A histogram analysis of diffusion and perfusion features of cervical cancer based on intravoxel incoherent motion magnetic resonance imaging.

OBJECTIVE: To evaluate the diagnostic potential based on histogram analysis of IVIM parameters between uterine cervical cancers (CC) - normal myometrium (Myo) versus CC - gluteus maximus muscle (GM) and to study the feasibility of histogram analysis of IVIM parameters to differentiate the early from locally advanced stage CCs. METHODS: 64 patients with pathologically confirmed CC were enrolled. Histogram indices mean, median, 25th, and ð 75th percentile of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) value of entire tumor were statistically analyzed and compared between CC - GM versus CC - Myo, as well as between early and locally advanced stage CCs. A multivariate analysis was performed to identify indices that could best distinguish early from locally advanced stage CC. Receiver operating characteristic curves (ROC) were used to evaluate the diagnostic efficiency of every histogram parameter. RESULTS: All the tested histogram indices significantly differed between the patients with CC - GM vs. CC - Myo, nonetheless, CC - GM yielded higher range area under the curve (AUC) value of 0.8-0.99 vs. 0.6-0.99. The additional significant difference was found among all the tested histogram indices of D*, mean, median, and 75th percentile of f, mean and 75th percentile of ADC, and 75th percentile of D discriminating early from locally advanced CCs. ROC curves indicated that the 75th percentile of D* value 28.17 × 10-3 mm2/s could best differentiate early from locally advanced stage CCs, with AUC of 0.776. In the multivariate analysis, ROC indicated the 50th percentile of D* and f was the most significant with AUCs of 0.856. CONCLUSIONS: The histogram analysis of IVIM parameters depicted that gluteus maximus served better reference tissue in comparison to myometrium. The histogram index 75th percentile of ADC, D, D*, and f may serve a diagnostic biomarker to differentiate the early from locally advanced stage CCs.

A study on diffusion and kurtosis features of cervical cancer based on non-Gaussian diffusion weighted model.

OBJECTIVE: To explore the diffusion and kurtosis features of cervical cancer (CC) and study the feasibility of diffusion kurtosis imaging (DKI) based on the non-Gaussian diffusion-weighted model to differentiate the stage and grade of CC. METHODS: A total of 50 patients with pathologically confirmed CC were enrolled. MRI examinations including DKI (with 5b values 200, 500, 1000, 1500, and 2000smm-2 were performed before any treatment. The apparent coefficient (Dapp) and the apparent kurtosis value (Kapp) were derived from the non-gaussian diffusion model, and the apparent diffusion coefficient (ADC) was derived from the Gaussian model. The parameters of CC and normal tissue (myometrium) were obtained, analyzed statistically, and evaluated with respect to differentiating stage and grade between the tissue and the CC. RESULTS: ADC and Dapp values of CC were significantly lower than that of the normal myometrium (P=0.024 and P<0.001, respectively), while the Kapp value was not found to exhibit a significant difference. Compared to the well/moderately differentiated CC, poorly differentiated CC had a significantly decreased mean ADC and Dapp (P=0.018 and P=0.026, respectively); however, the mean Kapp (P=0.035) increased significantly. In the clinical staging, the DKI sequence was advantageous over conventional MRI sequences (degree of accuracy: 90% vs. 74%), Although in the quantitative analysis, these parameters did not show a significant difference. CONCLUSIONS: The pilot study demonstrated that these diffusion and kurtosis indices from DKI based on the non-Gaussian diffusion-weighted model putatively differentiated the grade and stage of CC.