Department of Radiology, Hebei Medical University, Shijiazhuang, Hebei, China.
Department of Radiology, HeBei North University, ZhangJiakou, Hebei, China.
World Neurosurg. 2023 Dec;180:e149-e157. doi: 10.1016/j.wneu.2023.09.015. Epub 2023 Sep 9.
To explore the clinical value of constructing a nomogram model based on apparent diffusion coefficient values within 1 cm of the residual tumor cavity to predict the postoperative progression of gliomas.
Clinical data of patients with glioma who underwent surgery were retrospectively retrieved from the First Hospital of Qinhuangdao. The mean apparent diffusion coefficient (mADC) was measured using a picture archiving and communication system. The Kaplan-Meier survival curve was constructed with the optimal mADC threshold determined by the X-tile. A nomogram was developed based on the independent risk factors determined using the Cox proportional hazards model (Cox regression model) to predict the progression of postoperative glioma. A receiver operating characteristic curve was drawn to evaluate the prediction accuracy of the model, and decision curve analysis was performed to assess the clinical value of the nomogram.
There was good agreement between the mADC values of the 2 repeated measurements before and after, with a consistency correlation coefficient of 0.83. Multivariate Cox regression analysis showed that peritumoral mADC values, degree of peritumoral enhancement, age, pathological grading, and degree of tumor resection were independent risk factors for predicting postoperative progression of glioma (all P < 0.05). The receiver operating characteristic curves of the nomogram predicting 1, 2, and 3 years postoperative progression were 0.86, 0.82, and 0.91, respectively. The calibration curve showed good consistency between the observed and predicted values in the model. The curve showed that the nomogram model has a good clinical application value.
The peritumoral mADC values, degree of peritumoral enhancement, age, pathological grade, and degree of tumor resection were independent factors affecting the postoperative progression of glioma. The nomogram model established for the first time based on mADC values within 1 cm of the tumor can predict the postoperative condition of patients with glioma intuitively and comprehensively. It can provide a relatively accurate prediction tool for neurosurgeons to individualize the evaluation of survival and prognosis, and formulate treatment plans for patients.
探讨基于肿瘤残腔 1cm 内表观扩散系数值构建列线图模型预测脑胶质瘤术后进展的临床价值。
回顾性检索秦皇岛第一医院脑胶质瘤手术患者的临床资料，使用图像存档与通信系统测量平均表观扩散系数（mADC）值。采用 X-tile 确定最佳 mADC 阈值绘制 Kaplan-Meier 生存曲线。采用 Cox 比例风险模型（Cox 回归模型）确定独立危险因素，建立预测术后脑胶质瘤进展的列线图。绘制受试者工作特征曲线评估模型预测准确性，进行决策曲线分析评估列线图的临床价值。
2 次测量前后 mADC 值具有良好的一致性，一致性相关系数为 0.83。多因素 Cox 回归分析显示，瘤周 mADC 值、瘤周强化程度、年龄、病理分级、肿瘤切除程度是预测脑胶质瘤术后进展的独立危险因素（均 P<0.05）。列线图预测 1、2、3 年术后进展的受试者工作特征曲线分别为 0.86、0.82、0.91。校准曲线显示模型的观察值与预测值之间具有良好的一致性。表明该列线图模型具有良好的临床应用价值。
瘤周 mADC 值、瘤周强化程度、年龄、病理分级、肿瘤切除程度是影响脑胶质瘤术后进展的独立因素。首次基于肿瘤残腔 1cm 内 mADC 值建立的列线图模型，能够直观、全面地预测脑胶质瘤患者的术后情况，可为神经外科医生提供较为准确的生存和预后评估预测工具，制定个体化治疗方案。
