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Using Bayesian logistic regression to evaluate a new type of dosimetric constraint for prostate radiotherapy treatment planning
Abstract
Modern radiotherapy treatments can be optimized using dose-volume constraints which specify the volume of tumor and organs-at-risk receiving a given threshold dose. Careful derivation and evaluation of rectal constraints is essential to allow safe dose escalation in radiotherapy of prostate cancer. The authors present a new type of hybrid dosimetric constraint which comprises both volumetric and spatial factors of the dose-distribution. The authors also propose a framework to evaluate these constraints.
The authors used data from the RT01 prostate radiotherapy trial (ISRCTN 47772397) to derive this set of hybrid constraints for the rectum based on measures extracted from dose-surface maps. For comparison, the authors also derive a set of dose-volume constraints. In order to evaluate these dosimetric constraints, the authors propose a new framework for predicting radiation-induced toxicities using Bayesian logistic regression with high-order interactions. The predictive power of the new RT01-based constraints, as well as of two sets of rectal dose-volume constraints proposed in the recent literature-The constraints proposed by other researchers [C. Fiorino, G. Fellin, T. Rancati, V. Vavassori, C. Bianchi, V. C. Borca, G. Girelli, M. Mapelli, L. Menegotti, S. Nava, and R. Valdagni, "Clinical and dosimetric predictors of late rectal syndrome after 3D-CRT for localized prostate cancer: Preliminary results of a multicenter prospective study," Int. J. Radiat. Oncol., Biol., Phys. 70, 1130-1137 (2008)] and the constraints used in the conventional or hypofractionated high dose intensity modulated radiotherapy for prostate cancer (CHHiP) trial [C. P. South, V. S. Khoo, O. Naismith, A. Norman, and D. P. Dearnaley, "A comparison of treatment planning techniques used in two randomised UK external beam radiotherapy trials for localised prostate cancer," Clin. Oncol. (R Coll. Radiol) 20, 15-21 (2008)]--were evaluated using a tenfold cross-validation with follow-up data from the RT01 trial. The predictive power was quantified using receiver-operator characteristic (ROC) curves. Toxicities considered were rectal bleeding, loose stools, and a global toxicity score.
Dose-volume constraints had less predictive power than the new type of hybrid constraints. A probabilistic model for predicting rectal bleeding based on the dose-volume constraints proposed by other researchers [C. Fiorino, G. Fellin, T. Rancati, V. Vavassori, C. Bianchi, V. C. Borca, G. Girelli, M. Mapelli, L. Menegotti, S. Nava, and R. Valdagni, "Clinical and dosimetric predictors of late rectal syndrome after 3D-CRT for localized prostate cancer: Preliminary results of a multicenter prospective study," Int. J. Radiat. Oncol., Biol., Phys. 70, 1130-1137 (2008)], the CHHiP dose-volume constraints, the RT01-based dose-volume constraints, and the hybrid constraints resulted in average areas under the ROC curves of 0.56, 0.58, 0.62, and 0.67, respectively. For predicting loose stools, the corresponding values were 0.57, 0.53, 0.66, and 0.71, respectively. The areas under the respective ROC curves for predicting the global toxicity score were 0.58, 0.55, 0.61, and 0.63.
Thus, imposing the new type of hybrid constraints when generating a treatment plan should result in a reduction in the incidence of radiation-induced late rectal toxicity.
... 36 The doses and volumes chosen comprised the constraints from two recent trials. 37,38 Planned and daily delivered DSMs were produced based on algorithms described by Murray et al 39 and Buettner et al. 40 The rectum was considered as a cylinder and dose was sampled at points on each CT slice. The cylinder was "cut" at the point where a vertical line from the centroid of each contour crossed the posterior edge and unfolded ( Figure 1). ...
... A limitation of this work was the lack of availability of images and contours for the most inferior part of the rectum, owing to this being located away from the planning target volume and Figure 5. Graphs showing absolute differences in dose (a) and volumes of rectum (b) between accumulated and planned dose-volume histograms (DVHs) for the 10 participants. Doses to 80%, 70%, 65%, 60%, 55%, 50%, 40%, 30%, 25%, 15%, 5% and 3% of the rectum are shown in (a) and volumes treated to 20,30,40,50,60,65,70 and 75 Gy are shown in (b). For Participant A, all accumulated doses and volumes were higher than planned. ...
We sought to calculate accumulated dose (DA) to the rectum in patients treated with radiotherapy for prostate cancer. We were particularly interested in whether dose-surface maps (DSMs) provide additional information to dose-volume histograms (DVHs).
Manual rectal contours were obtained for kilo-voltage (kV) and daily mega-voltage (MV) CT scans for 10 participants from the VoxTox Study (380 scans). Daily delivered dose recalculation was performed using a ray-tracing algorithm. Delivered DVHs were summated to create accumulated DVHs. The rectum was considered as a cylinder, cut and unfolded to produce daily delivered DSMs; these were summated to produce accumulated DSMs.
Accumulated dose-volumes were different from planned in all participants. For one participant, all DA levels were higher and all volumes were larger than planned. For four participants, all DA levels were lower and all volumes were smaller than planned. For each of these four participants, ≥1% of pixels on the accumulated DSM received ≥5 Gy more than had been planned.
Differences between accumulated and planned dose-volumes were seen in all participants. DSMs were able to identify differences between DA and planned dose that could not be appreciated from the DVHs. Further work is needed to extract the dose data embedded in the DSMs. These will be correlated with toxicity as part of the VoxTox Programme. Advances in knowledge: DSMs are able to identify differences between DA and planned dose that cannot be appreciated from DVHs alone, and should be incorporated into future studies investigating links between DA and toxicity.
... Radiation therapy technique determines the spatial distribution of dose that is summarised by the DVH. Some attempts have been made to examine spatial distribution of dose and correlate with late toxicity (45,77). Such methodology is complex, due to the number of possible predictive components, and is not yet replicable in clinical use. ...
Cancer and normal tissues in a population of patients exhibit variability in biological response to the same dose of radiation. The sources of this variability include:
• Inherent biological factors of each patient, tumour or tissue
• Metrics used to measure, classify or declare biological outcomes
• Volumetric (prescription of target and or avoidance regions)
• Dosimetric and delivery
Dosimetric and delivery variation is easily measured and has relatively little impact on variation of outcome in modelling studies. Volumetric variation is probably the greatest source of uncertainty, dependent on human judgement by oncologists. However, analysis methodology is generally overlooked as a source of variation in reported dose-effect results and is the subject of investigation in this thesis. Dosimetric and clinical data from clinical trials and prospective cohort studies have been used to illustrate the contribution of analysis methodology to variation in dose-effect relationships using evidence from prostate cancer radiation therapy. The primary data source is the Trans-Tasman Radiation Oncology Group clinical trial 03.04 "RADAR", which investigated dose escalation in external beam radiotherapy for prostate cancer. Systematic review of the medical physics literature shows that prostate cancer radiotherapy toxicity reporting does not fully account for treatment delivery method, which biases and causes unreported variation in dose-effect results. The toxicity dose-volume-effect relationship is shown to vary depending on the anatomical subsite delineated and the type/grade of toxicity outcome chosen. Multivariate regression of multiple dose factors is not reliable due to multicollinearity of these factors. Heterogeneity in method of analysis is an important and overlooked component of variability in reported results of dose effect relationships in radiotherapy trials and studies. Harmonisation of analysis or correction for this heterogeneity will reduce uncertainties allowing better modelling of truly biological effects in the molecular oncology era.
... In addition, although only four DGPs were investigated in this work, other DGPs which were explored in previous studies also indicated associations with rectal toxicity. For instance, Buettner et al. investigated the eccentricity of the fitted ellipse of the dose region and found associations of the eccentricity with loose stools [5,39,44]. Moulton et al. also reported that compactness, circularity and confinement to the ellipse fits were correlated with rectal bleeding [18]. Incorporating these spatial features, which are crafted to depict the dose coverage and the shape of dose distribution, into the current model may potentially improve the predictive performance. ...
... In addition, although only four DGPs were investigated in this work, other DGPs which were explored in previous studies also indicated associations with rectal toxicity. For instance, Buettner et al. investigated the eccentricity of the fitted ellipse of the dose region and found associations of the eccentricity with loose stools [5,39,44]. Moulton et al. also reported that compactness, circularity and confinement to the ellipse fits were correlated with rectal bleeding [18]. Incorporating these spatial features, which are crafted to depict the dose coverage and the shape of dose distribution, into the current model may potentially improve the predictive performance. ...
Background: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction.
Methods: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including twelve with Grade ≥2 rectum toxicity and thirty patients with Grade 0-1 toxicity (non-toxicity patients). The cumulative equivalent 2-Gy rectal surface dose was deformably summed using the deformation vector fields obtained through a recent developed local topology preserved non-rigid point matching algorithm. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectum surface dose map (RSDM). The dose volume parameters (DVPs) were calculated from the 3D rectum surface, while the texture features and the dose geometric parameters (DGPs) were extracted from the 2D RSDM. Representative features further computed from DVPs, textures and DGPs by principle component analysis (PCA) and statistical analysis were respectively fed into a support vector machine equipped with a sequential feature selection procedure. The predictive powers of the representative features were compared with the GEC-ESTRO dosimetric parameters D0.1/1/2cc.
Results: Satisfactory predictive accuracy of sensitivity 74.75% and 84.75%, specificity 72.67% and 79.87%, and area under the receiver operating characteristic curve (AUC) 0.82 and 0.91 were respectively achieved by the PCA features and statistical significant features, which were superior to the D0.1/1/2cc (AUC 0.71). The relative area in dose levels of 64Gy, 67Gy, 68Gy, 87Gy, 88Gy and 89Gy, perimeters in dose levels of 89Gy, as well as two texture features were ranked as the important factors that were closely correlated with rectal toxicity.
Conclusions: Our extensive experimental results have demonstrated the feasibility of the proposed scheme. A future large patient cohort study is still needed for model validation.
... Of note, the rate of toxicity was comparable with other published prostate cancer series [4,6]. Beyond the main difference of using mild toxicity endpoints rather than the most common moderate/severe complications, our methods and findings have been already touched by many research groups [8,24,30,31]. However, bootstrap and leave-one-out methods in NTCP modeling, parameters for non-bleeding late GI toxicity, AH/AC drugs as effective protecting drugs, and the inclusion of clinical factors other than dose have been often dealt with separately in the literature. ...
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.
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).
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).
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.
... By summarizing a variety of different endpoints in the global toxicity endpoint (including rectal bleeding and loose stools), geometrical descriptors such as lateral extent become less important and a more general descriptor such as DSH describes the outcome best. It has been suggested that the dose-response-relationship of the rectum differs between endpoints (Peeters et al. 2006a) and in previous studies we have found evidence that not only the relevance of specific dose-levels but also the importance of different spatial and morphometric aspects of the dose-distribution changes for different endpoints (Buettner et al. 2009b, Buettner et al. 2010). ...
Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.
Introduction
The focus of this study is to find the optimal clinical tumour volume (CTV) to planning tumour volume (PTV) margins for precise radiotherapy treatment of prostate cancer. The geometrical shape of the target volume posses challenges in accurately identifying the CTV to PTV margins, especially when the organ affected by cancer demonstrates anatomical variations and the surrounding organs have high radio-sensitivity, in comparison to the organ of origin of the cancer.
Materials and methods
The geometrical margins of CTV to PTV are investigated using portal imaging, in three directions. This study is carried out on 20 patients treated by the external photon beam radiotherapy of prostate cancer using standard accelerator without stereotaxic and without prostate markers.
Results and discussion
Based on previous studies and the findings of our work, we propose CTV to PTV margin of 5·84 mm in the lateral direction, of 5·1 mm in the cranio-spinal direction and of 7·3 mm in the antero-posterior direction for external photon beam radiotherapy of prostate cancer.
Conclusion
The proposed CTV to PTV margins ensure high radiotherapy treatment precision of prostate cancer.
Objective:
The VoxTox Study, linking delivered dose to toxicity requires recalculation of typically 20-37 fractions per patient, for nearly 2000 patients. This requires a non-interactive interface permitting batch calculation with multiple computers.
Methods:
Data are extracted from the TomoTherapy archive, and processed using the computational-task management system GANGA. Doses are calculated for each fraction of radiotherapy using the daily MV CT images. The calculated dose cube is saved as a DICOM RTDOSE object, which can then be read by utilities that calculate dose volume histograms (DVH) or dose surface maps (DSM). The rectum is delineated on daily MV images using an implementation of the Chan-Vese algorithm.
Results:
On a cluster of up to 117 CPUs, dose cubes for all fractions of 151 patients took 12 days to calculate. Outlining the rectum on all slices and fractions on 151 patients took 7 hours. We also present results of the HU calibration of TomoTherapy MV images, measured over an eight-year period, showing that The HU calibration has become less variable over time, with no large changes observed after 2011.
Conclusions:
We have developed a system for automatic dose recalculation of TomoTherapy dose distributions. This does not tie up the clinically-needed planning system, but can be run on a cluster of independent machines, enabling recalculation of delivered dose without user intervention. Advances in knowledge: The use of a task management system for automation of dose calculation and outlining enables work to be scaled up to level required for large studies.
Dose constraints based on histograms provide a convenient and widely-used method for informing and guiding radiotherapy treatment planning. Methods of derivation of such constraints are often poorly described. Two non-parametric methods for derivation of constraints are described and investigated in the context of determination of dose-specific cut-points—values of the free parameter (e.g., percentage volume of the irradiated organ) which best reflect resulting changes in complication incidence. A method based on receiver operating characteristic (ROC) analysis and one based on a maximally-selected standardized rank sum are described and compared using rectal toxicity data from a prostate radiotherapy trial. Multiple test corrections are applied using a free step-down resampling algorithm, which accounts for the large number of tests undertaken to search for optimal cut-points and the inherent correlation between dose–histogram points. Both methods provide consistent significant cut-point values, with the rank sum method displaying some sensitivity to the underlying data. The ROC method is simple to implement and can utilize a complication atlas, though an advantage of the rank sum method is the ability to incorporate all complication grades without the need for grade dichotomization.
Bayesian analysis is frequently confused with conjugate Bayesian
analysis. This is particularly the case in the analysis
of clinical trial data. Even though conjugate analysis is
perceived to be simpler computationally (but see below, Berger's
prior), the price to be paid is high: such analysis is not robust
with respect to the prior, i.e. changing the prior may affect the
conclusions without bound. Furthermore, conjugate Bayesian
analysis is blind with respect to the potential conflict between
the prior and the data. Robust priors, however, have bounded
influence. The prior is discounted automatically when there are
conflicts between prior information and data. In other words,
conjugate priors may lead to a dogmatic analysis while robust
priors promote self-criticism since prior and sample information
are not on equal footing. The original proposal of robust priors
was made by de-Finetti in the 1960's. However, the practice has
not taken hold in important areas where the Bayesian approach is
making definite advances such as in clinical trials where
conjugate priors are ubiquitous.
¶
We show here how the Bayesian analysis for simple binary binomial
data, expressed in its exponential family form, is improved by
employing Cauchy priors. This requires no undue computational
cost, given the advances in computation and analytical
approximations. Moreover, we introduce in the analysis of clinical
trials a robust prior originally developed by J.O. Berger that we
call Berger's prior. We implement specific choices of prior
hyperparameters that give closed-form results when coupled with a
normal log-odds likelihood. Berger's prior yields a robust
analysis with no added computational complication compared to the
conjugate analysis. We illustrate the results with famous textbook
examples and also with a real data set and a prior obtained from a
previous trial. On the formal side, we present a general and novel
theorem, the "Polynomial Tails Comparison Theorem." This theorem
establishes the analytical behavior of any likelihood function
with tails bounded by a polynomial when used with priors with
polynomial tails, such as Cauchy or Student's $t$. The advantages
of the theorem are that the likelihood does not have to be a
location family nor exponential family distribution and that the
conditions are easily verifiable. The binomial likelihood can be
handled as a direct corollary of the result. Next, we proceed to
prove a striking result: the intrinsic prior to test a normal
mean, obtained as an objective prior for hypothesis testing, is a
limit of Berger's robust prior. This result is useful for
assessments and for MCMC computations. We then generalize the
theorem to prove that Berger's prior and intrinsic priors are
robust with normal likelihoods. Finally, we apply the results to a
large clinical trial that took place in Venezuela, using prior
information based on a previous clinical trial conducted in
Finland.
¶
Our main conclusion is that introducing the existing prior
information in the form of a robust prior is more justifiable
simultaneously for federal agencies, researchers, and other
constituents because the prior information is coherently discarded
when in conflict with the sample information.
Bayesian analysis is frequently limited to conjugate Bayesian analysis, particularly in the case in the analysis of clinical trial data. Even though conjugate analysis may be simpler computationally, the price to be paid is high: such analysis is not robust with respect to the prior, i.e., changing the prior may affect the conclusions without bound. Furthermore conjugate Bayesian analysis is blind with respect to the potential conflict between the prior and the data. On the other hand, robust priors have bounded influence. The prior is discounted automatically when there are conflicts between prior information and data. The original proposal of robust priors was made by de-Finetti in the 1960's. However, the practice has not taken hold in important areas such as in clinical trials where conjugate priors are ubiquitous.
We show here how the Bayesian analysis for simple binary binomial data, after expressing in its exponentially family form, is improved by employing Cauchy priors. Moreover, we also introduce in the analysis of clinical trials a robust prior originally developed by J.O. Berger that gives closed-form results when coupled with a normal log-odds likelihood. Berger's prior yields the superior robust analysis with no added computational complication compared to the conjugate analysis. We illustrate the results with famous textbook examples and a with data set and a prior from a previous trial.
On the formal side, we give here a theorem that we call the “Polynomial Tails Comparison Theorem.” This theorem establishes the analytical behavior of any likelihood function with tails bounded by a polynomial when used with priors with polynomial-order tails, such as Cauchy or Student's t. The likelihood does not have to be a location family nor exponential family distribution and the conditions of the theorem are easily verifiable. For Berger's prior robustness can be established directly since the exact expressions for posterior moments are known.
Many studies have been performed to assess correlations between measures derived from dose-volume histograms and late rectal toxicities for radiotherapy of prostate cancer. The purpose of this study was to quantify correlations between measures describing the shape and location of the dose distribution and different outcomes. The dose to the rectal wall was projected on a two-dimensional map. In order to characterize the dose distribution, its centre of mass, longitudinal and lateral extent, and eccentricity were calculated at different dose levels. Furthermore, the dose-surface histogram (DSH) was determined. Correlations between these measures and seven clinically relevant rectal-toxicity endpoints were quantified by maximally selected standardized Wilcoxon rank statistics. The analysis was performed using data from the RT01 prostate radiotherapy trial. For some endpoints, the shape of the dose distribution is more strongly correlated with the outcome than simple DSHs. Rectal bleeding was most strongly correlated with the lateral extent of the dose distribution. For loose stools, the strongest correlations were found for longitudinal extent; proctitis was most strongly correlated with DSH. For the other endpoints no statistically significant correlations could be found. The strengths of the correlations between the shape of the dose distribution and outcome differed considerably between the different endpoints. Due to these significant correlations, it is desirable to use shape-based tools in order to assess the quality of a dose distribution.
The incidence of late-toxicities after radiotherapy can be modelled based on the dose delivered to the organ under consideration. Most predictive models reduce the dose distribution to a set of dose-volume parameters and do not take the spatial distribution of the dose into account. The aim of this study was to develop a classifier predicting radiation-induced rectal bleeding using all available information on the dose to the rectal wall. The dose was projected on a two-dimensional dose-surface map (DSM) by virtual rectum-unfolding. These DSMs were used as inputs for a classification method based on locally connected neural networks. In contrast to fully connected conventional neural nets, locally connected nets take the topology of the input into account. In order to train the nets, data from 329 patients from the RT01 trial (ISRCTN 47772397) were split into ten roughly equal parts. By using nine of these parts as a training set and the remaining part as an independent test set, a ten-fold cross-validation was performed. Ensemble learning was used and 250 nets were built from randomly selected patients from the training set. Out of these 250 nets, an ensemble of expert nets was chosen. The performances of the full ensemble and of the expert ensemble were quantified by using receiver-operator-characteristic (ROC) curves. In order to quantify the predictive power of the shape, ensembles of fully connected conventional neural nets based on dose-surface histograms (DSHs) were generated and their performances were quantified. The expert ensembles performed better than or equally as well as the full ensembles. The area under the ROC curve for the DSM-based expert ensemble was 0.64. The area under the ROC curve for the DSH-based expert ensemble equalled 0.59. This difference in performance indicates that not only volumetric, but also morphological aspects of the dose distribution are correlated to rectal bleeding after radiotherapy. Thus, the shape of the dose distribution should be taken into account when a predictive model for radiation-induced rectal bleeding is developed.
The R package coin implements a unified approach to permutation tests providing a huge class of independence tests for nominal, ordered, numeric, and censored data as well as multivariate data at mixed scales. Based on a rich and flexible conceptual framework that embeds different permutation test procedures into a common theory, a computational framework is established in coin that likewise embeds the corresponding R functionality in a common S4 class structure with associated generic functions. As a consequence, the computational tools in coin inherit the flexibility of the underlying theory and conditional inference functions for important special cases can be set up easily. Conditional versions of classical tests---such as tests for location and scale problems in two or more samples, independence in two- or three-way contingency tables, or association problems for censored, ordered categorical or multivariate data---can easily be implemented as special cases using this computational toolbox by choosing appropriate transformations of the observations. The paper gives a detailed exposition of both the internal structure of the package and the provided user interfaces along with examples on how to extend the implemented functionality.
To evaluate whether androgen deprivation impacts late rectal toxicity in patients with localised prostate carcinoma treated with three-dimensional conformal radiotherapy. One hundred and eighty-two consecutive patients treated with 3DCRT between 1995 and 1999 at our Institution and with at least 12 months follow-up were analysed. three-dimensional conformal radiotherapy consisted in 70–76 Gy delivered with a conformal 3-field arrangement to the prostate±seminal vesicles. As part of treatment, 117 patients (64%) received neo-adjuvant and concomitant androgen deprivation while 88 (48.4%) patients were continued on androgen deprivation at the end of three-dimensional conformal radiotherapy as well. Late rectal toxicity was graded according to the RTOG morbidity scoring scale. Median follow up is 25.8 (range: 12–70.2 months). The 2-year actuarial likelihood of grade 2–4 rectal toxicity was 21.8±3.2%. A multivariate analysis identified the use of adjuvant androgen deprivation (P=0.0196) along with the dose to the posterior wall of the rectum on the central axis (P=0.0055) and the grade of acute rectal toxicity (P=0.0172) as independent predictors of grade 2–4 late rectal toxicity. The 2-year estimates of grade 2–4 late rectal toxicity for patients receiving or not adjuvant hormonal treatment were 30.3±5.2% and 14.1±3.8%, respectively. Rectal tolerance is reduced in presence of adjuvant androgen deprivation.
British Journal of Cancer (2002) 86, 1843–1847. doi:10.1038/sj.bjc.6600266 www.bjcancer.com
© 2002 Cancer Research UK
Radiotherapy is the most frequently used treatment for men with localised prostate cancer. Conformal radiotherapy (CFRT) is a relatively new development. MRC RT01 was set-up to explore optimum CFRT dose.
RT01 was an international multi-centre randomised controlled trial for men with T1b-T3a, N0, M0 prostate cancer that evolved from a single-centre pilot trial of similar design. All men received at least 3 months of pre-radiotherapy hormone treatment, before randomisation to standard (64 Gy) or high dose (74 Gy) radical CFRT. Accrual was completed in December 2001 with 843 men randomised from 25 centres in less than 4 years. RT01 has been a catalyst for implementing CFRT across UK. In addition to the Trial Management Group, independent Data Monitoring and Ethics Committee and independent Trial Steering Committee, a Quality of Life and Health Economics (QL/HE) group, a radiotherapy Quality Assurance (QA) Group and a Radiography Trial Implementation Group were set up. The QL/HE group ensured implementation, compliance, analysis and interpretation of the QL and HE data in the trial. The inauguration of QA and Radiography groups facilitated inter-centre collaboration. The QA Group ensured procedures were in place before and during trial participation, and monitored quality and consistency with systems including a physics questionnaire, a clinical examples exercise, a standard operating procedure document, designing and building a phantom, and convening a complications modelling subgroup. The Radiography group agreed and implemented technique improvements.
More centres participated than initially predicted, enabling recruitment better than scheduled. The trial expedited the implementation of CFRT in many UK radiotherapy centres. Additionally, the QA and Radiography groups helped ensure smooth initiation and established consistency in planning, dosimetry and delivery of prostate CFRT services at participating UK centres. Considerable data has been collected; a series of papers will be produced, although mature clinical trial results are not anticipated until 2006-2008.
Purpose. To develop and disseminate a report aimed primarily at practicing radiation oncology physicians and medical physicists that describes the current state-of-the-art of intensity-modulated radiotherapy (IMRT). Those areas needing further research and development are identified by category and recommendations are given, which should also be of interest to IMRT equipment manufacturers and research funding agencies. Methods and Materials. The National Cancer Institute formed a Collaborative Working Group of experts in IMRT to develop consensus guidelines and recommendations for implementation of IMRT and for further research through a critical analysis of the published data supplemented by clinical experience. A glossary of the words and phrases currently used in IMRT is given in the Appendix. Recommendations for new terminology are given where clarification is needed. Results. IMRT, an advanced form of external beam irradiation, is a type of three-dimensional conformal radiotherapy (3D-CRT). It represents one of the most important technical advances in RT since the advent of the medical linear accelerator. 3D-CRT/IMRT is not just an add-on to the current radiation oncology process; it represents a radical change in practice, particularly for the radiation oncologist. For example, 3D-CRT/IMRT requires the use of 3D treatment planning capabilities, such as defining target volumes and organs at risk in three dimensions by drawing contours on cross-sectional images (i.e., CT, MRI) on a slice-by-slice basis as opposed to drawing beam portals on a simulator radiograph. In addition, IMRT requires that the physician clearly and quantitatively define the treatment objectives. Currently, most IMRT approaches will increase the time and effort required by physicians, medical physicists, dosimetrists, and radiation therapists, because IMRT planning and delivery systems are not yet robust enough to provide totally automated solutions for all disease sites. Considerable research is needed to model the clinical outcomes to allow truly automated solutions. Current IMRT delivery systems are essentially first-generation systems, and no single method stands out as the ultimate technique. The instrumentation and methods used for IMRT quality assurance procedures and testing are not yet well established. In addition, many fundamental questions regarding IMRT are still unanswered. For example, the radiobiologic consequences of altered time-dose fractionation are not completely understood. Also, because there may be a much greater ability to trade off dose heterogeneity in the target vs. avoidance of normal critical structures with IMRT compared with traditional RT techniques, conventional radiation oncology planning principles are challenged. All in all, this new process of planning and treatment delivery has significant potential for improving the therapeutic ratio and reducing toxicity. Also, although inefficient currently, it is expected that IMRT, when fully developed, will improve the overall efficiency with which external beam RT can be planned and delivered, and thus will potentially lower costs. Conclusion. Recommendations in the areas pertinent to IMRT, including dose-calculation algorithms, acceptance testing, commissioning and quality assurance, facility planning and radiation safety, and target volume and dose specification, are presented. Several of the areas in which future research and development are needed are also indicated. These broad recommendations are intended to be both technical and advisory in nature, but the ultimate responsibility for clinical decisions pertaining to the implementation and use of IMRT rests with the radiation oncologist and radiation oncology physicist. This is an evolving field, and modifications of these recommendations are expected as new technology and data become available. (C) 2001 Elsevier Science Inc.
Purpose:
To develop and disseminate a report aimed primarily at practicing radiation oncology physicians and medical physicists that describes the current state-of-the-art of intensity-modulated radiotherapy (IMRT). Those areas needing further research and development are identified by category and recommendations are given, which should also be of interest to IMRT equipment manufacturers and research funding agencies.
Methods and materials:
The National Cancer Institute formed a Collaborative Working Group of experts in IMRT to develop consensus guidelines and recommendations for implementation of IMRT and for further research through a critical analysis of the published data supplemented by clinical experience. A glossary of the words and phrases currently used in IMRT is given in the. Recommendations for new terminology are given where clarification is needed.
Results:
IMRT, an advanced form of external beam irradiation, is a type of three-dimensional conformal radiotherapy (3D-CRT). It represents one of the most important technical advances in RT since the advent of the medical linear accelerator. 3D-CRT/IMRT is not just an add-on to the current radiation oncology process; it represents a radical change in practice, particularly for the radiation oncologist. For example, 3D-CRT/IMRT requires the use of 3D treatment planning capabilities, such as defining target volumes and organs at risk in three dimensions by drawing contours on cross-sectional images (i.e., CT, MRI) on a slice-by-slice basis as opposed to drawing beam portals on a simulator radiograph. In addition, IMRT requires that the physician clearly and quantitatively define the treatment objectives. Currently, most IMRT approaches will increase the time and effort required by physicians, medical physicists, dosimetrists, and radiation therapists, because IMRT planning and delivery systems are not yet robust enough to provide totally automated solutions for all disease sites. Considerable research is needed to model the clinical outcomes to allow truly automated solutions. Current IMRT delivery systems are essentially first-generation systems, and no single method stands out as the ultimate technique. The instrumentation and methods used for IMRT quality assurance procedures and testing are not yet well established. In addition, many fundamental questions regarding IMRT are still unanswered. For example, the radiobiologic consequences of altered time-dose fractionation are not completely understood. Also, because there may be a much greater ability to trade off dose heterogeneity in the target vs. avoidance of normal critical structures with IMRT compared with traditional RT techniques, conventional radiation oncology planning principles are challenged. All in all, this new process of planning and treatment delivery has significant potential for improving the therapeutic ratio and reducing toxicity. Also, although inefficient currently, it is expected that IMRT, when fully developed, will improve the overall efficiency with which external beam RT can be planned and delivered, and thus will potentially lower costs.
Conclusion:
Recommendations in the areas pertinent to IMRT, including dose-calculation algorithms, acceptance testing, commissioning and quality assurance, facility planning and radiation safety, and target volume and dose specification, are presented. Several of the areas in which future research and development are needed are also indicated. These broad recommendations are intended to be both technical and advisory in nature, but the ultimate responsibility for clinical decisions pertaining to the implementation and use of IMRT rests with the radiation oncologist and radiation oncology physicist. This is an evolving field, and modifications of these recommendations are expected as new technology and data become available.
We propose a new prior distribution for classical (non-hierarchical) logistic regres- sion models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, and then placing independent Student-t prior distributions on the coefficients. As a default choice, we recommend the Cauchydistribution with center 0 and scale 2.5, which in the simplest setting is a longer-tailed version of the distribu- tion attained by assuming one-half additional success and one-half additional failure in a logistic regression. Cross-validation on a corpus of datasets shows the Cauchy class of prior distributions to outperform existing implementations of Gaussian and Laplace priors. We recommend this prior distribution as a default choice for routine applied use. It has the advantage of always giving answers, even when there is complete separation in logistic regression (a common problem, even when the sample size is large and the number of predictors is small) and also automatically applying more shrinkage to higher- order interactions. This can be useful in routine data analysis as well as in automated procedures such as chained equations for missing-data imputation. We implement a procedure to fit generalized linear models in R with the Student-t prior distribution by incorporating an approximate EM algorithm into the usual itera- tively weighted least squares. We illustrate with several examples, including a series of logistic regressions predicting voting preferences, a small bioassay experiment, and an imputation model for a public health data set.
Statistical learning plays a key role in many areas of science, finance and industry. Here are some examples of learning problems:
Two samples can be compared by selecting a cut point and then forming a 2 X 2 table of the numbers of observations above and below the cut point in each sample. When the cut point is selected so as to maximize the standard chi square statistic, the chi square percentile points are inappropriate. Actual significance levels are computed for large samples, and correct percentile points are tabulated. -Authors
Bayesian classification and regression with high-order interactions is largely infeasible because Markov chain Monte Carlo (MCMC) would need to be applied with a great many parameters, whose number increases rapidly with the order. In this paper we show how to make it feasible by effectively reducing the number of parameters, exploiting the fact that many interactions have the same values for all training cases. Our method uses a single "compressed" parameter to represent the sum of all parameters associated with a set of patterns that have the same value for all training cases. Using symmetric stable distributions as the priors of the original parameters, we can easily find the priors of these compressed parameters. We therefore need to deal only with a much smaller number of compressed parameters when training the model with MCMC. After training the model, we can split these compressed parameters into the original ones as needed to make predictions for test cases. We show in detail how to compress parameters for logistic sequence prediction models. Experiments on both simulated and real data demonstrate that a huge number of parameters can indeed be reduced by our compression method.
WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probability models. Models may be specified either textually via the BUGS language or pictorially using a graphical interface called DoodleBUGS. WinBUGS processes the model specification and constructs an object-oriented representation of the model. The software offers a user-interface, based on dialogue boxes and menu commands, through which the model may then be analysed using Markov chain Monte Carlo techniques. In this paper we discuss how and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design. We also discuss how the framework may be extended. It is possible to write specific applications that form an apparently seamless interface with WinBUGS for users with specialized requirements. It is also possible to interface with WinBUGS at a lower level by incorporating new object types that may be used by WinBUGS without knowledge of the modules in which they are implemented. Neither of these types of extension require access to, or even recompilation of, the WinBUGS source-code.
PURPOSE: Androgen deprivation therapy (AD) has been shown to increase late ≥ grade 2 rectal toxicity when used concurrently with three-dimensional conformal radiotherapy (3DCRT). Intensity modulated radiotherapy (IMRT) has the potential to reduce toxicity by limiting the radiation dose received by the bowel and bladder. This study compares both genitourinary (GU) and gastrointestinal (GI) toxicity in men treated with 3DCRT+AD versus IMRT+AD. METHODS AND MATERIALS: From July 1992 to July 2004, 293 men received 3DCRT (n=170) or IMRT (n=123) with concurrent AD (< 6 months, n=123; ≥ 6 months, n =170). Median RT doses were 76 Gy for 3DCRT (ICRU) and 76 Gy for IMRT (95% to the PTV). Toxicity was assessed by a patient symptom questionnaire assessing toxicity completed at each visit and recorded using a modified late effects normal tissue task force radiation morbidity scale (LENT). RESULTS: Mean follow-up was 86 months (SD=29.3) for the 3DCRT group and 40 months (SD=9.7) for the IMRT group. Acute GI toxicity (OR=4, 95% CI: 1.6-11.7, p=0.005) was significantly higher with 3DCRT than with IMRT and was independent of AD duration (i.e. <6 vs. ≥6 months). Time to development of late GI toxicity was significantly longer in the IMRT group. The 5-year Kaplan-Meier estimates for ≥ grade 2 GI toxicity were 20% for 3DCRT versus 8% for IMRT (p=0.01). On MVA, ≥ grade 2 late GI toxicity (HR=2.1, 95% CI: 1.1-4.3, p=0.04) was more prevalent in 3DCRT patients. CONCLUSIONS: Compared to 3DCRT, IMRT significantly decreased acute and late GI toxicity in patients treated with AD.
A great deal of quantitative information regarding the dose-volume relationships of pelvic organs at risk has been collected and analysed over the last 10 years. The need to improve our knowledge in the modelling of late and acute toxicity has become increasingly important, due to the rapidly increasing use of inverse-planned intensity-modulated radiotherapy (IMRT) and the consequent need of a quantitative assessment of dose-volume or biological-based cost functions. This comprehensive review concerns most organs at risk involved in planning optimisation for prostate and other types of pelvic cancer. The rectum is the most investigated organ: the largest studies on dose-volume modelling of rectal toxicity show quite consistent results, suggesting that sufficiently reliable dose-volume/EUD-based constraints can be safely applied in most clinical situations. Quantitative data on bladder, bowel, sexual organs and pelvic bone marrow are more lacking but are rapidly emerging; however, for these organs, further investigation on large groups of patients is necessary.
Radical radiotherapy for prostate cancer is effective but dose limited because of the proximity of normal tissues. Comprehensive dose-volume analysis of the incidence of clinically relevant late rectal toxicities could indicate how the dose to the rectum should be constrained. Previous emphasis has been on constraining the mid-to-high dose range (>/=50 Gy). Evidence is emerging that lower doses could also be important.
Data from a large multicenter randomized trial were used to investigate the correlation between seven clinically relevant rectal toxicity endpoints (including patient- and clinician-reported outcomes) and an absolute 5% increase in the volume of rectum receiving the specified doses. The results were quantified using odds ratios. Rectal dose-volume constraints were applied retrospectively to investigate the association of constraints with the incidence of late rectal toxicity.
A statistically significant dose-volume response was observed for six of the seven endpoints for at least one of the dose levels tested in the range of 30-70 Gy. Statistically significant reductions in the incidence of these late rectal toxicities were observed for the group of patients whose treatment plans met specific proposed dose-volume constraints. The incidence of moderate/severe toxicity (any endpoint) decreased incrementally for patients whose treatment plans met increasing numbers of dose-volume constraints from the set of V30<or=80%, V40<or=65%, V50<or=55%, V60<or=40%, V65<or=30%, V70<or=15%, and V75<or=3%.
Considering the entire dose distribution to the rectum by applying dose-volume constraints such as those tested here in the present will reduce the incidence of late rectal toxicity.
Treatment planners frequently modify beam arrangements and use IMRT to improve target dose coverage while satisfying dose constraints on normal tissues. The authors herein analyze the limitations of these strategies and quantitatively assess the extent to which dose can be redistributed within the patient volume. Specifically, the authors hypothesize that (1) the normalized integral dose is constant across concentric shells of normal tissue surrounding the target (normalized to the average integral shell dose), (2) the normalized integral shell dose is constant across plans with different numbers and orientations of beams, and (3) the normalized integral shell dose is constant across plans when reducing the dose to a critical structure. Using the images of seven patients previously irradiated for cancer of brain or prostate cancer and one idealized scenario, competing three-dimensional conformal and IMRT plans were generated using different beam configurations. Within a given plan and for competing plans with a constant mean target dose, the normalized integral doses within concentric "shells" of surrounding normal tissue were quantitatively compared. Within each patient, the normalized integral dose to shells of normal tissue surrounding the target was relatively constant (1). Similarly, for each clinical scenario, the normalized integral dose for a given shell was also relatively constant regardless of the number and orientation of beams (2) or degree of sparing of a critical structure (3). 3D and IMRT planning tools can redistribute, rather than eliminate dose to the surrounding normal tissues (intuitively known by planners). More specifically, dose cannot be moved between shells surrounding the target but only within a shell. This implies that there are limitations in the extent to which a critical structure can be spared based on the location and geometry of the critical structure relative to the target.
The purpose of this paper is to use the outcome of a dose escalation protocol for three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer to study the dose-response for late rectal toxicity and to identify anatomic, dosimetric, and clinical factors that correlate with late rectal bleeding in multivariate analysis.
Seven hundred forty-three patients with T1c-T3 prostate cancer were treated with 3D-CRT with prescribed doses of 64.8 to 81.0 Gy. The 5-year actuarial rate of late rectal toxicity was assessed using Kaplan-Meier statistics. A retrospective dosimetric analysis was performed for patients treated to 70.2 Gy (52 patients) or 75.6 Gy (119 patients) who either exhibited late rectal bleeding (RTOG Grade 2/3) within 30 months after treatment (i.e., 70.2 Gy-13 patients, 75. 6 Gy-36 patients) or were nonbleeding for at least 30 months (i.e., 70.2 Gy-39 patients, 75.6 Gy-83 patients). Univariate and multivariate logistic regression was performed to correlate late rectal bleeding with several anatomic, dosimetric, and clinical variables.
A dose response for >/= Grade 2 late rectal toxicity was observed. By multivariate analysis, the following factors were significantly correlated with >/= Grade 2 late rectal bleeding for patients prescribed 70.2 Gy: 1) enclosure of the outer rectal contour by the 50% isodose on the isocenter slice (i.e., Iso50) (p < 0.02), and 2) smaller anatomically defined rectal wall volume (p < 0.05). After 75.6 Gy, the following factors were significant: 1) smaller anatomically defined rectal wall volume (p < 0.01), 2) higher rectal D(max) (p < 0.01), 3) enclosure of rectal contour by Iso50 (p < 0.01), 4) patient age (p = 0.02), and 5) history of diabetes mellitus (p = 0.04). In addition to these five factors, acute rectal toxicity was also significantly correlated (p = 0.05) with late rectal bleeding when patients from both dose groups were combined in multivariate analysis.
A multivariate logistic regression model is presented which describes the probability of developing late rectal bleeding after conformal irradiation of prostate cancer. Late rectal bleeding correlated with factors which may indicate that a greater fractional volume of rectal wall was exposed to high dose, such as smaller rectal wall volume, inclusion of the rectum within the 50% isodose on the isocenter slice, and higher rectal D(max).
A trial of nonescalated conformal versus conventional radiotherapy treatment of prostate cancer has been carried out at the Royal Marsden NHS Trust (RMH) and Institute of Cancer Research (ICR), demonstrating a significant reduction in the rate of rectal bleeding reported for patients treated using the conformal technique. The rate of bleeding has been shown to fall significantly as the extent of rectal wall receiving a planned dose-level in excess of 57 Gy is reduced. Dose-distributions delivered to the rectal wall over the course of radiotherapy treatment inevitably differ from planned distributions. In a previous paper estimates were obtained of the uncertainties in some planned rectal dose-distribution parameters generated by patient setup error, rectal wall movement and the variable degree of rectal wall distension. Here these uncertainties are combined to obtain estimates of the total planning uncertainties in rectal dose-distribution parameters thought likely, on the basis of mechanistic biological modeling, to correlate strongly with the complication rate. Working from these totaled uncertainty values, together with values of patient-to-patient and technique-to-technique differences in planned dose-distribution parameters, it can be inferred that the rectal dose-distribution uncertainties: (i) Have only a marginal impact on fits of a normal tissue complication probability (ntcp) model to RMH/ICR dose-distribution and grade 1, 2, 3 bleeding data (slightly flattening observed volume-response curves); (ii) only slightly reduce the power of a 2 x 100 patient trial of conformal versus conventional prostate radiotherapy to detect a significantly lower rate of grade 1,2,3 rectal bleeding amongst conformally treated patients; (iii) do not diminish the information content of individual planned patient dose-distribution data to the point where the fitting of technique-averaged data would provide as sensitive a test of the existence of a volume effect as the fitting of individual patient data.
To develop a method to project surface elements of a bent tubular organ, e.g. the rectum, in order to create a two-dimensional (2D) map and to use this method to quantify on a local scale shape and position variations of the rectum.
For this study we used data of 19 patients, who each received a planning CT scan and 9-13 repeat CT scans that were considered representative for the radiotherapy course. We combined maps from multiple CT scans of the same patient to quantify local rectal wall displacements. To make a map we first computed a central axis through the rectum and divided it into segments of equal length assuming that the length of these segments was invariant under rectum shape and position changes. Next, we constructed for each segment a planar cross section through the rectum, which was oriented orthogonally to that segment. The amount of rectal wall tissue was assumed to be constant in all orthogonal cross sections throughout the entire rectum. We unfolded the cross-sected rectal wall at the dorsal side and projected either the associated dose or the coordinates onto the map.
The largest variation in the position of the rectal wall during the treatment course occurred at the upper anterior, left and right side (1 SD=5-7 mm). Near the anus the variation was <3 mm (1 SD) and at the posterior side of the rectum <4 mm (1 SD). The anterior-posterior (AP) and left-right displacements between the rectum in the planning CT scan and the mean rectum shape during the treatment were localized between 40 and 80% of the central axis. At the upper anterior, left, and right side the displacements were 5-8 mm (1 SD). These rectal wall displacements correlated with the rectum volume in the planning CT scan. At the upper anterior side the correlation coefficient between the AP displacements and the planning rectum volume was 0.85.
We quantified variations in rectum shape and in dose in the rectal wall. The systematic error in rectal wall position was found to be larger than the random shape and position variations. We successfully developed a method to virtually unfold a rectum and to project the dose onto a 2D map. The spatial information of the dose distribution can be used in the analysis of rectum complications.
Cluster models are newly developed normal-tissue complication probability models in which the spatial aspects of radiation-induced injury are taken into account by considering the size of spatially contiguous aggregates of damaged tissue units. The purpose of this study was to test the validity of a two-dimensional cluster model of late rectal toxicity based on maximum cluster size of damage to rectal surface.
A paired case-control study was performed in which each of 9 patients experiencing Grade 2 or higher late rectal toxicity after intensity-modulated radiation therapy of localized prostate cancer was paired with a patient having a similar rectal dose-surface histogram but free of rectal toxicity. Numeric simulations were performed to determine the distribution of maximum cluster size on each rectal surface for each of many different choices of possible model parameters.
Model parameters were found for which patients with rectal toxicity were consistently more likely to have a significantly larger mean maximum cluster size than their matched controls. These parameter values correspond to a 50% probability of tissue-unit damage at doses near 30 Gy.
This study suggests that a cluster model based on maximum cluster size of damage to rectal surface successfully incorporates spatial information beyond that contained in the rectal dose-surface histogram and may therefore provide a useful new tool for predicting rectal normal-tissue complication probability after radiotherapy.
To analyze whether inclusion of predisposing clinical features in the Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) model improves the estimation of late gastrointestinal toxicity.
This study includes 468 prostate cancer patients participating in a randomized trial comparing 68 with 78 Gy. We fitted the probability of developing late toxicity within 3 years (rectal bleeding, high stool frequency, and fecal incontinence) with the original, and a modified LKB model, in which a clinical feature (e.g., history of abdominal surgery) was taken into account by fitting subset specific TD50s. The ratio of these TD50s is the dose-modifying factor for that clinical feature. Dose distributions of anorectal (bleeding and frequency) and anal wall (fecal incontinence) were used.
The modified LKB model gave significantly better fits than the original LKB model. Patients with a history of abdominal surgery had a lower tolerance to radiation than did patients without previous surgery, with a dose-modifying factor of 1.1 for bleeding and of 2.5 for fecal incontinence. The dose-response curve for bleeding was approximately two times steeper than that for frequency and three times steeper than that for fecal incontinence.
Inclusion of predisposing clinical features significantly improved the estimation of the NTCP. For patients with a history of abdominal surgery, more severe dose constraints should therefore be used during treatment plan optimization.
To evaluate the relationship between erectile function and the radiation dose to the penile bulb and other proximal penile structures in men receiving conformal radiotherapy (CFRT) for prostate cancer (PCa).
The Medical Research Council (MRC) RT01 trial randomised 843 men who had localised PCa to receive either 64 or 74 Gy after 3 - 6 months neoadjuvant hormonal treatment. Fifty-one men were selected who were potent prior to hormonal treatment, having completed both pre-hormone and 2-year post-CFRT Quality of Life assessments, and on whom dose volume data were available for analysis. The men were divided into three groups according to 2-year follow-up: potent, reduced potency, and impotent. The bulb of the penis together with the crura, were outlined on restored treatment plans. Dose - volume histograms were generated and compared between the three groups. An ordered logistic regression model was used to calculate the odds ratio of a range of dose - volume parameters to the penile bulb and effect on erectile dysfunction. The dose to the penile bulb was correlated to the dose received by the crura.
Of the 51 patients, 12 remained potent, 22 had reduced potency, and 17 were impotent at 2 years. No differences were seen in mean dose to the penile bulb by allocated treatment (t test = 1.61, p = 0.11). The mean doses to the penile bulb received by the potent, reduced potency, and impotent groups were 45.5 Gy (SD 17.1), 48 Gy (SD 16.1), and 59.2 Gy (SD 13.8), respectively. There was a strong correlation between the mean dose received by the penile bulb and dose to the crura (r = 0.82, p < 0.0001). 83.3% of impotent patients received a D90 > or = 50 Gy to the penile bulb compared with 29.4% of patients who maintained potency at 2 years (p = 0.006).
There is evidence from this study to suggest a dose volume effect on the penile bulb and erectile dysfunction. A D90 > or = 50 Gy is associated with a significant risk of erectile dysfunction and this should form a basis for selecting dose constraints in future dose escalation studies.
Accurate modeling of rectal complications based on dose-volume histogram (DVH) data are necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different equivalent uniform dose (EUD)-based and dose-volume-based normal tissue complication probability (NTCP) models to rectal wall DVHs and follow-up data for 319 prostate cancer patients to identify the dosimetric factors most predictive for Grade > or = 2 rectal bleeding.
Data for 319 patients treated at the William Beaumont Hospital with three-dimensional conformal radiotherapy (3D-CRT) under an adaptive radiotherapy protocol were used for this study. The following models were considered: (1) Lyman model and (2) logit-formula with DVH reduced to generalized EUD, (3) serial reconstruction unit (RU) model, (4) Poisson-EUD model, and (5) mean dose- and (6) cutoff dose-logistic regression model. The parameters and their confidence intervals were determined using maximum likelihood estimation.
Of the patients, 51 (16.0%) showed Grade 2 or higher bleeding. As assessed qualitatively and quantitatively, the Lyman- and Logit-EUD, serial RU, and Poisson-EUD model fitted the data very well. Rectal wall mean dose did not correlate to Grade 2 or higher bleeding. For the cutoff dose model, the volume receiving > 73.7 Gy showed most significant correlation to bleeding. However, this model fitted the data more poorly than the EUD-based models.
Our study clearly confirms a volume effect for late rectal bleeding. This can be described very well by the EUD-like models, of which the serial RU- and Poisson-EUD model can describe the data with only two parameters. Dose-volume-based cutoff-dose models performed worse.
To assess the predictors of late rectal toxicity in a prospectively investigated group of patients treated at 70-80 Gy for prostate cancer (1.8-2 Gy fractions) with three-dimensional conformal radiotherapy.
A total of 1,132 patients were entered into the study between 2002 and 2004. Three types of rectal toxicity, evaluated by a self-administered questionnaire, mainly based on the subjective objective management, analytic late effects of normal tissue system, were considered: stool frequency/tenesmus/pain, fecal incontinence, and bleeding. The data from 506 patients with a follow-up of 24 months were analyzed. The correlation between a number of clinical and dosimetric parameters and Grade 2 or greater toxicity was investigated by univariate and multivariate (MVA) logistic analyses.
Of the 1,132 patients, 21, 15, and 30 developed stool frequency/tenesmus/pain, fecal incontinence, and bleeding, respectively. Stool frequency/tenesmus/pain correlated with previous abdominal/pelvic surgery (MVA, p=0.05, odds ratio [OR], 3.3). With regard to incontinence, MVA showed the volume receiving>or=40 Gy (V40) (p=0.035, OR, 1.037) and surgery (p=0.02, OR, 4.4) to be the strongest predictors. V40 to V70 were highly predictive of bleeding; V70 showed the strongest impact on MVA (p=0.03), together with surgery (p=0.06, OR, 2.5), which was also the main predictor of Grade 3 bleeding (p=0.02, OR, 4.2).
The predictive value of the dose-volume histogram was confirmed for bleeding, consistent with previously suggested constraints (V50<55%, V60<40%, V70<25%, and V75<5%). A dose-volume histogram constraint for incontinence can be suggested (V40<65-70%). Previous abdominal/pelvic surgery correlated with all toxicity types; thus, a modified constraint for bleeding (V70<15%) can be suggested for patients with a history of abdominal/pelvis surgery, although further validation on a larger population with longer follow-up is needed.
To compare the radiotherapy planning techniques from two multicentre randomised external beam radiotherapy trials in the UK of conformal radiotherapy vs intensity-modulated radiotherapy (IMRT).
Sixteen sequential patients with histologically confirmed localised prostate cancer treated in the conventional or hypofractionated IMRT trial (CHHiP) were planned using both the CHHiP and Medical Research Council RT-01 planning protocols to 74 Gy in 37 daily fractions. The CHHiP plan used a single phase simple forward planned three-field IMRT plan for easy multicentre adoption. The RT-01 plan used two phases: three-field conformal radiotherapy plan to 64 Gy followed by a six-field boost of 10 Gy. After coverage of the planning target volumes according to the respective trial protocols, the dose to the rectum and bladder was assessed for the two planning techniques.
There was acceptable planning target volume coverage by both the CHHiP and RT-01 plans. All CHHiP plans produced lower mean irradiated rectal volumes at all measured dose levels compared with the RT-01 plans, particularly for irradiated rectal volumes at 50 and 70 Gy (P<0.05). In the cases when a CHHiP plan failed to meet its own trial dose constraints, the volumes of irradiated rectum were less than if an RT-01 planning technique had been used. The CHHiP plans gave lower mean irradiated bladder volumes at both 50 and 60 Gy, but higher volumes at 74 Gy. These differences in irradiated bladder volumes were significant at the 60 and 74 Gy dose levels (P<0.05) in favour of the CHHiP and RT-01 plans, respectively.
The forward planned CHHiP IMRT planning solution gives more favourable rectal sparing than the RT-01 plan. This is important to limit any potential increase in late rectal toxicity for prostate cancer patients treated with high-dose conventional or hypofractionated schedules.
Maximally selected statistics for the estimation of simple cutpoint models are embedded into a generalized conceptual framework based on conditional inference procedures. This powerful framework contains most of the published procedures in this area as special cases, such as maximally selected chi(2) and rank statistics, but also allows for direct construction of new test procedures for less standard test problems. As an application, a novel maximally selected rank statistic is derived from this framework for a censored response partitioned with respect to two ordered categorical covariates and potential interactions. This new test is employed to search for a high-risk group of rectal cancer patients treated with a neo-adjuvant chemoradiotherapy. Moreover, a new efficient algorithm for the evaluation of the asymptotic distribution for a large class of maximally selected statistics is given enabling the fast evaluation of a large number of cutpoints.
We seek to identify dosimetric and anatomic indicators of late rectal toxicity in prostate cancer patients treated with intensity modulated radiation therapy (IMRT). Data from 49 patients sampled from 698 patients treated for clinically localized prostate cancer at the Memorial Sloan-Kettering Cancer Center with IMRT to a dose of 81 Gy were analyzed. The end point of the study was late Grade 2 or worse rectal toxicity within 30 months of treatment. Dosimetric analysis was performed on the rectum surface in three dimensions and on two-dimensional dose maps obtained by flattening the rectum surface using a conformal mapping procedure. Several parameters including the percentage and absolute surface area of the rectum irradiated, mean dose as a function of location on the rectum, planning target volume (PTV) size and rectum size were analyzed for correlation to toxicity. Significance was set at p < 0.05 for a two-sided t-test. Correlation between absolute areas irradiated and toxicity was observed on both the rectum surface and flattened rectum. Patients with toxicity also received a significantly higher mean dose to the superior 25% of the rectum surface and 15% of the flattened rectum. PTV volume, PTV height, rectum surface area and average cross-sectional area were significantly larger in patients with toxicity. The conformal mapping procedure has potential utility for evaluating dose to the rectum and risk of toxicity. Late rectal toxicity was related to the irradiation of the upper part of the rectum and also to the absolute area irradiated, PTV size, and rectum size on the planning computed tomography (CT) scan.
: In this paper limit theorems for the conditional distributions of linear test statistics are proved. The assertions are conditioned on the #-field of permutation symmetric sets. Limit theorems are proved both for the conditional distributions under the hypothesis of randomness and under general contiguous alternatives with independent but not identically distributed observations. The proofs are based on results on limit theorems for exchangeable random variables by Strasser and Weber, [20]. The limit theorems under contiguous alternatives are consequences of a LAN-result for likelihood ratios of symmetrized product measures. The results of the paper have implications for statistical applications. By example it is shown that minimum variance partitions which are defined by observed data (e.g. by LVQ) lead to asymptotically optimal adaptive tests for the k-sample problem. As another application it is shown that conditional k-sample tests which are based on data-driven partitions lead t...
Adjuvant androgen deprivation impacts late rectal toxicity after conformal radiotherapy of prostate car-cinoma Quantification of local rectal wall dis-placements by virtual rectum unfolding
- M Marcenaro
- V Orsatti
- ͑2002͒ M S Vitale
- M Hoogeman
- J Van Herk
- P De Bois
- P C M Muller-Timmermans
- J V Koper
- Lebesque
Marcenaro, M. Orsatti, and V. Vitale, " Adjuvant androgen deprivation impacts late rectal toxicity after conformal radiotherapy of prostate car-cinoma, " Br. J. Cancer 86, 1843–1847 ͑2002͒. M. S. Hoogeman, M. van Herk, J. de Bois, P. Muller-Timmermans, P. C. M. Koper, and J. V. Lebesque, " Quantification of local rectal wall dis-placements by virtual rectum unfolding, " Radiother. Oncol. 70, 21–30 ͑2004͒.
ter conformal radiotherapy for prostate cancer: normal tissue complication probability 513 modeling
ter conformal radiotherapy for prostate cancer: normal tissue complication probability
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modeling.. " Int J Radiat Oncol Biol Phys 66, 11–19 (2006).
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- M W Skwarchuk
- A Jackson
- M J Zelefsky
- E S Venkatraman
- D M Cowen
- S Lev
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egrün, C. M. Burman, Z. Fuks, S. A. Leibel, and C. C. Ling, " Late rectal toxicity after
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Does the 457 shape of the rectal surface dose distribution predict the risk of late rectal incontinence 458 and bleeding, in patients treated with high-dose 3dcrt for localized prostate cancer
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M. Pasquino, M. Stasi, G. Fellin, V. Vavassori, R. Valdagni, and C. Fiorino, " Does the
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and bleeding, in patients treated with high-dose 3dcrt for localized prostate cancer?. "
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Does the shape of the rectal surface dose distribution predict the risk of late rectal incontinence and bleeding, in patients treated with high-dose 3DCRT for localized prostate cancer?
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A weakly informative default prior distribution for logistic and other regression models
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