PURPOSE: To determine the utility of multiparametric diffusion-weighted imaging (DWI) including monoexponential (apparent diffusion coefficient [ADC]), biexponential (Df , Ds , and f), stretched-exponential (distributed diffusion coefficient [DDC] and α), and kurtosis (mean diffusivity [MD] and mean kurtosis [MK]) models in the differentiation and characterization of breast lesions, and assess their associations with prognostic factors in invasive breast cancer. MATERIALS AND METHODS: This study included 101 patients (44 benign and 57 malignant lesions) who underwent 3T breast multi-b-value DWI. Diffusion model selection was investigated in benign and malignant lesions using the Akaike information criteria (AIC). Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for statistical analysis. RESULTS: Goodness-of-fit analysis showed that most benign lesion voxels (50.5%) were preferred by the kurtosis model, and most malignant lesion voxels (51.2%) by the stretched-exponential model. All diffusion measures showed significant differences between benign and malignant lesions (P < 0.05), and between in situ and invasive cancers (P < 0.05) except MD (P = 0.103). There were no significant differences in areas under the ROC curves (AUCs) between ADC and non-monoexponential diffusion parameters (P > 0.05), except Df and α, whose AUCs were significantly lower than AUC of ADC for differentiating benign from malignant lesions (P = 0.03 and P < 0.01, respectively). In patients with invasive breast cancer, α was significantly correlated with tumor size (P = 0.007) and Ki-67 expression (P = 0.012), Df was significantly correlated with lymph node metastasis (P = 0.021) and Ki-67 expression (P = 0.042), and ADC, Ds , f, DDC, and MD were significantly correlated with estrogen receptor status (all P < 0.05). CONCLUSION: Multiparametric DWI shows relationships with pathologic outcomes and prognostic factors of breast lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:740-750.
PURPOSE: To determine the utility of multiparametric diffusion-weighted imaging (DWI) including monoexponential (apparent diffusion coefficient [ADC]), biexponential (Df , Ds , and f), stretched-exponential (distributed diffusion coefficient [DDC] and α), and kurtosis (mean diffusivity [MD] and mean kurtosis [MK]) models in the differentiation and characterization of breast lesions, and assess their associations with prognostic factors in invasive breast cancer. MATERIALS AND METHODS: This study included 101 patients (44 benign and 57 malignant lesions) who underwent 3T breast multi-b-value DWI. Diffusion model selection was investigated in benign and malignant lesions using the Akaike information criteria (AIC). Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for statistical analysis. RESULTS: Goodness-of-fit analysis showed that most benign lesion voxels (50.5%) were preferred by the kurtosis model, and most malignant lesion voxels (51.2%) by the stretched-exponential model. All diffusion measures showed significant differences between benign and malignant lesions (P < 0.05), and between in situ and invasive cancers (P < 0.05) except MD (P = 0.103). There were no significant differences in areas under the ROC curves (AUCs) between ADC and non-monoexponential diffusion parameters (P > 0.05), except Df and α, whose AUCs were significantly lower than AUC of ADC for differentiating benign from malignant lesions (P = 0.03 and P < 0.01, respectively). In patients with invasive breast cancer, α was significantly correlated with tumor size (P = 0.007) and Ki-67 expression (P = 0.012), Df was significantly correlated with lymph node metastasis (P = 0.021) and Ki-67 expression (P = 0.042), and ADC, Ds , f, DDC, and MD were significantly correlated with estrogen receptor status (all P < 0.05). CONCLUSION: Multiparametric DWI shows relationships with pathologic outcomes and prognostic factors of breast lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:740-750.
Authors: Alexey Surov; Jin You Kim; Marco Aiello; Wei Huang; Thomas E Yankeelov; Andreas Wienke; Maciej Pech Journal: In Vivo Date: 2022 Jan-Feb Impact factor: 2.155
Authors: Jin Joo Kim; Jin You Kim; Hie Bum Suh; Lee Hwangbo; Nam Kyung Lee; Suk Kim; Ji Won Lee; Ki Seok Choo; Kyung Jin Nam; Taewoo Kang; Heeseung Park Journal: Eur Radiol Date: 2021-08-04 Impact factor: 5.315