3843
Value of whole-lesion histogram analysis based on ADC and ASL in predicting the response to chemotherapy and prognosis of PCNSL1Radiology, The First Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, China
Synopsis
Keywords: Tumors (Pre-Treatment), Quantitative Imaging
Motivation: Primary central nervous system lymphoma (PCNSL) is a rare malignant non-Hodgkin's lymphoma with a poor prognosis, the combination chemotherapy regimen based on methotrexate is the main therapeutic regimen. There are no reliable indicators to predict the treatment response and survival outcome of PCNSL patients.
Goal(s): To predict the response to methotrexate (MTX) chemotherapy and prognosis in primary central nervous system lymphoma (PCNSL) patients by the histogram parameters based on apparent diffusion coefficient (ADC) and arterial spin labeling (ASL).
Approach: Use the univariate and multivariate logistic regressions to identify the independent predictors for the response of MTX chemotherapy. The predictive performance was assessed by the receiver operating characteristic. The Kaplan-Meier analysis and Cox regression were used to analyze the OS.
Results: Number of lesions (NL), the maximum of ADC values and the 95th percentile of CBF values were independent predictive factors of chemotherapy response.
Impact: ADC and CBF values are promising predictive factors of chemotherapy response and outcome in PCNSL patients.
Objective
To predict the chemotherapy response and overall survival (OS) in primary central nervous system lymphoma (PCNSL) patients by the histogram parameters of apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) derived from diffusion-weighted imaging (DWI) and arterial spin labeling (ASL) respectively.Method
Thirty-six patients pathologically confirmed as primary central nervous system diffuse large B-cell lymphoma and treated with a combined MTX-based chemotherapy regimens were retrospectively involved in this study. The patients were divided into response group (R) and non-response group (non-R). The differences in Histogram parameters, including maximum, minimum, mean and the 5th, 10th, 25th, 50th, 75th 90th, and 95th percentiles extracted from ADC and CBF maps were analyzed between R and non-R groups. The univariate and multivariate logistic regressions were performed to identify the independent predictors for MTX chemosensitivity. The performance of independent predictive parameters and their combine prediction model were assessed by the receiver operating characteristic (ROC) analysis. The Kaplan-Meier analysis with Log-rank test and Cox regression were used to analyze the overall survival.Results
The proportion of patients with age>60 (p=0.026) and multiple lesions (p=0.020) in non-R group was significantly higher than R group. ADCmax, ADCmean, ADC5-50 percentiles, CBFmax, CBFmean and CBF5-95 percentiles in R group were significantly higher than non-R patients (all p<0.05). The number of lesions (NL), ADCmax and CBF95 were independent predictive factors of chemotherapy (p=0.034, p=0.048 and p=0.045). The combination model consisted of ADCmax, CBF95 and NL showed the best performance with the area under the ROC curve (AUC) of 0.963 (95% CI=0.910-1.000, p<0.001). The ROC analysis showed that the cut-off points of ADCmax was 1568.00 (AUC=0.788, 95%CI=0.605-0.972, p=0.011) and CBF95 was 57.98 (AUC=0.856, 95%CI=0.725-0.987, p=0.002). The patients with CBF95<57.98 (χ2=4.460, p=0.035) and multiple lesions (χ2=6.396, p=0.011) have significantly shorter OS. Multivariate Cox regression test showed that multiple lesions (HR, 3.796; 95%CI, 1.024-14.073; p =0.046) was an independent risk factor for poor OS.Conclusion
ADC and CBF quantitative histogram paraments are promising factors for the pre-treatment prediction of MTX chemotherapy response and outcome in PCNSL patients.Acknowledgements
Throughout the writing of this dissertation I have received a great deal of support and assistance.I would first like to thank my supervisor, Lin Ma, whose expertise was invaluable in formulating the research questions and methodology. Your insightful feedback pushed me to sharpen my thinking and brought my work to a higher level.I would particularly like to acknowledge my group mates for their wonderful collaboration and patient support.References
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