Fan Fu1,2, Xuefei Sun3, Yingying Li4, Yuanbo Liu3, Yi Shan1,2, Nan Ji5, Xiaochen Wang4, Jie Lu6,7,8, Shengjun Sun9. 1. Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. 2. Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. 3. Department of Hematology, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nansihuan Road, Fengtai District, Beijing, 100070, China. 4. Department of Neuroradiology, Beijing Tiantan Hospital, No. 119 Nansihuan Road, Fengtai District, Beijing, 100070, China. 5. Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100070, China. 6. Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. imaginglu@hotmail.com. 7. Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. imaginglu@hotmail.com. 8. Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. imaginglu@hotmail.com. 9. Neuroradiology Department, Beijing Neurosurgical Institute, No. 45 Changchun Street, Xicheng District, Beijing, 100070, China. sunshengjun0212@163.com.
Abstract
OBJECTIVES: To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the response of chemotherapy and clinical outcomes in primary central-nervous-system lymphoma (PCNSL) patients. METHODS: DCE-MRI in 56 patients enrolled in a prospective study was performed at baseline and 30 days after treatment from 2016 to 2019. Multivariate logistic regression analyses were performed to assess risk factors for tumor responses. The predictive values of related parameters derived from DCE were analyzed via receiver operating characteristic (ROC) curve analysis. To evaluate prognostic factors, the Kaplan-Meier survival analysis with log-rank tests and Cox regression tests were analyzed. RESULTS: Ktrans and Ve were higher in the non-response group than in the response group (p < 0.05). The Ktrans and the percentage of Ktrans decreased after 30 days of treatment were independent predictors of chemotherapy responses (p = 0.034 and p = 0.019). ROC analysis indicated that the cut-off point of Ktrans for predicting chemotherapeutic responses was 0.353 min-1 (AUC, 0.941; 95% CI, 0.87-1; p < 0.001) and percentage of Ktrans decreased after 30 days of treatment was 15.2% (AUC, 0.858; 95% CI, 0.742-0.970; p < 0.001). The greater decrease in Ktrans correlated with a longer progression-free survival (PFS) (χ2 = 13.203, p < 0.001). The higher Ktrans was an independent predictor for shorter PFS (hazard ratio, 10.182; 95% CI, 2.510-41.300; p = 0.001). CONCLUSIONS: Ktrans and Ktrans change measured by DCE-MRI were reliable biomarkers for predicting chemotherapy responses in PCNSL patients. KEY POINTS: • Baseline Ktrans and greater decrease in Ktrans can predict chemotherapeutic efficacy. • DCE-MRI provides quantitative parameters reflecting the tumor microenvironment. • Targeted treatment therapy can be given with more evidence in the future.
OBJECTIVES: To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the response of chemotherapy and clinical outcomes in primary central-nervous-system lymphoma (PCNSL) patients. METHODS:DCE-MRI in 56 patients enrolled in a prospective study was performed at baseline and 30 days after treatment from 2016 to 2019. Multivariate logistic regression analyses were performed to assess risk factors for tumor responses. The predictive values of related parameters derived from DCE were analyzed via receiver operating characteristic (ROC) curve analysis. To evaluate prognostic factors, the Kaplan-Meier survival analysis with log-rank tests and Cox regression tests were analyzed. RESULTS:Ktrans and Ve were higher in the non-response group than in the response group (p < 0.05). The Ktrans and the percentage of Ktrans decreased after 30 days of treatment were independent predictors of chemotherapy responses (p = 0.034 and p = 0.019). ROC analysis indicated that the cut-off point of Ktrans for predicting chemotherapeutic responses was 0.353 min-1 (AUC, 0.941; 95% CI, 0.87-1; p < 0.001) and percentage of Ktrans decreased after 30 days of treatment was 15.2% (AUC, 0.858; 95% CI, 0.742-0.970; p < 0.001). The greater decrease in Ktrans correlated with a longer progression-free survival (PFS) (χ2 = 13.203, p < 0.001). The higher Ktrans was an independent predictor for shorter PFS (hazard ratio, 10.182; 95% CI, 2.510-41.300; p = 0.001). CONCLUSIONS:Ktrans and Ktrans change measured by DCE-MRI were reliable biomarkers for predicting chemotherapy responses in PCNSL patients. KEY POINTS: • Baseline Ktrans and greater decrease in Ktrans can predict chemotherapeutic efficacy. • DCE-MRI provides quantitative parameters reflecting the tumor microenvironment. • Targeted treatment therapy can be given with more evidence in the future.
Entities:
Keywords:
Biomarkers; Lymphoma; Magnetic resonance imaging; Prognosis; Survival