-, and treatment-related factors. We aimed to build and validate a predictive model for acute salivary dysfunction (aSD) for locally advanced nasopharyngeal carcinoma (NPC) patients by combining clinical and dosimetric factors.

METHODS

A cohort of consecutive NPC patients treated curatively with IMRT and chemotherapy at 70 Gy (2-2.12 Gy/fraction) were utilised. Parotid glands (cPG, considered as a single organ) and the oral cavity (OC) were selected as organs-at-risk. The aSD was assessed at baseline and weekly during RT, grade ≥ 2 aSD chosen as the endpoint. Dose-volume histograms were reduced to the Equivalent Uniform Dose (EUD). Dosimetric and clinical/treatment features selected via LASSO were inserted into a multivariable logistic model. Model validation was performed on two cohorts of patients with prospective aSD, and scored using the same schedule/scale: a cohort (NPC_V) of NPC patients (as in model training), and a cohort of mixed non-NPC head and neck cancer patients (HNC_V).

RESULTS

The model training cohort included 132 patients. Grade ≥ 2 aSD was reported in 90 patients (68.2%). Analyses resulted in a 4-variables model, including doses of up to 98% of cPG (cPG_D98%, OR = 1.04), EUD to OC with n = 0.05 (OR = 1.11), age (OR = 1.08, 5-year interval) and smoking history (OR = 1.37, yes vs. no). Calibration was good. The NPC_V cohort included 38 patients, with aSD scored in 34 patients (89.5%); the HNC_V cohort included 93 patients, 77 with aSD (92.8%). As a general observation, the incidence of aSD was significantly different in the training and validation populations (p = 0.01), thus impairing calibration-in-the-large. At the same time, the effect size for the two dosimetric factors was confirmed. Discrimination was also satisfactory in both cohorts: AUC was 0.73, and 0.68 in NPC_V and HNC_V cohorts, respectively.

CONCLUSION

cPG D98% and the high doses received by small OC volumes were found to have the most impact on grade ≥ 2 acute xerostomia, with age and smoking history acting as a dose-modifying factor. Findings on the development population were confirmed in two prospectively collected validation populations.

Breast cancer patient perspective on opportunities and challenges of a genetic test aimed to predict radio-induced side effects before treatment: Analysis of the Italian branch of the REQUITE project

AIM

To explore breast cancer patient's perspective on future genetic testing for prediction of toxicity after breast radiotherapy (RT).

MATERIALS AND METHODS

The study involved patient enrolled in the Italian branch of the REQUITE project conducted at the National Cancer Institute in Milan. Semi-structured interviews were conducted within one month from the end of radiotherapy treatment by two radiation oncologists and a radiotherapy technician previously trained by a clinical psychologist with experience in the oncology field. Semi-structured interviews are characterized by a set of pre-defined questions and developed ad hoc by researchers in Leicester within the REQUITE project. The interview questions investigated interest in undergoing the genetic test and expectations on its usefulness and disadvantages.

RESULTS

Eighteen interviews were conducted and analysed. Forty-five initial codes were combined into nine themes which were then clustered in two main macro-areas (i) Opportunities and (ii) Challenges. Overall, all patients understand the aim of the genetic test and considered its intrinsic opportunity to make the physician more confident with the treatment. Regarding side effects, most of patients felt prepared to RT but not without fear. Many women considered important to have the largest and reliable information, also about negative experiences. Prevailing emotions were anxiety and fear but not connected to genetic test's result.

CONCLUSIONS

A genetic test could be an opportunity because generate knowledge and give patients a dynamic role in the decision-making approach. Prediction of single patient radiosensitivity before RT could prompt suggestion to entail a more and more tailored radiation treatment in the era of personalized approach.

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.

Radiomic and radiogenomic modeling for radiotherapy: strategies, pitfalls, and challenges

The power of predictive modeling for radiotherapy outcomes has historically been limited by an inability to adequately capture patient-specific variabilities; however, next-generation platforms together with imaging technologies and powerful bioinformatic tools have facilitated strategies and provided optimism. Integrating clinical, biological, imaging, and treatment-specific data for more accurate prediction of tumor control probabilities or risk of radiation-induced side effects are high-dimensional problems whose solutions could have widespread benefits to a diverse patient population-we discuss technical approaches toward this objective. Increasing interest in the above is specifically reflected by the emergence of two nascent fields, which are distinct but complementary: radiogenomics, which broadly seeks to integrate biological risk factors together with treatment and diagnostic information to generate individualized patient risk profiles, and radiomics, which further leverages large-scale imaging correlates and extracted features for the same purpose. We review classical analytical and data-driven approaches for outcomes prediction that serve as antecedents to both radiomic and radiogenomic strategies. Discussion then focuses on uses of conventional and deep machine learning in radiomics. We further consider promising strategies for the harmonization of high-dimensional, heterogeneous multiomics datasets (panomics) and techniques for nonparametric validation of best-fit models. Strategies to overcome common pitfalls that are unique to data-intensive radiomics are also discussed.

External Validation of a Predictive Model for Acute Skin Radiation Toxicity in the REQUITE Breast Cohort

Background: Acute skin toxicity is a common and usually transient side-effect of breast radiotherapy although, if sufficiently severe, it can affect breast cosmesis, aftercare costs and the patient's quality-of-life. The aim of this study was to develop predictive models for acute skin toxicity using published risk factors and externally validate the models in patients recruited into the prospective multi-center REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side-effects and improve QUalITy of lifE in cancer survivors) study.

Methods: Patient and treatment-related risk factors significantly associated with acute breast radiation toxicity on multivariate analysis were identified in the literature. These predictors were used to develop risk models for acute erythema and acute desquamation (skin loss) in three Radiogenomics Consortium cohorts of patients treated by breast-conserving surgery and whole breast external beam radiotherapy (n = 2,031). The models were externally validated in the REQUITE breast cancer cohort (n = 2,057).

Results: The final risk model for acute erythema included BMI, breast size, hypo-fractionation, boost, tamoxifen use and smoking status. This model was validated in REQUITE with moderate discrimination (AUC 0.65), calibration and agreement between predicted and observed toxicity (Brier score 0.17). The risk model for acute desquamation, excluding the predictor tamoxifen use, failed to validate in the REQUITE cohort.

Conclusions: While most published prediction research in the field has focused on model development, this study reports successful external validation of a predictive model using clinical risk factors for acute erythema following radiotherapy after breast-conserving surgery. This model retained discriminatory power but will benefit from further re-calibration. A similar model to predict acute desquamation failed to validate in the REQUITE cohort. Future improvements and more accurate predictions are expected through the addition of genetic markers and application of other modeling and machine learning techniques.

Automated Radiotherapy Planning for Patient-Specific Exploration of the Trade-Off Between Tumor Dose Coverage and Predicted Radiation-Induced Toxicity-A Proof of Principle Study for Prostate Cancer

Background: Currently, radiation-oncologists generally evaluate a single treatment plan for each patient that is possibly adapted by the planner prior to final approval. There is no systematic exploration of patient-specific trade-offs between planning aims, using a set of treatment plans with a-priori defined (slightly) different balances. To this purpose, we developed an automated workflow and explored its use for prostate cancer. Materials and Methods: For each of the 50 study patients, seven plans were generated, including the so-called clinical plan, with currently clinically desired ≥99% dose coverage for the low-dose planning target volume (PTVLow). The six other plans were generated with different, reduced levels of PTVLow coverage, aiming at reductions in rectum dose and consequently in predicted grade≥2 late gastro-intestinal (GI) normal tissue complication probabilities (NTCPs), while keeping other dosimetric differences small. The applied NTCP model included diabetes as a non-dosimetric predictor. All plans were generated with a clinically applied, in-house developed algorithm for automated multi-criterial plan generation. Results: With diabetes, the average NTCP reduced from 24.9 ± 4.5% for ≥99% PTVLow coverage to 17.3 ± 2.6% for 90%, approaching the NTCP (15.4 ± 3.0%) without diabetes and full PTVLow coverage. Apart from intended differences in PTVLow coverage and rectum dose, other differences between the clinical plan and the six alternatives were indeed minor. Obtained NTCP reductions were highly patient-specific (ranging from 14.4 to 0.1%), depending on patient anatomy. Even for patients with equal NTCPs in the clinical plan, large differences were found in NTCP reductions. Conclusions: A clinically feasible workflow has been proposed for systematic exploration of patient-specific trade-offs between various treatment aims. For each patient, automated planning is used to generate a limited set of treatment plans with well-defined variations in the balances between the aims. For prostate cancer, trade-offs between PTVLow coverage and predicted GI NTCP were explored. With relatively small coverage reductions, significant NTCP reductions could be obtained, strongly depending on patient anatomy. Coverage reductions could also make up for enhanced NTCPs related to diabetes as co-morbidity, again dependent on the patient. The proposed system can play an important role in further personalization of patient care.

Dosimetric comparison of artificial walls of bladder and rectum with real walls in common prostate IMRT techniques: Patient and Monte Carlo study

BACKGROUND

Rectum and bladder are hallow structures and considered as critical organs in prostate cancer intensity modulated radiotherapy (IMRT). Therefore, dose received by these organ walls must be considered for prediction of radiobiological effects. Contouring the real organ walls is quite difficult and time consuming in CT/MRI images, so the easy contouring artificial walls with uniform thickness could be appropriated alternatives.

OBJECTIVE

To compare reconstructed artificial walls with real walls of bladder and rectum in common prostate IMRT techniques based on dose volume-histograms (DVHs) derived from artificial and real walls.

METHODS

Artificial walls were reconstructed with 2-10 mm and 2-8 mm thicknesses for bladder and rectum, respectively. Four common IMRT techniques were applied to each patient. Spearman correlation was used to find the relation between the DVHs of true walls with artificial walls and whole organs. Monte Carlo (MC) simulations of the IMRT techniques and dosimetric comparison were also performed on a standard patient data.

RESULTS

The 2 mm thickness artificial walls showed the minimum differences with the true bladder and rectum walls based on absolute evaluations (the maximum difference < 10cc and standard deviation < 15cc). However, relative evaluations showed that all the artificial walls had high correlations with real walls for selecting dose volume parameters. There was also good agreement between the treatment planning system and MC simulations results.

CONCLUSION

The DVH of whole organs was not a good surrogate of the true wall. The 2 mm artificial walls can be regarded as good alternatives for both of rectum and bladder. However, in relative dose evaluations all studied artificial walls were appropriate.

Evaluating the predictive value of quantec rectum tolerance dose suggestions on acute rectal toxicity in prostate carcinoma patients treated with IMRT

Aim

To investigate the predictive value of convenience of rectum dosimetry with Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) dose limits, maximum rectum dose (Dmax), total rectal volume (TVrectum), rectal volume included in PTV (VrectumPTV) on Grade 2-3 acute rectal toxicity for utilization in clinical practice.

Background

Numerous previous data have reported frequent acute proctitis after external-beam RT of prostate cancer. Predicting toxicity limited with dose information is inadequate in clinical practice due to comorbidities and medications used.

Materials and Method

Sixty-four non-metastatic prostate cancer patients treated with IMRT were enrolled. Patients were treated to a total dose of 70-76 Gy. Rectal dose volume histograms (DVH) of all patients were evaluated retrospectively, and a QUANTEC Score between 0 and 5 was calculated for each patient. The correlation between the rectal DVH data, QUANTEC score, TVrectum, VrectumPTV, rectum Dmax and Grade 2-3 rectal toxicity was investigated.

Results

In the whole group grade 1, 2 and 3 acute rectal toxicities were 25%, 18.8% and 3.1%, respectively. In the DVH data, rectum doses of all patients were under RTOG dose limits. Statistically significant correlation was found between grade 2-3 rectal toxicity and TVrectum (p = 0,043); however. It was not correlated with QUANTEC score, VrectumPTV and Dmax.

Conclusion

Our results were not able to show any significant correlation between increasing convenience with QUANTEC limits and lower rectal toxicity. Conclusively, new dosimetric definitions are warranted to predict acute rectal toxicity more accurately in prostate cancer patients during IMRT treatment.

Patterns in ano-rectal dose maps and the risk of late toxicity after prostate IMRT

Purpose: The aim of this work was to determine how the spatial pattern of dose in the ano-rectal wall is related to late gastro-intestinal toxicity for prostate cancer patients treated with mainly IMRT.Patients and methods: Patients from the DUE-01 multicentre study with patient-reported (prospective) follow-up and available dosimetric data were included. Conventionally fractionated patients received 74-80 Gy and hypofractionated patients received 65-75.2 Gy. A large majority of the patients were treated with intensity-modulated radiotherapy (IMRT). Dose-surface maps (DSMs) for the anal canal and rectum as a single structure, and for the anal canal and the rectum separately, were co-registered rigidly in two dimensions and, for the patients with and without toxicity, respectively, the mean value of the dose in each pixel was calculated. A pixel-wise t-test was used to highlight the anatomical areas where there was a significant difference between the 'mean dose maps' of each group. Univariate models were also fitted to a range of spatial parameters. The endpoints considered were a mean grade ≥1 late fecal incontinence and a maximum grade ≥2 late rectal bleeding.Results: Twenty-six out of 213 patients had fecal incontinence, while 21/225 patients had rectal bleeding. Incontinence was associated with a higher dose in the caudal region of the anal canal; the most relevant spatial parameter was the lateral extent of the low and medium isodoses (5-49 Gy in EQD2). Bleeding was associated with high isodoses reaching the posterior rectal wall. The spatial dose parameters with the highest AUC value (.69) were the lateral extent of the 60-70 Gy isodoses.Conclusions: To avoid fecal incontinence it is important to limit the portion of the anal canal irradiated. Our analysis confirms that rectal bleeding is a function of similar spatial dose parameters for patients treated with IMRT, compared to previous studies on patients treated with three-dimensional conformal radiotherapy.

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

PURPOSE

REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data.

METHODS

An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated.

RESULTS

The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician- (47,025 forms) and patient- (54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade ≥2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung).

CONCLUSION

The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers.

PATIENT SUMMARY

Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short- and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity.

Normal tissue complication probability (NTCP) models for modern radiation therapy

Mathematical models of normal tissue complication probability (NTCP) able to robustly predict radiation-induced morbidities (RIM) play an essential role in the identification of a personalized optimal plan, and represent the key to maximizing the benefits of technological advances in radiation therapy (RT). Most modern RT techniques pose, however, new challenges in estimating the risk of RIM. The aim of this report is to schematically review NTCP models in the framework of advanced radiation therapy techniques. Issues relevant to hypofractionated stereotactic body RT and ion beam therapy are critically reviewed. Reirradiation scenarios for new or recurrent malignances and NTCP are also illustrated. A new phenomenological approach to predict RIM is suggested.

Developing a multivariable normal tissue complication probability model to predict late rectal bleeding following intensity-modulated radiation therapy

Purpose: To develop a multivariable normal tissue complication probability (NTCP) model to predict moderate to severe late rectal bleeding following intensity-modulated radiation therapy (IMRT).

Methods and materials: Sixty-eight patients with localized prostate cancer treated by IMRT from 2008 to 2011 were enrolled. The median follow-up time was 56 months. According to the criteria of D'Amico risk classifications, there were 9, 20 and 39 patients in low, intermediate and high-risk groups, respectively. Forty-two patients were combined with androgen deprivation therapy. Fifteen patients had suffered from grade 2 or more (grade 2+) late rectal bleeding. The numbers of predictors for a multivariable logistic regression NTCP model were determined by the least absolute shrinkage and selection operator (LASSO).

Results: The most important predictors for late rectal bleeding ranked by LASSO were platelet count, risk group and the relative volume of rectum receiving at least 65 Gy (V₆₅). The NTCP model of grade 2+ rectal bleeding was as follows: S = -17.49 + Platelets (1000/μL) * (-0.025) + Risk group * Corresponding coefficient (low-risk group = 0; intermediate-risk group = 19.07; high-risk group = 20.41) + V₆₅ * 0.045.

Conclusions: A LASSO-based multivariable NTCP model comprising three important predictors (platelet count, risk group and V₆₅) was established to predict the incidence of grade 2+ late rectal bleeding after IMRT.

Dosimetry and Gastrointestinal Toxicity Relationships in a Phase II Trial of Pelvic Lymph Node Radiotherapy in Advanced Localised Prostate Cancer

AIMS

Pelvic lymph node (PLN) radiotherapy for high-risk prostate cancer is limited by late gastrointestinal toxicity. Application of rectal and bowel constraints may reduce risks of side-effects. We evaluated associations between intensity-modulated radiotherapy (IMRT) dose-volume data and long-term gastrointestinal toxicity.

MATERIALS AND METHODS

Data from a single-centre dose-escalation trial of PLN-IMRT were analysed, including conventionally fractionated (CFRT) and hypofractionated (HFRT) radiotherapy schedules. Associations between volumes of rectum and bowel receiving specified doses and clinician- and patient-reported toxicity outcomes were investigated independently. A metric, δ median (δM), was defined as the difference in the medians of a volume between groups with and without toxicity at a specified dose and was used to test for statistically significant differences.

RESULTS

Constraints were respected in most patients and, when exceeded, led to higher rates of gastrointestinal toxicity. Biologically relevant associations between rectum dose-points and toxicity were more numerous with both mild and moderate toxicity thresholds, but statistical significance was limited after correction for false discovery rate. Rectal V50Gy (CFRT) associated with grade 2+ bleeding; bowel V43Gy and V47 (HFRT/4 days/week schedule) associated with patient-reported loose stools and diarrhoea, respectively. Further investigation showed that CFRT patients with rectal bleeding had a mean rectal V50Gy above the treatment planning constraint.

CONCLUSIONS

When dose-volume parameters are kept below tight constraints, toxicity is low. Residual dosimetry loses much of its predictive power for gastrointestinal toxicity in the setting of PLN-IMRT for prostate cancer. We have benchmarked dose-volume constraints for safely delivering PLN-IMRT using CFRT or HFRT.

Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma

PURPOSE

To develop normal tissue complications (NTCP) models for hepatocellular cancer (HCC) patients who undergo liver radiation therapy (RT) and to evaluate the potential role of functional imaging and measurement of blood-based circulating biological markers before and during RT to improve the performance of these models.

METHODS AND MATERIALS

The data from 192 HCC patients who had undergone RT from 2005 to 2014 were evaluated. Of the 192 patients, 146 had received stereotactic body RT (SBRT) and 46 had received conventional RT to a median physical tumor dose of 49.8 Gy and 50.4 Gy, respectively. The physical doses were converted into 2-Gy equivalents for analysis. Two approaches were investigated for modeling NTCP: (1) a generalized Lyman-Kutcher-Burman model; and (2) a generalization of the parallel architecture model. Three clinical endpoints were considered: the change in albumin-bilirubin (ALBI), change in Child-Pugh (C-P) score, and grade ≥3 liver enzymatic changes. Local dynamic contrast-enhanced magnetic resonance imaging portal venous perfusion information was used as an imaging biomarker for local liver function. Four candidate inflammatory cytokines were considered as biological markers. The imaging findings and cytokine levels were incorporated into NTCP modeling, and their role was evaluated using goodness-of-fit metrics.

RESULTS

Using dosimetric information only, the Lyman-Kutcher-Burman model for the ALBI/C-P change had a steeper response curve compared with grade ≥3 enzymatic changes. Incorporating portal venous perfusion imaging information into the parallel architecture model to represent functional reserve resulted in relatively steeper dose-response curves compared with dose-only models. A larger loss of perfusion function was needed for enzymatic changes compared with ALBI/C-P changes. Increased transforming growth factor-β1 and eotaxin expression increased the trend of expected risk in both NTCP modeling approaches but did not reach statistical significance.

CONCLUSIONS

The incorporation of imaging findings and biological markers into NTCP modeling of liver toxicity improved the estimates of expected NTCP risk compared with using dose-only models. In addition, such generalized NTCP models should contribute to a better understanding of the normal tissue response in HCC SBRT patients and facilitate personalized treatment.

Predicting Late Fecal Incontinence Risk After Radiation Therapy for Prostate Cancer: New Insights From External Independent Validation

PURPOSE

This study aimed to validate a previously published predictive model for late fecal incontinence (FI) in a contemporary population of prostate cancer patients treated with radical radiation therapy.

METHODS AND MATERIALS

The validation included patients treated with intensity-modulated radiation therapy (IMRT) (2010-2014). Prescribed dose range was 65-80 Gy, including conventional and moderate hypo-fractionated treatments. Rectal toxicity was scored using LENT/SOMA, a minimum 2-year follow up was considered. We chose to validate the model published by Rancati et al for predicting chronic FI, developed on a 3-dimensional conformal radiation therapy (3DCRT) population. It considered a longitudinal endpoint defined as the average toxicity grade during the follow up. This continuous endpoint was dichotomized using a cut-off value of mean FI grade >1. The model included mean rectal dose (Dmean), previous diseases of the colon (COLO) and previous abdominal surgery (SURG). Doses were corrected to 2 Gy/fraction using the linear-quadratic model and applying alpha/beta ratio = 4.8 Gy.

RESULTS

228 patients constituted the validation population. A mean FI grade >1 was scored in 25 patients (11%). Logistic regression confirmed risk factors reported in the literature, with similar odds ratios (ORs) for Dmean (1.04 ± 0.03 vs 1.06 ± 0.04) and SURG (1.9 ± 1.7 vs 1.6 ± 1.45); COLO was not confirmed. Consequently, the predictive models including Dmean/Dmean + SURG were evaluated using calibration plots. Both showed a clear discriminative trend, but the absolute observed toxicity rates were underestimated (ie, absolute predicted rates were always lower than corresponding absolute observed rates). This result was consistent with an unexpected effect of hypofractionation (OR = 2.20, conventional = 8.1% vs hypofractionated = 17.4%) beyond the standard correction using linear-quadratic model. Nevertheless, the FI rate in the conventionally treated group was almost double the rate observed in the previously studied cohort (4.3% vs 8.1%).

CONCLUSIONS

The study confirms previously published results indicating that abdominal surgery and rectal mean dose are risk factors for late FI. Calibration plots highlight a possible role of hypofractionation beyond linear-quadratic correction.

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling

PURPOSE

To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort.

METHODS AND MATERIALS

Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated.

RESULTS

The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05).

CONCLUSIONS

The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP modeling.

Late toxicity in the randomized multicenter HYPRO trial for prostate cancer analyzed with automated treatment planning

PURPOSE/OBJECTIVE

Assess to what extent the use of automated treatment planning would have reduced organ-at-risk dose delivery observed in the randomized HYPRO trial for prostate cancer, and estimate related toxicity reductions. Investigate to what extent improved plan quality for hypofractionation scheme as achieved with automated planning can potentially reduce observed enhanced toxicity for the investigated hypofractionation scheme to levels observed for conventional fractionation scheme.

MATERIAL/METHODS

For 725 trial patients, VMAT plans were generated with an algorithm for automated multi-criterial plan generation (autoVMAT). All clinically delivered plans (CLINICAL), generated with commonly applied interactive trial-and-error planning were also available for the investigations. Analyses were based on dose-volume histograms (DVH) and predicted normal tissue complication probabilities (NTCP) for late gastrointestinal (GI) toxicity.

RESULTS

Compared to CLINICAL, autoVMAT plans had similar or higher PTV coverage, while large and statistically significant OAR sparing was achieved. Mean doses in the rectum, anus and bladder were reduced by 7.8 ± 4.7 Gy, 7.9 ± 6.0 Gy and 4.2 ± 2.9 Gy, respectively (p < 0.001). NTCPs for late grade ≥2 GI toxicity, rectal bleeding and stool incontinence were reduced from 23.3 ± 9.1% to 19.7 ± 8.9%, from 9.7 ± 2.8% to 8.2 ± 2.8%, and from 16.8 ± 8.5% to 13.1 ± 7.2%, respectively (p < 0.001). Reductions in rectal bleeding NTCP were observed for all published Equivalent Uniform Dose volume parameters, n. AutoVMAT allowed hypofractionation with predicted toxicity similar to conventional fractionation with CLINICAL plans.

CONCLUSION

Compared to CLINICAL, autoVMAT had superior plan quality, with meaningful NTCP reductions for both conventional fractionation and hypofractionation schemes. AutoVMAT plans might reduce toxicity for hypofractionation to levels that were clinically observed (and accepted) for conventional fractionation. This may be relevant when considering clinical use of the investigated hypofractionation schedule with relatively high fraction dose (3.4 Gy).

Prostate Cancer Patients with Late Radiation Toxicity Exhibit Reduced Expression of Genes Involved in DNA Double-Strand Break Repair and Homologous Recombination

Severe late damage to normal tissue is a major limitation of cancer radiotherapy in prostate cancer patients. In a recent retrospective study, late radiation toxicity was found to relate to a decreased decay of γ-H2AX foci and reduced induction of DNA double-strand break repair genes. Here, we report evidence of prognostic utility in prostate cancer for γ-H2AX foci decay ratios and gene expression profiles derived from ex vivo-irradiated patient lymphocytes. Patients were followed ≥2 years after radiotherapy. Clinical characteristics were assembled, and toxicity was recorded using the Common Terminology Criteria (CTCAE) v4.0. No clinical factor was correlated with late radiation toxicity. The γ-H2AX foci decay ratio correlated negatively with toxicity grade, with a significant difference between grade ≥3 and grade 0 patients (P = 0.02). A threshold foci decay ratio, determined in our retrospective study, correctly classified 23 of 28 patients with grade ≥3 toxicity (sensitivity 82%) and 9 of 14 patients with grade 0 toxicity (specificity 64%). Induction of homologous recombination (HR) repair genes was reduced with increasing toxicity grade. The difference in fold induction of the HR gene set was most pronounced between grade 0 and grade ≥3 toxicity (P = 0.008). Notably, reduced responsiveness of HR repair genes to irradiation and inefficient double-strand break repair correlated with severe late radiation toxicity. Using a decay ratio classifier, we correctly classified 82% of patients with grade ≥3 toxicity, suggesting a prognostic biomarker for cancer patients with a genetically enhanced risk for late radiation toxicity to normal tissues after radiotherapy. Cancer Res; 77(6); 1485-91. ©2017 AACR.

Influence of daily imaging on plan quality and normal tissue toxicity for prostate cancer radiotherapy

Background

Modern radiotherapy offers various possibilities for image guided verification of patient positioning. Different clinically relevant IGRT (image guided radiotherapy) scenarios were considered with regard to their influence on dosimetric plan quality and normal tissue complication probability (NTCP).

Methods

This study is based on treatment plans of 50 prostate patients. We evaluate the clinically performed IGRT and simulate the influence of different daily IGRT scenarios on plan quality. Imaging doses of planar and cone-beam-CT (CBCT) images for three different energies (6 MV, 1 MV and 121 kV) were added to the treatment plans. The plan quality of the different scenarios was assessed by a visual inspection of the dose distribution and dose-volume-histogram (DVH) and a statistical analysis of DVH criteria. In addition, an assessment of the normal tissue complication probability was performed.

Results

Daily 1MV-CBCTs result in undesirable high dose regions in the target volume. The DVH shows that the scenarios with actual imaging performed, daily kV-CBCT and daily 6MV imaging (1x CBCT, 4x planar images per week) do not differ exceedingly from the original plan; especially imaging with daily kV-CBCT has little influence to the sparing of organs at risk. In contrast, daily 1MV- CBCT entails an additional dose of up to two fraction doses. Due to the additional dose amount some DVH constraints for plan acceptability could no longer be satisfied, especially for the daily 1MV-CBCT scenario. This scenario also shows increased NTCP for the rectum.

Conclusion

Daily kV-CBCT has negligible influence on plan quality and is commendable for the clinical routine. If no kV-modality is available, a daily IGRT scenario with one CBCT per week and planar axial images on the other days should be preferred over daily MV-CBCT.

Modelling late stool frequency and rectal pain after radical radiotherapy in prostate cancer patients: Results from a large pooled population

AIM

To investigate late gastrointestinal toxicity in a large pooled population of prostate cancer patients treated with radical radiotherapy. Normal tissue complication probability models were developed for late stool frequency and late rectal pain.

METHODS AND MATERIALS

Population included 1336 patients, 3-year minimum follow-up, treated with 66-80Gy. Toxicity was scored with LENT-SOMA-scale. Two toxicity endpoints were considered: grade ⩾2 rectal pain and mean grade (average score during follow-up) in stool frequency >1. DVHs of anorectum were reduced to equivalent uniform dose (EUD). The best-value of the volume parameter n was determined through numerical optimization. Association between EUD/clinical factors and the endpoints was investigated by logistic analyses. Likelihood, Brier-score and calibration were used to evaluate models. External calibration was also carried out.

RESULTS

4% of patients (45/1122) reported mean stool frequency grade >1; grade ⩾2 rectal pain was present in the TROG 03.04 RADAR population only (21/677, 3.1%): for this endpoint, the analysis was limited to this population. Analysis of DVHs highlighted the importance of mid-range doses (30-50Gy) for both endpoints. EUDs calculated with n=1 (OR=1.04) and n=0.35 (OR=1.06) were the most suitable dosimetric descriptors for stool frequency and rectal pain respectively. The final models included EUD and cardiovascular diseases (OR=1.78) for stool frequency and EUD and presence of acute gastrointestinal toxicity (OR=4.2) for rectal pain.

CONCLUSION

Best predictors of stool frequency and rectal pain are consistent with findings previously reported for late faecal incontinence, indicating an important role in optimization of mid-range dose region to minimize these symptoms highly impacting the quality-of-life of long surviving patients.

Big Data Analytics for Prostate Radiotherapy

Radiation therapy is a first-line treatment option for localized prostate cancer and radiation-induced normal tissue damage are often the main limiting factor for modern radiotherapy regimens. Conversely, under-dosing of target volumes in an attempt to spare adjacent healthy tissues limits the likelihood of achieving local, long-term control. Thus, the ability to generate personalized data-driven risk profiles for radiotherapy outcomes would provide valuable prognostic information to help guide both clinicians and patients alike. Big data applied to radiation oncology promises to deliver better understanding of outcomes by harvesting and integrating heterogeneous data types, including patient-specific clinical parameters, treatment-related dose-volume metrics, and biological risk factors. When taken together, such variables make up the basis for a multi-dimensional space (the "RadoncSpace") in which the presented modeling techniques search in order to identify significant predictors. Herein, we review outcome modeling and big data-mining techniques for both tumor control and radiotherapy-induced normal tissue effects. We apply many of the presented modeling approaches onto a cohort of hypofractionated prostate cancer patients taking into account different data types and a large heterogeneous mix of physical and biological parameters. Cross-validation techniques are also reviewed for the refinement of the proposed framework architecture and checking individual model performance. We conclude by considering advanced modeling techniques that borrow concepts from big data analytics, such as machine learning and artificial intelligence, before discussing the potential future impact of systems radiobiology approaches.

Predicting toxicity in radiotherapy for prostate cancer

This comprehensive review addresses most organs at risk involved in planning optimization for prostate cancer. It can be considered an update of a previous educational review that was published in 2009 (Fiorino et al., 2009). The literature was reviewed based on PubMed and MEDLINE database searches (from January 2009 up to September 2015), including papers in press; for each section/subsection, key title words were used and possibly combined with other more general key-words (such as radiotherapy, dose-volume effects, NTCP, DVH, and predictive model). Publications generally dealing with toxicity without any association with dose-volume effects or correlations with clinical risk factors were disregarded, being outside the aim of the review. A focus was on external beam radiotherapy, including post-prostatectomy, with conventional fractionation or moderate hypofractionation (<4Gy/fraction); extreme hypofractionation is the topic of another paper in this special issue. Gastrointestinal and urinary toxicity are the most investigated endpoints, with quantitative data published in the last 5years suggesting both a dose-response relationship and the existence of a number of clinical/patient related risk factors acting as dose-response modifiers. Some results on erectile dysfunction, bowel toxicity and hematological toxicity are also presented.

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.

Prediction of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancer

Background

Gastrointestinal (GI) toxicity is a common effect following radiation therapy (RT) for prostate cancer. Purpose of the present work is to compare two Normal Tissue Complication Probability (NTCP) modelling approaches for prediction of late radio-induced GI toxicity after prostate external beam radiotherapy.

Methods

The study includes 84 prostate cancer patients evaluated for late rectal toxicity after 3D conformal radiotherapy. Median age was 72 years (range 53-85). All patients received a total dose of 76 Gy to the prostate gland with daily fractions of 2 Gy. The acute and late radio-induced GI complications were classified according to the RTOG/EORTC scoring system. Rectum dose-volume histograms were extracted for Lyman-Kutcher-Burman (LKB) NTCP model fitting using Maximum Likelihood Estimation. The bootstrap method was employed to test the fit robustness. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive power of the LKB and to compare it with a multivariate logistic NTCP model previously determined.

Results

At a median follow-up of 36 months, 42% (35/84) of patients experienced grade 1-2 (G1-2) acute GI events while 25% (21/84) of patients developed G1-2 late GI events. The best-estimate of fitting parameters for LKB NTCP model for mild\moderate GI toxicity resulted to be: D₅₀ = 87.3 Gy, m = 0.37 and n = 0.10. Bootstrap result showed that the parameter fit was robust. The AUC values for the LKB and for the multivariate logistic models were 0.60 and 0.75, respectively.

Conclusions

We derived the parameters of the LKB model for mild\moderate GI toxicity prediction and we compared its performance with that of a data-driven multivariate model. Compared to LKB, the multivariate model confirmed a higher predictive power as showed by the AUC values.

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.

On feature extraction and classification in prostate cancer radiotherapy using tensor decompositions

External beam radiotherapy is commonly prescribed for prostate cancer. Although new radiation techniques allow high doses to be delivered to the target, the surrounding healthy organs (rectum and bladder) may suffer from irradiation, which might produce undesirable side-effects. Hence, the understanding of the complex toxicity dose-volume effect relationships is crucial to adapt the treatment, thereby decreasing the risk of toxicity. In this paper, we introduce a novel method to classify patients at risk of presenting rectal bleeding based on a Deterministic Multi-way Analysis (DMA) of three-dimensional planned dose distributions across a population. After a non-rigid spatial alignment of the anatomies applied to the dose distributions, the proposed method seeks for two bases of vectors representing bleeding and non bleeding patients by using the Canonical Polyadic (CP) decomposition of two fourth order arrays of the planned doses. A patient is then classified according to its distance to the subspaces spanned by both bases. A total of 99 patients treated for prostate cancer were used to analyze and test the performance of the proposed approach, named CP-DMA, in a leave-one-out cross validation scheme. Results were compared with supervised (linear discriminant analysis, support vector machine, K-means, K-nearest neighbor) and unsupervised (recent principal component analysis-based algorithm, and multidimensional classification method) approaches based on the registered dose distribution. Moreover, CP-DMA was also compared with the Normal Tissue Complication Probability (NTCP) model. The CP-DMA method allowed rectal bleeding patients to be classified with good specificity and sensitivity values, outperforming the classical approaches.

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.

Reduced activity of double-strand break repair genes in prostate cancer patients with late normal tissue radiation toxicity

PURPOSE

To investigate clinical parameters and DNA damage response as possible risk factors for radiation toxicity in the setting of prostate cancer.

METHODS AND MATERIALS

Clinical parameters of 61 prostate cancer patients, 34 with (overresponding, OR) and 27 without (non-responding, NR) severe late radiation toxicity were assembled. In addition, for a matched subset the DNA damage repair kinetics (γ-H2AX assay) and expression profiles of DNA repair genes were determined in ex vivo irradiated lymphocytes.

RESULTS

Examination of clinical data indicated none of the considered clinical parameters to be correlated with the susceptibility of patients to develop late radiation toxicity. Although frequencies of γ-H2AX foci induced immediately after irradiation were similar (P=.32), significantly higher numbers of γ-H2AX foci were found 24 hours after irradiation in OR compared with NR patients (P=.03). Patient-specific γ-H2AX foci decay ratios were significantly higher in NR patients than in OR patients (P<.0001). Consequently, NR patients seem to repair DNA double-strand breaks (DSBs) more efficiently than OR patients. Moreover, gene expression analysis indicated several genes of the homologous recombination pathway to be stronger induced in NR compared with OR patients (P<.05). A similar trend was observed in genes of the nonhomologous end-joining repair pathway (P=.09). This is congruent with more proficient repair of DNA DSBs in patients without late radiation toxicity.

CONCLUSIONS

Both gene expression profiling and DNA DSB repair kinetics data imply that less-efficient repair of radiation-induced DSBs may contribute to the development of late normal tissue damage. Induction levels of DSB repair genes (eg, RAD51) may potentially be used to assess the risk for late radiation toxicity.

Long term rectal function after high-dose prostatecancer radiotherapy: results from a prospective cohort study

PURPOSE

To prospectively evaluate long-term late rectal bleeding (lrb) and faecal incontinence (linc) after high-dose radiotherapy (RT) for prostate cancer in the AIROPROS 0102 population, and to assess clinical/dosimetric risk factors.

MATERIALS AND METHODS

Questionnaires of 515 patients with G0 baseline incontinence and bleeding scores (follow-up ≥6 years) were analysed. Correlations between lrb/linc and many clinical and dosimetric parameters were investigated by univariate and multivariate logistic analyses. The correlation between lrb/linc and symptoms during the first 3 years after RT was also investigated.

RESULTS

Of 515 patients lrb G1, G2 and G3 was found in 32 (6.1%), 2 (0.4%) and 3 (0.6%) patients while linc G1, G2 and G3 was detected in 50 (9.7%), 3 (0.6%) and 3 (0.6%), respectively. The prevalence of G2-G3 lrb events was significantly reduced compared to the first 3-years (1% vs 2.7%, p=0.016) ≥G1 lrb was significantly associated with V75 Gy (OR=1.07). In multivariate analysis, ≥G1 linc was associated with V40 Gy (OR=1.015), use of antihypertensive medication (OR=0.38), abdominal surgery before RT (OR=4.7), haemorrhoids (OR=2.6), and G2-G3 acute faecal incontinence (OR=4.4), a nomogram to predict the risk of long-term ≥G1 linc was proposed. Importantly, the prevalence of ≥G1 linc was significantly correlated with the mean incontinence score during the first 3 years after RT (OR=16.3).

CONCLUSIONS

Long-term (median: 7 years) rectal symptoms are prevalently mild and strongly correlated with moderate/severe events occurring in the first 3 years after RT. Linc was associated with several risk factors.

Reducing rectal injury during external beam radiotherapy for prostate cancer

Rectal bleeding and faecal incontinence are serious injuries that men with prostate cancer who receive radiotherapy can experience. Although technical advances--including the use of intensity-modulated radiotherapy coupled with image-guided radiotherapy--have enabled the delivery of dose distributions that conform to the shape of the tumour target with steep dose gradients that reduce the dose given to surrounding tissues, radiotherapy-associated toxicity can not be avoided completely. Many large-scale prospective studies have analysed the correlations of patient-related and treatment-related parameters with acute and late toxicity to optimize patient selection and treatment planning. The careful application of dose-volume constraints and the tuning of these constraints to the individual patient's characteristics are now considered the most effective ways of reducing rectal morbidity. Additionally, the use of endorectal balloons (to reduce the margins between the clinical target volume and planning target volume) and the insertion of tissue spacers into the region between the prostate and anterior rectal wall have been investigated as means to further reduce late rectal injury. Finally, some drugs and other compounds are also being considered to help protect healthy tissue. Overall, a number of approaches exist that must be fully explored in large prospective trials to address the important issue of rectal toxicity in prostate cancer radiotherapy.

Patient-reported outcomes after 3-dimensional conformal, intensity-modulated, or proton beam radiotherapy for localized prostate cancer

BACKGROUND

Recent studies have suggested differing toxicity patterns for patients with prostate cancer who receive treatment with 3-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiotherapy (IMRT), or proton beam therapy (PBT).

METHODS

The authors reviewed patient-reported outcomes data collected prospectively using validated instruments that assessed bowel and urinary quality of life (QOL) for patients with localized prostate cancer who received 3DCRT (n = 123), IMRT (n = 153) or PBT (n = 95). Clinically meaningful differences in mean QOL scores were defined as those exceeding half the standard deviation of the baseline mean value. Changes from baseline were compared within groups at the first post-treatment follow-up (2-3 months from the start of treatment) and at 12 months and 24 months.

RESULTS

At the first post-treatment follow-up, patients who received 3DCRT and IMRT, but not those who received PBT, reported a clinically meaningful decrement in bowel QOL. At 12 months and 24 months, all 3 cohorts reported clinically meaningful decrements in bowel QOL. Patients who received IMRT reported clinically meaningful decrements in the domains of urinary irritation/obstruction and incontinence at the first post-treatment follow-up. At 12 months, patients who received PBT, but not those who received IMRT or 3DCRT, reported a clinically meaningful decrement in the urinary irritation/obstruction domain. At 24 months, none of the 3 cohorts reported clinically meaningful changes in urinary QOL.

CONCLUSIONS

Patients who received 3DCRT, IMRT, or PBT reported distinct patterns of treatment-related QOL. Although the timing of toxicity varied between the cohorts, patients reported similar modest QOL decrements in the bowel domain and minimal QOL decrements in the urinary domains at 24 months. Prospective randomized trials are needed to further examine these differences.

Spacer stability and prostate position variability during radiotherapy for prostate cancer applying a hydrogel to protect the rectal wall

BACKGROUND AND PURPOSE

The aim was to evaluate the spacer dimensions and prostate position variability during the course of radiotherapy for prostate cancer.

MATERIALS AND METHODS

CT scans were performed in a group of 15 patients (G1) after the 10 ml injection of a hydrogel spacer (SpaceOAR™) and 30 patients without a spacer (G2) before the beginning of treatment (CT1) and in the last treatment week, 10-12 weeks following spacer implantation (CT2). Spacer dimensions and displacements were determined and prostate displacements compared.

RESULTS

Mean volume of the hydrogel increased slightly (17%; p<0.01), in 4 of 15 patients >2 cm(3). The average displacement of the hydrogel center of mass was 0.6mm (87%≤ 2.2mm), -0.6mm (100% ≤ 2.2mm) and 1.4mm (87% ≤ 4.3mm) in the x-, y- and z-axes (not significant). The average distance between prostate and anterior rectal wall before/at the end of radiotherapy was 1.6 cm/1.5 cm, 1.2 cm/1.3 cm and 1.0 cm/1.1cm at the level of the base, middle and apex (G1). Prostate position variations were similar comparing G1 and G2, but significant systematic posterior displacements were only found in G2.

CONCLUSIONS

A stable distance between the prostate and anterior rectal wall results during the radiotherapy course after injection of the spacer before treatment planning. Larger posterior prostate displacements could be reduced.