Practical and technical key challenges in head and neck adaptive radiotherapy: The GORTEC point of view.

Anatomical variations occur during head and neck (H&N) radiotherapy (RT) treatment. These variations may result in underdosage to the target volume or overdosage to the organ at risk. Replanning during the treatment course can be triggered to overcome this issue. Due to technological, methodological and clinical evolutions, tools for adaptive RT (ART) are becoming increasingly sophisticated. The aim of this paper is to give an overview of the key steps of an H&N ART workflow and tools from the point of view of a group of French-speaking medical physicists and physicians (from GORTEC). Focuses are made on image registration, segmentation, estimation of the delivered dose of the day, workflow and quality assurance for an implementation of H&N offline and online ART. Practical recommendations are given to assist physicians and medical physicists in a clinical workflow.

Planning With Patient-Specific Rectal Sub-Region Constraints Decreases Probability of Toxicity in Prostate Cancer Radiotherapy.

Background: A rectal sub-region (SRR) has been previously identified by voxel-wise analysis in the inferior-anterior part of the rectum as highly predictive of rectal bleeding (RB) in prostate cancer radiotherapy. Translating the SRR to patient-specific radiotherapy planning is challenging as new constraints have to be defined. A recent geometry-based model proposed to optimize the planning by determining the achievable mean doses (AMDs) to the organs at risk (OARs), taking into account the overlap between the planning target volume (PTV) and OAR. The aim of this study was to quantify the SRR dose sparing by using the AMD model in the planning, while preserving the dose to the prostate. Material and Methods: Three-dimensional volumetric modulated arc therapy (VMAT) planning dose distributions for 60 patients were computed following four different strategies, delivering 78 Gy to the prostate, while meeting the genitourinary group dose constraints to the OAR: (i) a standard plan corresponding to the standard practice for rectum sparing (STDpl), (ii) a plan adding constraints to SRR (SRRpl), (iii) a plan using the AMD model applied to the rectum only (AMD_RECTpl), and (iv) a final plan using the AMD model applied to both the rectum and the SRR (AMD_RECT_SRRpl). After PTV dose normalization, plans were compared with regard to dose distributions, quality, and estimated risk of RB using a normal tissue complication probability model. Results: AMD_RECT_SRRpl showed the largest SRR dose sparing, with significant mean dose reductions of 7.7, 3, and 2.3 Gy, with respect to the STDpl, SRRpl, and AMD_RECTpl, respectively. AMD_RECT_SRRpl also decreased the mean rectal dose by 3.6 Gy relative to STDpl and by 3.3 Gy relative to SRRpl. The absolute risk of grade ≥1 RB decreased from 22.8% using STDpl planning to 17.6% using AMD_RECT_SRRpl considering SRR volume. AMD_RECT_SRRpl plans, however, showed slightly less dose homogeneity and significant increase of the number of monitor units, compared to the three other strategies. Conclusion: Compared to a standard prostate planning, applying dose constraints to a patient-specific SRR by using the achievable mean dose model decreased the mean dose by 7.7 Gy to the SRR and may decrease the relative risk of RB by 22%.

Technical Note: A simple algorithm to convert EPID gray values into absorbed dose to water without prior knowledge.

PURPOSE: Full integration of EPID-based dosimetry in a global quality control workflow is still complicated. All the actual solutions are based on a relation between image gray-level signal and total linac-delivered dose. In this study, we propose a simple algorithm relying pixel gray-level of EPID image with average linac delivered dose per acquisition frame. METHODS: Calibration models are constructed for Varian and Elekta linacs including scattering conditions and EPID-arm backscatter-specific corrections. Only simple homogeneous fields are required to establish the EPID dose conversion model for each x-ray beam. Then, the model was evaluated by comparing calculated and converted dose distributions for homogeneous and modulated beams using gamma maps. RESULTS: To fit average dose per frame (Dfnorm ) vs pixel gray value (Ngnorm ) of each EPID image, a logarithmic curve Dfnorm=A+B∗lnNgnorm-C, has been chosen where A, B and C are constants depending on beam energy. Gamma comparison (2%, 2 mm, threshold 15%) between converted images and calculated dose distributions for linac control and pretreatment patient fields led to a gamma pass rate higher than 97% for all the analyzed fields. CONCLUSIONS: Without a prior irradiation settings knowledge except the incident energy beam, we use EPID as a reliable dose to water detector for both homogeneous and modulated beams.