To assess the efficacy of diffusion kurtosis imaging (DKI) in differentiating low-grade from high-grade tumors and evaluating the aggressiveness of bladder cancer.
From January 2017 to July 2017, 35 patients (28 males, 7 females; mean age 63 ± 9 years) diagnosed with bladder cancer underwent diffusion-weighted imaging (DWI) with two types of DKI protocols: (1) multi-b value ranging from 0 to 2000 s/mm2 to obtain mean diffusivity/kurtosis (MDb/MKb) and (2) the tensor method with 32 directions with 3 b values (0, 1000, and 2000s/mm2) to obtain mean/axial/radial diffusivity (MDt/Da/Dr), mean/axial/radial kurtosis (MKt/Ka/Kr), and fractional anisotropy (FA) before radical cystectomy. Comparisons between the low- and high-grade groups, non-muscle-invasive bladder cancer (NMIBC), and muscle-invasive bladder cancer (MIBC) were performed with the areas under the receiver operating characteristic curves (AUCs).
The MKt and Kr values were significantly (p = 0.017 and p = 0.048) higher in patients with high-grade bladder tumors than in those with low-grade tumors. The MKt, Kr, and MKb values were significantly (p = 0.022, p = 0.000, and p = 0.044, respectively) higher in patients with MIBC than in those with NMIBC, while no significant differences (p > 0.05) were found in other values. The AUC of Kr (0.883) was the largest and was significantly higher than those of other metrics (all p < 0.05) for differentiating MIBC from NMIBC, with a sensitivity and specificity of 81.8% and 91.7%, respectively.
Kurtosis metrics performed better than diffusion metrics in differentiating MIBC from NMIBC, and directional kurtosis and Kr metrics may also have great potential in providing additional information regarding bladder cancer invasiveness.
• Kurtosis metrics performed better than diffusion metrics in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC). • Directional kurtosis can provide additional directional microstructural information regarding bladder cancer invasiveness.
European radiology. 2019 Jan 21 [Epub ahead of print]
Fang Wang, Hai-Ge Chen, Rui-Yun Zhang, Di Jin, Shuai-Shuai Xu, Guang-Yu Wu, Jian-Rong Xu
Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, No.1630, Dongfang road, Pudong, Shanghai, 200127, China., Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China., Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, No.1630, Dongfang road, Pudong, Shanghai, 200127, China. ., Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, No.1630, Dongfang road, Pudong, Shanghai, 200127, China. .