introduction: To investigate the effect of the magnetic resonance imaging (MRI) fractional order calculus model (FORC) on distinguishing endometrial carcinoma (EC) from normal endometrium and on distinguishing different pathological grades of EC. materials and methods: Patients with pathologically-confirmed EC and normal volunteers with normal endometrium were enrolled to undergo MRI scan with multiple b values for analysis of the differences in the first-order statistical parameters of β, μ, and D. results: Fifty patients with EC aged 56.0±7.9 years were enrolled and divided into group G1 (low-grade group, n=5), G2 (low-grade group, n=33), and G3 (high-grade group, n=12). Thirty volunteers with matched age 55.4 ± 9.0 years and normal endometrium were enrolled as the control group. The first-order statistical parameters β, μ, and D of the EC group were all significantly (P0.05) difference in the parameters among different pathological grades of EC. The Energy and Total Energy of the β first-order statistical parameter were significantly (P0.05) different between G1 and G3 pathological grades of EC, both with an AUC of 0.864. The Energy, Kurtosis, and total Energy of the β first-order statistical parameter were significantly (P0.05) different between G2 and G3 pathological grades and had an AUC of 0.730, 0.795, and 0.812, respectively. The Entropy, Total Energy, and Energy of the D first-order statistical parameter had a significant (P0.05) difference between G2 and G3 grades and had an AUC of 0.724, 0.761, and 0.756, respectively. The Energy, Entropy, and Total Energy of the μ first-order statistical parameter had a significant (P0.05) difference between G2 and G3 grades and had an AUC of 0.801, 0.773, and 0.815, respectively. discussion: The use of the parameters of the FROC model is effective for the diagnosis of EC, and the first-order statistical parameters have high clinical values in differentiating high- and low-grade EC. conclusion: The use of the parameters of the FROC model is effective for the diagnosis of EC, and the first-order statistical parameters have high clinical values in differentiating high- and low-grade EC.
Li et al. (Sun,) studied this question.