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使用深度学习的快速磁共振成像在急性缺血性脑卒中的全面评估中的应用。

Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke.

机构信息

Imaging Department, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France.

Biostatistics Department - Delegation for Clinical Research and Innovation, Lille Catholic Hospitals, Lille Catholic University, F-59000, Lille, France.

出版信息

Eur Radiol. 2023 May;33(5):3715-3725. doi: 10.1007/s00330-023-09508-0. Epub 2023 Mar 16.

Abstract

OBJECTIVES

Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR sequences. We aimed to assess the performance of an artificial intelligence-enhanced ultrafast (UF) protocol, compared to the reference protocol, in the AIS management.

METHODS

We included patients admitted in the emergency department for suspected AIS. Each patient underwent a 3-T MR protocol, including reference acquisitions of T2-FLAIR, DWI, and SWI (duration: 7 min 54 s) and their accelerated multishot EPI counterparts for T2-FLAIR and T2*, complemented by a single-shot EPI DWI (duration: 1 min 54 s). Two blinded neuroradiologists reviewed each dataset, assessing DWI (detection, location, number of acute lesions), FLAIR (vascular hyperintensities, visibility of acute lesions), and SWI/T2* (hemorrhagic transformation, thrombus). We compared the agreement between the diagnoses obtained with both protocols using kappa coefficients.

RESULTS

A total of 173 patients were included consecutively, of whom 80 with an AIS in DWI. We found an almost perfect agreement between the UF and reference protocols regarding the detection, distribution, number of AIS in DWI (κ = 0.98, 0.98, and 0.87 respectively), the presence of vascular hyperintensities, and the presence of a parenchymal hyperintensity in the AIS region in FLAIR (κ = 0.93 and 0.89 respectively). Agreement was substantial in T2*/SWI for thrombus detection, and fair for hemorrhagic transformation detection (κ = 0.64 and 0.38 respectively). Differential diagnoses were similarly detected by both protocols (κ = 1).

CONCLUSIONS

Our AI-enhanced ultrafast MRI protocol allowed an effective detection and characterization of both AIS and differential diagnoses in less than 2 min.

KEY POINTS

• The AI-enhanced ultrafast MRI protocol allowed an effective detection of acute stroke. • Characterization of stroke features with the UF protocol was equivalent to the reference sequences. • Differential diagnoses were detected similarly by the UF and reference protocols.

摘要

目的

急性缺血性脑卒中(AIS)是一种需要快速和信息丰富的磁共振序列的急症。我们旨在评估人工智能增强超快(UF)方案与参考方案在 AIS 管理中的性能。

方法

我们纳入了因疑似 AIS 而收入急诊的患者。每位患者均接受了 3-T 磁共振方案检查,包括 T2-FLAIR、DWI 和 SWI 的参考采集(时长:7 分 54 秒)及其多shot EPI 对应物,用于 T2-FLAIR 和 T2*,并补充单次 shot EPI DWI(时长:1 分 54 秒)。两位盲法神经放射科医生审查了每个数据集,评估 DWI(检测、位置、急性病变数量)、FLAIR(血管高信号、急性病变可见性)和 SWI/T2*(出血性转化、血栓)。我们使用 κ 系数比较了两种方案获得的诊断之间的一致性。

结果

共连续纳入 173 例患者,其中 80 例 DWI 显示 AIS。我们发现 UF 方案和参考方案在 DWI 中 AIS 的检测、分布、数量(κ 值分别为 0.98、0.98 和 0.87)、血管高信号的存在和 FLAIR 中 AIS 区域的实质高信号的存在方面具有几乎完美的一致性(κ 值分别为 0.93 和 0.89)。在 T2*/SWI 中血栓的检测具有中等程度的一致性,而出血性转化的检测具有适度的一致性(κ 值分别为 0.64 和 0.38)。两种方案都可以有效地检测出不同的诊断(κ 值为 1)。

结论

我们的人工智能增强超快 MRI 方案在不到 2 分钟的时间内有效检测和诊断 AIS 及其鉴别诊断。

关键点

• AI 增强超快 MRI 方案可以有效检测急性脑卒中。

• UF 方案对脑卒中特征的特征描述与参考序列相当。

• UF 和参考方案可以同样有效地检测出不同的诊断。

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