Rationale and Objectives
The objective of this study was to compare the performance of diffusion kurtosis tensor imaging and diffusion-weighted imaging in the characterization of clear cell renal cell carcinoma (ccRCC) and their correlations with tumor histopathology.
Materials and Methods
Ninety-one patients diagnosed with ccRCC who underwent diffusion kurtosis tensor imaging were included in this study. Fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, mean kurtosis (MK), radial kurtosis (Krad), and axial kurtosis (Kax) data were produced. A nuclear grade of 1–4 (G1–4) was assigned for each case based on the Fuhrman grading system, whereas tumor histopathology was characterized by the nuclear-to-cytoplasm ratio, the cell nuclei count, and the cell volume fraction.
Results
All of the metric values except for Kax and fractional anisotropy could be used to discriminate G1 vs G3, G1 vs G4, G2 vs G3, and G2 vs G4, whereas MK and Kax could be used to discriminate G3 vs G4 ( P < 0.05). Moreover, the MK and Krad values exhibited better performance in differentiating G2 from G3 ( P < 0.04 compared to the other metrics). The nuclear-to-cytoplasm ratio was positively correlated with the MK, Krad, and Kax values ( P < 0.001) and negatively correlated with the mean diffusivity, radial diffusivity, and axial diffusivity values ( P < 0.001), whereas the cell volume fraction and the cell nuclei count did not correlate with any metric examined.
Conclusion
The kurtosis metrics were superior to the diffusion metrics in grading ccRCC.
Introduction
Renal cell carcinoma (RCC) is the most lethal of the urologic malignancies and comprises various subtypes, among which clear cell renal cell carcinoma (ccRCC) accounts for the majority (70%). Different ccRCC grades exhibit diverse biological behaviors and variable clinical outcomes . Meanwhile, minimally invasive techniques, such as percutaneous radiofrequency, cryoablation, microwave therapy, and high-intensity focused ultrasound ablation, have been suggested as feasible alternatives to the surgical treatment of RCC . Accurately identifying the tumor grade in ccRCC by magnetic resonance imaging (MRI) would provide a potential advantage in treatment decisions in the future, as well as a useful modality for related research fields. MRI is a noninvasive technique used to diagnose renal tumors. In particular, diffusion-weighted imaging (DWI) can be used to further characterize biological tissue structures by measuring the diffusion of water molecules . Previous studies on renal tumors have shown that the apparent diffusion coefficient (ADC) value derived from DWI signals may provide a quantitative method for differentiating benign from malignant tumors and identifying the histopathologic degree of ccRCC . However, the performance of DWI is limited because of the confounding overlap of broad ADC ranges .
Conventional DWI assumes that water diffusion has a Gaussian distribution. However, because of the microstructural complexity of tissues and cells, including cell membranes, intracellular organelles, and water compartments, the diffusion of water molecules tends to deviate from a Gaussian distribution , thereby limiting the effectiveness of conventional DWI. Kurtosis is a dimensionless statistical metric for quantifying the non-Gaussianity of an arbitrary probability distribution , and diffusion kurtosis tensor (DKT) imaging is an extension of diffusion tensor imaging (DTI) that quantifies non-Gaussian water diffusion by acquiring data for at least two nonzero diffusion gradient factors ( b values) in at least 15 independent directions. The kurtosis metrics (ie, the mean kurtosis [MK], axial kurtosis [Kax], and radial kurtosis [Krad]) and the conventional diffusion metrics (ie, the mean diffusivity [MD], axial diffusivity [Dax], radial diffusivity [Drad], and fractional anisotropy [FA]) can be derived from DKT imaging data simultaneously. The Kax and the Krad are parallel and perpendicular to the main direction of diffusion, respectively, whereas the MK is the average kurtosis over all diffusion directions . Accordingly, DKT imaging may be more suitable than DWI and DTI for evaluating microstructural changes in tissues. DKT imaging has offered numerous diagnostic possibilities in the liver, kidneys, and prostate gland . Although a recently published study indicated that it is feasible to use diffusion kurtosis imaging (DKI) to assess the ccRCC grade , that particular study did not use a tensor-based method, which precludes the evaluation of the Krad and the Kax. The value of DKT imaging in the assessment of ccRCC has not yet been comprehensively reported. The purpose of our study was to explore the value of the diffusion and kurtosis metrics in the characterization of ccRCC with different grades and to correlate them with the cytoarchitectural differences in tumor grades.
Materials and Methods
Patients
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MRI Protocol
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TABLE 1
Protocols of Magnetic Resonance Sequences
Sequence T1-Weighted In-phase or Opposed-phase Image T2-Weighted Imaging T2-Weighted Imaging Diffusion Tensor Imaging Contrast-enhanced Imaging Scan plane Axal Axial Coronal Axial Axial TR/TE 180/2.1, 4.4 2308/79 1500/85 3300/57 6/2 FOV (cm) 38~42 38~42 42 38~42 38~42 Thickness (mm) 5 5 4 5 2.5 Spacing (mm) 1 1 0.4 1 0 Matrix 512 × 512 512 × 512 512 × 512 128 × 128 512 × 512 NEX 1 3 1 2 1 Bandwidth 62.5 44 83.3 125 125 Fat saturation None Yes None Yes Yes Flip angle 80 90 90 90 15 Other_b_ Values: 0, 300, 600
Number of directions: 32
FOV, field of view; NEX, number of excitations; TE, echo time; TR, repetition time.
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Imaging Analysis
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Histologic Results
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Statistical Analysis
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Results
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TABLE 2
Diffusion and Kurtosis Metrics of Clear Cell Renal Cell Carcinoma and Normal Renal Parenchyma
G1 G2 G3 G4 All Cortex Medulla Interobserver and Intraobserver Agreement MD 2.80 ± 0.55 2.75 ± 0.49 1.92 ± 0.70 1.58 ± 0.50 2.47 ± 0.72 3.55 ± 0.57 2.78 ± 0.37 0.903/0.895 MK 0.90 ± 0.31 0.97 ± 0.30 1.53 ± 0.39 1.89 ± 0.42 1.17 ± 0.48 0.70 ± 0.14 0.89 ± 0.24 0.860/0.869 Krad 0.81 ± 0.29 0.94 ± 0.31 1.50 ± 0.32 1.73 ± 0.50 1.10 ± 0.46 0.67 ± 0.20 0.93 ± 0.36 0.901/0.874 Kax 1.03 ± 0.27 1.13 ± 0.31 1.33 ± 0.42 1.79 ± 0.31 1.22 ± 0.39 0.70 ± 0.15 0.84 ± 0.18 0.983/0.905 Drad 2.41 ± .049 2.39 ± 0.45 1.45 ± 0.64 1.16 ± 0.44 2.08 ± 0.70 3.02 ± 0.51 2.23 ± 0.35 0.966/0.895 Dax 3.60 ± 0.71 3.49 ± 0.61 2.75 ± 0.88 2.33 ± 0.67 3.35 ± 0.82 4.62 ± 0.79 3.87 ± 0.70 0.936/0.874 FA 0.30 ± 0.07 0.29 ± 0.17 0.32 ± 0.09 0.30 ± 0.10 0.30 ± 0.19 0.28 ± 0.07 0.35 ± 0.09 0.910/0.866 N/C 0.24 ± 0.09 0.33 ± 0.11 0.54 ± 0.13 0.57 ± 0.10 0.37 ± 0.16 NA NA NA CNC 377.67 ± 191.38 397.54 ± 85.710 375.17 ± 120.88 403.55 ± 115.80 388.53 ± 129.19 NA NA NA CVF 0.65 ± 0.22 0.63 ± 0.18 0.61 ± 0.14 0.67 ± 0.14 0.63 ± 0.18 NA NA NA
CNC, cell nuclei count; CVF, cell volume fraction; Dax, axial diffusivity; Drad, radial diffusivity; FA, fractional anisotropy; Kax, axial kurtosis; Krad, radial kurtosis; MD, mean diffusivity; MK, mean kurtosis; NA, not applicable; N/C, nuclear-to-cytoplasm ratio.
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TABLE 3
Comparative Analysis of Diffusion and Kurtosis Metrics Between Tumor and Normal Parenchyma and Between Tumors with Different Grades
MD MK Krad Kax Drad Dax FA Cortex vs medulla
AUC 0.880 0.766 0.710 0.696 0.887 0.824 0.712P Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 ccRCC vs cortex
AUC 0.910 0.842 0.818 0.924 0.893 0.899 0.538P Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.379 ccRCC vs medulla
AUC 0.587 0.661 0.616 0.819 0.521 0.707 0.681P Value 0.043 <0.001 0.007 <0.001 0.617 <0.001 <0.001 ccRCC (G1 vs G2)
AUC 0.535 0.585 0.634 0.640 0.519 0.503 0.636P Value 0.640 0.258 0.064 0.077 0.966 0.799 0.072 ccRCC (G1 vs G3)
AUC 0.846 0.895 0.946 0.686 0.870 0.806 0.581P Value <0.001 <0.001 <0.001 0.044 0.001 0.001 0.383 ccRCC (G1 vs G4)
AUC 0.954 0.981 0.981 0.968 0.958 0.889 0.579P Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.492 ccRCC (G2 vs G3)
AUC 0.799 0.898 0.904 0.608 0.821 0.736 0.662P Value <0.001 <0.001 <0.001 0.203 <0.001 0.005 0.055 ccRCC (G2 vs G4)
AUC 0.919 0.967 0.950 0.944 0.953 0.865 0.617P Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.279 ccRCC (G3 vs G4)
AUC 0.639 0.796 0.650 0.839 0.683 0.589 0.528P Value 0.231 0.022 0.195 0.010 0.114 0.443 0.811
AUC, area under curve; ccRCC, clear cell renal cell carcinoma; Dax, axial diffusivity; Drad, radial diffusivity; FA, fractional anisotropy; Kax, axial kurtosis; Krad, radial kurtosis; MD, mean diffusivity; MK, mean kurtosis.
TABLE 4
The Correlation of the Diffusion and Kurtosis Metrics with Tumor Histopathology
MD MK Krad Kax Drad Dax FA N/C_r_ −0.474 0.543 0.560 0.438 −0.507 −0.433 −0.092P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.387 CNC_r_ −0.074 0.022 0.026 −0.019 −0.075 −0.073 −0.081P 0.487 0.834 0.804 0.862 0.483 0.490 0.447 CVF_r_ 0.039 −0.050 0.005 −0.053 0.045 0.014 −0.066P 0.715 0.637 0.961 0.615 0.669 0.892 0.534
CNC, cell nuclei count; CVF, cell volume fraction; Dax, axial diffusivity; Drad, radial diffusivity; FA, fractional anisotropy; Kax, axial kurtosis; Krad, radial kurtosis; MD, mean diffusivity; MK, mean kurtosis; N/C, nuclear-to-cytoplasm ratio.
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Discussion
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Conclusion
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