Elizabeth A Bartlett1, Mala Ananth2, Samantha Rossano3, Mengru Zhang4, Jie Yang5, Shu-Fei Lin6, Nabeel Nabulsi6, Yiyun Huang6, Francesca Zanderigo7,8, Ramin V Parsey9,10, Christine DeLorenzo9,10. 1. Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA. Elizabeth.Bartlett@stonybrook.edu. 2. Department of Neuroscience, Stony Brook University, Stony Brook, NY, USA. 3. Department of Biomedical Engineering, Yale University, New Haven, CT, USA. 4. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA. 5. Department of Family, Population, and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA. 6. Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA. 7. Department of Psychiatry, Columbia University, New York, NY, USA. 8. Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, NY, USA. 9. Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA. 10. Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA.
Abstract
PURPOSE: To determine if one venous blood sample can substitute full arterial sampling in quantitative modeling for multiple positron emission tomography (PET) radiotracers using simultaneous estimation of the input function (SIME). PROCEDURES: Participants underwent PET imaging with [11C]ABP688, [11C]CUMI-101, and [11C]DASB. Full arterial sampling and additional venous blood draws were performed for quantification with the arterial input function (AIF) and SIME using one arterial or venous (vSIME) sample. RESULTS: Venous and arterial metabolite-corrected plasma activities were within 6 % of each other at varying time points. vSIME- and AIF-derived outcome measures were in good agreement, with optimal sampling times of 12 min ([11C]ABP688), 90 min ([11C]CUMI-101), and 100 min ([11C]DASB). Simulation-based power analyses revealed that SIME required fewer subjects than the AIF method to achieve statistical power, with significant reductions for [11C]CUMI-101 and [11C]DASB with vSIME. Replication of previous findings and test-retest analyses bolstered the simulation analyses. CONCLUSIONS: We demonstrate the feasibility of AIF recovery using SIME with one venous sample for [11C]ABP688, [11C]CUMI-101, and [11C]DASB. This method simplifies PET acquisition while allowing for fully quantitative modeling, although some variability and bias are present with respect to AIF-based quantification, which may depend on the accuracy of the single venous blood measurement.
PURPOSE: To determine if one venous blood sample can substitute full arterial sampling in quantitative modeling for multiple positron emission tomography (PET) radiotracers using simultaneous estimation of the input function (SIME). PROCEDURES: Participants underwent PET imaging with [11C]ABP688, [11C]CUMI-101, and [11C]DASB. Full arterial sampling and additional venous blood draws were performed for quantification with the arterial input function (AIF) and SIME using one arterial or venous (vSIME) sample. RESULTS: Venous and arterial metabolite-corrected plasma activities were within 6 % of each other at varying time points. vSIME- and AIF-derived outcome measures were in good agreement, with optimal sampling times of 12 min ([11C]ABP688), 90 min ([11C]CUMI-101), and 100 min ([11C]DASB). Simulation-based power analyses revealed that SIME required fewer subjects than the AIF method to achieve statistical power, with significant reductions for [11C]CUMI-101 and [11C]DASB with vSIME. Replication of previous findings and test-retest analyses bolstered the simulation analyses. CONCLUSIONS: We demonstrate the feasibility of AIF recovery using SIME with one venous sample for [11C]ABP688, [11C]CUMI-101, and [11C]DASB. This method simplifies PET acquisition while allowing for fully quantitative modeling, although some variability and bias are present with respect to AIF-based quantification, which may depend on the accuracy of the single venous blood measurement.
Authors: Elisa Roccia; Arthur Mikhno; Francesca Zanderigo; Elsa D Angelini; R Todd Ogden; J John Mann; Andrew F Laine Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2015
Authors: Ramin V Parsey; Victoria Arango; Doreen M Olvet; Maria A Oquendo; Ronald L Van Heertum; J John Mann Journal: J Cereb Blood Flow Metab Date: 2005-07 Impact factor: 6.200
Authors: Kenji Ishibashi; Chelsea L Robertson; Mark A Mandelkern; Andrew T Morgan; Edythe D London Journal: Mol Imaging Date: 2013 Nov-Dec Impact factor: 4.488
Authors: Valerie Treyer; Johannes Streffer; Matthias T Wyss; Andrea Bettio; Simon M Ametamey; Uta Fischer; Mark Schmidt; Fabrizio Gasparini; Christoph Hock; Alfred Buck Journal: J Nucl Med Date: 2007-06-15 Impact factor: 10.057
Authors: Rajapillai L I Pillai; Elizabeth A Bartlett; Mala R Ananth; Chencan Zhu; Jie Yang; Greg Hajcak; Ramin V Parsey; Christine DeLorenzo Journal: Neuroimage Date: 2020-03-10 Impact factor: 6.556
Authors: Nadine M Melhem; Yongqi Zhong; Jeffrey M Miller; Francesca Zanderigo; R Todd Ogden; M Elizabeth Sublette; Madison Newell; Ainsley Burke; John G Keilp; Mohammad Lesanpezeshki; Elizabeth Bartlett; David A Brent; J John Mann Journal: Int J Neuropsychopharmacol Date: 2022-01-12 Impact factor: 5.176
Authors: Martin J Lan; Francesca Zanderigo; Spiro P Pantazatos; M Elizabeth Sublette; Jeffrey Miller; R Todd Ogden; J John Mann Journal: Int J Neuropsychopharmacol Date: 2022-08-04 Impact factor: 5.678
Authors: Mala Ananth; Elizabeth A Bartlett; Christine DeLorenzo; Xuejing Lin; Laura Kunkel; Nehal P Vadhan; Greg Perlman; Michala Godstrey; Daniel Holzmacher; R Todd Ogden; Ramin V Parsey; Chuan Huang Journal: Eur J Nucl Med Mol Imaging Date: 2020-02-13 Impact factor: 9.236