Shiteng Suo

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging of Breast Cancer at 3.0 Tesla: Comparison of Different Curve-Fitting Methods

To compare three different curve‐fitting methods for intravoxel incoherent motion (IVIM) analysis in breast cancer.

Characterization of breast masses as benign or malignant at 3.0T MRI with whole‐lesion histogram analysis of the apparent diffusion coefficient

To investigate the utility of whole‐lesion apparent diffusion coefficient (ADC) histogram analysis in capturing breast lesion heterogeneity and determine which ADC metric may help best differentiate benign from malignant breast mass lesions at 3.0T magnetic resonance imaging (MRI).

Stroke assessment with intravoxel incoherent motion diffusion‐weighted MRI

Intravoxel incoherent motion (IVIM) diffusion‐weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non‐invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi‐b‐value diffusion‐weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b‐values to a simple mono‐exponential model. The IVIM‐derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow‐related parameter fD*, were calculated with the bi‐exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono‐exponential model using all b‐values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t‐test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi‐exponential behavior, and the IVIM model showed better goodness of fit than the mono‐exponential model with lower Akaike information criterion values. The paired Student t‐test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright

Apparent diffusion coefficient measurement in glioma: Influence of region‐of‐interest determination methods on apparent diffusion coefficient values, interobserver variability, time efficiency, and diagnostic ability

To compare four methods of region‐of‐interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in distinguishing low‐grade gliomas (LGGs) from high‐grade gliomas (HGGs).

Multiparametric diffusion-weighted imaging in breast lesions: Association with pathologic diagnosis and prognostic factors: DWI in Breast Lesions

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.

Multiparametric diffusion‐weighted imaging in breast lesions: Association with pathologic diagnosis and prognostic factors

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.

Preliminary study of diffusion kurtosis imaging in thyroid nodules and its histopathologic correlation

ObjectivesTo evaluate the utility of diffusion kurtosis imaging (DKI) of patients with thyroid nodules and to assess the probable correlation with histopathological factors.MethodsThe study included 58 consecutive patients with thyroid nodules who underwent magnetic resonance imaging (MRI) examination, including DKI and diffusion-weighted imaging (DWI). Histopathological analysis of paraffin sections included cell density and immunohistochemical analysis of Ki-67 and vascular endothelial growth factor (VEGF). Statistical analyses were performed using Student’s t-test, receiver operating characteristic (ROC) curves and Spearman’s correlation.ResultsThe diffusion parameters, cell density and immunohistochemistry analysis between malignant and benign lesions showed significant differences. The largest area under the ROC curve was acquired for the D value (AUC = 0.797). The highest sensitivity was shown with the use of K (threshold = 0.832, sensitivity = 0.917). The Ki-67 expression generally stayed low. A moderate correlation was found between ADC, D and cell density (r = −0.536, P = 0.000; r = −0.570, P = 0.000) and ADC, D and VEGF expression (r = −0.451, P = 0.000; r = −0.522, P = 0.000).ConclusionThe DKI-derived parameters D and K demonstrated an advantage compared to conventional DWI for thyroid lesion diagnosis. While the histopathological study indicated that the D value correlated better with extracellular change than the ADC value, the K value probably changed relative to the intracellular structure.Key Points• DWI and DKI parameters can identify PTC from benign thyroid nodules.• Correlations were found between diffusion parameters and histopathological analysis.• DKI obtains better diagnostic accuracy than conventional DWI.

Application of a Simplified Method for Estimating Perfusion Derived from Diffusion-Weighted MR Imaging in Glioma Grading

Purpose: To evaluate the feasibility of a simplified method based on diffusion-weighted imaging (DWI) acquired with three b-values to measure tissue perfusion linked to microcirculation, to validate it against from perfusion-related parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging, and to investigate its utility to differentiate low- from high-grade gliomas. Materials and Methods: The prospective study was approved by the local institutional review board and written informed consent was obtained from all patients. From May 2016 and May 2017, 50 patients confirmed with glioma were assessed with multi-b-value DWI and DCE MR imaging at 3.0 T. Besides conventional apparent diffusion coefficient (ADC0,1000) map, perfusion-related parametric maps for IVIM-derived perfusion fraction (f) and pseudodiffusion coefficient (D*), DCE MR imaging-derived pharmacokinetic metrics, including Ktrans, ve and vp, as well as a metric named simplified perfusion fraction (SPF), were generated. Correlation between perfusion-related parameters was analyzed by using the Spearman rank correlation. All imaging parameters were compared between the low-grade (n = 19) and high-grade (n = 31) groups by using the Mann-Whitney U test. The diagnostic performance for tumor grading was evaluated with receiver operating characteristic (ROC) analysis. Results: SPF showed strong correlation with IVIM-derived f and D* (ρ = 0.732 and 0.716, respectively; both P < 0.001). Compared with f, SPF was more correlated with DCE MR imaging-derived Ktrans (ρ = 0.607; P < 0.001) and vp (ρ = 0.397; P = 0.004). Among all parameters, SPF achieved the highest accuracy for differentiating low- from high-grade gliomas, with an area under the ROC curve value of 0.942, which was significantly higher than that of ADC0,1000 (P = 0.004). By using SPF as a discriminative index, the diagnostic sensitivity and specificity were 87.1% and 94.7%, respectively, at the optimal cut-off value of 19.26%. Conclusion: The simplified method to measure tissue perfusion based on DWI by using three b-values may be helpful to differentiate low- from high-grade gliomas. SPF may serve as a valuable alternative to measure tumor perfusion in gliomas in a noninvasive, convenient and efficient way.

Assessment of response to anti-angiogenic targeted therapy in pulmonary metastatic renal cell carcinoma: R2* value as a predictive biomarker

PurposeTo evaluate the utility of MR R2*-mapping and the optimal time-point for assessing the response of pulmonary metastatic renal cell carcinoma (mRCC) to anti-angiogenic targeted therapy (aATT).Materials and methodsThe exploration-sample group and the validation-sample group consisted of 22 and 16 patients. The parameters of MR R2*-mapping, including the R2* value at each time-point (R2*base, R2*1cyc and R2*2cyc) and change between different time-points (R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc), were evaluated with a receiver-operating-characteristic analysis, and a cut-off value derived from the clinical outcome was applied to the Kaplan-Meier method to assess the value of R2* mapping and Response-Evaluation-Criteria in Solid Tumours (RECIST) during treatment evaluation.ResultsThe inter-, intra-observer agreements and inter-scan consistency were excellent (p > 0.80). For the exploration-sample group, the areas under the curve for the parameters of MR R2* mapping were 0.55, 0.60, 0.83, 0.64, 0.88 and 0.83 for R2*base, R2*1cyc, R2*2cyc, R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc. For the validation-sample, R2*(2cyc-base)/base better predicted progression-free survival (p = 0.03) than RECIST and other R2* mapping parameters with a lower p value.ConclusionAssessing aATT outcome based on changes in the R2* value between baseline and second treatment is more accurate than assessment at other time-points and assessment based on the RECIST.Key Points• The inter-scan consistency of R2*-mapping in pulmonary mRCC are excellent.• The intra-/inter-observer agreement of R2* mapping in pulmonary mRCC are excellent.• Using changes in R2* value between baseline/after second-treatment is better than RECIST.• The choice of baseline/after second treatment is better than other time-points.

Evaluation of carotid plaque vulnerability in vivo: Correlation between dynamic contrast-enhanced MRI and MRI-modified AHA classification

To noninvasively monitor carotid plaque vulnerability by exploring the relationship between pharmacokinetic parameters (PPs) of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) and plaque types based on MRI‐modified American Heart Association (AHA) classification, as well as to assess the ability of PPs in discrimination between stable and vulnerable plaques suspected on MRI.