Feature-Guided Deep Radiomics for Glioblastoma Patient Survival Prediction

Glioblastoma is recognized as World Health Organization (WHO) grade IV glioma with an aggressive growth pattern. The current clinical practice in diagnosis and prognosis of Glioblastoma using MRI involves multiple steps including manual tumor sizing. Accurate identification and segmentation of multiple abnormal tissues within tumor volume in MRI is essential for precise survival prediction. Manual tumor and abnormal tissue detection and sizing are tedious, and subject to inter-observer variability. Consequently, this work proposes a fully automated MRI-based glioblastoma and abnormal tissue segmentation, and survival prediction framework. The framework includes radiomics feature-guided deep neural network methods for tumor tissue segmentation; followed by survival regression and classification using these abnormal tumor tissue segments and other relevant clinical features. The proposed multiple abnormal tumor tissue segmentation step effectively fuses feature-based and feature-guided deep radiomics information in structural MRI. The survival prediction step includes two representative survival prediction pipelines that combine different feature selection and regression approaches. The framework is evaluated using two recent widely used benchmark datasets from Brain Tumor Segmentation (BraTS) global challenges in 2017 and 2018. The best overall survival pipeline in the proposed framework achieves leave-one-out cross-validation (LOOCV) accuracy of 0.73 for training datasets and 0.68 for validation datasets, respectively. These training and validation accuracies for tumor patient survival prediction are among the highest reported in literature. Finally, a critical analysis of radiomics features and efficacy of these features in segmentation and survival prediction performance is presented as lessons learned

Latest Developments on the Viscosity of Nanofluids

a b s t r a c t The past decade has seen the rapid development of nanofluids science in many aspects. Number of research is conducted that is mostly focused on the thermal conductivity of these fluids. However, nanofluid viscosity also deserves the same attention as thermal conductivity. In this paper, different characteristics of viscosity of nanofluids including nanofluid preparation methods, temperature, particle size and shape, and volume fraction effects are thoroughly compiled and reviewed. Furthermore, a precise review on theoretical models/correlations of conventional models related to nanofluid viscosity is presented. The existing experimental results about the nanofluids viscosity show clearly that viscosity augmented accordingly with an increase of volume concentration and decreased with the temperature rise. However, there are some contradictory results on the effects of temperature on viscosity. Moreover, it is shown that particle size has some noteworthy effects over viscosity of nanofluids

Optimization of ultrasonication period for better dispersion and stability of TiO2-water nanofluid

Nanofluids are promising in many fields, including engineering and medicine. Stability deterioration may be a critical constraint for potential applications of nanofluids. Proper ultrasonication can improve the stability, and possibility of the safe use of nanofluids in different applications. In this study, stability properties of TiO2-H2O nanofluid for varying ultrasonication durations were tested. The nanofluids were prepared through two-step method; and electron microscopies, with particle size distribution and zeta potential analyses were conducted for the evaluation of their stability. Results showed the positive impact of ultrasonication on nanofluid dispersion properties up to some extent. Ultrasonication longer than 150 min resulted in re-agglomeration of nanoparticles. Therefore, ultrasonication for 150 min was the optimum period yielding highest stability. A regression analysis was also done in order to relate the average cluster size and ultrasonication time to zeta potential. It can be concluded that performing analytical imaging and colloidal property evaluation during and after the sample preparation leads to reliable insights

Stability, thermophysical properties and performance assessment of alumina-water nanofluid with emphasis on ultrasonication and storage period

Owing to the improvements in thermophysical properties, nanofluids are considered advantageous over pure fluids in heat transfer applications. However, these improvements may be regarded as meaningful for applications provided that optimum dispersion of nanoparticles is ensured throughout the process, which mostly depend on preparation technique. In this study, alumina (Al2O3)-water nanofluids of 0.5 vol% were prepared using ultrasonication (up to 5 h) and stored at stationary condition until 30 days. We have evaluated stability as temporal volume fraction by measuring density. Further, thermal conductivity and viscosity were measured, and heat transfer performance was analyzed for the case of fully developed laminar flow inside a tube. All the measurements were conducted at 25 degrees C temperature. Results revealed that longer ultrasonication reduces sedimentation of nanoparticles and hence, increases stability of nanofluids. Thermal conductivity increased, while viscosity decreased with increasing sonication time. Moreover, these thermophysical properties decreased with storage periods. It was observed, until 30 days of storage that ultrasonication process for different durations induced significant changes in viscosity, although those in thermal conductivity was not as pronounced. All the prepared samples were determined beneficial as heat transfer fluids over water, even after 30 days from preparation

Thermal performance analysis of Al2O3/R-134a nanorefrigerant

Nowadays, nanofluids are being considered as an efficient heat transfer fluid in various thermal applications. Refrigerant-based nanofluids, termed as "nanorefrigerants", have the potential to improve the heat transfer performances of refrigeration and air-conditioning systems. This study analyzed the thermophysical properties and their effects on the coefficient of performance (COP) resulted by addition of 5 vol.% AlO nanoparticles into R-134a refrigerant at temperatures of 283-308 K. The analysis has been done for a uniform mass flux through a horizontal smooth tube using established correlations. The results indicate that the thermal conductivity, dynamic viscosity, and density of AlO/R-134a nanorefrigerant increased about 28.58%, 13.68%, and 11%, respectively compared to the base refrigerant (R-134a) for the same temperature. On the other hand, specific heat of nanorefrigerant is slightly lower than that of R-134a. Moreover, AlO/R-134a nanorefrigerant shows the highest COP of 15%, 3.2%, and 2.6% for thermal conductivity, density, and specific heat, respectively compared to R-134a refrigerant. Therefore, application of nanoparticles in refrigeration and air-conditioning systems is promising to improve the performances of the systems

Experimental investigation on effect of ultrasonication duration on colloidal dispersion and thermophysical properties of alumina-water nanofluid

Two decades have been going on since nanofluid was introduced with the hope that it could enhance the thermal performances of heat transfer applications. Nevertheless, yet, there are no standards for nanofluid preparation process (sonicator type, power, amplitude, duration) to achieve stable and well-dispersed nanofluid. The aim of this research is to analyze the consequence of ultrasonication duration on colloidal dispersion and thermophysical properties of 0.5 vol.% of Al2O3-water nanofluid. A horn ultrasonic dismembrator was used for different periods from Oh to 5 h for nanofluid preparation. Particle size distribution (PSD), zeta potential, and microstructure were studied to check the dispersion characteristics. Thermal conductivity, viscosity, and density of the nanofluid were analyzed for different temperatures from 10 degrees C to 50 degrees C. Better dispersion, higher thermal conductivity and density, and lower viscosity have been observed with the increase of sonication time. Furthermore, thermal conductivity was found to be increased but viscosity and density were decreased with the increase of temperature. The research concluded that higher ultrasonication duration is best and at least 2 h of ultrasonication is needed for better performance of the nanofluid. (C) 2015 Elsevier Ltd. All rights reserved