How Can Radiomics Help the Clinical Management of Patients with Acute Ischemic Stroke?

被引:1
作者
Porto-Alvarez, Jacobo [1 ]
Martinez, Antonio Mosqueira [1 ]
Martinez Fernandez, Javier [1 ]
Lopez, Marta Sanmartin [1 ]
Ulla, Miguel Blanco [1 ]
Vazquez Herrero, Fernando [1 ]
Pumar, Jose Manuel [1 ]
Rodriguez-Yanez, Manuel [2 ]
Pereiro, Anxo Manuel Minguillon [2 ]
Villaverde, Alberto Bolon [3 ]
Rey, Ramon Iglesias [4 ]
Souto-Bayarri, Miguel [1 ]
机构
[1] Complexo Hosp Univ Santiago De Compostela, Radiol Dept, Santiago De Compostela 15706, Spain
[2] Complexo Hosp Univ Santiago De Compostela, Neurol Dept, Santiago De Compostela 15706, Spain
[3] Complexo Hosp Univ Santiago De Compostela, Anaesthesia Dept, Santiago De Compostela 15706, Spain
[4] Hlth Res Inst Santiago De Compostela IDIS, Neuroimaging & Biotechnol Lab NOBEL, Clin Neurosci Res Lab LINC, Santiago De Compostela 15706, Spain
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 18期
关键词
acute ischemic stroke; AIS; radiomics; artificial intelligence; AI; neuroradiology; neurology; OUTCOMES; IMAGES; MODEL;
D O I
10.3390/app131810061
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Acute ischemic stroke (AIS) is the loss of neurological function due to a sudden reduction in cerebral blood flow and is a leading cause of disability and death worldwide. The field of radiological imaging has experienced growth in recent years, which could be boosted by the advent of artificial intelligence. One of the latest innovations in artificial intelligence is radiomics, which is based on the fact that a large amount of quantitative data can be extracted from radiological images, from which patterns can be identified and associated with specific pathologies. Since its inception, radiomics has been particularly associated with the field of oncology and has shown promising results in a wide range of clinical situations. The performance of radiomics in non-tumour pathologies has been increasingly explored in recent years, and the results continue to be promising. The aim of this review is to explore the potential applications of radiomics in AIS patients and to theorize how radiomics may change the paradigm for these patients in the coming years.
引用
收藏
页数:16
相关论文
共 66 条
  • [51] Diffusion-weighted imaging-based radiomics for predicting 1-year ischemic stroke recurrence
    Wang, Hao
    Sun, Yi
    Zhu, Jie
    Zhuang, Yuzhong
    Song, Bin
    [J]. FRONTIERS IN NEUROLOGY, 2022, 13
  • [52] A Clinical-Radiomics Nomogram for Functional Outcome Predictions in Ischemic Stroke
    Wang, Hao
    Sun, Yi
    Ge, Yaqiong
    Wu, Pu-Yeh
    Lin, Jixian
    Zhao, Jing
    Song, Bin
    [J]. NEUROLOGY AND THERAPY, 2021, 10 (02) : 819 - 832
  • [53] Developing a model for estimating infarction onset time based on computed tomography radiomics in patients with acute middle cerebral artery occlusion
    Wen, Xuehua
    Shu, Zhenyu
    Li, Yumei
    Hu, Xingfei
    Gong, Xiangyang
    [J]. BMC MEDICAL IMAGING, 2021, 21 (01)
  • [54] Prediction of Malignant Acute Middle Cerebral Artery Infarction via Computed Tomography Radiomics
    Wen, Xuehua
    Li, Yumei
    He, Xiaodong
    Xu, Yuyun
    Shu, Zhenyu
    Hu, Xingfei
    Chen, Junfa
    Jiang, Hongyang
    Gong, Xiangyang
    [J]. FRONTIERS IN NEUROSCIENCE, 2020, 14
  • [55] who, Global Health Estimates: Leading Causes of Death
  • [56] Imaging of acute ischemic brain injury: the return of computed tomography
    Wintermark, M
    Bogousslavsky, J
    [J]. CURRENT OPINION IN NEUROLOGY, 2003, 16 (01) : 59 - 63
  • [57] Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke
    Xie, Gang
    Li, Ting
    Ren, Yitao
    Wang, Danni
    Tang, Wuli
    Li, Junlin
    Li, Kang
    [J]. FRONTIERS IN NEUROSCIENCE, 2022, 16
  • [58] Radiomics-based intracranial thrombus features on preoperative noncontrast CT predicts successful recanalization of mechanical thrombectomy in acute ischemic stroke
    Xiong, Xing
    Wang, Jia
    Ke, Jun
    Hong, Rong
    Jiang, Shu
    Ye, Jing
    Hu, Chunhong
    [J]. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2023, 13 (02) : 682 - +
  • [59] CT radiomics features as a diagnostic tool for classifying basal ganglia infarction onset time
    Yao, Xiang
    Mao, Ling
    Lv, Shunli
    Ren, Zhenghong
    Li, Wentao
    Ren, Ke
    [J]. JOURNAL OF THE NEUROLOGICAL SCIENCES, 2020, 412
  • [60] Applications and limitations of radiomics
    Yip, Stephen S. F.
    Aerts, Hugo J. W. L.
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (13) : R150 - R166