Comparative Study of Monoexponential, Intravoxel Incoherent Motion, Kurtosis, and IVIM-Kurtosis Models for the Diagnosis and Aggressiveness Assessment of Prostate Cancer - Liu, Ying; Wang, Xuan; Cui, Yadong; Jiang, Yuwei; Yu, Lu; Liu, Ming; Zhang, Wei; Shi, Kaining; Zhang, Jintao; Zhang, Chen; Li, Chunmei; Chen, Min (Frontiers in Oncology, 2020)
Objective: This study aimed to compare the potential of monoexponential model (MEM), intravoxel incoherent motion (IVIM) model, kurtosis model, and IVIM–kurtosis model in the diagnosis and aggressiveness assessment of prostate cancer (PCa). Materials and Methods: Thirty-six patients were recruited. Diffusion-weighted images were acquired on a 3.0-T magnetic resonance imaging (MRI) system using 0 b values up to 2000 s/mm2 and analyzed using four models: MEM (ADCMEM), IVIM (DIVIM, D*IVIM, fIVIM), kurtosis (Dkurtosis, Kkurtosis), and IVIM–kurtosis (DIVIM–kurtosis, D*IVIM–kurtosis, fIVIM–kurtosis, DIVIM–kurtosis) models. The values of these parameters were calculated and compared between PCa, benign prostatic hyperplasia (BPH), and prostatitis. Correlations between these parameters and the Gleason score (GS) of PCa were evaluated using the Pearson test. Results: Forty-five lesions were studied, including 18 PCa, 12 prostatitis, and 15 BPH lesions. The ADCMEM, DIVIM, fIVIM, Dkurtosis, and DIVIM–kurtosis values were significantly lower and Kkurtosis and KIVIM–kurtosis values were significantly higher in PCa compared with prostatitis and BPH. The area under the curve (AUC) of ADCMEM showed significantly higher values than that of fIVIM and KIVIM–kurtosis, but no statistical differences were found between the other parameters. The D*IVIM–kurtosis value correlated negatively and fIVIM–kurtosis and KIVIM–kurtosis values correlated positively with the GS. Conclusion: The MEM, IVIM, kurtosis, and IVIM–kurtosis models were all useful for the diagnosis of PCa, and the diagnostic efficacy seemed to be similar. The IVIM–kurtosis model may be superior to the MEM, IVIM, and kurtosis models in the grading of PCa.