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PURPOSE: Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning-based dual-omics model, which aims to improve the RP prediction performance by integrating more data points and exploring the data in greater depth. MATERIALS AND METHODS: The bimodality data were the original dose (OD) distribution and the ventilation image (VI) derived from four-dimensional computed tomography (4DCT). The functional dose (FD) distribution was obtained by weighting OD with VI. A pre-trained three-dimensional convolution (C3D) network was used to extract the features from FD, VI, and OD. The extracted features were then filtered and selected using entropy-based methods. The prediction models were constructed with four most commonly used binary classifiers. Cross-validation, bootstrap, and nested sampling methods were adopted in the process of training and hyper-tuning. RESULTS: Data from 217 thoracic cancer patients treated with radiotherapy were used to train and validate the prediction model. The 4DCT-based VI showed the inhomogeneous pulmonary function of the lungs. More than half of the extracted features were singular (of none-zero value for few patients), which were eliminated to improve the stability of the model. The area under curve (AUC) of the dual-omics model was 0.874 (95% confidence interval: 0.871-0.877), and the AUC of the single-omics model was 0.780 (0.775-0.785, VI) and 0.810 (0.804-0.811, OD), respectively. CONCLUSIONS: The dual-omics outperformed single-omics for RP prediction, which can be contributed to: (1) using more data points; (2) exploring the data in greater depth; and (3) incorporating of the bimodality data.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Deep Learning , Lung Neoplasms , Radiation Pneumonitis , Four-Dimensional Computed Tomography , Humans , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/radiotherapy , Radiation Pneumonitis/etiologyABSTRACT
Objective:To establish an automatic planning method using volumetric-modulated arc therapy (VMAT) for primary liver cancer (PLC) radiotherapy based on predicting the feasibility dose-volume histogram (DVH) and evaluate its performance.Methods:Ten patients with PLC were randomly chosen in this retrospective study. Pinnacle Auto-Planning was used to design the VMAT automatic plan, and the feasibility DVH curve was obtained through the PlanIQ dose prediction, and the initial optimization objectives of the automatic plan were set according to the displayed feasible objectives interval. The plans were accessed according to dosimetric parameters of the planning target volume and organs at risk as well as the monitor units. All patients′ automatic plans were compared with clinically accepted manual plans by using the paired t-test. Results:There was no significant difference of the planning target volume D 2%, D 98%, D mean or homogeneity index between the automatic and manual plans ((58.55±2.81) Gy vs.(57.98±4.17) Gy, (47.15±1.58) Gy vs.(47.82±1.38) Gy, (53.14±0.95) Gy vs.(53.44±1.67) Gy and 1.15±0.05 vs. 1.14±0.07, all P>0.05). The planning target volume conformity index of the manual plan was slightly higher than that of the automatic plan (0.77±0.08 vs. 0.69±0.06, P<0.05). The mean doses of normal liver, V 30Gy, V 20Gy, V 10Gy, V 5Gy and V< 5Gy of the automatic plan were significantly better than those of the manual plan ((26.68±11.13)% vs.(28.00±10.95)%, (29.96±11.50)% vs.(31.89±11.51)%, (34.88±11.51)% vs.(38.66±11.67)%, (45.38±12.40)% vs.(50.74±13.56)%, and (628.52±191.80) cm 3vs.(563.15±188.39) cm 3, all P<0.05). The mean doses of the small intestine, the duodenum, and the heart, as well as lung V 10 of the automatic plan were significantly less than those of the manual plan ((1.83±2.17) Gy vs.(2.37±2.81) Gy, (9.15±9.36) Gy vs.(11.18±10.49) Gy, and (5.44±3.10) Gy vs.(6.25±3.26) Gy, as well as (12.70±7.08)% vs.(14.47±8.11)%, all P<0.05). Monitor units did not significantly differ between two plans ((710.67±163.72) MU vs.(707.53±155.89) MU, P>0.05). Conclusions:The automatic planning method using VMAT for PLC radiotherapy based on predicting the feasibility DVH enhances the quality for PLC plans, especially in terms of normal liver sparing. Besides, it also has advantages for the protection of the intestine, whole lung and heart.
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Objective@#To explore the correlation between microdamage in white matter and radiotherapy dose at early stage after radiotherapy (RT) in patients with nasopharyngeal carcinoma (NPC).@*Methods@#Thirty-three patients who were initially diagnosed with NPC were recruited and received diffusion tensor imaging (DTI) scan and neuro-cognitive scale test within 1 week before RT and the first day after RT. DTI-related characteristic parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ‖), and radial diffusivity (λ⊥) were calculated based on whole-brain voxel analysis method. Paired t-test was conducted to evaluate statistical significance between pre-RT and post-RT groups. In the subgroup analysis, all the subjects were divided into 3 groups according to the average dose of temporal lobe, and each group was set with an equal dose interval range. The DTI-related parameters of whole brain pre-RT and post-RT in each group were statistically compared. All the statistical results were corrected by FDR with a threshold of P<0.05 and clusters>100.@*Results@#FA, MD, λ‖ and λ⊥in the post-RT group significantly differed compared with those in the pre-RT group (P<0.05). The values of FA, MD, λ‖ and λ⊥were 0.455±0.016, (9.893±0.403)×10-4, (13.441±0.412)×10-4 and (8.231±0.429)×10-4, respectively. Subgroup analysis showed that the extent and degree of λ‖ and λ⊥ changes were exacerbated with the increase of the average dose of temporal lobe after RT. Particularly in high-dose group, the average dose range was 25-35 Gy and the extent of regions with significant changes was significantly larger than those in the medium-dose (15-25 Gy) and low-dose groups (5-15 Gy)(P<0.05).@*Conclusions@#DTI can be utilized to detect" normal" brain tissue microdamage in NPC patients at early stage after RT. The average radiation dose of temporal lobe may be one of the reasons for the severity of cerebral microdamage. In the future, DTI technique may be useful for guiding exposure dose of organs at risk during RT planning and to evaluate the cohort with a high risk of cerebral microdamage at early stage after RT, thereby protecting normal cerebral tissues to the maximum extent.
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Magnetic resonance imaging (MRI) simulator (MRI-Sim) can provide superior images for radiotherapy.Due to the complexity of MRI technology and the safety problem caused by strong magnetic field, the acquisition and implementation of MRI simulation is more complicated than CT simulation.In order to ensure the introduction of MRI-Sim, this paper reviews the selection, installation, and acceptance test of MRI-Sim, including the selection of host and auxiliary equipment, installation site preparation, and safety precautions,as well as MRI-Sim acceptance test and commissioning.