Quantitative positron emission tomography imaging of angiogenesis in rats with forelimb ischemia using 68Ga-NOTA-c(RGDyK) View Full Text


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Article Info

DATE

2013-07-16

AUTHORS

Joong Hyun Kim, Young-Hwa Kim, Young Joo Kim, Bo Yeun Yang, Jae Min Jeong, Hyewon Youn, Dong Soo Lee, Jae Sung Lee

ABSTRACT

Gallium-68-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA)—cyclic Arg-Gly-Asp-D-Tyr-Lys (c(RGDyK)) was developed for αvβ3 targeting, and is a promising agent for imaging of cancer and disorders related to angiogenesis. In this study, we performed kinetic analysis of 68Ga-NOTA-c(RGDyK) in rats with surgically induced forelimb ischemia, and immunohistochemical analysis was also performed to assess αvβ3 immuno-staining level. Animal models were created by excision of the left brachial vessels, and a sham operation was performed on the right brachial region under 2 % isoflurane anesthesia. Using an animal positron emission tomography/computed tomography (PET/CT) scanner, a list mode PET scan (120 min) was started with the injection of 68Ga-NOTA-c(RGDyK) via the tail vein at 3, 5 and 7 days after ischemic surgery. Volumes of interest were drawn on the left ventricle, sham operation, control, and ischemic regions. Compartmental and two graphical analyses (Logan and RE plots) were performed for kinetic parameter estimation. The immunohistochemical analysis was also performed after the last PET scan, and cell components were scored on a six point scale for quantification of immuno-staining level (0-negative to 5-very high). A 3-compartment model with reversible binding best described the tissue time-activity curves. The distribution volume of the ischemic region was significantly higher than that of the sham operation (P < 10−6) and control region (P < 10−9). Both the Logan and RE plots showed high correlation with compartmental analysis (R2 = 0.96 and 0.95 for Logan and RE, respectively). The temporal changes in distribution volume and binding potential were not significant. The immuno-staining level of the ischemic region was significantly higher than that of sham operation (P < 10−4) and control region (P < 10−8). Kinetic modeling studies with dynamic 68Ga-NOTA-c(RGDyK) PET scan are feasible based on an image-derived input function in a rat ischemia model. The kinetic modeling analysis performed in this study will be useful for the quantitative evaluation of 68Ga-NOTA-c(RGDyK) binding to αvβ3 in angiogenic tissues. More... »

PAGES

837-846

References to SciGraph publications

  • 2010-10-12. 68Ga-Labeled Radiopharmaceuticals for Positron Emission Tomography in NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2002-02. Role of integrins in cell invasion and migration in NATURE REVIEWS CANCER
  • 2002-02-01. Specialization of tumour vasculature in NATURE REVIEWS CANCER
  • 2010-06-18. Positron emission tomography tracers for imaging angiogenesis in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2007-03-02. The 68Ge/68Ga generator has high potential, but when can we use 68Ga-labelled tracers in clinical routine? in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2010-12-16. MicroPET Imaging of Integrin αvβ3 Expressing Tumors Using 89Zr-RGD Peptides in MOLECULAR IMAGING AND BIOLOGY
  • 2003-09. Therapeutic antagonists and conformational regulation of integrin function in NATURE REVIEWS DRUG DISCOVERY
  • 2005-12-14. Angiogenesis in life, disease and medicine in NATURE
  • 2005-12-14. Angiogenesis as a therapeutic target in NATURE
  • 2010-10-10. A new 18F-labeled BBN-RGD peptide heterodimer with a symmetric linker for prostate cancer imaging in AMINO ACIDS
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    http://scigraph.springernature.com/pub.10.1007/s10456-013-9359-4

    DOI

    http://dx.doi.org/10.1007/s10456-013-9359-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1030345152

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23857293


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    37 schema:description Gallium-68-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA)—cyclic Arg-Gly-Asp-D-Tyr-Lys (c(RGDyK)) was developed for αvβ3 targeting, and is a promising agent for imaging of cancer and disorders related to angiogenesis. In this study, we performed kinetic analysis of 68Ga-NOTA-c(RGDyK) in rats with surgically induced forelimb ischemia, and immunohistochemical analysis was also performed to assess αvβ3 immuno-staining level. Animal models were created by excision of the left brachial vessels, and a sham operation was performed on the right brachial region under 2 % isoflurane anesthesia. Using an animal positron emission tomography/computed tomography (PET/CT) scanner, a list mode PET scan (120 min) was started with the injection of 68Ga-NOTA-c(RGDyK) via the tail vein at 3, 5 and 7 days after ischemic surgery. Volumes of interest were drawn on the left ventricle, sham operation, control, and ischemic regions. Compartmental and two graphical analyses (Logan and RE plots) were performed for kinetic parameter estimation. The immunohistochemical analysis was also performed after the last PET scan, and cell components were scored on a six point scale for quantification of immuno-staining level (0-negative to 5-very high). A 3-compartment model with reversible binding best described the tissue time-activity curves. The distribution volume of the ischemic region was significantly higher than that of the sham operation (P < 10−6) and control region (P < 10−9). Both the Logan and RE plots showed high correlation with compartmental analysis (R2 = 0.96 and 0.95 for Logan and RE, respectively). The temporal changes in distribution volume and binding potential were not significant. The immuno-staining level of the ischemic region was significantly higher than that of sham operation (P < 10−4) and control region (P < 10−8). Kinetic modeling studies with dynamic 68Ga-NOTA-c(RGDyK) PET scan are feasible based on an image-derived input function in a rat ischemia model. The kinetic modeling analysis performed in this study will be useful for the quantitative evaluation of 68Ga-NOTA-c(RGDyK) binding to αvβ3 in angiogenic tissues.
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