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Published on: December 15, 2014
Diffusion Kurtosis MR Imaging of Invasive Breast Cancer: Correlations With Prognostic Factors and Molecular Subtypes
Han Sol Kang1, Jin You Kim1, Jin Joo Kim1
1Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea.
Background:
The associations between diffusion kurtosis imaging (DKI)-derived parameters and clinical prognostic factors of breast cancer have not been fully evaluated; this knowledge may have implications for outcome prediction and treatment strategies.
Purpose:
To determine associations between quantitative diffusion parameters derived from DKI and diffusion-weighted imaging (DWI) and the prognostic factors and molecular subtypes of breast cancer.
Study Type:
Retrospective.
Population:
A total of 383 women (mean age, 53.8 years; range, 31-82 years) with breast cancer who underwent preoperative breast MRI including DKI and DWI.
Field Strength/Sequence:
A 3.0 T; DKI using a spin-echo echo-planar imaging (EPI) sequence (b values: 200, 500, 1000, 1500, and 2000 sec/mm2 ), DWI using a readout-segmented EPI sequence (b values: 0 and 1000 sec/mm2 ) and dynamic contrast-enhanced breast MRI.
Assessment:
Two radiologists (J.Y.K. and H.S.K. with 9 years and 1 year of experience in MRI, respectively) independently measured kurtosis, diffusivity, and apparent diffusion coefficient (ADC) values of breast cancer by manually placing a regions of interest within the lesion. Diffusion measures were compared according to nodal status, grade, and molecular subtypes.
Statistical Tests:
Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, receiver operating characteristic (ROC) analysis, and multivariate logistic regression analysis. (Statistical significance level of P < 0.05).
Results:
All diffusion measures showed significant differences according to axillary nodal status and histological grade. Kurtosis showed significant differences among molecular subtypes. The luminal subtype (median 1.163) showed a higher kurtosis value compared to the HER2-positive (median 0.962) or triple-negative subtypes (median 1.072). ROC analysis for differentiating HER2-positive from luminal subtypes revealed that kurtosis yielded the highest area under the curve of 0.781. In multivariate analyses, kurtosis remained a significant factor associated with differentiation between HER2-positive and luminal (odds ratio [OR] = 0.993), triple-negative and luminal (OR = 0.995), and HER2-positive and triple-negative subtypes (OR = 0.994).
Data Conclusion:
Quantitative diffusion parameters derived from DKI and DWI are associated with prognostic factors for breast cancer. Moreover, DKI-derived kurtosis can help distinguish between the molecular subtypes of breast cancer.
Evidence Level:
4 TECHNICAL EFFICACY: 3.
