Role of radiotherapy in the management of bladder cancer: Recommendations of the French society for radiation oncology.

We present the recommendations of the French society of oncological radiotherapy on the indications and techniques for external beam radiotherapy for bladder cancer.

Implementation of an optimization method for parotid gland sparing during inverse planning for head and neck cancer radiotherapy.

PURPOSE: To guide parotid gland (PG) sparing at the dose planning step, a specific model based on overlap between PTV and organ at risk (Moore et al.) was developed and evaluated for VMAT in head-and-neck (H&N) cancer radiotherapy. MATERIALS AND METHODS: One hundred and sixty patients treated for locally advanced H&N cancer were included. A model optimization was first performed (20 patients) before a model evaluation (110 patients). Thirty cases were planned with and without the model to quantify the PG dose sparing. The inter-operator variability was evaluated on one case, planned by 12 operators with and without the model. The endpoints were PG mean dose (Dmean), PTV homogeneity and number of monitor units (MU). RESULTS: The PG Dmean predicted by the model was reached in 89% of cases. Using the model significantly reduced the PG Dmean: -6.1±4.3Gy. Plans with the model showed lower PTV dose homogeneity and more MUs (+10.5% on average). For the inter-operator variability, PG dose volume histograms without the optimized model were significantly different compared to those with the model; the Dmean standard deviation for the ipsilateral PG decreased from 2.2Gy to 1.2Gy. For the contralateral PG, this value decreased from 2.9Gy to 0.8Gy. CONCLUSION: During the H&N inverse planning, the optimized model guides to the lowest PG achievable mean dose, allowing a significant PG mean dose reduction of -6.1Gy. Integrating this method at the treatment-planning step significantly reduced the inter-patient and inter-operator variabilities.

A density assignment method for dose monitoring in head-and-neck radiotherapy.

BACKGROUND AND PURPOSE: During head-and-neck (H&N) radiotherapy, the parotid glands (PGs) may be overdosed; thus, a tool is required to monitor the delivered dose. This study aimed to assess the dose accuracy of a patient-specific density assignment method (DAM) for dose calculation to monitor the dose to PGs during treatment. PATIENTS AND METHODS: Forty patients with H&N cancer received an intensity modulated radiation therapy (IMRT), among whom 15 had weekly CTs. Dose distributions were calculated either on the CTs (CTref), on one-class CTs (1C-CT, water), or on three-class CTs (3C-CT, water-air-bone). The inter- and intra-patient DAM uncertainties were evaluated by the difference between doses calculated on CTref and 1C-CTs or 3C-CTs. PG mean dose (Dmean) and spinal cord maximum dose (D2%) were considered. The cumulated dose to the PGs was estimated by the mean Dmean of the weekly CTs. RESULTS: The mean (maximum) inter-patient DAM dose uncertainties for the PGs (in cGy) were 23 (75) using 1C-CTs and 12 (50) using 3C-CTs (p ≤ 0.001). For the spinal cord, these uncertainties were 118 (245) and 15 (67; p ≤ 0.001). The mean (maximum) DAM dose uncertainty between cumulated doses calculated on CTs and 3C-CTs was 7 cGy (45 cGy) for the PGs. Considering the difference between the planned and cumulated doses, 53% of the ipsilateral and 80% of the contralateral PGs were overdosed by +3.6 Gy (up to 8.2 Gy) and +1.9 Gy (up to 5.2 Gy), respectively. CONCLUSION: The uncertainty of the three-class DAM appears to be clinically non-significant (<0.5 Gy) compared with the PG overdose (up to 8.2 Gy). This DAM could therefore be used to monitor PG doses and trigger replanning.

Adaptive radiotherapy for head and neck cancer.

INTRODUCTION: Large anatomical variations can be observed during the treatment course intensity-modulated radiotherapy (IMRT) for head and neck cancer (HNC), leading to potential dose variations. Adaptive radiotherapy (ART) uses one or several replanning sessions to correct these variations and thus optimize the delivered dose distribution to the daily anatomy of the patient. This review, which is focused on ART in the HNC, aims to identify the various strategies of ART and to estimate the dosimetric and clinical benefits of these strategies. MATERIAL AND METHODS: We performed an electronic search of articles published in PubMed/MEDLINE and Science Direct from January 2005 to December 2016. Among a total of 134 articles assessed for eligibility, 29 articles were ultimately retained for the review. Eighteen studies evaluated dosimetric variations without ART, and 11 studies reported the benefits of ART. RESULTS: Eight in silico studies tested a number of replanning sessions, ranging from 1 to 6, aiming primarily to reduce the dose to the parotid glands. The optimal timing for replanning appears to be early during the first two weeks of treatment. Compared to standard IMRT, ART decreases the mean dose to the parotid gland from 0.6 to 6 Gy and the maximum dose to the spinal cord from 0.1 to 4 Gy while improving target coverage and homogeneity in most studies. Only five studies reported the clinical results of ART, and three of those studies included a non-randomized comparison with standard IMRT. These studies suggest a benefit of ART in regard to decreasing xerostomia, increasing quality of life, and increasing local control. Patients with the largest early anatomical and dose variations are the best candidates for ART. CONCLUSION: ART may decrease toxicity and improve local control for locally advanced HNC. However, randomized trials are necessary to demonstrate the benefit of ART before using the technique in routine practice.

[External beam radiotherapy cone beam-computed tomography-based dose calculation]. / Calcul de dose de radiothérapie à partir de tomographies coniques : état de l'art.

In external beam radiotherapy, the dose planning is currently based on computed tomography (CT) images. A relation between Hounsfield numbers and electron densities (or mass densities) is necessary for dose calculation taking heterogeneities into account. In image-guided radiotherapy process, the cone beam CT is classically used for tissue visualization and registration. Cone beam CT for dose calculation is also attractive in dose reporting/monitoring perspectives and particularly in a context of dose-guided adaptive radiotherapy. The accuracy of cone beam CT-based dose calculation is limited by image characteristics such as quality, Hounsfield numbers consistency and restrictive sizes of volume acquisition. The analysis of the literature identifies three kinds of strategies for cone beam CT-based dose calculation: establishment of Hounsfield numbers versus densities curves, density override to regions of interest, and deformable registration between CT and cone beam CT images. Literature results show that discrepancies between the reference CT-based dose calculation and the cone beam CT-based dose calculation are often lower than 3%, regardless of the method. However, they can also reach 10% with unsuitable method. Even if the accuracy of the cone beam CT-based dose calculation is independent of the method, some strategies are promising but need improvements in the automating process for a routine implementation.

[MRI-based radiotherapy planning]. / Planification à partir d'imagerie par résonance magnétique en radiothérapie.

MRI-based radiotherapy planning is a topical subject due to the introduction of a new generation of treatment machines combining a linear accelerator and a MRI. One of the issues for introducing MRI in this task is the lack of information to provide tissue density information required for dose calculation. To cope with this issue, two strategies may be distinguished from the literature. Either a synthetic CT scan is generated from the MRI to plan the dose, or a dose is generated from the MRI based on physical underpinnings. Within the first group, three approaches appear: bulk density mapping assign a homogeneous density to different volumes of interest manually defined on a patient MRI; machine learning-based approaches model local relationship between CT and MRI image intensities from multiple data, then applying the model to a new MRI; atlas-based approaches use a co-registered training data set (CT-MRI) which are registered to a new MRI to create a pseudo CT from spatial correspondences in a final fusion step. Within the second group, physics-based approaches aim at computing the dose directly from the hydrogen contained within the tissues, quantified by MRI. Excepting the physics approach, all these methods generate a synthetic CT called "pseudo CT", on which radiotherapy planning will be finally realized. This literature review shows that atlas- and machine learning-based approaches appear more accurate dosimetrically. Bulk density approaches are not appropriate for bone localization. The fastest methods are machine learning and the slowest are atlas-based approaches. The less automatized are bulk density assignation methods. The physical approaches appear very promising methods. Finally, the validation of these methods is crucial for a clinical practice, in particular in the perspective of adaptive radiotherapy delivered by a linear accelerator combined with an MRI scanner.

[Adaptive radiotherapy in routine use? State of the art: The medical physicist's point of view]. / Radiothérapie adaptative en routine ? État de l'art : point de vue du physicien médical.

The development of both image-guided and intensity-modulated radiotherapy has underlined the question of treatment adaptation to anatomical and/or biological changes occurring during radiotherapy course and modifying delivered dose to the patient. Adaptive radiotherapy has been introduced when several plans are used to treat a patient during radiotherapy. Adaptation may be performed online, offline or in a hybrid way. New images of the patient are needed for adaptive radiotherapy to perform many processes: image registration, segmentation and evaluation of cumulative dose. Deformable image registration methods are generally used to image registration and contours propagation. Fraction and cumulative dose evaluations use deformable image registration methods or more complex methods based on Monte-Carlo calculation. These methods have uncertainties and have to be evaluated. However, evaluation and validation tools are still being developed. The physicist's mission is to ensure that every new technology, such as adaptive radiotherapy, is deployed with highest safety, by technical validation and by implementing a specific quality assurance program. Adaptive radiotherapy implementation still raises many questions, so its potential clinical application requires great caution and should be carefully explored in prospective clinical trials.