Purpose This study aimed to predict the progression-free survival (PFS) of the patients who were diagnosed with hypopharyngeal cancer and received postoperative chemoradiotherapy by using multi-omics method which integrating clinical factors, dosimetric and radiomic features. Materials and methods This study retrospectively collected the pretreatment T1-weighted MR imaging data of 88 hypopharyngeal cancer patients with postoperative chemoradiotherapy, including 56 cases from one center (training and testing cohorts) and 32 cases from another center (external validation cohort), and the gross tumor volumes (GTV) were countered for all cases. A Python-based library, pyradiomics was used to extract the radiomics features from each GTV. Least absolute shrinkage and selection operator (LASSO) regression was used to identify the most important features for classifier establishment. On the other hand, complete radiotherapy data are retained for 48 patients among them, and the planning tumor volumes (PTV) were countered for radiotherapy planning. The dose distribution features extracted by using pyradiomics and the dosimetric parameters were combined with the radiomics features to establish the classifiers. The probabilities of positive sample calculated from the best classifier, the radiomics and multi-omics signatures were obtained for establish the Cox proportional hazards models. Results The ensemble learning (EL) model was selected as the superior model with the higher area under the receiver operating characteristic curve (AUC) values than other classifier during the radiomics-only analysis, and the EL model with stacking technique showed the best performance, yielding AUC values of 0.93, 0.79, and 0.78 for the training, testing, and external validation cohorts, respectively. Furthermore, the multi-omics analysis integrating radiomics and dosiomics improved the effectiveness of the EL model with AUC values of 0.98 and 0.88 for the training and testing cohorts, respectively. Furthermore, the C-index of the Cox proportional hazards models resulted in a 0.099 improvement in the testing cohort when employing the multi-omics signature versus the radiomics signature. Conclusion Regarding the patients with hypopharyngeal cancer receiving postoperative chemoradiotherapy, the multi-omics-based prognostic prediction could achieve a more robust predictive capability than the radiomics-only study. This approach warrants further validation through prospective studies.

Purpose To establish and validate a delta-radiomics-based model for predicting progression-free survival (PFS) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) following induction chemotherapy (IC). Methods and Materials A total of 250 LA-NPC patients (training cohort: n = 145; validation cohort: n = 105) were enrolled. Radiomic features were extracted from MRI scans taken before and after IC, and changes in these features were calculated. Following feature selection, a delta-radiomics signature was constructed using LASSO-Cox regression analysis. A prognostic nomogram incorporating independent clinical indicators and the delta-radiomics signature was developed and assessed for calibration and discrimination. Risk stratification by the nomogram was evaluated using Kaplan-Meier methods. Results The delta-radiomics signature, consisting of 12 features, was independently associated with prognosis. The nomogram, integrating the delta-radiomics signature and clinical factors demonstrated excellent calibration and discrimination. The model achieved a Harrell’s concordance index (C-index) of 0.848 in the training cohort and 0.820 in the validation cohort. Risk stratification identified two groups with significantly different PFS rates. The three-year PFS for high-risk patients who received concurrent chemoradiotherapy (CCRT) or radiotherapy plus adjuvant chemotherapy (RT+AC) after IC was significantly higher than for those who received RT alone, reaching statistical significance. In contrast, for low-risk patients, the three-year PFS after IC was slightly higher for those who received CCRT or RT+AC compared to those who received RT alone; however, this difference did not reach statistical significance. Conclusions Our delta MRI-based radiomics model could be useful for predicting PFS and may guide subsequent treatment decisions after IC in LA-NPC.

PurposeThe present study aimed to develop a porous structure with plug-ins (PSP) to broaden the Bragg peak width (BPW, defined as the distance in water between the proximal and distal 80% dose) of the carbon ion beam while maintaining a sharp distal falloff width (DFW, defined as the distance along the beam axis where the dose in water reduces from 80% to 20%).MethodsThe binary voxel models of porous structure (PS) and PSP were established in the Monte Carlo code FLUKA and the corresponding physical models were manufactured by 3D printing. Both experiment and simulation were performed for evaluating the modulation capacity of PS and PSP. BPWs and DFWs derived from each integral depth dose curves were compared. Fluence homogeneity of 430 MeV/u carbon-ion beam passing through the PSP was recorded by analyzing radiochromic films at six different locations downstream the PSP in the experiment. Additionally, by changing the beam spot size and incident position on the PSP, totally 48 different carbon-ion beams were simulated and corresponding deviations of beam metrics were evaluated to test the modulating stability of PSP.ResultsAccording to the measurement data, the use of PSP resulted in an average increase of 0.63 mm in BPW and a decrease of 0.74 mm in DFW compared to PS. The 2D radiation field inhomogeneities were lower than 3 % when the beam passing through a ≥ 10 cm PMMA medium. Furthermore, employing a spot size of ≥ 6 mm ensures that beam metric deviations, including BPW, DFW, and range, remain within a deviation of 0.1 mm across various incident positions.ConclusionThe developed PSP demonstrated its capability to effectively broaden the BPW of carbon ion beams while maintaining a sharp DFW comparing to PS. The superior performance of PSP, indicates its potential for clinical use in the future.

AbstractBackgroundMonte Carlo (MC) code FLUKA possesses widespread usage and accuracy in the simulation of particle beam radiotherapy. However, the conversion from computer‐aided design (CAD) mesh format models to FLUKA readable geometries could not be implemented directly and conveniently. A simple method was required to be developed.PurposeThe present study proposed a simple method to voxelize CAD mesh format files by using a Python‐based script and establishing geometric models in FLUKA.MethodsFive geometric models including cube, sphere, cone, ridge filter (RGF), and 1D‐Ripple Filter (1D‐RiFi) were created and exported as CAD mesh format files (.stl). An open‐source Python‐based script was used to convert them into voxels by endowing X, Y, and Z (following the Cartesian coordinates system) of solid materials in the three‐dimensional (3D) grid. A FLUKA (4‐2.2, CERN) predefined routine was used to establish the voxelized geometry model (VGM), while Flair (3.2‐1, CERN) was used to build the direct geometry model (DGM) in FLUKA for comparison purposes. Uniform carbon ion radiation fields 8×8 cm3 and 4×4 cm3 were generated to transport through the five pairs of models, 2D and 3D dose distributions were compared. The integral depth dose (IDD) in water of three different energy levels of carbon ion beams transported through 1D‐RiFis were also simulated and compared. Moreover, the volume between CAD mesh and VGMs, as well as the computing speed between FLUKA DGMs and VGMs were simultaneously recorded.ResultsThe volume differences between VGMs and CAD mesh models were not more than 0.6%. The maximum mean point‐to‐point deviation of IDD distribution was 0.7% ± 0.51% (mean ± standard deviation). The 3D dose Gamma‐index passing rates were never lower than 97% with criteria of 1%–1 mm. The difference in computing CPU time was 2.89% ± 0.22 on average.ConclusionsThe present study proposed and verified a Python‐based method for converting CAD mesh format files into VGMs and establishing them in FLUKA simply as well as accurately.

Abstract Purpose To quantify the influence of beam optics asymmetric distribution on dose. Methods Nine reference cubic targets and corresponding plans with modulation widths (M) of 3, 6, and 9 cm and with center depths (CDs) of 6, 12, and 24 cm were generated by the treatment planning system (TPS). The Monte Carlo code FLUKA was used for simulating the dose distribution from the aforementioned original plans and the dose perturbation by varying ±5%, ±15%, ±20%, ±25%, and ±40% in spot full width half maximum to the X‐direction while keeping consistent in the Y‐direction. The dosimetric comparisons in dose deviation, γ‐index analysis, lateral penumbra, and flatness were evaluated. Results The largest 3D absolute mean deviation was 15.0% ± 20.9% (mean ± standard deviation) in M3CD6, whereas with the variation from −15% to +20%, the values were below 5% for all cube plans. The lowest 2D γ‐index passing rate was 80.6% with criteria of 2%–2 mm by a +40% variation in M3CD6. For the M9CD24 with a −40% variation, the maximum 1D dose deviations were 5.6% and 15.7% in the high‐dose region and the edge of the radiation field, respectively. The maximum deviations of penumbra and flatness were 3.4 mm and 11.4%, respectively. Conclusions The scenario of beam optics asymmetric showed relatively slight influence on the global dose distribution but severely affected dose on the edge of the radiation field. For scanning carbon‐ion therapy facilities, beam spot lateral profile settings in TPS base data should be properly handled when beam optics asymmetry variation is over 15%.

Objective:To develop a spot scanning carbon ion beam model based on Monte Carlo code FLUKA and verify the accuracy of physical dose.Methods:A geometric model of the treatment nozzle was established in FLUKA. Various parameters such as monoenergy nominal energy, Gaussian energy spectrum distribution, initial spot size, and beam angular distribution in the model were adjusted to match the reference data of integral depth dose (IDD) and in-air spot size measuremed experimentally. Carbon ion beam plans were generated by using the treatment planning system (TPS). The difference in output dose distribution between FLUKA and TPS was compared by the gamma analysis.Results:The differences in Bragg peak width, beam range, and distal falloff width extracted from the IDD curve between the FLUKA model and measured vaues were less than 0.1 mm, with the maximum difference in spot sizes of 0.17 mm. Under the criterion of 2 mm/2% in all the simulations, 2D- and 3D-γ pass rates were all above 95%.Conclusions:An accurate spot scanning carbon beam model was developed based on the Monte Carlo code FLUKA. It has the potential to be used for not only the verification of clinical treatment plans, but also the development of new ion beam therapy equipment and the calculation of biologically effective dose.

BackgroundIn particle radiotherapy, the Bragg peak (BP) width of carbon ion beam is required to be broadened whilst Ripple filter (RiFi) is often used as a clinical broadening device. However, it may cause extra lateral scattering. Porous material expressed as the porous structure 1.0 (PS 1.0) can be used to reduce such scattering but bring an oversized distal falloff width (DFW).PurposeThis study aims to develop a novel porous structure, described as a porous structure 2.0 (PS 2.0), to broaden the BP width.MethodsFirst of all, the Monte Carlo code, FLUKA was selected as the tool for this simulation. Two geometry models of broadening structure (1D-RiFi and PS 1.0) were built. Then, the PS 2.0 was simulated by inserting numerous of Polymethyl Methacrylate (PMMA) sticks in the PS 1.0 with a certain proportion. The performance of PS 2.0 was evaluated by analyzing the DFW and isocenter spot size of the modulated carbon ion beams. Finally, a plane homogeneous radiation field was simulated and fluence homogeneities were compared by using a 2D (X-Z) dose distribution and quantized by calculating the 1D-lateral flatness.ResultsCompared to the PS 1.0, the DFW is reduced by at most 1.11 mm by using PS 2.0 with a similar BP width broadening ability at the same beam range. Fluence homogeneity of PS 2.0 is excellent in all the downstream locations, and the isocenter spot size is reduced by at most 1.72 mm at the same beam range.ConclusionsThis study provides a new method for simulating the PS 2.0 as a BP broadening device with smaller DFW, better homogeneous and reduced isocenter spot size in comparison to PS 1.0.