Emily Nicole Holy, Elizabeth Li, Anjan Bhattarai, Evan Fletcher, Evelyn R. Alfaro, Danielle J. Harvey, Benjamin A. Spencer, Simon R. Cherry, Charles S. DeCarli, Audrey P. Fan
{"title":"Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET","authors":"Emily Nicole Holy, Elizabeth Li, Anjan Bhattarai, Evan Fletcher, Evelyn R. Alfaro, Danielle J. Harvey, Benjamin A. Spencer, Simon R. Cherry, Charles S. DeCarli, Audrey P. Fan","doi":"10.1186/s13550-024-01104-7","DOIUrl":null,"url":null,"abstract":"Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort. 18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer’s disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ( $$ {BP}_{ND})$$ was also calculated from the multi-reference tissue model (MRTM). Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with $$ {BP}_{ND}$$ analysis. $$ {BP}_{ND} $$ and VT from kinetic models were correlated (r² = 0.46, P < 2 $$ {e}^{-16})$$ with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ( $$ {r}^{2}$$ = 0.65, P < 2 $$ {e}^{-16}$$ ) with Logan graphical VT estimation. Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to $$ {BP}_{ND} $$ in amyloid-positive and amyloid-negative older individuals.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13550-024-01104-7","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort. 18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer’s disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ( $$ {BP}_{ND})$$ was also calculated from the multi-reference tissue model (MRTM). Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with $$ {BP}_{ND}$$ analysis. $$ {BP}_{ND} $$ and VT from kinetic models were correlated (r² = 0.46, P < 2 $$ {e}^{-16})$$ with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ( $$ {r}^{2}$$ = 0.65, P < 2 $$ {e}^{-16}$$ ) with Logan graphical VT estimation. Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to $$ {BP}_{ND} $$ in amyloid-positive and amyloid-negative older individuals.