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Med. Biol."],"published-print":{"date-parts":[[2019,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    This study aims at assessing whether EANM harmonisation strategy combined with EQ\u00b7PET methodology could be successfully applied to harmonize brain 2-deoxy-2[\n                    <jats:sup>18<\/jats:sup>\n                    F]fluoro-D-glucose ([\n                    <jats:sup>18<\/jats:sup>\n                    F]FDG) positron emission tomography (PET) images.\n                  <\/jats:p>\n                  <jats:p>\n                    The\n                    <jats:italic>NEMA NU 2<\/jats:italic>\n                    body phantom was prepared according to the EANM guidelines with an [\n                    <jats:sup>18<\/jats:sup>\n                    F]FDG solution. Raw PET phantom data were reconstructed with three different reconstruction protocols frequently used in clinical PET brain imaging: (\n                    <jats:inline-formula\/>\n                    ) Ordered subset expectation maximization (OSEM) 3D with time of flight (TOF), 2 iterations and 21 subsets; (\n                    <jats:inline-formula\/>\n                    ) OSEM 3D with TOF, 6 iterations and 21 subsets; and (\n                    <jats:inline-formula\/>\n                    ) OSEM 3D with TOF, point spread function (PSF), and 8 iterations and 21 subsets. EQ\u00b7PET filters were computed as the Gaussian smoothing that best independently aligned the recovery coefficients (RCs) of reconstructions\n                    <jats:inline-formula\/>\n                    and\n                    <jats:inline-formula\/>\n                    with the RCs of the reference reconstruction,\n                    <jats:inline-formula\/>\n                    . The performance of the EQ\u00b7PET filter to reduce variations in quantification due to differences in reconstruction was investigated using clinical PET brain images of 35 early-onset Alzheimer\u2019s disease (EOAD) patients. Qualitative assessments and multiple quantitative metrics on the cortical surface at different scale levels with or without partial volume effect correction were evaluated on the [\n                    <jats:sup>18<\/jats:sup>\n                    F]FDG brain data before and after application of the EQ\u00b7PET filter.\n                  <\/jats:p>\n                  <jats:p>\n                    The EQ\u00b7PET methodology succeeded in finding the optimal smoothing that minimised root-mean-square error (RMSE) calculated using human brain [\n                    <jats:sup>18<\/jats:sup>\n                    F]FDG-PET datasets of EOAD patients, providing harmonized comparisons in the neurological context. Performance was superior for TOF than for TOF\u2009\u2009+\u2009\u2009PSF reconstructions.\n                  <\/jats:p>\n                  <jats:p>\n                    Results showed the capability of the EQ\u00b7PET methodology to minimize reconstruction-induced variabilities between brain [\n                    <jats:sup>18<\/jats:sup>\n                    F]FDG-PET images. However, moderate variabilities remained after harmonizing PSF reconstructions with standard non-PSF OSEM reconstructions, suggesting that precautions should be taken when using PSF modelling.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ab35b4","type":"journal-article","created":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T19:00:16Z","timestamp":1564081216000},"page":"175002","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Using EQ\u00b7PET to reduce reconstruction-dependent variations in [\n                    <sup>18<\/sup>\n                    F]FDG-PET brain imaging"],"prefix":"10.1088","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9860-8193","authenticated-orcid":false,"given":"Matthieu","family":"Vanhoutte","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Franck","family":"Semah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renaud","family":"Lopes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alice","family":"Jaillard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gr\u00e9gory","family":"Petyt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anne-Laure","family":"Aziz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H\u00e9l\u00e8ne","family":"Lahousse","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00e9r\u00f4me","family":"Declerck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florence","family":"Pasquier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruce","family":"Spottiswoode","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8277-6125","authenticated-orcid":false,"given":"Rachid","family":"Fahmi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2019,8,28]]},"reference":[{"key":"pmbab35b4bib001","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/s00259-017-3740-2","type":"journal-article","article-title":"EANM\/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies","volume":"44","author":"Aide","year":"2017","journal-title":"Eur. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2019-03-19","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2019-07-25","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2019-08-28","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}