共 50 条
Applications of artificial intelligence for DWI and PWI data processing in acute ischemic stroke: Current practices and future directions
被引:15
|作者:
Ben Alaya, Ines
[1
]
Limam, Hela
[2
]
Kraiem, Tarek
[1
]
机构:
[1] Tunis El Manar Univ, Higher Inst Med Technol Tunis, Lab Biophys & Med Technol, Tunis 1006, Tunisia
[2] Univ Tunis El Manar, Inst Super dInformat, Inst Super Gest Tunis, Lab BestMod, Tunis 1002, Tunisia
来源:
关键词:
Stroke;
Diffusion MRI;
Artificial intelligence;
Magnetic resonance imaging;
Ischemic penumbra;
Perfusion imaging;
ARTERIAL INPUT FUNCTION;
CEREBRAL-BLOOD-FLOW;
DIFFUSION-COEFFICIENT THRESHOLD;
PERFUSION IMAGING EVALUATION;
EVALUATION TRIAL EPITHET;
LESION SEGMENTATION;
AUTOMATIC SELECTION;
PENUMBRAL FLOW;
WEIGHTED MRI;
QUANTIFICATION;
D O I:
10.1016/j.clinimag.2021.09.015
中图分类号:
R8 [特种医学];
R445 [影像诊断学];
学科分类号:
1002 ;
100207 ;
1009 ;
摘要:
Multimodal Magnetic Resonance Imaging (MRI) techniques of Perfusion-Weighted Imaging (PWI) and DiffusionWeighted Imaging (DWI) data are integral parts of the diagnostic workup in the acute stroke setting. The visual interpretation of PWI/DWI data is the most likely procedure to triage Acute Ischemic Stroke (AIS) patients who will access reperfusion therapy, especially in those exceeding 6 h of stroke onset. In fact, this process defines two classes of tissue: the ischemic core, which is presumed to be irreversibly damaged, visualized on DWI data and the penumbra which is the reversibly injured brain tissue around the ischemic tissue, visualized on PWI data. AIS patients with a large ischemic penumbra and limited infarction core have a high probability of benefiting from endovascular treatment. However, it is a tedious and time-consuming procedure. Consequently, it is subject to high inter- and intraobserver variability. Thus, the assessment of the potential risks and benefits of endovascular treatment is uncertain. Fast, accurate and automatic post-processing of PWI and DWI data is important for clinical diagnosis and is necessary to help the decision making for therapy. Therefore, an automated procedure that identifies stroke slices, stroke hemisphere, segments stroke regions in DWI, and measures hypoperfused tissue in PWI enhances considerably the reproducibility and the accuracy of stroke assessment. In this work, we draw an overview of several applications of Artificial Intelligence (AI) for the automation processing and their potential contributions in clinical practices. We compare the current approaches among each other's with respect to some key requirements.
引用
收藏
页码:79 / 86
页数:8
相关论文