Volume measurement of liver metastases using multidetector computed tomography: comparison of lesion diameter and volume segmentation - a phantom study

Rofo. 2010 Dec;182(12):1082-90. doi: 10.1055/s-0029-1245814. Epub 2010 Nov 23.

Abstract

Purpose: To compare lesion volume determination by applying diameter measurement and three different segmentation algorithms at different slice thicknesses reconstructed from computed tomography (CT) of a phantom model for hepatic colorectal metastases.

Materials and methods: Based on CT attenuation measurements obtained retrospectively from 20 patients with colorectal liver metastases, a phantom model was designed with a sponge soaked with a dilution of contrast agent and 6 embedded polyamide spheres (diameter, 8 - 30 mm) to simulate the contrast behavior of liver metastases. CT scans were obtained and reconstructed at different slice thicknesses (0.625/1.25/2.5/3.75 mm; increment, 1). One observer performed software-aided volume determination using the maximum diameter, manual segmentation, seed point method, and threshold method six times for each lesion in a randomized order. Statistical analysis revealed the absolute and relative differences from the actual lesion volumes and the intraobserver differences as well as the influence of slice thickness for each method.

Results: The mean relative differences of the seed point method (1.2 - 5.9%) and manual segmentation (2.6 - 4.9%) were significantly lower than the threshold method (5.4 - 12.8%) and diameter measurement (12.3 - 18.5%; p < 0.01). Volume determination by manual segmentation and the seed point method benefited from the use of thin-slice CT datasets. The intraobserver variation was lowest when using the manual segmentation (1.5 - 3.3%) and the seed point method (2.2 - 3.9%; p < 0.001).

Conclusion: Manual segmentation and the seed point method for thin CT slices were the methods with the lowest volume differences and intraobserver variation.

Publication types

  • Comparative Study

MeSH terms

  • Colorectal Neoplasms / diagnostic imaging*
  • Humans
  • Image Enhancement / methods*
  • Imaging, Three-Dimensional / methods*
  • Liver / diagnostic imaging
  • Liver Neoplasms / diagnostic imaging*
  • Liver Neoplasms / secondary*
  • Observer Variation
  • Phantoms, Imaging*
  • Sensitivity and Specificity
  • Software
  • Tomography, Spiral Computed / methods*
  • Tumor Burden / physiology*