Dataset Information

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.

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-V_brain, infarct-V_infarct, and non-infarct-V_non-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): V_brain (ρ = 0.87, p < 0.001), V_infarct (0.92, p < 0.001), V_non-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarct:non-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.

SUBMITTER: Santo BA

PROVIDER: S-EPMC10070917 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Publications

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.

Santo Briana A BA Ciecierska Shiau-Sing K SK Mousavi Janbeh Sarayi S Mostafa SM Jenkins TaJania D TD Baig Ammad A AA Monteiro Andre A Koenigsknecht Carmon C Pionessa Donald D Gutierrez Liza L King Robert M RM Gounis Matthew M Siddiqui Adnan H AH Tutino Vincent M VM

Heliyon 20230324 4

<h4>Background</h4>Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to <i>in vivo</i> stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections.<h4>Methods</h4>Three rat ischemic stroke cohorts were used in this study (Total <i>n</i> = 91 rats; Cohort 1 <i>n</i> = 21, Cohort 2 <i>n</i> = 40, Cohort 3 <i>n</i> = 30). For each, bra ...[more]

PMID: 37025889

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Dataset Information

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.

Background

Methods

Results

Conclusion

Publications

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.

Similar Datasets

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