Evaluating microstructures in endometrial cancer using diffusion‐relaxation correlated spectroscopic imaging: Histopathological correlations

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doi:10.1002/mp.17768

Abstract

Background

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.

Purpose

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.

Materials and Methods

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/mm ² ) 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.

Results

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]).

Conclusion

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.