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一种基于CT纹理的列线图,用于预测急性前循环大血管闭塞血管内血栓切除术后脑实质内高密度患者的无效再灌注。

A CT texture-based nomogram for predicting futile reperfusion in patients with intraparenchymal hyperdensity after endovascular thrombectomy for acute anterior circulation large vessel occlusion.

作者信息

Dong Meijuan, Chen Chun, Chen Wei, An Kun

机构信息

Department of Endocrinology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huai'an, China.

Department of Neurology, Xuzhou Medical University Affiliated Hospital of Huai'an, Huai'an, China.

出版信息

Front Neurol. 2024 Apr 19;15:1327585. doi: 10.3389/fneur.2024.1327585. eCollection 2024.

DOI:10.3389/fneur.2024.1327585
PMID:38708002
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11066250/
Abstract

BACKGROUND

Post-thrombectomy intraparenchymal hyperdensity (PTIH) in patients with acute anterior circulation large vessel occlusion is a common CT sign associated with a higher incidence of futile reperfusion (FR). We aimed to develop a nomogram to predict FR specifically in patients with PTIH.

METHODS

We retrospectively collected information on patients with acute ischemic stroke who underwent endovascular thrombectomy (EVT) at two stroke centers. A total of 398 patients with PTIH were included to develop and validate the nomogram, including 214 patients in the development cohort, 92 patients in the internal validation cohort and 92 patients in the external validation cohort. The nomogram was developed according to the independent predictors obtained from multivariate logistic regression analysis, including clinical factors and CT texture features extracted from hyperdense areas on CT images within half an hour after EVT. The performance of the nomogram was evaluated with integrated discrimination improvement (IDI), category-free net reclassification improvement (NRI), the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analyses for discrimination, calibration ability, and clinical net benefits, respectively.

RESULTS

Our nomogram was constructed based on three clinical factors (age, NIHSS score and ASPECT score) and two CT texture features (entropy and kurtosis), with AUC-ROC of 0.900, 0.897, and 0.870 in the development, internal validation, and external validation cohorts, respectively. NRI and IDI further validated the superior predictive ability of the nomogram compared to the clinical model. The calibration plot revealed good consistency between the predicted and the actual outcome. The decision curve indicated good positive net benefit and clinical validity of the nomogram.

CONCLUSION

The nomogram enables clinicians to accurately predict FR specifically in patients with PTIH within half an hour after EVT and helps to formulate more appropriate treatment plans in the early post-EVT period.

摘要

背景

急性前循环大血管闭塞患者血栓切除术后脑实质内高密度(PTIH)是一种常见的CT征象,与无效再灌注(FR)发生率较高相关。我们旨在开发一种列线图,以专门预测PTIH患者的FR。

方法

我们回顾性收集了在两个卒中中心接受血管内血栓切除术(EVT)的急性缺血性卒中患者的信息。总共纳入398例PTIH患者以开发和验证列线图,其中214例患者纳入开发队列,92例患者纳入内部验证队列,92例患者纳入外部验证队列。列线图是根据多变量逻辑回归分析获得的独立预测因素制定的,包括临床因素和在EVT后半小时内从CT图像上的高密度区域提取的CT纹理特征。分别使用综合鉴别改善(IDI)、无类别净重新分类改善(NRI)、受试者工作特征曲线下面积(AUC-ROC)、校准图和决策曲线分析来评估列线图在鉴别、校准能力和临床净效益方面的性能。

结果

我们的列线图基于三个临床因素(年龄、美国国立卫生研究院卒中量表[NIHSS]评分和脑缺血性病变评分[ASPECT]评分)和两个CT纹理特征(熵和峰度)构建,在开发队列、内部验证队列和外部验证队列中的AUC-ROC分别为0.900、0.897和0.870。NRI和IDI进一步验证了列线图与临床模型相比具有更好的预测能力。校准图显示预测结果与实际结果之间具有良好的一致性。决策曲线表明列线图具有良好的正净效益和临床有效性。

结论

该列线图使临床医生能够在EVT后半小时内准确预测PTIH患者的FR,并有助于在EVT后早期制定更合适的治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/fa3e5628289e/fneur-15-1327585-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/b5639694c860/fneur-15-1327585-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/2a134fee51f9/fneur-15-1327585-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/24b0cb44ca34/fneur-15-1327585-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/5b21891f169b/fneur-15-1327585-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/ee2f4a701cee/fneur-15-1327585-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/fa3e5628289e/fneur-15-1327585-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/b5639694c860/fneur-15-1327585-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/2a134fee51f9/fneur-15-1327585-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/24b0cb44ca34/fneur-15-1327585-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/5b21891f169b/fneur-15-1327585-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/ee2f4a701cee/fneur-15-1327585-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f224/11066250/fa3e5628289e/fneur-15-1327585-g006.jpg

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