Comparison of Biexponential and Monoexponential Model of Diffusion-Weighted Imaging for Distinguishing between Common Renal Cell Carcinoma and Fat Poor Angiomyolipoma.
10.3348/kjr.2016.17.6.853
- Author:
Yuqin DING
1
;
Mengsu ZENG
;
Shengxiang RAO
;
Caizhong CHEN
;
Caixia FU
;
Jianjun ZHOU
Author Information
1. Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai 200032, China. zhoujianjunzs@126.com
- Publication Type:Original Article
- Keywords:
Intravoxel incoherent motion;
Diffusion-weighted imaging;
DWI;
Renal cell carcinoma;
Angiomyolipoma
- MeSH:
Angiomyolipoma*;
Area Under Curve;
Carcinoma, Renal Cell*;
Cohort Studies;
Diffusion;
Diffusion Magnetic Resonance Imaging;
Humans;
Magnetic Resonance Imaging;
Perfusion;
ROC Curve;
Sensitivity and Specificity
- From:Korean Journal of Radiology
2016;17(6):853-863
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: To compare the diagnostic accuracy of intravoxel incoherent motion (IVIM)-derived parameters and apparent diffusion coefficient (ADC) in distinguishing between renal cell carcinoma (RCC) and fat poor angiomyolipoma (AML). MATERIALS AND METHODS: Eighty-three patients with pathologically confirmed renal tumors were included in the study. All patients underwent renal 1.5T MRI, including IVIM protocol with 8 b values (0–800 s/mm²). The ADC, diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated. One-way ANOVA was used for comparing ADC and IVIM-derived parameters among clear cell RCC (ccRCC), non-ccRCC and fat poor AML. The diagnostic performance of these parameters was evaluated by using receiver operating characteristic (ROC) analysis. RESULTS: The ADC were significantly greater in ccRCCs than that of non-ccRCCs and fat poor AMLs (each p < 0.010, respectively). The D and D* among the three groups were significantly different (all p < 0.050). The f of non-ccRCCs were less than that of ccRCCs and fat poor AMLs (each p < 0.050, respectively). In ROC analysis, ADC and D showed similar area under the ROC curve (AUC) values (AUC = 0.955 and 0.964, respectively, p = 0.589) in distinguishing between ccRCCs and fat poor AMLs. The combination of D > 0.97 × 10⁻³ mm²/s, D* < 28.03 × 10⁻³ mm²/s, and f < 13.61% maximized the diagnostic sensitivity for distinguishing non-ccRCCs from fat poor AMLs. The final estimates of AUC (95% confidence interval), sensitivity, specificity, positive predictive value, negative predictive value and accuracy for the entire cohort were 0.875 (0.719–0.962), 100% (23/23), 75% (9/12), 88.5% (23/26), 100% (9/9), and 91.4% (32/35), respectively. CONCLUSION: The ADC and D showed similar diagnostic accuracy in distinguishing between ccRCCs and fat poor AMLs. The IVIM-derived parameters were better than ADC in discriminating non-ccRCCs from fat poor AMLs.
