Thomas Godefroy, Mathieu Pavoine, David Bourhis, Romain Le Pennec, Kevin Kerleguer, Romain Floch, Pierre-Yves Salaün, Nicolas Karakatsanis, Philippe Thuillier, Ronan Abgral
{"title":"动态26⁸Ga-DOTATOC全身PET/CT扫描中基于种群的输入函数（PBIF）的Feng模型建模：PET/CT Vision 600系统®上缩短成像方案的可行性。","authors":"Thomas Godefroy, Mathieu Pavoine, David Bourhis, Romain Le Pennec, Kevin Kerleguer, Romain Floch, Pierre-Yves Salaün, Nicolas Karakatsanis, Philippe Thuillier, Ronan Abgral","doi":"10.1186/s40658-025-00773-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study focuses on modeling a population-based input function (PBIF) in dynamic ⁶⁸Ga-DOTATOC PET/CT exams, with the aim of developing clinically adoptable protocols. The PBIF is derived from an image-derived input function (IDIF), ensuring a non-invasive and standardized approach to tracer kinetic modeling.</p><p><strong>Methods: </strong>Patients with well-differentiated neuroendocrine tumors were included from the GAPETNET clinical trial (n = 37), divided into a PBIF modeling group (n = 20) and an independent validation group (n = 17). Dynamic whole-body (dWB) PET/CT imaging was performed using a Vision 600 PET/CT system. A population-based input function (PBIF) was modeled using the Feng approach and scaled to individual patient-specific IDIFs over two different time windows (sPBIF<sub>3 - 7</sub>: 25-55 min, sPBIF<sub>5 - 7</sub>: 40-55 min). The scaled PBIF was normalized to IDIF data from 6 to 55 min post-injection. A full individual patient-specific IDIF using data from 0 to 70 min post-injectionwas used as the reference for AUC and Ki comparisons. IDIFs and scaled PBIFs were compared by assessing the area under the curve (AUC) and radiotracer influx rate (Ki). Linear correlation and Bland-Altman analyses were conducted for AUC and Ki comparisons. Additionally, Mann-Whitney tests were performed to compare Ki values obtained with IDIF and sPBIF in both tumoral lesions and physiological organs.</p><p><strong>Results: </strong>The lowest mean relative AUC bias was observed with sPBIF<sub>3 - 7</sub>, calculated to be 2.7 ± 7.9%, and was slightly higher with sPBIF<sub>5 - 7</sub> (7.35 ± 8.58%). The correlation coefficient (R²) with the sPBIFs was high, with a minimum of 0.95 for the sPBIF<sub>5 - 7</sub>. When analyzing K<sub>i</sub> metrics, biases tended to be lower with the 40-55 min time window (Mean ± SD bias = 1.61 ± 3.33 for K<sub>i max</sub> and 1.64 ± 2.96 for K<sub>i mean</sub>). No significant differences in K<sub>i</sub> values was observed with the sPBIFs compared to the IDIF (p > 0.05), for either tumoral lesion or physiological organs.</p><p><strong>Conclusion: </strong>Our study has demonstrated the feasibility the PBIF approach to estimate tumor or physiological Ki values from a shortened dWB ⁶⁸Ga-DOTATOC PET acquisition, using the Feng model.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"70"},"PeriodicalIF":3.2000,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271040/pdf/","citationCount":"0","resultStr":"{\"title\":\"Modeling of a population-based input function (PBIF) using the Feng model in dynamic ⁶⁸Ga-DOTATOC whole body PET/CT scans: feasibility of shortened imaging protocols on PET/CT Vision 600 system <sup>®</sup>.\",\"authors\":\"Thomas Godefroy, Mathieu Pavoine, David Bourhis, Romain Le Pennec, Kevin Kerleguer, Romain Floch, Pierre-Yves Salaün, Nicolas Karakatsanis, Philippe Thuillier, Ronan Abgral\",\"doi\":\"10.1186/s40658-025-00773-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>This study focuses on modeling a population-based input function (PBIF) in dynamic ⁶⁸Ga-DOTATOC PET/CT exams, with the aim of developing clinically adoptable protocols. The PBIF is derived from an image-derived input function (IDIF), ensuring a non-invasive and standardized approach to tracer kinetic modeling.</p><p><strong>Methods: </strong>Patients with well-differentiated neuroendocrine tumors were included from the GAPETNET clinical trial (n = 37), divided into a PBIF modeling group (n = 20) and an independent validation group (n = 17). Dynamic whole-body (dWB) PET/CT imaging was performed using a Vision 600 PET/CT system. A population-based input function (PBIF) was modeled using the Feng approach and scaled to individual patient-specific IDIFs over two different time windows (sPBIF<sub>3 - 7</sub>: 25-55 min, sPBIF<sub>5 - 7</sub>: 40-55 min). The scaled PBIF was normalized to IDIF data from 6 to 55 min post-injection. A full individual patient-specific IDIF using data from 0 to 70 min post-injectionwas used as the reference for AUC and Ki comparisons. IDIFs and scaled PBIFs were compared by assessing the area under the curve (AUC) and radiotracer influx rate (Ki). Linear correlation and Bland-Altman analyses were conducted for AUC and Ki comparisons. Additionally, Mann-Whitney tests were performed to compare Ki values obtained with IDIF and sPBIF in both tumoral lesions and physiological organs.</p><p><strong>Results: </strong>The lowest mean relative AUC bias was observed with sPBIF<sub>3 - 7</sub>, calculated to be 2.7 ± 7.9%, and was slightly higher with sPBIF<sub>5 - 7</sub> (7.35 ± 8.58%). The correlation coefficient (R²) with the sPBIFs was high, with a minimum of 0.95 for the sPBIF<sub>5 - 7</sub>. When analyzing K<sub>i</sub> metrics, biases tended to be lower with the 40-55 min time window (Mean ± SD bias = 1.61 ± 3.33 for K<sub>i max</sub> and 1.64 ± 2.96 for K<sub>i mean</sub>). No significant differences in K<sub>i</sub> values was observed with the sPBIFs compared to the IDIF (p > 0.05), for either tumoral lesion or physiological organs.</p><p><strong>Conclusion: </strong>Our study has demonstrated the feasibility the PBIF approach to estimate tumor or physiological Ki values from a shortened dWB ⁶⁸Ga-DOTATOC PET acquisition, using the Feng model.</p>\",\"PeriodicalId\":11559,\"journal\":{\"name\":\"EJNMMI Physics\",\"volume\":\"12 1\",\"pages\":\"70\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271040/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EJNMMI Physics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40658-025-00773-0\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EJNMMI Physics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40658-025-00773-0","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Modeling of a population-based input function (PBIF) using the Feng model in dynamic ⁶⁸Ga-DOTATOC whole body PET/CT scans: feasibility of shortened imaging protocols on PET/CT Vision 600 system ®.
Background: This study focuses on modeling a population-based input function (PBIF) in dynamic ⁶⁸Ga-DOTATOC PET/CT exams, with the aim of developing clinically adoptable protocols. The PBIF is derived from an image-derived input function (IDIF), ensuring a non-invasive and standardized approach to tracer kinetic modeling.
Methods: Patients with well-differentiated neuroendocrine tumors were included from the GAPETNET clinical trial (n = 37), divided into a PBIF modeling group (n = 20) and an independent validation group (n = 17). Dynamic whole-body (dWB) PET/CT imaging was performed using a Vision 600 PET/CT system. A population-based input function (PBIF) was modeled using the Feng approach and scaled to individual patient-specific IDIFs over two different time windows (sPBIF3 - 7: 25-55 min, sPBIF5 - 7: 40-55 min). The scaled PBIF was normalized to IDIF data from 6 to 55 min post-injection. A full individual patient-specific IDIF using data from 0 to 70 min post-injectionwas used as the reference for AUC and Ki comparisons. IDIFs and scaled PBIFs were compared by assessing the area under the curve (AUC) and radiotracer influx rate (Ki). Linear correlation and Bland-Altman analyses were conducted for AUC and Ki comparisons. Additionally, Mann-Whitney tests were performed to compare Ki values obtained with IDIF and sPBIF in both tumoral lesions and physiological organs.
Results: The lowest mean relative AUC bias was observed with sPBIF3 - 7, calculated to be 2.7 ± 7.9%, and was slightly higher with sPBIF5 - 7 (7.35 ± 8.58%). The correlation coefficient (R²) with the sPBIFs was high, with a minimum of 0.95 for the sPBIF5 - 7. When analyzing Ki metrics, biases tended to be lower with the 40-55 min time window (Mean ± SD bias = 1.61 ± 3.33 for Ki max and 1.64 ± 2.96 for Ki mean). No significant differences in Ki values was observed with the sPBIFs compared to the IDIF (p > 0.05), for either tumoral lesion or physiological organs.
Conclusion: Our study has demonstrated the feasibility the PBIF approach to estimate tumor or physiological Ki values from a shortened dWB ⁶⁸Ga-DOTATOC PET acquisition, using the Feng model.
期刊介绍：
EJNMMI Physics is an international platform for scientists, users and adopters of nuclear medicine with a particular interest in physics matters. As a companion journal to the European Journal of Nuclear Medicine and Molecular Imaging, this journal has a multi-disciplinary approach and welcomes original materials and studies with a focus on applied physics and mathematics as well as imaging systems engineering and prototyping in nuclear medicine. This includes physics-driven approaches or algorithms supported by physics that foster early clinical adoption of nuclear medicine imaging and therapy.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
