医学
气管狭窄
气道
光学相干层析成像
核医学
狭窄
病理
内科学
放射科
外科
作者
Ziqing Zhou,Zhu‐Quan Su,Wan Sun,Minglu Zhong,Yu Chen,Chang‐Hao Zhong,Huan-Jie Chen,Shiyue Li
出处
期刊:Respiration
[Karger Publishers]
日期:2020-01-01
卷期号:99 (6): 500-507
被引量:3
摘要
<b><i>Background:</i></b> The predictors and airway morphological changes during the development of postintubation tracheal stenosis (PITS) have not been well elucidated. <b><i>Objectives:</i></b> To elucidate the validation of endobronchial optical coherence tomography (EB-OCT) in assessing the airway morphological changes in PITS. <b><i>Methods:</i></b> We performed oral endotracheal intubation in 12 beagles to establish the PITS model. EB-OCT was performed respectively before modeling and on the 1st, 7th, and 12th day after extubation in 9 canines, and was conducted consecutively in 3 canines during the development of PITS. Histological findings and the thickness and gray-scale value of the tracheal wall assessed by EB-OCT measurements were analyzed and compared. <b><i>Results:</i></b> The tracheal wall edema, granulation tissue proliferation, cartilage destruction in PITS, and airway wall thickening detected by EB-OCT were in concordance with the histopathological measurements. The consecutive EB-OCT observation of the airway structure demonstrated the tracheal wall thickness significantly increased from 344.41 ± 44.19 μm before modeling to 796.67 ± 49.75 μm on the 9th day after modeling (<i>p</i> < 0.05). The airway wall gray-scale values assessed by EB-OCT decreased from 111.19 ± 14.71 before modeling to 74.96 ± 4.08 on the 9th day after modeling (<i>p</i> < 0.05). The gray-scale value was negatively correlated with the airway wall thickness (<i>r</i> = –0.945, <i>p</i> = 0.001). <b><i>Conclusion:</i></b> The EB-OCT imaging, in concordance with the histopathological finding, was validated for assessing the airway morphological changes during the development of PITS. The EB-OCT evaluation of cartilage damage and gray-scale value measurement might help predict the development and prognosis of PITS.
科研通智能强力驱动
Strongly Powered by AbleSci AI