Whole-Body Parametric Imaging of <sup>18</sup>F-FDG PET Using uEXPLORER with Reduced Scanning Time

Wu, Yaping; Feng, Tao; Zhao, Yizhang; Xu, Tianyi; Fu, Fangfang; Huang, Zhun; Meng, Nan; Li, Hongdi; Shao, Fengmin

doi:10.2967/jnumed.120.261651

Cited by 45 publications

(46 citation statements)

References 22 publications

(24 reference statements)

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“…Furthermore, we compared the quantification of DTW to several existing simplified quantification methods, including Patlak analysis, FUR, and SUV, as a surrogate for the net influx rate K i . The proposed DTW protocol produced the most accurate quantification, followed by FUR and Patlak analysis, while SUV had the lowest correlation, which is consistent with previous study findings [ 20 , 26 , 46 ]. In terms of visual performance, the DTW protocol generated parametric K i and K 1 images that were more consistent with the reference and had less noise than the Patlak analysis had.…”

Section: Discussionsupporting

confidence: 91%

“…Many efforts have been made to avoid invasive blood sampling and shorten the duration of scans. Several noninvasive methods for determining the input function have been proposed, including image-derived input function (IDIF) [ 21 , 22 ], population-based input function (PBIF) [ 23 , 24 ], model-based input function [ 25 ], and hybrid input function [ 26 ] (combination of IDIF and PBIF). The difficulty in obtaining the input function for a bed position with no large artery in the field of view (FOV) is a concern when using these methods.…”

Section: Introductionmentioning

confidence: 99%

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Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Wang

et al. 2022

EJNMMI Phys

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Purpose Efforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body 18F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup. Methods The research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate Ki. Results Ki and K1 derived from the DTW protocol showed overall good consistency (P < 0.01) with the reference from the 60-min dynamic scan with 10-min early scan and 5-min late scan (Ki correlation: 0.971, 0.990, and 0.990; K1 correlation: 0.820, 0.940, and 0.975 in the cerebral cortex, muscle, and tumor lesion, respectively). Similar correlationss were found for other micro-parameters. The DTW protocol had the lowest bias relative to standard Ki than any of the quantification methods, followed by FUR and Patlak. SUV had the weakest correlation with Ki. The whole-body Ki and K1 images generated by the DTW protocol were consistent with the reference parametric images. Conclusions Using the DTW protocol, the dynamic total-body FDG scan time can be reduced to 15 min while obtaining accurate Ki and K1 quantification and acceptable visual performance in parametric images. However, the trade-off between quantification accuracy and protocol implementation feasibility must be considered in practice. We recommend that the DTW protocol be used when the clinical task requires reliable visual assessment or quantifying multiple micro-parameters; FUR with a hybrid input function may be a more feasible approach to quantifying regional metabolic rate with a known lesion position or organs of interest.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Wang

et al. 2022

EJNMMI Phys

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“…Wu et al. ( 29 ) explored and proved the possibility of shortened acquisition time for parametric imaging of K i in FDG PET scan employing the nonlinear estimation approach with 7 patients scanned on a total-body PET scanner. Wu et al.…”

Section: Discussionmentioning

confidence: 99%

Improved Clinical Workflow for Whole-Body Patlak Parametric Imaging Using Two Short Dynamic Acquisitions

Wang

Miao

et al. 2022

Front. Oncol.

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ObjectiveWe sought to explore the feasibility of shorter acquisition times using two short dynamic scans for a multiparametric PET study and the influence of quantitative performance in shortened dynamic PET.MethodsTwenty-one patients underwent whole-body dynamic 18F-FDG PET/CT examinations on a PET/CT (Siemens Biograph Vision) with a total scan time of 75 min using continuous bed motion for Patlak multiparametric imaging. Two sets of Patlak multiparametric images were produced: the standard MRFDG and DVFDG images (MRFDG-std and DVFDG-std) and two short dynamic MRFDG and DVFDG images (MRFDG-tsd and DVFDG-tsd), which were generated by a 0–75 min post injection (p.i.) dynamic PET series and a 0–6 min + 60–75 min p.i. dynamic PET series, respectively. The maximum, mean, and peak values of the standard and two short dynamic multiparametric acquisitions were obtained and compared using Passing–Bablok regression and Bland–Altman analysis.ResultsHigh correlations were obtained between MRFDG-tsd and MRFDG-std, and between DVFDG-tsd and DVFDG-std for both normal organs and all lesions (0.962 ≦ Spearman’s rho ≦ 0.982, p < 0.0001). The maximum, mean, and peak values of the standard and two short dynamic multiparametric acquisitions were also in agreement. For normal organs, the Bland–Altman plot showed that the mean bias of MRFDG-max, MRFDG-mean, and MRFDG-peak was -0.002 (95% CI: -0.032–0.027), -0.002 (95% CI: -0.026–0.023), and -0.002 (95% CI: -0.026–0.022), respectively. The mean bias of DVFDG-max, DVFDG-mean, and DVFDG-peak was -3.3 (95% CI: -24.8–18.2), -1.4 (95% CI: -12.1–9.2), and -2.3 (95% CI: -15–10.4), respectively. For lesions, the Bland–Altman plot showed that the mean bias of MRFDG-max, MRFDG-mean, and MRFDG-peak was -0.009 (95% CI: -0.056–0.038), -0.004 (95% CI: -0.039–0.031), and -0.004 (95% CI: -0.036–0.028), respectively. The mean bias of DVFDG-max, DVFDG-mean, and DVFDG-peak was -8.4 (95% CI: -42.6–25.9), -4.8 (95% CI: -20.2–10.6), and -4.0 (95% CI: -23.7–15.6), respectively.ConclusionsThis study demonstrates the feasibility of using two short dynamic scans that include the first 0–6 min and 60–75 min scans p.i. for Patlak multiparametric images, which can increase patient throughout for parametric analysis.

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“…In a similar work, Wu et al showed that a dual imaging protocol that used PET data from 0 to 4 min and 54 to 60 min p.i can be used to estimate tumour K i with 12-30% bias [14]. In that same study, Wu et al also showed that a dual injection protocol can be used to estimate tumour K i with a 10 minute PET acquisition [14]. Use of PBIFs has also been evaluated with PET data acquired from SAFOV PET scanners.…”

Section: Discussionmentioning

confidence: 99%

“…Recent work with LAFOV PET systems has shown that abbreviated dynamic imaging protocols can be used to extract net tissue in ux of 18 F-FDG, i.e. the Patlak slope, known as K i (ml g − 1 min − 1 ) with a total scan duration of 10 minutes [14]. We have also previously shown that K i and some of the kinetic microparameters can be estimated with low bias and good precision with a total scan duration of 15-20 minutes [15].…”

Section: Introductionmentioning

confidence: 99%

Feasibility of using abbreviated scans protocols with population-based input functions for accurate kinetic modelling of 18F-FDG datasets from a long-axial FOV PET scanner

Eriksson

Mingels

Alberts

et al. 2022

Preprint

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Background: Accurate kinetic modelling of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples but the introduction of long axial field of view (LAFOV) PET systems enables use of non-invasive image derived input functions (IDIF) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition which is impractical in a busy clinical setting. Population-based input functions (PBIF) have previously shown potential in accurate Patlak analysis of 18F-FDG datasets and can enable the use of shortened dynamic imaging protocols. We not exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore use of PBIF with abbreviated protocols in 18F-FDG total body kinetic modelling. Methods: Dynamic PET data were acquired in 24 oncological subjects for 65 minutes following the administration of 18F-FDG. IDIFs were extracted from the descending thoracic aorta and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIF) were generated by scaling the PBIF with AUC of IDIF curve tails using various portions of image data (35-65, 40-65, 45-65, 50-65 and 55-65 min post injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumour lesions and cerebral grey matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t*=35 min was used as reference and mean bias and precision (standard deviation of bias) were calculated to assess relative performance of different sPBIFs. Comparison of parametric images generated using IDIF and sPBIFs was also performed. Results: There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P>0.05). The sPBIF55-65 showed the best performance with 1.5% bias and %6.8 precision in tumour lesions. Using the sPBIF55-65 with Patlak model, 20 minutes of PET data (i.e. 45 to 65 min post injection) achieved <15% precision error in Ki estimates in tumour lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 mins of PET data as reference, Patlak Ki images generated using sPBIF55-65 with 20 minutes of PET data (t*=45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB. Conclusion: We demonstrate the feasibility of performing accurate 18F-FDG Patlak analysis using sPBIFs with only 20 minutes of PET data from a LAFOV PET scanner.

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Whole-Body Parametric Imaging of ¹⁸F-FDG PET Using uEXPLORER with Reduced Scanning Time

Cited by 45 publications

References 22 publications

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Improved Clinical Workflow for Whole-Body Patlak Parametric Imaging Using Two Short Dynamic Acquisitions

Feasibility of using abbreviated scans protocols with population-based input functions for accurate kinetic modelling of 18F-FDG datasets from a long-axial FOV PET scanner

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Whole-Body Parametric Imaging of 18F-FDG PET Using uEXPLORER with Reduced Scanning Time

Cited by 45 publications

References 22 publications

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Improved Clinical Workflow for Whole-Body Patlak Parametric Imaging Using Two Short Dynamic Acquisitions

Feasibility of using abbreviated scans protocols with population-based input functions for accurate kinetic modelling of 18F-FDG datasets from a long-axial FOV PET scanner

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Whole-Body Parametric Imaging of ¹⁸F-FDG PET Using uEXPLORER with Reduced Scanning Time