Idiopathic perinatal hepatic infarct as a cause of liver mass

We present the case of a 2-week-old male infant who presented with an asymptomatic liver mass and underwent surgical resection because of suspicion of malignancy after extensive radiological study with ultrasonography, computed tomography, and MRI. Pathological examination revealed a peripheral hepatic infarct with calcifications and a rim of peripheral organization suggestive of being at least 2 weeks old. This case reviews the scarce cases of hepatic infarct in newborns and highlights the fact that, although untreated perinatal hepatic infarction usually progresses to atrophy of the affected area with compensation by the unaffected liver, surgical resection remains an option in cases of complications or uncertain diagnosis

Management\u27s Perspective on Critical Success Factors Affecting Mobile Learning in Higher Education Institutions - An Empirical Study

Mobile learning (m-Learning) is considered to be one of the fastest growing learning platforms. The immense interest in m-Learning is attributed to the incredible rate of growth of mobile technology and its proliferation into every aspect of modern life. Despite this, m-Learning has not experienced a similar adoption rate in the education sector, chiefly higher education. Researchers have attempted to explain this anomaly by conducting several studies in the area. However, mostly the research in m-Learning is examined from the perspective of the students and educators. In this research, it is contended that there is a third important stakeholder group whose opinion is equally important in determining the success of m-Learning: the university management. Although diversified by nature, heads of departments, deans, and information technology system administrators are nevertheless considered members of any university management. The results of the research show that university commitment to m-Learning, university learning practices, and change management practices were the factors critical to the success of m-Learning, from the university management perspective

Anatomy and pathology of the canal of Nuck.

The canal of Nuck is the female equivalent of the processus vaginalis in the male but is less well known than its male counterpart. It is a rare entity not commonly encountered by radiologists, particularly in the adult population. Knowledge of the embryology and anatomy of the canal of Nuck is essential for identification of the various pathologic conditions that may occur in this location. Moreover, radiologists should be familiar with this entity to compose an appropriate and thorough differential diagnosis of a labial mass/swelling. In this review, we discuss both the anatomy and the more common pathology that can be encountered within it

Characterization of solid renal neoplasms using MRI-based quantitative radiomics features

PURPOSE To assess the diagnostic value of magnetic resonance imaging (MRI)-based radiomics features using machine learning (ML) models in characterizing solid renal neoplasms, in comparison/combination with qualitative radiologic evaluation. METHODS Retrospective analysis of 125 patients (mean age 59 years, 67% males) with solid renal neoplasms that underwent MRI before surgery. Qualitative (signal and enhancement characteristics) and quantitative radiomics analyses (histogram and texture features) were performed on T2-weighted imaging (WI), T1-WI pre- and post-contrast, and DWI. Mann-Whitney U test and receiver-operating characteristic analysis were used in a training set (n = 88) to evaluate diagnostic performance of qualitative and radiomics features for differentiation of renal cell carcinomas (RCCs) from benign lesions, and characterization of RCC subtypes (clear cell RCC [ccRCC] and papillary RCC [pRCC]). Random forest ML models were developed for discrimination between tumor types on the training set, and validated on an independent set (n = 37). RESULTS We assessed 104 RCCs (51 ccRCC, 29 pRCC, and 24 other subtypes) and 21 benign lesions in 125 patients. Significant qualitative and quantitative radiomics features (area under the curve [AUC] between 0.62 and 0.90) were included for ML analysis. Models with best diagnostic performance on validation sets showed AUC of 0.73 (confidence interval [CI] 0.5-0.96) for differentiating RCC from benign lesions (using combination of qualitative and radiomics features); AUC of 0.77 (CI 0.62-0.92) for diagnosing ccRCC (using radiomics features), and AUC of 0.74 (CI 0.53-0.95) for diagnosing pRCC (using qualitative features). CONCLUSION ML models incorporating MRI-based radiomics features and qualitative radiologic assessment can help characterize renal masses

Energy and exergy analysis and thermo-economic optimization of the ground source heat pump integrated with radiant wall panel and fan-coil unit with floor heating or radiator

Current study is aimed at making the most appropriate design considering the dynamic energy, exergy and economic analysis of Ground Source Heat Pumps (GSHP). The energy required to heat and to cool a 200 m(2) office in Istanbul is determined, and based on these data, the entering and leaving water and soil temperatures of horizontal Ground Heat Exchanger (GHE) are obtained numerically for a ten-year period with realistic boundary conditions using meteorological data. The results obtained from the numerical study are confirmed by GHE experimental setup built in Yildiz Technical University. The variations of COP, second-law efficiency and exergy destruction of each component of GSHP at both seasons of the first, fifth and tenth years are obtained for Radiant Wall Panel Unit (RW-PU), Floor Heating + Fan-Coil Unit (FH-FCU) and Radiator + Fan-Coil Unit (R-FCU) systems. At the end of the 10-year dynamic simulation period of the GSHP system, the average values of COP and second law efficiency for RW-PU, FHFCU and R-FCU are found as 4.01, 3.37, 3.01, and 39.29%, 38.04%, 36.63%, respectively. Furthermore, considering the initial investment and operational costs of RW-PU, FH-FCU and R-FCU systems integrated into the GSHP system, an objective function is defined as an optimization parameter. (C) 2020 Elsevier Ltd. All rights reserved