PubMed · 10076328
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S Hagen. 1998-11-04. Making inferences from data.. https://pubmed.ncbi.nlm.nih.gov/10076328/
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PURPOSE: We investigated the value of contrast-enhanced color Doppler sonography in the differential diagnosis of liver tumors. METHODS: We prospectively examined 105 focal liver lesions in 100 patients by real-time gray-scale sonography, color Doppler sonography, and contrast-enhanced color Doppler sonography with galactose-based microbubbles (SH U 508A; Levovist). The final diagnoses of the liver lesions as confirmed by pathology or additional imaging techniques were 31 metastases, 25 hemangiomas, 19 hepatocellular carcinomas, 19 focal nodular hyperplasias, 2 cholangiocellular carcinomas, and 9 other lesions. RESULTS: Vascularity could be detected in 43 (41%) of the 105 lesions by conventional color Doppler sonography compared to 67 (64%) by contrast-enhanced color Doppler sonography. Contrast-enhanced color Doppler sonography identified moderate or extensive vascularity in all 19 focal nodular hyperplasias, moderate or extensive vascularity in 16 hepatocellular carcinomas and both cholangiocellular carcinomas, and no or minor vascularity in all but 3 hemangioma. The combination of gray-scale, conventional color Doppler, and contrast-enhanced color Doppler sonography led to the correct diagnosis in 81% of cases (85 of 105), compared to 57% (60/105) for gray-scale and conventional color Doppler sonography and 31% (33/105) for gray-scale sonography alone. CONCLUSIONS: Contrast-enhanced color Doppler sonography improves the detection of tumor vascularity and is useful in the differential diagnosis of liver lesions.
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Methods for optimal sample size determination are developed using four popular multiple comparison procedures (Scheffe's, Bonferroni's, Tukey's and Dunnett's procedures), where random samples of the same size n are to be selected from k (>/=2) normal populations with common variance sigma2, and where primary interest concerns inferences about a family of L linear contrasts among the k population means. For a simultaneous coverage probability of (1-alpha), the optimal sample size is defined to be the smallest integer value n*m such that, simultaneously for all L confidence intervals, the width of the lth confidence interval will be no greater than tolerance 2deltal (l=1,2,...,L) with tolerance probability at least (1-gamma), treating the pooled sample variance S2p as a random variable. Using Scheffe's procedure as an illustration, comparisons are made to usual sample size methods that incorrectly ignore the stochastic nature of S2p. The latter approach can lead to serious underestimation of required sample sizes and hence to unacceptably low values of the actually tolerance probability (1-gamma'). Our approach guarantees a lower bound of [1-(alpha+gamma)] for the probability that the L confidence intervals will both cover the parametric functions of interest and also be sufficiently narrow. Recommendations are provided regarding the choices among the four multiple comparison procedures for sample size determination and inference-making.