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The relationship between perihematomal edema and hematoma expansion in acute spontaneous intracerebral hemorrhage: an exploratory radiomics analysis study.
Zhou, Zhiming; Wu, Xiaojia; Chen, Yuanyuan; Tan, Yuanxin; Zhou, Yu; Huang, Tianxing; Zhou, Hongli; Lai, Qi; Guo, Dajing.
Afiliação
  • Zhou Z; Department of Radiology, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Wu X; Chongqing Medical Imaging Artificial Intelligence Lab, Chongqing, China.
  • Chen Y; Department of Radiology, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Tan Y; Chongqing Medical Imaging Artificial Intelligence Lab, Chongqing, China.
  • Zhou Y; Department of Radiology, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Huang T; Chongqing Medical Imaging Artificial Intelligence Lab, Chongqing, China.
  • Zhou H; Department of Radiology, Fifth People's Hospital of Chongqing, Chongqing, China.
  • Lai Q; Department of Radiology, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Guo D; Chongqing Medical Imaging Artificial Intelligence Lab, Chongqing, China.
Front Neurosci ; 18: 1394795, 2024.
Article em En | MEDLINE | ID: mdl-38745941
ABSTRACT

Background:

The relationship between early perihematomal edema (PHE) and hematoma expansion (HE) is unclear. We investigated this relationship in patients with acute spontaneous intracerebral hemorrhage (ICH), using radiomics.

Methods:

In this multicenter retrospective study, we analyzed 490 patients with spontaneous ICH who underwent non-contrast computed tomography within 6 h of symptom onset, with follow-up imaging at 24 h. We performed HE and PHE image segmentation, and feature extraction and selection to identify HE-associated optimal radiomics features. We calculated radiomics scores of hematoma (Radscores_HEA) and PHE (Radscores_PHE) and constructed a combined model (Radscore_HEA_PHE). Relationships of the PHE radiomics features or Radscores_PHE with clinical variables, hematoma imaging signs, Radscores_HEA, and HE were assessed by univariate, correlation, and multivariate analyses. We compared predictive performances in the training (n = 296) and validation (n = 194) cohorts.

Results:

Shape_VoxelVolume and Shape_MinorAxisLength of PHE were identified as optimal radiomics features associated with HE. Radscore_PHE (odds ratio = 1.039, p = 0.032) was an independent HE risk factor after adjusting for the ICH onset time, Glasgow Coma Scale score, baseline hematoma volume, hematoma shape, hematoma density, midline shift, and Radscore_HEA. The areas under the receiver operating characteristic curve of Radscore_PHE in the training and validation cohorts were 0.808 and 0.739, respectively. After incorporating Radscore_PHE, the integrated discrimination improvements of Radscore_HEA_PHE in the training and validation cohorts were 0.009 (p = 0.086) and -0.011 (p < 0.001), respectively.

Conclusion:

Radscore_PHE, based on Shape_VoxelVolume and Shape_MinorAxisLength of PHE, independently predicts HE, while Radscore_PHE did not add significant incremental value to Radscore_HEA.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Neurosci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Neurosci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça