Burrowes K.S.,University of Oxford |
De Backer J.,FluidDA N.V. |
Smallwood R.,University of Sheffield |
Sterk P.J.,University of Amsterdam |
And 6 more authors.
Interface Focus | Year: 2013
The respiratory system comprises several scales of biological complexity: the genes, cells and tissues that work in concert to generate resultant function. Malfunctions of the structure or function of components at any spatial scale can result in diseases, to the detriment of gas exchange, right heart function and patient quality of life. Vast amounts of data emerge from studies across each of the biological scales; however, the question remains: how can we integrate and interpret these data in a meaningful way? Respiratory disease presents a huge health and economic burden, with the diseases asthma and chronic obstructive pulmonary disease (COPD) affecting over 500 million people worldwide. Current therapies are inadequate owing to our incomplete understanding of the disease pathophysiology and our lack of recognition of the enormous disease heterogeneity:we need to characterize this heterogeneity on a patient-specific basis to advance healthcare. In an effort to achieve this goal, the AirPROM consortium (Airway disease Predicting Outcomes through patient-specific computational Modelling) brings together a multidisciplinary team and a wealth of clinical data. Together we are developing an integrated multi-scale model of the airways in order to unravel the complex pathophysiological mechanisms occurring in the diseases asthma and COPD. © 2013 The Author(s) Published by the Royal Society. All rights reserved.
Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2009.5.3 | Award Amount: 15.53M | Year: 2011
The airways diseases asthma and chronic obstructive pulmonary disease affect over 400 million people world-wide and cause considerable morbidity and mortality. Airways disease costs the European Union in excess of 56 billion per annum. Current therapies are inadequate and we do not have sufficient tools to predict disease progression or response to current or future therapies. Our consortium, Airway Disease PRedicting Outcomes through Patient Specific Computational Modelling (AirPROM), brings together the exisiting clinical consortia (EvA FP7, U-BIOPRED IMI and BTS Severe Asthma), and expertise in physiology, radiology, image analysis, bioengineering, data harmonization, data security and ethics, computational modeling and systems biology. We shall develop an integrated multi-scale model building upon existing models. This airway model will be comprised of an integrated micro-scale and macro-scale airway model informed and validated by omic data and ex vivo models at the genome-transcriptome-cell-tissue scale and by CT and functional MRI imaging coupled to detailed physiology at the tissue-organ scale utilising Europes largest airway disease cohort. Validation will be undertaken cross-sectionally, following interventions and after longitudinal follow-up to incorporate both spatial and temporal dimensions. AirPROM has a comprehensive data management platform and a well-developed ethico-legal framework. Critically, AirPROM has an extensive exploitation plan, involving at its inception and throughout its evolution those that will develop and use the technologies emerging from this project. AirPROM therefore will bridge the critical gaps in our clinical management of airways disease, by providing validated models to predict disease progression and response to treatment and the platform to translate these patient-specific tools, so as to pave the way to improved, personalised management of airways disease.
Van Holsbeke C.S.,Fluidda nv |
Leemans G.,University of Antwerp |
Vos W.G.,Fluidda nv |
De Backer J.W.,Fluidda nv |
And 6 more authors.
Respiratory care | Year: 2014
A completely different treatment approach was chosen for 2 patients with unilateral diaphragmatic paralysis and complaints of dyspnea despite similar anatomic and physiologic abnormalities. These decisions were supported by results obtained by functional respiratory imaging (FRI). FRI generated functional information on lobar ventilation and local drug deposition. In the first patient, some lobes were poorly ventilated, and drug deposition simulation showed that some regions were undertreated. This patient underwent diaphragmatic plication to restore ventilation. In the second patient, all lobes were still ventilated. A conservative approach with regular follow-ups was chosen to wait for spontaneous recovery of the diaphragmatic function. Both patients improved subjectively and objectively. These cases demonstrate how novel medical imaging techniques such as FRI can be used to personalize respiratory treatment in patients with unilateral diaphragmatic paralysis. Copyright © 2014 by Daedalus Enterprises.
PubMed | Ghent University, Fluidda nv and University of Antwerp
Type: Case Reports | Journal: Respiratory care | Year: 2014
A completely different treatment approach was chosen for 2 patients with unilateral diaphragmatic paralysis and complaints of dyspnea despite similar anatomic and physiologic abnormalities. These decisions were supported by results obtained by functional respiratory imaging (FRI). FRI generated functional information on lobar ventilation and local drug deposition. In the first patient, some lobes were poorly ventilated, and drug deposition simulation showed that some regions were undertreated. This patient underwent diaphragmatic plication to restore ventilation. In the second patient, all lobes were still ventilated. A conservative approach with regular follow-ups was chosen to wait for spontaneous recovery of the diaphragmatic function. Both patients improved subjectively and objectively. These cases demonstrate how novel medical imaging techniques such as FRI can be used to personalize respiratory treatment in patients with unilateral diaphragmatic paralysis.
Vos W.,FluidDA Nv |
Backer J.D.,FluidDA Nv |
Poli G.,Chiesi Pharmaceuticals |
De Volder A.,University of Antwerp |
And 5 more authors.
Respiration | Year: 2013
Background: Inhaled formulations using extrafine particles of long-acting β2-agonists and corticosteroids were developed to optimize asthma treatment. Findings that these combinations reach and treat smaller airways more effectively are predominantly based on general non-specific outcomes with little information on regional characteristics. Objectives: This study aims to assess long-term effects of extrafine beclomethasone/formoterol on small airways of asthmatic patients using novel functional imaging methods. Methods: Twenty-four stable asthma patients were subdivided into three groups (steroid naive, n = 7; partially controlled, n = 6; well controlled, n = 11). Current treatment was switched to a fixed combination of extrafine beclomethasone/formoterol (Foster®; Chiesi Pharmaceuticals, Parma, Italy). Patients underwent lung function evaluation and thorax high-resolution computerized tomography (HRCT) scan. Local airway resistance was obtained from computational fluid dynamics (CFD). Results: After 6 months, the entire population showed improvement in pre-bronchodilation imaging parameters, including small airway volume (p = 0.0007), resistance (p = 0.011), and asthma control score (p = 0.016). Changes in small airway volume correlated with changes in asthma control score (p = 0.004). Forced expiratory volume in 1 s (p = 0.044) and exhaled nitric oxide (p = 0.040) also improved. Functional imaging provided more detail and clinical relevance compared to lung function tests, especially in the well-controlled group where only functional imaging parameters showed significant improvement, while the correlation with asthma control score remained. Conclusions: Extrafine beclomethasone/formoterol results in a significant reduction of small airway obstruction, detectable by functional imaging (HRCT/CFD). Changes in imaging parameters correlated significantly with clinically relevant improvements. This indicates that functional imaging is a useful tool for sensitive assessment of changes in the respiratory system after asthma treatment. Copyright © 2013 S. Karger AG, Basel.
De Backer J.,FluidDA nv |
Vos W.,FluidDA nv |
Van Holsbeke C.,FluidDA nv |
Vinchurkar S.,FluidDA nv |
And 3 more authors.
International Journal of COPD | Year: 2013
Background: Previous studies have demonstrated the potential beneficial effect of N-acetylcysteine (NAC) in chronic obstructive pulmonary disease (COPD). However, the required dose and responder phenotype remain unclear. The current study investigated the effect of high-dose NAC on airway geometry, inflammation, and oxidative stress in COPD patients. Novel functional respiratory imaging methods combining multislice computed tomography images and computer-based flow simulations were used with high sensitivity for detecting changes induced by the therapy. Methods: Twelve patients with Global Initiative for Chronic Obstructive Lung Disease stage II COPD were randomized to receive NAC 1800 mg or placebo daily for 3 months and were then crossed over to the alternative treatment for a further 3 months. Results: Significant correlations were found between image-based resistance values and glutathione levels after treatment with NAC (P = 0.011) and glutathione peroxidase at baseline (P = 0.036). Image-based resistance values appeared to be a good predictor for glutathione peroxidase levels after NAC (P = 0.02), changes in glutathione peroxidase levels (P = 0.035), and reduction in lobar functional residual capacity levels (P = 0.00084). In the limited set of responders to NAC therapy, the changes in airway resistance were in the same order as changes induced by budesonide/formoterol. Conclusion: A combination of glutathione, glutathione peroxidase, and imaging parameters could potentially be used to phenotype COPD patients who would benefit from addition of NAC to their current therapy. The findings of this small pilot study need to be confirmed in a larger pivotal trial. © 2013 De Backer et al.
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
Vinchurkar S.,FluidDA NV |
De Backer L.,University of Antwerp |
Vos W.,FluidDA NV |
Van Holsbeke C.,FluidDA NV |
And 2 more authors.
Inhalation Toxicology | Year: 2012
Context: Asthma affects 20 million Americans resulting in an economic burden of approximately18 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%. Conclusion: 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. © 2012 Informa Healthcare USA, Inc.