构造性梗死分析：一种用于从TTC染色组织中自动进行全脑梗死分析的计算工具。
Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue.
作者信息
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
机构信息
Canon Stroke and Vascular Research Center, Buffalo, NY, USA.
Department of Pathology and Anatomical Sciences, Buffalo, NY, USA.
出版信息
Heliyon. 2023 Mar 24;9(4):e14837. doi: 10.1016/j.heliyon.2023.e14837. eCollection 2023 Apr.
BACKGROUND
Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to 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 = 91 rats; Cohort 1 = 21, Cohort 2 = 40, Cohort 3 = 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, infarct-V, and non-infarct-V volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development ( = 3 training cases with 36 slices [18 anterior and posterior faces], = 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 (ρ = 0.87, < 0.001), V (0.92, < 0.001), V (0.80, < 0.001), %infarct (0.87, = 0.001), and infarct:non-infact ratio (ρ = 0.92, < 0.001).
CONCLUSION
Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.
背景
通过对2,3,5-三苯基氯化四氮唑（TTC）染色的脑切片测量梗死体积对于中风模型至关重要。在本研究中，我们开发了一种交互式、可调节的软件，该软件可根据连续的TTC染色脑切片自动计算全脑梗死指标。
方法
本研究使用了三个大鼠缺血性中风队列（共91只大鼠；队列1 = 21只，队列2 = 40只，队列3 = 30只）。对于每个队列，将大脑进行连续切片，用TTC染色，并从前侧和后侧进行扫描。由领域专家完成真实标注和梗死形态计量分析（例如，脑体积、梗死体积和非梗死体积）。我们使用队列1进行脑和梗死分割模型开发（3个训练病例，36个切片[18个前侧和后侧]，18个测试病例，218个切片[109个前侧和后侧]），以及梗死形态计量自动化。梗死量化流程和预训练模型被打包为一个独立软件，并应用于内部验证数据集队列2。最后，将软件和模型的可训练性作为一个用例，用来自另一个机构的数据集队列3进行测试。
结果
在所有数据集中均观察到了高分割性能和具有统计学意义的量化性能（手动测量与软件测量之间的相关性）。分割性能：队列1脑准确率 = 0.95/f1分数 = 0.90，梗死准确率 = 0.96/f1分数 = 0.89；队列2脑准确率 = 0.97/f1分数 = 0.90，梗死准确率 = 0.97/f1分数 = 0.80；队列3脑准确率 = 0.96/f1分数 = 0.92，梗死准确率 = 0.95/f1分数 = 0.82。梗死量化（队列平均值）：体积（ρ = 0.87，P < 0.001），体积（0.92，P < 0.001），体积（0.80，P < 0.001），梗死百分比（0.87，P = 0.001），以及梗死与非梗死比率（ρ = 0.92，P < 0.001）。
结论
构造性梗死分析软件为基于TTC的中风快速评估提供了一种强大且适应性强的方法。
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