2022
DOI: 10.1016/j.ejps.2022.106272
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A computed tomography imaging-based subject-specific whole-lung deposition model

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Cited by 10 publications
(5 citation statements)
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References 54 publications
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“…C1 and C2 subjects demonstrated a significant reduction in lung deformation when contrasted with C0 subjects. This feature was evident in the lung size at TLC ( Table S1 ), being in agreement with Zhang et al (2022) . The size reduction at TLC signifying a decline in respiratory muscle strength within both clusters ( McNarry et al, 2022 ).…”
Section: Discussionsupporting
confidence: 81%
See 1 more Smart Citation
“…C1 and C2 subjects demonstrated a significant reduction in lung deformation when contrasted with C0 subjects. This feature was evident in the lung size at TLC ( Table S1 ), being in agreement with Zhang et al (2022) . The size reduction at TLC signifying a decline in respiratory muscle strength within both clusters ( McNarry et al, 2022 ).…”
Section: Discussionsupporting
confidence: 81%
“…While C0 and C2 subjects did not differ significantly in CV, C1 subjects had higher CV values than others (p<0.05). The selection of 0.5 μm particles enabled a comparison with our previous study involving COPD subjects ( Zhang et al, 2022 ), which used Technetium-99 m sulfur colloid (< 1.0 μm) for ventilation SPECT imaging.…”
Section: Resultsmentioning
confidence: 99%
“…on the wall of the trachea and main bronchi 17 . Similar results on the movement of particles in a study on a respiratory tract model, which excluded the mouth-throat region were confirmed by Zhang et al They confirmed that large particles of around 10.0 µm were retained in the central airways, trachea and main bronchi by sedimentation 18 .…”
Section: Discussionsupporting
confidence: 75%
“…It is not possible to fully replicate real-life settings, for example physiological factors including lung surface features and airway humidity [19,38], and the complex process of aerosolization [19,39]. However, CT scanning and modeling is increasingly being used to assess lung deposition [40]. In silico FRI has demonstrated consistency with SPECT/CT under similar conditions in patients with asthma [21] and consistency with scintigraphy in different populations [41][42][43], including patients with COPD; thus, in silico FRI has become an accepted estimate of lung deposition.…”
Section: Discussionmentioning
confidence: 99%