A whole lung in silico model to estimate age dependent particle dosimetry
Abstract Anatomical and physiological changes alter airflow characteristics and aerosol distribution in the developing lung. Correlation between age and aerosol dosimetry is needed, specifically because youth are more susceptible to medication side effects. In this study, we estimate aerosol dosages...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-05-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-90509-8 |
| _version_ | 1819038955700486144 |
|---|---|
| author | Kamran Poorbahrami Irene E. Vignon-Clementel Shawn C. Shadden Jessica M. Oakes |
| author_facet | Kamran Poorbahrami Irene E. Vignon-Clementel Shawn C. Shadden Jessica M. Oakes |
| author_sort | Kamran Poorbahrami |
| collection | DOAJ |
| description | Abstract Anatomical and physiological changes alter airflow characteristics and aerosol distribution in the developing lung. Correlation between age and aerosol dosimetry is needed, specifically because youth are more susceptible to medication side effects. In this study, we estimate aerosol dosages (particle diameters of 1, 3, and 5 $$\upmu$$ μ m) in a 3 month-old infant, a 6 year-old child, and a 36 year-old adult by performing whole lung subject-specific particle simulations throughout respiration. For 3 $$\upmu$$ μ m diameter particles we estimate total deposition as 88, 73, and $$66\%$$ 66 % and the conducting versus respiratory deposition ratios as 4.0, 0.5, and 0.4 for the infant, child, and adult, respectively. Due to their lower tidal volumes and functional residual capacities the deposited mass is smaller while the tissue concentrations are larger in the infant and child subjects, compared to the adult. Furthermore, we find that dose cannot be predicted by simply scaling by tidal volumes. These results highlight the need for additional clinical and computational studies that investigate the efficiency of treatment, while optimizing dosage levels in order to alleviate side effects, in youth. |
| first_indexed | 2024-12-21T08:45:32Z |
| format | Article |
| id | doaj.art-9f1faad053c34f50b0d9bf7665e4e011 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-21T08:45:32Z |
| publishDate | 2021-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-9f1faad053c34f50b0d9bf7665e4e0112022-12-21T19:09:50ZengNature PortfolioScientific Reports2045-23222021-05-0111111210.1038/s41598-021-90509-8A whole lung in silico model to estimate age dependent particle dosimetryKamran Poorbahrami0Irene E. Vignon-Clementel1Shawn C. Shadden2Jessica M. Oakes3Department of Mechanical and Industrial Engineering, Northeastern UniversityInria Saclay-Ile-de-FranceDepartment of Mechanical Engineering, University of California BerkeleyDepartment of Bioengineering, Northeastern UniversityAbstract Anatomical and physiological changes alter airflow characteristics and aerosol distribution in the developing lung. Correlation between age and aerosol dosimetry is needed, specifically because youth are more susceptible to medication side effects. In this study, we estimate aerosol dosages (particle diameters of 1, 3, and 5 $$\upmu$$ μ m) in a 3 month-old infant, a 6 year-old child, and a 36 year-old adult by performing whole lung subject-specific particle simulations throughout respiration. For 3 $$\upmu$$ μ m diameter particles we estimate total deposition as 88, 73, and $$66\%$$ 66 % and the conducting versus respiratory deposition ratios as 4.0, 0.5, and 0.4 for the infant, child, and adult, respectively. Due to their lower tidal volumes and functional residual capacities the deposited mass is smaller while the tissue concentrations are larger in the infant and child subjects, compared to the adult. Furthermore, we find that dose cannot be predicted by simply scaling by tidal volumes. These results highlight the need for additional clinical and computational studies that investigate the efficiency of treatment, while optimizing dosage levels in order to alleviate side effects, in youth.https://doi.org/10.1038/s41598-021-90509-8 |
| spellingShingle | Kamran Poorbahrami Irene E. Vignon-Clementel Shawn C. Shadden Jessica M. Oakes A whole lung in silico model to estimate age dependent particle dosimetry Scientific Reports |
| title | A whole lung in silico model to estimate age dependent particle dosimetry |
| title_full | A whole lung in silico model to estimate age dependent particle dosimetry |
| title_fullStr | A whole lung in silico model to estimate age dependent particle dosimetry |
| title_full_unstemmed | A whole lung in silico model to estimate age dependent particle dosimetry |
| title_short | A whole lung in silico model to estimate age dependent particle dosimetry |
| title_sort | whole lung in silico model to estimate age dependent particle dosimetry |
| url | https://doi.org/10.1038/s41598-021-90509-8 |
| work_keys_str_mv | AT kamranpoorbahrami awholelunginsilicomodeltoestimateagedependentparticledosimetry AT ireneevignonclementel awholelunginsilicomodeltoestimateagedependentparticledosimetry AT shawncshadden awholelunginsilicomodeltoestimateagedependentparticledosimetry AT jessicamoakes awholelunginsilicomodeltoestimateagedependentparticledosimetry AT kamranpoorbahrami wholelunginsilicomodeltoestimateagedependentparticledosimetry AT ireneevignonclementel wholelunginsilicomodeltoestimateagedependentparticledosimetry AT shawncshadden wholelunginsilicomodeltoestimateagedependentparticledosimetry AT jessicamoakes wholelunginsilicomodeltoestimateagedependentparticledosimetry |