With the aging of the global population, the prevalence of neurodegenerative diseases is increasing and these diseases bring a huge burden to the healthcare system. However, accurately diagnostic tools for such diseases are still lacking. The extensive genetic similarities between the animal model (e.g., mouse) and human make them an excellent tool of understanding common developmental processes and pathologies in human. With the development of genetic information and manipulation technology for animal models, combining genetic tools with a range of manipulated environmental factors can help better understand the complex mechanisms of neurodegenerative diseases.
Over the past few decades, with the advance of animal models, neurosciences have become increasingly demanding for non-invasive imaging technologies. In recent years, magnetic resonance imaging (MRI) has played an increasingly critical role in the research of neurodegenerative diseases, for its capability to provide comprehensive and multi-parameter information about the structure and function of the nervous system. As an advanced, non-invasive neuroimaging tool, MRI can identify the characteristic of different neurodegenerative diseases, contribute to the diagnostic process and monitor disease progression. The emergence of advanced MRI applications, including structure, diffusion tensor, function, and perfusion, makes it possible to map the structure and function change during the neurodegeneration process. And these objective measurements may have particular sensitivity for identifying pathological markers in vivo.
Despite this, the biomarkers that current MRI imaging methods can identify were too limited to account for the complex pathological changes involved in neurodegenerative diseases. Meanwhile, the development of nanomolecular probes can display specific molecules at the tissue, cell and subcellular levels. In addition, for the large amount of image data acquired by MRI, how to choose the appropriate processing method to correct, optimize and analyze them, in order to obtain clinical indicators, is also one of the essential problems to be solved urgently. Finally, detecting and screening of disease biomarkers, as well as brain function evaluation by animal models are enhanced by cutting-edge science and technology, such as artificial intelligence, bridging the translational gap from animal to human.
This Research Topic provides an open platform for research on advancements in the field of imaging method, imaging processing method and brain functional evaluation of neurological disease based on animal model via MRI. Studies address one of the following sub-areas are welcome:
- Novel imaging method via animal magnetic resonance imaging to estimate neurological diseases.
- Novel imaging processing method and computational model tools of multi-modal magnetic resonance imaging based on animal model for neurological diseases.
- Novel evaluation method of brain function via magnetic resonance imaging based on animal model.
- Identification of neuroimaging biomarkers for neurological diseases (e.g., Alzheimer’s disease, Parkinson's disease, stroke) based on animal model.
- Deep learning for analysis of animal magnetic resonance imaging.
- Evaluation of brain function based on novel applications of contrast agent imaging.
With the aging of the global population, the prevalence of neurodegenerative diseases is increasing and these diseases bring a huge burden to the healthcare system. However, accurately diagnostic tools for such diseases are still lacking. The extensive genetic similarities between the animal model (e.g., mouse) and human make them an excellent tool of understanding common developmental processes and pathologies in human. With the development of genetic information and manipulation technology for animal models, combining genetic tools with a range of manipulated environmental factors can help better understand the complex mechanisms of neurodegenerative diseases.
Over the past few decades, with the advance of animal models, neurosciences have become increasingly demanding for non-invasive imaging technologies. In recent years, magnetic resonance imaging (MRI) has played an increasingly critical role in the research of neurodegenerative diseases, for its capability to provide comprehensive and multi-parameter information about the structure and function of the nervous system. As an advanced, non-invasive neuroimaging tool, MRI can identify the characteristic of different neurodegenerative diseases, contribute to the diagnostic process and monitor disease progression. The emergence of advanced MRI applications, including structure, diffusion tensor, function, and perfusion, makes it possible to map the structure and function change during the neurodegeneration process. And these objective measurements may have particular sensitivity for identifying pathological markers in vivo.
Despite this, the biomarkers that current MRI imaging methods can identify were too limited to account for the complex pathological changes involved in neurodegenerative diseases. Meanwhile, the development of nanomolecular probes can display specific molecules at the tissue, cell and subcellular levels. In addition, for the large amount of image data acquired by MRI, how to choose the appropriate processing method to correct, optimize and analyze them, in order to obtain clinical indicators, is also one of the essential problems to be solved urgently. Finally, detecting and screening of disease biomarkers, as well as brain function evaluation by animal models are enhanced by cutting-edge science and technology, such as artificial intelligence, bridging the translational gap from animal to human.
This Research Topic provides an open platform for research on advancements in the field of imaging method, imaging processing method and brain functional evaluation of neurological disease based on animal model via MRI. Studies address one of the following sub-areas are welcome:
- Novel imaging method via animal magnetic resonance imaging to estimate neurological diseases.
- Novel imaging processing method and computational model tools of multi-modal magnetic resonance imaging based on animal model for neurological diseases.
- Novel evaluation method of brain function via magnetic resonance imaging based on animal model.
- Identification of neuroimaging biomarkers for neurological diseases (e.g., Alzheimer’s disease, Parkinson's disease, stroke) based on animal model.
- Deep learning for analysis of animal magnetic resonance imaging.
- Evaluation of brain function based on novel applications of contrast agent imaging.
