Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors
- 28 November 2015
- journal article
- research article
- Published by Springer Nature in European Radiology
- Vol. 26 (8) , 2547-2558
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.Keywords
This publication has 64 references indexed in Scilit:
- Cancer heterogeneity: implications for targeted therapeuticsBritish Journal of Cancer, 2013
- Quantitative analysis of diffusion-weighted magnetic resonance imaging in malignant breast lesions using different b value combinationsEuropean Radiology, 2012
- Stromal Estrogen Receptor-α Promotes Tumor Growth by Normalizing an Increased AngiogenesisCancer Research, 2012
- In Vivo Assessment of Ductal Carcinoma in Situ Grade: A Model Incorporating Dynamic Contrast-enhanced and Diffusion-weighted Breast MR Imaging ParametersRadiology, 2012
- Heterogeneity in breast cancerJournal of Clinical Investigation, 2011
- Intratumor Heterogeneity in Evolutionary Models of Tumor ProgressionGenetics, 2011
- Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast‐enhanced kineticsMagnetic Resonance in Medicine, 2011
- Deconstructing the molecular portraits of breast cancerMolecular Oncology, 2010
- Preoperative concurrent paclitaxel-radiation in locally advanced breast cancer: pathologic response correlates with five-year overall survivalBreast Cancer Research and Treatment, 2010
- Estimating the Dimension of a ModelThe Annals of Statistics, 1978