Measurements and detection of abdominal aortic aneurysm growth: Accuracy and reproducibility of a segmentation software

Eur J Radiol. 2012 Aug;81(8):1688-94. doi: 10.1016/j.ejrad.2011.04.044. Epub 2011 May 20.

Abstract

Purpose: To validate the reproducibility and accuracy of a software dedicated to measure abdominal aortic aneurysm (AAA) diameter, volume and growth over time.

Materials and methods: A software enabling AAA segmentation, diameter and volume measurement on computed tomography angiography (CTA) was tested. Validation was conducted in 28 patients with an AAA having 2 consecutive CTA examinations. The segmentation was performed twice by a senior radiologist and once by 3 medical students on all 56 CTAs. Intra and inter-observer reproducibility of D-max and volumes values were calculated by intraclass correlation coefficient (ICC). Systematic errors were evaluated by Bland-Altman analysis. Differences in D-max and volume growth were compared with paired Student's t-tests.

Results: Mean D-max and volume were 49.6±6.2mm and 117.2±36.2ml for baseline and 53.6±7.9mm and 139.6±56.3ml for follow-up studies. Volume growth (17.3%) was higher than D-max progression (8.0%) between baseline and follow-up examinations (p<.0001). For the senior radiologist, intra-observer ICC of D-max and volume measurements were respectively estimated at 0.997 (≥0.991) and 1.000 (≥0.999). Overall inter-observer ICC of D-max and volume measurements were respectively estimated at 0.995 (0.990-0.997) and 0.999 (>0.999). Bland-Altman analysis showed excellent inter-reader agreement with a repeatability coefficient <3mm for D-max, <7% for relative D-max growth, <6ml for volume and <6% for relative volume growth.

Conclusion: Software AAA volume measurements were more sensitive than AAA D-max to detect AAA growth while providing an equivalent and high reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms
  • Angiography / methods*
  • Aortic Aneurysm, Abdominal / diagnostic imaging*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Observer Variation
  • Pattern Recognition, Automated / methods*
  • Radiographic Image Enhancement / methods
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Radiography, Abdominal / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Software Validation
  • Software*
  • Tomography, X-Ray Computed / methods*