On measuring the change in size of pulmonary nodules

Anthony P. Reeves, Antoni B. Chan, David F. Yankelevitz, Claudia I. Henschke, Bryan Kressler, William J. Kostis

Research output: Contribution to journalArticlepeer-review

206 Scopus citations

Abstract

The pulmonary nodule is the most common manifestation of lung cancer, the most deadly of all cancers. Most small pulmonary nodules are benign, however, and currently the growth rate of the nodule provides for one of the most accurate noninvasive methods of determining malignancy. In this paper, we present methods for measuring the change in nodule size from two computed tomography image scans recorded at different times; from this size change the growth rate may be established. The impact of partial voxels for small nodules is evaluated and isotropic resampling is shown to improve measurement accuracy. Methods for nodule location and sizing, pleural segmentation, adaptive thresholding, image registration, and knowledge-based shape matching are presented. The latter three techniques provide for a significant improvement in volume change measurement accuracy by considering both image scans simultaneously. Improvements in segmentation are evaluated by measuring volume changes in benign or slow growing nodules. In the analysis of 50 nodules, the variance in percent volume change was reduced from 11.54% to 9.35% (p = 0.03) through the use of registration, adaptive thresholding, and knowledge-based shape matching.

Original languageEnglish
Pages (from-to)435-450
Number of pages16
JournalIEEE Transactions on Medical Imaging
Volume25
Issue number4
DOIs
StatePublished - Apr 2006
Externally publishedYes

Keywords

  • Computed tomography
  • Growth rate estimation
  • Image registration
  • Image segmentation
  • Pulmonary nodules
  • Rule-based segmentation.

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