Planning issues on linac-based stereotactic radiotherapy

This work aims to summarize and evaluate the current planning progress based on the linear accelerator in stereotactic radiotherapy (SRT). The specific techniques include 3-dimensional conformal radiotherapy, dynamic conformal arc therapy, intensity-modulated radiotherapy, and volumetric-modulated arc therapy (VMAT). They are all designed to deliver higher doses to the target volume while reducing damage to normal tissues; among them, VMAT shows better prospects for application. This paper reviews and summarizes several issues on the planning of SRT to provide a reference for clinical application.

Data-Driven Dose-Volume Histogram Prediction

Purpose

To evaluate dose-volume histogram (DVH) prediction from prior radiation therapy data.

Methods and Materials

An Oncospace radiation therapy database was constructed including images, structures, and dose distributions for patients with advanced lung cancer. DVH data was queried for total lungs, esophagus, heart, and external body contours. Each query returned DVH data for the N-most similar organs at risk (OARs) based on OAR-to-planning-target-volume (PTV) geometry via the overlap volume histogram (OVH). The DVHs for 5, 20, and 50 of the most similar OVHs were returned for each OAR for each patient. The OVH(0cm) is the relative volume of the OAR overlapping with the PTV, and the OVH(2cm) is the relative volume of the OAR 2 cm away from the PTV. The OVH(cm) and DVH(%) queried from the database were separated into interquartile ranges (IQRs), nonoutlier ranges (NORs) (equal to 3 × IQR), and the average database DVH (DVH-DB) computed from the NOR data. The ability to predict the clinically delivered DVH was evaluated based on percentiles and differences between the DVH-DB and the clinical DVH (DVH-CL) for a varying number of returned patient DVHs for a subset of patients.

Results

The ability to predict the clinically delivered DVH was excellent in the lungs and body; the IQR and NOR were <4% and <16%, respectively, in the lungs and <1% and <5%, respectively, in the body at all distances less than 2 cm from the PTV. For 21/23 patients considered, the differences in lung DVH-DB and DVH-CL were <4.6% and in 14/23 cases, <3%. In esophagus and heart, the ability to predict DVH-CL was weaker, with mean DVH differences >10% for 12/23 esophagi and 10/23 hearts. In esophagus and heart queries, the NOR was often 10% to 100% volume in dose ranges between 0% and 50% of prescription, independent of the number of patients queried.

Conclusions

Using prior data to predict clinical dosimetry is increasingly of interest, but model- and data-driven methods have limitations if based on limited data sets. This study's results showed that prediction may be reasonable in organs containing tumors with known overlap, but for nonoverlapped OARs, planning preference and plan design may dominate the clinical dose.

Efficient optimization of R50% when planning multiple cranial metastases simultaneously in single isocenter SRS/SRT

Simultaneous optimization of multiple Planning Target Volumes (PTVs) of varying size and location in the cranium is a non-trivial task. The rate of dose falloff around PTV structures is variable and depends on PTV characteristics such as the volume. The metric R50% is one parameter that can be used to quantify dose falloff achieved in a given treatment plan. An important treatment planning question is how to construct optimization conditions that result in the efficient production of acceptable plan outcomes considering metrics such as R50%. Guidance provided in literature suggests generating multiple shell control structures around each PTV. The constraints applied to these shells can vary significantly depending on PTV volume. Additionally, there is no clear guidance on how to prospectively determine objective constraints for the optimization shells to achieve a specified goal of R50%. Based on physical principles and empirical evidence, we provide clear quantitative guidance on how to translate the desired R50% outcome into appropriately sized optimization structures around PTVs via an equation that depends on a desired goal for R50% and the volume of PTV. Optimization schema are also provided that allow the goal R50% to be approached or achieved for all PTVs individually. We demonstrate the application of the methodology using commercially available treatment planning software and radiotherapy treatment equipment.

The surface area effect: How the intermediate dose spill depends on the PTV surface area in SRS

Purpose

Stereotactic radiosurgery (SRS) is rapidly becoming the standard of care for many intracranial targets. The characteristics of the planning target volume (PTV) can affect the intermediate dose spill and thus normal brain volume dose which is correlated with brain toxicity. R50% (volume receiving 50% of prescription dose divided by PTV volume) is a useful metric to quantify the intermediate dose spill. We propose a novel understanding of how the PTV surface area (SA_PTV) affects the intermediate dose spill of SRS treatments.

Methods

Using a phantom model provided by a computed tomography (CT) of the IROC Head Phantom® and Eclipse® Treatment Planning System, we investigate the relationship of R50% and SA_PTV in single‐target SRS treatments. The planning studies are conducted for SRS treatments on a Varian TrueBeam® linear accelerator with high‐definition MLC and a 6 MVFFF beam mode. These data are analyzed to ascertain trends in R50% related to SA_PTV. Since SA_PTV is not available as a structure property in the Eclipse RTPS, we introduce an Eclipse script to extract PTV surface area of arbitrary‐shaped PTVs. We compare a physically reasonable theoretical prediction of R50%, R50%_Analytic, to the R50% achieved in treatment planning studies.

Results

The SRS phantom study indicates good correlation between the plan R50% and SA_PTV. A near‐linear relationship of plan R50% vs SA_PTV is observed as predicted by the R50%_Analytic model. Agreement between plan R50% values and R50%_Analytic predictions is good for all but the very smallest PTV volumes.

Conclusions

We demonstrate dependence of the intermediate dose spill measured by R50% on the SA_PTV. We call that dependence the surface area effect. This dependence is explicit in the R50%_Analytic prediction model. The predicted value of R50%_Analytic for a given PTV could be used for guidance during SRS treatment plan optimization, and plan evaluation for that PTV.

Cleaning the dose falloff in lung SBRT plan

PURPOSE

To investigate a planning technique that can possibly reduce low-to-intermediate dose spillage (measured by R50%, D2cm values) in lung SBRT plans.

MATERIALS AND METHODS

Dose falloff outside the target was studied retrospectively in 102 SBRT VMAT plans of lung tumor. Plans having R50% and/or D2cm higher than recommended tolerances in RTOG protocols 0813 and 0915 were replanned with new optimization constraints using novel shell structures and novel constraints. Violations in the RTOG R50% value can be rectified with a dose constraint to a novel shell structure ("OptiForR50"). The construction of structure OptiForR50% and the novel optimization criteria translate the RTOG goals for R50% into direct inputs for the optimizer. Violations in the D2cm can be rectified using constraints on a 0.5 cm thick shell structure with inner surface 2cm from the PTV surface. Wilcoxon signed-rank test was used to compare differences in dose conformity, volume of hot spots, R50%, D2cm of the target in addition to the OAR doses. A two-sided P-value of 0.05 was used to assess statistical significance.

RESULTS

Among 102 lung SBRT plans with PTV sizes ranging from 5 to 179 cc, 32 plans with violations in R50% or D2cm were reoptimized. The mean reduction in R50% (4.68 vs 3.89) and D2cm (56.49 vs 52.51) was statistically significant both having P < 0.01. Target conformity index, volume of 105% isodose contour outside PTV, normal lung V20, and mean dose to heart and aorta were significantly lowered with P < 0.05.

CONCLUSION

The novel planning methodology using multiple shells including the novel OptiForR50 shell with precisely calculated dimensions and optimizer constraints lead to significantly lower values of R50% and D2cm and lower dose spillage in lung SBRT plans. All plans were successfully brought into the zone of no RTOG violations.

An analytical expression for R50% dependent on PTV surface area and volume: a lung SBRT comparison

In stereotactic body radiation therapy (SBRT), R50% is a common metric for intermediate dose spill and is defined in RTOG 0915 as the ratio of 50% isodose cloud volume (IDC50%) to the planning target volume (PTV). By coupling sound physical principles with the basic definition of intermediate dose spill, we derive an exact analytical expression for R50% for the case of a spherical volume. This expression for R50% depends on three quantities: the surface area of PTV (SA_PTV), the volume of PTV (V_PTV), and the dose gradient Δr. Validity of our analytical expression for R50% was confirmed via direct comparison to peer‐reviewed, multi‐institutional, diverse clinical data. The comparison of our R50% values computed from our analytical expression to the clinical data yielded an average percent difference of 3.8 ± 4.5%.

Second cancer risk after primary cancer treatment with three-dimensional conformal, intensity-modulated, or proton beam radiation therapy

BACKGROUND

The comparative risks of a second cancer diagnosis are uncertain after primary cancer treatment with 3-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiotherapy (IMRT), or proton beam radiotherapy (PBRT).

METHODS

Pediatric and adult patients with a first cancer diagnosis between 2004 and 2015 who received 3DCRT, IMRT, or PBRT were identified in the National Cancer Database from 9 tumor types: head and neck, gastrointestinal, gynecologic, lymphoma, lung, prostate, breast, bone/soft tissue, and brain/central nervous system. The diagnosis of second cancer was modeled using multivariable logistic regression adjusting for age, follow-up duration, radiotherapy (RT) dose, chemotherapy, sociodemographic variables, and other factors. Propensity score matching also was used to balance baseline characteristics.

RESULTS

In total, 450,373 patients were identified (33.5% received 3DCRT, 65.2% received IMRT, and 1.3% received PBRT) with median follow-up of 5.1 years after RT completion and a cumulative follow-up period of 2.54 million person-years. Overall, the incidence of second cancer diagnosis was 1.55 per 100 patient-years. In a comparison between IMRT versus 3DCRT, there was no overall difference in the risk of second cancer (adjusted odds ratio [OR], 1.00; 95% CI, 0.97-1.02; P = .75). By comparison, PBRT had an overall lower risk of second cancer versus IMRT (adjusted OR, 0.31; 95% CI, 0.26-0.36; P < .0001). Results within each tumor type generally were consistent in the pooled analyses and also were maintained in propensity score-matched analyses.

CONCLUSIONS

The risk of a second cancer diagnosis was similar after IMRT versus 3DCRT, whereas PBRT was associated with a lower risk of second cancer risk. Future work is warranted to determine the cost-effectiveness of PBRT and to identify the population best suited for this treatment.

Estimation of dosimetric discrepancy due to use of Onyx™ embolic system in Stereotactic Radiosurgery/Radiotherapy (SRS/SRT) planning

More often the embolic materials in the brain create artefacts in the planning CT images that could lead to a dose variation in planned and delivered dose. The aim of the study was to evaluate the dosimetric effect of artefacts generated by the Onyx™ embolization material during Stereotactic Radiosurgery/Radiotherapy (SRS/SRT) planning. An in-house made novel Polymethyl Methacrylate (PMMA) head phantom (specially designed for SRS/SRT plans) was used for this purpose. For the evaluation process, we have created concentric ring structures around the central Onyx materials on both the CT sets (with and without Onyx material). The verification plans were generated using different algorithms namely Analytical Anisotropic Algorithm (AAA), Acuros XB and Monaco based Monte Carlo on both CT sets. Mean integral dose over the region of interest were calculated in both CT sets. The dosimetric results shows, due to the presence of Onyx material, relative variation in mean integral dose to the proximal structure (Ring 1) were -4.02%, -2.98%, and -2.49% for Monte Carlo, Acuros XB, and AAA respectively. Observed variations are attributed to the presence of artefacts due to Onyx material. Artefacts influence the accuracy of dose calculation during the planning. All the calculation algorithms are not equally capable to account such variations. Special cares are to be taken while choosing the calculation algorithms as it impacts the results of treatment outcome.

A fast deep learning approach for beam orientation optimization for prostate cancer treated with intensity-modulated radiation therapy

PURPOSE

Beam orientation selection, whether manual or protocol-based, is the current clinical standard in radiation therapy treatment planning, but it is tedious and can yield suboptimal results. Many algorithms have been designed to optimize beam orientation selection because of its impact on treatment plan quality, but these algorithms suffer from slow calculation of the dose influence matrices of all candidate beams. We propose a fast beam orientation selection method, based on deep learning neural networks (DNN), capable of developing a plan comparable to those developed by the state-of-the-art column generation (CG) method. Our model's novelty lies in its supervised learning structure (using CG to teach the network), DNN architecture, and ability to learn from anatomical features to predict dosimetrically suitable beam orientations without using dosimetric information from the candidate beams. This may save hours of computation.

METHODS

A supervised DNN is trained to mimic the CG algorithm, which iteratively chooses beam orientations one-by-one by calculating beam fitness values based on Karush-Kush-Tucker optimality conditions at each iteration. The DNN learns to predict these values. The dataset contains 70 prostate cancer patients - 50 training, 7 validation, and 13 test patients - to develop and test the model. Each patient's data contains 6 contours: PTV, body, bladder, rectum, and left and right femoral heads. Column generation was implemented with a GPU-based Chambolle-Pock algorithm, a first-order primal-dual proximal-class algorithm, to create 6270 plans. The DNN trained over 400 epochs, each with 2500 steps and a batch size of 1, using the Adam optimizer at a learning rate of 1 × 10-5 and a sixfold cross-validation technique.

RESULTS

The average and standard deviation of training, validation, and testing loss functions among the six folds were 0.62 ± 0.09%, 1.04 ± 0.06%, and 1.44 ± 0.11%, respectively. Using CG and supervised DNN, we generated two sets of plans for each scenario in the test set. The proposed method took at most 1.5 s to select a set of five beam orientations and 300 s to calculate the dose influence matrices for 5 beams and finally 20 s to solve the fluence map optimization (FMO). However, CG needed around 15 h to calculate the dose influence matrices of all beams and at least 400 s to solve both the beam orientation selection and FMO problems. The differences in the dose coverage of PTV between plans generated by CG and by DNN were 0.2%. The average dose differences received by organs at risk were between 1 and 6 percent: Bladder had the smallest average difference in dose received (0.956 ± 1.184%), then Rectum (2.44 ± 2.11%), Left Femoral Head (6.03 ± 5.86%), and Right Femoral Head (5.885 ± 5.515%). The dose received by Body had an average difference of 0.10 ± 0.1% between the generated treatment plans.

CONCLUSIONS

We developed a fast beam orientation selection method based on a DNN that selects beam orientations in seconds and is therefore suitable for clinical routines. In the training phase of the proposed method, the model learns the suitable beam orientations based on patients' anatomical features and omits time intensive calculations of dose influence matrices for all possible candidate beams. Solving the FMO to get the final treatment plan requires calculating dose influence matrices only for the selected beams.

Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose-volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy

PURPOSE

We propose a novel domain-specific loss, which is a differentiable loss function based on the dose-volume histogram (DVH), and combine it with an adversarial loss for the training of deep neural networks. In this study, we trained a neural network for generating Pareto optimal dose distributions, and evaluate the effects of the domain-specific loss on the model performance.

METHODS

In this study, three loss functions - mean squared error (MSE) loss, DVH loss, and adversarial (ADV) loss - were used to train and compare four instances of the neural network model: (a) MSE, (b) MSE + ADV, (c) MSE + DVH, and (d) MSE + DVH+ADV. The data for 70 prostate patients, including the planning target volume (PTV), and the organs at risk (OAR) were acquired as 96 × 96 × 24 dimension arrays at 5 mm3 voxel size. The dose influence arrays were calculated for 70 prostate patients, using a 7 equidistant coplanar beam setup. Using a scalarized multicriteria optimization for intensity-modulated radiation therapy, 1200 Pareto surface plans per patient were generated by pseudo-randomizing the PTV and OAR tradeoff weights. With 70 patients, the total number of plans generated was 84 000 plans. We divided the data into 54 training, 6 validation, and 10 testing patients. Each model was trained for a total of 100,000 iterations, with a batch size of 2. All models used the Adam optimizer, with a learning rate of 1 × 10-3 .

RESULTS

Training for 100 000 iterations took 1.5 days (MSE), 3.5 days (MSE+ADV), 2.3 days (MSE+DVH), and 3.8 days (MSE+DVH+ADV). After training, the prediction time of each model is 0.052 s. Quantitatively, the MSE+DVH+ADV model had the lowest prediction error of 0.038 (conformation), 0.026 (homogeneity), 0.298 (R50), 1.65% (D95), 2.14% (D98), and 2.43% (D99). The MSE model had the worst prediction error of 0.134 (conformation), 0.041 (homogeneity), 0.520 (R50), 3.91% (D95), 4.33% (D98), and 4.60% (D99). For both the mean dose PTV error and the max dose PTV, Body, Bladder and rectum error, the MSE+DVH+ADV outperformed all other models. Regardless of model, all predictions have an average mean and max dose error <2.8% and 4.2%, respectively.

CONCLUSION

The MSE+DVH+ADV model performed the best in these categories, illustrating the importance of both human and learned domain knowledge. Expert human domain-specific knowledge can be the largest driver in the performance improvement, and adversarial learning can be used to further capture nuanced attributes in the data. The real-time prediction capabilities allow for a physician to quickly navigate the tradeoff space for a patient, and produce a dose distribution as a tangible endpoint for the dosimetrist to use for planning. This is expected to considerably reduce the treatment planning time, allowing for clinicians to focus their efforts on the difficult and demanding cases.

Leukoencephalopathy After Stereotactic Radiosurgery for Brain Metastases

PURPOSE

Although the use of stereotactic radiosurgery (SRS) in the treatment of multiple brain metastases has increased dramatically during the past decade to avoid the neurocognitive dysfunction induced by whole brain radiation therapy (WBRT), the cumulative neurocognitive effect of numerous SRS sessions remains unknown. Because leukoencephalopathy is a sensitive marker for radiation-induced central nervous system damage, we studied the clinical and dosimetric predictors of SRS-induced leukoencephalopathy.

METHODS AND MATERIALS

Patients treated at our institution with at least 2 sessions of SRS for brain metastases from 2007 to 2013 were reviewed. The pre- and post-SRS magnetic resonance imaging sequences were reviewed and graded for white matter changes associated with radiation leukoencephalopathy using a previously validated scale. Patient characteristics and SRS dosimetric parameters were reviewed for factors that contributed to leukoencephalopathy using Cox proportional hazards modeling.

RESULTS

A total of 103 patients meeting the inclusion criteria were identified. The overall incidence of leukoencephalopathy was 29% at year 1, 38% at year 2, and 53% at year 3. Three factors were associated with radiation-induced leukoencephalopathy: (1) the use of WBRT (P=.019); (2) a higher SRS integral dose to the cranium (P=.036); and (3) the total number of intracranial metastases (P=.003).

CONCLUSIONS

Our results have established that WBRT plus SRS produces leukoencephalopathy at a much higher rate than SRS alone. In addition, for patients who did not undergo WBRT before SRS, the integral dose was associated with the development of leukoencephalopathy. As the survival of patients with central nervous system metastases increases and as the neurotoxicity of chemotherapeutic and targeted agents becomes established, these 3 potential risk factors will be important to consider.

Utilization of intensity-modulated radiation therapy and image-guided radiation therapy in pancreatic cancer: is it beneficial?

The recent development of intensity-modulated radiation therapy (IMRT) and improvements in image-guided radiotherapy (IGRT) have provided considerable advances in the utilization of radiation therapy (RT) for the management of pancreatic cancer. IGRT allows for the reduction of treatment volumes, potentially less chance of a marginal miss, and quality assurance of gastrointestinal filling, while IMRT has been shown to reduce both sudden and late side effects compared with 3-dimensional conformal RT. Here, we review published data and provide essential recommendations on the utilization of IMRT and IGRT for the management of patients with pancreatic cancer.

Feasibility of extreme dose escalation for glioblastoma multiforme using 4π radiotherapy

Background

Glioblastoma multiforme (GBM) frequently recurs at the same location after radiotherapy. Further dose escalation using conventional methods is limited by normal tissue tolerance. 4π non-coplanar radiotherapy has recently emerged as a new potential method to deliver highly conformal radiation dose using the C-arm linacs. We aim to study the feasibility of very substantial GBM dose escalation while maintaining normal tissue tolerance using 4π.

Methods

11 GBM patients previously treated with volumetric modulated arc therapy (VMAT/RapidArc) on the NovalisTx™ platform to a prescription dose of either 59.4 Gy or 60 Gy were included. All patients were replanned with 30 non-coplanar beams using a 4π radiotherapy platform, which inverse optimizes both beam angles and fluence maps. Four different prescriptions were used including original prescription dose and PTV (4πPTV_PD), 100 Gy to the PTV and GTV (4πPTV_100Gy), 100 Gy to the GTV only while maintaining prescription dose to the rest of the PTV (4πGTV_100Gy), and a 5 mm margin expansion plan (4πPTV_PD+5mm). OARs included in the study are the normal brain (brain – PTV), brainstem, chiasm, spinal cord, eyes, lenses, optical nerves, and cochleae.

Results

The 4π plans resulted in superior dose gradient indices, as indicated by >20% reduction in the R50, compared to the clinical plans. Among all of the 4π cases, when compared to the clinical plans, the maximum and mean doses were significantly reduced (p < 0.05) by a range of 47.01-98.82% and 51.87-99.47%, respectively, or unchanged (p > 0.05) for all of the non-brain OARs. Both the 4πPTV_PD and 4π GTV_100GYplans reduced the mean normal brain mean doses.

Conclusions

4π non-coplanar radiotherapy substantially increases the dose gradient outside of the PTV and better spares critical organs. Dose escalation to 100 Gy to the GTV or additional margin expansion while meeting clinical critical organ dose constraints is feasible. 100 Gy to the PTV result in higher normal brain doses but may be tolerated when delivered in proportionally increased treatment fractions. Therefore, 4π non-coplanar radiotherapy on C-arm gantry may provide an accessible tool to improve the outcome of GBM radiotherapy through extreme dose escalation.

Dosimetric Evaluation of Volumetric-Modulated Arc Therapy (RapidArc) for Primary Leiomyosarcoma in the Spine

This study aims to investigate the suitability of volumetric-modulated arc therapy (VMAT) with RapidArc for primary leiomyosarcoma (LMS) in the spine, and present a new method to improve the target coverage and organs at risk (OAR) sparing. Five patients with LMS were retrospectively reviewed. The intensity-modulated radiotherapy (IMRT) with five coplanar beams (5b-IMRT) or seven coplanar beams (7b-IMRT), and VMAT using four quasi-quarter coplanar arcs (4q-VMAT) or two full coplanar arcs (2f-VMAT) were generated. Planning target volume (PTV) dose coverage, OAR dose sparing, conformity index (CI), and homogeneity index (HI) were evaluated. A hollow-cylinder model (HCM) was also used for feasible optimal beam arrangements. The mean doses to PTV were 95.2% ± 1.0%, 93.0% ± 1.0%, 97.9% ± 1.0% and 96.2% ± 1.5% for 4q-VMAT, 2f-VMAT, 5b-IMRT and 7b-IMRT respectively, while the mean maximum doses to spinal cord (SC) were 43.7 ± 0.9 Gy, 42.0 ± 0.8 Gy, 41.4 ± 1.2 Gy and 40.6 ± 1.4 Gy. Compared to 5b-IMRT, the mean doses delivered to kidneys decreased by about 35.1% (8.5 Gy), 2.5% (0.6 Gy) and 35.5% (8.6 Gy) for 4q-VMAT, 2f-VMAT, and 7b-IMRT, respectively. The CI proposed by Baltas et al. was twice as good with IMRT than with 4q-VMAT, and the numbers of monitor units were increased five- and threefold with 7b-IMRT and with 5b-IMRT compared to VMAT. The unexpected results we presented here show that VMAT technique can't achieve highly conformal treatment plans while maintaining SC sparing for LMS in the spine. An approach is proposed based on a hollow-cylinder model, but it is difficult to apply to clinical practice. In this case, VMAT is not superior to IMRT except for significant reduction in delivery time.

Dose escalation to high-risk sub-volumes based on non-invasive imaging of hypoxia and glycolytic activity in canine solid tumors: a feasibility study

INTRODUCTION

Glycolytic activity and hypoxia are associated with poor prognosis and radiation resistance. Including both the tumor uptake of 2-deoxy-2-[18 F]-fluorodeoxyglucose (FDG) and the proposed hypoxia tracer copper(II)diacetyl-bis(N4)-methylsemithio-carbazone (Cu-ATSM) in targeted therapy planning may therefore lead to improved tumor control. In this study we analyzed the overlap between sub-volumes of FDG and hypoxia assessed by the uptake of 64Cu-ATSM in canine solid tumors, and evaluated the possibilities for dose redistribution within the gross tumor volume (GTV).

MATERIALS AND METHODS

Positron emission tomography/computed tomography (PET/CT) scans of five spontaneous canine solid tumors were included. FDG-PET/CT was obtained at day 1, 64Cu-ATSM at day 2 and 3 (3 and 24 h pi.). GTV was delineated and CT images were co-registered. Sub-volumes for 3 h and 24 h 64Cu-ATSM (Cu3 and Cu24) were defined by a threshold based method. FDG sub-volumes were delineated at 40% (FDG40) and 50% (FDG50) of SUVmax. The size of sub-volumes, intersection and biological target volume (BTV) were measured in a treatment planning software. By varying the average dose prescription to the tumor from 66 to 85 Gy, the possible dose boost (DB) was calculated for the three scenarios that the optimal target for the boost was one, the union or the intersection of the FDG and 64Cu-ATSM sub-volumes.

RESULTS

The potential boost volumes represented a fairly large fraction of the total GTV: Cu3 49.8% (26.8-72.5%), Cu24 28.1% (2.4-54.3%), FDG40 45.2% (10.1-75.2%), and FDG50 32.5% (2.6-68.1%). A BTV including the union (∪) of Cu3 and FDG would involve boosting to a larger fraction of the GTV, in the case of Cu3∪FDG40 63.5% (51.8-83.8) and Cu3∪FDG50 48.1% (43.7-80.8). The union allowed only a very limited DB whereas the intersection allowed a substantial dose escalation.

CONCLUSIONS

FDG and 64Cu-ATSM sub-volumes were only partly overlapping, suggesting that the tracers offer complementing information on tumor physiology. Targeting the combined PET positive volume (BTV) for dose escalation within the GTV results in a limited DB. This suggests a more refined dose redistribution based on a weighted combination of the PET tracers in order to obtain an improved tumor control.

Feasibility of non-coplanar tomotherapy for lung cancer stereotactic body radiation therapy

To quantify the dosimetric gains from non-coplanar helical tomotherapy (HT) arcs for stereotactic body radiation therapy (SBRT) of lung cancer, we created oblique helical arcs by rotating patient's CT images. Ten, 20 and 30 degrees of yaws were introduced in the treatment planning for a patient with a hypothetical lung tumor at the upper, middle and lower portion of the right lung, and the upper and middle left lung. The planning target volume (PTV) was 43 cm(3). 60 Gy was prescribed to the PTV. Dose to organs at risk (OARs), which included the lungs, heart, spinal cord and chest wall, was optimized using a 2.5 cm jaw, 0.287 pitch and modulation factor of 2.5. Composite plans were generated by dose summation of the resultant plans. These plans were evaluated for its conformity index (R(x)) and percentile volume of lung receiving radiation dose of x Gy (V(x)). Conformity index was defined by the ratio of x percent isodose volume and PTV. The results show that combination of non-coplanar arcs reduced R(50) by 4.5%, R(20) by 26% and R(10) by 30% on average. Non-coplanar arcs did not affect V(20) but reduced V(10) and V(5) by 10% and 24% respectively. Composite of the non-coplanar arcs also reduced maximum dose to the spinal cord by 20-39%. Volume of chest wall receiving higher than 30 Gy was reduced by 48% on average. Heart dose reduction was dependent on the location of the PTV and the choice of non-coplanar orientations. Therefore we conclude that non-coplanar HT arcs significantly improve critical organ sparing in lung SBRT without changing the PTV dose coverage.

[Intensity modulated radiotherapy as adjuvant post-operative treatment for retroperitoneal sarcoma: acute toxicity]

PURPOSE

To assess the acute toxicity of intensity modulated radiotherapy as post-operative adjuvant treatment for retroperitoneal sarcoma.

PATIENTS AND METHODS

Patients who received adjuvant intensity modulated radiotherapy from January 2009 to September 2010 were retrospectively reviewed.

RESULTS

Fourteen patients entered the study (seven primary tumours and seven relapses). All tumours were liposarcoma and had macroscopically complete resection, epiploplasty was systematically realized. Median tumour size was 21 cm (range: 15-45), median planning target volume was 580 cm(3) (range: 329-1172) and median prescribed dose was 50.4 Gy (range: 45-54). Median follow-up was 11.5 months (range: 2-21.4). Acute toxicity was mild: acute digestive toxicity grade 1-2 occurred in 12/14 patients (86%). However, there was no weight loss of more than 5% during radiotherapy and no treatment interruption was required. Two months after completion of radiotherapy, digestive toxicity grade 1 remained present in 1/14 patients (7%). One case of grade 3 toxicity occurred during follow-up (transient abdominal pain). Three relapses occurred: two were outside treaded volume and one was both in and outside treated volume.

CONCLUSIONS

Intensity modulated radiotherapy in the postoperative setting of retroperitoneal sarcoma provides low acute toxicity. Longer follow-up is needed to assess late toxicity, especially for bowel, kidney and radio-induced malignancies.

IMRT or conformal radiotherapy for adjuvant treatment of retroperitoneal sarcoma?

PURPOSE

To compare the dose distribution between three-dimensional conformal radiotherapy (3DCRT), intensity modulated radiotherapy (IMRT) with six coplanar beams (6b-IMRT) and IMRT with nine coplanar beams (9b-IMRT) during adjuvant radiotherapy for retroperitoneal sarcoma.

METHODS AND MATERIALS

The 10 most recent patients who had received adjuvant radiotherapy were reviewed. Three different treatment plans were generated (3DCRT, 6b-IMRT and 9b-IMRT) to deliver 50.4 Gy in 28 fractions. The dose delivered to the organs at risk (intestinal cavity (IC), contra- and ipsilateral kidney, liver, stomach and whole body), and the conformity index (CI) were compared.

RESULTS

The integral dose to the intestinal cavity was similar with the three modalities but the dose distribution was different, with a change-over around 25 Gy: the V50 and the V40 were reduced five- and twofold, respectively, with IMRT compared to 3DCRT, and the V20 was increased by about 25% with IMRT. A similar integral dose was delivered to the whole body with the three modalities. The treated volume (V95 body) was approximately halved with IMRT compared to 3DCRT, and the CI was twice as good with IMRT than with 3DCRT. As expected, the V5 (body) was higher with IMRT compared to 3DCRT (p<0.0001) (a 12% increase with 6b-IMRT and a 21% increase with 9b-IMRT). Compared to 3DCRT, the mean dose delivered to the contralateral kidney increased from 1.5 to 4-4.4 Gy with IMRT. The number of monitor units was increased with IMRT, especially when nine beams were used instead of six.

CONCLUSIONS

As expected, IMRT greatly reduced the high-dose irradiated volume and increased the low-dose exposure of the intestinal cavity, with a change-over around 25 Gy, compared to 3DCRT. The conformity index was compellingly better with IMRT. The integral dose delivered to the whole body was conserved with both 3DCRT and IMRT. Longer follow-up is needed to assess late toxicities to the small bowel, contralateral kidney and the risk of second cancers.

A comparison of three different adaptive strategies in image-guided radiotherapy of bladder cancer

The urinary bladder shows considerable individual variation in shape and position during a course of radiotherapy (RT). In this study we have developed and compared three different adaptive RT (ART) strategies for bladder cancer involving daily cone beam CT (CBCT) imaging and plan selection.

MATERIAL AND METHODS

Ten patients treated for bladder cancer had daily CBCTs acquired that were registered online using bony anatomy registration. Seven patients received intensity modulated RT (IMRT) with a simultaneous integrated boost (SIB) technique to the bladder and pelvic lymph nodes. Three patients received treatment to the bladder only. Retrospectively, we compared three ART strategies that were all based on daily selection of the most suitable plan from a library consisting of three IMRT-plans corresponding to a small, medium and large target volume. ART method A utilised population-based margins while methods B and C used the bladder as seen on CBCT-scans from the first week of treatment; method B without delineation of the bladder on CBCT and method C with delineation of the bladder. Total dose distributions were calculated using the planning CT. For each patient, we calculated ratios of the dose volume histograms (DVHs) for the three ART strategies relative to non-adaptive therapy.

RESULTS

The inter-patient variation was large for all three ART strategies. The mean ratios of the volumes receiving 57 Gy or more (corresponding to 95% of prescribed dose) for methods A, B and C were 0.66 (SD: 0.11), 0.67 (SD: 0.13) and 0.67 (SD: 0.16) respectively when compared to the non-adaptive plan.

CONCLUSION

When using any of the ART strategies, it is possible to reduce significantly the volumes receiving high doses compared to the use of a standard non-adaptive plan. The differences in dose volume parameters between the three methods were small compared with the differences from the standard plan.

[IMRT combined to IGRT: increase of the irradiated volume. Consequences?]

Image-guided radiotherapy (IGRT) combined or not with intensity-modulated radiation therapy (IMRT) are new and very useful techniques. However, these new techniques are responsible of irradiation at low dose in large volumes. The control of alignment, realignment of the patient and target positioning in external beam radiotherapy are increasingly performed by radiological imaging devices. The management of this medical imaging depends on the practice of each radiotherapy centre. The physical doses due to the IGRT are however quantifiable and traceable. In one hand, these doses appear justified for a better targeting and could be considered negligible in the context of radiotherapy. On the other hand, the potential impact of these low doses should deserve the consideration of professionals. It appears important therefore to report and consider not only doses in target volumes and in "standard" organs at risk, but also the volume of all tissue receiving low doses of radiation. The recent development of IMRT launches the same issue concerning the effects of low doses of radiation. Indeed, IMRT increases the volume of healthy tissue exposed to radiation. At low dose (<100mGy), many parameters have to be considered for health risk estimations: the induction of genes and activation of proteins, bystander effect, radio-adaptation, the specific low-dose radio-hypersensitivity and individual radiation sensitivity. With the exception of the latter, the contribution of these parameters is generally protective in terms of carcinogenesis. An analysis of secondary cancers arising out of field appears to confirm such notion. The risk of secondary tumours is not well known in these conditions of treatment associating IMRT and IGRT. It is therefore recommended that the dose due to imaging during therapeutic irradiation be reported.

Using Bayesian logistic regression to evaluate a new type of dosimetric constraint for prostate radiotherapy treatment planning

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

The minimum knowledge base for predicting organ-at-risk dose-volume levels and plan-related complications in IMRT planning

IMRT treatment planning requires consideration of two competing objectives: achieving the required amount of radiation for the planning target volume and minimizing the amount of radiation delivered to all other tissues. It is important for planners to understand the tradeoff between competing factors so that the time-consuming human interaction loop (plan-evaluate-modify) can be eliminated. Treatment-plan-surface models have been proposed as a decision support tool to aid treatment planners and clinicians in choosing between rival treatment plans in a multi-plan environment. In this paper, an empirical approach is introduced to determine the minimum number of treatment plans (minimum knowledge base) required to build accurate representations of the IMRT plan surface in order to predict organ-at-risk (OAR) dose-volume (DV) levels and complications as a function of input DV constraint settings corresponding to all involved OARs in the plan. We have tested our approach on five head and neck patients and five whole pelvis/prostate patients. Our results suggest that approximately 30 plans were sufficient to predict DV levels with less than 3% relative error in both head and neck and whole pelvis/prostate cases. In addition, approximately 30-60 plans were sufficient to predict saliva flow rate with less than 2% relative error and to classify rectal bleeding with an accuracy of 90%.