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Med Sci Monit ; 26: e920239, 2020 Feb 29.
Artigo em Inglês | MEDLINE | ID: mdl-32111815

RESUMO

BACKGROUND Acute pulmonary embolism is one of the most common cardiovascular diseases. Computer-aided technique is widely used in chest imaging, especially for assessing pulmonary embolism. The reliability and quantitative analyses of computer-aided technique are necessary. This study aimed to evaluate the reliability of geometry-based computer-aided detection and quantification for emboli morphology and severity of acute pulmonary embolism. MATERIAL AND METHODS Thirty patients suspected of acute pulmonary embolism were analyzed by both manual and computer-aided interpretation of vascular obstruction index and computer-aided measurements of emboli quantitative parameters. The reliability of Qanadli and Mastora scores was analyzed using computer-aided and manual interpretation. RESULTS The time costs of manual and computer-aided interpretation were statistically different (374.90±150.16 versus 121.07±51.76, P<0.001). The difference between the computer-aided and manual interpretation of Qanadli score was 1.83±2.19, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (intraclass correlation coefficient, ICC=0.998). The difference between the computer-aided and manual interpretation of Mastora score was 1.46±1.62, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (ICC=0.997). The emboli quantitative parameters were moderately correlated with the Qanadli and Mastora scores (all P<0.001). CONCLUSIONS Computer-aided technique could reduce the time costs, improve the and reliability of vascular obstruction index and provided additional quantitative parameters for disease assessment.


Assuntos
Diagnóstico por Computador , Embolia/diagnóstico por imagem , Artéria Pulmonar/diagnóstico por imagem , Embolia Pulmonar/diagnóstico , Análise Custo-Benefício , Diagnóstico por Computador/economia , Diagnóstico por Computador/métodos , Precisão da Medição Dimensional , Feminino , Humanos , Processamento de Imagem Assistida por Computador/métodos , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Índice de Gravidade de Doença
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