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MicroCT and Histological Analysis of Clot Composition in Acute Ischemic Stroke : A Comparative Study of MT-Retrieved Clots and Clot Analogs.
Santo, Briana A; Jenkins, TaJania D; Ciecierska, Shiau-Sing K; Baig, Ammad A; Levy, Elad I; Siddiqui, Adnan H; Tutino, Vincent M.
Afiliação
  • Santo BA; Canon Stroke and Vascular Research Center, University at Buffalo, 875 Ellicott Street, 14203, Buffalo, NY, USA.
  • Jenkins TD; Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY, USA.
  • Ciecierska SK; Canon Stroke and Vascular Research Center, University at Buffalo, 875 Ellicott Street, 14203, Buffalo, NY, USA.
  • Baig AA; Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY, USA.
  • Levy EI; Canon Stroke and Vascular Research Center, University at Buffalo, 875 Ellicott Street, 14203, Buffalo, NY, USA.
  • Siddiqui AH; Canon Stroke and Vascular Research Center, University at Buffalo, 875 Ellicott Street, 14203, Buffalo, NY, USA.
  • Tutino VM; Department of Neurosurgery, University at Buffalo, Buffalo, NY, USA.
Clin Neuroradiol ; 34(2): 431-439, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38294532
ABSTRACT

PURPOSE:

Assessing clot composition on prethrombectomy computed tomography (CT) imaging may help in stroke treatment planning. In this study we seek to use microCT imaging of fabricated blood clots to understand the relationship between CT radiographic signals and the biological makeup.

METHODS:

Clots (n = 10) retrieved by mechanical thrombectomy (MT) were collected, and 6 clot analogs of varying RBC composition were made. We performed paired microCT and histological image analysis of all 16 clots using a ScanCo microCT 100 (4.9 µm resolution) and standard H&E staining (imaged at 40×). From these data types, first order statistic (FOS) radiomics were computed from microCT, and percent composition of RBCs (%RBC) was computed from histology. Polynomial and linear regression (LR) were used to build statistical models based on retrieved thrombus microCT and %RBC that were evaluated for their ability to predict the %RBC of clot analogs from mean HU. Correlation analyses of microCT FOS with composition were completed for both retrieved clots and analogs.

RESULTS:

The LR model fits relating MT-retrieved clot %RBC with mean (R2 = 0.625, p = 0.006) and standard deviation (R2 = 0.564, p < 0.05) in HUs on microCT were significant. Similarly, LR models relating analog histological %RBC to analog protocol %RBC (R2 = 0.915, p = 0.003) and mean HUs on microCT (R2 = 0.872, p = 0.007) were also significant. When the LR model built using MT-retrieved clots was used to predict analog %RBC from mean HUs, significant correlation was observed between predictions and actual histological %RBC (R2 = 0.852, p = 0.009). For retrieved clots, significant correlations were observed for energy and total energy with %RBC and %FP (|R| > 0.7, q < 0.01). Analogs further demonstrated significant correlation between FOS energy, total energy, variance and %WBC (|R| > 0.9, q < 0.01).

CONCLUSION:

MicroCT can be used to build models that predict AIS clot composition from routine CT parameters and help us to better understand radiomic signatures associated with clot composition and first pass outcomes. In future work, such observations can be used to better infer clot composition and inform thrombectomy prognostics from pretreatment CTs.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article