OBJECTIVE: Imaging diagnosis of cervical lymphadenopathy has conventionally used ultrasonography. Shear wave elastography (SWE) is a recent ultrasound technological advancement that has shown promise in the important medical problem of differentiating between benign and malignant cervical lymph nodes based on quantitative measurements of elasticity modulus. However, widely varying elasticity modulus metrics and regions-of-interest (ROIs) were used in existing studies, leading to inconsistent findings and results that are hard to compare with each other. METHODS: Using a large dataset of 264 cervical lymph nodes from 200 patients, we designed a study comparing three elasticity modulus metrics (Emax, Emean, and standard deviation-SD) with three different ROIs to evaluate the effect of such selections. The metric values were compared between the benign and malignant node groups. The different ROI and metric selections were also compared through receiver operating characteristics curve analysis. RESULTS: For all ROIs, all metric values were significantly different between the two groups, indicting their diagnostic potential. This was confirmed by the ≥0.80 area under the curve (AUC) values achieved with these metrics. Different ROIs had no effect on Emax, whereas all ROIs achieved high performance at 0.88 AUC. For Emean, the smallest ROI focusing on the area of the highest elasticity achieved the best diagnostic performance. In contrast, the larger ROIs achieved higher performances for SD. CONCLUSIONS: This study illustrated the effect of elasticity modulus and ROI selection on the diagnostic performance of SWE on cervical lymphadenopathy. These new findings help guide relevant future studies and clinical applications of this important quantitative imaging modality.

ABSTRACT Effects of leached amylose (AM) and amylopectin (AP) on textural and morphological properties of cooked rice were investigated separately by replacing cooking liquid with AM and AP separated from pouring cooking liquid. The pouring of cooking water reduced the hardness (from 28.45 to 19.42N) and stickiness (from 1.74 to 1.19N·s) significantly. However, the addition of AM and AP enhanced the hardness (27.63N) and stickiness (1.71N·s).Scanning electron microscopy show that the leached short-chain AM entered the surface hollows in the cooked rice after water evaporation. Meanwhile, the Long-chain AM cross-linked to formed a three-dimensional network structures, which covered on the filled hollows. This distribution led to a harder texture of cooked rice. The leached AP absorbed water and swelledto form masses. Atthe gelatinization temperature,theAPmassesagglomeratedtoformafilmlayer,whichcoveredtheunevenstructure, the thicker and smoother film contributed to the sticky texture.

Na construção de uma área de influência, o método de dilatação baseada em rasterização inevitavelmente introduz erros, e o método de dupla linha paralela envolve uma série de operações complexas. Neste artigo, propõe-se um algoritmo de armazenamento paralelo baseado na fusão de área e MPI (Interface de transferência de Mensagem) para melhorar o desempenho de análise de armazenamento, no processamento de grandes conjuntos de dados. Os resultados experimentais revelam que há três grandes gargalos de desempenho que impactam significativamente a eficiência de construção de armazenamentos seriais e paralelos, incluindo a estratégia de fusão de área, a tarefa / método do balanceamento de carga e os MPI resultantes da estratégia de fusão. Para superar esses gargalos, são sugeridas abordagens de correspondência de otimização envolvendo a estratégia de fusão em árvore, um método orientado de partição do número de vértices em tarefas paralelas e uma estratégia de fusão dos inter-processos. Os experimentos foram realizados para examinar a eficiência do algoritmo paralelo de otimização. Os resultados estimados sugerem que as abordagens de otimização podem fornecer alto desempenho e capacidade de processamento para a construção de armazenamento em um ambiente paralelo agrupado. Esse método pode fornecer sugestões sobre a paralelização de algoritmos de análise espacial.

On buffer zone construction, the rasterization-based dilation method inevitably introduces errors, and the double-sided parallel line method involves a series of complex operations. In this paper, we proposed a parallel buffer algorithm based on area merging and MPI (Message Passing Interface) to improve the performances of buffer analyses on processing large datasets. Experimental results reveal that there are three major performance bottlenecks which significantly impact the serial and parallel buffer construction efficiencies, including the area merging strategy, the task load balance method and the MPI inter-process results merging strategy. Corresponding optimization approaches involving tree-like area merging strategy, the vertex number oriented parallel task partition method and the inter-process results merging strategy were suggested to overcome these bottlenecks. Experiments were carried out to examine the performance efficiency of the optimized parallel algorithm. The estimation results suggested that the optimization approaches could provide high performance and processing ability for buffer construction in a cluster parallel environment. Our method could provide insights into the parallelization of spatial analysis algorithm.