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

Abstract

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.

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

“…In terms of image quality, our study found that the quality of Ki-30 min images is as good as that of Ki-65 min images by visual quality assessment. In a different setting by Wang et al, they compared the MR glu images of two-short-dynamic-scanning protocols (0-6 min + 60-75 min) and standard scanning protocols concluding that both protocols produced good-quality MR glu images with no visual distinction [ 21 ]. In addition, our study found that the number of lesions detected in the two image types is consistent.…”

“…It often needs another plasma input function (IF), such as population-based IF (PBIF). However, it may introduce errors into the parametric analysis as it does not take into account the specificity of the individual IF [ 20 ]; (ii) two-short-dynamic-scanning, which requires two separate scans after 18 F-FDG injection, such as (0-6 min + 60-75 min) scans, (0-10 min + 55-60 min) scans, (0-10 min + 40-60 min) scan and two 5-min scans [ 21 – 25 ]. These studies showed that the generated parameter metabolic rate of glucose (MR glu ) [ 21 ] or Ki [ 22 , 24 , 25 ] is highly correlated with the reference parameter calculated from the full scan.…”

“…However, it may introduce errors into the parametric analysis as it does not take into account the specificity of the individual IF [ 20 ]; (ii) two-short-dynamic-scanning, which requires two separate scans after 18 F-FDG injection, such as (0-6 min + 60-75 min) scans, (0-10 min + 55-60 min) scans, (0-10 min + 40-60 min) scan and two 5-min scans [ 21 – 25 ]. These studies showed that the generated parameter metabolic rate of glucose (MR glu ) [ 21 ] or Ki [ 22 , 24 , 25 ] is highly correlated with the reference parameter calculated from the full scan. However, such a protocol requires a break in the middle, and the problem of image registration can limit the feasibility; and (iii) only early-time scanning, with dynamic analysis carried out based on the acquired data from the early frames, such as 0-30 min scans.…”

Characteristics of whole-body dynamic 18F-FDG PET/CT Patlak multi-parametric imaging in lung cancer and the influence of different delineation methods on quantitative parameters

“…Dias et al ( 9 ) recommended the use of a population-based input function (PBIF) to transform Patlak imaging into a 20-min procedure]. We have previously reported on 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 ( 10 ). Several reports have demonstrated the use of dynamic whole-body PET/CT to describe parameters in normal tissues and different types of tumors, such as non-small cell lung cancer, breast cancer, nasopharyngeal carcinoma, and so on ( 11 - 13 ).…”

Clinical validation of a population-based input function for 20-min dynamic whole-body 18F-FDG multiparametric PET imaging

“…However, since this is not viable in a clinical setting, a validated alternative solution is to estimate the IF from the 60-min PET data using an image-derived input function (IDIF) [3,5,11]. Since the acquisition of the initial part of the scan after injection is required, some groups have proposed shorter "dual time-point" protocols [12,13] where the IDIF is obtained from an initial 0-6 min scan over the heart region, and the patient is rescanned again later for example 60-75 min after injection. Although this alternative temporarily frees the scanner for other patients, it is logistically challenging and requires extra CT scans.…”