Jie Xiao1,2,3, Haojun Yu1,2,3, Xiuli Sui1,2,3, Yan Hu1,2,3, Yanyan Cao1,2,3, Guobing Liu1,2,3, Yiqiu Zhang1,2,3,4, Pengcheng Hu1,2,3, Ying Wang5, Chenwei Li5, Baixuan Xu6, Hongcheng Shi7,8,9,10. 1. Department of Nuclear Medicine, Zhongshan Hospital affiliated Fudan University, 180 Fenglin Road, Shanghai, 200032, China. 2. Institute of Nuclear Medicine, Fudan University, Shanghai, 200032, China. 3. Shanghai Institute of Medical Imaging, Shanghai, 200032, China. 4. Collaborative Innovation Center for Molecular Imaging Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, 030001, People's Republic of China. 5. Central Research Institute, United Imaging Healthcare, Shanghai, 201807, China. 6. Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, 100853, China. xbx301@163.com. 7. Department of Nuclear Medicine, Zhongshan Hospital affiliated Fudan University, 180 Fenglin Road, Shanghai, 200032, China. Shi.hongcheng@zs-hospital.sh.cn. 8. Institute of Nuclear Medicine, Fudan University, Shanghai, 200032, China. Shi.hongcheng@zs-hospital.sh.cn. 9. Shanghai Institute of Medical Imaging, Shanghai, 200032, China. Shi.hongcheng@zs-hospital.sh.cn. 10. Collaborative Innovation Center for Molecular Imaging Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, 030001, People's Republic of China. Shi.hongcheng@zs-hospital.sh.cn.
Abstract
PURPOSE: PET image quality is influenced by the patient size according to the current guideline. The study aimed to propose an optimized dose regimen to yield a constant image quality independent of patient habitus to meet the clinical needs. METHODS: A first patient cohort of 78 consecutive oncological patients (59.7 ± 13.7 years) who underwent a total-body PET/CT scan were retrospectively enrolled to develop the regimen. The patients were randomly distributed in four body mass index (BMI) groups according to the World Health Organization (WHO) criteria. The liver SNR (signal-to-noise ratio, SNRL) was obtained by manually drawing regions of interest (ROIs) and normalized (SNRnorm) by the product of injected activity and acquisition time. Fits of SNRnorm against different patient-dependent parameters were performed to determine the best correlating parameter and fit method. A qualitative assessment on image quality was performed using a 5-point Likert scale to determine the acceptable threshold of SNRL. Thus, an optimized regimen was proposed and validated by a second patient cohort consisted of prospectively enrolled 38 oncological patients. RESULTS: The linear fit showed SNRnorm had the strongest correlation (R2 = 0.69) with the BMI than other patient-dependent parameters and fit method. The qualitative assessment indicated a SNRL value of 14.0 as an acceptable threshold to achieve sufficient image quality. The optimized dose regimen was determined as a quadratic relation with BMI: injected activity (MBq) = 39.2 (MBq)/(- 0.03*BMI + 1.49)2. In the validation study, the SNRL no longer decreased with the increase of BMI. There was no significant difference of the image quality regarding the value of SNRL between different BMI groups (p > 0.05). In addition, the injected activity was reduced by 75.6 ± 2.9%, 72.1 ± 4.0%, 67.1 ± 4.4%, and 64.8 ± 3.5% compared with the first cohort for the four BMI groups, respectively. CONCLUSION: The study proposed a quadratic relation between the 18F-FDG injected activity and the patient's BMI for total-body 18F-FDG PET imaging. In this regimen, the image quality can maintain in a constant level independent of patient habitus and meet the clinical requirement with a reduced injected activity.
PURPOSE: PET image quality is influenced by the patient size according to the current guideline. The study aimed to propose an optimized dose regimen to yield a constant image quality independent of patient habitus to meet the clinical needs. METHODS: A first patient cohort of 78 consecutive oncological patients (59.7 ± 13.7 years) who underwent a total-body PET/CT scan were retrospectively enrolled to develop the regimen. The patients were randomly distributed in four body mass index (BMI) groups according to the World Health Organization (WHO) criteria. The liver SNR (signal-to-noise ratio, SNRL) was obtained by manually drawing regions of interest (ROIs) and normalized (SNRnorm) by the product of injected activity and acquisition time. Fits of SNRnorm against different patient-dependent parameters were performed to determine the best correlating parameter and fit method. A qualitative assessment on image quality was performed using a 5-point Likert scale to determine the acceptable threshold of SNRL. Thus, an optimized regimen was proposed and validated by a second patient cohort consisted of prospectively enrolled 38 oncological patients. RESULTS: The linear fit showed SNRnorm had the strongest correlation (R2 = 0.69) with the BMI than other patient-dependent parameters and fit method. The qualitative assessment indicated a SNRL value of 14.0 as an acceptable threshold to achieve sufficient image quality. The optimized dose regimen was determined as a quadratic relation with BMI: injected activity (MBq) = 39.2 (MBq)/(- 0.03*BMI + 1.49)2. In the validation study, the SNRL no longer decreased with the increase of BMI. There was no significant difference of the image quality regarding the value of SNRL between different BMI groups (p > 0.05). In addition, the injected activity was reduced by 75.6 ± 2.9%, 72.1 ± 4.0%, 67.1 ± 4.4%, and 64.8 ± 3.5% compared with the first cohort for the four BMI groups, respectively. CONCLUSION: The study proposed a quadratic relation between the 18F-FDG injected activity and the patient's BMI for total-body 18F-FDG PET imaging. In this regimen, the image quality can maintain in a constant level independent of patient habitus and meet the clinical requirement with a reduced injected activity.
Authors: Simon R Cherry; Terry Jones; Joel S Karp; Jinyi Qi; William W Moses; Ramsey D Badawi Journal: J Nucl Med Date: 2017-09-21 Impact factor: 10.057
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Authors: Alessandro Broccoli; Cristina Nanni; Alberta Cappelli; Francesco Bacci; Alessandro Gasbarrini; Elena Tabacchi; Carlo Piovani; Lisa Argnani; Riccardo Ghermandi; Elena Sabattini; Rita Golfieri; Stefano Fanti; Pier Luigi Zinzani Journal: Eur J Nucl Med Mol Imaging Date: 2020-06-15 Impact factor: 9.236
Authors: Karen D Bosch; Sugama Chicklore; Gary J Cook; Andrew R Davies; Mark Kelly; James A Gossage; Cara R Baker Journal: Eur J Nucl Med Mol Imaging Date: 2019-08-03 Impact factor: 9.236
Authors: Edwin K Leung; Yasser G Abdelhafez; Eric Berg; Zhaoheng Xie; Xuezhu Zhang; Reimund Bayerlein; Benjamin Spencer; Elizabeth Li; Negar Omidvari; Aaron Selfridge; Simon R Cherry; Jinyi Qi; Ramsey D Badawi Journal: Phys Med Biol Date: 2022-06-10 Impact factor: 4.174