Xinming Zhao1, Xiaoduo Yu2, Qi Zhang3, Han Ouyang3, Feng Ye3, Ying Song3, Lizhi Xie4. 1. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. xinmingzh@sina.com. 2. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. yxd136@139.com. 3. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. 4. GE Healthcare, MR Research China, Beijing, China.
Abstract
PURPOSE: To prospectively assess the incremental value of intravoxel incoherent motion (IVIM) DWI in determining whether the adenocarcinoma originated from the uterine corpus or cervix. METHODS: Eighty consecutive uterine adenocarcinomas from the cervix or endometrium confirmed by histopathology underwent IVIM DWI acquisition on a 3.0T MR scanner before treatment. Five morphologic features were analyzed using Fisher exact test; IVIM DWI-derived parameters, including apparent diffusion coefficient (ADC), true coefficient diffusivity (D), perfusion-related diffusivity (D*), and perfusion fraction (f) were compared using two-sample independent t-test or Mann-Whitney U test. Logistic regression analysis was used to develop different diagnosis model. The ROCs of these variables and diagnostic models were compared to evaluate the diagnostic efficiency. RESULTS: Among single morphologic features, tumor location yielded the highest AUC of 0.891 in distinguishing endometrial adenocarcinoma (EAC) from cervical adenocarcinoma (CAC). Among single IVIM DWI-derived parameters, f values showed the best diagnostic performance (AUC: 0.837) at the optimal cut-off value of 0.261. Additionally, the combined diagnostic model, which consisted of tumor location, ADC and f showed the largest AUC of 0.967 with the highest sensitivity of 88.14%, highest specificity of 100.00%, and highest accuracy of 91.25%. CONCLUSION: IVIM DWI-derived parameters add additional diagnostic value to conventional morphologic features. A combined diagnosis model is a promising imaging tool for predicting the origin of uterine adenocarcinoma, further contributing to therapeutic decision-making.
PURPOSE: To prospectively assess the incremental value of intravoxel incoherent motion (IVIM) DWI in determining whether the adenocarcinoma originated from the uterine corpus or cervix. METHODS: Eighty consecutive uterine adenocarcinomas from the cervix or endometrium confirmed by histopathology underwent IVIM DWI acquisition on a 3.0T MR scanner before treatment. Five morphologic features were analyzed using Fisher exact test; IVIM DWI-derived parameters, including apparent diffusion coefficient (ADC), true coefficient diffusivity (D), perfusion-related diffusivity (D*), and perfusion fraction (f) were compared using two-sample independent t-test or Mann-Whitney U test. Logistic regression analysis was used to develop different diagnosis model. The ROCs of these variables and diagnostic models were compared to evaluate the diagnostic efficiency. RESULTS: Among single morphologic features, tumor location yielded the highest AUC of 0.891 in distinguishing endometrial adenocarcinoma (EAC) from cervical adenocarcinoma (CAC). Among single IVIM DWI-derived parameters, f values showed the best diagnostic performance (AUC: 0.837) at the optimal cut-off value of 0.261. Additionally, the combined diagnostic model, which consisted of tumor location, ADC and f showed the largest AUC of 0.967 with the highest sensitivity of 88.14%, highest specificity of 100.00%, and highest accuracy of 91.25%. CONCLUSION: IVIM DWI-derived parameters add additional diagnostic value to conventional morphologic features. A combined diagnosis model is a promising imaging tool for predicting the origin of uterine adenocarcinoma, further contributing to therapeutic decision-making.
Entities:
Keywords:
Differential diagnosis; Diffusion; Magnetic resonance imaging; Perfusion; Uterine neoplasms
Authors: Pedro T Ramirez; Michael Frumovitz; Michael R Milam; Michael Deavers; Ricardo dos Reis; Revathy B Iyer; Priya Bhosale; Kathleen M Schmeler Journal: Int J Gynecol Cancer Date: 2010-11 Impact factor: 3.437