基于临床-病理-影像指标构建预测模型评估脑膜瘤术后脑水肿加重的风险

宋万立 ,  张海军

国际神经病学神经外科学杂志 ›› 2025, Vol. 52 ›› Issue (06) : 56 -63.

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国际神经病学神经外科学杂志 ›› 2025, Vol. 52 ›› Issue (06) : 56 -63. DOI: 10.16636/j.cnki.jinn.1673-2642.2025.06.008
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基于临床-病理-影像指标构建预测模型评估脑膜瘤术后脑水肿加重的风险

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Value of a predictive model based on clinical⁃pathological⁃imaging indicators in assessing the aggravation of cerebral edema after meningioma surgery

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摘要

目的 基于临床-病理-影像指标构建预测模型对脑膜瘤患者术后脑水肿加重的风险进行评估。 方法 回顾性分析2020年1月—2024年1月开封市中心医院100例接受脑膜瘤手术治疗患者的临床、病理及影像学资料,根据其术后脑水肿是否加重分为加重组(n=26)和未加重组(n=74)。多因素Logistic回归分析脑膜瘤患者术后脑水肿加重的影响因素,并以此构建Logistic回归预测模型,绘制受试者工作特征(ROC)曲线,采用ROC曲线下面积(AUC)评估临床-病理-影像指标构建模型对脑膜瘤患者术后脑水肿加重的预测价值。采用Bootstrap法对其进行内部验证。 结果 100例脑膜瘤患者中,有26.00%的患者出现术后脑水肿加重。多因素Logistic回归分析结果显示,术前瘤周水肿(OR=1.687,95%CI:1.443~1.931)、肿瘤大小(OR=1.790,95%CI:1.653~1.926)、肿瘤部位(OR=1.840,95%CI:1.733~1.948)、CT增强形态(OR=1.811,95%CI:1.702~1.920)均为脑膜瘤患者术后脑水肿加重的影响因素(P<0.05)。基于上述因素构建临床-病理-影像Logistic回归预测模型:Logistic(P)=-4.326+0.523(术前瘤周水肿)+0.582(肿瘤大小)+0.610(肿瘤部位)+0.594(CT增强形态),其对脑膜瘤患者术后脑水肿加重预测的敏感度、特异度及AUC分别为81.21%、90.58%及0.914(P<0.001)。对模型鲁棒性进行检测,风险模型敏感度为81.21%、特异度为90.58%、阳性预测值为85.30%、阴性预测值为88.10%、准确率为87.50%、精准率为85.30%、召回率为81.21%、综合评价指标(F1⁃Score)为83.20%,F1⁃Score变异系数CV=5.2%(<10%)。 结论 基于术前瘤周水肿、肿瘤大小、肿瘤部位、CT增强形态构建的临床-病理-影像联合模型对预测脑膜瘤患者术后脑水肿加重的敏感度、特异度及AUC水平均较高,预测效能好,临床应用价值较高。

Abstract

Objective To investigate the value of a predictive model based on clinical⁃pathological⁃imaging indicators in assessing the aggravation of cerebral edema after meningioma surgery. Methods A retrospective analysis was performed for the clinical, pathological, and imaging data of 100 patients with meningioma who received meningioma surgery in Kaifeng Central Hospital from January 2020 to January 2024, and according to the presence or absence of the aggravation of cerebral edema after surgery, the patients were divided into aggravation group with 26 patients and non⁃aggravation group with 74 patients. A logistic regression analysis was used to investigate the influencing factors for the aggravation of cerebral edema after surgery in patients with meningioma, and a logistic regression predictive model was established based on the above risk factors. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was used to assess the value of the model based on clinical⁃pathological⁃imaging indicators in predicting the aggravation of cerebral edema after surgery in patients with meningioma. The Bootstrap method was used for internal validation. Results Among the 100 patients with meningioma, 26.00% (26/100) had aggravation of cerebral edema after surgery. The multivariate logistic regression analysis showed that preoperative peritumoral edema (odds ratio [OR]=1.687, 95% confidence interval [CI]:1.443-1.931), tumor size (OR=1.790,95%CI:1.653~1.926), tumor location (OR=1.840,95%CI:1.733~1.948), and CT⁃enhanced morphology (OR=1.811,95%CI:1.702~1.920) were risk factors for aggravation of cerebral edema after surgery in patients with meningioma. The logistic regression clinical⁃pathological⁃imaging predictive model based on the above factors was established as Logistic (P) = -4.326 + 0.523 (preoperative peritumoral edema) + 0.582 (tumor size) + 0.610 (tumor location) + 0.594 (CT⁃enhanced morphology), with a sensitivity of 81.21%, a specificity of 90.58%, and an AUC of 0.914 in predicting the aggravation of cerebral edema after surgery in patients with meningioma. Robustness testing was performed for the risk prediction model with a sensitivity of 81.21%, a specificity of 90.58%, a positive predictive value of 85.30%, a negative predictive value of 88.10%, an accuracy rate of 87.50%, a precision rate of 85.30%, a recall rate of 81.21%, and a comprehensive evaluation index (F1⁃Score) of 83.20%, with a coefficient of variation of 5.2% (<10%) for F1⁃Score. Conclusions The clinical⁃pathological⁃imaging model constructed based on preoperative peritumoral edema, tumor size, tumor location, and CT⁃enhanced morphology has high sensitivity, specificity, and AUC in predicting the aggravation of brain edema after surgery in meningioma patients, with a good predictive performance and a high clinical application value.

Graphical abstract

关键词

脑膜瘤 / 脑水肿 / 瘤周水肿 / 病理特征 / CT增强形态 / 脑肿瘤 / 手术

Key words

meningioma / cerebral edema / peritumoral edema / pathological features / CT⁃enhanced morphology / brain tumors / surgery

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宋万立,张海军. 基于临床-病理-影像指标构建预测模型评估脑膜瘤术后脑水肿加重的风险[J]. 国际神经病学神经外科学杂志, 2025, 52(06): 56-63 DOI:10.16636/j.cnki.jinn.1673-2642.2025.06.008

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流行病学资料显示1-2,脑膜瘤发病率居颅内肿瘤第2位,仅次于胶质瘤,且超过90%的脑膜瘤呈良性。脑膜瘤由脑膜上皮细胞发展而来,生长缓慢,好发于中老年人,发病高峰年龄在60~70岁3。脑膜瘤病因目前尚不明确,可能与颅脑外伤、放射性照射等因素有关4。目前,对于世界卫生组织(WHO)Ⅰ级脑膜瘤,临床常采用手术切除治疗,临床疗效显著。但相关研究表明5-8,脑膜瘤术后由于脑组织受损导致血液循环受影响或继发感染等原因,较易出现脑积水、脑水肿及神经功能障碍等疾病,其机制可能与手术致使血管通透性增加有关9-12。其中脑水肿最为常见,可使患者出现恶心呕吐、头痛、视力下降、嗜睡等症状;若脑水肿病情持续加重,导致脑细胞处于持续缺氧状态,可能出现反应迟缓、神经功能缺失、意识障碍等情况,严重影响患者的预后13。因此,探讨脑膜瘤患者术后脑水肿加重的影响因素,找出行之有效的治疗方式,并提前予以针对性干预,对改善患者的预后至关重要。既往研究表明,预测脑膜瘤患者术后脑水肿加重主要关注患者的临床和病理特征,但针对患者影像学方面的研究较少,本研究旨在构建临床-病理-影像联合模型,并探究其对脑膜瘤患者术后脑水肿加重的预测价值,为改善脑膜瘤患者预后提供科学的理论依据,现报道如下。

1 资料与方法

1.1 一般资料

回顾性分析2020年1月—2024年1月于开封市中心医院100例接受脑膜瘤手术治疗患者的临床、病理及影像学资料,根据其术后脑水肿是否加重分为加重组(n=26)和未加重组(n=74)。纳入标准:①经影像学检查及病理确诊为脑膜瘤;②首次进行颅内手术;③临床、病理及影像学资料完整;④术后第1天进行头颅计算机体层成像(CT)检查;⑤签署知情同意书。排除标准:①合并其他良、恶性肿瘤或多发性脑膜瘤;②合并严重头颅外伤史或颅内感染;③合并帕金森病、阿尔茨海默病等神经系统疾病;④合并凝血功能障碍或自身免疫疾病。本研究经本院医学伦理委员会审批通过(批号:2025ks-lw015)。

1.2 方法

1.2.1 手术方法

术前常规禁饮禁食,并严格控制高血压等原发疾病。根据患者头颅影像结果制定手术切口及入路,于全身麻醉下进行开颅显微镜下脑膜瘤切除术,同时阻断其血供,切除脑膜瘤所附着部位的硬脑膜并进行修补,至关颅,术毕。术后第1天进行头颅CT检查,符合脑膜瘤术后脑水肿加重标准者则纳入加重组;反之,纳入未加重组。脑膜瘤术后脑水肿加重标准:①水肿范围扩大,CT显示,如果术后脑水肿的范围较术前明显扩大,表现为水肿带的宽度增加或水肿区域扩展到新的脑区,可以认为是脑水肿加重的表现;②水肿程度加重,CT显示,脑水肿的程度可以通过水肿带的密度变化来评估,如果水肿区域的密度进一步降低,提示水肿加重;③脑室受压或中线移位,严重的脑水肿可能导致脑室受压变形或中线结构移位,这也是脑水肿加重的重要影像学表现。

1.2.2 资料收集

由同一高年资医生整理入组患者临床、病理及影像学资料,其中临床资料包括性别、年龄、术前是否有瘤周水肿、是否有癫痫或合并疾病、是否使用脱水剂或激素、术中是否产生皮层静脉损伤,病理资料包括肿瘤大小、部位、WHO分级、切除程度(Simpson分级),影像指标包括CT钙化征象、瘤周边界是否清楚及增强形态。其中脑膜瘤按WHO分级:WHO Ⅰ级为良性肿瘤,是脑膜瘤的主要类型;WHO Ⅱ级为非典型性脑膜瘤,介于良恶性之间;WHO Ⅲ级为恶性脑膜瘤。Simpson分级:Ⅰ级为完全切除脑膜瘤及其附着的异常脑组织,无任何残留;Ⅱ级为完全切除脑膜瘤,但脑组织中有部分残留物;Ⅲ级为切除部分脑膜瘤,保留大部分瘤体;Ⅳ级为切除了一小部分脑膜瘤组织或只进行了活检;Ⅴ级为只做减压术和(或)活检。

1.3 统计学方法

数据分析使用SPSS 26.0软件,计量资料采用均数±标准差(x¯±s)表示,比较使用t检验,计数资料采用例(%)表示,比较采用χ2 检验。使用Logistic回归分析患者术后脑水肿加重的影响因素,筛选出鲁棒性最好的变量构建预测模型,受试者操作特征(receiver operator characteristic, ROC)曲线、曲线下面积(area under the curve, AUC)和校准曲线评价模型的预测效能和校准能力。Bootstrap法对其进行内部验证,绘制校正曲线,并用Hosmer⁃Lemeshow检验评估模型一致性,以P<0.05为差异有统计学意义。

2 结果

2.1 脑膜瘤患者术后脑水肿加重率

100例脑膜瘤患者中,有26.00%的患者出现术后脑水肿加重。

2.2 两组患者临床、病理、影像学资料比较

两组患者术前瘤周水肿、肿瘤大小、肿瘤部位及CT增强形态比较,差异有统计学意义(P<0.05),见表1

2.3 典型病例分析

患者1,女,61岁,于就诊前活动时出现头晕、恶心伴呕吐、头晕呈天旋地转样、不能睁眼等,不伴有语言不清、四肢无力及吞咽困难,急至医院进行治疗。行脑部MRI(核磁共振成像)+MRA(磁共振血管成像)发现:①右侧额顶叶异常信号,考虑占位病灶建议进一步检查;②双侧基底节区、右侧丘脑陈旧性脑梗死;③老年脑改变;④脑MRA示动脉硬化改变。病理报告显示,脑膜瘤,伴广泛纤维化,WHO Ⅰ级。免疫组织化学检测结果:EMA(+),Ki⁃67(1%+),PR(+),SSTR2(+),D2-40(局部+),3-cad(+),STAT6(-),H3K27me3(+),见图1

患者2,男,69岁,于10年前无明显诱因出现双耳鸣,耳部发胀伴听力下降,右耳为著,未进行相关治疗。半月余前出现双下肢无力,持续时间约15 min,无头晕、恶心、呕吐、肢体麻木或视物模糊等症状,MRI发现,右侧小脑天幕区考虑脑膜瘤。病理报告显示,梭形细胞肿瘤,WHO Ⅱ级,免疫组织化学检测结果:Ki⁃67(10%+),PR(-),SSTR2(+),D2⁃40(+),E⁃cad(+),EMA(-),GFAP(-),H3K27me3(+),S⁃100(-),SOX⁃10(-),CD34(灶+),STAT6(-),Desmin(-);A2+A3+A4:Ki⁃67(10%+),见图2

2.4 影响脑膜瘤患者术后脑水肿加重的因素分析

采用多因素Logistic回归,变量筛选使用逐步回归法(向前:LR),入选标准为0.05,剔除标准为0.10。结果显示,术前瘤周水肿(OR=1.687,95%CI:1.767~3.710)、肿瘤大小(OR=1.790,95%CI:1.784~4.084)、肿瘤部位(OR=1.840,95%CI:1.785~4.317)、CT增强形态(OR=1.811,95%CI:1.802~4.038)均为影响脑膜瘤患者术后脑水肿加重的影响因素(P<0.05),见表2

2.5 模型构建

基于术前瘤周水肿、肿瘤大小、肿瘤部位及CT增强形态构建临床-病理-影像Logistic回归预测模型:Logistic(P)=-4.326+0.523(术前瘤周水肿)+0.582(肿瘤大小)+0.610(肿瘤部位)+0.594(CT增强形态)。P值越大,对术后患者脑水肿加重风险越高。

2.6 模型验证

风险预测模型预测脑膜瘤患者术后脑水肿加重的敏感度、特异度及AUC分别为81.21%、90.58%和0.914(P<0.001),见图3。Bootstrap法检测中AUC为0.831(95%CI:0.784~0.915)。内部验证结果显示如图4,预测值与实际预测值均在理想曲线附近,且Hosmer⁃Lemeshow拟合优度曲线检验(df=8)χ2 =2.156,P=0.725。对模型鲁棒性进行检测,风险模型敏感度为81.21%、特异度为90.58%、阳性预测值为85.30%、阴性预测值为88.10%、准确率为87.50%、精准率为85.30%、召回率为81.21%、综合评价指标(F1⁃Score)为83.20%,F1⁃Score变异系数CV=5.2%(<10%)。

3 讨论

本研究结果显示,术前存在瘤周水肿的脑膜瘤患者,可降低术后脑水肿加重的发生风险。分析其原因可能源于瘤周水肿提示脑膜瘤患者瘤周血-脑屏障已被破坏,予手术切除时,并未进一步破坏瘤周血-脑屏障13-14;术后由于肿瘤占位效应被解除,瘤周水肿与正常脑组织的压力差也随之下降15-16。肿瘤>5 cm的患者,在切除过程中不可避免对正常脑组织进行一些牵拉,术后会增加炎症反应和脑水肿加重的发生风险17-18。脑膜瘤位于矢状窦镰旁时,由于该部位与硬脑膜粘连紧密,血供丰富,肿瘤可侵蚀周边颅骨,增加对静脉窦的压迫程度,使瘤周血-脑屏障易被损伤19-20;术后瘤腔周围脑组织静脉回流受阻,静脉压力增加,血管扩张,血管通透性增强,进而增加脑水肿的发生风险21。本研究结果还揭示,加重组与未加重组的CT不均匀增强的发生率分别为73.08%、31.08%,组间比较有统计学差异,表明CT结果显示不均匀增强的患者,其术后脑水肿加重的发生风险较大,考虑可能与肿瘤有继发性恶变有关22。后续可继续探讨CT不均匀强化与脑膜瘤患者术后脑水肿加重的关系。此外本研究查阅了大量近年来在脑膜瘤方面的文献,这些研究从基因表达、影像组学、分子病理等多个层面揭示了脑膜瘤的异质性及其与预后的关联,为本研究构建多维度预测模型提供了重要的理论依据和方法学参考,见表41-22

为了进一步明确临床-病理-影像联合模型对脑膜瘤患者术后脑水肿的预测效能,本研究基于多因素Logistic回归分析结果构建预测模型并将其纳入ROC曲线。结果显示,该联合模型预测脑膜瘤患者术后脑水肿加重的敏感度、特异度及AUC分别为81.21%、90.58%和0.914,提示临床-病理-影像联合模型对脑膜瘤患者术后脑水肿的预测效能好,具有一定临床指导意义。模型有助于将术前易于获取的指标转化为量化的风险评估工具,为实现围手术期精准管理提供了关键依据。对于术后脑水肿高发人群,术前可实施预防性干预,如激素处理、个性化手术规划等,基于肿瘤部位优化手术入路以减少脑组织损伤,并在术后开展动态监测,从而降低神经功能缺失风险。

然而,本研究纳入的病例数量有限(100例),这可能对研究结果的统计效能和普适性产生一定影响。其次,由于数据来源的限制,我们未能在外部数据集中验证模型的性能。本研究在单因素分析中未发现其他指标有显著差异,但未来可扩大样本量或引入影像组学特征进行深入探索。此外,影像指标仅基于CT增强形态,未来可结合MRI多序列特征等临床资料,进一步评估和优化模型的预测能力。

综上所述,基于术前瘤周水肿、肿瘤大小、肿瘤部位、CT增强形态构建的临床-病理-影像联合模型对预测脑膜瘤患者术后脑水肿加重的敏感度、特异度及AUC水平均较高,预测效能好,临床应用价值较高。

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2023年度开封市科技发展计划(2303069)

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