{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sato H"],"funding":["Chiba Foundation for Health Promotion and Disease Prevention","Ministry of Education, Culture, Sports, Science and Technology"],"pagination":["100442"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9525813"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9"],"pubmed_abstract":["<h4>Purpose</h4>The quantitative assessment of impaired lung motions and their association with the clinical characteristics of COPD patients is challenging. The aim of this study was to measure respiratory kinetics, including asynchronous movements, and to analyze the relationship between lung area and other clinical parameters.<h4>Materials and methods</h4>This study enrolled 10 normal control participants and 21 COPD patients who underwent dynamic MRI and pulmonary function testing (PFT). The imaging program was implemented using MATLAB®. Each lung area was detected semi-automatically on a coronal image (imaging level at the aortic valve) from the inspiratory phase to the expiratory phase. The Dice index of the manual measurements was calculated, with the relationship between lung area "],"journal":["European journal of radiology open"],"pubmed_title":["Semiautomatic assessment of respiratory dynamics using cine MRI in chronic obstructive pulmonary disease."],"pmcid":["PMC9525813"],"funding_grant_id":["19K12816","1272"],"pubmed_authors":["Suzuki T","Ye C","Shimada A","Kawata N","Iwao Y","Tatsumi K","Haneishi H","Sato H","Masuda Y"],"additional_accession":[]},"is_claimable":false,"name":"Semiautomatic assessment of respiratory dynamics using cine MRI in chronic obstructive pulmonary disease.","description":"<h4>Purpose</h4>The quantitative assessment of impaired lung motions and their association with the clinical characteristics of COPD patients is challenging. The aim of this study was to measure respiratory kinetics, including asynchronous movements, and to analyze the relationship between lung area and other clinical parameters.<h4>Materials and methods</h4>This study enrolled 10 normal control participants and 21 COPD patients who underwent dynamic MRI and pulmonary function testing (PFT). The imaging program was implemented using MATLAB®. Each lung area was detected semi-automatically on a coronal image (imaging level at the aortic valve) from the inspiratory phase to the expiratory phase. The Dice index of the manual measurements was calculated, with the relationship between lung area ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2025-04-19T11:33:01.391Z","creation":"2025-04-19T11:33:01.391Z"},"accession":"S-EPMC9525813","cross_references":{"pubmed":["36193450"],"doi":["10.1016/j.ejro.2022.100442"]}}