Evaluation of Ethos intelligent optimization engine for left locally advanced breast cancer.

Purpose: To evaluate the feasibility to use a standard Ethos planning template to treat left-sided breast cancer with regional lymph nodes. Material/Methods: The tuning cohort of 5 patients was used to create a planning template. The validation cohort included 15 patients treated for a locally advanced left breast cancer randomly enrolled. The Ethos planning template was tuned using standard 3 partial arc VMAT and two collimator rotation configurations: 45/285/345° and 30/60/330°. Re-planning was performed automatically using the template without editing. The study was conducted with a schedule of 42.3 Gy in 18 fractions to the breast/chestwall, internal mammary chain (IMC) and regional lymph nodes ("Nodes"). The PTV was defined as a 3D extension of the CTV with a margin of 7 mm, excluding the 5mm below the skin. The manual treatment plans were performed using Eclipse treatment planning system with AAA and PO algorithms (v15.6) and a manual arc VMAT configuration and imported in Ethos TPS (v1.1) for a dose calculation with Ethos Acuros algorithm. The automated plans were compared with the manual plans using PTV and CTV coverage, homogeneity and conformity indices (HI and CN) and doses to organs at risk (OAR) via DVH metrics. For each plan, the patient quality assurance (QA) were performed using Mobius3D and gamma index. Finally, two breast radiation oncologists performed a blinded assessment of the clinical acceptability of each of the three plans (manual and automated) for each patient. Results: The manual and automated plans provided suitable treatment planning as regards dose constraints. The dosimetric comparison showed the CTV_breast D99% were significantly improved with both automated plans (p< 0,002) while PTV coverage was comparable. The doses to the organs at risk were equivalent for the three plans. Concerning treatment delivery, the Ethos-45° and Ethos-30° plans led to an increase in MUs compared to the manual plans, without affecting the beam on time. The average gamma index pass rates remained consistently above 98% regardless of the type of plan utilized. In the blinded evaluation, clinicians 1 and 2 assessed 13 out of 15 plans for Ethos 45° and 11 out of 15 plans for Ethos 30° as clinically acceptable. Conclusion: Using a standard planning template for locally advanced breast cancer, the Ethos TPS provided automated plans that were clinically acceptable and comparable in quality to manually generated plans. Automated plans also dramatically reduce workflow and operator variability.

Feasibility study of adaptive radiotherapy with Ethos for breast cancer.

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.

Intraoperative partial irradiation for highly selected patients with breast cancer: Results of the INTRAOBS prospective study.

PURPOSE: To evaluate our long-term experience on one-day breast intraoperative radiotherapy (IORT) given as sole radiation treatment to selected patients with breast cancer. METHODS AND MATERIALS: Inclusion criteria of INTRAOBS study (prospective observational study) were: ER+ T1N0 unifocal ductal carcinoma; absence of lymphovascular invasion or of extensive intraductal component (Scarff-Bloom-Richardson grade III and HER2+++ excluded). Two different linacs were used (20Gy/1 fraction): one dedicated electron linac (

Size-based characterization of nanoparticle mixtures by the inline coupling of capillary electrophoresis to Taylor dispersion analysis.

Separation of closely related nanoparticles is still a challenging issue for the characterization of complex mixtures for industrial/research applications or regulatory purposes. In this work, the remarkable separating performances of CE were complemented with the absolute size-based determination provided by Taylor dispersion analysis (TDA) for the characterization of nanoparticle mixtures. The inline hyphenation of CE to TDA was successfully implemented for the baseline separation followed by a size-based characterization of a bimodal mixture containing two closely size-related nanolatexes (70nm and 56nm radii). A pixel sensor UV area imager providing three detection points along the capillary was used for a differential measurement of the peak broadening during the Taylor dispersion step. Comparison of this new technique with dynamic light scattering and hydrodynamic chromatography is also discussed.

Characterization of carboxylated nanolatexes by capillary electrophoresis.

Poly(styrene-co-acrylic acid) (St/AA) and poly(styrene-co-methacrylic acid) (St/MA) nanolatexes with different acid contents were prepared by emulsion copolymerization and were analyzed by capillary electrophoresis (CE) and by laser doppler velocimetry (LDV). Due to the intrinsic differences in the methodologies, CE (separative technique) and LDV (zetametry, nonseparative technique) lead to very different electrophoretic mobility distributions. Beyond these differences, the variation of the electrophoretic mobility is a complex and nonlinear function of the hydrodynamic radius, the ionic strength, and the zeta potential. To gain better insight on the influence of the ionic strength and the acid content on the electrophoretic behavior of the nanolatexes, the electrophoretic mobility data were changed into surface charge densities using the O'Brien, White, and Ohshima modeling. This approach leads to the conclusion that the surface charge density is mainly controlled at high ionic strength (∼50 mM) by the adsorption of anionic surfactants coming from the sample. On the contrary, at low ionic strength, and/or in the presence of neutral surfactant in the electrolyte, the acid content was the main parameter controlling the surface charge density of the nanolatexes.