ObjectiveTo explore the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in preoperatively predicting human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer.MethodsIn this prospective study, 114 and 56 female patients with invasive ductal carcinoma were consecutively included in a derivation cohort and an independent validation cohort, respectively. Each patient was categorized into HER2-positive or HER2-negative groups based on the pathologic result. All patients underwent DSI and conventional MRI including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). The tumor size, type of the time-signal intensity curve (TIC) from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, and quantitative parameters derived from DSI, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) of primary tumors, were measured and compared between the HER2-positive and HER2-negative groups in the derivation cohort. Univariable and multivariable logistic regression analyses were used to determine the potential independent predictors of HER2 status. The discriminative ability of quantitative parameters was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort.ResultsIn the derivation cohort, the tumor size, TIC type, and ADC values did not differ between the HER2-positive and HER2-negative groups (p = 0.126–0.961). DSI quantitative parameters including axial kurtosis of DKI (DKI_AK), non-Gaussianity (MAP_NG), axial non-Gaussianity (MAP_NGAx), radial non-Gaussianity (MAP_NGRad), return-to-origin probability (MAP_RTOP), return-to-axis probability of MAP (MAP_RTAP), and intracellular volume fraction of NODDI (NODDI_ICVF) were lower in the HER2-positive group than in the HER2-negative group (p ≤ 0.001–0.035). DSI quantitative parameters including radial diffusivity (DTI_RD), mean diffusivity of DTI (DTI_MD), mean squared diffusion (MAP_MSD), and q-space inverse variance of MAP (MAP_QIV) were higher in the HER2-positive group than in the HER2-negative group (p = 0.016–0.049). The ROC analysis showed that the area under the curve (AUC) of ADC was 0.632 and 0.568, respectively, in the derivation and validation cohorts. The AUC values of DSI quantitative parameters ranged from 0.628 to 0.700 and from 0.673 to 0.721, respectively, in the derivation and validation cohorts. Logistic regression analysis showed that only NODDI_ICVF was an independent predictor of HER2 status (p = 0.001), with an AUC of 0.700 and 0.721, respectively, in the derivation and validation cohorts.ConclusionsDSI could be helpful for preoperative prediction of HER2, but DSI alone may not be sufficient in predicting HER2 status preoperatively in patients with breast cancer.

Background Diffusion-weighted imaging (DWI) was introduced into clinical use some years ago. However, its use in the diagnosis of cerebral schistosomiasis has not been reported. Purpose To investigate the ability of the apparent diffusion coefficient (ADC) value of DWI in the diagnosis of cerebral schistosomiasis, and to differentiate it from brain high-grade gliomas and metastasis. Material and Methods Conventional brain MRI with pre-contrast, post-contrast, and DWI was performed on 50 cases of cerebral schistosomiasis, high-grade glioma, and brain metastasis. The ADC values of the three lesions, the proximal and the distal perifocal edema were measured. In order to remove the individual difference effect of ADC values, relative ADC (rADC) values were calculated through dividing the ADC value of the lesion area by that of the contralateral normal white matter. rADC values were used to evaluate the differences among cerebral schistosomiasis, brain high-grade gliomas, and metastasis. Results rADC of cerebral schistosomiasis was significantly lower than rADC of brain metastasis ( P < 0.05), without any significant differences when compared with high-grade gliomas. rADC of proximal perifocal edema in cerebral schistosomiasis was significantly higher than in high-grade gliomas ( P < 0.010), but not different compared with brain metastasis. Conclusion DWI examination with ADC values of lesions and proximal perifocal edema might be helpful in the exact diagnosis of cerebral schistosomiasis.

This study explored the feasibility of applying multiple diffusion models based on the same diffusion spectrum imaging (DSI) data into preoperative prediction of HER-2 status in patients with breast cancer (BC). The results showed that some diffusion parameters can discriminate HER-2 positive BC patients, but apparent diffusion coefficient (ADC) based on conventional mono-exponential model can not. This study suggests that the simultaneously application of multiple diffusion models from DSI data is feasible for diagnosis of patients with BC, which has certain clinical value of preoperative prediction of HER-2 status and is worthy of further research.

Mean apparent propagator (MAP)-MRI establishes a robust analytical framework based on the random motion distribution of natural water molecules. This study investigated the application of quantitative parameters derived from MAP-MRI in patients with breast cancer and determined whether MAP-MRI can be adopted as a better method than apparent diffusion coefficient (ADC) from conventional DWI to preoperative diagnosis tumor-stromal ratio. The results suggested that quantitative assessment with MAP-MRI showed superior predictive performance than conventional DWI for preoperative diagnosis of tumor-stromal ratio in patients with breast cancer.