Tommaso Volpi
Postdoctoral AssociateAbout
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 Research Interests
Positron-Emission Tomography
Public Health Interests
Modeling
Publications
2025
Current Advances in PARP1‐Targeted Theranostics
Tong J, Chen B, Volpi T, Li Y, Ellison P, Cai Z. Current Advances in PARP1‐Targeted Theranostics. Journal Of Labelled Compounds And Radiopharmaceuticals 2025, 68: e4135. PMID: 39995212, DOI: 10.1002/jlcr.4135.Peer-Reviewed Original ResearchConceptsPoly (ADP-ribose) polymerase 1Blood-brain barrierCentral nervous systemBlood-tumor barrierPotential clinical useBRCA mutationsHomologous recombination repair pathwayPARP inhibitorsPharmacodynamic evaluationPatient stratificationPersonalized oncologyPharmacological characteristicsClinical useBrain tumorsBrain barrierDiagnostic imagingPET imagingCancerNervous systemTherapeutic interventionsBrain cancerPathophysiological conditionsTreatment assessmentPARPiNeurological disorders
2024
EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [(18)F]FDG brain studies.
De Francisci M, Silvestri E, Bettinelli A, Volpi T, Goyal MS, Vlassenko AG, Cecchin D, Bertoldo A. EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [(18)F]FDG brain studies. EJNMMI Phys 2024, 11: 105. PMID: 39715888, DOI: 10.1186/s40658-024-00707-2.Peer-Reviewed Original ResearchQuantitative Accuracy Assessment of the NeuroEXPLORER for Diverse Imaging Applications: Moving Beyond Standard Evaluations.
Omidvari N, Shanina E, Leung E, Sun X, Li Y, Mulnix T, Gravel P, Henry S, Matuskey D, Volpi T, Jones T, Badawi R, Li H, Carson R, Qi J, Cherry S. Quantitative Accuracy Assessment of the NeuroEXPLORER for Diverse Imaging Applications: Moving Beyond Standard Evaluations. Journal Of Nuclear Medicine 2024, 66: 150-157. PMID: 39638433, PMCID: PMC11705792, DOI: 10.2967/jnumed.124.268309.Peer-Reviewed Original ResearchContrast recovery coefficientHoffman phantomUniform phantomIQ phantomRecovery coefficientBrain PET systemHoffman brain phantomBrain uptakeSpatial resolutionDiverse imaging applicationsCylindrical phantomPET systemBrain phantomNeuroimaging studiesImage qualityImaging conditionsPhantomReconstruction parametersImaging time pointsTime pointsImage-derived input functionHigher spatial resolutionQuantitative accuracyDelayed time pointsBrain disordersIndividual-level metabolic connectivity from dynamic [(18)F]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 JJ, Vlassenko AG, Goyal MS, Cecchin D, Corbetta M, Bertoldo A. Individual-level metabolic connectivity from dynamic [(18)F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard. Eur J Nucl Med Mol Imaging 2024 PMID: 39472368, DOI: 10.1007/s00259-024-06956-8.Peer-Reviewed Original ResearchPerformance 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 ResearchPeak 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 ResearchSynaptic 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 Research