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| * lung nodules | * lung nodules | ||
| - | Imalife ran from 2017 to 2022. | + | Participants with a lung nodule between 100-300 mm3 (~5,4% of all scanned participants) were invited for a repeat CT scan after 3-4 months for scientific purposes, to evaluate natural evolution of lung nodules in the general population. |
| ===== Subcohort ===== | ===== Subcohort ===== | ||
| - | Imalife was performed in ~12.000 Lifelines [[cohort|participants]] of ≥45 years who completed a [[pulmonary function test]]. | + | Imalife ran from 2017 to 2022. The assessments were performed in ~12.000 Lifelines [[cohort|participants]] of 45+ years who completed a [[pulmonary function test]].\\ |
| + | To ensure sufficient participants in the older age groups, selection criteria were later adjusted to 60+ and, in the final phase, 75+. | ||
| ===== Publications using Imalife data ===== | ===== Publications using Imalife data ===== | ||
| - | * Xia, C et al. (2019) Cardiovascular Risk Factors and Coronary Calcification in a Middle-aged Dutch Population. Journal of Thoracic Imaging 36(3): 174-180 | + | * Xia, C et al. (2019) [[https://journals.lww.com/thoracicimaging/fulltext/2021/05000/cardiovascular_risk_factors_and_coronary.6.aspx|Cardiovascular Risk Factors and Coronary Calcification in a Middle-aged Dutch Population]]. Journal of Thoracic Imaging 36(3): 174-180 |
| - | * Van den Oever L.B. et al. (2020) Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium. European Journal of Radiology 129, 109114 | + | * Van den Oever L.B. et al. (2020) [[https://linkinghub.elsevier.com/retrieve/pii/S0720-048X(20)30303-X|Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium]]. European Journal of Radiology 129, 109114 |
| - | * Xia, C et al. (2021) High-pitch dual-source CT for coronary artery calcium scoring: A head-to-head comparison of non-triggered chest versus triggered cardiac acquisition. Journal of Cardiovascular Computed Tomography 15(1): 65-72 | + | * Xia, C et al. (2021) [[https://linkinghub.elsevier.com/retrieve/pii/S1934-5925(20)30145-3|High-pitch dual-source CT for coronary artery calcium scoring: A head-to-head comparison of non-triggered chest versus triggered cardiac acquisition]]. Journal of Cardiovascular Computed Tomography 15(1): 65-72 |
| - | * Lancaster, H et al. (2021) Seasonal prevalence and characteristics of low-dose CT detected lung nodules in a general Dutch population. Sci Rep 11(1): 9139 | + | * Lancaster, H et al. (2021) [[https://www.nature.com/articles/s41598-021-88328-y|Seasonal prevalence and characteristics of low-dose CT detected lung nodules in a general Dutch population]]. Sci Rep 11(1): 9139 |
| - | * Cai, J. et al. (2022) CT characteristics of solid pulmonary nodules of never smokers versus smokers: A population-based study. Eur J Radiol 154:110410 | + | * Dudurych, I. et al. (2021) [[https://eurradiolexp.springeropen.com/articles/10.1186/s41747-021-00247-9|Creating a training set for artificial intelligence from initial segmentations of airways]] Eur Rad Exp 5, 54 |
| - | * Wisselink, H. et al. (2023) Predicted versus CT-derived total lung volume in a general population: The ImaLife study. Plos ONE 18(6):e0287383 | + | * Cai, J. et al. (2022) [[https://www.sciencedirect.com/science/article/pii/S0720048X22002601?via%3Dihub|CT characteristics of solid pulmonary nodules of never smokers versus smokers: A population-based study]]. Eur J Radiol 154:110410 |
| - | * Dudurych, I. et al. (2023) Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction. Eur Radiol in press | + | * Wisselink, H. et al. (2023) [[https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287383|Predicted versus CT-derived total lung volume in a general population: The ImaLife study]]. Plos ONE 18(6):e0287383 |
| + | * Dudurych, I. et al. (2023) [[https://link.springer.com/article/10.1007/s00330-023-09615-y|Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction]]. Eur Radiol 33, 6718–6725 | ||
| + | * Wisselink, H et al (2023) [[https://www.sciencedirect.com/science/article/pii/S0720048X23000232?via%3Dihub|CT-based emphysema characterization per lobe: A proof of concept]] Eur J Rad 160, 110709 | ||
| + | * Cai, J et al. (2024) [[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11154756/|Who is at risk of lung nodules on low-dose CT in a Western country? A population-based approach]] ERJ Open 63(6): 2301736 | ||
| + | * Sourlos, N. et al. (2024) [[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11102890/|Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT]] Eur Radiol Exp 8(1):63 | ||
| + | * Dudurych I et al. (2024) [[https://pubs.rsna.org/doi/epdf/10.1148/radiol.232677|Low-dose CT–derived bronchial parameters in individuals with healthy lungs]] Radiology 311(3):e23267 | ||
| ===== Variables ===== | ===== Variables ===== | ||
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