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We present two cases of cardiac metastases adjacent to the right ventricle in a 55-year-old male and a 61-year-old female, both treated with magnetic resonance (MR)-guided adaptive stereotactic radiation therapy (SBRT). The prescribed regimen was 30Gy delivered in 3 fractions using a 1.5 Tesla magnetic resonance linear accelerator (MR-linac). Patients exhibited favorable tolerance to the treatment, with no observed acute toxicity.

Remote-sensing-based interpretation of engineering geological lithology units provides essential lithological information for engineering planning, design, and construction projects. However, dense vegetation cover can easily interfere with the lithological spectral characteristics of optical remote sensing. Utilizing known geological background prototype-guided knowledge as a guide can mitigate interpretation interference from vegetation. Hence, for the interpretation of engineering geological lithology units, we aimed to develop a novel semantic segmentation network, LSBPnet, which combines a geological background prototype-guided learning model with a U-Net-based model. The geological background prototype-guided learning model employs lithological prototype features learned from the surrounding geological units of the predicted target to identify similarities with the predicted target's features. The model encompasses three steps: inputting known background images and known labels, learning prototype features of the background information, and learning target features based on the background information prototype perception. Using the engineering geological lithology of the Yangtze River's middle reaches as the focus area, which is a region with high vegetation cover, the proposed network achieved a 13.94% increase in the overall accuracy compared with that of commonly prevalent semantic segmentation networks. Incorporating the geological background prototype-guided knowledge helped to strengthen the distinction and relationship between the target and its surrounding lithological features, thereby improving the assessment of prediction outcomes. The diverse ablation experiments further highlighted the importance of incorporating background prototype-guided knowledge.

Abstract Planning for palliative radiotherapy is performed without the advantage of MR or PET imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative treatment of head and neck cancer. Two multi-institutional datasets of palliative-intent treatment plans were retrospectively acquired: a set of 102 non-contrast-enhanced CTs and a set of 96 contrast-enhanced CTs. The nnU-Net auto-segmentation network was chosen for its strength in medical image segmentation, and five approaches separately trained: (1) heuristic-cropped, non-contrast images with a single GTV channel, (2) cropping around a manually-placed point in the tumor center for non-contrast images with a single GTV channel, (3) contrast-enhanced images with a single GTV channel, (4) contrast-enhanced images with separate primary and nodal GTV channels, and (5) contrast-enhanced images along with synthetic MR images with separate primary and nodal GTV channels. Median Dice similarity coefficient ranged from 0.6 to 0.7, surface Dice from 0.30 to 0.56, and 95th Hausdorff distance from 14.7 to 19.7 mm across the five approaches. Only surface Dice exhibited statistically-significant difference across these five approaches using a two-tailed Wilcoxon Rank-Sum test (p ≤ 0.05). Our CT-only results met or exceeded published values for head and neck GTV autocontouring using multi-modality images. However, significant edits would be necessary before clinical use in palliative radiotherapy.

Purpose: MR-guided radiotherapy (MRgRT) has the advantage of utilizing high soft tissue contrast imaging to track daily changes in target and critical organs throughout the entire radiation treatment course. Head and neck (HN) stereotactic body radiation therapy (SBRT) has been increasingly used to treat localized lesions within a shorter timeframe. The purpose of this study is to examine the dosimetric difference between the step-and-shot intensity modulated radiation therapy (IMRT) plans on Elekta Unity and our clinical volumetric modulated arc therapy (VMAT) plans on Varian TrueBeam for HN SBRT. Method: Fourteen patients treated on TrueBeam sTx with VMAT treatment plans were re-planned in the Monaco treatment planning system for Elekta Unity MR-Linac (MRL). The plan qualities, including target coverage, conformity, homogeneity, nearby critical organ doses, gradient index and low dose bath volume, were compared between VMAT and Monaco IMRT plans. Additionally, we evaluated the Unity adaptive plans of adapt-to-position (ATP) and adapt-to-shape (ATS) workflows using simulated setup errors for five patients and assessed the outcomes of our treated patients. Results: Monaco IMRT plans achieved comparable results to VMAT plans in terms of target coverage, uniformity and homogeneity, with slightly higher target maximum and mean doses. The critical organ doses in Monaco IMRT plans all met clinical goals; however, the mean doses and low dose bath volumes were higher than in VMAT plans. The adaptive plans demonstrated that the ATP workflow may result in degraded target coverage and OAR doses for HN SBRT, while the ATS workflow can maintain the plan quality. Conclusion: The use of Monaco treatment planning and online adaptation can achieve dosimetric results comparable to VMAT plans, with the additional benefits of real-time tracking of target volume and nearby critical structures. This offers the potential to treat aggressive and variable tumors in HN SBRT and improve local control and treatment toxicity.

Background and Purpose: Application of different deformable dose accumulation (DDA) solutions makes institutional comparisons after online-adaptive magnetic resonance-guided radiotherapy (OA-MRgRT) challenging. The aim of this multi-institutional study was to analyze accuracy and agreement of DDA-implementations in OA-MRgRT. Material and Methods: One gold standard (GS) case deformed with a biomechanical-model and five clinical cases consisting of prostate (2x), cervix, liver, and lymph node cancer, treated with OA-MRgRT, were analyzed. Six centers conducted DDA using institutional implementations. Deformable image registration (DIR) and DDA results were compared using the contour metrics Dice Similarity Coefficient (DSC), surface-DSC, Hausdorff-distance (HD95%), and accumulated dose-volume histograms (DVHs) analyzed via intraclass correlation coefficient (ICC) and clinical dosimetric criteria (CDC). Results: For the GS, median DDA errors ranged from 0.0 to 2.8 Gy across contours and implementations. DIR of clinical cases resulted in DSC > 0.8 for up to 81.3% of contours and a variability of surface-DSC values depending on the implementation. Maximum HD95%=73.3 mm was found for duodenum in the liver case. Although DVH ICC > 0.90 was found after DDA for all but two contours, relevant absolute CDC differences were observed in clinical cases: Prostate I/II showed maximum differences in bladder V28Gy (10.2/7.6%), while for cervix, liver, and lymph node the highest differences were found for rectum D2cm3 (2.8 Gy), duodenum Dmax (7.1 Gy), and rectum D0.5cm3 (4.6 Gy). Conclusion: Overall, high agreement was found between the different DIR and DDA implementations. Case- and algorithm-dependent differences were observed, leading to potentially clinically relevant results. Larger studies are needed to define future DDA-guidelines.

Accurate estimation of seepage losses in large-scale canal systems and identification of their impact factors are important for improving water conveyance efficiency in agricultural districts. However, seepage losses can vary widely across different regions and periods, making it difficult to obtain a complete understanding of the variation process based solely on local scale studies. In addition, although there are currently some complex numerical models available for large-canal systems in agricultural districts, they are rarely used in practice due to their complexity. This study evaluated the regional-scale spatio-temporal seepage processes of the Zaohuo canal, a 55 km’s sub-main earthen canal located in the Hetao Irrigation District, China, under current and future water-saving conditions using MODFLOW-SWR. In addition, a pre-processing tool was developed to process spatial geographic data and spatial topology between different canals. Furthermore, the sensitivity of different influencing factors, such as the permeability of canal bed sediments, surface and groundwater level, and local lining, was also investigated. The optimal relationship between lining areas when partial lining is used and seepage losses was also investigated. The calculated water conveyance efficiency coefficient is 0.7871, which fits well with the reported results and proves the reliability of the simulation. In addition, it was found that seepage losses are most sensitive to the surface water level of the canal, followed by the permeability of canal bed sediments and then the groundwater level. Moreover, new hybrid lining can reduce the seepage losses by about 92.02%, but ongoing maintenance is vital. When lining the key portion of the canal, the seepage losses will be significantly reduced with the increase of lining area. The seepage losses reduction factor increases by 5.8% for every 1 × 105 m2 increase in lining area when the lining area is below 1 × 106 m2, while the effect is not significant when that limitation is exceeded. This study can support decision-making for water-saving projects in large water conveyance canals in regional-scale agriculture districts.

While current MR-Linac (MRL) treatment workflows utilize a large table overlay during CT simulation to convert indexing between the two machines, we developed a look-up-table (LUT) as an alternative approach. After populating the LUT, index conversion factors were verified at three separate table locations. The resultant root-mean-square isocenter shifts on the MRL were 0.04/0.08 cm, 0.08/0.07 cm, and 0.09/0.08 cm with/without using the table overlay during simulation in the lateral, longitudinal, and vertical directions, respectively, which is within registration tolerance. Clinical implementation of the LUT has resulted in a more efficient MRL treatment workflow while maintaining accurate patient setup.

Coastal nuclear power plants discharge large amounts of warm cooling water, which may have environmental impacts. This study proposes a method for determining the long-term impact area based on the average distribution of sea surface temperate (SST) increases. Taking the Daya Bay Nuclear Power Plant as a case study, 101 TM/ETM+ images acquired from 2000 to 2013 were used to obtain SST products. Cross-validation with NR_2P products showed that the accuracy of the SST products, in terms of the systematic error, root-mean-square error, and mean absolute error of 1,000 randomly selected verification points, was all 0.7. An annual SST cycle harmonic model was established. The mean difference between the modeled and observed SSTs was −2.1 to 2.5°C with a standard deviation range of 0–1°C. The long-term impact area was extracted by the harmonic analysis method and multi-year average method for comparison. The following conclusions can be drawn: 1) with sufficient SST samples, the temperature distributions of the two methods are similar, with the multi-year average method giving less noise and clearer boundaries. 2) When SST data are lacking for some months, the mean and standard deviation of the percentage of pixels belonging to areas of different temperature rise were calculated. The standard deviations of the two methods were both 0°C, the multi-year average method had a standard deviation of 0.506, while the harmonic analysis method had a value of 0.128. Overall, the harmonic analysis method makes it possible to obtain and evaluate the long-term stability impact area of the thermal discharge over a period of time comprehensively and quantitatively. Even though it introduces a small amount of noise, it has less dependence on the input SST products and could improve the stability and reliability of thermal discharge monitoring, providing technical support for precise pollution control.

Solid waste produced by the nonferrous smelting industry has a significant number of notable differences. The lack of recognition of solid waste characteristics is the main factor restricting its disposal and utilization. In this study, we analyzed the main production processes of the nonferrous smelting industry; identified the key production nodes of solid waste; and clarified the characteristics, including the physical, chemical, and pollution characteristics of solid wastes, through a large sample statistical analysis. We found similarities among solid wastes from a common generation source as well as notable differences among the different generation sources: slags and sludges from waste acid treatment and wastewater treatment units had a water content of 27.43–52.71% and 51.14–68.27%, respectively, which were significantly higher than those of other metallurgy and dust collection units; the pH of slags from an electrorefining unit was strongly alkaline; the mineral phase of sludges from wastewater treatment was only calcite; slags from a waste acid treatment unit were mainly in phase of gypsum, claudetite, and anglesite; the chemical composition of slags from pyrometallurgy and hydrometallurgy units was mainly SiO2 and Fe2O3. In this paper, we discuss a new classification method based on a common generation source for the first time. These results are beneficial to guide the disposal, utilization, and management of solid waste.

PurposeVariability in contouring structures of interest for radiotherapy continues to be challenging. Although training can reduce such variability, having radiation oncologists provide feedback can be impractical. We developed a contour training tool to provide real-time feedback to trainees, thereby reducing variability in contouring.MethodsWe developed a novel metric termed localized signed square distance (LSSD) to provide feedback to the trainee on how their contour compares with a reference contour, which is generated real-time by combining trainee contour and multiple expert radiation oncologist contours. Nine trainees performed contour training by using six randomly assigned training cases that included one test case of the heart and left ventricle (LV). The test case was repeated 30 days later to assess retention. The distribution of LSSD maps of the initial contour for the training cases was combined and compared with the distribution of LSSD maps of the final contours for all training cases. The difference in standard deviations from the initial to final LSSD maps, ΔLSSD, was computed both on a per-case basis and for the entire group.ResultsFor every training case, statistically significant ΔLSSD were observed for both the heart and LV. When all initial and final LSSD maps were aggregated for the training cases, before training, the mean LSSD ([range], standard deviation) was –0.8 mm ([–37.9, 34.9], 4.2) and 0.3 mm ([–25.1, 32.7], 4.8) for heart and LV, respectively. These were reduced to –0.1 mm ([–16.2, 7.3], 0.8) and 0.1 mm ([–6.6, 8.3], 0.7) for the final LSSD maps during the contour training sessions. For the retention case, the initial and final LSSD maps of the retention case were aggregated and were –1.5 mm ([–22.9, 19.9], 3.4) and –0.2 mm ([–4.5, 1.5], 0.7) for the heart and 1.8 mm ([–16.7, 34.5], 5.1) and 0.2 mm ([-3.9, 1.6],0.7) for the LV.ConclusionsA tool that uses real-time contouring feedback was developed and successfully used for contour training of nine trainees. In all cases, the utility was able to guide the trainee and ultimately reduce the variability of the trainee’s contouring.

Objectives: We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5 T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort. Methods: Thirty patients with HNSCC who received curative-intent RT at MD Anderson Cancer Center, were included. Baseline and weekly MRI were obtained, and various ADC parameters were extracted from the regions of interest (ROIs). Baseline and weekly ADC parameters were correlated with response during and after RT, and the recurrence using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman’s Rho test. Recursive partitioning analysis (RPA) identified the optimal ΔADC threshold associated with different oncologic outcomes. Results: There was a significant rise in all ADC parameters at different time points of RT compared to baseline for both gross primary disease (GTV-P) and gross nodal disease volumes (GTV-N). The increased ADC values for GTV-P were statistically significant only for primary tumors achieving complete remission (CR) during RT. RPA identified GTV-P ΔADC 5th percentile > 13% at the mid-RT as the most significant parameter associated with primary tumors’ CR during RT (p

In order to solve the problems of typical tailings resource utilization from Panxi region, the technology of comprehensive utilization of the low-grade tailings was studied. Based on the research results of mineralogy of tailings process, the technical route of "floating-magnetic-gravity echelon recovery of useful mineral——silicon fertilizer from tailings" suitable for the tailing property is determined. On the basis of the recovery and utilization of valuable elements, the hard-to-use tailing resources are transformed into mica concentrate withyield of 11.78%、K2O grade 7.77%、recovery rate of 25.92% and silicon fertilizer products with effective silicon more than 40%. The tailings can be reduced by 64.66%, thus realizing the resource recovery and reduction of tailing.

Abstract Manually delineating upper abdominal organs at risk (OARs) is a time-consuming task. To develop a deep-learning-based tool for accurate and robust auto-segmentation of these OARs, forty pancreatic cancer patients with contrast-enhanced breath-hold computed tomographic (CT) images were selected. We trained a three-dimensional (3D) U-Net ensemble that automatically segments all organ contours concurrently with the self-configuring nnU-Net framework. Our tool’s performance was assessed on a held-out test set of 30 patients quantitatively. Five radiation oncologists from three different institutions assessed the performance of the tool using a 5-point Likert scale on an additional 75 randomly selected test patients. The mean (± std. dev.) Dice similarity coefficient values between the automatic segmentation and the ground truth on contrast-enhanced CT images were 0.80 ± 0.08, 0.89 ± 0.05, 0.90 ± 0.06, 0.92 ± 0.03, 0.96 ± 0.01, 0.97 ± 0.01, 0.96 ± 0.01, and 0.96 ± 0.01 for the duodenum, small bowel, large bowel, stomach, liver, spleen, right kidney, and left kidney, respectively. 89.3% (contrast-enhanced) and 85.3% (non-contrast-enhanced) of duodenum contours were scored as a 3 or above, which required only minor edits. More than 90% of the other organs’ contours were scored as a 3 or above. Our tool achieved a high level of clinical acceptability with a small training dataset and provides accurate contours for treatment planning.

A considerable amount of secondary aluminum dross is generated in the aluminum refining process. Secondary aluminum dross (SAD) is hazardous waste because of its constituent pollutants, such as AlN, fluoride, chloride, and heavy metal pollutants. SAD treatment can be categorized into thermal and wet methods. The thermal process has attracted considerable research attention because of its simplicity and ability to prepare Al–Mg spinels, refractory materials, and ceramics and recover alumina during the treatment. However, at this stage, SAD pyrolysis processes are typically focused on the removal of single pollutants. Limited studies have explored the simultaneous removal of various pollutants and their interactions. This study focused on the pyroprocess in the SAD treatment process and investigated the SAD mechanism in the preparation of Al–Mg spinel, refractories, ceramics, and recycled alumina. Furthermore, the conversion of AlN, fluoride, chloride salts, and heavy metals, which are the main pollutants generated in the thermal reaction of SAD, and their control mechanisms were analyzed. The synergistic mechanism of SAD denitrification∖chlorine salt and fluoride fixation∖heavy metal was studied through the reaction mechanism of similar component minerals in the pyroprocess for improving the high-value utilization of SAD and scientific prevention and control of secondary pollution. Finally, the feasibility of preparing ceramic pellets from aluminum dross (AD) was evaluated. The results of the study can provide crucial development directions for SAD utilization.

PURPOSEAutomation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).DESIGNIn this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology.RESULTSRPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain.CONCLUSIONThe RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.

Abstract Root lodging due to strong storm wind is a common problem in maize (Zea mays) production, leading to reduced crop yield and quality and harvest efficiency. Little information is available on quantifying effects of vertical leaf area distribution on root lodging in crops such as maize. Anti-lodging index of root was computed by the formula: ALroot = Mroot / Mwind, where AL denotes anti-lodging index, and M moment of force. Mroot, root failure moment of force equals to moment arm times max root side-pulling force measured in situ by means of the digital pole dynamometer, and Mwind, wind resultant moment of force is estimated with vertical leaf area distribution and wind speed. Two maize cultivars were examined at 5 different growth stages from V8 to physiological maturity in 2019 and 2020, in Qingdao, China. Root anti-lodging index in tested cultivars fluctuated to a small extent within any year during whole growth period excluding at V8, while there was an inter-annual shift in index means (1.23 vs 0.84). Both root failure moment and wind resultant moment increased first and then decreased with the growth stage, and their influences on root anti-lodging index varied with the year. At wind grade 6, effect sizes, as contribution to root anti-lodging index, of root moment and wind moment were respectively 0.88 and 0.98. The difference in anti-lodging index between cultivars seemed to be disappearing as wind grade goes up. Root failure moment of force positively related to single root tensile resistance, root-soil ball volume, root number and total root length, whose correlation coefficient was the maximum of 0.94. Root anti-lodging index of maize proved stable from V8 on during whole growth period, and vertical leaf area distribution played a substantial role in maize root lodging in terms of wind resultant moment. Our findings provide the insights into root lodging events in crops such as maize, and would serve an approach to assessing crop root lodging resistance in breeding and cultivation programs.

Bauxite-type vanadium deposit in north sichuan is a newly discovered type of vanadium deposit. Through the study of process mineralogy and selectivity of vanadium, it is found that vanadium has two kinds of occurrence states: The main is an independent mineral in the form of vanadite, and the other is in the form of isomorphism in sericite and illite. The experimental study on the washability of vanadium ore shows that the bauxite type vanadium ore is economic. The valuable element vanadium and molybdenum in ore can be recovered effectively by the combined flowsheet of “ Recovery of sulfide by heavy separation- recovery of vanadium and molybdenum from tailings by roasting in air and alkaline leaching-Recovery of clay ore by leaching residue”. The associated pyrite and clay minerals in ore are utilized synthetically. After the test, the slag leaching rate of vanadium is 74.42%, the liquid leaching rate of vanadium is 75.97%, the slag leaching rate of molybdenum is 88.77%, the liquid leaching rate of molybdenum is 91.00%.

Abstract Low planting density and irrational nitrogen (N) fertilization are two common practices in conventional cropping of smallholder maize production in Huanghuaihai region of China. A 2-year field experiment was carried out to study the effects of N application and planting density on maize phenology, dry matter accumulation, profit, yield, N uptake and efficiency indices. The experiments included three N application levels (120 kg ha−1, N1; 180 kg ha−1, N2; 240 kg ha−1, N3) and three planting densities (60,000 plants ha−1, D1; 75,000 plants ha−1, D2; 90,000 plants ha−1, D3). Increasing N input and planting density delayed the physiological maturity and enhanced dry matter accumulation. Comparing with the traditional N3 level, grain yield and profit were kept stable at N2 level and decreased at N1 level, partial factor productivity of applied N (PFPN) and nitrogen efficiency ratio (NER) were increased with the decreasing of N level. Comparing with the traditional D1 density, grain yield, profit and PFPN were increased at D2 density and then kept stable at D3 density, NER was kept stable at D2 density and then decreased at D3 density. Based on the predicted maximum profit, the optimal combinations of N application and planting density were 199 kg ha−1 and 81,081 plants ha−1 in 2017, and 205 kg ha−1 and 84,782 plants ha−1 in 2018. The two optimal combinations had an increase of 17.6% for grain yield, 39.8% for PEPN, 3.6% for NRE than the traditional N3D1 treatment. Therefore, an appropriate combination of increased planting density with reduced N application could enhance profit and nitrogen use of summer maize in Huanghuaihai region of China.

The abandoned mines along the Yangtze River in Jiangsu Province is the key area along the Yangtze River Economic Belt, which need to be restored and governed. Among the ecological restoration projects, it has been one of the difficulties that how to quickly and intuitively track the progress of the distribution and restoration of a great many abandoned mines in the region. In this paper, the author takes the 10 km area on both sides of the Belt as study object. And selects high-resolution remote sensing images in each year from 2017 to 2020 as the data source. By human-computer interactive interpretation on the ArcGIS platform and field verification, the author obtains the information such as the distribution of open-pit abandoned mines, geological environment problems and ecological restoration in the study area. This paper mainly focus on the geological environment problems existing in abandoned mines and summarizes the ecological restoration measures. It is shown that it ’s a wide area need to be restored in Zhenjiang and Nanjing. The area of open-pit abandoned mines mainly focus on the quarries and transit sites of the mines, with construction limestone and construction sand mines as the main types of mines involved. The environmental problems mainly include topography and geomorphological destruction, geological disasters, ecological environment damage and soil and water pollution, etc. And the part rehabilitated and being rehabilitated of the study area show an increasing trend from 2018 to 2020. As of October 2020, the restoration area of abandoned mines has been effective, with 67.08% of the area restored. The main ecological restoration measures include natural restoration, soil backfilling, land leveling, slope cutting and integrated land management. It is recommended that the original landform of the mining area should be protected to the maximum extent and the land resources fully utilized when carrying out restoration and treatment. The results and suggestions provide technical reference for the ecological restoration and treatment of open-pit abandoned mines in the same type of area.

MRI-linear accelerator (MR-linac) devices have been introduced into clinical practice in recent years and have enabled MR-guided adaptive radiation therapy (MRgART). However, by accounting for anatomical changes throughout radiation therapy (RT) and delivering different treatment plans at each fraction, adaptive radiation therapy (ART) highlights several challenges in terms of calculating the total delivered dose. Dose accumulation strategies—which typically involve deformable image registration between planning images, deformable dose mapping, and voxel-wise dose summation—can be employed for ART to estimate the delivered dose. In MRgART, plan adaptation on MRI instead of CT necessitates additional considerations in the dose accumulation process because MRI pixel values do not contain the quantitative information used for dose calculation. In this review, we discuss considerations for dose accumulation specific to MRgART and in relation to current MR-linac clinical workflows. We present a general dose accumulation framework for MRgART and discuss relevant quality assurance criteria. Finally, we highlight the clinical importance of dose accumulation in the ART era as well as the possible ways in which dose accumulation can transform clinical practice and improve our ability to deliver personalized RT.

Surface deformation due to hydrocarbon extraction from buried reservoirs may gradually evolve to geological hazards, which can undermine the safety of infrastructure facilities. Monitoring the surface deformation and studying on the influencing factors of surface deformation have great significance to ensure the stability of oilfield development, and prevent geological hazards. In this study, Sentinel-1 interferometric synthetic aperture radar (InSAR) data of Karamay Oilfield acquired between January 2018 to December 2020 was used to map how the land surface has deformed in response to hydrocarbon exploitation. Based on the monitoring results of time series InSAR, geological data, and oilfield data, the correlations between the different factors and the surface deformation were analyzed. The results show that the reservoir buried depth, porosity and permeability have an impact on the surface deformation, and the influence on surface uplift is obviously greater than that on surface subsidence. Surface uplift decreases with the increasing buried depth and the decreasing porosity and permeability, and the correlation between porosity and surface uplift is the best. However, the impact is limited in the area with shallow reservoir depth, high porosity, and high permeability, such as the heavy oil blocks in the study area.

The increase of planting density is a dominant approach for the higher yield of maize. However, the stalks of some varieties are prone to lodging under high density conditions. Much research has been done on the evaluation of maize lodging resistance. But there are few comprehensive reports on the determination of maize lodging resistance in situ without injury under field conditions. This study introduces a non-destructive in situ tester to determine the lodging resistance of the different maize varieties in the field. The force value can be obtained by pulling the stalk to different angles with this instrument, which is used to evaluate the lodging resistance of maize varieties. From 2018 to 2020, a total of 1,172 sample plants from 113 maize varieties were tested for the lodging resistance of plants. The statistical results show that the values of force on maize plants at 45° inclination angles (F45) are appropriate to characterize maize lodging resistance in situ by nondestructive testing in the field. According to the F45 value, the maximum lodging resistance Fmax can be inferred. The formula is: Fmax =1.1354 F45 – 0.3358. The evaluation results of lodging resistance of different varieties of this study are basically consistent with the test results of three-point bending method, moving wind tunnel and other methods. Therefore, the F45 value is the optimal index for nondestructive evaluation of maize stalk-lodging resistance under the field-planting conditions.

Purpose: The clinical management of brain metastases after stereotactic radiosurgery (SRS) is difficult, because a physician must review follow-up magnetic resonance imaging (MRI) scans to determine treatment outcome, which is often labor intensive. The purpose of this study was to develop an automated framework to contour brain metastases in MRI to help treatment planning for SRS and understand its limitations. Methods and Materials: Two self-adaptive nnU-Net models trained on postcontrast 3-dimensional T1-weighted MRI scans from patients who underwent SRS were analyzed. Performance was evaluated by computing positive predictive value (PPV), sensitivity, and Dice similarity coefficient (DSC). The training and testing sets included 3482 metastases on 845 patient MRI scans and 930 metastases on 206 patient MRI scans, respectively. Results: In the per-patient analysis, PPV was 90.1% ± 17.7%, sensitivity 88.4% ± 18.0%, DSC 82.2% ± 9.5%, and false positive (FP) 0.4 ± 1.0. For large metastases (≥6 mm), the per-patient PPV was 95.6% ± 17.5%, sensitivity 94.5% ± 18.1%, DSC 86.8% ± 7.5%, and FP 0.1 ± 0.4. The quality of autosegmented true-positive (TP) contours was also assessed by 2 physicians using a 5-point scale for clinical acceptability. Seventy-five percent of contours were assigned scores of 4 or 5, which shows that contours could be used as-is in clinical application, and the remaining 25% were assigned a score of 3, which means they needed minor editing only. Notably, a deep dive into FPs indicated that 9% were TP metastases not identified on the original radiology review, but identified on subsequent follow-up imaging (early detection). Fifty-four percent were real metastases (TP) that were identified but purposefully not contoured for target treatment, mainly because the patient underwent whole-brain radiation therapy before/after SRS treatment. Conclusions: These findings show that our tool can help radiologists and radiation oncologists detect and contour tumors from MRI, make precise decisions about suspicious lesions, and potentially find lesions at early stages.

Finding out about the ecosystem damaged by mining development and carrying out ecological risk diagnoses are important prerequisites for formulating mine ecological restoration strategies. This study established an integrated approach to quantitatively analyze mining ecological risks by combining water conservation and biodiversity conservation ecosystem service functions with natural ecological conditions, and based on these, proposes appropriate mine ecological restoration strategies. Results show that: (1) A total of 14,874.80 hm2 of ecosystems were damaged in the Qinghai section of the Yellow River Basin, caused by mining excavation, crushing and hollow collapse, and of which 52.10% were located in national important ecological function areas and National Nature Reserves, which caused a decrease of the important ecosystem service functions of water conservation and biodiversity conservation in the area, and aggravated the ecological risks of the river source area; (2) The areas of high ecological risk and comparatively high ecological risk in the research area are 1,093,800 hm2 and 902,100 hm2, which accounted for 7.27% and 6.00% of the land area, respectively. Ecological risk hotspot areas are mainly distributed in the Qilian Mountains, Hehuang Valley, Sanjiangyuan and other key water systems and water sources; (3) According to the principle of “one mine, one policy”, we propose five mine ecological restoration models: ecological reconstruction, artificial assistance and protection and conservation, artificial assistance, protection and conservation and natural restoration. This study provides a reliable basis for exploring the status of mining ecological risk at the source of the Yellow River and scientifically carrying out ecological restoration and risk management.

Abstract Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients’ outcome and support clinical decision-making. However, radiomics features are sensitive to several factors, including scanning protocols. The purpose of this study was to investigate the robustness of magnetic resonance imaging (MRI) radiomics features with various MRI scanning protocol parameters and scanners using an MRI radiomics phantom. The variability of the radiomics features with different scanning parameters and repeatability measured using a test–retest scheme were evaluated using the coefficient of variation and intraclass correlation coefficient (ICC) for both T1- and T2-weighted images. For variability measures, the features were categorized into three groups: large, intermediate, and small variation. For repeatability measures, the average T1- and T2-weighted image ICCs for the phantom (0.963 and 0.959, respectively) were higher than those for a healthy volunteer (0.856 and 0.849, respectively). Our results demonstrated that various radiomics features are dependent on different scanning parameters and scanners. The radiomics features with a low coefficient of variation and high ICC for both the phantom and volunteer can be considered good candidates for MRI radiomics studies. The results of this study will assist current and future MRI radiomics studies.

Recent advances in integrating 1.5 Tesla magnetic resonance (MR) imaging with a linear accelerator (MR-Linac) allow MR-guided stereotactic body radiotherapy (SBRT) for prostate cancer. Choosing an optimal strategy for daily online plan adaptation is particularly important for MR-guided radiotherapy. We analyzed deformable dose accumulation on scans from four patients and found that daily anatomy changes had little impact on the delivered dose, with the dose to the prostate within 0.5% and dose to the rectum/bladder mostly less than 0.5 Gy. These findings could help in the choice of an optimal strategy for online plan adaptation for MR-guided prostate SBRT.

The arterial pulse wave is a physiological signal which can reflect the function of the human cardiovascular system. Owing to the measurement being convenient and safe, radial pulse waves have been often used in noninvasive monitoring of human health, which can further reflect the health status of the cardiovascular system, including information of the aorta and peripheral arteries. Moreover, radial pulse waves can assist clinical diagnosis in the prevention and treatment of cardiovascular disease. This paper systematically reviews the progress in analysis of pulse wave analysis, including pulse wave acquisition, waveform processing, pattern classification, parameter estimation, and clinical applications. In terms of waveform acquisition, this paper reviews a variety of methods to obtain radial pulse waves, including tonometry, photoplethysmography, ultrasound manometry, and flexible tactile pressure sensors. In the aspect of waveform processing, this paper summarizes the methods of radial pulse waves preprocessing and feature extraction. With the rapid development of machine learning and deep learning algorithms, radial pulse waves can be used to identify the status of human cardiovascular systems and to estimate parameters related to cardiovascular function. This paper also discusses the applications of radial pulse waves in clinical practice, including cardiovascular function evaluation and pulse diagnosis in traditional Chinese medicine. Some open-source databases and analysis software are also listed. The current development trend, challenges, and future directions of analysis of radial pulse waves are also offered.

Background: Recent studies highlight the carcinogenesis role of SHC-adaptor protein 1 (SHC1) in cancer initiation, development, and progression. However, its aberrant expression, diagnostic and prognostic value remain unknown in a variety of tumors.Methods: The SHC1 expression profiles were analyzed using GTEx database, TCGA database, Oncomine and CPTAC database. The survival analysis was conducted using GEPIA2, Kaplan-Meier Plotter, UALCAN, and PrognoScan. The diagnostic values of SHC1 were calculated with the “pROC” package in R software. The genetic alteration of SHC1 and mutations were analyzed using cBioPortal. TIMER2 was employed to estimate the correlations between SHC1 expression and tumor-infiltrating immune cells in the TCGA cohort. Enrichment analysis of SHC1 was conducted using the R package “clusterProfiler.”Results: SHC1 was ubiquitously highly expressed and closely associated with worse prognosis of multiple major cancer types (all p < 0.05). Further, SHC1 gene mutations were strongly linked to poor OS and DFS in SKCM (all p < 0.05). An enhanced phosphorylation level of SHC1 at the S139 site was observed in clear cell RCC. Additionally, the results revealed SHC1 expression was strongly linked to TMB, MMRs, MSI, TAMs, DNA methylation, m6A RNA methylation, tumor-associated immune infiltration, and immune checkpoints in multiple cancers (all p < 0.05). In addition, the results of the ROC analysis indicated the SHC1 exhibited strong diagnostic capability for KICH (AUC = 0.92), LIHC (AUC = 0.95), and PAAD (AUC = 0.95). Finally, enrichment analysis indicated that SHC1 may potentially involve in the regulation of numerous signaling pathways in cancer metabolism and protein phosphorylation-related functions.Conclusions: These findings highlight that SHC1 plays an important role in the tumor immune microenvironment, and SHC1 has been identified to have prognostic and diagnostic value in multiple cancers. Thus, SHC1 is a potential target for cancer immunotherapy and effective prognostic and diagnostic biomarker.

Polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs) are highly toxic and persistent compounds that provoke a wave of publicity. Bromophenols are important precursors for forming PBDD/Fs, and their reaction path has always been a research hotspot. In this study, the formation characteristic of PBDD/Fs from 2,4,6-TBP were studied. The yields of 2,3,7,8-substituted PBDD/Fs and 2,4,6,8-TBDF for the different thermal products ranged from 0.067 to 10.3 ng/g and 0.207–9.68 ng/g, respectively. The effects of adding Cu, Fe, and Sb2O3 were investigated and found to be more inclined to accelerate the formation of ortho-substituted PBDD/Fs than 2,3,7,8-PBDD/Fs. The formation pathways of 2,3,7,8-substituted PBDD/Fs and 2,4,6,8-TBDF were also proposed. 2,4,6,8-TBDF is generated in the C-C coupling reactions of some radical intermediates from the debromination of 2,4,6-TBP. The 2,3,7,8-PBDD/Fs are produced through more complex debromination, bromine substitution, and bromine rearrangement reactions. In addition, various catalytic effects on PBDD/F formation pathways were found, and the catalytic effect of Cu by the Ullmann reaction was the highest, while bromophenol oxidation by Fe was the highest. These results proved that both 2,3,7,8-substituted and non-2,3,7,8-substituted PBDD/Fs would be generated from 2,4,6-TBP, and the effects of the catalyst on the Br substituted position of 2,3,7,8-substituted PBDD/Fs were much lower than the Br-substituted position on bromophenol.

Abstract Purpose To quantify tumor anatomic change of non-small cell lung cancer (NSCLC) patients given passive-scattering proton therapy (PSPT) and intensity-modulated radiation therapy (IMRT) through 6–7 weeks of treatment, and analyze the correlation between anatomic change and the need to adopt adaptive radiotherapy (ART). Materials and methods Weekly 4D CT sets of 32 patients (8/8 IMRT with/without ART, 8/8 PSPT with/without ART) acquired during treatment, were registered to the planning CT using an in-house developed deformable registration algorithm. The anatomic change was quantified as the mean variation of the region of interest (ROI) relative to the planning CT by averaging the magnitude of deformation vectors of all voxels within the ROI contour. Mean variations of GTV and CTV were compared between subgroups classified by ART status and treatment modality using the independent t-test. Logistic regression analysis was performed to clarify the effect of anatomic change on the probability of ART adoption. Results There was no significant difference (p = 0.679) for the time-averaged mean CTV variations from the planning CT between IMRT (7.61 ± 2.80 mm) and PSPT (7.21 ± 2.67 mm) patients. However, a significant difference (p = 0.001) was observed between ART (8.93 ± 2.19 mm) and non-ART (5.90 ± 2.33 mm) patients, when treatment modality was not considered. Mean CTV variation from the planning CT in all patients increases significantly (p

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is ‘clinical acceptability’? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of ‘clinical acceptability’ and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

Purpose: To provide a series of suggestions for other Medical Physics practices to follow in order to provide effective radiation therapy treatments during the COVID-19 pandemic. Methods and Materials: We reviewed our entire Radiation Oncology infrastructure to identify a series of workflows and policy changes that we implemented during the pandemic that yielded more effective practices during this time. Results: We identified a structured list of several suggestions that can help other Medical Physics practices overcome the challenges involved in delivering high quality radiotherapy services during this pandemic. Conclusions: Our facility encompasses 4 smaller Houston Area Locations (HALs), a main campus with 8 distinct services based on treatment site (ie. Thoracic, Head and Neck, Breast, Gastrointestinal, Gynecology, Genitourinary, Hematologic Malignancies, Melanoma and Sarcoma and Central Nervous System/Pediatrics), a Proton Center facility, an MR-Linac, a Gamma Knife clinic and an array of brachytherapy services. Due to the scope of our services, we have gained experience in dealing with the rapidly changing pandemic effects on our clinical practice. Our paper provides a resource to other Medical Physics practices in search of workflows that have been resilient during these challenging times.

Purpose: The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. Methods: In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. Results: The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. Conclusion: We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics.

Soil salinization is a major eco-environmental problem in irrigated agro-ecosystems. Understanding regional soil salinity spatial patterns and seasonal dynamics and their driving factors under changing environments is beneficial to managing soil salinity to maintain agricultural production in arid agricultural areas. To better investigate this topic, soil salinity was measured, ranging from topsoil to the depth of 1.8 m in an irrigation district with 68 sampling sites before and after the crop growing seasons of the dry year of 2017 and wet year of 2018. Soil texture, groundwater table depth, groundwater salinity, and crop type were monitored. The results indicated that an increase in soil salinity in the root zone (0–0.6 m) was accompanied by a decrease in soil salinity in the deep soil (0.6–1.8 m) through the crop growing season due to water movement from the deep layer to shallow layer, whereas the opposite trend was observed during the fallow seasons. During the dry year, the area with soil desalted was measured to be 19.89%, 14.42%, and 2.78% lower at depths of 0–0.6 m, 0.6–1.2 m, and 1.2–1.8 m than that during the wet year. The groundwater table depth in the crop growing season had the least impact on the change in root zone soil salinity (p > 0.05). Interactions between crop types and groundwater table depth had a significant effect on the change of soil salinity in the root zone during the growing season of the dry year, but were insignificant during the wet year. Crop types, groundwater table depth, and climate conditions determined the contribution of shallow groundwater to crop water consumption and, to a greater extent, soil salinity. Regression tree analysis showed that groundwater salinity and soil texture had a greater influence on soil salinity than groundwater table depth and land elevation. The effect of groundwater on soil salinity is strongly related to soil texture, and the salinity of fine-textured soil was 36–54% greater than that of coarse-textured soil due to large capillary action. Therefore, we suggest strengthening groundwater management in areas with fine-textured soil to relieve soil salinization, particularly during dry years.

Land cover classification (LCC) of heterogeneous mining areas is important for understanding the influence of mining activities on regional geo-environments. Hyperspectral remote sensing images (HSI) provide spectral information and influence LCC. Convolutional neural networks (CNNs) improve the performance of hyperspectral image classification with their powerful feature learning ability. However, if pixel-wise spectra are used as inputs to CNNs, they are ineffective in solving spatial relationships. To address the issue of insufficient spatial information in CNNs, capsule networks adopt a vector to represent position transformation information. Herein, we combine a clustering-based band selection method and residual and capsule networks to create a deep model named ResCapsNet. We tested the robustness of ResCapsNet using Gaofen-5 Imagery. The images covered two heterogeneous study areas in Wuhan City and Xinjiang Province, with spatially weakly dependent and spatially basically independent datasets, respectively. Compared with other methods, the model achieved the best performances, with averaged overall accuracies of 98.45 and 82.80% for Wuhan study area, and 92.82 and 70.88% for Xinjiang study area. Four transfer learning methods were investigated for cross-training and prediction of those two areas and achieved good results. In summary, the proposed model can effectively improve the classification accuracy of HSI in heterogeneous environments.

Irrigated agriculture in arid and semi-arid regions is seriously threatened by water shortage and soil salinization. The well-canal conjunctive irrigation scheme provides a stable groundwater resource for irrigation and can reduce surface salt accumulation by decreasing the groundwater levels, which makes it more suitable to alleviate the problems of irrigated agriculture in arid and semi-arid regions. However, the soil salinization process requires assessment on regional spatial and decadal time scales, as it is a continuous but slow change. Therefore, a water and salt balance model (WSBM) for well-canal conjunctive irrigation is developed herein to obtain long-term predictions of regional root zone salinity dynamics in canal- and well-irrigated areas. In the developed model, the characteristic length of the well-canal conjunctive irrigated area (Lc) is used to couple the canal- and well-irrigated areas. The performance of the WSBM as well as a sensitivity analysis and the value rule of the special parameter Lc are evaluated by comparing the simulation results with those derived from the MODFLOW. The results demonstrate the validity of the developed model, and the special parameter Lc is found to be insensitive, with a value approximately two-thirds of the center distance when the canal and well irrigation districts are regularly adjacent or centrosymmetric. Moreover, when a real-world application is adopted, the water table depth and root-zone soil salinity are simulated in the Longsheng well-canal irrigation area in the Hetao Irrigation District, Inner Mongolia, China. Water table depth and soil salinity collected from 2002–2005 and from 2006–2020 are used to calibrate and validate the model. The calibrated model is subsequently used to predict soil salinity dynamics in the next 100 years under current and future water-saving conditions. The predictions indicate that the soil salinity is basically stable at a relatively low level (

PurposeTo automate the estimation of swallowing motion from 2D MR cine images using deformable registration for future applications of personalized margin reduction in head and neck radiotherapy and outcome assessment of radiation-associated dysphagia.MethodsTwenty-one patients with serial 2D FSPGR-MR cine scans of the head and neck conducted through the course of definitive radiotherapy for oropharyngeal cancer. Included patients had at least one cine scan before, during, or after radiotherapy, with a total of 52 cine scans. Contours of 7 swallowing related regions-of-interest (ROIs), including pharyngeal constrictor, epiglottis, base of tongue, geniohyoid, hyoid, soft palate, and larynx, were manually delineated from consecutive frames of the cine scan covering at least one swallowing cycle. We applied a modified thin-plate-spline robust-point-matching algorithm to register the point sets of each ROI automatically over frames. The deformation vector fields from the registration were then used to estimate the motion during swallowing for each ROI. Registration errors were estimated by comparing the deformed contours with the manual contours.ResultsOn average 22 frames of each cine scan were contoured. The registration for one cine scan (7 ROIs over 22 frames) on average took roughly 22 minutes. A number of 8018 registrations were successfully batch processed without human interaction after the contours were drawn. The average registration error for all ROIs and all patients was 0.36 mm (range: 0.06 mm- 2.06 mm). Larynx had the average largest motion in superior direction of all structures under consideration (range: 0.0 mm- 58.7 mm). Geniohyoid had the smallest overall motion of all ROIs under consideration and the superior-inferior motion was larger than the anterior-posterior motion for all ROIs.ConclusionWe developed and validated a deformable registration framework to automate the estimation of swallowing motion from 2D MR cine scans.

Purpose: We assessed automated contouring of normal structures for patients with head-and-neck cancer (HNC) using a multiatlas deformable-image-registration algorithm to better provide a fully automated radiation treatment planning solution for low- and middle-income countries, provide quantitative analysis, and determine acceptability worldwide. Methods: Autocontours of eight normal structures (brain, brainstem, cochleae, eyes, lungs, mandible, parotid glands, and spinal cord) from 128 patients with HNC were retrospectively scored by a dedicated HNC radiation oncologist. Contours from a 10-patient subset were evaluated by five additional radiation oncologists from international partner institutions, and interphysician variability was assessed. Quantitative agreement of autocontours with independently physician-drawn structures was assessed using the Dice similarity coefficient and mean surface and Hausdorff distances. Automated contouring was then implemented clinically and has been used for 166 patients, and contours were quantitatively compared with the physician-edited autocontours using the same metrics. Results: Retrospectively, 87% of normal structure contours were rated as acceptable for use in dose-volume-histogram–based planning without edit. Upon clinical implementation, 50% of contours were not edited for use in treatment planning. The mean (± standard deviation) Dice similarity coefficient of autocontours compared with physician-edited autocontours for parotid glands (0.92 ± 0.10), brainstem (0.95 ± 0.09), and spinal cord (0.92 ± 0.12) indicate that only minor edits were performed. The average mean surface and Hausdorff distances for all structures were less than 0.15 mm and 1.8 mm, respectively. Conclusion: Automated contouring of normal structures generates reliable contours that require only minimal editing, as judged by retrospective ratings from multiple international centers and clinical integration. Autocontours are acceptable for treatment planning with no or, at most, minor edits, suggesting that automated contouring is feasible for clinical use and in the ongoing development of automated radiation treatment planning algorithms.

Abstract Personalized cancer therapy seeks to tailor treatment to an individual patient’s biology. Therefore, a means to characterize radiosensitivity is necessary. In this study, we investigated radiosensitivity in the normal esophagus using an imaging biomarker of radiation-response and esophageal toxicity, esophageal expansion, as a method to quantify radiosensitivity in 134 non-small-cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiosensitivity. Patients within the cluster of higher response and lower dose were labelled as radiosensitive. This information was used as a variable in toxicity prediction modelling (lasso logistic regression). The resultant model performance was quantified and compared to toxicity prediction modelling without utilizing radiosensitivity information. The esophageal expansion-response was highly variable between patients, even for similar radiation doses. K-Means clustering was able to identify three patient subgroups of radiosensitivity: radiosensitive, radio-normal, and radioresistant groups. Inclusion of the radiosensitive variable improved lasso logistic regression models compared to model performance without radiosensitivity information. Esophageal radiosensitivity can be quantified using esophageal expansion and K-Means clustering to improve toxicity prediction modelling. Finally, this methodology may be applied in clinical trials to validate pre-treatment biomarkers of esophageal toxicity.

Abstract Radiomics is the use of quantitative imaging features extracted from medical images to characterize tumor pathology or heterogeneity. Features measured at pretreatment have successfully predicted patient outcomes in numerous cancer sites. This project was designed to determine whether radiomics features measured from non–small cell lung cancer (NSCLC) change during therapy and whether those features (delta-radiomics features) can improve prognostic models. Features were calculated from pretreatment and weekly intra-treatment computed tomography images for 107 patients with stage III NSCLC. Pretreatment images were used to determine feature-specific image preprocessing. Linear mixed-effects models were used to identify features that changed significantly with dose-fraction. Multivariate models were built for overall survival, distant metastases, and local recurrence using only clinical factors, clinical factors and pretreatment radiomics features, and clinical factors, pretreatment radiomics features, and delta-radiomics features. All of the radiomics features changed significantly during radiation therapy. For overall survival and distant metastases, pretreatment compactness improved the c-index. For local recurrence, pretreatment imaging features were not prognostic, while texture-strength measured at the end of treatment significantly stratified high- and low-risk patients. These results suggest radiomics features change due to radiation therapy and their values at the end of treatment may be indicators of tumor response.

The suitable groundwater exploitation scheme in freezing-thawing agricultural areas under the well-canal conjunctive irrigation conditions is confronted with two major challenges, which are computationally expensive local grid refinements along wells, and the model suitability problem in the freezing-thawing period. In this study, an empirical method for groundwater level prediction in the freezing-thawing period was developed and integrated with the local grid refinement groundwater model MODFLOW-LGR for the groundwater process prediction. The model was then applied to estimate the suitable groundwater exploitation scheme, including the size of well-irrigated area and the irrigation area of single well. The results showed that suitable size of well-irrigated area should be smaller than 15 × 106 m2, and the recommended irrigation area of single well as 15 × 104 m2 to 19 × 104 m2. The recommended layout parameters of groundwater exploitation were further used to plan the well-canal conjunctive irrigation scheme in Yongji irrigation district located in northern China. This study provides an important pilot example of the conjunctive use of groundwater and surface water in arid irrigation areas with a seasonal freezing-thawing period.

Water storage in unsaturated and saturated zones during the crop non-growing season is one of the important supplementary water resources to meet crop water requirements in arid areas with shallow water table depth. It is necessary to analyze utilization of the soil-ground water storage during the crop growing season and its attribution to irrigation during the non-growing season. To facilitate the analysis, a new method based on measurements of soil moisture content and water table depth is developed. The measurements used in this study include (1) 15-year data of soil moisture content within a depth of 1 m from the land surface and water table depth measured in Jiefangzha, including its four subareas and (2) 4-year data of the same kind in Yonglian, located in arid northern China. The soil-ground water storage utilization is calculated as the difference of water storage between the beginning and end of the crop growing season in the whole computational soil profile. The results of average soil-ground water storage utilization in Jiefangzha and its four subareas and Yonglian are 121 mm, 126 mm, 113 mm, 124 mm, 185 mm and 117 mm, and the corresponding average utilization efficiencies in the non-growing season are 32.2%, 32.5%, 31.5%, 31.6%, 57.3% and 47.6%, respectively. Further, the water table fluctuation method was used to estimate the variation in water storage. The coefficients of soil-ground water storage utilization, soil-ground water storage utilization below 1 m soil depth and ground water utilization are defined, and their average values are 0.271, 0.111 and 0.026 in Jiefangzha, respectively. Then, the contribution of soil-ground water storage utilization to actual evapotranspiration is evaluated, which are over 23.5% in Jiefangzha and Yonglian. These results indicate that the soil-ground water storage plays an important role in the ecological environment in arid areas with shallow water table depth.

This paper proposed primary factors for preliminary screening of candidate mines and annual monitoring of green mines based on integrated analysis on green mine construction requirements, assessment indicators, etc.; introduced technical procedure, work content and work method of monitoring through example analysis, and preliminarily built a technology system for preliminary screening of candidate mines and annual monitoring of green mines.

With the continuous improvement of the understanding of the geological law and continuous innovation of unconventional oil and gas exploration and mining technology, China has made great breakthroughs in newly-added geological reserves of unconventional oil and gas resources, such as shale gas, coalbed methane, etc. But for many reasons, attention has not been paid to oil and gas resources (petroleum, natural gas, coalbed methane, shale gas), and regional remote sensing monitoring research has not been carried out. Based on high-resolution remote sensing data of the year 2018 and human-computer interactive interpretation technique, this paper built remote sensing interpretation signs of oil and gas mines, carried out exploration of remote sensing monitoring methods for oil and gas mines, completed remote sensing monitoring over development status of oil and gas mines in Ordos Basin, and proved feasibility of remote sensing monitoring method.

[This corrects the article DOI: 10.1371/journal.pone.0178524.].

PURPOSE:To evaluate the uncertainty of radiomics features from contrast-enhanced breath-hold helical CT scans of non-small cell lung cancer for both manual and semi-automatic segmentation due to intra-observer, inter-observer, and inter-software reliability. METHODS:Three radiation oncologists manually delineated lung tumors twice from 10 CT scans using two software tools (3D-Slicer and MIM Maestro). Additionally, three observers without formal clinical training were instructed to use two semi-automatic segmentation tools, Lesion Sizing Toolkit (LSTK) and GrowCut, to delineate the same tumor volumes. The accuracy of the semi-automatic contours was assessed by comparison with physician manual contours using Dice similarity coefficients and Hausdorff distances. Eighty-three radiomics features were calculated for each delineated tumor contour. Informative features were identified based on their dynamic range and correlation to other features. Feature reliability was then evaluated using intra-class correlation coefficients (ICC). Feature range was used to evaluate the uncertainty of the segmentation methods. RESULTS:From the initial set of 83 features, 40 radiomics features were found to be informative, and these 40 features were used in the subsequent analyses. For both intra-observer and inter-observer reliability, LSTK had higher reliability than GrowCut and the two manual segmentation tools. All observers achieved consistently high ICC values when using LSTK, but the ICC value varied greatly for each observer when using GrowCut and the manual segmentation tools. For inter-software reliability, features were not reproducible across the software tools for either manual or semi-automatic segmentation methods. Additionally, no feature category was found to be more reproducible than another feature category. Feature ranges of LSTK contours were smaller than those of manual contours for all features. CONCLUSION:Radiomics features extracted from LSTK contours were highly reliable across and among observers. With semi-automatic segmentation tools, observers without formal clinical training were comparable to physicians in evaluating tumor segmentation.

In order to test the feasibility of computer simulation in field maize planting, the selection of the method of single seed precise sowing in maize is studied based on the quadratic function model Y = A×(D-Dm)2+Ym, which depicts the relationship between maize yield and planting density. And the advantages and disadvantages of the two planting methods under the condition of single seed sowing are also compared: Method 1 is optimum density planting, while Method 2 is the ideal seedling emergence number planting. It is found that the yield reduction rate and yield fluctuation of Method 2 are all lower than those of Method 1. The yield of Method 2 increased by at least 0.043 t/hm2, and showed more advantages over Method 1 with higher yield level. Further study made on the influence of seedling emergence rate on the yield of maize finds that the yields of the two methods are both highly positively correlated with the seedling emergence rate and the standard deviations of their yields are both highly negatively correlated with the seedling emergence rate. For the study of the break-up problem of sparse caused by the method of single seed precise sowing, the definition of seedling missing spots is put forward. The study found that the relationship between number of hundred-dot spot and field seedling emergence rate is as the parabola function y = -189.32x2 + 309.55x - 118.95 and the relationship between number of spot missing seedling and field seedling emergence rate is as the negative exponent function y = 395.69e-6.144x. The results may help to guide the maize seeds production and single seed precise sowing to some extent.

Consistent pixel sizes are of fundamental importance for assessing texture features that relate intensity and spatial information in radiomics studies. To correct for the effects of variable pixel sizes, we combined image resampling with Butterworth filtering in the frequency domain and tested the correction on computed tomography (CT) scans of lung cancer patients reconstructed 5 times with pixel sizes varying from 0.59 to 0.98 mm. One hundred fifty radiomics features were calculated for each preprocessing and field-of-view combination. Intra-patient agreement and inter-patient agreement were compared using the overall concordance correlation coefficient (OCCC). To further evaluate the corrections, hierarchical clustering was used to identify patient scans before and after correction. To assess the general applicability of the corrections, they were applied to 17 CT scans of a radiomics phantom. The reduction in the inter-scanner variability relative to non-small cell lung cancer patient scans was quantified. The variation in pixel sizes caused the intra-patient variability to be large (OCCC

Endoscopic examinations are frequently-used procedures for patients with head and neck cancer undergoing radiotherapy, but radiation treatment plans are created on computed tomography (CT) scans. Image registration between endoscopic video and CT could be used to improve treatment planning and analysis of radiation-related normal tissue toxicity. The purpose of this study was to explore the feasibility of endoscopy-CT image registration without prospective physical tracking of the endoscope during the examination.A novel registration technique called Location Search was developed. This technique uses physical constraints on the endoscope's view direction to search for the virtual endoscope coordinates that maximize the similarity between the endoscopic video frame and the virtual endoscopic image. Its performance was tested on phantom and patient images and compared to an established registration technique, Frame-To-Frame Tracking.In phantoms, Location Search had average registration errors of 0.55 ± 0.60 cm for point measurements and 0.29 ± 0.15 cm for object surface measurements. Frame-To-Frame Tracking achieved similar results on some frames, but it failed on others due to the virtual endoscope becoming lost. This weakness was more pronounced in patients, where Frame-To-Frame tracking could not make it through the nasal cavity. On successful patient video frames, Location Search was able to find endoscope positions with an average distance of 0.98 ± 0.53 cm away from the ground truth positions. However, it failed on many frames due to false similarity matches caused by anatomical structural differences between the endoscopic video and the virtual endoscopic images.Endoscopy-CT image registration without prospective physical tracking of the endoscope is possible, but more development is required to achieve an accuracy suitable for clinical translation.