Effect of 3D-printed Reconstruction System in Size of Left DLT

Status Not yet recruiting

Clinical Trial Summary

The precise and accurate size of DLT is a prerequisite to ensure its accurate position of its placement. Three-dimensional (3D) reconstruction technology can accurately reproduce the tracheobronchial structure to improve the correct size selection of DLT. To make it simpler, the investigators developed an automatic comparison software for 3D reconstruction based on computed tomography data (3DRACS). In this study, the investigators aimed to prove that 3DRACS is much more efficient in endobronchial intubation compared to the traditional method.

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. The investigators 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 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

Clinical Trial Details

NCT number	NCT06258954
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	April 1, 2024
Completion date	July 30, 2024

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