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Background Both patient-specific dose recalculation and γ passing rate analysis are important for the quality assurance (QA) of intensity modulated radiotherapy (IMRT) plans. The aim of this study was to analyse the correlation between the γ passing rates and the volumes of air cavities (Vair) and bony structures (Vbone) in target volume of head and neck cancer. Methods Twenty nasopharyngeal carcinoma and twenty nasal natural killer T-cell lymphoma patients were enrolled in this study. Nine-field sliding window IMRT plans were produced and the dose distributions were calculated by anisotropic analytical algorithm (AAA), Acuros XB algorithm (AXB) and SciMoCa based on the Monte Carlo (MC) technique. The dose distributions and γ passing rates of the targets, organs at risk, air cavities and bony structures were compared among the different algorithms. Results The γ values obtained with AAA and AXB were 95.6 ± 1.9% and 96.2 ± 1.7%, respectively, with 3%/2 mm criteria (p > 0.05). There were significant differences (p Vair (R2 = 0.674) and inversely proportional to the natural logarithm of Vbone (R2 = 0.816). When the Vair in the targets was smaller than approximately 80 cc or the Vbone in the targets was larger than approximately 6 cc, the γ values of AAA were below 95%. Using AXB, no significant relationship was found between the γ values and Vair or Vbone. Conclusion In clinical head and neck IMRT QA, greater attention should be paid to the effect of Vair and Vbone in the targets on the γ passing rates when using different dose calculation algorithms.

Purpose Dynamic myocardial perfusion computed tomography (DM-PCT) imaging offers benefits over quantitative assessment of myocardial blood flow (MBF) for diagnosis and risk stratification of coronary artery disease. However, one major drawback of DM-PCT imaging is that a high radiation level is imparted by repeated scanning. To address this issue, in this work, we developed a statistical iterative reconstruction algorithm based on the penalized weighted least-squares (PWLS) scheme by incorporating a motion adaptive sparsity prior (MASP) model to achieve high-quality DM-PCT imaging with low tube current dynamic data acquisition. For simplicity, we refer to the proposed algorithm as “PWLS-MASP’’. Methods The MASP models both the spatial and temporal structured sparsity of DM-PCT sequence images with the assumption that the differences between adjacent frames after motion correction are sparse in the gradient image domain. To validate and evaluate the effectiveness of the present PWLS-MASP algorithm thoroughly, a modified XCAT phantom and preclinical porcine DM-PCT dataset were used in the study. Results The present PWLS-MASP algorithm can obtain high-quality DM-PCT images in both phantom and porcine cases, and outperforms the existing filtered back-projection algorithm and PWLS-based algorithms with total variation regularization (PWLS-TV) and robust principal component analysis regularization (PWLS-RPCA) in terms of noise reduction, streak artifacts mitigation, and time density curve estimation. Moreover, the PWLS-MASP algorithm can yield more accurate diagnostic hemodynamic parametric maps than the PWLS-TV and PWLS-RPCA algorithms. Conclusions The study indicates that there is a substantial advantage in using the present PWLS-MASP algorithm for low-dose DM-PCT, and potentially in other dynamic tomography areas.

A novel scaffold of arylpiperazine derivatives was discovered as potent androgen receptor (AR) antagonist through rational drug designation based on our pre-work, leading to the discovery of a series of new antiproliferative compounds. Compounds 10, 16, 27, 29 and 31 exhibited relatively strong antagonistic potency against AR and exhibited potent AR binding affinities, while compounds 5, 6, 10, 14, 16, 19, 21, 27 and 31 exhibited strong cytotoxic activities against LNCaP cells (AR-rich) as well as also displayed the higher activities than finasteride toward PC-3 (AR-deficient) and DU145 (AR-deficient). Docking study suggested that the most potent antagonist 16 mainly bind to AR ligand binding pocket (LBP) site through hydrogen bonding interactions. The structure-activity relationship (SAR) of these designed arylpiperazine derivatives was rationally explored and discussed. These results indicated that the novel scaffold compounds demonstrated a step towards the development of novel and improved AR antagonists, and promising candidates for future development were identified.

Modern radiotherapy (RT) is being enriched by big digital data and intensive technology. Multimodality image registration, intelligence-guided planning, real-time tracking, image-guided RT (IGRT), and automatic follow-up surveys are the products of the digital era. Enormous digital data are created in the process of treatment, including benefits and risks. Generally, decision making in RT tries to balance these two aspects, which is based on the archival and retrieving of data from various platforms. However, modern risk-based analysis shows that many errors that occur in radiation oncology are due to failures in workflow. These errors can lead to imbalance between benefits and risks. In addition, the exact mechanism and dose-response relationship for radiation-induced malignancy are not well understood. The cancer risk in modern RT workflow continues to be a problem. Therefore, in this review, we develop risk assessments based on our current knowledge of IGRT and provide strategies for cancer risk reduction. Artificial intelligence (AI) such as machine learning is also discussed because big data are transforming RT via AI.

For the development of potential anti-prostate cancer agents, 24 kinds of novel naftopidil-based arylpiperazine derivatives have been synthesized and characterized by spectroscopic methods. Their antitumor activities were evaluated against several classical prostate cancer cell lines including PC-3, LNCaP, and DU145. Among all the compounds, 9, 13, 17, 21 and 27 showed strong cytotoxic activities against DU145 cells (IC50

OBJECTIVE: In clinical cerebral perfusion CT examination, repeated scanning the region of interest in the cine mode increases the radiation dose of the patients, while decreasing the radiation dose by lowering the scanning current results in poor image quality and affects the clinical diagnosis. We propose a penalized weighted least-square (PWLS) method for recovering the projection data to improve the quality of low-dose cerebral perfusion CT imaged. This method incorporates the statistical distribution characteristics of brain perfusion CT projection data and uses the statistical properties of the projection data for modeling. The PWLS method was used to recover the data, and the Gauss-Seidel (GS) method was employed for iterative solving. Adaptive weighting is introduced between the original projection data and the projection data after PWLS restoration. The experimental results on the clinical data demonstrated that the PWLS-based sinogram restoration method improved noise reduction and artifact suppression as compared with the conventional noise reduction methods, and better retained the edges and details to generate better cerebral perfusion maps.

OBJECTIVE: To investigate the effect of detector performance during digital breast tomography (DBT) projection data acquisition on reconstructed image quality. METHODS: With reference to the traditional detector data correction method and the specific data acquisition pattern in DBT imaging, we utilized dark field correction, light field and its gain correction for processing the projection data collected by the detector. The reconstructed images were evaluated using iterative reconstruction method based on total generalized variation (TGV). RESULTS: In physical breast phantom experiment, the proposed method resulted in a reduced Heel effect caused by nonuniform photon number. The reconstructed DBT images after correction showed obviously improved image quality especially in the details with a low contrast. CONCLUSION: The dark field correction, light field and its gain correction process for DBT image reconstruction can improve the image quality.

Dynamic cerebral perfusion x-ray computed tomography (PCT) imaging has been advocated to quantitatively and qualitatively assess hemodynamic parameters in the diagnosis of acute stroke or chronic cerebrovascular diseases. However, the associated radiation dose is a significant concern to patients due to its dynamic scan protocol. To address this issue, in this paper we propose an image restoration method by utilizing coupled dictionary learning (CDL) scheme to yield clinically acceptable PCT images with low-dose data acquisition. Specifically, in the present CDL scheme, the 2D background information from the average of the baseline time frames of low-dose unenhanced CT images and the 3D enhancement information from normal-dose sequential cerebral PCT images are exploited to train the dictionary atoms respectively. After getting the two trained dictionaries, we couple them to represent the desired PCT images as spatio-temporal prior in objective function construction. Finally, the low-dose dynamic cerebral PCT images are restored by using a general DL image processing. To get a robust solution, the objective function is solved by using a modified dictionary learning based image restoration algorithm. The experimental results on clinical data show that the present method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the state-of-the-art methods.

In the title compound, [Cu(C9H5N2O2)2(H2O)2], the Cu(II) ion lies on an inversion centre and has an elongated centrosymmetric octahedral environment, equatorially trans-coordinated by two N,O-bidentate quinoxaline-2-carboxylate ligands and axially coordinated by two water O atoms. Symmetry-related molecules are linked by strong O-H...O hydrogen bonds, involving the uncoordinated carboxyl O atom of the carboxylate group and the coordinated water molecules, to form a two-dimensional network. Weak intermolecular C-H...N interactions also stabilize the crystal structure.

Biochar derived from excess sludge was used for hexavalent chromium [Cr( VI)] removal from water as a sorbent, and impacts of co-existing humic acid on performance of Cr( VI) sorption onto biochar were studied. The experimental results indicated that humic acid facilitated biochar adsorption of Cr(VI), which enhanced capacity of Cr sorption and shortened reaction time reaching equilibrium remarkably. The sorption kinetic process could be described with the pseudo second order model. On the condition of initial pH 4.0, biochar concentration 20 g x L(-1), initial concentration of Cr(VI) in the range of 50-800 mg x L(-1), the Langmuir model fitted adsorption isotherm better than the Freudlich model. The Langmuir Q0 values of biochar with and without existing humic acid were 10.10 mg x g(-1) and 5.56 mg x g(-1), respectively. In the pH range of 2.0-8.0, sorption capacity of all sorbents decreased with increasing initial pH value. Ascending concentration of humic acid in solution promoted sorption capacity of biochar. Fourier transform infrared spectroscopy (FTIR) analysis showed that hydroxyl, carboxyl, ester, aromatic C-H stretch and ring C=C on the biochar were responsible for Cr(VI) sorption. Combined with X-ray photoelectron spectroscopy (XPS) analysis, mechanism of promoting Cr( VI) sorption onto biochar was speculated that humic acid enhanced concentration of Cr( VI) ions aggregating on the surface of biochar and benefited Cr(VI) adsorption coupled with subsequent reduction by biochar functional groups. Meanwhile, humic acid also increased amount of Cr(VI) and Cr(II) removal from aqueous solution.

Positive region is the one of the core concepts in rough set theory, which algorithm complexity of region directly affects other algorithms. With a equivalent definition of area, this paper proposes a calculation method based on the diagonal matrix. This method stores the compatible object set searched every time in the diagonal of diagonal matrix, and the object searched has to be zero processed, thereby the method reduces the amount of computation. Examples show that the method convenient, simple and intuitive, and can improve the of computing positive region.

The title Schiff base compound, C18H21N3O2, was synthesized by a condensation reaction of 4-hydroxy­benzaldehyde with diethyl­enetriamine. The crystal structure determination reveals that one of the terminal hydr­oxy groups is deproton­ated while the imino group of the mol­ecule is protonated; thus the compound is a zwitterion. The two terminal benzene rings are nearly parallel to one another, with a dihedral angle of 9.94 (6)°. Inter­molecular O—H⋯O and N—H⋯O hydrogen bonding helps to stabilize the crystal structure.