Thermal utilization techniques and strategies for secondary aluminum dross: A review.

Secondary aluminum ash (SAD) disposal is challenging, particularly in developing countries, and presents severe eco-environmental risks. This paper presents the treatment techniques, mechanisms, and effects of SAD at the current technical-economic level based on aluminum ash's resource utilization and environmental properties. Five recovery techniques were summarized based on aluminum's recoverability in SAD. Four traditional utilization methods were outlined as per the utilization of alumina in SAD. Three new utilization methods of SAD were summarized based on the removability (or convertibility) of aluminum nitride in SAD. The R-U-R (recoverability, utilizability, and removability) theory of SAD was formed based on several studies that helped identify the fingerprint of SAD. Furthermore, the utilization strategies of SAD, which supported the recycling of aluminum ash, were proposed. To form a perfect fingerprint database and develop various relevant techniques, future research must focus on an extensive examination of the characteristics of aluminum ash. This research will be advantageous for addressing the resource and environmental challenges of aluminum ash.

Roles of red mud in remediation of contaminated soil in mining areas: Mechanisms, advances and perspectives.

Red mud (RM) is a kind of strong alkaline solid waste produced from the aluminum industry, which contributes significantly to environmental pollution and can cause severe health issues.Currently, RM is widely recognized as a potential material for soil remediation because of its rich metal oxide content, such as Fe/Al oxides. However, there is no comprehensive description on the roles of RM in passivation remediation of contaminated soil in mining areas. This review summarizes the mechanisms of passivation of heavy metals (HMs) in contaminated soil by RM, including precipitation, adsorption and ion exchange. Besides the effects of adding RM on soil physicochemical properties, heavy metal forms and ecological environment are further elaborated. Moreover, using the co-hydrothermal carbonization of RM and biomass for enhancing the efficiency of contaminated soil remediation is proposed as the main prospective research. This paper provides technical references for the resource utilization of RM and the treatment of heavy metal-contaminated soil.

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation. METHODS: Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer radiotherapy. A comprehensive search of optimal hyperparameters for all models was conducted by varying the initial learning rate, image normalization methods, and (when appropriate) convolutional kernel size, the number of learnable parameters via network depth and the number of feature maps per convolution, and nonlinear activation functions. This yielded over 1700 unique models, which were all trained until performance converged and then tested on a separate dataset. RESULTS: Of all hyperparameters, the choice of initial learning rate was most consistently significant for improved performance on the test set, with all top-performing models using learning rates of 0.0001. The optimal image normalization was not consistent across architectures. High overlap (mean Dice similarity coefficient = 0.98) and surface distance agreement (mean surface distance < 2 mm) were achieved between the treatment field apertures for all architectures using the identified best hyperparameters. Overlap Dice similarity coefficient (DSC) and distance metrics (mean surface distance and Hausdorff distance) indicated that DeepLabv3+ and D-LinkNet architectures were least sensitive to initial hyperparameter selection. CONCLUSION: DeepLabv3+ and D-LinkNet are most robust to initial hyperparameter selection. Learning rate, nonlinear activation function, and kernel size are also important hyperparameters for improving performance.

Pyrolytic kinetics, reaction mechanisms and gas emissions of waste automotive paint sludge via TG-FTIR and Py-GC/MS.

The present study experimentally quantified the pyrolysis behaviors of waste solvent-based automotive paint sludge (OAPS) and water-based automotive paint sludge (WAPS) at four different heating rates using thermogravimetric-Fourier transform infrared (TG-FTIR) spectrometry and pyrolysis-gas chromatography-mass (Py-GC/MS) spectrometry analyses. Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods combined with the master-plots method were employed to investigate the pyrolysis kinetics and reaction mechanisms of waste automotive paint sludge. Three reaction stages and three reaction peaks in stage 2 were distinguished for both OAPS and WAPS degradation. The average activation energy (Ea) estimates for OAPS (FWO: 179.09 kJ/mol; KAS: 168.28 kJ/mol) were slightly higher than WAPS (FWO: 175.90 kJ/mol; KAS: 164.80 kJ/mol) according to FWO and KAS methods. The main pyrolysis reaction mechanisms of both OAPS and WAPS closely matched with the order-based model corresponding to 3rd and 2nd order random nucleation on an individual particle. The evolved gas species of CH4, CO2, phenols, NH3, H2O, and CO from OAPS and WAPS pyrolysis were identified by TG-FTIR. According to Py-GC/MS, hydrocarbons (47.2%) and O-components (42.7%) were relatively large after OAPS and WAPS pyrolysis, respectively. Melamine was the most abundant N-component product after pyrolysis of OAPS (5.8%) and WAPS (4.8%).

Occurrence and formation pathways analysis of PBDD/Fs from 2,4,6-tribromophenol under thermal reaction conditions.

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.

Impact of geometric distortion on dose deviation for photon and proton treatment plans.

We investigated the dose deviation related to geometric distortion and dose gradient on magnetic resonance-only treatment planning for intensity-modulated radiation therapy and proton therapy. The residual geometric distortion of two different magnetic resonance imaging (MRI) sequences (A) and (B) was applied in the computed tomography image and the structure set of each patient through a polynomial MRI geometric distortion model to simulate MRI-based treatment planning. A 3D histogram was generated to specify the relationship of dose deviation to geometric distortion and dose gradient. When the dose gradient (Gd ) approached zero, the maximum dose deviation reached 1.64% and 2.71% for photon plans of sequences A and B, respectively. For proton plans, the maximum dose deviation reached 3.15% and 4.89% for sequences A and B, respectively. When the geometric distortion (d) was close to zero, the maximum dose deviation was less than 0.8% for photon and proton plans of both sequences. Under extreme conditions (d = 2 mm and Gd  = 4.5%/mm), the median value of dose deviation reached 3% and 3.49% for photon and proton plans, respectively for sequence A, and 2.93% and 4.55% for photon and proton plans, respectively, for sequence B. We demonstrate that the dose deviation is specific to MRI hardware parameters. Compared to the photon plan, the proton plan is more sensitive to the changes in geometric distortion. For typical clinical MRI geometric distortion (d ≤2 mm), the median dose deviation is expected to be within 3% and 5% for photon and proton plans, respectively.

Dosimetric analysis of MR-LINAC treatment plans for salvage spine SBRT re-irradiation.

PURPOSE: We investigated the feasibility of thoracic spine stereotactic body radiotherapy (SBRT) using the Elekta Unity magnetic resonance-guided linear accelerator (MRL) in patients who received prior radiotherapy. We hypothesized that Monaco treatment plans can improve the gross tumor volume minimum dose (GTVmin) with spinal cord preservation and maintain consistent plan quality during daily adaptation. METHODS: Pinnacle clinical plans for 10 patients who underwent thoracic spine SBRT (after prior radiotherapy) were regenerated in the Monaco treatment planning system for the Elekta Unity MRL using 9 and 13 intensity-modulated radiotherapy (IMRT) beams. Monaco adapt-to-position (ATP) and adapt-to-shape (ATS) workflow plans were generated using magnetic resonance imaging with a simulated daily positional setup deviation, and these adaptive plans were compared with Monaco reference plans. Plan quality measures included target coverage, Paddick conformity index, gradient index, homogeneity index, spinal cord D0.01cc , esophagus D0.01cc , lung V10, and skin D0.01cc . RESULTS: GTVmin values from the Monaco 9-beam and 13-beam plans were significantly higher than those from Pinnacle plans (p < 0.01) with similar spinal cord dose. Spinal cord D0.01cc , esophagus D0.01cc , and lung V10 did not statistically differ among the three plans. The electron-return effect did not induce remarkable dose effects around the lungs or skin. While in the ATP workflow, a large increase in GTVmin was observed at the cost of a 10%-50% increase in spinal cord D0.01cc , in the ATS workflow, the spinal cord dose increase was maintained within 3% of the reference plan. CONCLUSION: These findings show that MRL plans for thoracic spine SBRT are safe and feasible, allowing tumor dose escalation with spinal cord preservation and consistent daily plan adaptation using the ATS workflow. Careful plan review of hot spots and lung dose is necessary for safe MRL-based treatment.

Brain stereotactic radiosurgery using MR-guided online adaptive planning for daily setup variation: An end-to-end test.

Online magnetic resonance (MR)-guided radiotherapy is expected to benefit brain stereotactic radiosurgery (SRS) due to superior soft tissue contrast and capability of daily adaptive planning. The purpose of this study was to investigate daily adaptive plan quality with setup variations and to perform an end-to-end test for brain SRS with multiple metastases treated with a 1.5-Tesla MR-Linac (MRL). The RTsafe PseudoPatient Prime brain phantom was used with a delineation insert that includes two predefined structures mimicking gadolinium contrast-enhanced brain lesions. Daily adaptive plans were generated using six preset and six random setup variations. Two adaptive plans per daily MR image were generated using the adapt-to-position (ATP) and adapt-to-shape (ATS) workflows. An adaptive patient plan was generated on a diagnostic MR image with simulated translational and rotational daily setup variation and was compared with the reference plan. All adaptive plans were compared with the reference plan using the target coverage, Paddick conformity index, gradient index (GI), Brain V12 or V20, optimization time and total monitor units. Target doses were measured as an end-to-end test with two ionization chambers inserted into the phantom. With preset translational variations, V12 from the ATS plan was 17% lower than that of the ATP plan. With a larger daily setup variation, GI and V12 of the ATS plan were 10% and 16% lower than those of the ATP plan, respectively. Compared to the ATP plans, the plan quality index of the ATS plans was more consistent with the reference plan, and within 5% in both phantom and patient plans. The differences between the measured and planned target doses were within 1% for both treatment workflows. Treating brain SRS using an MRL is feasible and could achieve satisfactory dosimetric goals. Setup uncertainties could be accounted for using online plan adaptation. The ATS workflow achieved better dosimetric results than the ATP workflow at the cost of longer optimization time.

Characterizing the emission behaviors of cumulative VOCs from automotive solvent-based paint sludge.

Volatile organic compounds (VOCs) diffused from paint sludge are potential hazard contributing significantly to environmental pollution and exposure to them can cause severe health issues. In this paper, a diffusion-controlled model was firstly developed for characterizing the emission behaviors of cumulative VOCs from automotive solvent-based paint sludge based on the worst field management scenario. The presented model is characterized by two key parameters: the diffusion coefficient (Dm) and the initial emittable concentration (Cm,0), which can be simultaneously obtained by our proposed ER-history method. Four major components were detected including 1-butanol, butyl acetate and 1,2,4-trimethylbenzene and 1-ethyl-4-methylbenzene. In addition, the model was validated by using environmental data in a ventilated test chamber, proving that the model is reliable and convincing. However, relative deviations of 1-butanol and butyl acetate are larger than those of 1,2,4-trimethylbenzene and 1-ethyl-4-methylbenzene, indicating that the model is more accurate for predicting hydrophobic VOCs release than those of hydrophilic VOCs. Besides, an increase in Cm,0 and Dm tends to enhance VOCs cumulation release. Our studies provide new insight into experimental designs for rapid model parameters measurement and a sound basis for estimating VOCs cumulative release from paint sludge as well as for hazardous waste.

Impact of slice thickness, pixel size, and CT dose on the performance of automatic contouring algorithms.

PURPOSE: To investigate the impact of computed tomography (CT) image acquisition and reconstruction parameters, including slice thickness, pixel size, and dose, on automatic contouring algorithms. METHODS: Eleven scans from patients with head-and-neck cancer were reconstructed with varying slice thicknesses and pixel sizes. CT dose was varied by adding noise using low-dose simulation software. The impact of these imaging parameters on two in-house auto-contouring algorithms, one convolutional neural network (CNN)-based and one multiatlas-based system (MACS) was investigated for 183 reconstructed scans. For each algorithm, auto-contours for organs-at-risk were compared with auto-contours from scans with 3 mm slice thickness, 0.977 mm pixel size, and 100% CT dose using Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD). RESULTS: Increasing the slice thickness from baseline value of 3 mm gave a progressive reduction in DSC and an increase in HD and MSD on average for all structures. Reducing the CT dose only had a relatively minimal effect on DSC and HD. The rate of change with respect to dose for both auto-contouring methods is approximately 0. Changes in pixel size had a small effect on DSC and HD for CNN-based auto-contouring with differences in DSC being within 0.07. Small structures had larger deviations from the baseline values than large structures for DSC. The relative differences in HD and MSD between the large and small structures were small. CONCLUSIONS: Auto-contours can deviate substantially with changes in CT acquisition and reconstruction parameters, especially slice thickness and pixel size. The CNN was less sensitive to changes in pixel size, and dose levels than the MACS. The results contraindicated more restrictive values for the parameters should be used than a typical imaging protocol for head-and-neck.

A field study of dioxins during co-processing of hazardous waste in multicomponent slurry gasifier.

A field test was conducted to study the emission and distribution characteristics of dioxins during co-processing of hazardous waste in a multicomponent slurry gasifier (MCSG). The toxicity equivalent concentrations of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) in all exhaust gas, waste water, and solid waste under both blank condition (i.e., feedstock was normal coal-water slurry) and test condition (i.e., feedstock mixed with hazardous waste and labeling reagents) were analyzed. Results showed that organic matter was fully degraded in the MCSG. The dioxin amount in the black water flash steam increased with the addition of hazardous waste and chlorine in the feedstock, and octachlorodibenzo-p-dioxins (OCDD) with the largest increase is the most easily formed monomer in dioxins. The dioxin amount in all samples was far below the standard limit in China and other countries. This indicates the low environmental risk from dioxins during the co-processing process. The dioxin distribution trend in solid, liquid, and gas phase during co-processing did not change: 86.63%-94.18%, 0.02%-0.13%, and 5.8%-13.23% of PCDDs were distributed in the exhaust gas, waste water, and solid waste, respectively, while 6.10%-22.95%, 0.59%-0.80%, and 76.45%-93.10% of PCDFs were distributed in the exhaust gas, waste water, and solid waste, respectively.

Impact of Intra-Fractional Motion on Dose Distributions in Lung IMRT.

AIM: To investigate the impact of intra-fractional motion on dose distribution in patients treated with intensity-modulated radiation therapy (IMRT) for lung cancer. MATERIALS AND METHODS: Twenty patients who had undergone IMRT for non-small cell lung cancer were selected for this retrospective study. For each patient, a four-dimensional computed tomography (CT) image set was acquired and clinical treatment plans were developed using the average CT. Dose distributions were then re-calculated for each of the 10 phases of respiratory cycle and combined using deformable image registration to produce cumulative dose distributions that were compared with the clinical treatment plans. RESULTS: Intra-fractional motion reduced planning target volume (PTV) coverage in all patients. The median reduction of PTV volume covered by the prescription isodose was 3.4%; D98 was reduced by 3.1 Gy. Changes in the mean lung dose were within ±0.7 Gy. V20 for the lung increased in most patients; the median increase was 1.6%. The dose to the spinal cord was unaffected by intra-fractional motion. The dose to the heart was slightly reduced in most patients. The median reduction in the mean heart dose was 0.22 Gy, and V30 was reduced by 2.5%.The maximum dose to the esophagus was also reduced in most patients, by 0.74 Gy, whereas V50 did not change significantly. The median number of points in which dose differences exceeded 3%/3 mm was 6.2%. FINDINGS: Intra-fractional anatomical changes reduce PTV coverage compared to the coverage predicted by clinical treatment planning systems that use the average CT for dose calculation. Doses to organs at risk were mostly over-predicted.

Development and application of an elastic net logistic regression model to investigate the impact of cardiac substructure dose on radiation-induced pericardial effusion in patients with NSCLC.

BACKGROUND: Typically, cardiac substructures are neither delineated nor analyzed during radiation treatment planning. Therefore, we developed a novel machine learning model to evaluate the impact of cardiac substructure dose for predicting radiation-induced pericardial effusion (PCE). MATERIALS AND METHODS: One-hundred and forty-one stage III NSCLC patients, who received radiation therapy in a prospective clinical trial, were included in this analysis. The impact of dose-volume histogram (DVH) metrics (mean and max dose, V5Gy[%]-V70Gy[%]) for the whole heart, left and right atrium, and left and right ventricle, on pericardial effusion toxicity (≥grade 2, CTCAE v4.0 grading) were examined. Elastic net logistic regression, using repeat cross-validation (n = 100 iterations, 75%/25% training/test set data split), was conducted with cardiac-based DVH metrics as covariates. The following model types were constructed and analyzed: (i) standard model type, which only included whole-heart DVH metrics; and (ii) a model type trained with both whole-heart and substructure DVH metrics. Model performance was analyzed on the test set using area under the curve (AUC), accuracy, calibration slope and calibration intercept. A final fitted model, based on the optimal model type, was developed from the entire study population for future comparisons. RESULTS: Grade 2 PCE incidence was 49.6% (n = 70). Models using whole heart and substructure dose had the highest performance (median values: AUC = 0.820; calibration slope/intercept = 1.356/-0.235; accuracy = 0.743) and outperformed the standard whole-heart only model type (median values: AUC = 0.799; calibration slope/intercept = 2.456/-0.729; accuracy = 0.713). The final fitted elastic net model showed high performance in predicting PCE (median values: AUC = 0.879; calibration slope/intercept = 1.352/-0.174; accuracy = 0.801). CONCLUSIONS: We developed and evaluated elastic net regression toxicity models of radiation-induced PCE. We found the model type that included cardiac substructure dose had superior predictive performance. A final toxicity model that included cardiac substructure dose metrics was developed and reported for comparison with external datasets.

Pathways and influential factors study on the formation of PBDD/Fs during co-processing BDE-209 in cement kiln simulation system.

The thermal processes of cement kilns are sources of polybrominated dibenzofurans and dioxins (PBDD/Fs); however, when co-processing decabromodiphenyl ether (BDE-209) soil in cement kilns, very few reports have investigated the mechanism of PBDD/Fs formation from BDE-209. Therefore, the pathways and factors that influence the formation of PBDD/Fs were investigated using Box-Behnken design (BBD) of the response surface methodology (RSM) at lab-scale. The PBDEs, HBr/Br2 and PBDD/Fs emissions in flue gas from the simulated thermal process were analyzed using gas chromatography/mass spectroscopy (GC/MS), high-resolution gas chromatography/high-resolution mass spectrometry (HRGC/HRMS), and ion chromatography (IC). Density functional theory (DFT) was also used to further discuss the formation of PBDD/Fs. The major products of BDE-209 thermal decomposition in flue gas were 97.1% HBr/Br2 (a.v. 26.6%/70.6%) > 2.7% PBDEs >0.2% PBDD/Fs. Formation of precursors were the main pathways for PBDD/Fs, and those precursors were dominated by higher-brominated PBDEs (heptã deca-BDEs); debromination of BDE-209 was also a crucial pathway for the formation of PBDD/Fs throughout the thermal process. Interestingly, it was easier to form HpBDD/Fs from OBDD/Fs than from PBDEs. The O2 percentage and interaction factors of O2 percentage, temperature, and CaCO3 percentage have the largest influence on PBDD/Fs emissions and formation.

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI) has gained popularity in radiation therapy simulation because it provides superior soft tissue contrast, which facilitates more accurate target delineation compared with computed tomography (CT) and does not expose the patient to ionizing radiation. However, image registration errors in commercial software have not been widely reported. Here we evaluated the accuracy of deformable image registration (DIR) by using a physical phantom for MRI. METHODS AND MATERIALS: We used the "Wuphantom" for end-to-end testing of DIR accuracy for MRI. This acrylic phantom is filled with water and includes several fillable inserts to simulate various tissue shapes and properties. Deformations and changes in anatomic locations are simulated by changing the rotations of the phantom and inserts. We used Varian Velocity DIR software (v4.0) and CT (head and neck protocol) and MR (T1- and T2-weighted head protocol) images to test DIR accuracy between image modalities (MRI vs CT) and within the same image modality (MRI vs MRI) in 11 rotation deformation scenarios. Large inserts filled with Mobil DTE oil were used to simulate fatty tissue, and small inserts filled with agarose gel were used to simulate tissues slightly denser than water (e.g., prostate). Contours of all inserts were generated before DIR to provide a baseline for contour size and shape. DIR was done with the MR Correctable Deformable DIR method, and all deformed contours were compared with the original contours. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were used to quantitatively validate DIR accuracy. We also used large and small regions of interest (ROIs) during between-modality DIR tests to simulate validation of DIR accuracy for organs at risk (OARs) and propagation of individual clinical target volume (CTV) contours. RESULTS: No significant differences in DIR accuracy were found for T1:T1 and T2:T2 comparisons (P > 0.05). DIR was less accurate for between-modality comparisons than for same-modality comparisons, and was less accurate for T1 vs CT than for T2 vs CT (P < 0.001). For between-modality comparisons, use of a small ROI improved DIR accuracy for both T1 and T2 images. CONCLUSION: The simple design of the Wuphantom allows seamless testing of DIR; here we validated the accuracy of MRI DIR in end-to-end testing. T2 images had superior DIR accuracy compared with T1 images. Use of small ROIs improves DIR accuracy for target contour propagation.

Acceleration of soil salinity accumulation and soil degradation due to greenhouse cultivation: a survey of farmers' practices in China.

Soil environment and water quality face large pressure due to the rapid expansion of greenhouse cultivation in China. However, studies rarely provide the linkage between farmers' practices and soil degradation in greenhouse cultivation field. In this study, a field survey and sampling of greenhouse cultivation soil were conducted in five regions of China to investigate the accumulation and variation characteristics of soil ion compositions in the field. First, the pH, ion compositions, and electrical conductivity (EC) of 132 composite soil samples were analyzed. Second, farmers' practices with regard to fertilizer, crop yield, and soil degradation processes were surveyed. Lastly, soil nutrient status was evaluated by different grades, and the principal component analysis method was used to analyze the main sources of soil ion compositions. Results of the study reveal the following: (1) Enrichment of greenhouse soil nutrient was mainly caused by excessive fertilization, which introduced the secondary salinization phenomenon for 3-5 years in plastic greenhouse and 1-3 years in multispan greenhouse. (2) Significant changes between the EC and salt ion composition of open soil and greenhouse cultivated soil were observed. The contents of nitrate nitrogen and ammonium nitrogen in the greenhouse soil were high. (3) After a certain period of cultivation in the greenhouse, salt accumulation, pH decline, and varying degrees of acidification were observed in the soil profile. The relationship between soil pH and EC values indicated that the balance of soil compositions was broken. The recommended methods for sustaining greenhouse cultivation include balanced fertilization, rotation practices, and reasonable water utilization in the field.

Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis?

PURPOSE: We evaluated the feasibility of using an automatic segmentation tool to delineate cardiac substructures from noncontrast computed tomography (CT) images for cardiac dosimetry and toxicity analyses for patients with nonsmall cell lung cancer (NSCLC) after radiotherapy. MATERIAL AND METHODS: We used an in-house developed multi-atlas segmentation tool to delineate 11cardiac substructures, including the whole heart, four heart chambers, and six greater vessels, automatically from the averaged 4D-CT planning images of 49 patients with NSCLC. Two experienced radiation oncologists edited the auto-segmented contours. Times for automatic segmentation and modification were recorded. The modified contours were compared with the auto-segmented contours in terms of Dice similarity coefficient (DSC) and mean surface distance (MSD) to evaluate the extent of modification. Differences in dose-volume histogram (DVH) characteristics were also evaluated for the modified versus auto-segmented contours. RESULTS: The mean automatic segmentation time for all 11 structures was 7-9 min. For the 49 patients, the mean DSC values (±SD) ranged from .73 ± .08 to .95 ± .04, and the mean MSD values ranged from 1.3 ± .6 mm to 2.9 ± 5.1 mm. Overall, the modifications were small; the largest modifications were in the pulmonary vein and the inferior vena cava. The heart V30 (volume receiving dose ≥30 Gy) and the mean dose to the whole heart and the four heart chambers were not different for the modified versus the auto-segmented contours based on the statistically significant condition of p < .05. Also, the maximum dose to the great vessels was no different except for the pulmonary vein. CONCLUSIONS: Automatic segmentation of cardiac substructures did not require substantial modifications. Dosimetric evaluation showed no significant difference between the auto-segmented and modified contours for most structures, which suggests that the auto-segmented contours can be used to study cardiac dose-responses in clinical practice.

Automatic detection of graticule isocenter and scale from kV and MV images.

PURPOSE: To automate the detection of isocenter and scale of the mechanical graticule on kilo-voltage (kV) or mega-voltage (MV) films or electronic portal imaging device (EPID) images. METHODS: We developed a robust image processing approach to automatically detect isocenter and scale of mechanical graticule from digitized kV or MV films and EPID images. After a series of preprocessing steps applied to the digital images, a combination of Hough transform and Radon transform was performed to detect the graticule axes and isocenter. The magnification of the graticule was automatically detected by solving an optimization problem using golden section search and parabolic interpolation algorithm. Tick marks of the graticule were then determined by extending from isocenter along the graticule axes with multiples of the magnification value. This approach was validated using 23 kV films, 26 MV films, and 91 EPID images in different anatomical sites (head-and-neck, thorax, and pelvis). Accuracy was measured by comparing computer detected results with manually selected results. RESULTS: The proposed approach was robust for kV and MV films of varying image quality. The isocenter was detected within 1 mm for 98% of the images. The exceptions were three kV films where the graticule was not actually visible. Of all images with correct isocenter detection, 99% had a magnification detection error less than 1% and tick mark detection error less than 1 mm, with the exception of 1 kV film (magnification error: 3.17%; tick mark error: 1.29 mm) and 1 MV film (magnification error: 0.45%; tick mark error: 1.11 mm). CONCLUSION: We developed an approach to robustly and automatically detect graticule isocenter and scale from two-dimensionla (2D) kV and MV films. This is a first step toward automated treatment planning based on 2D x-ray images.

Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom.

PURPOSE: Kilo-voltage cone-beam computed tomography (CBCT) is widely used for patient alignment, contour propagation, and adaptive treatment planning in radiation therapy. In this study, we evaluated the accuracy of deformable image registration (DIR) for CBCT under various imaging protocols with different noise and patient dose levels. METHODS: A physical phantom previously developed to facilitate end-to-end testing of the DIR accuracy was used with Varian Velocity v4.0 software to evaluate the performance of image registration from CT to CT, CBCT to CT, and CBCT to CBCT. The phantom is acrylic and includes several inserts that simulate different tissue shapes and properties. Deformations and anatomic changes were simulated by changing the rotations of both the phantom and the inserts. CT images (from a head and neck protocol) and CBCT images (from pelvis, head and "Image Gently" protocols) were obtained with different image noise and dose levels. Large inserts were filled with Mobil DTE oil to simulate soft tissue, and small inserts were filled with bone materials. All inserts were contoured before the DIR process to provide a ground truth contour size and shape for comparison. After the DIR process, all deformed contours were compared with the originals using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Both large and small volume of interests (VOIs) for DIR volume selection were tested by simulating a DIR process that included whole patient image volume and clinical target volumes (CTV) only (for CTVs propagation). RESULTS: For cross-modality DIR registration (CT to CBCT), the DSC were >0.8 and the MDA were <3 mm for CBCT pelvis, and CBCT head protocols. For CBCT to CBCT and CT to CT, the DIR accuracy was improved relative to the cross-modality tests. For smaller VOIs, the DSC were >0.8 and MDA <2 mm for all modalities. CONCLUSIONS: The accuracy of DIR depends on the quality of the CBCT image at different dose and noise levels.