Mika Naganawa, Jean-Dominique Gallezot, Songye Li, Nabeel B Nabulsi, Shannan Henry, Zhengxin Cai, David Matuskey, Yiyun Huang, Richard E Carson
{"title":"使用简化参考组织模型 2 对[18F]SynVesT-1 结合进行无创量化。","authors":"Mika Naganawa, Jean-Dominique Gallezot, Songye Li, Nabeel B Nabulsi, Shannan Henry, Zhengxin Cai, David Matuskey, Yiyun Huang, Richard E Carson","doi":"10.1007/s00259-024-06885-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>[<sup>18</sup>F]SynVesT-1, a positron emission tomography (PET) radiotracer for the synaptic vesicle glycoprotein 2A (SV2A), demonstrates kinetics similar to [<sup>11</sup>C]UCB-J, with high brain uptake, fast kinetics fitting well with the one-tissue compartment (1TC) model, and excellent test-retest reproducibility. Challenges arise due to the similarity between k<sub>2</sub> and [Formula: see text] (efflux rate of the reference region), when applying the simplified reference tissue model (SRTM) and related methods in [<sup>11</sup>C]UCB-J studies to accurately estimate [Formula: see text]. This study evaluated the suitability of these methods to estimate [<sup>18</sup>F]SynVesT-1 binding using centrum semiovale (CS) or cerebellum (CER) as reference regions.</p><p><strong>Method: </strong>Seven healthy participants underwent 120-min PET scans on the HRRT scanner with [<sup>18</sup>F]SynVesT-1. Six participants underwent test and retest scans. Arterial blood sampling and metabolite analysis provided input functions for the 1TC model, serving as the gold standard for kinetic parameters values. SRTM, coupled SRTM (SRTMC) and SRTM2 estimated were applied to estimate [Formula: see text](ref: CS) and DVR<sub>CER</sub>(ref: CER) values. For SRTM2, the population average of [Formula: see text] was determined from the 1TC model applied to the reference region. Test-retest variability and minimum scan time were also calculated.</p><p><strong>Results: </strong>The 1TC k<sub>2</sub> (1/min) values for CS and CER were 0.031 ± 0.004 and 0.021 ± 0.002, respectively. Although SRTMC [Formula: see text] was much higher than 1TC [Formula: see text], SRTMC underestimated BP<sub>ND</sub>(ref: CS) and DVR<sub>CER</sub> by an average of 3% and 1% across regions, respectively, due to similar bias in k<sub>2</sub> and [Formula: see text] estimation. SRTM underestimated BP<sub>ND</sub>(ref: CS) by an average of 3%, but with the CER as reference region, SRTM estimation was unstable and DVR<sub>CER</sub> underestimation varied by region (mean 10%). Using population average [Formula: see text] values, SRTM2 BP<sub>ND</sub> and DVR<sub>CER</sub> showed the best agreement with 1TC estimates.</p><p><strong>Conclusion: </strong>Our findings support the use of population [Formula: see text] value in SRTM2 with [<sup>18</sup>F]SynVesT-1 for the estimation of [Formula: see text] or DVR<sub>CER</sub>, regardless of the choice of reference region.</p>","PeriodicalId":11909,"journal":{"name":"European Journal of Nuclear Medicine and Molecular Imaging","volume":null,"pages":null},"PeriodicalIF":8.6000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Noninvasive quantification of [<sup>18</sup>F]SynVesT-1 binding using simplified reference tissue model 2.\",\"authors\":\"Mika Naganawa, Jean-Dominique Gallezot, Songye Li, Nabeel B Nabulsi, Shannan Henry, Zhengxin Cai, David Matuskey, Yiyun Huang, Richard E Carson\",\"doi\":\"10.1007/s00259-024-06885-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>[<sup>18</sup>F]SynVesT-1, a positron emission tomography (PET) radiotracer for the synaptic vesicle glycoprotein 2A (SV2A), demonstrates kinetics similar to [<sup>11</sup>C]UCB-J, with high brain uptake, fast kinetics fitting well with the one-tissue compartment (1TC) model, and excellent test-retest reproducibility. Challenges arise due to the similarity between k<sub>2</sub> and [Formula: see text] (efflux rate of the reference region), when applying the simplified reference tissue model (SRTM) and related methods in [<sup>11</sup>C]UCB-J studies to accurately estimate [Formula: see text]. This study evaluated the suitability of these methods to estimate [<sup>18</sup>F]SynVesT-1 binding using centrum semiovale (CS) or cerebellum (CER) as reference regions.</p><p><strong>Method: </strong>Seven healthy participants underwent 120-min PET scans on the HRRT scanner with [<sup>18</sup>F]SynVesT-1. Six participants underwent test and retest scans. Arterial blood sampling and metabolite analysis provided input functions for the 1TC model, serving as the gold standard for kinetic parameters values. SRTM, coupled SRTM (SRTMC) and SRTM2 estimated were applied to estimate [Formula: see text](ref: CS) and DVR<sub>CER</sub>(ref: CER) values. For SRTM2, the population average of [Formula: see text] was determined from the 1TC model applied to the reference region. Test-retest variability and minimum scan time were also calculated.</p><p><strong>Results: </strong>The 1TC k<sub>2</sub> (1/min) values for CS and CER were 0.031 ± 0.004 and 0.021 ± 0.002, respectively. Although SRTMC [Formula: see text] was much higher than 1TC [Formula: see text], SRTMC underestimated BP<sub>ND</sub>(ref: CS) and DVR<sub>CER</sub> by an average of 3% and 1% across regions, respectively, due to similar bias in k<sub>2</sub> and [Formula: see text] estimation. SRTM underestimated BP<sub>ND</sub>(ref: CS) by an average of 3%, but with the CER as reference region, SRTM estimation was unstable and DVR<sub>CER</sub> underestimation varied by region (mean 10%). Using population average [Formula: see text] values, SRTM2 BP<sub>ND</sub> and DVR<sub>CER</sub> showed the best agreement with 1TC estimates.</p><p><strong>Conclusion: </strong>Our findings support the use of population [Formula: see text] value in SRTM2 with [<sup>18</sup>F]SynVesT-1 for the estimation of [Formula: see text] or DVR<sub>CER</sub>, regardless of the choice of reference region.</p>\",\"PeriodicalId\":11909,\"journal\":{\"name\":\"European Journal of Nuclear Medicine and Molecular Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Nuclear Medicine and Molecular Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00259-024-06885-6\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Nuclear Medicine and Molecular Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00259-024-06885-6","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Noninvasive quantification of [18F]SynVesT-1 binding using simplified reference tissue model 2.
Purpose: [18F]SynVesT-1, a positron emission tomography (PET) radiotracer for the synaptic vesicle glycoprotein 2A (SV2A), demonstrates kinetics similar to [11C]UCB-J, with high brain uptake, fast kinetics fitting well with the one-tissue compartment (1TC) model, and excellent test-retest reproducibility. Challenges arise due to the similarity between k2 and [Formula: see text] (efflux rate of the reference region), when applying the simplified reference tissue model (SRTM) and related methods in [11C]UCB-J studies to accurately estimate [Formula: see text]. This study evaluated the suitability of these methods to estimate [18F]SynVesT-1 binding using centrum semiovale (CS) or cerebellum (CER) as reference regions.
Method: Seven healthy participants underwent 120-min PET scans on the HRRT scanner with [18F]SynVesT-1. Six participants underwent test and retest scans. Arterial blood sampling and metabolite analysis provided input functions for the 1TC model, serving as the gold standard for kinetic parameters values. SRTM, coupled SRTM (SRTMC) and SRTM2 estimated were applied to estimate [Formula: see text](ref: CS) and DVRCER(ref: CER) values. For SRTM2, the population average of [Formula: see text] was determined from the 1TC model applied to the reference region. Test-retest variability and minimum scan time were also calculated.
Results: The 1TC k2 (1/min) values for CS and CER were 0.031 ± 0.004 and 0.021 ± 0.002, respectively. Although SRTMC [Formula: see text] was much higher than 1TC [Formula: see text], SRTMC underestimated BPND(ref: CS) and DVRCER by an average of 3% and 1% across regions, respectively, due to similar bias in k2 and [Formula: see text] estimation. SRTM underestimated BPND(ref: CS) by an average of 3%, but with the CER as reference region, SRTM estimation was unstable and DVRCER underestimation varied by region (mean 10%). Using population average [Formula: see text] values, SRTM2 BPND and DVRCER showed the best agreement with 1TC estimates.
Conclusion: Our findings support the use of population [Formula: see text] value in SRTM2 with [18F]SynVesT-1 for the estimation of [Formula: see text] or DVRCER, regardless of the choice of reference region.
期刊介绍：
The European Journal of Nuclear Medicine and Molecular Imaging serves as a platform for the exchange of clinical and scientific information within nuclear medicine and related professions. It welcomes international submissions from professionals involved in the functional, metabolic, and molecular investigation of diseases. The journal's coverage spans physics, dosimetry, radiation biology, radiochemistry, and pharmacy, providing high-quality peer review by experts in the field. Known for highly cited and downloaded articles, it ensures global visibility for research work and is part of the EJNMMI journal family.
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