Comparison of biexponential and monoexponential DWI in evaluation of Fuhrman grading of clear cell renal cell carcinoma

Liu, Xiaohang; Yang, Xiaoqun

doi:10.5152/dir.2016.15519

Cited by 19 publications

(13 citation statements)

References 23 publications

(70 reference statements)

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“…D f and f, the other two important metrics in the biexponential model, are linked to perfusion and reflect the degree of tissue vascularity without the use of contrast agents. As for D f , its diagnostic value has always been controversial (131430). In our study, we did not find a significant difference between any subject subgroups for D f values.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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confidence: 99%

“…Intravoxel incoherent motion (IVIM) has been developed and utilized in neuroscience research because of its capability of extracting perfusion information from a diffusion sequence. [16][17][18] In a previous study among 55 pregnant women, the f value was suggested to be a suitable tool to reveal placental insufficiency and to identify risk of intrauterine growth retardation. 19 On the other hand, the reproducibility of IVIM MRI to examine microvascular perfusion and diffusion in the developing fetus depends greatly upon data quality, fetal and maternal movements, and fetal-specific image postprocessing.…”

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confidence: 99%

Fetal brain development at 25–39 weeks gestational age: A preliminary study using intravoxel incoherent motion diffusion‐weighted imaging

Yuan

Cui

et al. 2019

Magnetic Resonance Imaging

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Background The fetal brain developmental changes of water diffusivity and perfusion has not been extensively explored. Purpose/Hypothesis To evaluate the fetal brain developmental changes of water diffusivity and perfusion using intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI). Study Type Prospective. Population Seventy‐nine normal singleton fetuses were scanned without sedation of healthy pregnant women. Field Strength/Sequence 5 T MRI/T1/2‐weighted image and IVIM‐DWI. Assessment Pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were calculated in the frontal (FWM), temporal (TWM), parietal (PWM), and occipital white matter (OWM) as well as cerebellar hemisphere (CH), basal ganglia region (BGR), thalamus (TH), and pons using an IVIM model. Statistical Tests One‐way analysis of variable (ANOVA) followed by Bonferroni post‐hoc multiple comparison was employed to reveal the difference of IVIM parameters among the investigated brain regions. The linear and the nonlinear polynomial regression analyses were utilized to reveal the correlation between gestational age (GA) and IVIM parameters. Results There were significant differences in both D (F(7,623) = 96.64, P = 0.000) and f values (F(7,623) = 2.361, P = 0.0219), but not D* values among the varied brain regions. D values from TWM (r2 = 0.1402, P = 0.0002), PWM (r2 = 0.2245, P = 0.0002), OWM (r2 = 0.2519, P = 0.0002), CH (r2 = 0.2245, P = 0.0002), BGR (r2 = 0.3393, P = 0.0001), TH (r2 = 0.1259, P = 0.0001), and D* value from pons (r2 = 0.2206, P = 0.0002) were significantly correlated with GA using linear regression analysis. Quadratic regression analysis led to results similar to those using the linear regression model. Data Conclusion IVIM‐DWI parameters may indicate fetal brain developmental alterations but the conclusion is far from reached due to the not as high‐powered correlation between IVIM parameters and GA. Level of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:899–909.

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“…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.…”

Section: Discussionmentioning

confidence: 72%

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

Luo

Gao

et al. 2021

Cancer Imaging

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Background To probe the feasibility and reproducibility of diffusion kurtosis tensor imaging (DKTI) in renal cell carcinoma (RCC) and to apply DKTI in distinguishing the subtypes of RCC and the grades of clear cell RCC (CCRCC). Methods Thirty-eight patients with pathologically confirmed RCCs [CCRCC for 30 tumors, papillary RCC (PRCC) for 5 tumors and chromophobic RCC (CRCC) for 3 tumors] were involved in the study. Diffusion kurtosis tensor MR imaging were performed with 3 b-values (0, 500, 1000s/mm2) and 30 diffusion directions. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr) values and mean diffusity (MD) for RCC and contralateral normal parenchyma were acquired. The inter-observer agreements of all DKTI metrics of contralateral renal cortex and medulla were evaluated using Bland-Altman plots. Statistical comparisons with DKTI metrics of 3 RCC subtypes and between low-grade (Furman grade I ~ II, 22 cases) and high-grade (Furman grade III ~ IV, 8 cases) CCRCC were performed with ANOVA test and Student t test separately. Receiver operating characteristic (ROC) curve analyses were used to compare the diagnostic efficacy of DKTI metrics for predicting nuclear grades of CCRCC. Correlations between DKTI metrics and nuclear grades were also evaluated with Spearman correlation analysis. Results Inter-observer measurements for each metric showed great reproducibility with excellent ICCs ranging from 0.81 to 0.87. There were significant differences between the DKTI metrics of RCCs and contralateral renal parenchyma, also among the subtypes of RCC. MK and Ka values of CRCC were significantly higher than those of CCRCC and PRCC. Statistical difference of the MK, Ka, Kr and MD values were also obtained between CCRCC with high- and low-grades. MK values were more effective for distinguishing between low- and high- grade CCRCC (area under the ROC curve: 0.949). A threshold value of 0.851 permitted distinction with high sensitivity (90.9%) and specificity (87.5%). Conclusion Our preliminary results suggest a possible role of DKTI in differentiating CRCC from CCRCC and PRCC. MK, the principle DKTI metric might be a surrogate biomarker to predict nuclear grades of CCRCC. Trial registration ChiCTC, ChiCTR-DOD-17010833, Registered 10 March, 2017, retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=17559.

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Comparison of biexponential and monoexponential DWI in evaluation of Fuhrman grading of clear cell renal cell carcinoma

Cited by 19 publications

References 23 publications

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

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

Fetal brain development at 25–39 weeks gestational age: A preliminary study using intravoxel incoherent motion diffusion‐weighted imaging

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

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