赵 青,刘红阳,赵正宇,顾玲玲,徐 敏.DCE-MRI定量参数联合NLR、MLR对脑胶质瘤患者预后的预测价值[J].现代生物医学进展英文版,2024,(4):670-674. |
DCE-MRI定量参数联合NLR、MLR对脑胶质瘤患者预后的预测价值 |
Predictive Value of DCE-MRI Quantitative Parameters Combined with NLR and MLR in Predicting the Prognosis of Brain Glioma Patients |
Received:November 30, 2023 Revised:December 23, 2023 |
DOI:10.13241/j.cnki.pmb.2024.04.014 |
中文关键词: DCE-MRI定量参数 NLR MLR 脑胶质瘤 预后 预测价值 |
英文关键词: DCE-MRI quantitative parameters NLR MLR Brain glioma Prognosis Predictive value |
基金项目:江苏省科技计划项目(BY2021373) |
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中文摘要: |
摘要 目的:研究动态对比增强扫描-核磁共振检查(DCE-MRI)定量参数联合中性粒细胞计数/淋巴细胞计数比(NLR)及单核细胞计数/淋巴细胞计数比(MLR)对脑胶质瘤患者预后的预测价值。方法:选择从2020年1月到2022年6月在我院接受治疗的脑胶质瘤患者130例作为观察对象。患者均实施脑胶质瘤切除术后放疗,根据预后评价分为预后良好组(n=48)与预后不良组(n=82)。比较两组DCE-MRI定量参数、NLR、MLR;单因素和多因素分析患者预后不良的影响因素;采用受试者工作特征(ROC)曲线分析DCE-MRI定量参数联合NLR、MLR对预后不良的预测价值。结果:随访1年无失访,预后不良组的转运常数(Ktrans)、血管外细胞间隙体积百分数(Ve)、NLR及MLR较预后良好组明显更高(P<0.05)。预后不良组年龄和肿瘤分级为Ⅲ~Ⅳ级、低分化及术后放疗的比例均分别高于预后良好组(P<0.05),卡氏(KPS)评分低于预后良好组(P<0.05)。单因素及多因素Logistic回归分析发现,Ktrans、Ve、NLR及MLR升高是预后不良的危险因素(P<0.05)。ROC曲线分析发现,DCE-MRI定量参数Ktrans、Ve联合NLR、MLR对预后不良患者的预测价值最高,其曲线下面积(AUC)为0.874,灵敏度为95.21%,明显高于其他各项单独检测的结果。结论:脑胶质瘤预后不良患者的NLR、MLR与DCE-MRI定量参数异常升高,且三项联合有助于提升脑胶质瘤患者预后的预测价值。 |
英文摘要: |
ABSTRACT Objective: To study the predictive value of Dynamic contrast-enhanced scanning-magnetic resonance examination (DCE-MRI) quantitative parameters combined with neutrophil-lymphocyte radio (NLR) and monocyte lymphocyte ratio (MLR) in the prognosis of brain glioma patients. Methods: 130 brain glioma patients who received treatment in our hospital from January 2020 to June 2022 were selected as the observation objects. All patients were treated with radiotherapy after brain glioma resection. According to the prognosis evaluation, it was divided into good prognosis group (n=48) and poor prognosis group (n=82). Compare DCE-MRI quantitative parameters, NLR and MLR in two groups; Unvariate and multivariate analysis of the factors affecting poor patient outcomes; The predictive value of the DCE-MRI quantitative parameters combined with NLR and MLR was analyzed using the receiver operating characteristic (ROC) curve. Results: There was no loss to follow-up at 1 year,and the levels of transport constant (Ktrans), extravascular space volume percentage (Ve), NLR and MLR in the poor prognosis group were significantly higher than those in the good prognosis group (P<0.05). The proportion of age, tumor grade Ⅲ ~ Ⅳ, low differentiation and postoperative radiotherapy in the poor prognosis group were higher than those in the good prognosis group(P<0.05), and the Karnofsky Performance Status (KPS) score was lower than that in the good prognosis group(P<0.05). Univariate and multivariate Logistic regression analysis found that the factors associated with poor prognosis included Ktrans, Ve, NLR and MLR(P<0.05). The ROC curve analysis found that found that DCE-MRI quantitative parameters Ktrans, Ve combined with NLR and MLR had the highest predictive value for patients with poor prognosis, the area under the curve (AUC) was 0.874, and the sensitivity was 95.21%, which was significantly higher than the results of other individual tests. Conclusion: NLR, MLLR and DCE-MRI quantitative parameters are abnormally elevated in glioma patients with poor prognosis, with three combinations can improve the predictive value in the prognosis of brain glioma patients, and it is worth promoting and applying in clinical diagnosis. |
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