Research output per year
Research output per year
Personal profile
Research interests
The main research focus is aging and neurodegenerative disorders. Specific research interests include evaluating regulation and functional reserve of brain blood flow and metabolism using positron emission tomography in cognitively normal aging and neurodegenerative disorders; establishing metabolic markers of preclinical state of Alzheimer’s disease; identifying longitudinal patterns of beta-amyloid accumulation in preclinical and clinically manifested Alzheimer’s disease; evaluating the relationship between brain metabolism and beta-amyloid deposition and their potential contribution to optimization of treatment strategies in Alzheimer’s disease.
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Collaborations and top research areas from the last five years
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Individual-level metabolic connectivity from dynamic [18F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard
Vallini, G., Silvestri, E., Volpi, T., Lee, J. J., Vlassenko, A. G., Goyal, M. S., Cecchin, D., Corbetta, M. & Bertoldo, A., Feb 2025, In: European Journal of Nuclear Medicine and Molecular Imaging. 52, 3, p. 836-850 15 p.Research output: Contribution to journal › Article › peer-review
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Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study
ADOPIC and ADNI Investigators, Jan 2024, In: NeuroImage. 285, 120494.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [18F]FDG brain studies
De Francisci, M., Silvestri, E., Bettinelli, A., Volpi, T., Goyal, M. S., Vlassenko, A. G., Cecchin, D. & Bertoldo, A., Dec 2024, In: EJNMMI Physics. 11, 1, 105.Research output: Contribution to journal › Article › peer-review
Open Access -
Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning
CSF and Blood, Genetics, Neuropathology, NACC, DIAN, Cerebrovascular Disease (CVD) Risk, Hippocampal Sclerosis (HS-TDP43) Risk, Artificial Intelligence and Machine Learning, for the ADOPIC, ADNI Investigators, Biostats, Database and Bioinformatics, Cognition & Imaging, Oct 2024, In: Brain Imaging and Behavior. 18, 5, p. 1310-1322 13 p.Research output: Contribution to journal › Review article › peer-review
Open Access1 Scopus citations -
Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography - Computed Tomography Scanner
Lee, J., Metcalf, N., Durbin, T. A., Byers, J., Casey, K., Jafri, H., Goyal, M. & Vlassenko, A. G., Jun 7 2024, In: Journal of visualized experiments : JoVE. 208Research output: Contribution to journal › Article › peer-review