Evaluating microstructures in endometrial cancer using diffusion-relaxation correlated spectroscopic imaging:...

Endometrial cancer (EC) is a prevalent gynecologic malignancy where accurate grading and assessment are crucial for determining prognosis and treatment strategies. Conventional MRI techniques, including apparent diffusion coefficient (ADC) and T2-weighted imaging, often fail to capture the detailed microstructural complexities of EC.

To evaluate the efficacy of diffusion relaxation correlated spectroscopic imaging (DR-CSI) in assessing EC and to compare its diagnostic performance with conventional ADC and T2-weighted imaging.

Sixty-two patients with histopathologically confirmed EC were included in this prospective study. All patients underwent preoperative MRI, including DR-CSI using a multi-TE (50-90 ms) and multi-b-value (0-1600 s/mm²) echo-planar imaging sequence. The DR-CSI data were analyzed to generate a four-compartment D-T2 spectra, yielding corresponding volume fraction metrics (VF, I-IV). Voxel-wise ADC and T2 values were also obtained. The relationships between these imaging parameters and histopathologic results were evaluated using one-way ANOVA or Kruskal-Wallis tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.

VF_II and VF_III demonstrated significant differences across histological grades (p < 0.01 and p = 0.04, respectively). The combination of VF_II and VF_III provided optimal differentiation between low- and high-grade EC (Area under curve, AUC 0.801 [95% confidence interval: 0.623-0.937]). VF_IV exhibited superior performance in distinguishing lymph node metastasis (LNM) status (AUC 0.734 [0.556-0.892]). The combination of VF_IV and VF_II improved performance in predicting LNM status (AUC 0.826 [0.66-0.961]). However, no parameter alone effectively distinguished myometrial invasion (MI) statuses, but the combination of VF_I and ADC improved performance (AUC 0.706 [0.560-0.844]).

DR-CSI offers a novel and effective method for quantifying microstructural compartments in EC, providing superior diagnostic accuracy compared to conventional ADC and T2 values. The ability to capture detailed microstructural information from DR-CSI metrics holds promise for improving EC diagnosis and grading, offering deeper insights into tumor heterogeneity.