Qualitative stomach cancer assessment by multi-slice computed tomography
ABSTRACT A theoretical framework based on the Borrmann classification and the Japanese gastric cancer classification is proposed in order to qualitatively assess the stomach cancer from the three-dimensional (3-D) images obtained using multi-slice computerized tomography (MSCT). The main goal of thi...
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Universidad de Tarapacá.
2020
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oai:scielo:S0718-330520200004006942021-02-05Qualitative stomach cancer assessment by multi-slice computed tomographyChacón,GerardoRodríguez,Johel E.Bermúdez,ValmoreVera,MiguelHernandez,Juan DiegoPardo,AldoLameda,CarlosMadriz,DeliaBravo,Antonio José Stomach cancer adenocarcinoma macroscopic assessment Borrmann classification Japanese classification medical imaging multi-slice computerized tomography ABSTRACT A theoretical framework based on the Borrmann classification and the Japanese gastric cancer classification is proposed in order to qualitatively assess the stomach cancer from the three-dimensional (3-D) images obtained using multi-slice computerized tomography (MSCT). The main goal of this paper is to demonstrate through visual inspection, the MSCT capacity to effectively reflect the morphopathological characteristics of the stomach adenocarcinoma types. The idea is to contrast the pathological theoretic characteristics with those that are possible to understand from MSCT images available in clinical datasets. This research corresponds to a study with a mixed approach (qualitative and quantitative), applied to a total of 46 images available for patients diagnosed, from the data collection included of the Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD). The conclusions are established from a comparative analysis based on the document review and direct observation, the product being a matrix of compliance with the specific qualities of the theoretical standards, in the visualization of images performed by the clinical specialist from the datasets. A total of 6210 slices from 46 MSCT explorations are visually inspected, and then visual characteristics are contrasted with respect to the theoretic characteristics obtained from the cancer classifications. These characteristics match into about 96% of images inspected. The approach effectiveness measured using the positive predictive value is about 96.50%. The results of the images data also show a sensitivity of 97.83%, and specificity of 98.27%. MSCT is a precise imaging modality in the qualitative assessment of the staging of stomach cancer.info:eu-repo/semantics/openAccessUniversidad de Tarapacá.Ingeniare. Revista chilena de ingeniería v.28 n.4 20202020-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052020000400694en10.4067/S0718-33052020000400694 |
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Scielo Chile |
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Scielo Chile |
language |
English |
topic |
Stomach cancer adenocarcinoma macroscopic assessment Borrmann classification Japanese classification medical imaging multi-slice computerized tomography |
spellingShingle |
Stomach cancer adenocarcinoma macroscopic assessment Borrmann classification Japanese classification medical imaging multi-slice computerized tomography Chacón,Gerardo Rodríguez,Johel E. Bermúdez,Valmore Vera,Miguel Hernandez,Juan Diego Pardo,Aldo Lameda,Carlos Madriz,Delia Bravo,Antonio José Qualitative stomach cancer assessment by multi-slice computed tomography |
description |
ABSTRACT A theoretical framework based on the Borrmann classification and the Japanese gastric cancer classification is proposed in order to qualitatively assess the stomach cancer from the three-dimensional (3-D) images obtained using multi-slice computerized tomography (MSCT). The main goal of this paper is to demonstrate through visual inspection, the MSCT capacity to effectively reflect the morphopathological characteristics of the stomach adenocarcinoma types. The idea is to contrast the pathological theoretic characteristics with those that are possible to understand from MSCT images available in clinical datasets. This research corresponds to a study with a mixed approach (qualitative and quantitative), applied to a total of 46 images available for patients diagnosed, from the data collection included of the Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD). The conclusions are established from a comparative analysis based on the document review and direct observation, the product being a matrix of compliance with the specific qualities of the theoretical standards, in the visualization of images performed by the clinical specialist from the datasets. A total of 6210 slices from 46 MSCT explorations are visually inspected, and then visual characteristics are contrasted with respect to the theoretic characteristics obtained from the cancer classifications. These characteristics match into about 96% of images inspected. The approach effectiveness measured using the positive predictive value is about 96.50%. The results of the images data also show a sensitivity of 97.83%, and specificity of 98.27%. MSCT is a precise imaging modality in the qualitative assessment of the staging of stomach cancer. |
author |
Chacón,Gerardo Rodríguez,Johel E. Bermúdez,Valmore Vera,Miguel Hernandez,Juan Diego Pardo,Aldo Lameda,Carlos Madriz,Delia Bravo,Antonio José |
author_facet |
Chacón,Gerardo Rodríguez,Johel E. Bermúdez,Valmore Vera,Miguel Hernandez,Juan Diego Pardo,Aldo Lameda,Carlos Madriz,Delia Bravo,Antonio José |
author_sort |
Chacón,Gerardo |
title |
Qualitative stomach cancer assessment by multi-slice computed tomography |
title_short |
Qualitative stomach cancer assessment by multi-slice computed tomography |
title_full |
Qualitative stomach cancer assessment by multi-slice computed tomography |
title_fullStr |
Qualitative stomach cancer assessment by multi-slice computed tomography |
title_full_unstemmed |
Qualitative stomach cancer assessment by multi-slice computed tomography |
title_sort |
qualitative stomach cancer assessment by multi-slice computed tomography |
publisher |
Universidad de Tarapacá. |
publishDate |
2020 |
url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052020000400694 |
work_keys_str_mv |
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1714203485918986240 |