The liver is a common site of metastatic disease. Colorectal liver metastases (CLM) alone is diagnosed in approximately 50,000 patients each year in the United States. Treatment for liver metastases is monitored according to the size and number of the hepatic metastases visualized with contrast-enhanced computed tomography (CT). In routine clinical practice, lesion size is assessed according to uni- or bi-dimensional criteria. However, measurements made using these criteria are subject to inter-observer variability and to the inherent limitations of dimensional measurements to reflect volume. Thus, an investigation was conducted of computational methods for measurement of the area and volume of colorectal metastases to the liver. The study included CT images of the liver from five patients with a history of colorectal cancer. The image data included a total of ten hypo-attenuating lesions ranging in size from 0.4 to 79 cc. The lesions were segmented by manual contouring, by the 2D Watershed algorithm, by an active contour initialized by manual contouring and by a dual-scale active contour initialized with an ellipse. Each method is interactive and was applied two times to each image of each lesion (36 image slices in total) to determine the reproducibility of area and volume measurements. The Watershed algorithm was ineffective since it produced gross segmentation errors on a majority of the lesion slices while the active contour with initialization by manual contouring produced no significant improvement in reproducibility. The average difference between the first and second measurements of lesion areas by the multiresolution active contour was slightly less than for manual measurements (0.53/spl plusmn/0.83 and 0.58/spl plusmn/0.60 cm/sup 2/) but the difference was not statistically significant. However, area measurements by the dual-scale active contour had less variability in a greater number of slices than did manual contouring (p=0.00003). Greater variability ...