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

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

2021Journal of Magnetic Resonance Imaging33 citationsDOI

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: ) 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.

Topics & Concepts

KurtosisBreast cancerMedicineEffective diffusion coefficientMann–Whitney U testReceiver operating characteristicNuclear medicineDiffusion MRIBreast MRILogistic regressionMagnetic resonance imagingRadiologyOncologyCancerInternal medicineMammographyMathematicsStatisticsMRI in cancer diagnosisAdvanced Neuroimaging Techniques and ApplicationsRadiomics and Machine Learning in Medical Imaging