title: A case series on lung deposition analysis of inhaled medication using functional imaging based computational fluid dynamics in asthmatic patients: effect of upper airway morphology and comparison with in vivo data.
abstract: BACKGROUND
  Asthma affects 20 million Americans resulting in an economic burden of approximately $18 billion in the US alone (Allergies and Asthma Foundation 2000; National Center for Environmental Health (NCEH) 1999). Research studies based on differences in patient-specific airway morphology for asthma and the associated effect on deposition of inhaled aerosols are currently not available in the literature. Therefore, the role of morphological variations such as upper airway (extrathoracic) occlusion is not well documented.
  
  
  OBJECTIVE
  Functional imaging based computational fluid dynamics (CFD) of the respiratory airways for five asthmatic subjects is performed in this study using computed tomography (CT) based patient-specific airway models and boundary conditions.
  
  
  METHODS
  CT scans for 5 asthma patients were used to reconstruct 3D lung models using segmentation software. An averaged inhalation profile and patient-specific lobar flow distribution were used to perform the simulation. The simulations were used to obtain deposition for BDP/Formoterol® HFA pMDI in the patient-specific airway models.
  
  
  RESULTS
  The lung deposition obtained using CFD was in excellent agreement with available in vivo data using the same product. Specifically, CFD resulted in 30% lung deposition, whereas in vivo lung deposition was reported to be approximately 31%.
  
  
  CONCLUSIONS
  It was concluded that a combination of patient-specific airway models and lobar boundary conditions can be used to obtain accurate lung deposition estimates. Lower lung deposition can be expected for patients with higher extrathoracic resistance. Novel respiratory drug delivery devices need to accommodate population sub-groups based on these morphological and anatomical differences in addition to subject age.
authors.affiliation: FluidDA NV, Groeningenlei 132, Kontich 2550, Belgium. Samir.vinchurkar@fluidda.com
authors.forename: Samir
authors.initials: S
authors.lastname: Vinchurkar
authors.forename: Lieve De
authors.initials: LD
authors.lastname: Backer
authors.forename: Wim
authors.initials: W
authors.lastname: Vos
authors.forename: Cedric Van
authors.initials: CV
authors.lastname: Holsbeke
authors.forename: Jan De
authors.initials: JD
authors.lastname: Backer
authors.forename: Wilfired De
authors.initials: WD
authors.lastname: Backer
mesh_terms: D000280:Administration, Inhalation; D000328:Adult; D000336:Aerosols / Q000008:administration & dosage*; D001249:Asthma / Q000188:drug therapy; D005260:Female; D006801:Humans; D057446:Hydrodynamics; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D061330:Multidetector Computed Tomography; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D012143:Respiratory Physiological Phenomena; D012137:Respiratory System / Q000033:anatomy & histology / Q000378:metabolism*; D014057:Tomography, X-Ray Computed
chemical_list: D000336:Aerosols; D004364:Pharmaceutical Preparations