Matteo Tonietto, F. Zanderigo, A. Bertoldo, D. Devanand, J. Mann, B. Bodini, B. Stankoff
{"title":"基于种群的输入函数非线性混合效应建模多中心验证[18F]Fdg代谢率体素量化","authors":"Matteo Tonietto, F. Zanderigo, A. Bertoldo, D. Devanand, J. Mann, B. Bodini, B. Stankoff","doi":"10.1109/ISBI.2019.8759190","DOIUrl":null,"url":null,"abstract":"Population-based input function (PBF) methods provide a less-invasive approach to the quantification of dynamic positron emission tomography (PET) images. PBF methods require the a priori creation of an input function template from a group of subjects who underwent full arterial blood sampling with the same radiotracer. The template is then calibrated using one or two blood samples from the subject under analysis. In this study we propose to generate the PBF template from a group of 8 subjects using a non-linear mixed effect approach and a new input function model. We validated our PBF approach using an independent[18F] FDG dataset of 25 subjects acquired in a different PET center. Results showed a high correlation (> 0.98) and low bias (mean percentage error=1.0 ± 3.1%) between the voxel-wise estimates of [18F] FDG net uptake rate (Ki) obtained with the measured input function and those obtained with the proposed PBF, supporting its use for the quantification of [18F] FDG images acquired in different PET centers.","PeriodicalId":119935,"journal":{"name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Multicenter Validation Of Population-Based Input Function With Non-Linear Mixed Effect Modeling For Voxel-Wise Quantification Of [18F]Fdg Metabolic Rate\",\"authors\":\"Matteo Tonietto, F. Zanderigo, A. Bertoldo, D. Devanand, J. Mann, B. Bodini, B. Stankoff\",\"doi\":\"10.1109/ISBI.2019.8759190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Population-based input function (PBF) methods provide a less-invasive approach to the quantification of dynamic positron emission tomography (PET) images. PBF methods require the a priori creation of an input function template from a group of subjects who underwent full arterial blood sampling with the same radiotracer. The template is then calibrated using one or two blood samples from the subject under analysis. In this study we propose to generate the PBF template from a group of 8 subjects using a non-linear mixed effect approach and a new input function model. We validated our PBF approach using an independent[18F] FDG dataset of 25 subjects acquired in a different PET center. Results showed a high correlation (> 0.98) and low bias (mean percentage error=1.0 ± 3.1%) between the voxel-wise estimates of [18F] FDG net uptake rate (Ki) obtained with the measured input function and those obtained with the proposed PBF, supporting its use for the quantification of [18F] FDG images acquired in different PET centers.\",\"PeriodicalId\":119935,\"journal\":{\"name\":\"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBI.2019.8759190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2019.8759190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multicenter Validation Of Population-Based Input Function With Non-Linear Mixed Effect Modeling For Voxel-Wise Quantification Of [18F]Fdg Metabolic Rate
Population-based input function (PBF) methods provide a less-invasive approach to the quantification of dynamic positron emission tomography (PET) images. PBF methods require the a priori creation of an input function template from a group of subjects who underwent full arterial blood sampling with the same radiotracer. The template is then calibrated using one or two blood samples from the subject under analysis. In this study we propose to generate the PBF template from a group of 8 subjects using a non-linear mixed effect approach and a new input function model. We validated our PBF approach using an independent[18F] FDG dataset of 25 subjects acquired in a different PET center. Results showed a high correlation (> 0.98) and low bias (mean percentage error=1.0 ± 3.1%) between the voxel-wise estimates of [18F] FDG net uptake rate (Ki) obtained with the measured input function and those obtained with the proposed PBF, supporting its use for the quantification of [18F] FDG images acquired in different PET centers.