Publication Type Academic Article
Authors Cho G, Moy L, Kim S, Baete S, Moccaldi M, Babb J, Sodickson D, Sigmund E
Journal Eur Radiol
Volume 26
Issue 8
Pagination 2547-58
Date Published 11/28/2015
ISSN 1432-1084
Keywords Biomarkers, Tumor, Breast, Breast Neoplasms, Diffusion Magnetic Resonance Imaging
Abstract PURPOSE: To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. MATERIALS AND METHODS: This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. RESULTS: The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. CONCLUSION: Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. KEY POINTS: • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.
DOI 10.1007/s00330-015-4087-3
PubMed ID 26615557
PubMed Central ID PMC4894831
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