In-silico decongested trial effects on the impaired breathing function of a bulldog suffering from severe brachycephalic obstructive airway syndrome

Autor: Nguyen Dang Khoa, Nguyen Lu Phuong, Kenji Tani, Kiao Inthavong, Kazuhide Ito
Rok vydání: 2023
Předmět:
Zdroj: Computer Methods and Programs in Biomedicine. 228:107243
ISSN: 0169-2607
Popis: Brachycephalic obstructive airway syndrome (BOAS) susceptible dogs (e.g., French bulldog), suffer health complications related to deficient breathing primarily due to anatomical airway geometry. Surgical interventions are known to provide acceptable functional and cosmetic results; however, the long-term post-surgery outcome is not well known. In silico analysis provides an objective measure to quantify the respiratory function in postoperative dogs which is critical for successful long-term outcomes. A virtual surgery to open the airway can explore the ability for improved breathing in an obstructed airway of a patient dog, thus supporting surgeons in pre-surgery planning using computational fluid dynamics.In this study five surgical interventions were generated with a gradual increment of decongested levels in a bulldog based on computed tomography images. The effects of the decongested airways on the breathing function of a patient bulldog, i.e., airflow characteristics, pressure drop, wall shear stress, and air-conditioning capacity, were quantified by benchmarking against a clinically healthy bulldog using computational fluid dynamics (CFD) method.Our findings demonstrated a promising decrease in excessive airstream velocity, pressure drop, and wall shear stress in virtual surgical scenarios, while constantly preserving adequate air-conditioning efficiency. A linear fit curve was proposed to correlate the reduction in the pressure drop and decongested level.The in silico analysis is a viable tool providing visual and quantitative insight into new unexplored surgical techniques.
Databáze: OpenAIRE