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Prognostic value of radiomics-based hyperdense middle cerebral artery sign for patients with acute ischemic stroke after thrombectomy strategy.
Li, Linna; Li, Mingyang; Chen, Zhongping; Lu, Fei; Zhao, Min; Zhang, Huimao; Tong, Dan.
Afiliación
  • Li L; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Li M; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Chen Z; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Lu F; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Zhao M; Pharmaceutical Diagnostics, GE Healthcare, Beijing, China.
  • Zhang H; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Tong D; Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
Front Neurol ; 13: 1037204, 2022.
Article en En | MEDLINE | ID: mdl-36712442
ABSTRACT
Background and

purpose:

The purpose of this study was 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 categorized into two sets, namely, the training set (n = 81) and the test set (n = 21). Radiomics features (RFs) and clinical features (CFs) in the training set were selected by statistical analysis to create models. The models' discriminative ability was 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) and neutrophil-to-lymphocyte ratio (NLR) [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 [RM; 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 post-operative CFs alone [AUC (95%CI) = 0.856 (0.685-1.000)] or post-operative 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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Neurol Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Neurol Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: CH / SUIZA / SUÍÇA / SWITZERLAND