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Value of diffusion-weighted imaging in predicting parametrial invasion in stage IA2-IIA cervical cancer
Jung Jae Park1, Chan Kyo Kim, Sung Yoon Park
1Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-gu, Seoul, Republic of Korea, 135-710.
Objective:
To investigate the value of diffusion-weighted imaging (DWI) in evaluating parametrial invasion (PMI) in stage IA2-IIA cervical cancer.
Methods:
A total of 117 patients with stage IA2-IIA cervical cancer who underwent preoperative MRI and radical hysterectomy were included in this study. Preoperative clinical variables and MRI variables were analysed and compared between the groups with and without pathologically proven PMI.
Results:
All variables except age were significantly different between patients with and without pathologic PMI (P < 0.05). All variables except squamous cell carcinoma (SCC) antigen were also significantly correlated with pathologic PMI on univariate analysis (P < 0.05). Multivariate analysis indicated that PMI on MRI (P < 0.001) and tumour apparent diffusion coefficient (ADC) (P = 0.029) were independent predictors of pathologic PMI. Area under the curve of PMI on MRI increased significantly from 0.793 to 0.872 when combined with tumour ADC (P = 0.002). When PMI on MRI was further stratified by tumour ADC, the false negative rate was 2.0 % (1/49).
Conclusion:
In stage IA2-IIA cervical cancer, tumour ADC and PMI on MRI seem to be independent predictors of pathologic PMI. Combining the two predictors improved the diagnostic performance of identifying patients at low risk of pathologic PMI.
Key Points:
• Accurate PMI prediction is essential for appropriate treatment planning • Tumour ADC appears to be an independent predictor of pathologic PMI • Adding DWI to MRI improves accuracy for identifying low-risk patients for PMI.
