September 11, 2025: A new pet tracer can provide information on how spinal cord lesions affect not only spinal cord, but also the brain, according to a new research published in the Journal of Nuclear Medicine. By identifying the loss of synapses, the PET approach provides unique and complementary molecular information to other structural image methods, offering an objective promising metric to evaluate new therapies for spinal cord lesions.
According to the National Statistics Center of the spinal bite, the annual incidence of traumatic injury to the spinal cord is approximately 54 cases for one million people, and approximately 308,600 people in the United States live with a spinal cord injury. Clinical results vary according to the severity and location of the lesion, which potentially leads to a partial or complete loss of sensory or motor function below the level of injury. The current diagnosis of spinal cord injury is based on anatomical techniques such as X -rays and CT, which evaluate spinal integrity but provide limited physiological and pathological information.
“There is an urgent need for a quantitative and non -invasive image method for changes in the neuronal network after spinal cord injury,” said Jason Cai, PHD, associate professor of radiology and biomedical and pharmacology images at Yale Medicine Faculty in New Haven, Connecticut. “By offering a non -invasive quantitative method to visualize and quantify the loss of synapses throughout the central nervous system, SV2A PET could become an essential tool to evaluate and monitor the progression of spinal cord injury or predict recovery.”
The researchers used the newcomer radio SV2A marked with 18F, (18F) Synvest-1, to evaluate changes in synaptic density in a T7 contusion rat model. Nine rats were taken with spinal cord injuries T7 and seven simulated controls with (18f) synvest-1 pet on the first day and in the days nine to 11 after the lesion. Image findings from the site of injury and brain were compared to the image of the ex -vivo diffusion tensioner (DTI) and molecular biological analyzes.
(18F) Synvest-1 PET effectively identified the loss of synapses in the Contusion Science fiction rat model. It was found that absorption in the epicenter of spinal cord injuries was reduced by 58 percent and 52 percent in day one and days nine to 11 after the lesion, respectively, compared to simulated control rats. The absorption of 18F-Synvest-1 in the amygdala and the cerebellum was also less in spinal cord injury rats, and DTI’s ex-living analysis revealed damage to the fiber in the internal capsule and the somatosensory cortex.
“Our work has the potential to revolutionize the way in which the spinal cord injury is diagnosed and monitors,” said CAI. “SV2A PET could be used to evaluate the effects of new treatments in an objective and quantitative way, supporting more precise and personalized therapy strategies for patients with spinal cord injuries.”
The Authors of (18f) synvest-1 pet detects Sv2a changes in the spinal cord and brain of rack with spinal cord injury include baosheng chen, tutukhanim Balayeva, Takuya toyonaga, jie tong, William Mennie, Jelena Mihailovic, Daniel Coman And Yiyun Huang, Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut; Chao Zheng, Department of Radiology and Biomedical Images, University of Yale, New Haven, Connecticut and Azrieli Center for Neurocadioquimica, Center for Cerebral Health Image, Camh, Toronto, Ontario, Canada, and departments of Psychiatry, Chemistry, Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada; Xingxing Wang and Stephen M. Strittmatter, Neuroscience and Neurology Departments, Yale University, New Haven, Connecticut; Fahmeed Hyder and Richard E. Carson, Department of Radiology and Biomedical Images, Yale University, New Haven, Connecticut, and Department of Biomedical Engineering, Yale University, New Haven, Connecticut; and Zhengxin CAI, Department of Biomedical Engineering, University of Yale, New Haven, Connecticut, and Department of Pharmacology, Yale University, New Haven, Connecticut.
