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Criteria for rupture prediction of Abdominal Aortic Aneurysm (AAA) are based only on the diameter of AAA.
Also, other imaging techniques are being used for rupture prediction in animal models such as non-invasive MR imaging and near-infrared fluorescence [46, 47].
Correlations between 18F-FDG uptake and pathological weakening of the wall can aid in investigating how effective this imaging tool will be in rupture prediction.
This paper investigated fused deposition modelling (FDM) 3D printing method for manufacturing abdominal aortic aneurysm (AAA) physical models for rupture prediction and prevention.
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Creep and rupture predictions may be made from the results.
Biomechanical models, which compute stresses and strain, are promising to provide a more reliable rupture risk prediction.
Since AAA has an inflammatory component, increased inflammatory activity in the aortic wall could potentially indicate recent growth of an aneurysm and thus help in rupture risk prediction.
The role of 18F-FDG PET scanning in rupture risk prediction needs to be further investigated, and standardized imaging protocols and quantification methods need to be implemented.
Findings published by Sakalihasan et al. in 2002 prompted further research to investigate the role of 18F-FDG PET scanning in rupture risk prediction.
However, in the end, it is unlikely that one single PET scan with a random PET tracer will lead to a reliable single quantitative cutoff value for rupture risk prediction.
The technology was proved correct, and the pipe rupture risk prediction and classification maps can be used to provide technical guidance for the water distribution network design and operation maintenance.
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