Correlation between 18F-fluoromisonidazole PET and expression of HIF-1α and VEGF in newly diagnosed and recurrent malignant gliomas

Kawai, Nobuyuki; Lin, Wei; Cao, Weidong; Ogawa, Daisuke; Miyake, Keisuke; Haba, Reiji; Maeda, Yukito; Yamamoto, Yuka; Nishiyama, Yoshihiro; Tamiya, Takashi

doi:10.1007/s00259-014-2776-9

Cited by 68 publications

(61 citation statements)

References 33 publications

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“…Noninvasive methods include the use of bioreductive chemical markers such as 2-nitroimidazoles (37), which form adducts under hypoxic conditions and are irreversibly bound in hypoxic cells. 18 F-fluoromisonidazole is the most widely used PET radioligand for imaging hypoxia in humans (38)(39)(40).…”

Section: Discussionmentioning

confidence: 99%

Noninvasive PET Imaging and Tracking of Engineered Human Muscle Precursor Cells for Skeletal Muscle Tissue Engineering

et al. 2016

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Transplantation of human muscle precursor cells (hMPCs) is envisioned for the treatment of various muscle diseases. However, a feasible non-invasive tool to monitor cell survival, migration and integration into the host tissue is still missing. Methods In this study, we designed an adenoviral delivery system to genetically modify hMPCs to express a signaling-deficient form of a human dopamine D2 receptor (hD2R). The gene expression levels of the receptor were evaluated by Reverse Transcriptase Polymerase Chain Reaction (RTPCR) and infection efficiency was visualized by fluorescent microscopy. Viability, proliferation and differentiation capacity of the transduced cells were confirmed and their sustained myogenic phenotype was shown by flow cytometry analysis and fluorescent microscopy. 18F-Fallypride and 18F-FMISO, two well-established PET radioligands, were successfully synthesized and evaluated for their potential to image engineered hMPCs in a mouse model. Furthermore, biodistribution studies and autoradiography were also performed to determine the extent of signal specificity. Results To address the feasibility of the presented approach for tracking of hMPCs in an in vivo model, we first evaluated the safety of the adenoviral gene-delivery, which showed no detrimental effects on the primary human cells. Specific binding of 18F-Fallypride to hD2R_hMPCs was demonstrated in vitro, as well as in vivo, by performing autoradiography, biodistribution and PET experiments, respectively. Furthermore, 18F-FMISO uptake was evaluated at different time-points after cell inoculation in vivo, showing high signal only at the early stages. Finally, histological assessment of the harvested tissues confirmed the sustained survival of the transplanted cells at different time-points with formation of muscle tissue at the site of injection. Conclusion We here propose a signaling-deficient human D2R as a potent reporter for in vivo hMPCs PET tracking by 18F-Fallypride. This approach is a significant step forward towards a potential non-invasive tracking of hMPC_hD2R cells and bioengineered muscle tissues in the clinic.

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Section: Discussionmentioning

confidence: 99%

Noninvasive PET Imaging and Tracking of Engineered Human Muscle Precursor Cells for Skeletal Muscle Tissue Engineering

et al. 2016

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“…In contrast to biopsy and resection, current research suggests that the use of 18 F-FMISO imaging may provide the ability to distinguish GBM from lower-grade gliomas in vivo (63,64,(78)(79)(80) Finally, there has been some research into the field of triple coincidence PET imaging.…”

Section: Glioma Gradingmentioning

confidence: 99%

“…PET protocols where the first tracer continues to have linear dynamics during injection of the second with the specific case of a 64 Cu labelled monoclonal antibody specific to the EphA2 receptor tyrosine kinase ( 64 Cu-EphA2, nanomedicine) followed by 18 F-FDOPA (validation) considered. 64 Cu-EphA2 was chosen, as it has been shown to have slow uptake kinetics that persist for a number of hours (116).…”

Section: This Chapter Develops the Previous Technique To Allow Pre-vamentioning

confidence: 99%

“…64 Cu-EphA2 was chosen, as it has been shown to have slow uptake kinetics that persist for a number of hours (116). This concept is evaluated using a set of synthetic dual-tracer and true dual-tracer preclinical data sets.…”

Section: This Chapter Develops the Previous Technique To Allow Pre-vamentioning

confidence: 99%

“…This concept is evaluated using a set of synthetic dual-tracer and true dual-tracer preclinical data sets. In addition to investigating this technique, there is also interest in whether the antibody based tracer, 64 Cu-EphA2 (EphA2 receptor tyrosine kinase), is taken up in regions of metabolically active infiltrating tumour as assessed by 18 F-FDOPA uptake. Charles Gairdner Hospital, Perth, Western Australia.…”

Section: This Chapter Develops the Previous Technique To Allow Pre-vamentioning

confidence: 99%

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Dual-tracer simultaneous acquisition of positron emission tomography

Bell¹

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Positron emission tomography (PET) imaging is a versatile modality with the ability to examine metabolic factors in individual tissues in vivo. It is an indispensable tool for research and treatment planning of diseases such as cancer. However, versatility could be increased if it were possible to image multiple tracers simultaneously. Such an ability could be important in developing a treatment strategy for diseases that remain intractable in the majority of cases, such as advanced glioma.Metabolic imaging with PET using target specific radiotracers has been shown to improve the delineation of tumour margins and provide increased information about tumour microbiology. However, the physical properties of radiotracers limits their combined use, such that imaging of more than one molecular target using PET is not generally considered feasible.Multiplexing PET imaging (dual-tracer PET) offers a solution that allows for individual PET imaging of two or more individual radiotracers, within the same scanning session. Although the technique was first proposed in the 1980s, this approach is not utilised despite offering significant advantages such as multiple target imaging and validation of new PET radiopharmaceuticals. Reasons for this lack of implementation may include assumptions about the potential loss in image quality and the logistics in synthesizing multiple PET tracers simultaneously.In this PhD, Dual-Tracer PET imaging techniques were developed, with a focus on the ability to validate chosen dual-tracer protocols prior to scanning. A set of techniques was devised to handle cases of increasing complexity: (initially) where the first tracer can be assumed to be static after a certain amount of time; secondly where the first tracer has a constant slow uptake that can be assumed to be linear; and the general case where the first tracer retains residual dynamics, with the use of a basis pursuit to separate the signals.These approaches were tested by applying them to specific, clinically relevant use cases.Development of these techniques has provided a framework for study designers to effectively implement dual-tracer PET imaging with confidence for the validation of new tracers, the investigation of cases where multiple biological factors are important and the further development of diagnosis and treatment in future applications. Finally, by utilising iii basis pursuit approaches, it is possible to consider any combination of tracers regardless of tracer and without devising specific model of uptake within tissue.iv

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PET/CT in Brain Tumors: Current Artificial Intelligence Applications

Malamitsi

2022

Artificial Intelligence in PET/CT Oncologic Imaging

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Correlation between 18F-fluoromisonidazole PET and expression of HIF-1α and VEGF in newly diagnosed and recurrent malignant gliomas

Cited by 68 publications

References 33 publications

Noninvasive PET Imaging and Tracking of Engineered Human Muscle Precursor Cells for Skeletal Muscle Tissue Engineering

Noninvasive PET Imaging and Tracking of Engineered Human Muscle Precursor Cells for Skeletal Muscle Tissue Engineering

Dual-tracer simultaneous acquisition of positron emission tomography

PET/CT in Brain Tumors: Current Artificial Intelligence Applications

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