F Franchi1, M Olthoff2, J Krier3, C Noble2, M Al-Hijji2, V Ramaswamy2, T Witt2, M Burke4, M Benscoter4, A Lerman2, G S Sandhu2, M Rodriguez-Porcel2,3. 1. Department of Cardiovascular Medicine, Mayo Clinic School of Medicine Rochester, Mayo Clinic, 200 First St SW, Rochester, MN, 55902, USA. Franchi.Federico@mayo.edu. 2. Department of Cardiovascular Medicine, Mayo Clinic School of Medicine Rochester, Mayo Clinic, 200 First St SW, Rochester, MN, 55902, USA. 3. Department of Physiology and Biomedical Engineering, Mayo Clinic School of Medicine Rochester, Rochester, MN, 55902, USA. 4. Division of Engineering, Mayo Clinic School of Medicine Rochester, Rochester, MN, 55902, USA.
Abstract
PURPOSE: Metabolic alterations underlie many pathophysiological conditions, and their understanding is critical for the development of novel therapies. Although the assessment of metabolic changes in vivo has been historically challenging, recent developments in molecular imaging have allowed us to study novel metabolic research concepts directly in the living subject, bringing us closer to patients. However, in many instances, there is need for sensors that are in close proximity to the organ under investigation, for example to study vascular metabolism. METHODS: In this study, we developed and validated a metabolic detection platform directly in the living subject under an inflammatory condition. The signal collected by a scintillating fiber is amplified using a photomultiplier tube and decodified by an in-house tunable analysis platform. For in vivo testing, we based our experiments on the metabolic characteristics of macrophages, cells closely linked to inflammation and avid for glucose and its analog 18F-fluorodeoxyglucose (18F-FDG). The sensor was validated in New Zealand rabbits, in which inflammation was induced by either a) high cholesterol (HC) diet for 16 weeks or b) vascular balloon endothelial denudation followed by HC diet. RESULTS: There was no difference in weight, hemodynamics, blood pressure, or heart rate between the groups. Vascular inflammation was detected by the metabolic sensor (Inflammation: 0.60 ± 0.03 AU vs. control: 0.48 ± 0.03 AU, p = 0.01), even though no significant inflammation/atherosclerosis was detected by intravascular ultrasound, underscoring the high sensitivity of the system. These findings were confirmed by the presence of macrophages on ex vivo aortic tissue staining. CONCLUSION: In this study, we validated a tunable very sensitive metabolic sensor platform that can be used for the detection of vascular metabolism, such as inflammation. This sensor can be used not only for the detection of macrophage activity but, with alternative probes, it could allow the detection of other pathophysiological processes.
PURPOSE: Metabolic alterations underlie many pathophysiological conditions, and their understanding is critical for the development of novel therapies. Although the assessment of metabolic changes in vivo has been historically challenging, recent developments in molecular imaging have allowed us to study novel metabolic research concepts directly in the living subject, bringing us closer to patients. However, in many instances, there is need for sensors that are in close proximity to the organ under investigation, for example to study vascular metabolism. METHODS: In this study, we developed and validated a metabolic detection platform directly in the living subject under an inflammatory condition. The signal collected by a scintillating fiber is amplified using a photomultiplier tube and decodified by an in-house tunable analysis platform. For in vivo testing, we based our experiments on the metabolic characteristics of macrophages, cells closely linked to inflammation and avid for glucose and its analog 18F-fluorodeoxyglucose (18F-FDG). The sensor was validated in New Zealand rabbits, in which inflammation was induced by either a) high cholesterol (HC) diet for 16 weeks or b) vascular balloon endothelial denudation followed by HC diet. RESULTS: There was no difference in weight, hemodynamics, blood pressure, or heart rate between the groups. Vascular inflammation was detected by the metabolic sensor (Inflammation: 0.60 ± 0.03 AU vs. control: 0.48 ± 0.03 AU, p = 0.01), even though no significant inflammation/atherosclerosis was detected by intravascular ultrasound, underscoring the high sensitivity of the system. These findings were confirmed by the presence of macrophages on ex vivo aortic tissue staining. CONCLUSION: In this study, we validated a tunable very sensitive metabolic sensor platform that can be used for the detection of vascular metabolism, such as inflammation. This sensor can be used not only for the detection of macrophage activity but, with alternative probes, it could allow the detection of other pathophysiological processes.
Authors: Martin Janecek; Bradley E Patt; Jan S Iwanczyk; Lawrence MacDonald; Yuko Yamaguchi; H William Strauss; Ross Tsugita; Vartan Ghazarossian; Edward J Hoffman Journal: Mol Imaging Biol Date: 2004 May-Jun Impact factor: 3.488
Authors: Lalitha K Shankar; John M Hoffman; Steve Bacharach; Michael M Graham; Joel Karp; Adriaan A Lammertsma; Steven Larson; David A Mankoff; Barry A Siegel; Annick Van den Abbeele; Jeffrey Yap; Daniel Sullivan Journal: J Nucl Med Date: 2006-06 Impact factor: 10.057
Authors: Luis E Savastano; Quan Zhou; Arlene Smith; Karla Vega; Carlos Murga-Zamalloa; David Gordon; Jon McHugh; Lili Zhao; Michael Wang; Aditya Pandey; B Gregory Thompson; Jie Xu; Jifeng Zhang; Y Eugene Chen; Eric J Seibel; Thomas D Wang Journal: Nat Biomed Eng Date: 2017-02-10 Impact factor: 25.671