{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T02:34:16Z","timestamp":1789266856009,"version":"build-2803163510"},"reference-count":40,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T00:00:00Z","timestamp":1773100800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Zeitschrift f\u00fcr Medizinische Physik"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.zemedi.2026.03.009","type":"journal-article","created":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T23:35:55Z","timestamp":1774136155000},"page":"390-398","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Novel Quantitative Analysis in Myocardial Perfusion Imaging: How does it compare to the \u201cGolden Eye\u201d?"],"prefix":"10.1016","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2961-3126","authenticated-orcid":false,"given":"Yue","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juncheng","family":"Ni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Esteban Lucas","family":"Solari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto Villagran","family":"Asiares","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8817-1482","authenticated-orcid":false,"given":"Stephan G.","family":"Nekolla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.zemedi.2026.03.009_b0005","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1007\/s12410-012-9131-y","article-title":"Quantification of Myocardial Perfusion: SPECT","volume":"5","author":"Petretta","year":"2012","journal-title":"Current Cardiovascular Imaging Reports."},{"issue":"7","key":"10.1016\/j.zemedi.2026.03.009_b0010","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1038\/s41569-020-0341-8","article-title":"Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia","volume":"17","author":"Dewey","year":"2020","journal-title":"Nat Rev Cardiol."},{"issue":"2","key":"10.1016\/j.zemedi.2026.03.009_b0015","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1067\/mnc.2002.123122","article-title":"Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association","volume":"9","author":"Cerqueira","year":"2002","journal-title":"J Nucl Cardiol."},{"issue":"5","key":"10.1016\/j.zemedi.2026.03.009_b0020","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1007\/s12350-010-9246-y","article-title":"Single photon-emission computed tomography","volume":"17","author":"Holly","year":"2010","journal-title":"J Nucl Cardiol."},{"issue":"5","key":"10.1016\/j.zemedi.2026.03.009_b0025","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1161\/01.CIR.64.5.924","article-title":"Improved noninvasive assessment of coronary artery disease by quantitative analysis of regional stress myocardial distribution and washout of thallium-201","volume":"64","author":"Maddahi","year":"1981","journal-title":"Circulation."},{"issue":"12","key":"10.1016\/j.zemedi.2026.03.009_b0030","first-page":"2041","article-title":"Automated interpretation of planar thallium-201-dipyridamole stress-redistribution scintigrams using artificial neural networks","volume":"35","author":"Porenta","year":"1994","journal-title":"J Nucl Med."},{"issue":"1","key":"10.1016\/j.zemedi.2026.03.009_b0035","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.nuclcard.2004.10.006","article-title":"Automated quantification of myocardial perfusion SPECT using simplified normal limits","volume":"12","author":"Slomka","year":"2005","journal-title":"J Nucl Cardiol."},{"issue":"2","key":"10.1016\/j.zemedi.2026.03.009_b0040","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1161\/01.CIR.77.2.316","article-title":"Quantitative rotational thallium-201 tomography for identifying and localizing coronary artery disease","volume":"77","author":"DePasquale","year":"1988","journal-title":"Circulation."},{"issue":"6","key":"10.1016\/j.zemedi.2026.03.009_b0045","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1007\/BF02577348","article-title":"Quantitative planar and tomographic thallium-201 myocardial perfusion imaging","volume":"10","author":"Garcia","year":"1987","journal-title":"Cardiovasc Intervent Radiol."},{"issue":"1","key":"10.1016\/j.zemedi.2026.03.009_b0050","first-page":"17","article-title":"Quantification of rotational thallium-201 myocardial tomography","volume":"26","author":"Garcia","year":"1985","journal-title":"J Nucl Med."},{"key":"10.1016\/j.zemedi.2026.03.009_b0055","doi-asserted-by":"crossref","DOI":"10.1007\/s12410-016-9385-x","article-title":"Normal Databases for the Relative Quantification of Myocardial Perfusion","volume":"9","author":"Rubeaux","year":"2016","journal-title":"Curr Cardiovasc Imaging Rep."},{"issue":"1","key":"10.1016\/j.zemedi.2026.03.009_b0060","doi-asserted-by":"crossref","first-page":"13583","DOI":"10.1038\/s41598-024-64445-2","article-title":"A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging","volume":"14","author":"Kusumoto","year":"2024","journal-title":"Sci Rep."},{"key":"10.1016\/j.zemedi.2026.03.009_b0065","article-title":"Machine learning algorithms for predicting coronary artery disease: efforts toward an open source solution","volume":"7(6):FSO698","author":"Akella","year":"2021","journal-title":"Future Sci OA."},{"key":"10.1016\/j.zemedi.2026.03.009_b0070","article-title":"Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps","volume":"8","author":"de Souza Filho","year":"2021","journal-title":"Front Cardiovasc Med."},{"issue":"2","key":"10.1016\/j.zemedi.2026.03.009_b0075","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1007\/s12149-021-01708-2","article-title":"The application of artificial intelligence in nuclear cardiology","volume":"36","author":"Otaki","year":"2022","journal-title":"Ann Nucl Med."},{"issue":"14","key":"10.1016\/j.zemedi.2026.03.009_b0080","doi-asserted-by":"crossref","first-page":"6362","DOI":"10.3390\/app11146362","article-title":"Automatic Diagnosis of Coronary Artery Disease in SPECT Myocardial Perfusion Imaging Employing Deep Learning","volume":"11","author":"Papandrianos","year":"2021","journal-title":"Applied Sciences."},{"key":"10.1016\/j.zemedi.2026.03.009_b0085","series-title":"Exploring Classification of SPECT MPI images applying convolutional neural networks","first-page":"483","author":"Papandrianos","year":"2022"},{"key":"10.1016\/j.zemedi.2026.03.009_b0090","doi-asserted-by":"crossref","unstructured":"Arvidsson I, Overgaard NC, \u00c5str\u00f6m K, Heyden A, Figueroa MO, Rose JF, et al., editors. Prediction of Obstructive Coronary Artery Disease from Myocardial Perfusion Scintigraphy using Deep Neural Networks. 2020 25th International Conference on Pattern Recognition (ICPR); 2021 10\u201315 Jan. 2021.","DOI":"10.1109\/ICPR48806.2021.9412674"},{"issue":"5","key":"10.1016\/j.zemedi.2026.03.009_b0095","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1093\/ehjci\/jez177","article-title":"Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry","volume":"21","author":"Hu","year":"2020","journal-title":"Eur Heart J Cardiovasc Imaging."},{"key":"10.1016\/j.zemedi.2026.03.009_b0100","unstructured":"Y. Otaki B. Tamarappoo A. Singh T. Sharir L.-H. Hu H. Gransar et al. Diagnostic Accuracy of Deep Learning for Myocardial Perfusion Imaging in Men and Women with a High-Efficiency Parallel-Hole-Collimated Cadmium-Zinc-Telluride Camera: multicenter study Journal of Nuclear Medicine. 61 2020 92."},{"issue":"2","key":"10.1016\/j.zemedi.2026.03.009_b0105","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s00259-022-05972-w","article-title":"Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images","volume":"50","author":"Miller","year":"2023","journal-title":"Eur J Nucl Med Mol Imaging."},{"issue":"11","key":"10.1016\/j.zemedi.2026.03.009_b0110","first-page":"1768","article-title":"Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging","volume":"63","author":"Miller","year":"2022","journal-title":"J Nucl Med."},{"issue":"17","key":"10.1016\/j.zemedi.2026.03.009_b0115","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1161\/CIRCULATIONAHA.108.797761","article-title":"Evaluation of the novel myocardial perfusion positron-emission tomography tracer 18F-BMS-747158-02: comparison to 13N-ammonia and validation with microspheres in a pig model","volume":"119","author":"Nekolla","year":"2009","journal-title":"Circulation."},{"issue":"3","key":"10.1016\/j.zemedi.2026.03.009_b0120","first-page":"192","article-title":"Interpreting myocardial perfusion scintigraphy using single-photon emission computed tomography. Part 1. Kardiochirurgia i Torakochirurgia Polska\/Polish","volume":"14","author":"Czaja","year":"2017","journal-title":"Journal of Thoracic and Cardiovascular Surgery."},{"key":"10.1016\/j.zemedi.2026.03.009_b0125","series-title":"Hybrid Cardiac Imaging","first-page":"83","article-title":"Dyssynchrony","author":"Malhotra","year":"2022"},{"issue":"9","key":"10.1016\/j.zemedi.2026.03.009_b0130","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1007\/s002590050301","article-title":"Reproducibility of polar map generation and assessment of defect severity and extent assessment in myocardial perfusion imaging using positron emission tomography","volume":"25","author":"Nekolla","year":"1998","journal-title":"Eur J Nucl Med."},{"key":"10.1016\/j.zemedi.2026.03.009_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2020.103893","article-title":"Classification models for SPECT myocardial perfusion imaging","volume":"123","author":"Kaplan Berkaya","year":"2020","journal-title":"Comput Biol Med."},{"issue":"1","key":"10.1016\/j.zemedi.2026.03.009_b0140","doi-asserted-by":"crossref","first-page":"7569","DOI":"10.1038\/s41598-019-43951-8","article-title":"Classification of Polar Maps from Cardiac Perfusion Imaging with Graph-Convolutional Neural Networks","volume":"9","author":"Spier","year":"2019","journal-title":"Sci Rep."},{"key":"10.1016\/j.zemedi.2026.03.009_b0145","doi-asserted-by":"crossref","unstructured":"Chattopadhay A, Sarkar A, Howlader P, Balasubramanian VN, editors. Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. 2018 IEEE Winter Conference on Applications of Computer Vision (WACV); 2018 12\u201315 March 2018.","DOI":"10.1109\/WACV.2018.00097"},{"key":"10.1016\/j.zemedi.2026.03.009_b0150","doi-asserted-by":"crossref","unstructured":"Selvaraju RR, Cogswell M, Das A, Vedantam R, Parikh D, Batra D, editors. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. 2017 IEEE International Conference on Computer Vision (ICCV); 2017 22\u201329 Oct. 2017.","DOI":"10.1109\/ICCV.2017.74"},{"key":"10.1016\/j.zemedi.2026.03.009_b0155","series-title":"2015; 2015","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.zemedi.2026.03.009_b0160","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A, editors. You Only Look Once: Unified, Real-Time Object Detection. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2016 27\u201330 June 2016.","DOI":"10.1109\/CVPR.2016.91"},{"key":"10.1016\/j.zemedi.2026.03.009_b0165","series-title":"2016; 2016","author":"He","year":"2016"},{"issue":"5","key":"10.1016\/j.zemedi.2026.03.009_b0170","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1007\/s12350-016-0582-4","article-title":"Normal limits for transient ischemic dilation with (99m)Tc myocardial perfusion SPECT protocols","volume":"24","author":"Slomka","year":"2017","journal-title":"J Nucl Cardiol."},{"issue":"3","key":"10.1016\/j.zemedi.2026.03.009_b0175","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1007\/s12350-017-1040-7","article-title":"Diagnostic and prognostic significance of transient ischemic dilation (TID) in myocardial perfusion imaging: A systematic review and meta-analysis","volume":"25","author":"Alama","year":"2018","journal-title":"J Nucl Cardiol."},{"issue":"4","key":"10.1016\/j.zemedi.2026.03.009_b0180","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1007\/s12350-012-9559-0","article-title":"Assessment of transient ischemic dilation (TID) ratio in gated SPECT myocardial perfusion imaging (MPI) using regadenoson, a new agent for pharmacologic stress testing","volume":"19","author":"Katz","year":"2012","journal-title":"J Nucl Cardiol."},{"issue":"4","key":"10.1016\/j.zemedi.2026.03.009_b0185","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1053\/j.semnuclmed.2011.02.004","article-title":"The next generation of cardiac positron emission tomography imaging agents: discovery of flurpiridaz F-18 for detection of coronary disease","volume":"41","author":"Yu","year":"2011","journal-title":"Semin Nucl Med."},{"issue":"5","key":"10.1016\/j.zemedi.2026.03.009_b0190","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1161\/01.CIR.93.5.905","article-title":"Exercise myocardial perfusion SPECT in patients without known coronary artery disease: incremental prognostic value and use in risk stratification","volume":"93","author":"Hachamovitch","year":"1996","journal-title":"Circulation."},{"issue":"7","key":"10.1016\/j.zemedi.2026.03.009_b0195","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1016\/j.jcmg.2017.07.024","article-title":"Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning","volume":"11","author":"Betancur","year":"2018","journal-title":"JACC Cardiovasc Imaging."},{"issue":"3","key":"10.1016\/j.zemedi.2026.03.009_b0200","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1016\/j.jcmg.2019.02.028","article-title":"5-Year Prognostic Value of Quantitative Versus Visual MPI in Subtle Perfusion Defects: Results From REFINE SPECT","volume":"13","author":"Otaki","year":"2020","journal-title":"JACC Cardiovasc Imaging."}],"container-title":["Zeitschrift f\u00fcr Medizinische Physik"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S093938892600022X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S093938892600022X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T14:33:51Z","timestamp":1789223631000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S093938892600022X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["S093938892600022X"],"URL":"https:\/\/doi.org\/10.1016\/j.zemedi.2026.03.009","relation":{},"ISSN":["0939-3889"],"issn-type":[{"value":"0939-3889","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Novel Quantitative Analysis in Myocardial Perfusion Imaging: How does it compare to the \u201cGolden Eye\u201d?","name":"articletitle","label":"Article Title"},{"value":"Zeitschrift f\u00fcr Medizinische Physik","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.zemedi.2026.03.009","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier GmbH on behalf of DGMP, \u00d6GMP and SSRMP.","name":"copyright","label":"Copyright"}]}}