Magnetic resonance imaging plays an important role in the diagnosis and differential diagnosis of endometrial disorders. For advanced diseases, MRI is sensitive in detecting the interruption and extent of the myometrium. However, for early-stage diseases, especially those without obvious evidence of myometrium invasion on MRI, the imaging features of benign and malignant lesions often overlap. With advancements in MR sequences, some recent studies have focused on diffusion MRI for the evaluation of uterine cavity lesions (Takeuchi et al. 2005). In these studies, the diffusion images were found to be different when comparing endometrial cancer and normal endometrium or benign lesions; however, most of these studies focused on late-stage endometrial cancers with obvious invasion of the myometrium, which are easy to detect on MRI. In this study, we focused on the differential diagnosis of IAEC from BELs, which represent the most challenging detections for both radiologists and gynaecologists.

The values of ADC, D, DDC and Dk can all be used to reflect the restricted diffusion of water molecules in tissue and are mainly influenced by cell density. The apparent diffusion coefficient is the default measure of the mean diffusivity of water in tissue derived from the mono-exponential DWI model. While it is easy to obtain, ADC does not indicate the true diffusion value because it is also affected by the perfusion. The apparent diffusion coefficient was reported in the literature to have some ability to distinguish EC from BELs, but its efficacy for diagnosing early-stage EC is limited. In our study, the efficacy of ADC was low, with an AUC of 0.601, suggesting that advanced diffusion models are needed. Our study reveals that, compared with the other diffusion parameters, D had the highest diagnostic efficiency. This may be related to the fact that the value of D excludes the effect of microcirculation (Iima and Bihan 2016). Both DDC and Dk are regarded as composites of individual ADCs with different distributions and directions, respectively; theoretically, both can reflect the diffusion of water molecules more accurately than the ADC (Yamada et al. 2019). However, in our study, the diagnostic efficiency of DDC or Dk was not higher than ADC, which was inconsistent with previous studies (Meng et al. 2021a), possibly due to the difference in study groups. Intravoxel incoherent motion is a functional MRI method that can simultaneously reflect the capillary movement of water molecules (diffusion) and blood circulation (perfusion) in tissue. The D and D* values derived from the bi-exponential IVIM model reflect the diffusion of water molecules and micro-perfusion separately. The IVIM method was shown to be useful in the assessment of the biological behaviour of EC (Meng et al. 2021a), as well as the correlation of cell proliferation with antigen Ki-67 (Li et al. 2021) and the microsatellite instability status of EC (Ma et al. 2023; Bhosale et al. 2017). In our study, the D value of the IAEC group was lower than that of the BEL group, whereas the D* value of the IAEC group was higher compared with the BEL group. The difference in D* between the groups indicated that microperfusion was not negligible and should be further studied. The stretched exponential model has been developed to simultaneously quantify diffusion and tissue heterogeneity. The DDC parameter can reflect the diffusion movement status of water molecules in tissue. Zhang et al. found that DDC could be used to predict the grading of EC, and DDC outperformed ADC (Zhang et al. 2020). The α parameter provides information about the intravoxel water diffusion heterogeneity. A lower α value indicates a higher intravoxel diffusion heterogeneity caused by multi-exponential signal attenuation. Several previous studies have demonstrated that diffusion index α correlates with histological heterogeneity (Zhang et al. 2023; Liu et al. 2015). However, in our study, α did not show a significant difference between malignant and benign groups, presumably as our study focused on IAEC.

Diffusion kurtosis imaging is a method to quantify the deviations from free-water diffusion by estimating diffusion kurtosis from DWI images acquired at high b-values, compared with standard DWI protocols. A K-value derived from the DKI model is an extra parameter that can be used to describe the water molecular diffusivity beyond ADC and Dk. Diffusion kurtosis is a parameter without units, signifying the excess kurtosis compared with a mono-exponential Gaussian model; a larger value of K indicates a greater deviation of diffusion from perfectly Gaussian behaviour (Jensen et al. 2005; Jensen and Helpern 2010). An elevation in K was considered to represent cancer with reduced diffusion and increased complexity. Chen et al. found that DKI can be used to distinguish high-grade from low-grade ECs, and K was the best parameter in this regard, with an AUC of 0.891 (Chen et al. 2017). Yue et al. found that the value of K was higher in the EC than in the normal endometrium group; the AUC of the K value was 0.93, higher than that of Dk and ADC (Yue et al. 2019). The Dk value was obtained using the diffusion value from non-Gaussian distribution corrections, which reflect the overall diffusion and diffusion resistance of water molecules (Granata et al. 2020). The diffusion coefficient has been used to evaluate early-stage EC in several studies. Meng et al. (Meng et al. 2021a, 2021b) showed that Dk could be used to reflect risk stratification and histological features. In some research, Dk showed higher efficacy than ADC, which may be related to the fact that Dk was calculated by considering the restricted diffusion of water molecules in all directions and, therefore, could assess the diffusion of water molecules more accurately than ADC (Jin et al. 2022; Yue et al. 2019). Tian et al. found that both Dk and K were useful in the differential diagnosis of IAEC from endometrial polyps (Tian et al. 2023). The results from our study are consistent with those of previous studies. We found that the K-value in patients with IAEC was higher and Dk was lower than those in patients with BELs, which could be explained by the fact that EC tumour cells proliferate more actively and are more complex than benign lesion cells. Our result is consistent with the previous study; the AUCs of K and Dk were 0.864 and 0.675, respectively, slightly lower than those in the literature. However, the participants in our study were different from those in previous studies, as we focused on the differentiation of IAEC from BELs, which can be difficult for radiologists to establish. Our research also suggests that K performed better than Dk in differential diagnoses, which is consistent with previous studies.

This study had several limitations. First, some of the pathological diagnoses were established by endometrial curettage and biopsy, which may be subject to sampling error. However, such situations are unavoidable, given that a hysterectomy is not warranted for most benign pathologies. Second, all diffusion models used in this study were based on the same series of multiple b-values. Although there were suggestions for the tailored selection of different b-values for diverse advanced DWI models, no consensus was reached. Thus, we decided to use the same series to allow for easy comparison. However, this conclusion should be confirmed in a larger cohort of patients in future prospective studies.

In conclusion, this study compared the diagnostic efficacy of different diffusion models in differentiating IAEC from BELs. Among all diffusion parameters, K showed the best performance and was the only independent predictor; thus, DKI could be used as a non-invasive diagnosis method in clinical practice.