{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["10(21)"],"submitter":["Zhang X"],"pubmed_abstract":["<h4>Background</h4>Coronary angiography (CAG) is usually performed in patients with coronary heart disease (CHD) to evaluate the coronary artery stenosis. However, patients with iodine allergy and renal dysfunction are not suitable for CAG. We try to develop a radiomics machine learning model based on rest <sup>13</sup>N-ammonia (<sup>13</sup>N-NH<sub>3</sub>) positron emission tomography (PET) myocardial perfusion imaging (MPI) to predict coronary stenosis.<h4>Methods</h4>Eighty-four patients were included with the inclusion criteria: adult patients; suspected CHD; resting MPI and CAG were performed; and complete data. Coronary artery stenosis >75% were considered to be significant stenosis. Patients were randomly divided into a training group and a testing group with a ratio of 1:1. Myoc"],"journal":["Annals of translational medicine"],"pagination":["1167"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9708489"],"repository":["biostudies-literature"],"pubmed_title":["Development and evaluation of a radiomics model of resting <sup>13</sup>N-ammonia positron emission tomography myocardial perfusion imaging to predict coronary artery stenosis in patients with suspected coronary heart disease."],"pmcid":["PMC9708489"],"pubmed_authors":["Wang Q","Wang S","Zhang X","Sun T","Liu E","Xu W"],"additional_accession":[]},"is_claimable":false,"name":"Development and evaluation of a radiomics model of resting <sup>13</sup>N-ammonia positron emission tomography myocardial perfusion imaging to predict coronary artery stenosis in patients with suspected coronary heart disease.","description":"<h4>Background</h4>Coronary angiography (CAG) is usually performed in patients with coronary heart disease (CHD) to evaluate the coronary artery stenosis. However, patients with iodine allergy and renal dysfunction are not suitable for CAG. We try to develop a radiomics machine learning model based on rest <sup>13</sup>N-ammonia (<sup>13</sup>N-NH<sub>3</sub>) positron emission tomography (PET) myocardial perfusion imaging (MPI) to predict coronary stenosis.<h4>Methods</h4>Eighty-four patients were included with the inclusion criteria: adult patients; suspected CHD; resting MPI and CAG were performed; and complete data. Coronary artery stenosis >75% were considered to be significant stenosis. Patients were randomly divided into a training group and a testing group with a ratio of 1:1. Myoc","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Nov","modification":"2025-04-22T03:59:34.206Z","creation":"2025-04-05T20:53:52.614Z"},"accession":"S-EPMC9708489","cross_references":{"pubmed":["36467349"],"doi":["10.21037/atm-22-4692"]}}