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Abdom Radiol (NY) ; 43(9): 2455-2461, 2018 09.
Artigo em Inglês | MEDLINE | ID: mdl-29460042

RESUMO

PURPOSE: The aim of the study was to find which linear measurements, field and volume coefficients correlate the best with real volume of the spleen and can be further used for identification of splenomegaly. METHODS: Abdominal computed tomography (CT) examinations of 264 patients were retrospectively analyzed in terms of maximal length, maximal thickness, hilum thickness, maximal height, vertical height and estimated height. Spleen volume was manually measured in Vitrea software. Two- and three-dimensional coefficients were calculated through proper mathematical formulas from linear measurements. Splenomegaly cut-off: 314.5 cm3. Data were analyzed with use of Pearson correlation and χ2 test with statistical significance at p < 0.05. RESULTS: For single measurements, the correlation with real spleen volume was the strongest for maximal height (r = 0.804; p < 0.05). Among two-dimensional indexes, multiplication product of maximal length and vertical height reached the highest level of correlation with spleen volume (r = 0.923; p < 0.05) and had the highest sensitivity and specificity (94.3% and 93.0%, respectively) for splenomegaly detection (threshold 115 cm2). In case of three-dimensional ones, the coefficient calculated from maximal length, vertical height and hilum thickness established the strongest link with spleen volume (r = 0.956; p < 0.05). CONCLUSIONS: Coefficient calculated from maximal length, vertical height and hilum thickness correlates the strongest with spleen volume and can be utilized for monitoring of spleen volume instead of obsolete splenic index. The most suitable for quick splenomegaly screening is two-dimensional coefficient (maximal length × vertical height), with the cut-off 115 cm2.


Assuntos
Esplenomegalia/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Interpretação de Imagem Radiográfica Assistida por Computador , Estudos Retrospectivos
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