PET and SPECT Imaging As a Solid Guide to Detect and Discriminate Atypical Phenotypes of Neurodegenerative Disorders
European Journal of Clinical and Experimental Medicine(2024)
摘要
Introduction and aim. Atypical or mixed presentations of neurodegenerative disorders may postpone or confound the final diagnosis. Molecular imaging with positron emission tomography (PET) and single photon emission computed tomography (SPECT) radioligands provide target-specific information and may anticipate the diagnosis by “in vivo” detection of the neuro pathological substrate, as Aβ deposition, nigrostriatal dopaminergic depletion or tau inclusions. This concise review will dis cuss the potential of PET and SPECT imaging as a solid guide to better characterize atypical phenotypes of neurodegeneration in the clinical routine, with the potential to drive personalized interventions, improve cohort uniformity for clinical trials, and serve as biomarkers for targeted molecular therapies. Material and methods. Literature search was performed focusing on the role of PET and SPECT imaging in assessing atypical phenotypes of neurodegeneration, using the electronic source of database PubMed/MEDLINE and the web-based search engines Google, Google Scholar. Analysis of the literature. New disease-modifying drugs may increase their effect with early initiation, which is especially im portant in working persons and younger subjects presenting atypical symptoms. In older individuals, the coexistence of neu rodegeneration, age-related changes, cerebrovascular lesions, or depression makes challenging a definitive diagnosis. Quantitative tools able to measure tracer distribution increase the accuracy of molecular neuroimaging creating topographic maps that compare subject’s data with healthy controls databases. Conclusion. Atypical phenotypes may be associated with quantitative key-pattern allowing a more precise and early diagnosis of the neurodegenerative disorder. Finally, quantitative assessment of the pathological substrates allows us to track the disease process and measure treatment response.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要