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Clinical Trial Summary

Lung isolation techniques are commonly used to facilitate surgical exposure and to provide single-lung ventilation for patients. We have developed an automatic comparison software for 3D reconstruction based on CT data (3DRACS). It reconstructs the trachea and bronchus and compares them with the DLT, predicting the most suitable size and depth of the DLT for lung isolation.The aim of this study was to compare whether the use of 3DRACS to select a DLT size compared to conventional empirical selection methods could improve incidence of DLT intubation success and reduce airway injury.


Clinical Trial Description

Lung isolation techniques are commonly used to facilitate surgical exposure and to provide single-lung ventilation for patients undergoing various intra-thoracic procedures. Lung isolation is primarily accomplished with a double-lumen tube (DLT) or bronchial blocker. One published study showed that residents with limited experience had a 40% error rate in accurately placing a DLT. The accurate choice of the size of DLT is a prerequisite for good lung isolation.Currently, There is lack of proper objective criteria for selecting size of DLT. DLT size selection is estimated empirically using the patient's height and sex, and studies have shown that the size of DLT according CT images of the chest is more accurate than experience. we have developed an automatic comparison software for 3D reconstruction based on CT data (3DRACS). It reconstructs the trachea and bronchus and compares them with the DLT, predicting the most suitable size and depth of the DLT for lung isolation. The aim of this study was to compare whether the use of 3DRACS to select a DLT size compared to conventional empirical selection methods could improve incidence of DLT intubation success and reduce airway injury. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05899270
Study type Interventional
Source Sichuan Cancer Hospital and Research Institute
Contact Xin Wang, master
Phone +8685420443
Email 675202449@qq.com
Status Not yet recruiting
Phase N/A
Start date November 1, 2023
Completion date March 30, 2024

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