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Published on: December 15, 2014
Breast cancer recurrence risk prediction using whole-lesion histogram analysis with diffusion kurtosis imaging
1Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO.197 Ruijin Er Road, Shanghai 200025, China.
Aim:
To explore the role of whole-lesion histogram analysis on diffusion kurtosis imaging (DKI) for predicting breast cancer 21-gene expression profiles and recurrence scores (RSs).
Materials And Methods:
This retrospective study was approved by the institutional review board, and informed consent was waived. Seventy-two patients with breast cancer, who underwent genomic testing and DKI (b values: 0-2,800 s/mm2) were enrolled. Patients were divided into low-, intermediate-, and high-RS groups based on their genomic testing results. Diffusivity (D), kurtosis (K), total apparent diffusion coefficient (Total ADC), and ADC0-700 histogram parameters were calculated. Student's t-test, Wilcoxon signed-rank test, Jonckheere-Terpstra test, receiver operating characteristic curves, and Spearman's correlation were used for the statistical analysis.
Results:
Total ADC mean/30%/50%/70%, D mean/50%, K mean/30%/50%/70% showed significant differences among the low-, intermediate-, and high-RS groups (p ≤ 0.001, respectively). K50% had the strongest correlation with RSs (correlation coefficient, CC: 0.55). Furthermore, K50% was also correlated with the expression of gene PR, BCL2 and CEGP1 (CC: 0.45, -0.41, -0.41).
Conclusions:
Whole-lesion histogram analysis of DKI parameters can be a useful tool for RS prediction of breast cancer. K50% was found to be the most promising parameter for RS prediction.
