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Perspective - Journal of Biomedical Imaging and Bioengineering (2023) Volume 7, Issue 4
Precision Cardiac Metabolism Mapping Using Elevated Time-Activity Curve Extraction in Mouse FDG Imaging.
Zhang Liu*
Department of Information Technology and Electrical Engineering, The Chinese University of Hong Kong, Hong Kong
- *Corresponding Author:
- Zhang Liu
Department of Information Technology and Electrical Engineering,
The Chinese University of Hong Kong,
Hong Kong
E-mail:zhang4445@hotmail.com
Received:27-Jul-2023, Manuscript No. AABIB-23-109278; Editor assigned: 31-Aug-2023, PreQC No. AABIB-23-109278(PQ); Reviewed:14-Aug-2023, QC No. AABIB-23-109278; Revised: 21-Aug-2023, Manuscript No. AABIB-23-109278; Published: 28-Aug-2023, DOI: 10.35841/aabib-7.4.193
Citation: Liu Z, Precision Cardiac Metabolism Mapping Using Elevated Time-Activity Curve Extraction in Mouse FDG Imaging. J Biomed Imag Bioeng. 2023;7(4):19.
Introduction
The intricate dance of cardiac metabolism lies at the core of cardiovascular health, orchestrating the energy supply essential for the heart's relentless beating. Advanced imaging techniques have paved the way for us to observe and understand this metabolic symphony, with Positron Emission Tomography (PET) using 18F-fluorodeoxyglucose (FDG) as a key instrument. However, extracting precise insights from PET images requires the refinement of analysis methods, particularly in the context of small animal studies such as mouse FDG imaging. This article delves into the realm of precision cardiac metabolism mapping, achieved through the innovative approach of elevated time-activity curve extraction in mouse FDG imaging.[1].
Mouse models have become invaluable tools in cardiovascular research, allowing scientists to probe the intricacies of cardiac function and metabolism in a controlled environment. FDG-PET imaging in mice presents a unique opportunity to visualize glucose uptake patterns within the heart, reflecting its metabolic activity. However, extracting accurate time-activity curves—the graphical representation of FDG uptake over time—from these images is challenging due to the small size of the heart and the dynamic nature of cardiac metabolism.[2].
This article focuses on the novel technique of elevated time-activity curve extraction, which leverages state-of-the-art image processing and analysis algorithms. By carefully accounting for the nuances of mouse cardiac anatomy, movement, and variability in FDG uptake, this method elevates the precision of metabolic mapping. The result is a more detailed understanding of glucose uptake patterns within different regions of the mouse heart, enabling researchers to identify variations in metabolism that may hold key insights into disease processes, therapeutic responses, and genetic influences.[3].
The implications of precision cardiac metabolism mapping are far-reaching. In the realm of cardiovascular diseases, this approach could uncover metabolic aberrations associated with conditions such as heart failure, ischemia, and diabetes. Moreover, the application of elevated time-activity curve extraction extends beyond disease models, facilitating the study of normal metabolic fluctuations in response to interventions like exercise, diet, and drug administration. The input function and tissue TACs, which describe the arterial plasma and myocardial wall radioactivity concentrations, are required for myocardial blood flow and metabolic rate estimations in dynamic cardiac PET experiments. However, because to the tiny size of the mouse heart, the measured TACs would unavoidably lead to erroneous calculation of rate parameters if adequate modifications are not implemented in the mouse model. Manual blood sampling, considered the gold standard, is time-consuming and fundamentally incapable of capturing the early peak of the input function, particularly after a fast bolus injection. Furthermore, only 10% (e.g., 0.2 mL) of a mouse's total blood volume can be extracted without dramatically affecting its physiologic circumstances, limiting long-term investigations. To estimate the input function, automated blood collecting technologies with the possibility for reduced blood volumes have been devised.[4].
However, with innovation comes a challenge. Refining the techniques and algorithms for elevated time-activity curve extraction demands collaboration between experts in medical imaging, computational analysis, and cardiovascular biology. Validation against established methods, standardization across research settings, and the development of user-friendly tools are critical steps in ensuring the reliability and reproducibility of results.[5].
Conclusion
The marriage of advanced imaging, cutting-edge analysis, and cardiac metabolism research has birthed the concept of precision cardiac metabolism mapping. Elevated time-activity curve extraction emerges as a promising avenue to unlock finer insights from mouse FDG imaging, providing researchers with a sharper lens to decipher the metabolic symphony that sustains the heart's vitality. As this technique evolves, it promises to deepen our understanding of cardiovascular health, enrich drug development strategies, and open new avenues for precision medicine in the realm of heart health..
References
- Gargiulo S, Greco A, Gramanzini M, et al.PET/CT imaging in mouse models of myocardial ischemia..Biomed Res Int. 2012;2012.
- Laforest R, Sharp TL, Engelbach JA, et al.Measurement of input functions in rodents: challenges and solutions. Nucl Med Biol. 2005;32(7):679-85.
- Thackeray JT, Bankstahl JP, Wang Y, et al.. Clinically relevant strategies for lowering cardiomyocyte glucose uptake for 18 F-FDG imaging of myocardial inflammation in mice. Eur. J Nucl Med Mol Imaging. 2015;42:771-80.
- Ni R, Straumann N, Fazio S, et al Imaging increased metabolism in the spinal cord in mice after middle cerebral artery occlusion Photoacoustics. 2023;32:100532.
- Sekine H, Shimizu T, Yang J, et al..Pulsatile myocardial tubes fabricated with cell sheet engineering Circ. 2006;114(1_supplement):I-87