Purpose: The aim of this study was to assess the feasibility of online adaptive radiotherapy with Ethos for breast cancer.Materials and methods: This retrospective study included 20 breast cancer patients previously treated with TrueBeam. All had undergone breast surgery for different indications (right/left, lumpectomy/mastectomy) and were evenly divided between these four cases, with five extended cone beam computed tomography (CBCT) scans per patient. The dataset was used in an Ethos emulator to test the full adaptive workflow. The contours generated by artificial intelligence (AI) for the influencers (left and right breasts and lungs, heart) and elastic or rigid propagation for the target volumes (internal mammary chain (IMC) and clavicular lymph nodes (CLNs)) were compared to the initial contours delineated by the physician using two metrics: Dice similarity coefficient (DICE) and Hausdorff 95% distance (HD95). The repeatability of influencer generation was investigated. The times taken by the emulator to generate contours, optimize plans, and calculate doses were recorded. The quality of the scheduled and adapted plans generated by Ethos was assessed using planning target volume (PTV) coverage, homogeneity indices (HIs), and doses to organs at risk (OARs) via dose–volume histogram (DVH) metrics. Quality assurance (QA) of the treatment plans was performed using an independent portal dosimetry tool (EpiQA) and gamma index.Results: On average, the DICE for the influencers was greater than 0.9. Contours resulting from rigid propagation had a higher DICE and a lower HD95 than those resulting from elastic deformation but remained below the values obtained for the influencers: DICE values were 0.79 ± 0.11 and 0.46 ± 0.17 for the CLN and IMC, respectively. Regarding the repeatability of the influencer segmentation, the DICE was close to 1, and the mean HD95 was strictly less than 0.15 mm. The mean time was 73 ± 4 s for contour generation per AI and 80 ± 9 s for propagations. The average time was 53 ± 3 s for dose calculation and 125 ± 9 s for plan optimization. A dosimetric comparison of scheduled and adapted plans showed a significant difference in PTV coverage: dose received by 95% of the volume (D95%) values were higher and closer to the prescribed doses for adapted plans. Doses to organs at risk were similar. The average gamma index for quality assurance of adapted plans was 99.93 ± 0.38 for a 3%/3mm criterion.Conclusion: This study comprehensively evaluated the Ethos^® adaptive workflow for breast cancer and its potential technical limitations. Although the results demonstrated the high accuracy of AI segmentation and the superiority of adapted plans in terms of target volume coverage, a medical assessment is still required.

Background: Previous studies in 2D and in 3D conformal radiotherapy concludes that the maximal heart distance and the mean heart dose (MHD) are considered predictive of late cardiac toxicities. As the use of inverse-planned intensity modulated radiation therapy (IMRT) is increasing worldwide, we hypothesized that this 3D MHD might not be representative of heart exposure after IMRT for breast cancer (BC).Methods: Patients with left-sided BC and unfavorable cardiac anatomy received IMRT. Their treatment plan was compared to a virtual treatment plan for 3D conformal radiotherapy with similar target volume coverage (study A). Then, a second 3D conformal treatment plan was generated to achieve equivalent individual MHD obtained by IMRT. Then the heart and left anterior descending (LAD) coronary artery exposures were analyzed (study B). Last, the relationship between MHD and the heart volume or LAD coronary artery volume receiving at least 30Gy, 40Gy and 45Gy in function of each additional 1Gy to the MHD was assessed (study C).Results: A significant decrease of heart and LAD coronary artery exposure to high dose was observed with the IMRT compared with the 3D conformal radiotherapy plans that both ensured adequate target coverage (study A). The results of study B and C showed that 3D MHD was not representative of similar heart substructure exposure with IMRT, especially in the case of high dose exposure.Conclusions: The mean heart dose is not a representative dosimetric parameter to assess heart exposure following IMRT. Equivalent MHD values following IMRT and 3DRT BC treatment do not represent the same dose distribution leading to extreme caution when using this parameter for IMRT plan validation.

To evaluate the tumor repositioning during gated volumetric modulated arc therapy (VMAT) for liver stereotactic body radiotherapy(SBRT) treatment using implanted fiducial markers and intrafraction kilovoltage (kV) images acquired during dose delivery. Since 2012, 47 liver cancer patients with implanted fiducial markers were treated using the gated VMAT technique with a Varian Truebeam STx linear accelerator. The fiducial markers were implanted inside or close to the tumor target before treatment simulation. They were defined at the maximum inhalation and exhalation phases on a 4-dimensionnal computed tomography (4DCT) acquisition. During the treatment, kV images were acquired just before the beam-on at each breathing cycle at maximum exhalation and inhalation phases to verify the fiducial markers positions. For the five first fractions of treatment in the first ten consecutive patients, a total of 2705 intrafraction kV images were retrospectively analyzed to assess the differences between expected and actual positions of the fiducial markers along the cranio-caudal (CC) direction during the exhalation phase. The mean absolute intrafractional fiducial marker deviation along the CC direction was 1.0 mm at the maximum exhalation phase. In 99%, 95% and 90% cases, the fiducial marker deviations were ≤4.5 mm, 2.8 mm and 2.2 mm, respectively. Intrafraction kV images allowed us to ensure the consistency of tumor repositioning during treatment. In 99% cases, the fiducial marker deviations were ≤4.5 mm corresponding to our 5 mm treatment margin. This margin seems to be well-adapted to the gated VMAT SBRT treatment in liver disease.

Introduction: Following a preliminary work validating the technological feasibility of an adaptive workflow with Ethos for whole-breast cancer, this study aims to clinically evaluate the automatic segmentation generated by Ethos.Material and methods: Twenty patients initially treated on a TrueBeam accelerator for different breast cancer indications (right/left, lumpectomy/mastectomy) were replanned using the Ethos^® emulator. The adaptive workflow was performed using 5 randomly selected extended CBCTs per patient. The contours generated by artificial intelligence (AI) included both breasts, the heart, and the lungs. The target volumes, specifically the tumor bed (CTV_Boost), internal mammary chain (CTV_IMC), and clavicular nodes (CTV_Nodes), were generated through rigid propagation. The CTV_Breast corresponds to the ipsilateral breast, excluding 5mm from the skin. Two radiation oncologists independently repeated the workflow and qualitatively assessed the accuracy of the contours using a scoring system from 3 (contour to be redone) to 0 (no correction needed). Quantitative evaluation was carried out using the Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), surface Dice (sDSC) and the Added Path Length (APL). The interobserver variability (IOV) between the two observers was also assessed and served as a reference. Lastly, the dosimetric impact of contour correction was evaluated. The physician-validated contours were transferred onto the plans automatically generated by Ethos in adaptive mode. The dose prescription was 52.2Gy in 18 fractions for the boost, 42.3Gy for the breast, IMC, and nodes. The CTV/PTV margin was 2mm for all volumes, except for the IMC (5mm). Dose coverage (D_98%) was assessed for the CTVs, while specific parameters for organs at risk (OAR) were evaluated: mean dose and V_17Gy (relative volume receiving at least 17Gy) for the ipsilateral lung, mean dose and D_2cc (dose received by 2cc volume) for the heart, the contralateral lung and breast.Results: The qualitative analysis showed that no correction or only minor corrections were needed for 98.6% of AI-generated contours and 86.7% of the target volumes. Regarding the quantitative analysis, Ethos’ contour generation outperformed inter-observer variability for all structures in terms of DSC, HD, sDSC and APL. Target volume coverage was achieved for 97.9%, 96.3%, 94.2% and 68.8% of the breast, IMC, nodes and boost CTVs, respectively. As for OARs, no significant differences in dosimetric parameters were observed.Conclusion: This study shows high accuracy of segmentation performed by Ethos for breast cancer, except for the CTV_Boost. Contouring practices for adaptive sessions were revised following this study to improve outcomes.

Purpose/objectives: An artificial intelligence-based pseudo-CT from low-field MR images is proposed and clinically evaluated to unlock the full potential of MRI-guided adaptive radiotherapy for pelvic cancer care.Materials and method: In collaboration with TheraPanacea (TheraPanacea, Paris, France) a pseudo-CT AI-model was generated using end-to-end ensembled self-supervised GANs endowed with cycle consistency using data from 350 pairs of weakly aligned data of pelvis planning CTs and TrueFisp-(0.35T)MRIs. The image accuracy of the generated pCT were evaluated using a retrospective cohort involving 20 test cases coming from eight different institutions (US: 2, EU: 5, AS: 1) and different CT vendors. Reconstruction performance was assessed using the organs at risk used for treatment. Concerning the dosimetric evaluation, twenty-nine prostate cancer patients treated on the low field MR-Linac (ViewRay) at Montpellier Cancer Institute were selected. Planning CTs were non-rigidly registered to the MRIs for each patient. Treatment plans were optimized on the planning CT with a clinical TPS fulfilling all clinical criteria and recalculated on the warped CT (wCT) and the pCT. Three different algorithms were used: AAA, AcurosXB and MonteCarlo. Dose distributions were compared using the global gamma passing rates and dose metrics.Results: The observed average scaled (between maximum and minimum HU values of the CT) difference between the pCT and the planning CT was 33.20 with significant discrepancies across organs. Femoral heads were the most reliably reconstructed (4.51 and 4.77) while anal canal and rectum were the less precise ones (63.08 and 53.13). Mean gamma passing rates for 1%1mm, 2%/2mm, and 3%/3mm tolerance criteria and 10% threshold were greater than 96%, 99% and 99%, respectively, regardless the algorithm used. Dose metrics analysis showed a good agreement between the pCT and the wCT. The mean relative difference were within 1% for the target volumes (CTV and PTV) and 2% for the OARs.Conclusion: This study demonstrated the feasibility of generating clinically acceptable an artificial intelligence-based pseudo CT for low field MR in pelvis with consistent image accuracy and dosimetric results.

Liver SBRT is a therapeutic option for the treatment of HCC in patients not eligible for other local therapies. We retrospectively report the outcomes of a cohort of consecutive patients treated with SBRT for HCC at the Montpellier Cancer Institute. Between March 2013 and December 2018, 66 patients were treated with image-guided liver SBRT using VMAT and real-time adaptive tumor gating in our institute. The main endpoints considered in this study were local control, disease-free survival, overall survival, and toxicity. The median follow-up was 16.8 months. About 66.7% had prior liver treatment. Most patients received 50 Gy in five fractions of 10 Gy. No patient had local recurrence. Overall survival and disease-free survival were, respectively, 83.9% and 46.7% at one year. In multivariate analysis, the diameter of the lesions was a significant prognostic factor associated with disease-free survival (HR = 2.57 (1.19–5.53) p = 0.02). Regarding overall survival, the volume of PTV was associated with lower overall survival (HR = 2.84 (1.14–7.08) p = 0.025). No grade 3 toxicity was observed. One patient developed a grade 4 gastric ulcer, despite the dose constraints being respected. Image-guided liver SBRT with VMAT is an effective and safe treatment in patients with inoperable HCC, even in heavily pre-treated patients. Further prospective evaluation will help to clarify the role of SBRT in the management of HCC patients.