Tommaso Volpi
Postdoctoral AssociateDownloadHi-Res Photo
About
Titles
Postdoctoral Associate
Biography
During his PhD, Tommaso has worked on kinetic modelling of multiple PET tracers ([18F]FDG, [15O]H2O, [15O]O2) and integration with resting-state fMRI using multivariate analysis, with additional focus on image-derived input function and PET connectivity methods. Current projects involve mathematical modelling of PET data to obtain information on brain physiology (metabolism, receptor and synaptic density), and applications to brain disorders.
Appointments
Radiology & Biomedical Imaging
Postdoctoral AssociatePrimary
Other Departments & Organizations
Education & Training
- PhD
- University of Padova, Padova Neuroscience Center (2022)
- MD
- University of Padova (2017)
Research
Overview
Medical Subject Headings (MeSH)
Positron-Emission Tomography
ORCID
0000-0002-5451-6710
Research at a Glance
Yale Co-Authors
Frequent collaborators of Tommaso Volpi's published research.
Publications Timeline
A big-picture view of Tommaso Volpi's research output by year.
Ansel Hillmer, PhD
David Matuskey, MD
Irina Esterlis, PhD
Patrick Worhunsky, DPhil
Richard Carson, PhD
Tianyi Zeng, PhD
9Publications
8Citations
Publications
2024
Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager
Li H, Badawi R, Cherry S, Fontaine K, He L, Henry S, Hillmer A, Hu L, Khattar N, Leung E, Li T, Li Y, Liu C, Liu P, Lu Z, Majewski S, Matuskey D, Morris E, Mulnix T, Omidvari N, Samanta S, Selfridge A, Sun X, Toyonaga T, Volpi T, Zeng T, Jones T, Qi J, Carson R. Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager. Journal Of Nuclear Medicine 2024, 65: jnumed.124.267767. PMID: 38871391, PMCID: PMC11294061, DOI: 10.2967/jnumed.124.267767.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPeak noise-equivalent count rateNoise-equivalent count rateTime-of-flight resolutionField of viewCount rateExtended axial field-of-viewTransverse field-of-viewAxial field-of-viewField-of-view centerMini-Derenzo phantomSpatial resolutionTangential spatial resolutionsCount rate performanceContrast recovery coefficientHuman brain PET imagingMeasurements of spatial resolutionNEMA sensitivityEnergy resolutionScatter fractionBrain phantomBackprojection reconstructionBrain PET imagingTime resolutionRadial offsetF-FDG imagingThe brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?
Volpi T, Silvestri E, Aiello M, Lee JJ, Vlassenko AG, Goyal MS, Corbetta M, Bertoldo A. The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity? J Cereb Blood Flow Metab 2024, 271678X241237974. PMID: 38443762, DOI: 10.1177/0271678X241237974.Peer-Reviewed Original Research
2023
An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?
Volpi T, Maccioni L, Colpo M, Debiasi G, Capotosti A, Ciceri T, Carson RE, DeLorenzo C, Hahn A, Knudsen GM, Lammertsma AA, Price JC, Sossi V, Wang G, Zanotti-Fregonara P, Bertoldo A, Veronese M. An update on the use of image-derived input functions for human PET studies: new hopes or old illusions? EJNMMI Res 2023, 13: 97. PMID: 37947880, DOI: 10.1186/s13550-023-01050-w.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsA new framework for metabolic connectivity mapping using bolus [(18)F]FDG PET and kinetic modeling.
Volpi T, Vallini G, Silvestri E, Francisci M, Durbin T, Corbetta M, Lee JJ, Vlassenko AG, Goyal MS, Bertoldo A. A new framework for metabolic connectivity mapping using bolus [(18)F]FDG PET and kinetic modeling. J Cereb Blood Flow Metab 2023, 271678X231184365. PMID: 37377103, DOI: 10.1177/0271678X231184365.Peer-Reviewed Original ResearchLinking resting-state network fluctuations with systems of coherent synaptic density: A multimodal fMRI and 11C-UCB-J PET study
Fang X, Volpi T, Holmes S, Esterlis I, Carson R, Worhunsky P. Linking resting-state network fluctuations with systems of coherent synaptic density: A multimodal fMRI and 11C-UCB-J PET study. Frontiers In Human Neuroscience 2023, 17: 1124254. PMID: 36908710, PMCID: PMC9995441, DOI: 10.3389/fnhum.2023.1124254.Peer-Reviewed Original ResearchCitationsAltmetricConceptsSynaptic densityRSN activityResting-state network connectivityRSN functional connectivityAnterior default mode networkJ PET studyResting-state fMRIBrain functional organizationDefault mode networkHealthy adult participantsExecutive control networkRSN connectivityFunctional organizationPsychiatric disordersMedial prefrontalSalience networkPET studiesFunctional connectivityHealthy agingFractional amplitudeLow-frequency fluctuationsNeurophysiological linkSynaptic architectureAdult participantsDefault-mode activity
2022
Variability of regional glucose metabolism and the topology of functional networks in the human brain.
Palombit A, Silvestri E, Volpi T, Aiello M, Cecchin D, Bertoldo A, Corbetta M. Variability of regional glucose metabolism and the topology of functional networks in the human brain. Neuroimage 2022, 257: 119280. PMID: 35525522, DOI: 10.1016/j.neuroimage.2022.119280.Peer-Reviewed Original ResearchImage-derived Input Function in brain [(18)F]FDG PET data: which alternatives to the carotid siphons?
Silvestri E, Volpi T, Bettinelli A, De Francisci M, Jones J, Corbetta M, Cecchin D, Bertoldo A. Image-derived Input Function in brain [(18)F]FDG PET data: which alternatives to the carotid siphons? Annu Int Conf IEEE Eng Med Biol Soc 2022, 2022: 243-246. PMID: 36085666, DOI: 10.1109/EMBC48229.2022.9871200.Peer-Reviewed Original ResearchModeling venous plasma samples in [(18)F] FDG PET studies: a nonlinear mixed-effects approach.
Volpi T, Lee JJ, Silvestri E, Durbin T, Corbetta M, Goyal MS, Vlassenko AG, Bertoldo A. Modeling venous plasma samples in [(18)F] FDG PET studies: a nonlinear mixed-effects approach. Annu Int Conf IEEE Eng Med Biol Soc 2022, 2022: 4704-4707. PMID: 36086500, DOI: 10.1109/EMBC48229.2022.9871429.Peer-Reviewed Original Research
2021
Assessing different approaches to estimate single-subject metabolic connectivity from dynamic [(18)F]fluorodeoxyglucose Positron Emission Tomography data.
Volpi T, Silvestri E, Corbetta M, Bertoldo A. Assessing different approaches to estimate single-subject metabolic connectivity from dynamic [(18)F]fluorodeoxyglucose Positron Emission Tomography data. Annu Int Conf IEEE Eng Med Biol Soc 2021, 2021: 3259-3262. PMID: 34891936, DOI: 10.1109/EMBC46164.2021.9630441.Peer-Reviewed Original Research
Academic Achievements and Community Involvement
activity PET Kinetic Modeling on Ultra-High Performance Scanners: can we finally trust the Microparameters?
Poster PresentationSNMMI Annual Meeting 2024Details06/08/2024 - 06/11/2024Toronto, ON, CanadaCollaboratorsactivity Image-Derived Input Functions and Ultra-High Performance Brain PET scanners: have we finally made it?
Oral PresentationSNMMI Annual Meeting 2024Details06/08/2024 - 06/11/2024Toronto, ON, CanadaCollaboratorsactivity Fick’s Principle is back: can we get a Whole-Brain Blood Flow estimate from (almost) any PET tracer?
Oral PresentationSNMMI Annual Meeting 2024Details06/08/2024 - 06/11/2024Toronto, ON, CanadaCollaboratorshonor PIDSC Young Investigator Award - Honorable Mention
International AwardSNMMI Annual Meeting 2024Details06/09/2024Canadaactivity A Novel Approach to Modeling Enzyme Turnover Rates after Irreversible Inhibition: a Proof-Of-Concept Brain PET Study in Non-Human Primates
Poster PresentationNeuroReceptor Mapping 2024Details05/18/2024 - 05/21/2024Montreal, QC, CanadaCollaborators