A novel description of FDG excretion in the renal system: application to metformin-treated models

Garbarino, Sara; Caviglia, Giacomo; Benvenuto, Federico; Piana, Michele

doi:10.1088/0031-9155/59/10/2469

Cited by 22 publications

(44 citation statements)

References 23 publications

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“…The results provided by the application of BCM need for further investigations. In fact, the basic scheme of this approach is rather flexible and may be modified to allow for consideration of peculiarities of specific organs, as done for classical models in (Garbarino et al, 2014, 2015), may be associated with reference tissue formulations (see (Scussolini et al, 2018) and references cited therein), or to pixel-wise analysis (see (Scussolini et al, 2017) and references cited therein).…”

Section: Discussionmentioning

confidence: 99%

“…In order to solve it, our approach followed a regularized Newton-type method (Bauer et al, 2009; Delbary and Garbarino, 2016), already validated and applied successfully in other compartmental problems, e.g. models for complex physiologies (Garbarino et al, 2014, 2015), parametric imaging (Scussolini et al, 2017), and reference tissue approaches (Scussolini et al, 2018). The algorithm is denoted as reg-GN in the following.…”

Section: The Compartmental Modelmentioning

confidence: 99%

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The role of the endoplasmic reticulum in in vivo cancer FDG kinetics

Scussolini

Cossu

Marini

et al. 2019

Preprint

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2A very recent result obtained by means of an in vitro experiment with cancer cultured cells 3 has configured the endoplasmic reticulum as the preferential site for the accumulation of 2-4 deoxy-2-[ 18 F]fluoro-D-glucose (FDG). Such a result is coherent with cell biochemistry and is 5 made more significant by the fact that reticular accumulation rate of FDG is dependent upon 6 extracellular glucose availability. The objective of the present paper was to confirm this result 7 in vivo, using small animal models of CT26 cancer tissues. Specifically, assuming that the 8 endoplasmic reticulum plays a specific functional role in the framework of a three-compartment 9 model for FDG kinetics, we are able to explain positron emission tomography dynamic data in a 10 more reliable way than by means of a standard Sokoloff two-compartment system. This result is 11 made more solid from a computational viewpoint by means of some identifiability considerations 12 based on a mathematical analysis of the compartmental equations. 13 Keywords: cancer glucose metabolism, endoplasmic reticulum, in vivo models, FDG kinetics, compartmental analysis 14 1 INTRODUCTION 2-deoxy-2-[ 18 F]fluoro-D-glucose (FDG) is widely used as a glucose analogue tracer to evaluate glucose 15 metabolism in living organisms. As glucose, FDG is first transported into cells, where it is phosphorylated 16to FDG-6-phosphate (FDG6P) by hexokinase (HK) and then accumulates intracellularly. The measured 17 amount of emitted radiation is considered an accurate marker of overall glucose uptake by cells and tissues 18 (Cherry et al., 2012). In addition, FDG consumption by cancer cells is increased by the Warburg effect for 19 glucose (Vander et al., 2009); consequently, FDG may be employed in cancer detection and staging, and to 20 determine the effectiveness of medical treatments (Cairns et al., 2011). 21A recent result concerning the characterization of FDG kinetics in cultured cancer cells (Scussolini et 22 al., 2019) showed that the endoplasmic reticulum (ER) is the preferential site of FDG accumulation and 23 that, even more importantly, FDG reticular accumulation rate is dependent upon extracellular glucose 24 availability. This result is coherent with recent progress in cell biochemistry, which clarified that the 25 glucose-6-phosphatase (G6Pase), responsible for the dephosphorylation, is compartmentalized within the 26 endoplasmic reticulum (ER) (Ghosh et al., 2002; Marini et al., 2016). 27 1 Scussolini et al. The role of the endoplasmic reticulum The investigation in (Scussolini et al., 2019) relied on two methodological tools, one experimental 28 and one computational. In fact, on the one hand, FDG kinetics in cells cultured over a Petri dish, was 29 evaluated using the dedicated Ligand Tracer device (Björke and Andersson, 2006), which is able to count 30 electron/positron events without contaminating the counting rate of the cultured cells. On the other hand, 31 the data analysis was performed within the framework of a novel compartmental model, which extend...

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Section: Discussionmentioning

confidence: 99%

Section: The Compartmental Modelmentioning

confidence: 99%

The role of the endoplasmic reticulum in in vivo cancer FDG kinetics

Scussolini

Cossu

Marini

et al. 2019

Preprint

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“…-IP-102361 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Next steps for this piece of research activity will be the validation of reg-AS-TR against several experimental datasets in the case of both humans' and small animals' dynamic PET images. Further, we are going to generalize reg-AS-TR to the case of more complex compartmental models like the ones for the assessment of FDG kinetics in liver [26] and kidneys [27]. -IP-102361 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60…”

Section: Comments and Conclusionmentioning

confidence: 99%

Computational approaches for parametric imaging of dynamic PET data

Crisci

Piana²,

Ruggiero

et al. 2019

Preprint

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Parametric imaging of nuclear medicine data exploits dynamic functional images in order to reconstruct maps of kinetic parameters related to the metabolism of a specific tracer injected in the biological tissue. From a computational viewpoint, the realization of parametric images requires the pixel-wise numerical solution of compartmental inverse problems that are typically ill-posed and nonlinear. In the present paper we introduce a fast numerical optimization scheme for parametric imaging relying on a regularized version of the standard affine-scaling Trust Region method. The validation of this approach is realized in a simulation framework for brain imaging and comparison of performances is made with respect to a regularized Gauss-Newton scheme and a standard nonlinear least-squares algorithm.

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“…Moreover, we add the external urine compartment u, anatomically identified with the bladder, accounting for the tracer there accumulated, thanks to the excretion mechanism (differently from glucose, FDG is poorly absorbed in the renal tubule and is largely excreted in the urine, with accumulation in the bladder [41]). The resulting three-compartment non-catenary model represented in Figure 2 [11,35] has the following kinetic parameters:…”

Section: Three-compartment Non-catenary Systemmentioning

confidence: 99%

A physiology-based parametric imaging method for FDG–PET data

et al. 2017

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Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [ 18 F]-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

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A novel description of FDG excretion in the renal system: application to metformin-treated models

Cited by 22 publications

References 23 publications

The role of the endoplasmic reticulum in in vivo cancer FDG kinetics

The role of the endoplasmic reticulum in in vivo cancer FDG kinetics

Computational approaches for parametric imaging of dynamic PET data

A physiology-based parametric imaging method for FDG–PET data

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