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Postintubation Tracheal Stenosis Evaluated by Endobronchial Optical Coherence Tomography: A Canine Model Study
Zi-Qing Zhou1, Zhu-Quan Su1, Wan Sun1
1State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Endobronchial optical coherence tomography (EB-OCT) effectively assesses airway changes in postintubation tracheal stenosis (PITS). This imaging technique, validated against histology, can predict PITS development and prognosis.
Area of Science:
- Pulmonology
- Medical Imaging
- Otorhinolaryngology
Background:
- Predictors and airway morphological changes in postintubation tracheal stenosis (PITS) remain poorly understood.
- Accurate assessment of PITS development is crucial for timely intervention.
Purpose of the Study:
- To validate endobronchial optical coherence tomography (EB-OCT) for assessing airway morphological changes in PITS.
- To correlate EB-OCT findings with histopathological measurements in a PITS model.
Main Methods:
- A postintubation tracheal stenosis (PITS) model was established in beagles via oral endotracheal intubation.
- Endobronchial optical coherence tomography (EB-OCT) was performed at various time points.
- Histopathological analysis was conducted and compared with EB-OCT measurements of tracheal wall thickness and gray-scale values.
Main Results:
- EB-OCT findings, including edema, granulation tissue, cartilage destruction, and airway thickening, correlated well with histopathology.
- Tracheal wall thickness significantly increased, and gray-scale values decreased during PITS development (p < 0.05).
- A strong negative correlation was observed between gray-scale value and airway wall thickness (r = -0.945, p = 0.001).
Conclusions:
- EB-OCT is a validated tool for assessing airway morphological changes in PITS, consistent with histopathological findings.
- EB-OCT evaluation of cartilage damage and gray-scale values may aid in predicting PITS development and prognosis.
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