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Samimi R, Kamali-Asl A, Ahmadyar Y, van den Hoff J, Geramifar P, Rahmim A. Dual time-point [ 18F]FDG PET imaging for quantification of metabolic uptake rate: Evaluation of a simple, clinically feasible method. Phys Med 2024; 121:103336. [PMID: 38626637 DOI: 10.1016/j.ejmp.2024.103336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 03/11/2024] [Accepted: 03/25/2024] [Indexed: 04/18/2024] Open
Abstract
PURPOSE We aimed to investigate whether a clinically feasible dual time-point (DTP) approach can accurately estimate the metabolic uptake rate constant (Ki) and to explore reliable acquisition times through simulations and clinical assessment considering patient comfort and quantification accuracy. METHODS We simulated uptake kinetics in different tumors for four sets of DTP PET images within the routine clinical static acquisition at 60-min post-injection (p.i.). We determined Ki for a total of 81 lesions. Ki quantification from full dynamic PET data (Patlak-Ki) and Ki from DTP (DTP-Ki) were compared. In addition, we scaled a population-based input function (PBIFscl) with the image-derived blood pool activity sampled at different time points to assess the best scaling time-point for Ki quantifications in the simulation data. RESULTS In the simulation study, Ki estimated using DTP via (30,60-min), (30,90-min), (60,90-min), and (60,120-min) samples showed strong correlations (r ≥ 0.944, P < 0.0001) with the true value of Ki. The DTP results with the PBIFscl at 60-min time-point in (30,60-min), (60,90-min), and (60,120-min) were linearly related to the true Ki with a slope of 1.037, 1.008, 1.013 and intercept of -6 × 10-4, 2 × 10-5, 5 × 10-5, respectively. In a clinical study, strong correlations (r ≥ 0.833, P < 0.0001) were observed between Patlak-Ki and DTP-Ki. The Patlak-derived mean values of Ki, tumor-to-background-ratio, signal-to-noise-ratio, and contrast-to-noise-ratio were linearly correlated with the DTP method. CONCLUSIONS Besides calculating the retention index as a commonly used quantification parameter inDTP imaging,our DTP method can accurately estimate Ki.
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Affiliation(s)
- Rezvan Samimi
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Alireza Kamali-Asl
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran.
| | - Yashar Ahmadyar
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Jörg van den Hoff
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany; Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany
| | - Parham Geramifar
- Research Center for Nuclear Medicine, Tehran University of Medical Sciences, Tehran, Iran.
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
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Du F, Wumener X, Zhang Y, Zhang M, Zhao J, Zhou J, Li Y, Huang B, Wu R, Xia Z, Yao Z, Sun T, Liang Y. Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions. EJNMMI Phys 2024; 11:23. [PMID: 38441830 PMCID: PMC10914647 DOI: 10.1186/s40658-024-00625-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/27/2024] [Indexed: 03/08/2024] Open
Abstract
PURPOSE This study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference. METHODS Dynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon's rank sum test, Spearman's rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05. RESULTS The quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test. CONCLUSIONS This study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.
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Affiliation(s)
- Fen Du
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Xieraili Wumener
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Yarong Zhang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Maoqun Zhang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Jiuhui Zhao
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Jinpeng Zhou
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Yiluo Li
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Bin Huang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Rongliang Wu
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Zeheng Xia
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Zhiheng Yao
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Tao Sun
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
| | - Ying Liang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
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