Department of Neurology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Department of Neurology, Changshu No.2 People's Hospital, Changshu, China.
EuroIntervention. 2024 Mar 4;20(5):e312-e321. doi: 10.4244/EIJ-D-23-00611.
Intracranial atherosclerotic stenosis (ICAS), an important cause of stroke, is associated with a considerable stroke recurrence rate despite optimal medical treatment. Further assessment of the functional significance of ICAS is urgently needed to enable individualised treatment and, thus, improve patient outcomes.
We aimed to evaluate the haemodynamic significance of ICAS using the quantitative flow ratio (QFR) technique and to develop a risk stratification model for ICAS patients.
Patients with moderate to severe stenosis of the middle cerebral artery, as shown on angiography, were retrospectively enrolled. For haemodynamic assessment, the Murray law-based QFR (μQFR) was performed on eligible patients. Multivariate logistic regression models composed of μQFR and other risk factors were developed and compared for the identification of symptomatic lesions. Based on the superior model, a nomogram was established and validated by calibration.
Among 412 eligible patients, symptomatic lesions were found in 313 (76.0%) patients. The μQFR outperformed the degree of stenosis in discriminating culprit lesions (area under the curve [AUC]: 0.726 vs 0.631; DeLong test p-value=0.001), and the model incorporating μQFR and conventional risk factors also performed better than that containing conventional risk factors only (AUC: 0.850 vs 0.827; DeLong test p-value=0.034; continuous net reclassification index=0.620, integrated discrimination improvement=0.057; both p<0.001). The final nomogram showed good calibration (p for Hosmer-Lemeshow test=0.102) and discrimination (C-statistic 0.850, 95% confidence interval: 0.812-0.883).
The μQFR was significantly associated with symptomatic ICAS and outperformed the angiographic stenosis severity. The final nomogram effectively discriminated symptomatic lesions and may provide a useful tool for risk stratification in ICAS patients.
颅内动脉粥样硬化性狭窄(ICAS)是中风的一个重要原因,尽管进行了最佳的药物治疗,但其中风复发率仍然相当高。迫切需要进一步评估 ICAS 的功能意义,以便进行个体化治疗,从而改善患者的预后。
我们旨在使用定量血流比(QFR)技术评估 ICAS 的血流动力学意义,并为 ICAS 患者建立风险分层模型。
回顾性纳入经血管造影显示大脑中动脉中度至重度狭窄的患者。对符合条件的患者进行基于 Murray 定律的 QFR(μQFR)血流动力学评估。建立并比较包含 μQFR 和其他危险因素的多变量逻辑回归模型,以识别有症状的病变。基于最优模型建立了一个列线图,并通过校准进行验证。
在 412 名符合条件的患者中,313 名(76.0%)患者存在有症状的病变。μQFR 比狭窄程度更能区分责任病变(曲线下面积 [AUC]:0.726 比 0.631;DeLong 检验 p 值=0.001),并且包含 μQFR 和常规危险因素的模型也比仅包含常规危险因素的模型表现更好(AUC:0.850 比 0.827;DeLong 检验 p 值=0.034;连续净重新分类指数=0.620,综合判别改善=0.057;均 p<0.001)。最终的列线图显示出良好的校准(Hosmer-Lemeshow 检验 p 值=0.102)和判别能力(C 统计量 0.850,95%置信区间:0.812-0.883)。
μQFR 与有症状的 ICAS 显著相关,并且优于血管造影狭窄程度。最终的列线图能够有效区分有症状的病变,可能为 ICAS 患者的风险分层提供有用的工具。