{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T09:47:59Z","timestamp":1791884879253,"version":"4.3.4"},"reference-count":41,"publisher":"Bentham Science Publishers Ltd.","license":[{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":25,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004482","name":"Kuwait University Research, Kuwait","doi-asserted-by":"publisher","award":["Grant No. NR02\/25"],"award-info":[{"award-number":["Grant No. NR02\/25"]}],"id":[{"id":"10.13039\/501100004482","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["eurekaselect.com"],"crossmark-restriction":true},"short-container-title":["CMIR"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>This study aims to evaluate reference ranges for SPECT Myocardial Perfusion Imaging (MPI) parameters using Myoview\u00ae (tetrofosmin)\nradiopharmaceutical and Myovation\u00ae processing software. This study also aims to provide a reference range for future MPI quantitative studies in\npatients with suspected heart disease and to identify significant variables associated with an abnormal left ventricular ejection fraction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Data were retrospectively collected from 1,100 MPI studies (2017-2024) with 932 participants included after excluding poor-quality images.\nImaging was performed using a GE SPECT\/CT Optima NM\/CT640 camera, and images were reconstructed using the OSEM algorithm\n(Myovation\u00ae). Volumetric and quantitative parameters were extracted for analysis (e.g., Left Ventricular Ejection Fraction (LVEF), End-Systolic\nVolume (ESV), End-Diastolic Volume (EDV), Stroke Volume (SV), and dyssynchrony parameters). Reference ranges were derived using\ndescriptive statistics, and comparative analyses examined how parameters varied by sex and age. Regression analysis and Receiver Operating\nCharacteristic (ROC) curves were used to assess the relationship between abnormal LVEF and dyssynchrony indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The study analysed 932 participants under stress and 462 at rest, yielding adequate statistical power. Average LVEF was 68% in both conditions.\nAt stress, mean EDV was 95.1 mL and mean ESV was 34.7 mL; corresponding values at rest were 104.8 mL and 40.1 mL. Diagnosis significantly\ninfluenced all volumetric and dyssynchrony parameters at rest and during stress (all p &lt; 0.001), showing progressive ventricular dilation, reduced\nLVEF, and increased dyssynchrony from the normal to the ischemic and infarcted groups. Sex significantly affected LVEF and ventricular\nvolumes, with females exhibiting higher LVEF and smaller volumes, while age had minimal effects. Resting dyssynchrony indices correlated\nstrongly with stress LVEF, particularly in diseased groups. Logistic regression demonstrated good discrimination (AUC = 0.80) and calibration,\nidentifying resting volumetric and clinical factors as independent predictors of abnormal stress LVEF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion:<\/jats:title>\n                    <jats:p>This study defines sex- and age-specific reference ranges for gated SPECT MPI\u2013derived ventricular function in a Kuwaiti population. Ventricular\nvolumes, systolic function, and dyssynchrony varied significantly by sex and diagnosis, with progressive impairment across disease groups.\nLogistic regression analysis with multiple variables identified resting volumetric indices and demographic characteristics, rather than dyssynchrony\nmeasures, as the primary independent predictors of abnormal left ventricular function during stress. The model demonstrated good discriminatory\nability and calibration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Sex- and age-specific reference ranges for gated SPECT MPI reveal clinically meaningful variation in ventricular function and dyssynchrony by\ndiagnosis. Logistic regression findings indicate that conventional ventricular volumes and patient characteristics primarily drive stress systolic\nimpairment, while dyssynchrony indices offer complementary but not independent prognostic value.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2174\/0115734056444403260202075613","type":"journal-article","created":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T18:07:45Z","timestamp":1771178865000},"update-policy":"https:\/\/doi.org\/10.2174\/bsp_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Volumetric Reference Ranges for SPECT MPI Parameters and the Predictive Power of Dyssynchrony Parameters: A Cross-Sectional Study"],"prefix":"10.2174","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8018-3585","authenticated-orcid":true,"given":"Ahmad","family":"Alenezi","sequence":"first","affiliation":[{"name":"Department of Radiologic Sciences, Kuwait University, Kuwait City, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zekun","family":"Jiang","sequence":"additional","affiliation":[{"name":"West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Alshaheen","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Jahra Hospital, Ministry of Health, Kuwait City, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zain","family":"Khurshid","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Jahra Hospital, Ministry of Health, Kuwait City, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qamar","family":"Almutawa","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Jahra Hospital, Ministry of Health, Kuwait City, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ma\u2019en","family":"AlOdat","sequence":"additional","affiliation":[{"name":"Department of Medical Laboratory Science, Faculty of Allied Medical Science, Mutah University, Karak, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"965","reference":[{"key":"ref=1","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1093\/med\/9780197521434.003.0013","author":"Gomez J.","year":"2024","unstructured":"Gomez J.; Doukky R.;  Diagnosis and Risk Assessment with SPECT MPI  2024,280-302","journal-title":"Diagnosis and Risk Assessment with SPECT MPI"},{"key":"ref=2","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1007\/s10278-022-00705-9","volume":"36","author":"Sabouri M.","year":"2022","unstructured":"Sabouri M.; Hajianfar G.; Hosseini Z.; Amini M.; Mohebi M.; Ghaedian T.; Madadi S.; Rastgou F.; Oveisi M.; Bitarafan Rajabi A.; Shiri I.; Zaidi H.; Myocardial perfusion SPECT imaging radiomic features and machine learning algorithms for cardiac contractile pattern recognition. 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