Quantitative differentiation of breast lesions based on three-dimensional morphology from magnetic resonance imaging

Karen H. Shahar, Meiyappan Solaiyappan, David A. Bluemke

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The purpose of this study was to develop geometric indices, based on morphologic measurements, of contrast-enhanced breast lesions using threedimensional magnetic resonance imaging (MRI) that can statistically differentiate between benign and malignant lesions. Methods: Thirty-three patients with abnormal mammograms were scanned using three-dimensional MRI. The lesion was then extracted from the volume data set using interactive volume-rendering software. From the extracted region of interest, the surface boundary corresponding to the lesion was extracted using an isosurface method. The boundary was represented as a triangular mesh, from which the surface area and volume enclosed by the surface were computed. The following variables were tested for discrimination ability between benign and malignant lesions: 1) the volume-tosurface area (V/S) ratio, 2) spherical shape index (SSI), and 3) resolution reduction for V/S and SSI values (100%, 16%, 8%, 4%, 2%, and 1% resolution). In addition, comparisons were made between the V/S and SSI values at 100% versus their reduced resolutions. Results: Thirty-three subjects (15 malignant tumors and 18 benign tumors) were studied. The SSI index (P = 0.0063) was a significant discriminator for malignancy. The V/S ratio (P = 0.9280) did not seem to be a useful variable in distinguishing benign and malignant masses. The V/S resolution comparisons (P > 0.5897) and the SSI resolution comparisons (P > 0.05) were also not useful discriminating variables. Conclusion: The SSI seems to be a useful factor in differentiating between benign and malignant lesions. Current clinical interpretation of breast lesions using MRI may be enhanced by the adjunctive use of this objective postanalysis method.

Original languageEnglish (US)
Pages (from-to)1047-1053
Number of pages7
JournalJournal of computer assisted tomography
Volume26
Issue number6
DOIs
StatePublished - Nov 1 2002

Keywords

  • Breast cancer
  • Image analysis
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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