Dosimetric comparison of helical tomotherapy and volumetric modulated arc therapy in hippocampal avoidance whole-brain radiotherapy.

OBJECTIVE: This study aimed to discuss the dosimetric advantages of helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) technology in hippocampal avoidance whole-brain radiotherapy and provide references for clinical selection of ideal radiotherapy technology. METHODS: A total of 20 patients with hippocampal avoidance whole-brain radiotherapy were chosen randomly. Computed tomography (CT) and MRI scanning images were input into the treatment planning system (TPS). After the CT and enhanced magnetic resonance T1 weighted images were fused and registered, the same radiation therapy physician was invited to outline the tumor target volume. PTV-HS refers to the whole brain subtracted by 5 mm outward expansion of the hippocampus (HP). The prescribed dose was 30 Gy/10 fractions. HT and VMAT plans were designed for each patient in accordance with PTV. Under the premise that the 95% isodose curve covers the PTV, dose-volume histogram was applied to evaluate the PTV, conformal index (CI), heterogeneity index (HI), maximum dose (Dmax), mean dose (Dmean), minimum dose (Dmin) and absorbed doses of organs at risk (OARs) in HT and VMAT plans. Paired t-test was performed to compare the differences between two radiation therapy plans, and p  <  0.05 was considered statistically significant. RESULTS: These two plans had no significant difference in PTV-HS (max, min, and mean). However, the HI and CI of the HT plan were significantly better than those of the VMAT plan, showing statistically significant difference (p < 0.05). The HT plan was significantly superior to the VMAT plan in terms of the Dmax, Dmin, and Dmean of HP, left and right eye lens, left and right eye, and spinal cord, showing statistically significant difference (p < 0.05). The HT plan was also better than the VMAT plan in terms of the Dmax of the left optic nerve. However, the two plans showed no obvious differences in terms of the absorbed doses of the right optic nerve and brainstem, without statistical significance. CONCLUSIONS: Compared with the VMAT plan of hippocampal avoidance, HT technology has significant dosimetric advantages. HT plans significantly decreased the radiation dose and radiation volume of OARs surrounding the target area (e.g., surrounding eye lens and eye, especially hippocampal avoidance area) while increasing the CI and HI of PTV dose in whole brain radiotherapy (WBRT) greatly, thus enabling the decrease in the incidence rate of radioactive nerve function impairment.

SGRT-based stereotactic body radiotherapy for lung cancer setup accuracy and margin of the PTV.

OBJECTIVE: Surface-guided radiation therapy (SGRT, AlignRT) was used to analyze motion during stereotactic body radiotherapy (SBRT) in lung cancer patients and to explore the margin of the planning target volume (PTV). METHODS: The residual errors of the AlignRT were evaluated based on grayscale cone-beam computed tomography registration results before each treatment. AlignRT log file was used to analyze the correlation between the frequency and longest duration of errors larger than 2 mm and lasting longer than 2 s and maximum error with age and treatment duration. The displacement value at the end of treatment, the average displacement value, and the 95% probability density displacement interval were defined as intrafraction errors, and PTV1, PTV2, PTV3 were calculated by Van Herk formula or Z score analysis. Organ dosimetric differences were compared after the experience-based margin was replaced with PTV3. RESULTS: The interfraction residual errors were Vrt0 , 0.06 ± 0.18 cm; Lng0 , -0.03 ± 0.19 cm; Lat0 , 0.02 ± 0.15 cm; Pitch0 , 0.23 ± 0.7°; Roll0 , 0.1 ± 0.69°; Rtn0 , -0.02 ± 0.79°. The frequency, longest duration and maximum error in vertical direction were correlated with treatment duration (r = 0.404, 0.353, 0.283, p < 0.05, respectively). In the longitudinal direction, the frequency was correlated with age and treatment duration (r = 0.376, 0.283, p < 0.05, respectively), maximum error was correlated with age (r = 0.4, P < 0.05). Vertical, longitudinal, lateral margins of PTV1, PTV2, PTV3 were 2 mm, 4 mm, 2 mm; 2 mm, 2 mm, 2 mm, 3 mm, 5 mm, 3 mm, respectively. After replacing the original PTV, mean lung dose (MLD), 2-cm3 chest wall dose (CD), lung V20 decreased by 0.2 Gy, 2.1 Gy, 0.5%, respectively (p < 0.05). CONCLUSION: AlignRT can be used for interfraction setup and monitoring intrafraction motion. It is more reasonable to use upper and lower limits of the 95% probability density interval as an intrafraction error.

Dose prediction of organs at risk in patients with cervical cancer receiving brachytherapy using needle insertion based on a neural network method.

OBJECTIVE: A neural network method was employed to establish a dose prediction model for organs at risk (OAR) in patients with cervical cancer receiving brachytherapy using needle insertion. METHODS: A total of 218 CT-based needle-insertion brachytherapy fraction plans for loco-regionally advanced cervical cancer treatment were analyzed in 59 patients. The sub-organ of OAR was automatically generated by self-written MATLAB, and the volume of the sub-organ was read. Correlations between D2cm3 of each OAR and volume of each sub-organ-as well as high-risk clinical target volume for bladder, rectum, and sigmoid colon-were analyzed. We then established a neural network predictive model of D2cm3 of OAR using the matrix laboratory neural net. Of these plans, 70% were selected as the training set, 15% as the validation set, and 15% as the test set. The regression R value and mean squared error were subsequently used to evaluate the predictive model. RESULTS: The D2cm3/D90 of each OAR was related to volume of each respective sub-organ. The R values for bladder, rectum, and sigmoid colon in the training set for the predictive model were 0.80513, 0.93421, and 0.95978, respectively. The ∆D2cm3/D90 for bladder, rectum, and sigmoid colon in all sets was 0.052 ± 0.044, 0.040 ± 0.032, and 0.041 ± 0.037, respectively. The MSE for bladder, rectum, and sigmoid colon in the training set for the predictive model was 4.779 × 10-3, 1.967 × 10-3 and 1.574 × 10-3, respectively. CONCLUSION: The neural network method based on a dose-prediction model of OAR in brachytherapy using needle insertion was simple and reliable. In addition, it only addressed volumes of sub-organs to predict the dose of OAR, which we believe is worthy of further promotion and application.

Transmission of Areca Palm Velarivirus 1 by Mealybugs Causes Yellow Leaf Disease in Betel Palm (Areca catechu).

Yellow leaf disease (YLD) is the most destructive disease of betel palm (Areca catechu). A strong association between YLD and areca palm velarivirus 1 (APV1) has been observed. However, the causal relationship between APV1 and disease, and the transmission mode, warrant further investigation. This work showed that APV1 was transmitted by both Ferrisia virgata and Pseudococcus cryptus mealybugs and caused YLD symptoms in betel palm seedlings; therefore, we demonstrate that APV1 is a causal agent of YLD. APV1 was detected in the stylets, foreguts, midguts, and hindguts of the vectors via both immunocapture reverse transcription PCR and immunofluorescence assays. APV1 was not transmitted transovarially from viruliferous female F. virgata to their progeny. In summary, the transmission of APV1 by F. virgata may occur in a noncirculative, semipersistent manner. This study fills important gaps in our knowledge of velarivirus transmission, which is critical for developing YLD management practices.

Genomic diversity of Areca Palm Velarivirus 1 (APV1) in Areca palm (Areca catechu) plantations in Hainan, China.

BACKGROUND: Areca palm (Areca catechu L.) is an important commercial crop in southeast Asia, but its cultivation is threatened by yellowing leaf disease (YLD). Areca palm velarivirus 1 (APV1) was recently associated with YLD, but little is known regarding its population and genetic diversity. To assess the diversity of YLD, the APV1 genome was sequenced in YLD samples collected from different sites in Hainan. RESULTS: Twenty new and complete APV1 genomes were identified. The APV1 isolates had highly conserved sequences in seven open reading frames (ORFs; > 95% nucleotide [nt] identity) at the 3' terminal, but there was diversity (81-87% nt identity) in three ORFs at the 5' terminal. Phylogenetic analysis divided the APV1 isolates into three phylogroups, with 16 isolates (> 70%) in phylogroup A. Mixed infections with different genotypes in the same tree were identified; this was closely correlated with higher levels of genetic recombination. CONCLUSIONS: Phylogroup A is the most prevalent APV1 genotype in areca palm plantations in Hainan, China. Mixed infection with different genotypes can lead to genomic recombination of APV1. Our data provide a foundation for accurate diagnostics, characterization of etiology, and elucidation of the evolutionary relationships of APV1 populations.

[Common Troubles of Vacuum Components in Elekta Linear Accelerator and Fast Solutions].

The transportation of electron is inseparable from vacuum environment. The maintenance of the vacuum system of Elekta linear accelerator depends on two sputtering ionic pumps at the gun end and the target end. The traveling wave acceleration were used in Elekta linear accelerators. And the design of the electron gun filament is detachable. Because of these two reasons, the vacuum stability is relatively weak. Only two vacuum values are used to reflect the operation state of the whole vacuum system, which causes a few failures but will not trigger a the machine interlock. Considering the complexity of whole vacuum system, the problem of vacuum caused by the failure of various components in vacuum system is analyzed in this paper. It is hoped that some useful repairing experience and suggestions for the maintenance engineers of linear accelerator to solve the vacuum fault and rebuild the vacuum can be provided quickly.

Prevalence of Yellow Leaf Disease (YLD) and its Associated Areca Palm Velarivirus 1 (APV1) in Betel Palm (Areca catechu) Plantations in Hainan, China.

Yellow leaf disease (YLD) is an economically important disease affecting betel palm in several countries, the cause of which remains unclear despite associations with putative agents, including phytoplasmas. In this study, we screened the potential casual agents associated with YLD in Hainan, China using next-generation sequencing and revealed the association of areca palm velarivirus 1 (APV1) with the YLD-affected palm. The complete genome of the APV1-WNY isolate was determined to be 17,546 nucleotides in length, approximately 1.5 kb longer than the previously reported APV1_HN genome. Transmission electron microscopy showed that APV1 particles are flexuous and filamentous, a typical morphology of species in the Closteroviridae family. Comparison of symptomatic and symptomless tree populations showed a strong association between APV1 and YLD. APV1 was detected in Pseudococcus sp. mealybugs sampled from YLD-affected trees in many locations, suggesting that mealybugs are a potential transmission vector for APV1. Although further studies are needed to confirm a causal relationship, these results provide timely information for the prevention and management of YLD associated with APV1.

Dosimetric comparison of three intensity-modulated radiation therapies for left breast cancer after breast-conserving surgery.

PURPOSE: This study aimed to evaluate dosimetric differences of intensity-modulated radiation therapy (IMRT) in target and normal tissues after breast-conserving surgery. METHODS: IMRT five-field plan I, IMRT six-field plan II, and field-in-field-direct machine parameter optimization-IMRT plan III were designed for each of the 50 patients. One-way analysis of variance was performed to compare differences, and P < 0.05 was considered statistically significant. RESULTS: Homogeneity index of plan III is lower than those of plans I and II. No difference was identified in conformity index of targets. Plan I exhibited difference in mean dose (Dmean ) for the heart (P < 0.05). Plan I featured smaller irradiation dose volumes in V5 , V20 (P < 0.05) of the left lung than II. Plan I exhibited significantly higher V5 in the right lung than plans II and III (P < 0.05). Under plan I, irradiation dose at V5 in the right breast is higher than that in plans II and III. Patients in plan III presented less total monitor unit and total treatment time than those in plans I and II (P < 0.05). CONCLUSION: IMRT six-field plans II, and field-in-field-direct machine parameter optimization-IMRT plans III can reduce doses and volumes to the lungs and heart better while maintaining satisfying conformity index and homogeneity index of target. Nevertheless, plan II neglects target movements caused by respiration. In the same manner, plan III can substantially reduce MU and shorten patient treatment time. Therefore, plan III, which considers target movement caused by respiration, is a more practical radiation mode.

[The Analysis of MLC Failure in Elekta Precise Linear Accelerator].

The causes of common MLC failure in Elekta Precise linear accelerator were detailed analyzed. And the methods of repairing and handling MLC faults were also presented in detail. It is hoped that some repairing experience for the maintenance engineers of linear accelerator can be provided by this paper.

CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma.

BACKGROUND & AIMS: The present study utilized extracted computed tomography radiomics features to classify the gross tumor volume and normal liver tissue in hepatocellular carcinoma by mainstream machine learning methods, aiming to establish an automatic classification model. METHODS: We recruited 104 pathologically confirmed hepatocellular carcinoma patients for this study. GTV and normal liver tissue samples were manually segmented into regions of interest and randomly divided into five-fold cross-validation groups. Dimensionality reduction using LASSO regression. Radiomics models were constructed via logistic regression, support vector machine (SVM), random forest, Xgboost, and Adaboost algorithms. The diagnostic efficacy, discrimination, and calibration of algorithms were verified using area under the receiver operating characteristic curve (AUC) analyses and calibration plot comparison. RESULTS: Seven screened radiomics features excelled at distinguishing the gross tumor area. The Xgboost machine learning algorithm had the best discrimination and comprehensive diagnostic performance with an AUC of 0.9975 [95% confidence interval (CI): 0.9973-0.9978] and mean MCC of 0.9369. SVM had the second best discrimination and diagnostic performance with an AUC of 0.9846 (95% CI: 0.9835- 0.9857), mean Matthews correlation coefficient (MCC)of 0.9105, and a better calibration. All other algorithms showed an excellent ability to distinguish between gross tumor area and normal liver tissue (mean AUC 0.9825, 0.9861,0.9727,0.9644 for Adaboost, random forest, logistic regression, naivem Bayes algorithm respectively). CONCLUSION: CT radiomics based on machine learning algorithms can accurately classify GTV and normal liver tissue, while the Xgboost and SVM algorithms served as the best complementary algorithms.

Improved brain metastases segmentation using generative adversarial network and conditional random field optimization mask R-CNN.

BACKGROUND: In radiotherapy, the delineation of the gross tumor volume (GTV) in brain metastases using computed tomography (CT) simulation localization is very important. However, despite the criticality of this process, a pronounced gap exists in the availability of tools tailored for the automatic segmentation of the GTV based on CT simulation localization images. PURPOSE: This study aims to fill this gap by devising an effective tool specifically for the automatic segmentation of the GTV using CT simulation localization images. METHODS: A dual-network generative adversarial network (GAN) architecture was developed, wherein the generator focused on refining CT images for more precise delineation, and the discriminator differentiated between real and augmented images. This architecture was coupled with the Mask R-CNN model to achieve meticulous GTV segmentation. An end-to-end training process facilitated the integration between the GAN and Mask R-CNN functionalities. Furthermore, a conditional random field (CRF) was incorporated to refine the initial masks generated by the Mask R-CNN model to ensure optimal segmentation accuracy. The performance was assessed using key metrics, namely, the Dice coefficient (DSC), intersection over union (IoU), accuracy, specificity, and sensitivity. RESULTS: The GAN+Mask R-CNN+CRF integration method in this study performs well in GTV segmentation. In particular, the model has an overall average DSC of 0.819 ± 0.102 and an IoU of 0.712 ± 0.111 in the internal validation. The overall average DSC in the external validation data is 0.726 ± 0.128 and the IoU is 0.640 ± 0.136. It demonstrates favorable generalization ability. CONCLUSION: The integration of the GAN, Mask R-CNN, and CRF optimization provides a pioneering tool for the sophisticated segmentation of the GTV in brain metastases using CT simulation localization images. The method proposed in this study can provide a robust automatic segmentation approach for brain metastases in the absence of MRI.

Simultaneous integrated boost intensity-modulated radiotherapy post breast-conserving surgery: clinical efficacy, adverse effects, and cosmetic outcomes in breast cancer patients.

BACKGROUND: Simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) is an innovative technique delivering a higher dose to the tumor bed while irradiating the entire breast. This study aims to assess the clinical outcomes, adverse effects, and cosmetic results of SIB-IMRT following breast-conserving surgery in breast cancer patients. METHODS: We conducted a retrospective analysis of 308 patients with stage 0-III breast cancer who underwent breast-conserving surgery and SIB-IMRT from January 2016 to December 2020. The prescribed doses included 1.85 Gy/27 fractions to the whole breast and 2.22 Gy/27 fractions or 2.20 Gy/27 fractions to the tumor bed. Primary endpoints included overall survival (OS), local-regional control (LRC), distant metastasis-free survival (DMFS), acute and late toxicities, and cosmetic outcomes. RESULTS: The median follow-up time was 36 months. The 3-year OS, LRC, and DMFS rates were 100%, 99.6%, and 99.2%, respectively. Five patients (1.8%) experienced local recurrence or distant metastasis, and one patient succumbed to distant metastasis. The most common acute toxicity was grade 1-2 skin reactions (91.6%). The most common late toxicity was grade 0-1 skin and subcutaneous tissue reactions (96.7%). Five patients (1.8%) developed grade 1-2 upper limb lymphedema, and three patients (1.1%) had grade 1 radiation pneumonitis. Among the 262 patients evaluated for cosmetic outcomes at least 2 years post-radiotherapy, 96.9% achieved excellent or good results, while 3.1% had fair or poor outcomes. CONCLUSIONS: SIB-IMRT after breast-conserving surgery in breast cancer patients demonstrated excellent clinical efficacy, mild acute and late toxicities, and satisfactory cosmetic outcomes in our study. SIB-IMRT appears to be a feasible and effective option for breast cancer patients suitable for breast-conserving surgery.

The potential and sustainable strategy for swine wastewater treatment: Resource recovery.

Swine wastewater is highly polluted with complex and harmful substances that require effective treatment to minimize environmental damage. There are three commonly used biological technologies for treating swine wastewater: conventional biological technology (CBT), microbial electrochemical technology (MET), and microalgae technology (MT). However, there is a lack of comparison among these technologies and a lack of understanding of their unique advantages and efficient operation strategies. This review aims to compare and contrast the characteristics, influencing factors, improvement methods, and microbial mechanisms of each technology. CBT is cost-effective but has low resource recovery efficiency, while MET and MT have the highest potential for resource recovery. However, all three technologies are affected by various factors and toxic substances such as heavy metals and antibiotics. Improved methods include exogenous/endogenous enhancement, series reactor operation, algal-bacterial symbiosis system construction, etc. Though MET is limited by construction costs, CBT and MT have practical applications. While swine wastewater treatment processes have developed automatic control systems, the application need further promotion. Furthermore, key functional microorganisms involved in CBT's pollutant removal or transformation have been detected, as have related genes. The unique electroactive microbial cooperation mode and symbiotic mode of MET and MT were also revealed, respectively. Importantly, the future research should focus on broadening the scope and scale of engineering applications, preventing and controlling emerging pollutants, improving automated management level, focusing on microbial synergistic metabolism, enhancing resource recovery performance, and building a circular economy based on low-cost and resource utilization.

Dose fall-off during the treatment of thoracic spine metastasis with CyberKnife stereotactic body radiation therapy (SBRT).

CyberKnife stereotactic body radiation therapy (SBRT) is becoming increasingly used for cancer treatment and, to maximize its clinical application, it is important to define the dosimetric characteristics, optimal dose, and fractionation regimens. The aim of this study was to evaluate the dose fall-off in two fractionated regimens of CyberKnife SBRT during the treatment of thoracic spinal metastasis. Patients with spinal metastasis involving a vertebra and pedicle were treated with 40 Gy in 5 fractions (n = 4), and patients with spinal metastasis involving only a vertebra received 33 Gy in 3 fractions (n = 4). A new approach was used to measure absolute dose fall-off distance, relative dose fall-off distance, and the dose fall-off per unit distance along four reference directions in the axial plane. Patients treated with 33 Gy/3 fractions had a greater absolute dose fall-off distance in direction 1 (from the point with maximum dose [Dmax] towards the spinal cord) and direction 3 (the opposite of direction 1), a greater relative dose fall-off distance in direction 3, and a lower dose fall-off per unit distance in direction 1 and 3 compared to patients treated with 40 Gy/5 fractions (all p < 0.05). Overall, the dose fall-off towards the spinal cord is rapid during the treatment of thoracic spinal metastasis with CyberKnife SBRT, which allows a higher dose of radiation to be delivered to the tumor and, at the same time, better protection of the spinal cord.