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
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
共 50 条
  • [21] Artificial Intelligence in Plastic Surgery: Current Applications, Future Directions, and Ethical Implications
    Jarvis, Tyler
    Thornburg, Danielle
    Rebecca, Alanna M.
    Teven, Chad M.
    PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN, 2020, 8 (10) : E3200
  • [22] Impact of DWI/PWI MRI on therapeutic decision making in hyper-acute ischemic stroke
    Suarez, JI
    Schoenberger, A
    Zaidat, OO
    Tarr, RW
    Sunshine, JL
    Selman, WR
    Landis, DM
    STROKE, 2002, 33 (01) : 367 - 367
  • [23] No relationship between PWI/DWI and DWI/FLAIR mismatch: Data from the Ax200 ischemic stroke trial
    Wouters, A.
    Ringelstein, E. B.
    Norrving, B.
    Clamorro, A.
    Grond, M.
    Laage, R.
    Schneider, A.
    Thomalla, G.
    Thijs, V.
    CEREBROVASCULAR DISEASES, 2014, 37 : 85 - 85
  • [24] Integrating Artificial Intelligence in Stroke Rehabilitation: Current Trends and Future Directions; A mini review
    Afridi, Ayesha
    Obaid, Sumaiyah
    Raheel, Neha
    Rathore, Farooq Azam
    JOURNAL OF THE PAKISTAN MEDICAL ASSOCIATION, 2025, 75 (02) : 339 - 341
  • [25] Artificial Intelligence in Neuroradiology: Current Status and Future Directions
    Lui, Y. W.
    Chang, P. D.
    Zaharchuk, G.
    Barboriak, D. P.
    Flanders, A. E.
    Wintermark, M.
    Hess, C. P.
    Filippi, C. G.
    AMERICAN JOURNAL OF NEURORADIOLOGY, 2020, 41 (08) : E52 - E59
  • [26] Artificial Intelligence for Neurosurgery : Current State and Future Directions
    Noh, Sung Hyun
    Cho, Pyung Goo
    Kim, Keung Nyun
    Kim, Sang Hyun
    Shin, Dong Ah
    JOURNAL OF KOREAN NEUROSURGICAL SOCIETY, 2023, 66 (02) : 113 - 120
  • [27] Artificial Intelligence in Radiology: Current Technology and Future Directions
    Syed, Ali B.
    Zoga, Adam C.
    SEMINARS IN MUSCULOSKELETAL RADIOLOGY, 2018, 22 (05) : 540 - 545
  • [28] Genetics in Ischemic Stroke: Current Perspectives and Future Directions
    Zhang, Ka
    Loong, Shaun
    Yuen, Linus
    Venketasubramanian, Narayanaswamy
    Chin, Hui-Lin
    Lai, Poh San
    Tan, Benjamin
    JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE, 2023, 10 (12)
  • [29] Artificial Intelligence in Chemistry: Current Trends and Future Directions
    Baum, Zachary J.
    Yu, Xiang
    Ayala, Philippe Y.
    Zhao, Yanan
    Watkins, Steven P.
    Zhou, Qiongqiong
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2021, 61 (07) : 3197 - 3212
  • [30] A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects
    El Alaoui, Yousra
    Elomri, Adel
    Qaraqe, Marwa
    Padmanabhan, Regina
    Taha, Ruba Yasin
    El Omri, Halima
    El Omri, Abdelfatteh
    Aboumarzouk, Omar
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2022, 24 (07)