@article{Squarcina20151697,

title = {Fractal analysis of MRI data for the characterization of patients with schizophrenia and bipolar disorder},

author = { Letizia Squarcina and Alberto De Luca and Marcella Bellani and Paolo Brambilla and Federico E. Turkheimer and Alessandra Bertoldo},

url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84922309065&partnerID=40&md5=09d4981a2e5856322de548ebcfdc2216},

doi = {10.1088/0031-9155/60/4/1697},

year  = {2015},

date = {2015-01-01},

journal = {Physics in Medicine and Biology},

volume = {60},

number = {4},

pages = {1697-1716},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rizzo2014b,

title = {Kinetic modeling without accounting for the vascular component impairs the quantification of [11C]PBR28 brain PET data},

author = { Gaia Rizzo and Mattia Veronese and Matteo Tonietto and Paolo Zanotti Fregonara and Federico E. Turkheimer and Alessandra Bertoldo },

url = {http://www.ncbi.nlm.nih.gov/pubmed/24667911},

doi = {doi:10.1038/jcbfm.2014.55},

year  = {2014},

date = {2014-01-01},

journal = {J Cereb Blood Flow Metab},

volume = {34},

number = {6},

pages = {1060–1069},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Castellaro2014,

title = {Estimation of arterial arrival time and cerebral blood flow from QUASAR arterial spin labeling using stable spline},

author = {Castellaro, Marco and Peruzzo, Denis and Mehndiratta, Amit and Pillonetto, Gianluigi and Petersen, Esben Thade and Golay, Xavier and Chappell, Michael a. and Bertoldo, Alessandra},

url = {http://doi.wiley.com/10.1002/mrm.25525},

doi = {10.1002/mrm.25525},

issn = {07403194},

year  = {2014},

date = {2014-01-01},

journal = {Magn. Reson. Med.},

volume = {00},

number = {August},

pages = {n/a--n/a},

note = {[Epub ahead of print]},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Veronese2013611,

title = {A non-linear mixed effect modelling approach for metabolite correction of the arterial input function in PET studies},

author = { M. Veronese and R.N. Gunn and S. Zamuner and A. Bertoldo},

url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84870314852&partnerID=40&md5=09171bf0fea153b28dc9bc944bfa68f6},

doi = {10.1016/j.neuroimage.2012.10.048},

year  = {2013},

date = {2013-01-01},

journal = {NeuroImage},

volume = {66},

pages = {611-622},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bertoldo2001E524,

title = {Kinetic modeling of [18F]FDG in skeletal muscle by PET: A four-compartment five-rate-constant model},

author = { A. Bertoldo and P. Peltoniemi and V. Oikonen and J. Knuuti and P. Nuutila and C. Cobelli},

url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0034822946&partnerID=40&md5=775edadeea1ae315d8b4190da0e46580},

year  = {2001},

date = {2001-01-01},

journal = {American Journal of Physiology - Endocrinology and Metabolism},

volume = {281},

number = {3 44-3},

pages = {E524-E536},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Visani2024,

title = {Choroid plexus volume in multiple sclerosis can be estimated on structural MRI avoiding contrast injection},

author = {Valentina Visani and Francesca B. Pizzini and Valerio Natale and Agnese Tamanti and Mariagiulia Anglani and Alessandra Bertoldo and Massimiliano Calabrese and Marco Castellaro},

doi = {10.1186/s41747-024-00421-9},

issn = {2509-9280},

year  = {2024},

date = {2024-12-00},

urldate = {2024-12-00},

journal = {Eur Radiol Exp},

volume = {8},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title><jats:p>We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.93, FLAIR 0.93, CE-T1w 0.99). CE-T1w showed higher signal-to-noise ratio and contrast-to-noise ratio (CE-T1w 23.77 and 18.49, T1w 13.73 and 7.44, FLAIR 13.09 and 10.77, respectively). Manual segmentation of ChP resulted 3.073 ± 0.563 mL (mean ± standard deviation) on T1w, 3.787 ± 0.679 mL on FLAIR, and 2.984 ± 0.506 mL on CE-T1w images, with an error of 28.02 ± 19.02% for FLAIR and 3.52 ± 12.61% for T1w. FLAIR overestimated ChP volume compared to CE-T1w (<jats:italic>p</jats:italic> < 0.001). The Dice similarity coefficient of CE-T1w <jats:italic>versus</jats:italic> T1w and FLAIR was 0.67 ± 0.05 and 0.68 ± 0.05, respectively. Spatial error distribution per slice was calculated after nonlinear coregistration to the standard MNI152 space and showed a heterogeneous profile along the ChP especially near the fornix and the hippocampus. Quantitative analyses suggest T1w as a surrogate of CE-T1w to estimate ChP volume.</jats:p><jats:p><jats:bold>Relevance statement</jats:bold> To estimate the ChP volume, CE-T1w can be replaced by non-CE T1w sequences because the error is acceptable, while FLAIR overestimates the ChP volume. This encourages the development of automatic tools for ChP segmentation, also improving the understanding of the role of the ChP volume in multiple sclerosis, promoting longitudinal studies.</jats:p><jats:p><jats:bold>Key points</jats:bold> • CE-T1w sequences are considered the reference standard for ChP manual segmentation.</jats:p><jats:p>• FLAIR sequences showed a higher CNR than T1w sequences but overestimated the ChP volume.</jats:p><jats:p>• Non-CE T1w sequences can be a surrogate of CE-T1w sequences for manual segmentation of ChP.</jats:p>

                <jats:p><jats:bold>Graphical Abstract</jats:bold></jats:p>},

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{doi:10.1002/ana.25197,

title = {Inflammatory intrathecal profiles and cortical damage in multiple sclerosis},

author = {Roberta Magliozzi and Owain W Howell and Richard Nicholas and Carolina Cruciani and Marco Castellaro and Chiara Romualdi and Stefania Rossi and Marco Pitteri and Maria Donata Benedetti and Alberto Gajofatto and Francesca B Pizzini and Stefania Montemezzi and Sarah Rasia and Ruggero Capra and Alessandra Bertoldo and Francesco Facchiano and Salvatore Monaco and Richard Reynolds and Massimiliano Calabrese},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ana.25197},

doi = {10.1002/ana.25197},

year  = {2018},

date = {2018-01-01},

journal = {Annals of Neurology},

volume = {83},

number = {4},

pages = {739-755},

abstract = {Objective Gray matter (GM) damage and meningeal inflammation have been associated with early disease onset and a more aggressive disease course in multiple sclerosis (MS), but can these changes be identified in the patient early in the disease course? Methods To identify possible biomarkers linking meningeal inflammation, GM damage, and disease severity, gene and protein expression were analyzed in meninges and cerebrospinal fluid (CSF) from 27 postmortem secondary progressive MS and 14 control cases. Combined cytokine/chemokine CSF profiling and 3T magnetic resonance imaging (MRI) were performed at diagnosis in 2 independent cohorts of MS patients (35 and 38 subjects) and in 26 non-MS patients. Results Increased expression of proinflammatory cytokines (IFNγ, TNF, IL2, and IL22) and molecules related to sustained B-cell activity and lymphoid-neogenesis (CXCL13, CXCL10, LTα, IL6, and IL10) was detected in the meninges and CSF of postmortem MS cases with high levels of meningeal inflammation and GM demyelination. Similar proinflammatory patterns, including increased levels of CXCL13, TNF, IFNγ, CXCL12, IL6, IL8, and IL10, together with high levels of BAFF, APRIL, LIGHT, TWEAK, sTNFR1, sCD163, MMP2, and pentraxin III, were detected in the CSF of MS patients with higher levels of GM damage at diagnosis. Interpretation A common pattern of intrathecal (meninges and CSF) inflammatory profile strongly correlates with increased cortical pathology, both at the time of diagnosis and at death. These results suggest a role for detailed CSF analysis combined with MRI as a prognostic marker for more aggressive MS. Ann Neurol 2018 Ann Neurol 2018;83:739–755},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{scolozzi2018kinetic,

title = {The kinetic of F-18-FDG in lung cancer: compartmental models and voxel analysis},

author = {E Silvestri and V Scolozzi and G Rizzo and L Indovina and M Castellaro and MV Mattoli and S Taralli and P Graziano and G Cardillo and A Bertoldo and and M L Calcagni},

doi = {10.1186/s13550-018-0439-8},

year  = {2018},

date = {2018-01-01},

booktitle = {EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING},

volume = {8},

number = {1},

pages = {88},

organization = {SPRINGER 233 SPRING ST, NEW YORK, NY 10013 USA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID28750494,

title = {Brain PET and functional MRI: why simultaneously using hybrid PET/MR systems?},

author = {Diego Cecchin and Alessandro Palombit and Marco Castellaro and Erica Silvestri and Franco Bui and Henryk Barthel and Osama Sabri and Maurizio Corbetta and Alessandra Bertoldo},

url = {https://doi.org/10.23736/S1824-4785.17.03008-4},

doi = {10.23736/s1824-4785.17.03008-4},

issn = {1824-4785},

year  = {2017},

date = {2017-12-01},

journal = {The quarterly journal of nuclear medicine and molecular imaging},

volume = {61},

number = {4},

pages = {345—359},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid27626222,

title = {On the Role of the Inferior Intraparietal Sulcus in Visual Working Memory for Lateralized Single-feature Objects},

author = { Sabrina Brigadoi and Simone Cutini and Francesca Meconi and Marco Castellaro and Paola Sessa and Mattia Marangon and Alessandra Bertoldo and Pierre Joliceur and Roberto Dell'Acqua},

year  = {2017},

date = {2017-02-01},

journal = {J Cogn Neurosci},

volume = {29},

number = {2},

pages = {337--351},

abstract = {A consolidated practice in cognitive neuroscience is to explore the properties of human visual working memory through the analysis of electromagnetic signals using cued change detection tasks. Under these conditions, EEG/MEG activity increments in the posterior parietal cortex scaling with the number of memoranda are often reported in the hemisphere contralateral to the objects' position in the memory array. This highly replicable finding clashes with several reported failures to observe compatible hemodynamic activity modulations using fMRI or fNIRS in comparable tasks. Here, we reconcile this apparent discrepancy by acquiring fMRI data on healthy participants and employing a cluster analysis to group voxels in the posterior parietal cortex based on their functional response. The analysis identified two distinct subpopulations of voxels in the intraparietal sulcus (IPS) showing a consistent functional response among participants. One subpopulation, located in the superior IPS, showed a bilateral response to the number of objects coded in visual working memory. A different subpopulation, located in the inferior IPS, showed an increased unilateral response when the objects were displayed contralaterally. The results suggest that a cluster of neurons in the inferior IPS is a candidate source of electromagnetic contralateral responses to working memory load in cued change detection tasks.},

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}

}

@article{pmid28070897,

title = {Stable spline deconvolution for dynamic susceptibility contrast MRI},

author = { D. Peruzzo and M. Castellaro and G. Pillonetto and A. Bertoldo},

year  = {2017},

date = {2017-01-01},

journal = {Magn Reson Med},

keywords = {},

pubstate = {published},

tppubtype = {article}

}