Background And Purpose: In online adaptive stereotactic body radiotherapy treatments, linear accelerator delivery accuracy is essential. Recently introduced double stack multileaf collimators (MLCs) have new facets in their calibration. We established a radiation-based leaf-individual calibration (LIMCA) method for double stack MLCs.
Materials And Methods: MLC leaf positions were evaluated from four cardinal angles with test patterns at measurement positions throughout the radiation field on EBT3 radiochromic film for each single stack. The accuracy of the method and repeatability of the results were assessed. The effect of MLC positioning errors was characterized for a measured output factor curve and a clinical patient plan.
Results: All positions in the motor step - position calibration file were optimized in the established LIMCA method. The resulting double stack mean accuracy for all angles was 0.2 ± 0.1 mm for X1 (left bank) and 0.2 ± 0.2 mm for X2 (right bank). The accuracy of the leaf position evaluation was 0.2 mm (95% confidence level). The MLC calibration remained stable over four months. Small MLC leaf position errors (e.g. 1.2 mm field size reduction) resulted in important dose errors (-5.8 %) for small quadratic fields of 0.83 × 0.83 cm. Single stack position accuracy was essential for highly modulated treatment plans.
Conclusions: LIMCA is a new double stack MLC calibration method that increases treatment accuracy from four angles and for all moving leaves.
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http://dx.doi.org/10.1016/j.phro.2023.100477 | DOI Listing |
Acta Crystallogr E Crystallogr Commun
January 2025
Department of Chemistry, Taras Shevchenko National University of Kyiv, Volodymyrska str. 64/13, 01601 Kyiv, Ukraine.
The title compound, {(CHNO)[SnBr]} , is a layered hybrid perovskite crystallizing in the monoclinic space group 2/. The asymmetric unit consists of one HC-O-NH -CH cation (MeHA), one Sn atom located on a twofold rotation axis, and two Br atoms. The Sn atom has a distorted octa-hedral coordination environment formed by the bromido ligands.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electro-Optical Engineering, National Taipei University of Technology, Taipei, 10608, Taiwan.
This work reports on the preparation process of a double-layer perovskite active layer. The first active layer film, CsKPEAPbIBr, was fabricated using a spin-coating method, while the second active layer, MAPbBr, was deposited using MAPbBr single crystals as the evaporation source. Additionally, doping the PEDOT: PSS hole transport layer with ETA and EDA can enhance the uniformity of the perovskite film and reduce voids, improving charge transport efficiency.
View Article and Find Full Text PDFChem Sci
December 2024
Department of Materials Engineering Science, Graduate School of Engineering Science, Osaka University Toyonaka Osaka 560-8531 Japan
In this study, we theoretically examined the mechanism of aromaticity induced in closely stacked cofacial π-dimers of 4π antiaromatic molecules, which is called stacked-ring aromaticity, in terms of the effective number of π-electrons ( ) and Baird's rule. High-precision quantum chemical calculations combined with a multi-configurational wavefunction analysis revealed that double-triplet [(TT)] and intermolecular charge-transfer (CT) electron configurations mix substantially in the ground state wavefunctions of cyclobutadiene and Ni(ii) norcorrole dimer models at small stacking distance (). Since the T configuration gives rise to two unpaired electrons, the remaining 4 - 2 π electrons still participate in the intramolecular conjugation, which can be interpreted as the origin of the aromaticity of each monomer.
View Article and Find Full Text PDFWater Res
December 2024
Department of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, CA 92182, USA. Electronic address:
Tire tread particles are microplastics (< 5 mm) and leach organic chemicals into aquatic environments. It is important to understand the behavior of tire wear compounds in sunlight-exposed waters in terms of their persistence, removal, and transformation. Therefore, we conducted photolysis experiments with leachates from laboratory-generated tire tread particles (TTP) over 72 h in a solar simulator to evaluate the behavior of leached compounds and fluorescent components over time.
View Article and Find Full Text PDFNat Commun
January 2025
School of Computer Science and Engineering, Central South University, Changsha, China.
Machine learning offers a promising avenue for expediting the discovery of new compounds by accurately predicting their thermodynamic stability. This approach provides significant advantages in terms of time and resource efficiency compared to traditional experimental and modeling methods. However, most existing models are constructed based on specific domain knowledge, potentially introducing biases that impact their performance.
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