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Quantification of nasal airflow resistance in English bulldogs using computed tomography and computational fluid dynamics.
Veterinary Radiology & Ultrasound 2017 September
Stenotic nares, edematous intranasal turbinates, mucosal swelling, and an elongated, thickened soft palate are common sources of airflow resistance for dogs with brachycephalic airway syndrome. Surgery has focused on enlarging the nasal apertures and reducing tissue of the soft palate. However, objective measures of surgical efficacy are lacking. Twenty-one English bulldogs without previous surgery were recruited for this prospective, pilot study. Computed tomography was performed using conscious sedation and without endotracheal intubation using a 128 multidetector computed tomography scanner. Raw multidetector computed tomography data were rendered to create a three-dimensional surface mesh model by automatic segmentation of the air-filled nasal passage from the nares to the caudal soft palate. Three-dimensional surface models were used to construct computational fluid dynamics models of nasal airflow resistance from the nares to the caudal aspect of the soft palate. The computational fluid dynamics models were used to simulate airflow in each dog and airway resistance varied widely with a median 36.46 (Pa/mm)/(l/s) and an interquartile range of 19.84 to 90.74 (Pa/mm)/(/s). In 19/21 dogs, the rostral third of the nasal passage exhibited a larger airflow resistance than the caudal and middle regions of the nasal passage. In addition, computational fluid dynamics data indicated that overall measures of airflow resistance may significantly underestimate the maximum local resistance. We conclude that computational fluid dynamics models derived from nasal multidetector computed tomography can quantify airway resistance in brachycephalic dogs. This methodology represents a novel approach to noninvasively quantify airflow resistance and may have utility for objectively studying effects of surgical interventions in canine brachycephalic airway syndrome.
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