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. 2022 Jul;56(1):110-120.
doi: 10.1002/jmri.27999. Epub 2021 Nov 18.

Diffusion Kurtosis MR Imaging of Invasive Breast Cancer: Correlations With Prognostic Factors and Molecular Subtypes

Han Sol Kang  1 , Jin You Kim  1 , Jin Joo Kim  1 , Suk Kim  1 , Nam Kyung Lee  1 , Ji Won Lee  1 , Hie Bum Suh  1 , Lee Hwangbo  1 , Yohan Son  2 , Robert Grimm  3
Affiliations

Diffusion Kurtosis MR Imaging of Invasive Breast Cancer: Correlations With Prognostic Factors and Molecular Subtypes

Han Sol Kang et al. J Magn Reson Imaging. 2022 Jul.

Abstract

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.

Keywords: breast neoplasms; diffusion magnetic resonance imaging classification; immunologic subtyping; magnetic resonance imaging.

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