Background and purpose: In recent years

the development and application of diffusion-weighted imaging (DWI) have greatly improved the specificity of magnetic resonance (MR). The intravoxel incoherent motion (IVIM) model and the diffusion kurtosis imaging (DKI) model

as new technologies

have made some progress in clinical research. This study aimed to evaluate the diagnostic value of mono-exponential

IVIM and DKI models of DWI in characterizing benign and malignant breast lesions. Methods: Patients diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 or higher using mammography or ultrasonography were seleted for breast MR imaging. The exclusion criteria included: ① Patients who underwent core-needle biopsy or preoperative chemotherapy or surgery; ② Patients whose MR images had substantial motion artifacts. Turbo inversion recovery magnitude (TIRM)

multi-b DWI (readout-segmented echo-planar imaging) and dynamic contrast-enhanced T1WI were performed in all patients. Region of interests (ROIs) were drawn on apparent diffusion coefficient (D

ADC

) maps on the slice with the largest tumor area using b=50 and 1 000 s/mm

2

avoiding necrotic or cystic parts. The parameters of mono-exponential (D

ADC

)

IVIM [molecular diffusion coeffic

ient (D

DT

)

perfusion-related diffusion coefficient (D

*

) and perfusion fraction (f)

]

and diffusion kurtosis model [diffusivity coefficient (D

DK

)

kurtosis coefficient (K)

]

were measured by two radiologists. The difference in the parameters between malignant tumors and benign lesions was analyzed by independent sample t test. Receiver operating characteristic (ROC) curve was performed to compare the diagnostic value of different parameters based on the area under curve (AUC). Z test was performed to compare the difference of each AUC. Results: Eighty patients (83 lesions) were included in our study

and there were 38 breast benign lesions and 45 malignant lesions. D

ADC

D

DT

K and D

DK

values were all statistically significant for the differential diagnosis of malignant and benign breast lesions (P0.05). The optimal threshold values were D

ADC

1.08 ×10

-3

mm

2

/s

D

DT

value 1.06×10

-3

mm

2

/s

K value 0.756 and D

DK

value 1.36×10

-3

mm

2

/s. The D

*

and f values between benign and malignant lesions had a large degree of overlap

and the difference was not statistically significant (P＞0.05). The ROC curve area showed that the AUC of K and D

DT

values in differential diagnosis of benign and malignant breast lesions were the highest

0.956 and 0.947

respectively. The sensitivity and specificity of K value were 91.1% and 89.5%. The sensitivity and specificity of D

DT

value were 93.3% and 84.2%. The AUC of D

ADC

and D

DK

value were 0.933 and 0.923

respectively. The sensitivity and specificity of D

ADC

value were 88.9% and 84.2%. The sensitivity and specificity of D

DK

value were 91.1% and 84.2%. Finally

the AUC of D

ADC

D

DT

K and D

DK

values in the differential diagnosis of benign and malignant breast lesions were not statistically significant (P＞0.05). Conclusion:

The three models all had good performance in differential diagnosis of benign and malignant breast lesions. IVIM and DKI showed higher AUC

but the AUC had no statistically significant difference among all models. The mono-exponential model had good clinical value with the advantages of short detection time and easy postprocessing.