Tumor-to-blood ratio for assessment of fibroblast activation protein receptor density in pancreatic cancer using [68Ga]Ga-FAPI-04

Chen, Ruohua; Yang, Xinlan; Yu, Xiaofeng; Zhou, Xiang; Ng, Yee Ling; Zhao, Haitao; Li, Lianghua; Huang, Gang; Zhou, Yun; Li, Jianjun

doi:10.1007/s00259-022-06010-5

Cited by 19 publications

(3 citation statements)

References 28 publications

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“…Currently, most research in TB-PET data processing is focused on 18 F-FDG imaging, and the potential for non-FDG tracers must be leveraged. Some pioneering works have attempted imaging with 68 Ga-DOTATATE [116], 68 Ga-PSMA [117], 68 Ga-FAPI [118][119][120], 13 N-ammonia [121], 89 Zr [122,123], 18 F-Fluciclovine [124], 11 Cmethionine [125], Y-90 [126], and 82 Rb [127]. However, the optimal data processing methods differ considerably between non-FDG tracers, and need to be adapted accordingly.…”

Section: Future Directionsmentioning

confidence: 99%

Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis

Sun,

Chen,

Liu

et al. 2024

iRADIOLOGY

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Total‐body positron emission tomography (TB‐PET) has ultra‐high sensitivity and the unique ability to conduct dynamic imaging of the entire body. Both the hardware configuration and the data acquired from a TB‐PET scanner differ from those of the conventional short axial field‐of‐view scanners. Therefore, various aspects concerning data processing need careful consideration when implementing TB‐PET in clinical settings. Additionally, advances in data analysis are needed to fully uncover the potential of these systems. Although some progress has been achieved, further research and innovation in scan data management are necessary. In this report, we provide a comprehensive overview of the current progress, challenges, and possible future directions for TB‐PET data processing and analysis. For a review of clinical applications, please find the other review accompanying this paper.

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Section: Future Directionsmentioning

confidence: 99%

Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis

Sun,

Chen,

Liu

et al. 2024

iRADIOLOGY

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“…The dynamic PET images were corrected for radioactive decay, scatter, attenuation, and random, and were reconstructed into a matrix with voxel size of 2.34 ×2.34×2.89 mm 3 in x, y, z direction with ordered subset expectation maximization (OSEM) algorithm, time-of-flight (TOF) and point-spread function (PSF). The images were split into 97 frames (30×2 s, 12×5 s, 6×10 s, 4×30 s, 25×60 s, 15×120 s, 5×180 s) 23,24 .…”

Section: Dynamic Total-body Pet/ct Acquisition and Reconstructionmentioning

confidence: 99%

Changes of “brain-GI” interplay in Parkinson’s disease: a pilot study of dynamic total-body [11C]CFT PET/CT and kinetic modeling

Xin,

Wang,

Yang

et al. 2023

Preprint

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Purpose: Parkinson’s disease (PD) is a neurodegenerative disease characterized by progressive loss of dopaminergic neurons in the brain. To achieve better explorations of dopamine changes both centrally and peripherally, we employed uEXPLORER dynamic [11C]CFT PET/CT imaging combined with voxel-wise kinetic modeling. Methods: Eleven participants (five patients, PD and six healthy volunteers, HC) underwent 75-min dynamic scans were enrolled. Volumes of interest for four nigrostriatal nuclei (caudate, putamen, pallidum and substantial nigra) and three digestive organs (pancreas, stomach and duodenum) were delineated. Total-body parametric images of relative transporter rate constant (R1) and distribution volume ratio (DVR) using the simplified reference tissue model (SRTM2) were quantitatively generated by a linear regression with spatial-constraint algorithm. Standardized uptake value ratio (SUVR) at early and late phase were calculated as the semi-quantitative substitutes. Results: Significant differences between the two groups were identified in DVR and SUVRLP of putamen (P < 0.05) and SUVREP of stomach (P < 0.01). For HC group, negative correlations of R1 were achieved between stomach and both putamen and substantial nigra (all P < 0.05); positive correlations of DVR were identified between pancreas and all four brain nuclei (all P < 0.05). Yet in PD group, correlations of R1 or DVR between the targeted digestive and brain areas were considerably diminished. Similar trends in correlations were also found in SUVR analysis. Conclusions: We introduced a pioneering approach using dynamic total-body [11C]CFT PET/CT imaging to investigate distinctive patterns of potential “brain-GI” interplays, which may provide new insights towards the understanding of PD.

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“…Several types of subjects were recruited: healthy volunteers and patients diagnosed with cancer or infected with COVID-19. While the most of scans was done exclusively with the administration of fluorine-18 labeled fluorodeoxyglucose ( 18 F-FDG), there are other radiotracers of interest to be employed, such as 68 Ga-FAPI-04 [55]. A range of scanning and reconstruction protocols have been applied by different hospitals/institutions, but the magnitude of image voxels is generally on the order of ten million and a more dense sequence is commonly performed at the early time.…”

Section: Total-body Pet Studiesmentioning

confidence: 99%

Quantitation of Dynamic Total-Body PET Imaging: Recent Developments and Future Perspectives

2023

Preprint

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Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades. The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania) and Biograph Vision Quadra (Siemens Healthineers), further stimulate valuable inspiration to map kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results. In this contribution, the published dynamic total-body PET datasets are outlined and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model) and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments and future perspectives of these methodologies for a diverse-tissue environment.

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Tumor-to-blood ratio for assessment of fibroblast activation protein receptor density in pancreatic cancer using [68Ga]Ga-FAPI-04

Cited by 19 publications

References 28 publications

Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis

Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis

Changes of “brain-GI” interplay in Parkinson’s disease: a pilot study of dynamic total-body [11C]CFT PET/CT and kinetic modeling

Quantitation of Dynamic Total-Body PET Imaging: Recent Developments and Future Perspectives

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