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1.
Phys Med Biol ; 2019 Sep 05.
Artigo em Inglês | MEDLINE | ID: mdl-31487698

RESUMO

The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization into 3D cycle-consistent generative adversarial networks (cycle GAN) framework to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 17 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT generation method by leave-one-out cross-validation. Image quality between the sCT and CT images, gamma analysis passing rate, dose-volume metrics, distal range displacement, and the individual pencil beam Bragg peak shift between sCT- and CT-based proton plans were evaluated. The average mean absolute error (MAE) was 51.32±16.91 HU. The relative differences of the statistics of the PTV dose volume histogram (DVH) metrics in between sCT and CT were generally less than 1%. Mean values of dose difference, absolute dose difference (in percent of prescribed dose) were -0.07±0.07% and 0.23±0.08%. Mean gamma analysis pass rate of 1mm/1%, 2mm/2%, 3mm/3% criteria with 10% dose threshold were 92.39±5.97%, 97.95±2.95% and 98.97±1.62% respectively. The median, mean and standard deviation of absolute maximum range differences were 0.09 cm and 0.23±0.25 cm. The median and mean Bragg peak shifts among the 17 patients were 0.09 cm and 0.18±0.07 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for prostate proton radiotherapy.

2.
Org Lett ; 2019 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-31508970

RESUMO

Rare-earth catalysis has become a hot topic in the field of catalytic organic reaction. Chain ethers mostly have lower reactivity and lower boiling points which limited their reaction scope. Herein, we found a rare-earth Y(OTf)3 can catalyze the coupling reaction of ethers especially chain ethers and thioethers with azaarenes. This protocol features simple operations, a broad substrate scope (31 examples), moderate to good yields (up to 85%), and atom economy.

3.
Environ Sci Technol ; 2019 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-31419113

RESUMO

Phosphorus (P) is a vital micronutrient element for all life forms. Typically, P can be extracted from phosphate rock. Unfortunately, the phosphate rock is a nonrenewable resource with a limited reserve on the earth. High levels of P discharged to water bodies lead to eutrophication. Therefore, P needs to be removed and is preferably recovered as an additional P source. A possible way to achieve this goal is by electrochemically induced phosphate precipitation with coexisting calcium ions. Here, we report a new concept of phosphate removal and recovery, namely a CaCO3 packed electrochemical precipitation column, which achieved improved removal efficiency, shortened hydraulic retention time, and substantially enhanced stability, compared with our previous electrochemical system. The concept is based on the introduction of CaCO3 particles, which facilitates calcium phosphate precipitation by buffering the formed H+ at the anode, releases Ca2+, acts as seeds, and establishes a high pH environment in the bulk solution in addition to that in the vicinity of the cathode. It was found that the applied current, the CaCO3 particle size, and the feed rate affect the removal of phosphate. Under optimized conditions (particle size, <0.5 mm; feed rate, 0.4 L/d; current, 5 mA), in a continuous flow system, the CaCO3 packed electrochemical precipitation column achieved 90 ± 5% removal of phosphate in 40 days and >50% removal over 125 days with little maintenance. The specific energy consumptions of this system lie between 29 and 61 kWh/kg P. The experimental results demonstrate the promising potential of the CaCO3 packed electrochemical precipitation column for P removal and recovery from P-containing streams.

4.
Drug Des Devel Ther ; 13: 1957-1967, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31354241

RESUMO

Background: The authors have recently designed a new compound bisperoxovandium (pyridin-2-squaramide) [bpV(pis)] and verified that bpV(pis) confers neuroprotection through suppressing PTEN and activating ERK1/2, respectively. Intracerebral hemorrhage (ICH) is the second most common cause of stroke and has severe clinical outcome. In this study, we investigate the effect of bpV(pis) in ICH model both in vivo and in vitro. Materials and methods: The novel drug bpV(pis) was synthesized in the Faculty of Pharmacy, Wuhan University School of Medicine. An ICH model was generated on both SD rats and cells. bpV(pis) was injected into intracerebroventricular or culture media. Western blotting was applied to test the signal pathway. To determine the effect of bpV(pis) on PTEN inhibition and ERK1/2 activation, we measured the phosphorylation level of AKT (a direct downstream target of PTEN that negatively regulates AKT) and ERK1/2. FJC, MTT, and LDH were applied to measure the cell viability. Neurobehavioral tests were performed to measure the effect of bpV(pis). Results: The in vivo results showed that intracerebroventricular administration of bpV(pis) significantly alleviates hematoma, the damage of brain-blood barrier and brain edema. The in vitro results demonstrated that bpV(pis) treatment reduces ICH-induced neuronal injury. Western blotting results identified that bpV(pis) exerts a neuroprotective effect by significantly increasing the phosphorylation level of AKT and ERK1/2 after experimental ICH. Neurobehavioral tests indicate that bpV(pis) promotes functional recovery in ICH animals. Conclusion: This study provides first and direct evidence for a potential role of bpV(pis) in ICH therapy.

5.
BMC Nephrol ; 20(1): 254, 2019 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-31291904

RESUMO

BACKGROUND: In this study, we investigated the association of time-varying serum albumin levels with mortality over a 5-year period in one cohort of patients undergoing long-term peritoneal dialysis (PD) therapy. METHODS: The participants in this study enrolled 302 patients who underwent long-term PD at a single PD center in Taiwan. We reviewed medical records from 2011 to 2015 retrospectively. Time-averaged albumin level and serum albumin reach rate (defined as the percentage of serum albumin measurements that reached ≥3.5 g/dL) were applied as the predictor variables in the first 2 years (2011-2012). All-cause mortality was used as the outcome variable in the subsequent 3 years (2013-2015). Hazard function of all-cause mortality in the study participants was examined by using Cox proportional hazard regression models . RESULTS: Patients with different albumin reach rates (75-< 100%, 50-< 75%, 1-< 50%) did not exhibit a significantly increased risk for all-cause mortality. Patients with a 0% albumin reach rate exhibited a significantly increased risk for all-cause mortality (hazard ratio [HR] 7.59, 95% confidence interval [CI], 2.38-24.21) by fully adjusted analysis. Patients with time-averaged albumin levels of < 3.5 g/dL (HR 15.49, 95% CI 1.74-137.72) exhibited a higher risk for all-cause mortality than those with serum albumin levels ≥4.0 g/dL. CONCLUSIONS: This study demonstrated that higher serum albumin reach rates and higher time-averaged serum albumin levels are associated with a lower mortality rate over a 5-year period among patients undergoing long-term PD.

6.
Br J Radiol ; 92(1100): 20190067, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31192695

RESUMO

OBJECTIVE: The purpose of this work is to develop and validate a learning-based method to derive electron density from routine anatomical MRI for potential MRI-based SBRT treatment planning. METHODS: We proposed to integrate dense block into cycle generative adversarial network (GAN) to effectively capture the relationship between the CT and MRI for CT synthesis. A cohort of 21 patients with co-registered CT and MR pairs were used to evaluate our proposed method by the leave-one-out cross-validation. Mean absolute error, peak signal-to-noise ratio and normalized cross-correlation were used to quantify the imaging differences between the synthetic CT (sCT) and CT. The accuracy of Hounsfield unit (HU) values in sCT for dose calculation was evaluated by comparing the dose distribution in sCT-based and CT-based treatment planning. Clinically relevant dose-volume histogram metrics were then extracted from the sCT-based and CT-based plans for quantitative comparison. RESULTS: The mean absolute error, peak signal-to-noise ratio and normalized cross-correlation of the sCT were 72.87 ± 18.16 HU, 22.65 ± 3.63 dB and 0.92 ± 0.04, respectively. No significant differences were observed in the majority of the planning target volume and organ at risk dose-volume histogram metrics ( p > 0.05). The average pass rate of γ analysis was over 99% with 1%/1 mm acceptance criteria on the coronal plane that intersects with isocenter. CONCLUSION: The image similarity and dosimetric agreement between sCT and original CT warrant further development of an MRI-only workflow for liver stereotactic body radiation therapy. ADVANCES IN KNOWLEDGE: This work is the first deep-learning-based approach to generating abdominal sCT through dense-cycle-GAN. This method can successfully generate the small bony structures such as the rib bones and is able to predict the HU values for dose calculation with comparable accuracy to reference CT images.


Assuntos
Carcinoma Hepatocelular/radioterapia , Neoplasias Hepáticas/radioterapia , Imagem por Ressonância Magnética/métodos , Radiocirurgia/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Carcinoma Hepatocelular/diagnóstico por imagem , Aprendizado Profundo , Humanos , Fígado/diagnóstico por imagem , Neoplasias Hepáticas/diagnóstico por imagem , Radioterapia de Intensidade Modulada/métodos
7.
Med Phys ; 46(9): 3998-4009, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31206709

RESUMO

PURPOSE: The incorporation of cone-beam computed tomography (CBCT) has allowed for enhanced image-guided radiation therapy. While CBCT allows for daily 3D imaging, images suffer from severe artifacts, limiting the clinical potential of CBCT. In this work, a deep learning-based method for generating high quality corrected CBCT (CCBCT) images is proposed. METHODS: The proposed method integrates a residual block concept into a cycle-consistent adversarial network (cycle-GAN) framework, called res-cycle GAN, to learn a mapping between CBCT images and paired planning CT images. Compared with a GAN, a cycle-GAN includes an inverse transformation from CBCT to CT images, which constrains the model by forcing calculation of both a CCBCT and a synthetic CBCT. A fully convolution neural network with residual blocks is used in the generator to enable end-to-end CBCT-to-CT transformations. The proposed algorithm was evaluated using 24 sets of patient data in the brain and 20 sets of patient data in the pelvis. The mean absolute error (MAE), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC) indices, and spatial non-uniformity (SNU) were used to quantify the correction accuracy of the proposed algorithm. The proposed method is compared to both a conventional scatter correction and another machine learning-based CBCT correction method. RESULTS: Overall, the MAE, PSNR, NCC, and SNU were 13.0 HU, 37.5 dB, 0.99, and 0.05 in the brain, 16.1 HU, 30.7 dB, 0.98, and 0.09 in the pelvis for the proposed method, improvements of 45%, 16%, 1%, and 93% in the brain, and 71%, 38%, 2%, and 65% in the pelvis, over the CBCT image. The proposed method showed superior image quality as compared to the scatter correction method, reducing noise and artifact severity. The proposed method produced images with less noise and artifacts than the comparison machine learning-based method. CONCLUSIONS: The authors have developed a novel deep learning-based method to generate high-quality corrected CBCT images. The proposed method increases onboard CBCT image quality, making it comparable to that of the planning CT. With further evaluation and clinical implementation, this method could lead to quantitative adaptive radiation therapy.

8.
Biomed Res Int ; 2019: 2152584, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31192253

RESUMO

Patients on peritoneal dialysis (PD) encounter peritoneal functional and structural alterations. It is still unknown whether levels of plasminogen activator inhibitor type 1 (PAI-1), matrix metalloproteinases- (MMP-) 2, and vascular endothelial growth factor (VEGF) exhibit dynamic changes in peritoneal effluents. The aim of the present study was to investigate the longitudinal changes in these biomarkers in PD patients and their association with peritoneal small-solute transfer rate (PSTR). This prospective, single-center cohort study included 70 new PD patients. The presence of PAI-1, MMP-2, and VEGF in peritoneal effluents was measured regularly after PD initiation. The association between those biomarkers and 4-hour effluent:plasma creatinine ratio (PSTR) was analyzed. Longitudinal follow-up showed a tendency for PAI-1 (p < 0.001) and VEGF (p = 0.04) to increase with the duration of PD. Both PSTR at baseline and PSTR at 2 years significantly associated with PAI-1, MMP-2, and VEGF levels at baseline. PSTR at 2 years also associated with the MMP-2 level at 6 months and PAI-1 level at baseline. The present study illustrated a positive association of PSTR with selected biomarkers in peritoneal effluents observed over a 2-year period.

9.
Neural Plast ; 2019: 9693109, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31198419

RESUMO

Dance and music are expressive art forms. Previous behavioural studies have reported that dancers/musicians show a better sensorimotor ability and emotional representation of others. However, the neural mechanism behind this phenomenon is not completely understood. Recently, intensive researches have identified that the insula is highly enrolled in the empathic process. Thus, to expand the knowledge of insular function associated with empathy under the dance/music training background, we mapped the insular network and its associated brain regions in 21 dancers, 20 musicians, and 24 healthy controls using resting-state functional connectivity (FC) analysis. Whole brain voxel-based analysis was performed using seeds from the posterior insula (PI), the ventral anterior insula (vAI), and the dorsal anterior insula (dAI). The training effects of dance and music on insular subnetworks were then evaluated using one-way analysis of variance ANOVA. Increased insular FC with those seeds was found in dancers/musicians, including PI and anterior cingulated cortex (ACC), vAI and middle temporal gyrus (MTG) and middle cingulated cortex (MCC), and dAI and ACC and MTG. In addition, significant associations were found between discrepant insular FC patterns and empathy scores in dancers and musicians. These results indicated that dance/music training might enhance insular subnetwork function, which would facilitate integration of intero/exteroceptive information and result in better affective sensitivity. Those changes might finally facilitate the subjects' empathic ability.

10.
J Affect Disord ; 256: 458-467, 2019 Jun 22.
Artigo em Inglês | MEDLINE | ID: mdl-31254721

RESUMO

BACKGROUND: The revised Leiden index of depression sensitivity (LEIDS-RR) is commonly used worldwide to measure a marker of depression vulnerability termed cognitive reactivity (CR). However, the optimal cut-off scores for this scale and for the Chinese version of LEIDS-RR (LEIDS-RR-CV) are unknown. OBJECTIVES: The main aims were to examine the psychometric properties of the LEIDS-RR and establish appropriate cut-off scores for the Chinese population. METHODS: Psychometric evaluation was performed for 330 healthy individuals and 330 depression patients in remission, by incorporating classical test theory and item response theory (IRT) methods. Receiver operating characteristic curve analysis was used to determine the optimal LEIDS-RR-CV cut-off. RESULTS: Cronbach's α, two-week test-retest reliability, and marginal reliability for the LEIDS-RR-CV were 0.92, 0.40, and 0.96, respectively. Confirmatory factor analysis validated the five-factor model, and the cut-off values to screen a population at risk of depression were 60 and 55 for the healthy individuals and patients, respectively. Patients had higher CR than healthy individuals (t = 6.10, p = 0.00), and this was positively correlated with the total CES-D Scale score (r = 0.52, p = 0.00), also confirmed by IRT analysis, indicating the discriminative and concurrent validity of the scale. LIMITATIONS: The generalizability of these findings may be limited given the sampling method and the fact that all patients were recruited from a tertiary hospital. CONCLUSIONS: The 26-item LEIDS-RR-CV is a reliable and valid instrument to assess CR in Chinese populations. It can be used for screening at-risk populations and in epidemiological studies to guide the development of tailored intervention strategies.

11.
Med Phys ; 46(8): 3565-3581, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31112304

RESUMO

PURPOSE: Automated synthetic computed tomography (sCT) generation based on magnetic resonance imaging (MRI) images would allow for MRI-only based treatment planning in radiation therapy, eliminating the need for CT simulation and simplifying the patient treatment workflow. In this work, the authors propose a novel method for generation of sCT based on dense cycle-consistent generative adversarial networks (cycle GAN), a deep-learning based model that trains two transformation mappings (MRI to CT and CT to MRI) simultaneously. METHODS AND MATERIALS: The cycle GAN-based model was developed to generate sCT images in a patch-based framework. Cycle GAN was applied to this problem because it includes an inverse transformation from CT to MRI, which helps constrain the model to learn a one-to-one mapping. Dense block-based networks were used to construct generator of cycle GAN. The network weights and variables were optimized via a gradient difference (GD) loss and a novel distance loss metric between sCT and original CT. RESULTS: Leave-one-out cross-validation was performed to validate the proposed model. The mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and normalized cross correlation (NCC) indexes were used to quantify the differences between the sCT and original planning CT images. For the proposed method, the mean MAE between sCT and CT were 55.7 Hounsfield units (HU) for 24 brain cancer patients and 50.8 HU for 20 prostate cancer patients. The mean PSNR and NCC were 26.6 dB and 0.963 in the brain cases, and 24.5 dB and 0.929 in the pelvis. CONCLUSION: We developed and validated a novel learning-based approach to generate CT images from routine MRIs based on dense cycle GAN model to effectively capture the relationship between the CT and MRIs. The proposed method can generate robust, high-quality sCT in minutes. The proposed method offers strong potential for supporting near real-time MRI-only treatment planning in the brain and pelvis.

12.
Med Phys ; 46(7): 3133-3141, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31050804

RESUMO

PURPOSE: Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM. Manual segmentation during a framed SRS procedure is time consuming and subject to inter- and intraobserver variation. To address these drawbacks, we proposed a deep learning-based method to automatically segment AVMs on CT simulation image sets. METHODS: We developed a deep learning-based method using a deeply supervised three-dimensional (3D) V-Net with a compound loss function. A 3D supervision mechanism was integrated into a residual network, V-Net, to deal with the optimization difficulties when training deep networks with limited training data. The proposed compound loss function including logistic and Dice losses encouraged similarity and penalized discrepancy simultaneously between prediction and training dataset; this was utilized to supervise the 3D V-Net at different stages. To evaluate the accuracy of segmentation, we retrospectively investigated 80 AVM patients who had CT simulation and digital subtraction angiography (DSA) acquired prior to treatment. The AVM target volume was segmented by our proposed method. They were compared with clinical contours approved by physicians with regard to Dice overlapping, difference in volume and centroid, and dose coverage changes on original plan. RESULTS: Contours created by the proposed method demonstrated very good visual agreement to the ground truth contours. The mean Dice similarity coefficient (DSC), sensitivity and specificity of the contours delineated by our method were >0.85 among all patients. The mean centroid distance between our results and ground truth was 0.675 ± 0.401 mm, and was not significantly different in any of the three orthogonal directions. The correlation coefficient between ground truth and AVM volume resulting from the proposed method was 0.992 with statistical significance. The mean volume difference among all patients was 0.076 ± 0.728 cc; there was no statistically significant difference. The average differences in dose metrics were all less than 0.2 Gy, with standard deviation less than 1 Gy. No statistically significant differences were observed in any of the dose metrics. CONCLUSION: We developed a novel, deeply supervised, deep learning-based approach to automatically segment the AVM volume on CT images. We demonstrated its clinical feasibility by validating the shape and positional accuracy, and dose coverage of the automatic volume. These results demonstrate the potential of a learning-based segmentation method for delineating AVMs in the clinical setting.

13.
Med Phys ; 46(7): 3194-3206, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31074513

RESUMO

PURPOSE: Transrectal ultrasound (TRUS) is a versatile and real-time imaging modality that is commonly used in image-guided prostate cancer interventions (e.g., biopsy and brachytherapy). Accurate segmentation of the prostate is key to biopsy needle placement, brachytherapy treatment planning, and motion management. Manual segmentation during these interventions is time-consuming and subject to inter- and intraobserver variation. To address these drawbacks, we aimed to develop a deep learning-based method which integrates deep supervision into a three-dimensional (3D) patch-based V-Net for prostate segmentation. METHODS AND MATERIALS: We developed a multidirectional deep-learning-based method to automatically segment the prostate for ultrasound-guided radiation therapy. A 3D supervision mechanism is integrated into the V-Net stages to deal with the optimization difficulties when training a deep network with limited training data. We combine a binary cross-entropy (BCE) loss and a batch-based Dice loss into the stage-wise hybrid loss function for a deep supervision training. During the segmentation stage, the patches are extracted from the newly acquired ultrasound image as the input of the well-trained network and the well-trained network adaptively labels the prostate tissue. The final segmented prostate volume is reconstructed using patch fusion and further refined through a contour refinement processing. RESULTS: Forty-four patients' TRUS images were used to test our segmentation method. Our segmentation results were compared with the manually segmented contours (ground truth). The mean prostate volume Dice similarity coefficient (DSC), Hausdorff distance (HD), mean surface distance (MSD), and residual mean surface distance (RMSD) were 0.92 ± 0.03, 3.94 ± 1.55, 0.60 ± 0.23, and 0.90 ± 0.38 mm, respectively. CONCLUSION: We developed a novel deeply supervised deep learning-based approach with reliable contour refinement to automatically segment the TRUS prostate, demonstrated its clinical feasibility, and validated its accuracy compared to manual segmentation. The proposed technique could be a useful tool for diagnostic and therapeutic applications in prostate cancer.

14.
Phys Med Biol ; 64(14): 145015, 2019 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-31146267

RESUMO

Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy and reliability of target delineation due to its superior soft tissue contrast over CT. The MRI-only treatment process is currently an active field of research since it could eliminate systematic MR-CT co-registration errors, reduce medical cost, avoid diagnostic radiation exposure, and simplify clinical workflow. The purpose of this work is to validate the application of a deep learning-based method for abdominal synthetic CT (sCT) generation by image evaluation and dosimetric assessment in a commercial proton pencil beam treatment planning system (TPS). This study proposes to integrate dense block into a 3D cycle-consistent generative adversarial networks (cycle GAN) framework in an effort to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 21 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT image quality by leave-one-out cross validation. The CT image quality, dosimetric accuracy and the distal range fidelity were rigorously checked, using side-by-side comparison against the corresponding original CT images. The average mean absolute error (MAE) was 72.87 ± 18.16 HU. The relative differences of the statistics of the PTV dose volume histogram (DVH) metrics between sCT and CT were generally less than 1%. Mean 3D gamma analysis passing rate of 1 mm/1%, 2 mm/2%, 3 mm/3% criteria with 10% dose threshold were 90.76% ± 5.94%, 96.98% ± 2.93% and 99.37% ± 0.99%, respectively. The median, mean and standard deviation of absolute maximum range differences were 0.170 cm, 0.186 cm and 0.155 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for liver proton radiotherapy.

15.
Kidney Blood Press Res ; 44(2): 264-276, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30955008

RESUMO

BACKGROUND/AIMS: Studies on the long-term clinical benefits of hemodiafiltration (HDF) and high-flux hemodialysis (HFHD) are very limited. This study aimed to investigate the hospitalization rate and aortic arch calcification (AAC) of these two dialysis modalities over 6 years. METHODS: Participants who received regular HDF and HFHD in one hospital-facilitated hemodialysis center were prospectively enrolled after matching for age, sex, and diabetes between January 2009 and December 2014. Medical records were reviewed retrospectively on demographics, laboratory variables, calcified scores in aortic arch measured by chest radiography, and rates of hospital admission. Cox proportional hazard regression and linear regression were used to obtain the outcome results. RESULTS: The HDF and HFHD groups consisted of 108 and 102 participants, respectively. Levels of laboratory variables including small soluble solutes and Kt/V were not statistically different over the 6-year period between the HDF and HFHD groups. Calcified scores of the aortic arch increased over 6 years in both groups. The changes in the mean calcified scores were significant when compared between the two groups (0.44-1.82 in HFHD, 0.79-1.8 in HDF, respectively, p = 0.008). Hospitalization rates were 735 per 1,000 patients in the HDF group and 852 per 1,000 patients in the HFHD group, respectively. No significant difference was observed in frequency and days of hospitalization between HDF and HFHD. CONCLUSION: Hospitalization rates and AAC were observed to be equal for HDF and HFHD.

16.
Macromol Biosci ; 19(6): e1800390, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30951253

RESUMO

Bioprosthetic heart valves (BHVs) used in the clinic are mostly fixed by glutaraldehyde and the lack of endothelialization is a major problem for glutaraldehyde-fixed pericardia. Hyaluronic acid is a major glycosaminoglycan that exists in native heart valves. Coupled with its inherent biocompatibility, it may enhance endothelial adhesion and proliferation when associated with vascular endothelial growth factor (VEGF). In this study, an optimized system is developed to improve the endothelialization of glutaraldehyde-fixed pericardium. A hybrid pericardium with VEGF-loaded hyaluronic acid hydrogel coating is developed by the crosslinking of 1,4-butanediol diglycidyl ether. The adhesion and growth potential of human umbilical vein endothelial cells (HUVECs) on pericardia, platelet adhesion, and calcification by an in vivo rat subdermal implantation model are investigated. The results show improved HUVEC adhesion and proliferation, less platelet adhesion, and less calcification for hybrid pericardium by introducing the coating of VEGF-loaded hyaluronic acid hydrogel. Thus, the coating of VEGF-loaded hyaluronic acid hydrogel on pericardium is a promising approach to obtain bioprosthetic valves for clinical applications with increased endothelialization and antithrombotic and anticalcification properties.

17.
Med Dosim ; 2019 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-30948341

RESUMO

INTRODUCTION: Cone-beam CT (CBCT) image quality is important for its quantitative analysis in adaptive radiation therapy. However, due to severe artifacts, the CBCTs are primarily used for verifying patient setup only so far. We have developed a learning-based image quality improvement method which could provide CBCTs with image quality comparable to planning CTs (pCTs). The accuracy of dose calculations based on these CBCTs is unknown. In this study, we aim to investigate the dosimetric accuracy of our corrected CBCT (CCBCT) in brain stereotactic radiosurgery (SRS) and pelvic radiotherapy. MATERIALS AND METHODS: We retrospectively investigated a total of 32 treatment plans from 22 patients, each of whom with both original treatment pCTs and CBCTs acquired during treatment setup. The CCBCT and original CBCT (OCBCT) were registered to the pCT for generating CCBCT-based and OCBCT-based treatment plans. The original pCT-based plans served as ground truth. Clinically-relevant dose volume histogram (DVH) metrics were extracted from the ground truth, OCBCT-based and CCBCT-based plans for comparison. Gamma analysis was also performed to compare the absorbed dose distributions between the pCT-based and OCBCT/CCBCT-based plans of each patient. RESULTS: CCBCTs demonstrated better image contrast and more accurate HU ranges when compared side-by-side with OCBCTs. For pelvic radiotherapy plans, the mean dose error in DVH metrics for planning target volume (PTV), bladder and rectum was significantly reduced, from 1% to 0.3%, after CBCT correction. The gamma analysis showed the average pass rate increased from 94.5% before correction to 99.0% after correction. For brain SRS treatment plans, both original and corrected CBCT images were accurate enough for dose calculation, though CCBCT featured higher image quality. CONCLUSION: CCBCTs can provide a level of dose accuracy comparable to traditional pCTs for brain and prostate radiotherapy planning and the correction method proposed here can be useful in CBCT-guided adaptive radiotherapy.

18.
Spectrochim Acta A Mol Biomol Spectrosc ; 214: 487-495, 2019 May 05.
Artigo em Inglês | MEDLINE | ID: mdl-30818149

RESUMO

In this work, we have designed and synthesized a dinitrobenzene-sulfonate tetrahydro[5]helicene (H-DNP) as an effective fluorescent probe for detection of hydrogen sulfide (H2S). Upon the addition of H2S, a significant fluorescence enhancement (75-fold) at 495 nm can be observed with a distinct color change from colorless to yellow. Additionally, H-DNP shows low background spectroscopic signal, large Stokes Shift up to ~140 nm, good sensitivity, rapid response time less than 2 min, low detection limit (48 nM) and high selectivity toward common bio-thiols (Cysteine, Homocysteine and Glutathione). Compared with the previous dinitrophenoxy tetrahydro[5]helicene, this probe has shorter response time and lower detection limit. Most importantly, this probe H-DNP has low toxicity to cells and excellent cell permeability, which can be applied to visualize H2S in living cells.


Assuntos
Corantes Fluorescentes , Sulfeto de Hidrogênio/metabolismo , Compostos Policíclicos , Corantes Fluorescentes/síntese química , Corantes Fluorescentes/química , Corantes Fluorescentes/farmacologia , Células HeLa , Humanos , Limite de Detecção , Microscopia de Fluorescência , Compostos Policíclicos/síntese química , Compostos Policíclicos/química , Compostos Policíclicos/farmacologia
19.
Br J Radiol ; 92(1097): 20190089, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30912959

RESUMO

OBJECTIVE: The purpose of this study is to investigate the dosimetric feasibility of delivering focal dose to multiparametric (mp) MRI-defined DILs in CT-based high-dose-rate (HDR) prostate brachytherapy with MR/CT registration and estimate its clinical benefit. METHODS: We retrospectively investigated a total of 17 patients with mp-MRI and CT images acquired pre-treatment and treated by HDR prostate brachytherapy. 21 dominant intraprostatic lesions (DILs) were contoured on mp-MRI and propagated to CT images using a deformable image registration method. A boost plan was created for each patient and optimized on the original needle pattern. In addition, separate plans were generated using a virtually implanted needle around the DIL to mimic mp-MRI guided needle placement. DIL dose coverage and organ-at-rick (OAR) sparing were compared with original plan results. Tumor control probability (TCP) was estimated to further evaluate the clinical impact on the boost plans. RESULTS: Overall, optimized boost plans significantly escalated dose to DILs while meeting OAR constraints. The addition of mp-MRI guided virtual needles facilitate increased coverage of DIL volumes, achieving a V150 > 90% in 85 % of DILs compared with 57 % of boost plan without an additional needle. Compared with original plan, TCP models estimated improvement in DIL control by 28 % for patients with external-beam treatment and by 8 % for monotherapy patients. CONCLUSION: With MR/CT registration, the proposed mp-MRI guided DIL boost in CT-based HDR brachytherapy is feasible without violating OAR constraints, and indicates significant clinical benefit in improving TCP of DIL. It may represent a strategy to personalize treatment delivery and improve tumor control. ADVANCES IN KNOWLEDGE: This study investigated the feasibility of mp-MRI guided DIL boost in HDR prostate brachytherapy with CT-based treatment planning, and estimated its clinical impact by TCP and NTCP estimation.


Assuntos
Braquiterapia/métodos , Imagem por Ressonância Magnética , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/radioterapia , Tomografia Computadorizada por Raios X , Idoso , Estudos de Viabilidade , Humanos , Masculino , Pessoa de Meia-Idade , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Estudos Retrospectivos
20.
Artigo em Inglês | MEDLINE | ID: mdl-30857885

RESUMO

BACKGROUND: MicroRNA-101 (miR-101) is markedly downregulated in both hepatitis B virus-related liver cirrhosis and hepatocellular carcinoma (HCC). In this study, we aimed to investigate the effect and mechanism of miR-101 on hepatic stellate cell (HSC) activation and liver fibrosis. MATERIALS AND METHODS: HSC LX-2 was treated with TGF-ß1 and with or without miR-101 mimics. LX-2 vitality and proliferation, the expression of F-actin and mRNAs for α-SMA, collagen 1α1 (Col 1α1), and connective tissue growth factor 2 (CCN2) were measured. A 6-week intraperitoneal injection of carbon tetrachloride (CCl4) was used to induce experimental liver fibrosis in mice, which were treated using a miR-101 negative control or miR-101 agomir from the fourth week until the end of the experiment. Liver function, hepatic hydroxyproline, liver histopathology, collagen deposition, α-SMA, type I collagen (Col I) and the protein-expressions of p-PI3K, p-Akt and p-mTOR were measured. RESULTS: MiR-101 significantly suppressed the increased LX-2 vitality and high accumulation of extracellular matrix (ECM) induced by TGF-ß1. Exposure to CCl4 led to the impairment of liver function and disruption of normal hepatic parenchyma in mice, as well as obvious liver fibrosis indicated by elevated levels of hydroxyproline, α-SMA, and Col 1α1 in liver tissues. MiR-101 administration significantly improved liver function, relieved hepatic parenchyma damage, and reversed liver fibrosis by decreasing the accumulation of ECM components. Furthermore, miR-101 substantially downregulated the CCl4-increased p-PI3K, p-Akt, and p-mTOR in mouse liver. CONCLUSIONS: MiR-101 has antifibrotic effects in experimental liver fibrosis, and downregulating the PI3K/Akt/mTOR signaling pathway may be one of its antifibrotic mechanisms.

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