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Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.
Santo, Briana A; Ciecierska, Shiau-Sing K; Mousavi Janbeh Sarayi, S Mostafa; Jenkins, TaJania D; Baig, Ammad A; Monteiro, Andre; Koenigsknecht, Carmon; Pionessa, Donald; Gutierrez, Liza; King, Robert M; Gounis, Matthew; Siddiqui, Adnan H; Tutino, Vincent M.
Afiliação
  • Santo BA; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Ciecierska SK; Department of Pathology and Anatomical Sciences, Buffalo, NY, USA.
  • Mousavi Janbeh Sarayi SM; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Jenkins TD; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Baig AA; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Monteiro A; Department of Pathology and Anatomical Sciences, Buffalo, NY, USA.
  • Koenigsknecht C; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Pionessa D; Department of Neurosurgery, Buffalo, NY, USA.
  • Gutierrez L; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • King RM; Department of Neurosurgery, Buffalo, NY, USA.
  • Gounis M; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
  • Siddiqui AH; Department of Neurosurgery, Buffalo, NY, USA.
  • Tutino VM; Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
Heliyon ; 9(4): e14837, 2023 Apr.
Article em En | MEDLINE | ID: mdl-37025889
ABSTRACT

Background:

Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to in vivo stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections.

Methods:

Three rat ischemic stroke cohorts were used in this study (Total n = 91 rats; Cohort 1 n = 21, Cohort 2 n = 40, Cohort 3 n = 30). For each, brains were serially-sliced, stained with TTC and scanned on both anterior and posterior sides. Ground truth annotation and infarct morphometric analysis (e.g., brain-Vbrain, infarct-Vinfarct, and non-infarct-Vnon-infarct volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development (n = 3 training cases with 36 slices [18 anterior and posterior faces], n = 18 testing cases with 218 slices [109 anterior and posterior faces]), as well as infarct morphometrics automation. The infarct quantification pipeline and pre-trained model were packaged as a standalone software and applied to Cohort 2, an internal validation dataset. Finally, software and model trainability were tested as a use-case with Cohort 3, a dataset from a separate institute.

Results:

Both high segmentation and statistically significant quantification performance (correlation between manual and software) were observed across all datasets. Segmentation performance Cohort 1 brain accuracy = 0.95/f1-score = 0.90, infarct accuracy = 0.96/f1-score = 0.89; Cohort 2 brain accuracy = 0.97/f1-score = 0.90, infarct accuracy = 0.97/f1-score = 0.80; Cohort 3 brain accuracy = 0.96/f1-score = 0.92, infarct accuracy = 0.95/f1-score = 0.82. Infarct quantification (cohort average) Vbrain (ρ = 0.87, p < 0.001), Vinfarct (0.92, p < 0.001), Vnon-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarctnon-infact ratio (ρ = 0.92, p < 0.001).

Conclusion:

Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article