{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T23:18:36Z","timestamp":1788304716249,"version":"build-2803163510"},"reference-count":29,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:00:00Z","timestamp":1740096000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:00:00Z","timestamp":1740096000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Cereb Blood Flow Metab"],"published-print":{"date-parts":[[2025,7]]},"abstract":"\n Quantification of dopamine transporter (DAT) with [\n 18<\/jats:sup>\n F]FE-PE2I PET is an important progression marker for Parkinson\u2019s disease (PD). This study aimed to validate a novel correction (\n SUVR<\/jats:italic>\n c) for a less-biased estimate of\n SUVR<\/jats:italic>\n by accounting for [\n 18<\/jats:sup>\n F]FE-PE2I clearance-rate, in independent cross-sectional (38 PD, 38 controls), test-retest (9 PD) and longitudinal cohorts (21 PD).\n SUVR<\/jats:italic>\n c was calculated as\n \n \n \n \n SUVR<\/mml:mi>\n <\/mml:mrow>\n \n 1<\/mml:mn>\n \u00a0<\/mml:mi>\n \u2212<\/mml:mo>\n \u00a0<\/mml:mi>\n \n \n \n \n \u03b2<\/mml:mi>\n <\/mml:mrow>\n \n ref<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n \n \n \n k<\/mml:mi>\n <\/mml:mrow>\n \n 2<\/mml:mn>\n ,<\/mml:mo>\n ref<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n <\/mml:mfrac>\n \u00a0<\/mml:mi>\n +<\/mml:mo>\n \n \n \u03b2<\/mml:mi>\n <\/mml:mrow>\n \n tar<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n \n \n SUVR<\/mml:mi>\n <\/mml:mrow>\n \n \n \n k<\/mml:mi>\n <\/mml:mrow>\n \n 2<\/mml:mn>\n ,<\/mml:mo>\n ref<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n \n \n R<\/mml:mi>\n <\/mml:mrow>\n \n 1<\/mml:mn>\n <\/mml:mrow>\n <\/mml:msub>\n <\/mml:mrow>\n <\/mml:mfrac>\n <\/mml:mrow>\n <\/mml:mfrac>\n <\/mml:math>\n <\/jats:inline-formula>\n .\n \u03b2<\/jats:italic>\n tar<\/jats:sub>\n and\n \u03b2<\/jats:italic>\n ref<\/jats:sub>\n are the clearance rates from the target and reference tissues. Bias relative to\n DVR<\/jats:italic>\n , discriminative power, test-retest variability (TRV) and annual longitudinal change (ALC) were used to compare\n SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n ,\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n ,\n SUVR<\/jats:italic>\n 15\u201345\u2009min<\/jats:sub>\n and\n DVR. SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n showed high bias across all regions (HC: mean: 48.31\u2009\u00b1\u200920.49% [range: 28.32\u201353.80%]; PD: 29.91\u2009\u00b1\u200913.95% [20.45\u201339.80%]) that was corrected by\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n (HC: \u22120.80\u2009\u00b1\u200912.72% [\u22129.69\u201311.64%]; PD: \u22120.13\u2009\u00b1\u20097.41% [\u22125.04\u20132.97%]),\n p\u2009<\u2009<\/jats:italic>\n 0.001 for both groups compared to mean bias of\n SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n , similar to\n SUVR<\/jats:italic>\n 15\u201345\u2009min<\/jats:sub>\n . For the striatum, Cohen\u2019s\n d<\/jats:italic>\n was similar for all measures. TRV were 3.2\u2009\u00b1\u20092.5% (\n DVR<\/jats:italic>\n ), 6.4\u2009\u00b1\u20095.7% (\n SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n ), 6.8\u2009\u00b1\u20095.9% (\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n ) and 3.9\u2009\u00b1\u20093.2% (\n SUVR<\/jats:italic>\n 15\u201345\u2009min<\/jats:sub>\n ). Higher TRV of\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n was due to TRV of 9.2\u2009\u00b1\u20095.1% [1.1\u201319.4] for \u03b2\n tar<\/jats:sub>\n . ALC was 4.5\u2009\u00b1\u20094.2% (\n DVR<\/jats:italic>\n ), 5.2\u2009\u00b1\u20096.5% (\n SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n ), 4.4\u2009\u00b1\u20094.1% (\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n ) and 4.2\u2009\u00b1\u20094.1% (\n SUVR<\/jats:italic>\n 15\u201345\u2009min<\/jats:sub>\n ).\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n reduced bias compared to\n SUVR<\/jats:italic>\n 50\u201380\u2009min<\/jats:sub>\n , as previously reported.\n SUVR<\/jats:italic>\n c\n 50\u201380\u2009min<\/jats:sub>\n was sensitive to small changes of \u03b2\n tar<\/jats:sub>\n , with higher TRV compared to\n DVR<\/jats:italic>\n , but with similar ALC, suggesting that it can reliably assess longitudinal DAT changes.\n <\/jats:p>","DOI":"10.1177\/0271678x251322407","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T05:19:05Z","timestamp":1740115145000},"page":"1357-1370","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Correcting\n SUVR<\/i>\n bias by accounting for radiotracer clearance in tissue: A validation study with [\n 18<\/sup>\n F]FE-PE2I PET in cross-sectional, test-retest and longitudinal cohorts"],"prefix":"10.1177","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6840-3215","authenticated-orcid":false,"given":"Minyoung","family":"Oh","sequence":"first","affiliation":[{"name":"Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden"},{"name":"Asan Medical 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