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凝血比例,即通过深度学习得出的新的血栓负荷评分,与急性肺栓塞患者的风险分层相关。

Clot ratio, new clot burden score with deep learning, correlates with the risk stratification of patients with acute pulmonary embolism.

作者信息

Xi Linfeng, Xu Feiya, Kang Han, Deng Mei, Xu Wenqing, Wang Dingyi, Zhang Yunxia, Xie Wanmu, Zhang Rongguo, Liu Min, Zhai Zhenguo, Wang Chen

机构信息

Capital Medical University, Beijing, China.

National Center for Respiratory Medicine, Beijing, China.

出版信息

Quant Imaging Med Surg. 2024 Jan 3;14(1):86-97. doi: 10.21037/qims-23-322. Epub 2023 Nov 17.

DOI:10.21037/qims-23-322
PMID:38223063
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10784004/
Abstract

BACKGROUND

Risk stratification for patients with acute pulmonary embolism (APE) is significantly important for treatment and prognosis evaluation. We aimed to develop a novel clot burden score on computed tomography pulmonary angiography (CTPA) based on deep learning (DL) algorithm for risk stratification of APE.

METHODS

The study retrospectively enrolled patients newly diagnosed with APE in China-Japan Friendship Hospital consecutively. We collected baseline data and CTPA parameters, and calculated four different clot burden scores, including Qanadli score, Mastora score, clot volume and clot ratio. The former two were calculated by two radiologists separately, while clot volume and clot ratio were based on the DL algorithm. The area under the curve (AUC) of four clot burden scores were analyzed.

RESULTS

Seventy patients were enrolled, including 17 in high-/intermediate-high risk and 53 in low-/intermediate-low risk. Clot burden was related to the risk stratification of APE. Among four clot burden scores, clot ratio had the highest AUC (0.719, 95% CI: 0.569-0.868) to predict patients with higher risk. In the patients with hemodynamically stable APE, only clot ratio presented statistical difference (P=0.046).

CONCLUSIONS

Clot ratio is a new imaging marker of clot burden which correlates with the risk stratification of patients with APE. Higher clot ratio may indicate higher risk and acute right ventricular dysfunction in patients with hemodynamically stable status.

摘要

背景

急性肺栓塞(APE)患者的风险分层对于治疗和预后评估具有重要意义。我们旨在基于深度学习(DL)算法开发一种新型的计算机断层扫描肺动脉造影(CTPA)上的血栓负荷评分,用于APE的风险分层。

方法

本研究回顾性连续纳入了中日友好医院新诊断为APE的患者。我们收集了基线数据和CTPA参数,并计算了四种不同的血栓负荷评分,包括Qanadli评分、Mastora评分、血栓体积和血栓比例。前两项由两名放射科医生分别计算,而血栓体积和血栓比例基于DL算法。分析了四种血栓负荷评分的曲线下面积(AUC)。

结果

共纳入70例患者,其中高/中高风险组17例,低/中低风险组53例。血栓负荷与APE的风险分层相关。在四种血栓负荷评分中,血栓比例预测高风险患者的AUC最高(0.719,95%CI:0.569-0.868)。在血流动力学稳定的APE患者中,只有血栓比例存在统计学差异(P=0.046)。

结论

血栓比例是一种新的血栓负荷影像标志物,与APE患者的风险分层相关。较高的血栓比例可能表明血流动力学稳定的患者风险较高且存在急性右心室功能障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/41751bcc4616/qims-14-01-86-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/8c544c1d71d0/qims-14-01-86-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/84ee960ae4a3/qims-14-01-86-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/779ba71d296a/qims-14-01-86-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/41751bcc4616/qims-14-01-86-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/8c544c1d71d0/qims-14-01-86-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/84ee960ae4a3/qims-14-01-86-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/779ba71d296a/qims-14-01-86-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8d/10784004/41751bcc4616/qims-14-01-86-f4.jpg

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J Korean Med Sci. 2022 Mar 14;37(10):e76. doi: 10.3346/jkms.2022.37.e76.
2
Acute Pulmonary Embolism: Prognostic Role of Computed Tomography Pulmonary Angiography (CTPA).急性肺栓塞:计算机断层扫描肺动脉造影(CTPA)的预后作用
Tomography. 2022 Feb 14;8(1):529-539. doi: 10.3390/tomography8010042.
3
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J Thromb Thrombolysis. 2025 Feb;58(2):243-253. doi: 10.1007/s11239-024-03051-5. Epub 2024 Oct 22.
4
Machine learning in cancer-associated thrombosis: hype or hope in untangling the clot.癌症相关血栓形成中的机器学习:解开血栓之谜是炒作还是希望。
Bleeding Thromb Vasc Biol. 2024;3(Suppl 1). doi: 10.4081/btvb.2024.123. Epub 2024 May 16.
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4
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5
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