Standardized Input Function for 18F-FDG PET Studies in Mice: A Cautionary Study

A Comparison of Arterial Input Function Interpolation Methods for Patlak Plot Analysis of 68Ga-PSMA-11 PET Prostate Cancer Studies

Positron emission tomography (PET) imaging enables quantitative assessment of tissue physiology. Dynamic pharmacokinetic analysis of PET images requires accurate estimation of the radiotracer plasma input function to derive meaningful parameter estimates, and small discrepancies in parameter estimation can mimic subtle physiologic tissue variation. This study evaluates the impact of input function interpolation method on the accuracy of Patlak kinetic parameter estimation through simulations modeling the pharmacokinetic properties of [68Ga]-PSMA-11. This study evaluated both trained and untrained methods. Although the mean kinetic parameter accuracy was similar across all interpolation models, the trained node weighting interpolation model estimated accurate kinetic parameters with reduced overall variability relative to standard linear interpolation. Trained node weighting interpolation reduced kinetic parameter estimation variance by a magnitude approximating the underlying physiologic differences between normal and diseased prostatic tissue. Overall, this analysis suggests that trained node weighting improves the reliability of Patlak kinetic parameter estimation for [68Ga]-PSMA-11 PET.

PET AIF estimation when available ROI data is impacted by dispersive and/or background effects

Objective.Blood pool region of interest (ROI) data extracted from the field of view of a PET scanner can be impacted by both dispersive and background effects. This circumstance compromises the ability to correctly extract the arterial input function (AIF) signal. The paper explores a novel approach to addressing this difficulty.Approach.The method involves representing the AIF in terms of the whole-body impulse response (IR) to the injection profile. Analysis of a collection/population of directly sampled arterial data sets allows the statistical behaviour of the tracer's impulse response to be evaluated. It is proposed that this information be used to develop a penalty term for construction of a data-adaptive method of regularisation estimator of the AIF when dispersive and/or background effects maybe impacting the blood pool ROI data.Main results.Computational efficiency of the approach derives from the linearity of the impulse response representation of the AIF and the ability to substantially rely on quadratic programming techniques for numerical implementation. Data from eight different tracers, used in PET cancer imaging studies, are considered. Sample image-based AIF extractions for brain studies with:18F-labeled fluoro-deoxyglucose and fluoro-thymidine (FLT),11C-labeled carbon dioxide (CO2) and15O-labeled water (H2O) are presented. Results are compared to the true AIF based on direct arterial sampling. Formal numerical simulations are used to evaluate the performance of the AIF extraction method when the ROI data has varying amounts of contamination, in comparison to a direct approach that ignores such effects. It is found that even with quite small amounts of contamination, the mean squared error of the regularised AIF is significantly better than the error associated with direct use of the ROI data.Significance.The proposed IR-based AIF extraction scheme offers a practical methodological approach for situations where the available image ROI data may be contaminated by background and/or dispersion effects.

A guideline proposal for mice preparation and care in 18F-FDG PET imaging

The experimental outcomes of small-animal positron emission tomography (PET) imaging with ¹⁸F-labelled fluorodeoxyglucose (¹⁸F-FDG) can be particularly compromised by animal preparation and care. Several works intend to improve research reporting and amplify the quality and reliability of published research. Though these works provide valuable information to plan and conduct animal studies, manuscripts describe different methodologies—standardization does not exist. Consequently, the variation in details reported can explain the difference in the experimental results found in the literature. Additionally, the resources and guidelines defining protocols for small-animal imaging are scarce, making it difficult for researchers to obtain and compare accurate and reproducible data. Considering the selection of suitable procedures key to ensure animal welfare and research improvement, this paper aims to prepare the way for a future guideline on mice preparation and care for PET imaging with ¹⁸F-FDG. For this purpose, a global standard protocol was created based on recommendations and good practices described in relevant literature.

Kinetic modelling and quantification bias in small animal PET studies with [18F]AB5186, a novel 18 kDa translocator protein radiotracer

Introduction

Positron Emission Tomography (PET) imaging with selective 18 kDa translocator protein (TSPO) radiotracers has contributed to our understanding on the role of inflammation in disease development and progression. With an increasing number of rodent models of human disease and expansion of the preclinical PET imaging base worldwide, accurate quantification of longitudinal rodent TSPO PET datasets is necessary. This is particularly relevant as TSPO PET quantification relies on invasive blood sampling due to lack of a suitable tissue reference region. Here we investigate the kinetics and quantification bias of a novel TSPO radiotracer [¹⁸F]AB5186 in rats using automatic, manual and image derived input functions.

Methods

[¹⁸F]AB5186 was administered intravenously and dynamic PET imaging was acquired over 2 hours. Arterial blood was collected manually to derive a population based input function or using an automatic blood sampler to derive a plasma input function. Manually sampled blood was also used to analyze the [¹⁸F]AB5186 radiometabolite profile in plasma and applied to all groups as a population based dataset. Kinetic models were used to estimate distribution volumes (V_T) and [¹⁸F]AB5186 outcome measure bias was determined.

Results

[¹⁸F]AB5186 distribution in rats was consistent with TSPO expression and at 2 h post-injection 50% of parent compound was still present in plasma. Population based manual sampling methods and image derived input function (IDIF) underestimated V_T by ~50% and 88% compared with automatic blood sampling, respectively. The V_T variability was lower when using IDIF versus arterial blood sampling methods and analysis of the Bland-Altman plots showed a good agreement between methods of analysis.

Conclusion

Quantification of TSPO PET rodent data using image-derived methods, which are more amenable for longitudinal scanning of small animals, yields outcome measures with reduced variability and good agreement, albeit biased, compared with invasive blood sampling methods.