@article{Tonietto2015a,

title = {Improved models for plasma radiometabolite correction and their impact on kinetic quantification in PET studies},

author = { Matteo Tonietto and Mattia Veronese and Gaia Rizzo and Paolo Zanotti-Fregonara and Talakad G. Lohith and Masahiro Fujita and Sami S. Zoghbi and Alessandra Bertoldo},

url = {http://www.nature.com/jcbfm/journal/v35/n9/full/jcbfm201561a.html},

doi = {10.1038/jcbfm.2015.61},

issn = {0271-678x},

year  = {2015},

date = {2015-04-15},

journal = {J Cereb Blood Flow Metab},

volume = {35},

number = {9},

pages = {1462-1469},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rizzo2019,

title = {Generalization of endothelial modelling of TSPO PET imaging: Considerations on tracer affinities},

author = { Gaia Rizzo and Mattia Veronese and Matteo Tonietto and Benedetta Bodini and Bruno Stankoff and Catriona Wimberley and Sonia Lavisse and Michel Bottlaender and Peter S. Bloomfield and Oliver Howes and Paolo Zanotti-Fregonara and Federico E. Turkheimer and Alessandra Bertoldo},

doi = {10.1177/0271678X17742004},

issn = {15597016},

year  = {2019},

date = {2019-01-01},

journal = {J. Cereb. Blood Flow Metab.},

abstract = {The 18 kDa translocator protein (TSPO) is a marker of microglia activation and the main target of positron emission tomography (PET) ligands for neuroinflammation. Previous works showed that accounting for TSPO endothelial binding improves PET quantification for [ 11 C]PBR28, [ 18 F]DPA714 and [ 11 C]-R-PK11195. It is still unclear, however, whether the vascular signal is tracer-dependent. This work aims to explore the relationship between the TSPO vascular and tissue components for PET tracers with varying affinity, also assessing the impact of affinity towards the differentiability amongst kinetics and the ensuing ligand amenability to cluster analysis for the extraction of a reference region. First, we applied the compartmental model accounting for vascular binding to [ 11 C]-R-PK11195 data from six healthy subjects. Then, we compared the [ 11 C]-R-PK11195 vascular binding estimates with previously published values for [ 18 F]DPA714 and [ 11 C]PBR28. Finally, we determined the suitability for reference region extraction by calculating the angle between grey and white matter kinetics. Our results showed that endothelial binding is common to all TSPO tracers and proportional to their affinity. By consequence, grey and white matter kinetics were most similar for the radioligand with the highest affinity (i.e. [ 11 C]PBR28), hence poorly suited for the extraction of a reference region using supervised clustering.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rizzo_tmi_2016,

title = {Bayesian quantification of contrast-enhanced ultrasound images with adaptive inclusion of an irreversible component},

author = {G. Rizzo and M. Tonietto and M. Castellaro and B. Raffeiner and A. Coran and U. Fiocco and R. Stramare and E. Grisan},

doi = {10.1109/TMI.2016.2637698},

issn = {1558-254X},

year  = {2017},

date = {2017-04-07},

journal = {IEEE Transactions on Medical Imaging},

volume = {36},

number = {4},

pages = {1027 - 1036},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fiocco_clinrheu_2016,

title = {Pixel-based method of contrast-enhanced ultrasound demonstrates the linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+ IL-23+ CD161+ CD4+ T helper cells in the psoriatic arthritis joints},

author = {U. Fiocco and R. Stramare and V. Martini and A. Coran and M. Felicetti and G. Rizzo and M. Tonietto and F. Caso and L. Costa and A. Scanu and F. Oliviero and B. Raffeiner and F. Lunardi and R. Scarpa and L. Rubaltelli and D. Sacerdoti and A. Doria and E. Grisan},

doi = { 10.1007/s10067-016-3500-x},

issn = {1434-9949},

year  = {2017},

date = {2017-02-02},

journal = {Clinical Rheumatology},

volume = {36},

number = {2},

pages = {391–399},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid28213113,

title = {A Variational Bayesian inference method for parametric imaging of PET data},

author = { Marco Castellaro and Gaia Rizzo and Matteo Tonietto and Mattia Veronese and F. E. Turkheimer and M. A. Chappell and Alessandra Bertoldo},

year  = {2017},

date = {2017-02-01},

journal = {Neuroimage},

volume = {150},

pages = {136--149},

keywords = {},

pubstate = {published},

tppubtype = {article}

}