sCT and Dose Calculation

International audienceMagnetic resonance imaging (MRI) has recently established itself as a new standard in radiatiotherapy, owing to its high soft tissue contrast enabling a significantly more accurate volume segmentation and better characterisation of anatomical changes during treatments. The underlying synthetic computed tomography (sCT), required in clinics implementation for dose computation, is extensively investigated in this chapter. First, the generation methods, including bulk density assignment, atlas-based and voxel-based approaches, as well as the associated pros/cons, are described. An appealing compromise between ease, efficiency, and speed is bulk density assignment, which is already implemented in one commercial MRI-Linac. Very recently, however, deep learning has gained the upper hand and is set to become the reference method in clinical practice in the very near future. Second, the metrics to perform a multi-criteria sCT image quality evaluation are provided, as well as the latest performance obtained in the literature. High interest metrics include the body mean absolute error, dose volume histograms differences, global gamma indices with low-/high-dose thresholds, and metrics characterising registration differences between online positioning images and sCT/CT images. These metrics are complementary and enable to respectively assess Hounsfield units recovery, organ-scale dosimetric agreement, global dosimetric agreement in low-/high-dose regions, and patient setup ability. Third, after a reminder of some of the basics of distortions and artefacts in MR imaging, the latest recommendations in terms of assurance quality are described, with the ultimate aim of maximising the quality of the sCT produced. A particular focus is made on B0 inhomogeneities, residual gradient non-linearity, and susceptibility artefacts, owing to their high occurrence in clinical routine. Lastly, a concrete literature review of commercially available sCT products implementations into clinics, either with conventional linear accelerators (Linac) or with hybrid MRI-Linac, is provided. The associated performance, based on the metrics described in the second section, are also included

PET and MRI guided adaptive radiotherapy: Rational, feasibility and benefit

International audienceAdaptive radiotherapy (ART) corresponds to various replanning strategies aiming to correct for anatomical variations occurring during the course of radiotherapy. The goal of the article was to report the rational, feasibility and benefit of using PET and/or MRI to guide this ART strategy in various tumor localizations. The anatomical modifications defined by scanner taking into account tumour mobility and volume variation are not always sufficient to optimise treatment. The contribution of functional imaging by PET or the precision of soft tissue by MRI makes it possible to consider optimized ART. Today, the most important data for both PET and MRI are for lung, head and neck, cervical and prostate cancers. PET and MRI guided ART appears feasible and safe, however in a very limited clinical experience. Phase I/II studies should be therefore performed, before proposing cost-effectiveness comparisons in randomized trials and before using the approach in routine practice

Determination of acceptable Hounsfield units uncertainties via a sensitivity analysis for an accurate dose calculation in the context of prostate MRI-only radiotherapy

International audienceRadiation therapy is moving from CT based to MRI guided planning, particularly for soft tissue anatomy. An important requirement of this new workflow is the generation of synthetic-CT (sCT) from MRI to enable treatment dose calculations. Automatic methods to determine the acceptable range of CT Hounsfield Unit (HU) uncertainties to avoid dose distribution errors is thus a key step toward safe MRI-only radiotherapy. This work has analysed the effects of controlled errors introduced in CT scans on the delivered radiation dose for prostate cancer patients. Spearman correlation coefficient has been computed, and a global sensitivity analysis performed following the Morris screening method. This allows the classification of different error factors according to their impact on the dose at the isocentre. sCT HU estimation errors in the bladder appeared to be the least influential factor, and sCT quality assessment should not only focus on organs surrounding the radiation target, as errors in other soft tissue may significantly impact the dose in the target volume. This methodology links dose and intensity-based metrics, and is the first step to define a threshold of acceptability of HU uncertainties for accurate dose planning

External beam radiotherapy cone beam computed tomography-based dose calculation

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Highlights from the 59th scientific congress of the French Society of Medical Physics

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The dosimetric parameters impact on local recurrence in stereotactic radiotherapy for brain metastases

International audienceObjectives: Stereotactic radiotherapy (SRT) for brain metastases (BM) allows very good local control (LC). However, approximately 20 to 30% of these lesions will recur. The objective of this retrospective study was to evaluate the impact of dosimetric parameters on LC in cerebral SRT.Methods: Patients treated with SRT for 1-3 BM between January 2015 and December 2018 were retrospectively included. A total of 349 patients with 538 lesions were included. The median gross tumor volume (GTV) was 2 cm3 (IQR, 0-7). The median biological effective dose with α/β = 10 (BED10) was 60 Gy (IQR, 32-82). The median prescription isodose was 71% (IQR, 70-80). Correlations with LC were examined using the Cox regression model.Results: The median follow-up period was 55 months (min-max, 7-85). Median overall survival was 17.8 months (IQR, 15.2-21.9). There were 95 recurrences and LC at 1 and 2 years was 87.1% (95% CI, 84-90) and 78.1% (95% CI, 73.9-82.4), respectively. Univariate analysis showed that systemic treatment, dose to 2% and 50% of the planning target volume (PTV), BED10 > 50 Gy, and low PTV and GTV volume were significantly correlated with better LC. In the multivariate analysis, GTV volume, isodose, and BED10 were significantly associated with LC.Conclusion: These results show the importance of a BED10 > 50 Gy associated with a prescription isodose <80% to optimize LC during SRT for BM

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

International audienceBackground: 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%

Contour-guided deep learning based deformable image registration for dose monitoring during CBCT-guided radiotherapy of prostate cancer

Purpose: To evaluate deep learning (DL)-based deformable image registration (DIR) for dose accumulation during radiotherapy of prostate cancer patients.Methods and materials: Data including 341 CBCTs (209 daily, 132 weekly) and 23 planning CTs from 23 patients was retrospectively analyzed. Anatomical deformation during treatment was estimated using free-form deformation (FFD) method from Elastix and DL-based VoxelMorph approaches. The VoxelMorph method was investigated using anatomical scans (VMorph_Sc) or label images (VMorph_Msk), or the combination of both (VMorph_Sc_Msk). Accumulated doses were compared with the planning dose.Results: The DSC ranges, averaged for prostate, rectum and bladder, were 0.60-0.71, 0.67-0.79, 0.93-0.98, and 0.89-0.96 for the FFD, VMorph_Sc, VMorph_Msk, and VMorph_Sc_Msk methods, respectively. When including both anatomical and label images, VoxelMorph estimated more complex deformations resulting in heterogeneous determinant of Jacobian and higher percentage of deformation vector field (DVF) folding (up to a mean value of 1.90% in the prostate). Large differences were observed between DL-based methods regarding estimation of the accumulated dose, showing systematic overdosage and underdosage of the bladder and rectum, respectively. The difference between planned mean dose and accumulated mean dose with VMorph_Sc_Msk reached a median value of +6.3 Gy for the bladder and -5.1 Gy for the rectum.Conclusion: The estimation of the deformations using DL-based approach is feasible for male pelvic anatomy but requires the inclusion of anatomical contours to improve organ correspondence. High variability in the estimation of the accumulated dose depending on the deformable strategy suggests further investigation of DL-based techniques before clinical deployment

Voxel-wise analysis for spatial characterisation of pseudo-ct errors in MRI-only radiotherapy planning

International audienceSeveral approaches have been proposed to generate pseudo computed tomography (pCT) from MR images for radiotherapy dose calculation. Quantification of errors in pCT has been reported using global scores disregarding spatial heterogeneity. The aim of this work was to propose a population voxel-based workflow allowing the local assessment of errors in the generation of pCTs from MRI. For the voxel-wise analysis to be anatomically meaningful, a robust customized inter-patient non-rigid registration method brought the population images to the same coordinate system. To illustrate the use of this methodology, four pCT generation methods were compared: atlas-based, patch-based, and two deep learning methods. Considering global and local scores, deep learning appeared widely superior. Main source of errors were found in the cortical bones. The proposed workflow paves the way for quality control procedures within the clinical workflow. © 2021 IEEE

Pseudo-CT generation for MRI-only radiotherapy treatment planning comparison between patch-based, atlas-based, and bulk density methods

International audiencePurpose - Methods have been recently developed to generate pseudo-computed tomography (pCT) for dose calculation in magnetic resonance imaging (MRI)-only radiation therapy. This study aimed to propose an original nonlocal mean patch-based method (PBM) and to compare this PBM to an atlas-based method (ABM) and to a bulk density method (BDM) for prostate MRI-only radiation therapy. Materials and methods - Thirty-nine patients received a volumetric modulated arc therapy for prostate cancer. In addition to the planning computed tomography (CT) scans, T2-weighted MRI scans were acquired. pCTs were generated from MRIs using 3 methods: an original nonlocal mean PBM, ABM, and BDM. The PBM was performed using feature extraction and approximate nearest neighbor search in a training cohort. The PBM accuracy was evaluated in a validation cohort by using imaging and dosimetric endpoints. Imaging endpoints included mean absolute error and mean error between Hounsfield units of the pCT and the reference CT (CT). Dosimetric endpoints were based on dose-volume histograms calculated from the CT and the pCTs for various volumes of interest and on 3-dimensional gamma analyses. The PBM uncertainties were compared with those of the ABM and BDM. Results - The mean absolute error and mean error obtained from the PBM were 41.1 and -1.1 Hounsfield units. The PBM dose-volume histogram differences were 0.7% for prostate planning target volume V, 0.5% for rectum V, and 0.2% for bladder V Compared with ABM and BDM, PBM provided significantly lower dose uncertainties for the prostate planning target volume (70-78 Gy), the rectum (8.5-29 Gy, 40-48 Gy, and 61-73 Gy), and the bladder (12-78 Gy). The PBM mean gamma pass rate (99.5%) was significantly higher than that of ABM (94.9%) or BDM (96.1%). Conclusions - The proposed PBM provides low uncertainties with dose planned on CT. These uncertainties were smaller than those of ABM and BDM and are unlikely to be clinically significant