Comparison of Monoexponential, Biexponential, Stretched-Exponential, and Kurtosis Models of Diffusion-Weighted Imaging in Differentiation of Renal Solid Masses

Abstract

Objective To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [D f ], slow diffusion coefficient [D s ], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses. Materials and Methods A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30–69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. Results Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, D s , and MK showed significant differences between benign and malignant lesions ( p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) ( p < 0.05). α was significantly lower in the benign group than in the malignant group ( p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC ( p < 0.05) except D f and α ( p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) ( p > 0.05). Conclusion Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

Amide Proton Transfer‐Weighted Imaging and Multiple Models Diffusion‐Weighted Imaging Facilitates Preoperative Risk Stratification of Early‐Stage Endometrial Carcinoma

“…However, Liu et al showed that the D * of malignant breast lesions was significantly lower than that of benign lesions 33 . In addition, other studies, including the current one, have suggested that the D * value cannot effectively distinguish between different malignant lesions 11,31 . We believe that the structural differences between different tumors may be an important reason for the above results.…”

Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer

“…[10][11][12] The SEM DWI has been applied to malignant tumors, such as brain, kidney, cervix, and ovary tumors. [13][14][15][16][17] Only a few studies have demonstrated that SEM DWI could be useful in assessing PCa aggressiveness and for detecting PCa. 6,9,11,12 However, few studies have reported the results following the evaluation of PCa using histogram analysis of SEM DWI.…”

Application of diffusion kurtosis tensor MR imaging in characterization of renal cell carcinomas with different pathological types and grades

“…High-grade CCRCC were characterized by higher cellularity, more nuclear atypia, higher pleomorphism, and more vascular hyperplasia and necrosis [ 36 ], which lead to increased complexity of the intracellular microenvironment. Perfusion in high-grade CCRCC are also increased with predominant blood volume and tumor vascularization, verified by the studies performed with IVIM [ 31 , 37 ] and dynamic contrast MR [ 38 ]. MK can be a surrogate biomarker for predicting nuclear grade of CCRCC.…”

“…As patients with CRCC has better prognosis than those with CCRCC and PRCC [ 30 ], distinguishing CRCC from the other 2 common subtypes of RCC before surgery is essential for choosing an appropriate strategy and predicting the prognosis. Zhang et al [ 31 ] and Ding et al [ 28 ] found that MK value of CCRCC (0.62, 0.68, respectively) was lower than non-CCRCC (0.9, 0.88, respectively). As they all include CRCC and PRCC as one group (non-CCRCC), it could not be determined whether CRCC owed highest MK values among 3 subtypes of RCC.…”