Prevention of vertical HIV-1 transmission.
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Biomedical subjects
Publications and source records attributed to E Gurewitsch.
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Sonographic image density represents tissue echogenicity, or the acoustic nature of scanned tissue. It has the potential to distinguish normal from abnormal tissue. Humans are poor assessors of tissue echogenicity, yet their abilities have not been quantitatively compared to more objective methods. We compared the accuracy of image density differentiation by the human eye and by densitometry in the fetal liver model. A group of 60 observers was asked to compare the echogenicity of three pairs of images of a fetal liver. Twenty-three repeated the comparison several weeks later. Image density was measured by electro-optical densitometry. The two-tailed signed rank test was used to compare the observer's perceptions with the density values and the repeated observations with the original responses. The density of each fetal liver image in pair A was the same. Image B1 had a 12.3% lower density than image B2, and image C1 had a 6.3% greater density than image C2. Observers were accurate more often when comparing images with large density differences (pair B) than they were when comparing images with the same density (pair A) or with small density differences (pair C). Accuracy was not related to being medically qualified or from an obstetric or gynecological department. Intraobserver variation was not significant. We conclude that the human eye is extremely inaccurate at discerning differences in echogenicity when images have small or no differences in optical density. Densitometry is, therefore, indispensable for accurate image density assessment.
We studied the influence of changes in gain settings, log compression, persistence, preprocessing, and postprocessing on image density in the fetal liver model. Each parameter was studied while the others were held constant. The image density was objectively measured by electrooptical transmission densitometry using a transparent film output. Neither the persistence nor the preprocessing levels significantly changed image density. Postprocessing of sonographic images produced significant differences (p < 0.02) in mean image density of most of the various postprocessing curves and is a serious confounder of tissue echogenicity assessment. The data reconfirmed that there is a linear relationship (r = -0.94 to -0.997) between image density and gain setting. However, each log compression setting significantly changed (p < 0.0000001) this relationship, obviating possible image density calibration. Our data suggest that manipulation of image parameters by computed sonographic technology obviates accurate echogenicity assessment.
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