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Med Phys ; 25(12): 2432-9, 1998 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-9874837

RESUMO

Our purpose in this study was to investigate the influence of segmentation threshold and number of erosions on parameters used in quantitative computed tomography (CT) of the lung (erosions are shrink operations on the segmented area). Parameters assessed were mean lung density, area of the segmented lung, two percentiles, and the pixel index, which is the relative area of the histogram below -905 Hounsfield Units (HU). We analyzed images of ten emphysematous and ten nonemphysematous patients, that had been scanned at carina level in inspiration and expiration, using sections of 1, 2, 3, 5, and 10 mm in combination with a standard, a smooth, and an ultrasmooth reconstruction kernel. The lungs were segmented using pixel tracing at thresholds of -200, -400, and -600 HU with 0-4 erosions, followed by histogram analysis. The area of the segmented lungs decreased with 0.9%-3.2% per 100 HU decrease in threshold and with 2.2%-3.1% per erosion, dependent on patient group and respiratory status. Estimated mean lung density changed up to 30% by changing the threshold and the number of erosions. The pixel index and the 10th percentile depended only slightly on threshold and number of erosions, but the 90th percentile showed a strong dependence of up to 40%. It is concluded that the segmentation protocol can have a large impact on densitometric parameters and that standardization is mandatory for obtaining comparable results. Ideally a threshold equal to the average of the densities of lung and soft tissue should be used, but -400 HU will do in a limited but common density range (-910 to -790 HU). For densitometry two erosions are recommended, for volumetry zero erosions should be used.


Assuntos
Pulmão/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Enfisema/diagnóstico por imagem , Humanos , Imagens de Fantasmas , Interpretação de Imagem Radiográfica Assistida por Computador , Tomografia Computadorizada por Raios X/estatística & dados numéricos
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