# How Can Radiomics Help the Clinical Management of Patients with Acute Ischemic Stroke?
## 2 Radiomics
### Differentiation Hemorrhage from Idonimated Contrast Extravasation after Thrombectomy
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline
**Author** & **Year** & **Type** & **N** & **Target** & **Tentiory** & **RF** & **Type of Imaging** & **Results** & **Conclusions** \\ \hline Van Voveet et al. [46] & 2022 & R & 699 & Recaniltration & \multirow{2}{*}{Clot} & \multirow{2}{*}{-} & \multirow{2}{*}{CT} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{Clot-based radiomics are independently associated with workstation, but the results of the clinical and radiomics model was similar} \\ \cline{4-9} Qiu et al. [69] & 2019 & R & 67 & Recaniltration after & & & & & & & & & \\  & & & & & & & & & & & & \\  & & & & & & & & & & & & \\  & & & & & & & & & & & & \\  & & & & & & & & & & & & \\ \hline Fu et al. [50] & 2020 & R & 116 & Predict malignant & \multirow{2}{*}{MCA} & \multirow{2}{*}{13} & \multirow{2}{*}{NECT} & \multirow{2}{*}{AUC of 0.96} & \multirow{2}{*}{Radiomics could help to predict MCC} \\  & & & & & & & & & & using & & \\  & & & & & & & & & & & \\ \hline Jiang et al. [51] & 2022 & R & 389 & Predict malignant & \multirow{2}{*}{Stroke and CSF} & \multirow{2}{*}{1316} & \multirow{2}{*}{MRI} & \multirow{2}{*}{AUC 0.83-0.68} & MRI radiomic features can provide \\  & & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\  & & & & & & & & & & & \\ \hline Wen et al. [52] & 2020 & R & 126 & Predict mMCAI & MCA territory & 396 & CT/CTA & AUC of 0.917-0.913 & \multirow{2}{*}{CT-based radiomics can be a tool to predict the risk of mMCAI.} \\ \cline{4-9} Meng et al. [53] & 2022 & R & 71 & Predict hemorrhage & \multirow{2}{*}{Instruct} & \multirow{2}{*}{5400} & \multirow{2}{*}{MRI} & \multirow{2}{*}{AUC of 0.911} & \multirow{2}{*}{A combined model based on MRI radiomic features can predict the heartwise transformation in AIS patients} \\ \cline{4-9} Xie et al. [54] & 2022 & R & 118 & Predict hemorrhage & \multirow{2}{*}{Instruct} & \multirow{2}{*}{851} & \multirow{2}{*}{CT} & \multirow{2}{*}{AUC of 0.845-0.750} & \multirow{2}{*}{CT-based radiomics could help in the prediction of heartwise transformation in AIS patients} \\ \cline{4-9} Liu et al. [55] & 2021 & R & 104 & Predict hemorrhage & \multirow{2}{*}{Hemorrhage} & \multirow{2}{*}{1691} & \multirow{2}{*}{CT} & \multirow{2}{*}{AUC of 0.845-0.750} & \multirow{2}{*}{CT-based radiomics can predict hemodynamic expansion} \\ \cline{4-9} Liu et al. [55] & 2022 & R & 104 & \multirow{2}{*}{regenerative} & \multirow{2}{*}{Hemorrhage} & \multirow{2}{*}{1691} & \multirow{2}{*}{CT} & \multirow{2}{*}{AUC of 0.919-0.87} & \multirow{2}{*}{CT-based radiomics can predict hemodynamic expansion} \\ \cline{4-9} Chen Y et al. [64] & 2022 & R & 82 & histology prediction & NA & 116 & CTA & AUC of 0.9018 & Radiomics could effectively predict the Acc of 0.8929 & subtype of ischemic stroke. \\ \hline Jiang et al. [57] & 2023 & R & 403 & Biology prediction & Clot & NA & CT & AUC of 0.883 & Clot-based RR on identify the CE strokes. \\ \hline Cheng Y et al. [58] & 2022 & R & 221 & Time since stroke & Clot & 944 & CTA & AUC of 0.803 & Radiomics can estimate the TS1 in patients \\  & & & & & & & & AUC of 0.813-0.803 & with AIS. \\ \hline Yao et al. [59] & 2020 & R & 316 & Time since stroke & Instruct & 295 & CT & AUC of 0.892-0.974 & Radiomics is useful in the determination of \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\ \hline Wen et al. [60] & 2021 & R & 123 & Time since stroke & ASPECTS & 396 & CT/CTA & AUC of 0.888-0.833 & \multirow{2}{*}{CT-based radiomics can discriminate the TS in patients with MC/AU in the M1 segment.} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._