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Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors

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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.

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Acknowledgments

The scientific guarantor of this publication is Eric E. Sigmund, Ph.D. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise (James S. Babb). Institutional review board approval was obtained. Written informed consent was waived by the institutional review board. Some study subjects or cohorts have been previously reported in

• Sigmund EE, Cho GY, Kim S et al (2011) Intravoxel incoherent motion imaging of tumour microenvironment in locally advanced breast cancer. Magn Reson Med 65:1437–1447

• Cho GY, Moy L, Kim SG, Klautau Leite AP, Baete SH, Babb JS, Sodickson DK, Sigmund EE (2015) Comparison of contrast enhancement and diffusion-weighted magnetic resonance imaging in healthy and cancerous breast tissue. Eur J Radiol 84(10):1888–93. doi: 10.1016/j.ejrad.2015.06.023. Epub 2015 Jul 2.

• Cho GY, Moy L, Zhang JL et al (2014) Comparison of fitting methods and b-value sampling strategies for intravoxel incoherent motion in breast cancer. Magn Reson Med. 10.1002/mrm.25484

Methodology: retrospective, diagnostic or prognostic study, performed at one institution.

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Authors and Affiliations

  1. Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Ave. 4th Floor, New York City, NY, 10016, USA

    Gene Young Cho, Linda Moy, Sungheon G. Kim, Steven H. Baete, James S. Babb, Daniel K. Sodickson & Eric E. Sigmund

  2. Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, 10016, USA

    Gene Young Cho, Linda Moy, Sungheon G. Kim, Steven H. Baete, James S. Babb, Daniel K. Sodickson & Eric E. Sigmund

  3. New York University Langone Medical Center - Cancer Institute, New York, NY, 10016, USA

    Melanie Moccaldi

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  1. Gene Young Cho
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Cho, G.Y., Moy, L., Kim, S.G. et al. Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors. Eur Radiol 26, 2547–2558 (2016). https://doi.org/10.1007/s00330-015-4087-3

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