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1.
Plants (Basel) ; 10(4)2021 Mar 27.
Artigo em Inglês | MEDLINE | ID: mdl-33801576

RESUMO

Plants need water and energy for their growth and reproduction. However, how water and energy availability influence dryland plant diversity along the aridity gradient in water-limited regions is still lacking. Hence, quantitative analyses were conducted to evaluate the relative importance of water and energy to dryland plant diversity based on 1039 quadrats across 184 sites in China's dryland. The results indicated that water availability and the water-energy interaction were pivotal to plant diversity in the entire dryland and consistent with the predictions of the water-energy dynamic hypothesis. The predominance of water limitation on dryland plant diversity showed a weak trend with decreasing aridity, while the effects of energy on plants were found to be significant in mesic regions. Moreover, the responses of different plant lifeforms to water and energy were found to vary along the aridity gradient. In conclusion, the study will enrich the limited knowledge about the effects of water and energy on plant diversity (overall plants and different lifeforms) in the dryland of China along the aridity gradient.

2.
Chem Commun (Camb) ; 57(17): 2176-2179, 2021 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-33524086

RESUMO

Here, we introduce two Au23 nanoclusters to unveil the significance of metal-ligand binding-induced assembly. The Au23 cluster protected by the thiolate ligand is packed in the shell-by-shell arrangement, while the Au23 cluster capped by dual ligands of thiolate and PPh3 is constructed from the assembly of Au4 tetrahedra. Furthermore Au23 from Au4 tetrahedron-based assembly is capable of converting absorbed visible light into more excitons, compared to Au23 from shell-by-shell assembly, thus exhibiting more efficient photocatalysis.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33634551

RESUMO

Precise control of the composition and structure of active sites in an atom-by-atom fashion remains insuperable for heterogeneous catalysts. Here, we introduce tailor-made catalytic sites for the cycloaddition of CO2 to epoxides achieved by implementing Ag atoms at different levels of liberation in atomically precise Au nanoclusters. Our results reveal that a single open Ag site on the Au19 Ag4 cluster improves the ring-opening of epoxides and sequent CO2 insertion, while the partially exposed Ag site on the Au20 Ag1 cluster exhibits a weak affinity for epoxides and poor efficiency for CO2 capture. Structural tunability imparted by the atom-by-atom tailoring and unusual atomic charges distributed on Au and Ag atoms of the three clusters seem to be crucial for promoting challenging bond cleavages and formations in the chemical utilization of CO2 .

4.
Burns ; 2020 Nov 07.
Artigo em Inglês | MEDLINE | ID: mdl-33288327

RESUMO

BACKGROUND: Impaired wound healing, which is due to various external and internal factors that are involved in wound pathophysiology, leads to high rates of morbidity and mortality worldwide. Oxidative stress injury is an important factor that affects wound healing by changing the whole healing process. So, resveratrol, a dietary fruits polyphenol, which is known for its antioxidant properties, maybe the candidate to accelerate the wound-healing process. METHODS: The Human Umbilical Vein Endothelial Cells (HUVECs) was used for in vitro experiments to evaluate the effect of resveratrol on hyperglycemia-induced gene expression, oxidative stress and cell proliferation. The diabetic rat model was used to evaluate the effect of resveratrol on cutaneous burn injury healing process. RESULTS: Increases in H2O2 decreased cell viability with the 0-800 µM concentration range, and resveratrol could protect HUVECs against H2O2-induced injury. The scratched wound closed rate in H2O2 group was significantly smaller than the Control group (p < 0.05) and Resveratrol + H2O2 group (p < 0.05). The fluorescence intensity of ROS was lower in Control and Resveratrol + H2O2 groups than H2O2 group. Correspondingly, compared to H2O2 group, the expressions of Mn-SOD and nuclear Nrf2 (N-Nrf2) was up-regulated in Resveratrol + H2O2 group (p < 0.05). In vivo, compared with the saline group, using resveratrol could significantly accelerate wound healing of rats on Day 14 (p < 0.05) and make the regenerated skin structure more complete and inflammatory response lower. Moreover, the expressions of Mn-SOD was significantly up-regulated after using resveratrol. CONCLUSIONS: Resveratrol has the positive effects on promoting the acceleration and quality of skin wound healing, which maybe at least in part caused by the up-regulation of nuclear Nrf2 and Mn-SOD that subsequently attenuated oxidative stress.

5.
Phys Med Biol ; 2020 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-33181506

RESUMO

Accurate and efficient dose calculation is an important prerequisite to ensure the success of radiation therapy. However, all the dose calculation algorithms commonly used in current clinical practice have to compromise between calculation accuracy and efficiency, which may result in unsatisfactory dose accuracy or highly intensive computation time in many clinical situations. The purpose of this work is to develop a novel dose calculation algorithm based on the deep learning method for radiation therapy. In this study we performed a feasibility investigation on implementing a fast and accurate dose calculation based on a deep learning technique. A two dimensional (2D) fluence map was first converted into a three dimensional (3D) volume using ray traversal algorithm. A 3D U-Net like deep residual network was then established to learn a mapping between this converted 3D volume, CT and 3D dose distribution. Therefore an indirect relationship was built between a fluence map and its corresponding 3D dose distribution without using significantly complex neural networks. 200 patients, including nasopharyngeal, lung, rectum and breast cancer cases, were collected and applied to train the proposed network. Additional 47 patients were randomly selected to evaluate the accuracy of the proposed method through comparing dose distributions, dose volume histograms (DVH) and clinical indices with the results from a treatment planning system (TPS), which was used as the ground truth in this study. The proposed deep learning based dose calculation algorithm achieved good predictive performance. For 47 tested patients, the average per-voxel bias of the deep learning calculated value and standard deviation (normalized to the prescription), relative to the TPS calculation, is 0.17%±2.28%. The average deep learning calculated values and standard deviations for relevant clinical indices were compared with the TPS calculated results and the t-test p-values demonstrated the consistency between them.

6.
Chem Commun (Camb) ; 56(84): 12833-12836, 2020 Oct 28.
Artigo em Inglês | MEDLINE | ID: mdl-32966390

RESUMO

We report two ligand-protected Au4Ru2 and Au5Ru2 nanoclusters with distinct atomic-packing modes and electronic structures, both of which act as ideal model catalysts for identifying the catalytically active sites of catalysts on the nanoclusters. Au5Ru2 exhibits superior catalytic performances to Au4Ru2 for N-methylation of N-methylaniline to N-methylformanili, which is likely due to the site-cooperation catalysis of Au5Ru2.

7.
J Appl Clin Med Phys ; 21(10): 89-96, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32918385

RESUMO

PURPOSE: To study the impact of abdominal deep inspiration breath hold (DIBH) technique on knowledge-based radiotherapy treatment planning for left-sided breast cancer to guide the application of DIBH technology. MATERIALS AND METHODS: Two kernel density estimation (KDE) models were developed based on 40 left-sided breast cancer patients with two CT acquisitions of free breathing (FB-CT) and DIBH (DIBH-CT). Each KDE model was used to predict dose volume histograms (DVHs) based on DIBH-CT and FB-CT for another 10 new patients similar to our training datasets. The predicted DVHs were taken as a substitute for dose constraints and objective functions in the Eclipse treatment planning system, with the same requirements for the planning target volume (PTV). The mean doses to the heart, the left anterior descending coronary artery (LADCA) and the ipsilateral lung were evaluated and compared using the T-test among clinical plans, KDE predictions, and KDE plans. RESULTS: Our study demonstrated that the KDE model can generate deliverable simulations equivalent to clinically applicable plans. The T-test was applied to test the consistency hypothesis on another ten left-sided breast cancer patients. In cases of the same breathing status, there was no statistically significant difference between the predicted and the clinical plans for all clinically relevant DVH indices (P > 0.05), and all predicted DVHs can be transferred into deliverable plans. For DIBH-CT images, significant differences were observed between FB model predictions and clinical plans (P < 0.05). DIBH model prediction cannot be optimized to a deliverable plan based on FB-CT, with a counsel of perfection. CONCLUSION: KDE models can predict DVHs well for the same breathing conditions but degrade with different breathing conditions. The benefits of DIBH for a given patient can be evaluated with a quick comparison of prediction results of the two models before treatment planning.

8.
Plants (Basel) ; 9(8)2020 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-32759791

RESUMO

Convergence is commonly caused by environmental filtering, severe climatic conditions and local disturbance. The basic aim of the present study was to understand the pattern of leaf traits across diverse desert plant species in a common garden, in addition to determining the effect of plant life forms (PLF), such as herb, shrub and subshrub, phylogeny and soil properties on leaf traits. Six leaf traits, namely carbon (C), nitrogen (N), phosphorus (P), potassium (K), δ13C and leaf water potential (LWP) of 37 dominant desert plant species were investigated and analyzed. The C, N, K and δ13C concentrations in leaves of shrubs were found higher than herbs and subshrubs; however, P and LWP levels were higher in the leaves of subshrubs following herbs and shrubs. Moreover, leaf C showed a significant positive correlation with N and a negative correlation with δ13C. Leaf N exhibited a positive correlation with P. The relationship between soil and plant macro-elements was found generally insignificant but soil C and N exhibited a significant positive correlation with leaf P. Taxonomy showed a stronger effect on leaf C, N, P and δ13C than soil properties, explaining >50% of the total variability. C3 plants showed higher leaf C, N, P, K and LWP concentration than C4 plants, whereas C4 plants had higher δ13C than C3 plants. Legumes exhibited higher leaf C, N, K and LWP than nonlegumes, while nonlegumes had higher P and δ13C concentration than legumes. In all the species, significant phylogenetic signals (PS) were detected for C and N and nonsignificant PS for the rest of the leaf traits. In addition, these phylogenetic signals were found lower (K-value < 1), and the maximum K-value was noted for C (K = 0.35). The plants of common garden evolved and adapted themselves for their survival in the arid environment and showed convergent variations in their leaf traits. However, these variations were not phylogenetics-specific. Furthermore, marks of convergence found in leaf traits of the study area were most likely due to the environmental factors.

9.
New Phytol ; 228(5): 1524-1534, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32654190

RESUMO

Plant metabolism determines the structure and dynamics of ecological systems across many different scales. The metabolic theory of ecology quantitatively predicts the scaling of metabolic rate as a function of body size and temperature. However, the role of tissue water content has been neglected even though hydration significantly affects metabolism, and thus ecosystem structure and functioning. Here, we use a general model based on biochemical kinetics to quantify the combined effects of water content, body size and temperature on plant metabolic rates. The model was tested using a comprehensive dataset from 205 species across 10 orders of magnitude in body size from seeds to mature large trees. We show that water content significantly influences mass-specific metabolic rates as predicted by the model. The scaling exponents of whole-plant metabolic rate vs body size numerically converge onto 1.0 after water content is corrected regardless of body size or ontogenetic stage. The model provides novel insights into how water content together with body size and temperature quantitatively influence plant growth and metabolism, community dynamics and ecosystem energetics.

10.
Angew Chem Int Ed Engl ; 59(47): 21135-21142, 2020 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-32729214

RESUMO

The emergence of atomically precise metal nanoclusters with unique electronic structures provides access to currently inaccessible catalytic challenges at the single-electron level. We investigate the catalytic behavior of gold Au25 (SR)18 nanoclusters by monitoring an incoming and outgoing free valence electron of Au 6s1 . Distinct performances are revealed: Au25 (SR)18 - is generated upon donation of an electron to neutral Au25 (SR)18 0 and this is associated with a loss in reactivity, whereas Au25 (SR)18 + is generated from dislodgment of an electron from neutral Au25 (SR)18 0 with a loss in stability. The reactivity diversity of the three Au25 (SR)18 clusters stems from different affinities with reactants and the extent of intramolecular charge migration during the reactions, which are closely associated with the valence occupancies of the clusters varied by one electron. The stability difference in the three clusters is attributed to their different equilibria, which are established between the AuSR dissociation and polymerization influenced by one electron.

11.
J Phys Chem A ; 124(29): 6061-6067, 2020 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-32639744

RESUMO

Atomically precise metal clusters are now in the research spotlight, owing to the precise correlation between the physicochemical properties and their atomic-packing structures at an atomic-level. Herein we synthesized an Au8 cluster capped by four ferrocene ligands (DPPF), in which the ferrocene not only can direct the precise formation of the Au8 cluster, but also can solidify the structural pattern of the Au8 cluster. The Au8(DPPF)4 clusters as heterogeneous catalysts can achieve efficiently catalytic performances for the CO oxidation reaction, mainly due to the resistance to aggregation into large particles under reaction conditions. Our results suggest that the homolytic phosphine dissociation nature and the postdissociation reconstruction effect induced by Fe may enhance the catalytic performances of Au8(DPPF)4.

12.
Phys Med Biol ; 65(19): 195007, 2020 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-32604082

RESUMO

We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given 3D dose distribution. The proposed design of the adversarial network, which integrates a residual block into pix2pix framework, jointly trains a 'U-Net'-like architecture as the generator and a convolutional 'PatchGAN' classifier as the discriminator. 199 patients, including nasopharyngeal, lung and rectum, treated with intensity-modulated radiotherapy and volumetric-modulated arc therapy techniques were utilized to train the network. An additional 47 patients were used to test the prediction accuracy of the proposed deep learning model. The Dice similarity coefficient (DSC) was calculated to evaluate the similarity between the MLC aperture shapes obtained from the treatment planning system (TPS) and the deep learning prediction. The average and standard deviation of the bias between the TPS-generated MUs and predicted MUs was calculated to evaluate the MU prediction accuracy. In addition, the differences between TPS and deep learning-predicted MLC leaf positions were compared. The average and standard deviation of DSC was 0.94 ± 0.043 for 47 testing patients. The average deviation of predicted MUs from the planned MUs normalized to each beam or arc was within 2% for all the testing patients. The average deviation of the predicted MLC leaf positions was around one pixel for all the testing patients. Our results demonstrated the feasibility and reliability of the proposed approach. The proposed technique has strong potential to improve the efficiency and accuracy of the patient plan quality assurance process.


Assuntos
Aprendizado Profundo , Neoplasias Pulmonares/radioterapia , Neoplasias Nasofaríngeas/radioterapia , Planejamento da Radioterapia Assistida por Computador/métodos , Planejamento da Radioterapia Assistida por Computador/normas , Radioterapia de Intensidade Modulada/métodos , Neoplasias Retais/radioterapia , Humanos , Imagens de Fantasmas , Dosagem Radioterapêutica , Reprodutibilidade dos Testes
13.
J Am Chem Soc ; 142(9): 4141-4153, 2020 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-32048845

RESUMO

Unveiling the mystery of the contribution of nonsurface or noninterface sites in a catalyst to its catalytic performance remains a great challenge because of the difficulty in capturing precisely structural information (surface plus inner) encoded in the catalyst. This work attempts to elucidate the critical role of the internal vacancy in an atomically precise 24-atom gold cluster in regulating the catalytic performance on the hydrogenation reaction of CO2. The experiment results show that the Au24 cluster with internal vacancy can mitigate sintering and exhibit high catalytic activity under relatively harsh reaction conditions, in contrast to the structurally similar Au25 cluster without internal vacancy. Our computational study suggests that the internal vacancy in Au24 provides the cluster with much more structural flexibility, which may be crucial to resisting the aggregation of the cluster and further postponing the deactivation. The hydrogenation and coupling stages of the reaction intermediates are proposed to explain the potential reaction pathway of CO2 with H2 on the Au24 catalyst with internal vacancy.

14.
Med Phys ; 47(4): 1907-1919, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31901143

RESUMO

PURPOSE: To apply an imaging metric of the structural SIMilarity (SSIM) index to the radiotherapy dose verification field and evaluate its capability to reveal the different types of errors between two dose distributions. METHOD: The SSIM index consists of three sub-indices: luminance, contrast, and structure. Given two images, luminance analysis compares the local mean result, contrast analysis compares the local standard deviation, and the structure index represents the local Pearson correlation. Three test error patterns (absolute dose error, dose gradient error, and dose structure error) were designed to characterize the response of SSIM and its sub-indices and establish the correlation between the indices and different dose error types. After establishing the correlation, four radiotherapy plans (one MLC picket-fence test plan, one brain stereotactic radiotherapy plan, and two head-and-neck plans) were tested by computing each index and compared with the gamma analysis results to determine their similarities and differences. RESULTS: Among the three test error patterns, the luminance index decreased from 1 to 0.1 when the absolute dose agreement fell from 100% to 5%, the contrast index decreased from 1 to 0.36 when the dose gradient agreement fell from 100% to 10%, and the structure index decreased from 1 to 0.23 when the periodical dose pattern shifted (leading to a lower correlation). Thus, the luminance, contrast and structure index can detect the absolute dose error, gradient discrepancy, and dose structure error, respectively. For the four clinical cases, the sub-indices can reveal the type of error when gamma analysis only provided limited information. CONCLUSIONS: The correlation between the subcomponents of the SSIM index and the error types of the dose distribution were established. The SSIM index provides additional error information compared to that provided by gamma analysis.

15.
Biomed Phys Eng Express ; 6(1): 015025, 2020 01 20.
Artigo em Inglês | MEDLINE | ID: mdl-33438613

RESUMO

We develop a fully automated QA process to compare the image quality of all kV CBCT protocols on a Halcyon linac with ring gantry design, and evaluate image quality stability over a 10-month period. A total of 19 imaging scan and reconstruction protocols were characterized with measurement on a newly released QUART phantom. A set of image analysis algorithms were developed and integrated into an automated analysis suite to derive key image quality metrics, including HU value accuracy on density inserts, HU uniformity using the background plate, high contrast resolution with the modulation transfer function (MTF) from the edge profiles, low contrast resolution using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), slice thickness with the air gap modules, and geometric accuracy with the diameter of the phantom. Image quality data over 10 months was tracked and analyzed to evaluate the stability of the Halcyon kV imaging system. The HU accuracy over all 19 protocols is within tolerance (±50HU). The maximum uniformity deviation is 12.2 HU. The SNR and CNR, depending on the protocol selected, range from 18.5-911.9 and 1.9-102.8, respectively. A much-improved SNR and CNR were observed for iterative reconstruction (iCBCT) modes and protocols designed for large subjects over low dose and fast scanning modes. The Head and Image Gently protocols have the greatest high contrast resolution with MTF10% over 1 lp/mm and MTF50% over 0.6 lp/mm. The iCBCT mode slightly improved the MTF10% and MTF50% compared to the Feldkamp-Davis-Kress approach. The slice thickness (maximum error of 0.31 mm) and geometry metrics (maximum error of 0.7 mm) are all within tolerance (±0.5 mm for slice thickness and ±1 mm for geometry metrics). The long-term study over 10-month showed no significant drift for all key image quality metrics, which indicated the kV CBCT image quality is stable over time.

16.
J BUON ; 25(6): 2721-2730, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33455119

RESUMO

PURPOSE: PIWIL2, one of the PIWI gene subfamily, is now thought to be closely related to poor clinical outcomes in various cancers. The aim of this research was to comprehensively estimate its predictive value in the prognosis of cancer patients. METHODS: We thoroughly searched PubMed, Web of Science and Embase databases for eligible articles published until April 4th 2019, in which the association between cancer prognosis and PIWIL2 expression level was studied. Study qualities were assessed using NOS criteria. We performed analyses by Stata SE 12.0 and RevMan 5.3. The primary endpoints contained overall survival (OS), cancer-specific survival (CSS), metastasis-free survival (MFS), recurrence-free survival (RFS) and disease-free survival (DFS). RESULTS: Ten studies containing 2116 patients with 8 various solid cancers were finally included. The outcomes indicated that cancer patients with higher PIWIL2 expression level had significant shorter OS (HR:2.20, 95%CI:1.25-3.88, p=0.006), DFS/RFS/MFS (HR:2.96, 95%CI:1.68-5.23, p<0.001), CSS (HR: 2.12, 95%CI: 1.40-3.23, p<0.001) than cancer patients with lower PIWIL2 expression level. What's more, PIWIL2 over-expression was significantly correlated to more lymph node metastasis (LNM) (OR:1.61, 95%CI:1.28-2.02, p<0.001). And PIWIL2 expression was not significantly correlated with age, gender, differentiation, tumor invasion, tumor size, TNM stage and distant metastasis (DM). CONCLUSIONS: A higher expression level of PIWIL2 may predict a poorer prognosis of cancer patients. And its prognostic values are not significantly influenced by clinicopathological characters. Therefore, PIWIL2 could serve as a personalized prognostic predictor in cancers in the future.

17.
Radiat Oncol ; 14(1): 232, 2019 Dec 19.
Artigo em Inglês | MEDLINE | ID: mdl-31856866

RESUMO

OBJECTIVE: This study aims to investigate a hybrid automated treatment planning (HAP) solution that combines knowledge-based planning (KBP) and script-based planning for esophageal cancer. METHODS: In order to fully investigate the advantages of HAP, three planning strategies were implemented in the present study: HAP, KBP, and full manual planning. Each method was applied to 20 patients. For HAP and KBP, the objective functions for plan optimization were generated from a dose-volume histogram (DVH) estimation model, which was based on 70 esophageal patients. Script-based automated planning was used for HAP, while the regular IMRT inverse planning method was used for KBP. For full manual planning, clinical standards were applied to create the plans. Paired t-tests were performed to compare the differences in dose-volume indices among the three planning methods. RESULTS: Among the three planning strategies, HAP exhibited the best performance in all dose-volume indices, except for PTV dose homogeneity and lung V5. PTV conformity and spinal cord sparing were significantly improved in HAP (P < 0.001). Compared to KBP, HAP improved all indices, except for lung V5. Furthermore, the OAR sparing and target coverage between HAP and full manual planning were similar. Moreover, HAP had the shortest average planning time (57 min), when compared to KBP (63 min) and full manual planning (118 min). CONCLUSION: HAP is an effective planning strategy for obtaining a high quality treatment plan for esophageal cancer.


Assuntos
Neoplasias Esofágicas/radioterapia , Bases de Conhecimento , Órgãos em Risco/efeitos da radiação , Planejamento da Radioterapia Assistida por Computador/métodos , Adulto , Automação , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Dosagem Radioterapêutica , Radioterapia de Intensidade Modulada/métodos
18.
Sci Rep ; 9(1): 15346, 2019 10 25.
Artigo em Inglês | MEDLINE | ID: mdl-31653909

RESUMO

This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients' radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment.


Assuntos
Planejamento da Radioterapia Assistida por Computador , Neoplasias Retais/diagnóstico por imagem , Neoplasias Retais/radioterapia , Tomografia Computadorizada por Raios X , Algoritmos , Distribuição de Qui-Quadrado , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Biológicos , Estadiamento de Neoplasias , Neoplasias Retais/patologia , Análise de Sobrevida
19.
Radiother Oncol ; 141: 67-71, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31547944

RESUMO

PURPOSE: To analyze the impact of target dosimetry using propensity score matching (PSM) on patients' locoregional recurrence for nasopharyngeal carcinoma (NPC) and to find significant dose-volume factors of recurrence. METHODS: Sixty-eight nasopharyngeal carcinoma (NPC) patients with recorded locoregional recurrence were enrolled in this study. These patients were treated with IMRT in 2009-2010 in our department. Another 198 NPC patients without recurrence were randomly selected from the same treatment time period. The median follow-up time for all patients was 49.0 months. PSM was performed to match the recurrence and nonrecurrence cohorts. Dose-volume histograms (DVHs) of treatment planning were extracted for statistical analysis. Cox hazard model and Kaplan-Meier log-rank analysis were performed to evaluate correlations between PTV dose coverage and local/region recurrence. RESULTS: Propensity score matching balanced the clinical factors in two matches. Univariate cox survival model showed D90 and D95 were significantly correlated to the recurrence, and the D90 was the most significant (p = 0.036) one. The results of multivariate analysis show that only D90 is required for recurrence prediction when collinear dosimetric factors are considered. KM log-rank analysis showed that patients have significant local/regional control differences (p-value = 0.036, log-rank) in the D90 >101% and D90 <101% groups. CONCLUSION: D90 corresponds to significant dose-volume factors. PTV dose coverage has a significant impact on locoregional recurrence in NPC clinical routine patients.


Assuntos
Carcinoma Nasofaríngeo/radioterapia , Neoplasias Nasofaríngeas/radioterapia , Recidiva Local de Neoplasia/etiologia , Radiometria/métodos , Adulto , Idoso , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Carcinoma Nasofaríngeo/patologia , Carcinoma Nasofaríngeo/secundário , Neoplasias Nasofaríngeas/patologia , Recidiva Local de Neoplasia/patologia , Estadiamento de Neoplasias , Pontuação de Propensão , Modelos de Riscos Proporcionais , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador/métodos , Distribuição Aleatória
20.
Clin Lung Cancer ; 20(6): e638-e651, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31375452

RESUMO

BACKGROUND: The purpose of the study was to investigate the potential of a radiomic signature developed in a general non-small-cell lung cancer (NSCLC) cohort for predicting the overall survival of anaplastic lymphoma kinase (ALK)-positive (ALK+) patients with different treatment types. MATERIALS AND METHODS: After test-retest in the Reference Image Database to Evaluate Therapy Response data set, 132 features (intraclass correlation coefficient > 0.9) were selected in the least absolute shrinkage and selection operator Cox regression model with a leave-one-out cross-validation. The NSCLC radiomics collection from The Cancer Imaging Archive was randomly divided into a training set (n = 254) and a validation set (n = 63) to develop a general radiomic signature for NSCLC. In our ALK+ set, 35 patients received targeted therapy and 19 patients received nontargeted therapy. The developed signature was tested later in this ALK+ set. Performance of the signature was evaluated with the concordance index (C-index) and stratification analysis. RESULTS: The general signature had good performance (C-index > 0.6; log rank P < .05) in the NSCLC radiomics collection. It includes 5 features: Geom_va_ratio, W_GLCM_Std, W_GLCM_DV, W_GLCM_IM2, and W_his_mean. Its accuracy of predicting overall survival in the ALK+ set achieved 0.649 (95% confidence interval [CI], 0.640-0.658). Nonetheless, impaired performance was observed in the targeted therapy group (C-index = 0.573; 95% CI, 0.556-0.589) whereas significantly improved performance was observed in the nontargeted therapy group (C-index = 0.832; 95% CI, 0.832-0.852). Stratification analysis also showed that the general signature could only identify high- and low-risk patients in the nontargeted therapy group (log rank P = .00028). CONCLUSION: This preliminary study suggests that the applicability of a general signature to ALK+ patients is limited. The general radiomic signature seems to be only applicable to ALK+ patients who had received nontargeted therapy, which indicates that developing special radiomics signatures for patients treated with tyrosine kinase inhibitors might be necessary.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/diagnóstico , Diagnóstico por Imagem/métodos , Neoplasias Pulmonares/diagnóstico , Pulmão/diagnóstico por imagem , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Quinase do Linfoma Anaplásico/metabolismo , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/terapia , Estudos de Coortes , Feminino , Humanos , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/terapia , Masculino , Pessoa de Meia-Idade , Prognóstico , Análise de Sobrevida , Tomografia Computadorizada por Raios X , Adulto Jovem
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