Restricted spectrum imaging and diffusion kurtosis imaging for assessing lymph node metastasis in cervical cancer: a...

Area of Science:

• Oncology
• Radiology
• Medical Imaging

Background:

• Restricted spectrum imaging (RSI) and diffusion kurtosis imaging (DKI) offer detailed characterization of tumor microstructural features.
• The clinical utility of RSI and DKI for evaluating lymph node metastasis (LNM) in cervical cancer (CC) requires further investigation.

Purpose of the Study:

• To investigate the potential of RSI and DKI histogram parameters in predicting LNM in CC patients.
• To evaluate the diagnostic performance of individual parameters and a combined model for LNM prediction.

Main Methods:

• Pelvic MRI examinations were performed on 71 CC patients (30 LNM-negative, 41 LNM-positive).
• Histogram parameters from DKI (D, K) and RSI (f1, f2, f3) models were compared using statistical tests.
• Logistic regression, ROC curve analysis, calibration curves, and decision curve analysis were used to assess predictive factors and diagnostic efficacy.

Main Results:

• Significant differences in various DKI and RSI histogram parameters were observed between LNM-negative and LNM-positive groups (P < 0.05).
• Maximum diameter and DKI_Dmedian were identified as independent predictors of LNM status in CC.
• The combined model (maximum diameter + DKI_Dmedian) achieved superior diagnostic efficacy (AUC = 0.874, sensitivity = 0.927, specificity = 0.767) compared to individual parameters.

Conclusions:

• DKI and RSI histogram parameters show significant potential for predicting LNM in CC.
• The combination of maximum diameter and DKI_Dmedian serves as a promising joint biomarker for LNM prediction in CC patients.
• This combined approach enhances diagnostic accuracy for LNM in cervical cancer.