scholarly journals PORTAL VEIN AND LIVER BARIUM EMBOLISM

2021 ◽  
Vol 5 (2) ◽  
pp. 191-196
Author(s):  
N. I. Prokopchik ◽  
◽  
R. E. Yakubtsevich ◽  
S. SH. Kerimova ◽  
A. A. Balla ◽  
...  

Background. An upper and lower gastrointestinal (GI) series is an available and informative diagnostic test. Side effects are extremely rare. Objective. To present a case description of portal vein and liver barium embolism with a fatal outcome and explain the mechanism of its occurrence. Material and methods. The clinical manifestations, laboratory and instrumental findings, as well as autopsy of a female patient who died after lower GI radiography were analyzed. Results. To exclude intestinal obstruction, the patient underwent a barium follow through. Three days later, during X-ray computed tomography, barium and gas were detected in the inferior mesenteric vein, portal vein and its intrahepatic branches. During colonoscopy, diverticula of the sigmoid colon were detected, but the localization of the intestinalvenous fistula wasn’t determined. Conservative surgery failed and the death occurred 15 days after radiography. Conclusions. The autopsy revealed that the site of entry for the development of barium embolism as well as for gas, were diabrotic veins in peridiverticular abscesses localized in pericolic tissue.

1999 ◽  
Vol 11 (1) ◽  
pp. 199-211
Author(s):  
J. M. Winter ◽  
R. E. Green ◽  
A. M. Waters ◽  
W. H. Green

2013 ◽  
Vol 19 (S2) ◽  
pp. 630-631
Author(s):  
P. Mandal ◽  
W.K. Epting ◽  
S. Litster

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 591
Author(s):  
Manasavee Lohvithee ◽  
Wenjuan Sun ◽  
Stephane Chretien ◽  
Manuchehr Soleimani

In this paper, a computer-aided training method for hyperparameter selection of limited data X-ray computed tomography (XCT) reconstruction was proposed. The proposed method employed the ant colony optimisation (ACO) approach to assist in hyperparameter selection for the adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm, which is a total-variation (TV) based regularisation algorithm. During the implementation, there was a colony of artificial ants that swarm through the AwPCSD algorithm. Each ant chose a set of hyperparameters required for its iterative CT reconstruction and the correlation coefficient (CC) score was given for reconstructed images compared to the reference image. A colony of ants in one generation left a pheromone through its chosen path representing a choice of hyperparameters. Higher score means stronger pheromones/probabilities to attract more ants in the next generations. At the end of the implementation, the hyperparameter configuration with the highest score was chosen as an optimal set of hyperparameters. In the experimental results section, the reconstruction using hyperparameters from the proposed method was compared with results from three other cases: the conjugate gradient least square (CGLS), the AwPCSD algorithm using the set of arbitrary hyperparameters and the cross-validation method.The experiments showed that the results from the proposed method were superior to those of the CGLS algorithm and the AwPCSD algorithm using the set of arbitrary hyperparameters. Although the results of the ACO algorithm were slightly inferior to those of the cross-validation method as measured by the quantitative metrics, the ACO algorithm was over 10 times faster than cross—Validation. The optimal set of hyperparameters from the proposed method was also robust against an increase of noise in the data and can be applicable to different imaging samples with similar context. The ACO approach in the proposed method was able to identify optimal values of hyperparameters for a dataset and, as a result, produced a good quality reconstructed image from limited number of projection data. The proposed method in this work successfully solves a problem of hyperparameters selection, which is a major challenge in an implementation of TV based reconstruction algorithms.


2021 ◽  
Author(s):  
Katherine A. Wolcott ◽  
Guillaume Chomicki ◽  
Yannick M. Staedler ◽  
Krystyna Wasylikowa ◽  
Mark Nesbitt ◽  
...  

2021 ◽  
Vol 33 (7) ◽  
pp. 076610
Author(s):  
Chunwei Zhang ◽  
Yun She ◽  
Yingxue Hu ◽  
Zijing Li ◽  
Weicen Wang ◽  
...  

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