Utility of intravoxel incoherent motion MRI derived parameters for prediction of aggressiveness in urothelial bladder carcinoma

Preoperative accurate judgment of aggressiveness is of great importance to determine treatment and prognosis of bladder cancers.

To evaluate the utility of IVIM-MRI parameters in predicting aggressiveness of bladder urothelial carcinoma.

Prospective.

Sixty-seven patients with bladder urothelial cancer.

3.0 T/T2WI and IVIM-MRI.

All cases were categorized in low-, intermediate-, or high-aggressiveness proposed by Kobayashi depending on the T stage and pathological grade. Images analysis and IVIM-derived parameters (apparent diffusion coefficient standard ADC, true diffusion coefficient D, pseudodiffusion coefficient D*, and perfusion fraction f) measurements were performed independently by two radiologists.

Comparisons of IVIM-derived parameters in different aggressiveness levels were performed using one-way analysis of variance or Kruskal-Wallis test. Binary logistic regression models were used to calculate predicted probability of combined parameters. Diagnostic performance of individual and combined parameters for distinguishing high- from low-/intermediate-aggressiveness was assessed by using the receiver operating characteristics (ROC) curve.

The ADC and D values differed significantly among low-, intermediate-, and high-aggressive urothelial bladder carcinoma, respectively (P < 0.05). The f value showed significant differences between low- and high-aggressive and between intermediate- and high-aggressive bladder carcinoma (P < 0.05). The best parameter for differentiating high- from low-/intermediate-aggressive urothelial bladder carcinoma was ADC value, with the area under ROC curve (AUC) and accuracy of 0.895 and 85.97%, followed by f and D values with AUCs of 0.873 and 0.862, respectively. The best combination of parameters was combined D and f values, with AUC and accuracy of 0.931 and 91.82%.

ADC value showed slightly better diagnostic performance than D and f values in predicting bladder cancer aggressiveness. The combination of D and f model can produce a robust value than single parameter in evaluating aggressiveness.

1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018.

Journal of magnetic resonance imaging : JMRI. 2018 May 08 [Epub ahead of print]

Miaomiao Zhang, Yan Chen, Xinying Cong, Xinming Zhao

Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China., Department of Imaging, China Rehabilitation Research Center, Beijing, China.

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