Evidence map›Paper›PMID 40392375›Full record

ArticleEJNMMI physics2025

Feasibility of simplified Patlak parametric imaging with scaled population-based input function on pancreatic cancer.

Zhixin Hao, Haiqiong Zhang, Yonghong Dang, Jiangdong Qiu, Mengshi Yan, Xinchun Yan, Zhenghai Huang, Chao Ren, Taiping Zhang, Wenming Wu and 1 more

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Article in EJNMMI physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Zhixin Hao *Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Haiqiong Zhang *Department of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Yonghong DangDepartment of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Jiangdong QiuDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Mengshi YanBeijing United Imaging Research Institute of Intelligent Imaging, Beijing, 100094, China.
Xinchun YanDepartment of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Zhenghai HuangMedical Science Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Chao RenDepartment of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.
Taiping ZhangDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China. tpingzhang@yahoo.com.
Wenming WuDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China. doctorwuu@126.com.
Li HuoDepartment of Nuclear Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Center for Rare Diseases Research, Beijing Key Laboratory of Molecular Targeted Diagnosis and Therapy in Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China. huoli@pumch.cn.ORCID http://orcid.org/0000-0003-1216-083X

Funding

Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS) CIFMS-2023-I2M-2-002, CIFMS-2021-I2M-1-002, CIFMS-2021-I2M-1-003, CIFMS-2021-I2M-1-025National High Level Hospital Clinical Research Funding 2022-PUMCH-D-001, 2022-PUMCH-D-002National Natural Science Foundation of China 82071967
6 · The paper itself

Abstract

backgroundThis study evaluates the feasibility of using a simplified Patlak parametric imaging technique with a scaled population-based input function (sPBIF) in pancreatic cancer.

methodsTwenty-six patients underwent multi-bed, multi-pass [

resultsWe found good agreement between the AUC for IDIF and sPBIF with correlation coefficients of 0.87 and 0.93 for the 0-30 min and 0-50 min intervals, respectively. The Patlak parameters from IDIF and sPBIF presented correlation coefficients higher than 0.94. The SUV and Patlak K

conclusionsThe sPBIF approach enables the acquisition of additional Patlak parametric images alongside static SUV imaging in pancreatic cancer patients. K

Indexed as

[18F]FDGPancreatic cancerPatlak parametric imagingScaled PBIF

Identifiers

PMID40392375
PMCPMC12092890

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