AUTHOR=Li Linna , Li Mingyang , Chen Zhongping , Lu Fei , Zhao Min , Zhang Huimao , Tong Dan 

TITLE=Prognostic value of radiomics-based hyperdense middle cerebral artery sign for patients with acute ischemic stroke after thrombectomy strategy

JOURNAL=Frontiers in Neurology

VOLUME=Volume 13 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.1037204

DOI=10.3389/fneur.2022.1037204

ISSN=1664-2295

ABSTRACT=Background and purpose
To evaluate the prognostic value of radiomics-based hyperdense middle cerebral artery sign (HMCAS) for patients with acute ischemic stroke (AIS) after mechanical thrombectomy (MT) and to establish prediction models to identify patients who may benefit more from MT.
Methods
In this retrospective study, a total of 102 consecutive patients who presented with HMCAS on non-contrast computed tomography (NCCT) at admission and underwent MT in our hospital between January 2019 and December 2020 were recruited. Among them, 46 experienced favorable outcomes (modified Rankin Scale [mRS] ≤2) at 3 months of follow-up. All patients were divided into two sets: training set (n=81) and test set (n=21). Radiomics features (RFs) and clinical features (CFs) in the training set were selected by statistical analysis to create models. Models' discriminative ability were quantified using the area under the curve (AUC) and confirmed by decision curve analyses.
Results
The prediction model established using CFs before MT includes baseline National Institutes of Health Stroke Scale (NIHSS), neutrophil-to-lymphocyte ratio (NLR) and so on [AUC (95% confidence interval (CI)) =0.596 (0.312-0.881)]. A total of 1,389 RFs were extracted from each hyperdense territory and 8 RFs were left to build the radiomics model [AUC (95% CI) =0.798 (0.598-0.998)]. The model using preoperative CFs and RFs showed good performance [AUC (95% CI) =0.817 (0.625-1.000)]. The models using postoperative CFs alone [AUC (95% CI) =0.856 (0.685-1.000)] or postoperative CFs with RFs [AUC (95% CI) =0.894 (0.757-1.000)] also showed good discrimination.
Conclusion
The radiomics-based HMCAS might be a promising tool to predict the prognoses of patients with AIS after MT.