Search

Your search keyword '"d'Ambrosio, Alessandro"' showing total 329 results
Start Over Author "d'Ambrosio, Alessandro"
329 results on '"d'Ambrosio, Alessandro"'

1. Regional hippocampal atrophy reflects memory impairment in patients with early relapsing remitting multiple sclerosis

Author

Cortese, Rosa, Battaglini, Marco, Stromillo, Maria Laura, Luchetti, Ludovico, Leoncini, Matteo, Gentile, Giordano, Gasparini, Daniele, Plantone, Domenico, Altieri, Manuela, D’Ambrosio, Alessandro, Gallo, Antonio, Giannì, Costanza, Piervincenzi, Claudia, Pantano, Patrizia, Pagani, Elisabetta, Valsasina, Paola, Preziosa, Paolo, Tedone, Nicolo’, Rocca, Maria Assunta, Filippi, Massimo, and De Stefano, Nicola

Published
2024
Full Text
View/download PDF

4. Signs and symptoms of COVID‐19 in patients with multiple sclerosis

Author

Schiavetti, Irene, Carmisciano, Luca, Ponzano, Marta, Cordioli, Cinzia, Cocco, Eleonora, Marfia, Girolama Alessandra, Inglese, Matilde, Filippi, Massimo, Radaelli, Marta, Bergamaschi, Roberto, Immovilli, Paolo, Capobianco, Marco, De Rossi, Nicola, Brichetto, Giampaolo, Scandellari, Cinzia, Cavalla, Paola, Pesci, Ilaria, Confalonieri, Paolo, Perini, Paola, Trojano, Maria, Lanzillo, Roberta, Tedeschi, Gioacchino, Comi, Giancarlo, Battaglia, Mario Alberto, Patti, Francesco, Salvetti, Marco, Sormani, Maria Pia, Group, MuSC‐19 Study, Abbadessa, Gianmarco, Aguglia, Umberto, Allegorico, Lia, Allegri, Beatrice Maria Rossi, Alteno, Anastasia, Amato, Maria Pia, Annovazzi, Pietro, Antozzi, Carlo, Appendino, Lucia, Arena, Sebastiano, Baione, Viola, Balgera, Roberto, Barcella, Valeria, Baroncini, Damiano, Barrilà, Caterina, Bellacosa, Alessandra, Bellucci, Gianmarco, Bergamaschi, Valeria, Bezzini, Daiana, Biolzi, Beatrice, Bisecco, Alvino, Bonavita, Simona, Borriello, Giovanna, Bosa, Chiara, Bosco, Antonio, Bovis, Francesca, Bozzali, Marco, Brambilla, Laura, Morra, Vincenzo Brescia, Buccafusca, Maria, Bucciantini, Elisabetta, Bucello, Sebastiano, Buscarinu, Maria Chiara, Cabboi, Maria Paola, Calabrese, Massimiliano, Calabria, Francesca, Caleri, Francesca, Camilli, Federico, Caniatti, Luisa Maria, Cantello, Roberto, Capra, Ruggero, Capuano, Rocco, Carta, Patrizia, Celani, Maria Grazia, Cellerino, Maria, Cerqua, Raffaella, Chisari, Clara, Clerici, Raffaella, Clerico, Marinella, Cola, Gaia, Conte, Antonella, Conti, Marta Zaffira, Cordano, Christian, Cordera, Susanna, Corea, Francesco, Correale, Claudio, Cottone, Salvatore, Crescenzo, Francesco, Curti, Erica, d’Ambrosio, Alessandro, D’Amico, Emanuele, Danni, Maura Chiara, d’Arma, Alessia, Dattola, Vincenzo, de Biase, Stefano, De Luca, Giovanna, De Mercanti, Stefania Federica, De Mitri, Paolo, De Stefano, Nicola, Della Cava, Fabio Maria, Della Cava, Marco, and Di Lemme, Sonia

Subjects
Neurosciences, Multiple Sclerosis, Brain Disorders, Pain Research, Neurodegenerative, Good Health and Well Being, Humans, Aged, COVID-19, Ageusia, SARS-CoV-2, Anosmia, MuSC-19 Study Group, demyelinating diseases, disease-modifying treatment, multiple sclerosis, neurological disorders, Clinical Sciences, Neurology & Neurosurgery
Abstract

Background and purposeClinical outcomes of multiple sclerosis (MS) patients affected by coronavirus disease 2019 (COVID-19) have been thoroughly investigated, but a further analysis on main signs and symptoms and their risk factors still needs attention. The objective of this study was to group together and describe based on similarity the most common signs and symptoms of COVID-19 in MS patients and identify all factors associated with their manifestation.MethodLogistic and linear regression models were run to recognize factors associated with each pooled group of symptoms and their total number.ResultsFrom March 2020 to November 2021, data were collected from 1354 MS patients with confirmed infection of COVID-19. Ageusia and anosmia was less frequent in older people (odds ratio [OR] 0.98; p = 0.005) and more in smoker patients (OR 1.39; p = 0.049). Smoke was also associated with an incremental number of symptoms (OR 1.24; p = 0.031), substance abuse (drugs or alcohol), conjunctivitis and rash (OR 5.20; p = 0.042) and the presence of at least one comorbidity with shortness of breath, tachycardia or chest pain (OR 1.24; p = 0.008). Some disease-modifying therapies were associated with greater frequencies of certain COVID-19 symptoms (association between anti-CD20 therapies and increment in the number of concomitant symptoms: OR 1.29; p = 0.05). Differences in frequencies between the three waves were found for flu-like symptoms (G1, p = 0.024), joint or muscle pain (G2, p = 0.013) and ageusia and anosmia (G5, p

Published
2022

6. The effect of air pollution on COVID‐19 severity in a sample of patients with multiple sclerosis

Author

Bergamaschi, Roberto, Ponzano, Marta, Schiavetti, Irene, Carmisciano, Luca, Cordioli, Cinzia, Filippi, Massimo, Radaelli, Marta, Immovilli, Paolo, Capobianco, Marco, De Rossi, Nicola, Brichetto, Giampaolo, Cocco, Eleonora, Scandellari, Cinzia, Cavalla, Paola, Pesci, Ilaria, Zito, Antonio, Confalonieri, Paolo, Marfia, Girolama Alessandra, Perini, Paola, Inglese, Matilde, Trojano, Maria, Morra, Vincenzo Brescia, Pisoni, Enrico, Tedeschi, Gioacchino, Comi, Giancarlo, Battaglia, Mario Alberto, Patti, Francesco, Salvetti, Marco, Sormani, Maria Pia, Abbadessa, Gianmarco, Aguglia, Umberto, Allegorico, Lia, Allegri, Rossi Beatrice Maria, Alteno, Anastasia, Amato, Maria Pia, Annovazzi, Pietro, Antozzi, Carlo, Appendino, Lucia, Arena, Sebastiano, Baione, Viola, Balgera, Roberto, Barcella, Valeria, Baroncini, Damiano, Barrilà, Caterina, Battaglia, Mario A, Bellacosa, Alessandra, Bellucci, Gianmarco, Bergamaschi, Valeria, Bezzini, Daiana, Biolzi, Beatrice, Bisecco, Alvino, Bonavita, Simona, Borriello, Giovanna, Bosa, Chiara, Bosco, Antonio, Bovis, Francesca, Bozzali, Marco, Brambilla, Laura, Brescia, Morra Vincenzo, Buccafusca, Maria, Bucciantini, Elisabetta, Bucello, Sebastiano, Buscarinu, Maria Chiara, Cabboi, Maria Paola, Calabrese, Massimiliano, Calabria, Francesca, Caleri, Francesca, Camilli, Federico, Caniatti, Luisa Maria, Cantello, Roberto, Capra, Ruggero, Capuano, Rocco, Carta, Patrizia, Celani, Maria Grazia, Cellerino, Maria, Cerqua, Raffaella, Chisari, Clara, Clerici, Raffaella, Clerico, Marinella, Cola, Gaia, Conte, Antonella, Conti, Marta Zaffira, Cordano, Christian, Cordera, Susanna, Corea, Francesco, Correale, Claudio, Cottone, Salvatore, Crescenzo, Francesco, Curti, Erica, d'Ambrosio, Alessandro, and D'Amico, Emanuele

Subjects
Clinical Research, Neurosciences, Multiple Sclerosis, Brain Disorders, Autoimmune Disease, Neurodegenerative, Climate-Related Exposures and Conditions, Good Health and Well Being, Sustainable Cities and Communities, Air Pollution, COVID-19, Humans, Particulate Matter, SARS-CoV-2, MuSC-19 study group, air pollution, coronavirus, multiple sclerosis, Clinical Sciences, Neurology & Neurosurgery
Abstract

Background and purposeSome studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m3 (PM2.5), may contribute to severe COVID-19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID-19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID-19 severity amongst PwMS.MethodsData were retrieved from an Italian web-based platform (MuSC-19) which includes PwMS with COVID-19. PM2.5 2016-2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID-19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID-19 severity.ResultsIn all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID-19 course (odds ratio 1.90; p = 0.009).ConclusionsEven if several other factors explain the unfavourable course of COVID-19 in PwMS, the role of air pollutants must be considered and further investigated.

Published
2022

7. Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

Author

De Rosa, Alessandro Pasquale, Esposito, Fabrizio, Valsasina, Paola, d’Ambrosio, Alessandro, Bisecco, Alvino, Rocca, Maria A., Tommasin, Silvia, Marzi, Chiara, De Stefano, Nicola, Battaglini, Marco, Pantano, Patrizia, Cirillo, Mario, Tedeschi, Gioacchino, Filippi, Massimo, and Gallo, Antonio

Published
2023
Full Text
View/download PDF

8. Quality of care provided by Multiple Sclerosis Centers during Covid-19 pandemic: Results of an Italian multicenter patient-centered survey

Author

Altieri, Manuela, Capuano, Rocco, Bisecco, Alvino, d'Ambrosio, Alessandro, Risi, Mario, Cavalla, Paola, Vercellino, Marco, Annovazzi, Pietro, Zaffaroni, Mauro, De Stefano, Nicola, Stromillo, Maria Laura, D'Amico, Emanuele, Zanghì, Aurora, Buscarinu, Maria Chiara, Lanzillo, Roberta, De Luca, Giovanna, Calabrese, Massimiliano, Lorefice, Lorena, Di Filippo, Massimiliano, Valentino, Paola, Gajofatto, Alberto, Marfia, Girolama Alessandra, Fuiani, Aurora, Nociti, Viviana, Tedeschi, Gioacchino, and Gallo, Antonio

Published
2023
Full Text
View/download PDF

14. COVID-19 vaccines and attributable risk of neurological disorders: a multicentre, case-control study (COVIVAX)

Author

Pupillo, Elisabetta, primary, Bianchi, Elisa, additional, Beghi, Ettore, additional, Pedrazzini, Francesco, additional, Giglio, Angela, additional, Schilke, Edoardo, additional, Percetti, Marco, additional, Colleoni, Carlo Morotti, additional, Mainini, Gabriele, additional, Calabresi, Paolo, additional, Primiano, Guido, additional, Frisullo, Giovanni, additional, Padovani, Alessandro, additional, Cristillo, Viviana, additional, Pilotto, Andrea, additional, Arici, Davide, additional, Gipponi, Stefano, additional, Tedeschi, Gioacchini, additional, D'Ambrosio, Alessandro, additional, Melisi, Rosario, additional, Gallo, Antonio, additional, Bisecco, Alvino, additional, Salmaggi, Andrea, additional, Basilico, Paola, additional, Scaccabarozzi, Chiara, additional, Kiferle, Lorenzo, additional, Valenti, Raffaella, additional, Avino, Gianluca, additional, Borghi, Annamaria, additional, Contardi, Sara, additional, Zini, Andrea, additional, Ferrarese, Carlo, additional, and Beretta, Simone, additional

Published
2024
Full Text
View/download PDF

16. Correction to: Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

Author

De Rosa, Alessandro Pasquale, Esposito, Fabrizio, Valsasina, Paola, d’Ambrosio, Alessandro, Bisecco, Alvino, Rocca, Maria A., Tommasin, Silvia, Marzi, Chiara, De Stefano, Nicola, Battaglini, Marco, Pantano, Patrizia, Cirillo, Mario, Tedeschi, Gioacchino, Filippi, Massimo, and Gallo, Antonio

Published
2023
Full Text
View/download PDF

18. Consensus of algorithms for lesion segmentation in brain MRI studies of multiple sclerosis.

Author

De Rosa, Alessandro Pasquale, Benedetto, Marco, Tagliaferri, Stefano, Bardozzo, Francesco, D'Ambrosio, Alessandro, Bisecco, Alvino, Gallo, Antonio, Cirillo, Mario, Tagliaferri, Roberto, and Esposito, Fabrizio

Subjects
MULTIPLE sclerosis, BRAIN damage, MAGNETIC resonance imaging, ALGORITHMS, THERAPEUTICS
Abstract

Segmentation of multiple sclerosis (MS) lesions on brain MRI scans is crucial for diagnosis, disease and treatment monitoring but is a time-consuming task. Despite several automated algorithms have been proposed, there is still no consensus on the most effective method. Here, we applied a consensus-based framework to improve lesion segmentation on T1-weighted and FLAIR scans. The framework is designed to combine publicly available state-of-the-art deep learning models, by running multiple segmentation tasks before merging the outputs of each algorithm. To assess the effectiveness of the approach, we applied it to MRI datasets from two different centers, including a private and a public dataset, with 131 and 30 MS patients respectively, with manually segmented lesion masks available. No further training was performed for any of the included algorithms. Overlap and detection scores were improved, with Dice increasing by 4-8% and precision by 3-4% respectively for the private and public dataset. High agreement was obtained between estimated and true lesion load (ρ = 0.92 and ρ = 0.97) and count (ρ = 0.83 and ρ = 0.94). Overall, this framework ensures accurate and reliable results, exploiting complementary features and overcoming some of the limitations of individual algorithms. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

19. Increased genomic instability and reshaping of tissue microenvironment underlie oncogenic properties of Arid1a mutations

Author

D’Ambrosio, Alessandro, primary, Bressan, Davide, additional, Ferracci, Elisa, additional, Carbone, Francesco, additional, Mulè, Patrizia, additional, Rossi, Federico, additional, Barbieri, Caterina, additional, Sorrenti, Elisa, additional, Fiaccadori, Gaia, additional, Detone, Thomas, additional, Vezzoli, Elena, additional, Bianchi, Salvatore, additional, Sartori, Chiara, additional, Corso, Simona, additional, Fukuda, Akihisa, additional, Bertalot, Giovanni, additional, Falqui, Andrea, additional, Barbareschi, Mattia, additional, Romanel, Alessandro, additional, Pasini, Diego, additional, and Chiacchiera, Fulvio, additional

Published
2024
Full Text
View/download PDF

22. COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Author

Sormani, Maria Pia, Schiavetti, Irene, Carmisciano, Luca, Cordioli, Cinzia, Filippi, Massimo, Radaelli, Marta, Immovilli, Paolo, Capobianco, Marco, De Rossi, Nicola, Brichetto, Giampaolo, Cocco, Eleonora, Scandellari, Cinzia, Cavalla, Paola, Pesci, Ilaria, Zito, Antonio, Confalonieri, Paolo, Marfia, Girolama Alessandra, Perini, Paola, Inglese, Matilde, Trojano, Maria, Brescia Morra, Vincenzo, Tedeschi, Gioacchino, Comi, Giancarlo, Battaglia, Mario Alberto, Patti, Francesco, Salvetti, Marco, Abbadessa, Gianmarco, Aguglia, Umberto, Allegorico, Lia, Allegri Rossi, Beatrice Maria, Amato, Maria Pia, Annovazzi, Pietro, Antozzi, Carlo, Appendino, Lucia, Arena, Sebastiano, Baione, Viola, Balgera, Roberto, Barcella, Valeria, Baroncini, Damiano, Barrilà, Caterina, Bellacosa, Alessandra, Bellucci, Gianmarco, Bergamaschi, Roberto, Bergamaschi, Valeria, Bezzini, Daiana, Biolzi, Beatrice, Bisecco, Alvino, Bonavita, Simona, Borriello, Giovanna, Bosa, Chiara, Bosco, Antonio, Bovis, Francesca, Bozzali, Marco, Brambilla, Laura, Buccafusca, Maria, Bucciantini, Elisabetta, Bucello, Sebastiano, Buscarinu, Maria Chiara, Cabboi, Maria Paola, Calabrese, Massimiliano, Calabria, Francesca, Caleri, Francesca, Camilli, Federico, Caniatti, Luisa Maria, Cantello, Roberto, Capra, Ruggero, Capuano, Rocco, Carta, Patrizia, Celani, Maria Grazia, Cellerino, Maria, Cerqua, Raffaella, Chisari, Clara, Clerici, Raffaella, Clerico, Marinella, Cola, Gaia, Conte, Antonella, Conti, Marta Zaffira, Cordano, Christian, Cordera, Susanna, Corea, Francesco, Correale, Claudio, Cottone, Salvatore, Crescenzo, Francesco, Curti, Erica, dʼAmbrosio, Alessandro, DʼAmico, Emanuele, Danni, Maura Chiara, dʼArma, Alessia, Dattola, Vincenzo, de Biase, Stefano, Luca, Giovanna De, Mercanti, Stefania Federica De, De Mitri, Paolo, De Stefano, Nicola, Cava, Marco Della, Napoli, Mario di, Sapio, Alessia Di, Docimo, Renato, Dutto, Anna, Evangelista, Luana, Fanara, Salvatore, Diana, Ferraro, Ferrò, Maria Teresa, Fioretti, Cristina, Fratta, Mario, Frau, Jessica, Fronza, Marzia, Furlan, Roberto, Gajofatto, Alberto, Gallo, Antonio, Gallo, Paolo, Gasperini, Claudio, Ghazaryan, Anna, Giometto, Bruno, Gobbin, Francesca, Govone, Flora, Granella, Franco, Grange, Erica, Grasso, Maria Grazia, Guareschi, Angelica, Guaschino, Clara, Guerrieri, Simone, Guidetti, Donata, Iaffaldano, Pietro, Ianniello, Antonio, Iasevoli, Luigi, Imperiale, Daniele, Infante, Maria Teresa, Iodice, Rosa, Iovino, Aniello, Konrad, Giovanna, Landi, Doriana, Lanzillo, Roberta, Lapucci, Caterina, Lavorgna, Luigi, LʼEpiscopo, Maria Rita, Leva, Serena, Liberatore, Giuseppe, Lo Re, Marianna, Longoni, Marco, Lopiano, Leonardo, Lorefice, Lorena, Lucchini, Matteo, Lus, Giacomo, Maimone, Davide, Malentacchi, Maria, Mallucci, Giulia, Malucchi, Simona, Mancinelli, Chiara Rosa, Mancinelli, Luca, Manganotti, Paolo, Maniscalco, Giorgia Teresa, Mantero, Vittorio, Marangoni, Sabrina, Marastoni, Damiano, Marinelli, Fabiana, Marti, Alessandro, Boneschi, Filippo Martinelli, Masserano Zoli, Federco, Matta, Francesca, Mendozzi, Laura, Meucci, Giuseppe, Miante, Silvia, Miele, Giuseppina, Milano, Eva, Mirabella, Massimiliano, Missione, Rosanna, Moccia, Marcello, Moiola, Lucia, Montepietra, Sara, MontiBragadin, Margherita, Montini, Federico, Motta, Roberta, Nardone, Raffaele, Nicoletti, Carolina Gabri, Nobile-Orazio, Eduardo, Nozzolillo, Agostino, Onofrj, Marco, Orlandi, Riccardo, Palmieri, Anna, Paolicelli, Damiano, Pasquali, Livia, Pastò, Luisa, Pedrazzoli, Elisabetta, Petracca, Maria, Petrone, Alfredo, Piantadosi, Carlo, Pietroboni, Anna M, Pinardi, Federica, Ponzano, Marta, Portaccio, Emilio, Pozzato, Mattia, Pozzilli, Carlo, Prosperini, Luca, Protti, Alessandra, Ragonese, Paolo, Rasia, Sarah, Realmuto, Sabrina, Repice, Anna, Rigoni, Eleonora, Rilla, Maria Teresa, Rinaldi, Francesca, Romano, Calogero Marcello, Ronzoni, Marco, Rovaris, Marco, Ruscica, Francesca, Sabattini, Loredana, Salemi, Giuseppe, Saraceno, Lorenzo, Sartori, Alessia, Sartori, Arianna, Sbragia, Elvira, Scarano, Giuditta Ilaria, Scarano, Valentina, Schillaci, Valentina, Sessa, Maria, Sgarito, Caterina, Sibilia, Grazia, Siciliano, Gabriele, Signori, Alessio, Signoriello, Elisabetta, Sinisi, Leonardo, Sireci, Francesca, Sola, Patrizia, Solaro, Claudio, Sotgiu, Stefano, Sparaco, Maddalena, Stromillo, Maria Laura, Strumia, Silvia, Susani, Emanuela Laura, Tabiadon, Giulietta, Teatini, Francesco, Tomassini, Valentina, Tonietti, Simone, Torri, Clerici Valentina, Tortorella, Carla, Toscano, Simona, Totaro, Rocco, Trotta, Maria, Turano, Gabriella, Ulivelli, Monica, Valentino, Manzo, Vaula, Giovanna, Vecchio, Domizia, Vercellino, Marco, Verrengia, Elena Pinuccia, Vianello, Marika, Virgilio, Eleonora, Vitetta, Francesca, Vollaro, Stefano, Zaffaroni, Mauro, Zampolini, Mauro, Zarbo, Ignazio Roberto, and Zuliani, Luigi

Published
2022
Full Text
View/download PDF

24. Functional gradients reveal cortical hierarchy changes in multiple sclerosis.

Author

De Rosa, Alessandro Pasquale, d'Ambrosio, Alessandro, Bisecco, Alvino, Altieri, Manuela, Cirillo, Mario, Gallo, Antonio, and Esposito, Fabrizio

Subjects
*DEFAULT mode network, *SUPERVISED learning, *MULTIPLE sclerosis, *LARGE-scale brain networks, *FUNCTIONAL magnetic resonance imaging
Abstract

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting‐state functional MRI (rs‐fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs‐fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual‐to‐sensorimotor) and a secondary (sensory‐to‐transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory‐transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ=0.30$$ \rho =0.30 $$, p <.005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network‐level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold‐out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs‐fMRI studies across different MS populations. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

27. Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set

Author

Chiara, Marzi, D'Ambrosio, Alessandro, Stefano, Diciotti, Alvino, Bisecco, Manuela, Altieri, Massimo, Filippi, Maria Assunta Rocca, Loredana, Storelli, Pantano, Patrizia, Tommasin, Silvia, Cortese, ROSA MARIA, De Stefano, Nicola, Gioacchino, Tedeschi, Antonio, Gallo, the INNI Network, Marzi, Chiara, D'Ambrosio, Alessandro, Diciotti, Stefano, Bisecco, Alvino, Altieri, Manuela, Filippi, Massimo, Rocca, Maria Assunta, Storelli, Loredana, Pantano, Patrizia, Tommasin, Silvia, Cortese, Rosa, De Stefano, Nicola, Tedeschi, Gioacchino, Gallo, Antonio, Marzi C., d'Ambrosio A., Diciotti S., Bisecco A., Altieri M., Filippi M., Rocca M.A., Storelli L., Pantano P., Tommasin S., Cortese R., De Stefano N., Tedeschi G., and Gallo A.

Subjects
MRI, artificial intelligence, cognitive performance, information processing speed, machine learning, multiple sclerosis, symbol digit modalities test, Radiological and Ultrasound Technology, Neuropsychological Tests, Magnetic Resonance Imaging, Neurology, multiple sclerosi, Humans, Radiology, Nuclear Medicine and imaging, Neurology (clinical), Anatomy, Cognition Disorders, Processing Speed
Abstract

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS.

Published
2023

31. Validation of an iPad version of the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) (P3-3.010)

Author

Sacca, Francesco, primary, Costabile, Teresa, additional, Signoriello, Elisabetta, additional, Lauro, Francesca, additional, Altieri, Manuela, additional, Ziello, Antonio Rosario, additional, d’Ambrosio, Alessandro, additional, Bisecco, Alvino, additional, Maniscalco, Giorgia Teresa, additional, Bonavita, Simona, additional, Gallo, Antonio, additional, Morra, Vincenzo Brescia, additional, Lus, Giacomo, additional, and Russo, Cinzia Valeria, additional

Published
2023
Full Text
View/download PDF

32. Relation of sensorimotor and cognitive cerebellum functional connectivity with brain structural damage in patients with multiple sclerosis and no disability

Author

Tommasin, Silvia, Iakovleva, Viktoriia, Maria Assunta Rocca, Gianni', Costanza, Gioacchino, Tedeschi, De Stefano, Nicola, Pozzilli, Carlo, Massimo, Filippi, Pantano, Patrizia, Petsas, Nikolaos, Ruggieri, Serena, Piervincenzi, Claudia, Paola, Valsasina, Mauro, Sibilia, Preziosa, Paolo, Loredana, Storelli, Gallo, Antonio, Alvino, Bisecco, D'Ambrosio, Alessandro, Maria Laura Stromillo, Riccardo Tappa Brocci and, Tommasin, Silvia, Iakovleva, Viktoriia, Rocca, Maria Assunta, Giannì, Costanza, Tedeschi, Gioacchino, De Stefano, Nicola, Pozzilli, Carlo, Filippi, Massimo, and Pantano, Patrizia

Subjects
Multiple Sclerosis, Brain, Relapsing-Remitting, cognitive cerebellum, disability, functional magnetic resonance imaging, multiples sclerosis, neural plasticity, sensorimotor cerebellum, brain, cerebellum, cognition, Gray Matter, Humans, Magnetic Resonance Imaging, Brain Injuries, Multiple Sclerosis, Relapsing-Remitting, White Matter, Cognition, Neurology, Cerebellum, Neurology (clinical)
Abstract

Background and purpose: To investigate the relationship between the functional connectivity (FC) of the sensorimotor and cognitive cerebellum and measures of structural damage in patients with multiple sclerosis (MS) and no physical disability. Methods: We selected 144 relapsing-remitting MS patients with an Expanded Disability Status Scale score of ≤1.5 and 98 healthy controls from the Italian Neuroimaging Network Initiative database. From multimodal 3T magnetic resonance imaging (MRI), including functional MRI at rest, we calculated lesion load, cortical thickness, and white matter, cortical gray matter, and caudate, putamen, thalamic, and cerebellar volumes. Voxel-wise FC of the sensorimotor and cognitive cerebellum was assessed with seed-based analysis, and multiple regression analysis was used to evaluate the relationship between FC and structural damage. Results: Whole brain, white matter, caudate, putamen, and thalamic volumes were reduced in patients compared to controls, whereas cortical gray matter was not significantly different in patients versus controls. Both the sensorimotor and cognitive cerebellum showed a widespread pattern of increased and decreased FC that were negatively associated with structural measures, indicating that the lower the FC, the greater the tissue loss. Lastly, among multiple structural measures, cortical gray matter and white matter volumes were the best predictors of cerebellar FC alterations. Conclusions: Increased and decreased cerebellar FC with several brain areas coexist in MS patients with no disability. Our data suggest that white matter loss hampers FC, whereas, in the absence of atrophy, cortical volume represents the framework for FC to increase.

Published
2022
Full Text
View/download PDF

34. COVID-19 Vaccines and Attributable Risk of Neurological Disorders: A Multicentre, Case-Control Study (COVIVAX)

Author

Pupillo, Elisabetta, primary, Bianchi, Elisa, additional, Beghi, Ettore, additional, Pedrazzini, Francesco Andrea, additional, Giglio, Angela, additional, Schilke, Edoardo Dalmato, additional, Percetti, Marco, additional, Morotti Colleoni, Carlo, additional, Mainini, Gabriele, additional, Calabresi, Paolo, additional, Primiano, Guido, additional, Frisullo, Giovanni, additional, Padovani, Alessandro, additional, Cristillo, Viviana, additional, Pilotto, Andrea, additional, Arici, Davide, additional, Gipponi, Stefano, additional, Tedeschi, Gioacchino, additional, D’Ambrosio, Alessandro, additional, Melisi, Rosario, additional, Gallo, Antonio, additional, Bisecco, Alvino, additional, Salmaggi, Andrea, additional, Basilico, Paola, additional, Scaccabarozzi, Chiara, additional, Kiferle, Lorenzo, additional, Valenti, Raffaella, additional, Avino, Gianluca, additional, Borghi, Annamaria, additional, Contardi, Sara, additional, Zini, Andrea, additional, Ferrarese, Carlo, additional, and Bereta, Simone, additional

Published
2023
Full Text
View/download PDF

36. AQP4-MOG Double-Positive Neuromyelitis Optica Spectrum Disorder: Case Report with Central and Peripheral Nervous System Involvement and Review of Literature

Author

Spiezia, Antonio Luca, primary, Carotenuto, Antonio, additional, Iovino, Aniello, additional, Moccia, Marcello, additional, Gastaldi, Matteo, additional, Iodice, Rosa, additional, Tedeschi, Enrico, additional, Petracca, Maria, additional, Lavorgna, Luigi, additional, d’Ambrosio, Alessandro, additional, Brescia Morra, Vincenzo, additional, and Lanzillo, Roberta, additional

Published
2022
Full Text
View/download PDF

37. Efficacy and safety of belantamab-mafodotin in triple-refractory multiple myeloma patients: A multicentric real-life experience

Author

Iula, Rossella, primary, De Novellis, Danilo, additional, Trastulli, Fabio, additional, Della Pepa, Roberta, additional, Fontana, Raffaele, additional, Carobene, Angela, additional, Di Perna, Maria, additional, D’Ambrosio, Alessandro, additional, Romano, Martina, additional, Leone, Aldo, additional, De Fazio, Laura, additional, Fiumarella, Alfonso, additional, Gaeta, Giuseppe, additional, Marafioti, Violetta, additional, Barbato, Serafina, additional, Palmieri, Salvatore, additional, Rocco, Stefano, additional, Serio, Bianca, additional, Califano, Catello, additional, Pane, Fabrizio, additional, Ferrara, Felicetto, additional, Giudice, Valentina, additional, Selleri, Carmine, additional, and Catalano, Lucio, additional

Published
2022
Full Text
View/download PDF

38. Post-contrast MRI in multiple sclerosis: Towards a judicious use of gadolinium-based contrast agents

Author

Gentili, Lucia, primary, Capuano, Rocco, additional, Gaetani, Lorenzo, additional, Fiacca, Andrea, additional, Bisecco, Alvino, additional, d'Ambrosio, Alessandro, additional, Mancini, Andrea, additional, Guercini, Giorgio, additional, Tedeschi, Gioacchino, additional, Parnetti, Lucilla, additional, Gallo, Antonio, additional, and Di Filippo, Massimiliano, additional

Published
2022
Full Text
View/download PDF

41. Exposure to natalizumab throughout pregnancy: effectiveness and safety in an Italian cohort of women with multiple sclerosis

Author

Landi, Doriana, primary, Bovis, Francesca, additional, Grimaldi, Alfonso, additional, Annovazzi, Pietro Osvaldo, additional, Bertolotto, Antonio, additional, Bianchi, Alessia, additional, Borriello, Giovanna, additional, Brescia Morra, Vincenzo, additional, Bucello, Sebastiano, additional, Buscarinu, Maria Chiara, additional, Caleri, Francesca, additional, Capobianco, Marco, additional, Capra, Ruggero, additional, Cellerino, Maria, additional, Centonze, Diego, additional, Cerqua, Raffaella, additional, Chisari, Clara Grazia, additional, Clerico, Marinella, additional, Cocco, Eleonora, additional, Cola, Gaia, additional, Cordioli, Cinzia, additional, Curti, Erica, additional, d'Ambrosio, Alessandro, additional, D'Amico, Emanuele, additional, De Luca, Giovanna, additional, Di Filippo, Massimiliano, additional, Di Lemme, Sonia, additional, Fantozzi, Roberta, additional, Ferraro, Diana, additional, Ferraro, Elisabetta, additional, Gallo, Antonio, additional, Gasperini, Claudio, additional, Granella, Franco, additional, Inglese, Matilde, additional, Lanzillo, Roberta, additional, Lorefice, Lorena, additional, Lus, Giacomo, additional, Malucchi, Simona, additional, Margoni, Monica, additional, Mataluni, Giorgia, additional, Mirabella, Massimiliano, additional, Moiola, Lucia, additional, Nicoletti, Carolina Gabri, additional, Nociti, Viviana, additional, Patti, Francesco, additional, Pinardi, Federica, additional, Portaccio, Emilio, additional, Pozzilli, Carlo, additional, Ragonese, Paolo, additional, Rasia, Sarah, additional, Salemi, Giuseppe, additional, Signoriello, Elisabetta, additional, Vitetta, Francesca, additional, Totaro, Rocco, additional, Sormani, Maria Pia, additional, Amato, Maria Pia, additional, and Marfia, Girolama Alessandra, additional

Published
2022
Full Text
View/download PDF

42. Validation of an iPad version of the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS)

Author

Costabile, Teresa, primary, Signoriello, Elisabetta, additional, Lauro, Francesca, additional, Altieri, Manuela, additional, Ziello, Antonio Rosario, additional, D’Ambrosio, Alessandro, additional, Bisecco, Alvino, additional, Maniscalco, Giorgia, additional, Bonavita, Simona, additional, Gallo, Antonio, additional, Morra, Vincenzo Brescia, additional, Lus, Giacomo, additional, Saccà, Francesco, additional, and Russo, Cinzia Valeria, additional

Published
2022
Full Text
View/download PDF

43. Liposomal doxorubicin supercharge‐containing front‐line treatment in patients with advanced‐stage diffuse large B‐cell lymphoma or classical Hodgkin lymphoma: Preliminary results of a single‐centre phase II study

Author

Picardi, Marco, primary, Giordano, Claudia, additional, Pugliese, Novella, additional, Esposito, Maria, additional, Fatigati, Melania, additional, Muriano, Francesco, additional, Rascato, Maria G., additional, Della Pepa, Roberta, additional, D'Ambrosio, Alessandro, additional, Vigliar, Elena, additional, Troncone, Giancarlo, additional, Russo, Daniela, additional, Mascolo, Massimo, additional, Esposito, Giovanni, additional, Prastaro, Mariella, additional, Esposito, Roberta, additional, Tocchetti, Carlo G., additional, Fonti, Rosa, additional, Mainolfi, Ciro, additional, Del Vecchio, Silvana, additional, and Pane, Fabrizio, additional

Published
2022
Full Text
View/download PDF

44. Exposure to natalizumab throughout pregnancy: effectiveness and safety in an Italian cohort of women with multiple sclerosis

Author

Landi, Doriana, Bovis, Francesca, Grimaldi, Alfonso, Annovazzi, Pietro Osvaldo, Bertolotto, Antonio, Bianchi, Alessia, Borriello, Giovanna, Brescia Morra, Vincenzo, Bucello, Sebastiano, Buscarinu, Maria Chiara, Caleri, Francesca, Capobianco, Marco, Capra, Ruggero, Cellerino, Maria, Centonze, Diego, Cerqua, Raffaella, Chisari, Clara Grazia, Clerico, Marinella, Cocco, Eleonora, Cola, Gaia, Cordioli, Cinzia, Curti, Erica, D'Ambrosio, Alessandro, D'Amico, Emanuele, De Luca, Giovanna, Di Filippo, Massimiliano, Di Lemme, Sonia, Fantozzi, Roberta, Ferraro, Diana, Ferraro, Elisabetta, Gallo, Antonio, Gasperini, Claudio, Granella, Franco, Inglese, Matilde, Lanzillo, Roberta, Lorefice, Lorena, Lus, Giacomo, Malucchi, Simona, Margoni, Monica, Mataluni, Giorgia, Mirabella, Massimiliano, Moiola, Lucia, Nicoletti, Carolina Gabri, Nociti, Viviana, Patti, Francesco, Pinardi, Federica, Portaccio, Emilio, Pozzilli, Carlo, Ragonese, Paolo, Rasia, Sarah, Salemi, Giuseppe, Signoriello, Elisabetta, Vitetta, Francesca, Totaro, Rocco, Sormani, Maria Pia, Amato, Maria Pia, Marfia, Girolama Alessandra, Mirabella, Massimiliano (ORCID:0000-0002-7783-114X), Nociti, Viviana (ORCID:0000-0002-4607-3948), Landi, Doriana, Bovis, Francesca, Grimaldi, Alfonso, Annovazzi, Pietro Osvaldo, Bertolotto, Antonio, Bianchi, Alessia, Borriello, Giovanna, Brescia Morra, Vincenzo, Bucello, Sebastiano, Buscarinu, Maria Chiara, Caleri, Francesca, Capobianco, Marco, Capra, Ruggero, Cellerino, Maria, Centonze, Diego, Cerqua, Raffaella, Chisari, Clara Grazia, Clerico, Marinella, Cocco, Eleonora, Cola, Gaia, Cordioli, Cinzia, Curti, Erica, D'Ambrosio, Alessandro, D'Amico, Emanuele, De Luca, Giovanna, Di Filippo, Massimiliano, Di Lemme, Sonia, Fantozzi, Roberta, Ferraro, Diana, Ferraro, Elisabetta, Gallo, Antonio, Gasperini, Claudio, Granella, Franco, Inglese, Matilde, Lanzillo, Roberta, Lorefice, Lorena, Lus, Giacomo, Malucchi, Simona, Margoni, Monica, Mataluni, Giorgia, Mirabella, Massimiliano, Moiola, Lucia, Nicoletti, Carolina Gabri, Nociti, Viviana, Patti, Francesco, Pinardi, Federica, Portaccio, Emilio, Pozzilli, Carlo, Ragonese, Paolo, Rasia, Sarah, Salemi, Giuseppe, Signoriello, Elisabetta, Vitetta, Francesca, Totaro, Rocco, Sormani, Maria Pia, Amato, Maria Pia, Marfia, Girolama Alessandra, Mirabella, Massimiliano (ORCID:0000-0002-7783-114X), and Nociti, Viviana (ORCID:0000-0002-4607-3948)

Abstract

Assessing the risk of clinical and radiological reactivation during pregnancy and post partum in women with multiple sclerosis (MS) treated with natalizumab (NTZ) throughout pregnancy (LONG_EXP) compared with women interrupting treatment before (NO_EXP) and within >-30 days and ≤90 days from conception (SHORT_EXP), and describing newborns' outcomes.

Published
2022

47. Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

Author

Alessandro Pasquale De Rosa, Esposito, Fabrizio, Paola, Valsasina, D'Ambrosio, Alessandro, Alvino, Bisecco, Maria, A Rocca, Tommasin, Silvia, Chiara, Marzi, De Stefano, Nicola, Battaglini, Marco, Pantano, Patrizia, Cirillo, Mario, Gioacchino, Tedeschi, Massimo, Filippi, Antonio, Gallo, Manuela, Altieri, Riccardo, Borgo, Rocco, Capuano, Loredana, Storelli, Elisabetta, Pagani, Mauro, Sibilia, Piervincenzi, Claudia, Ruggieri, Serena, Petsas, Nikolaos, Cortese, ROSA MARIA, and Maria Laura Stromillo

Subjects
Multiple sclerosis, Functional connectivity, Functional magnetic resonance imaging, Quality control, MRI, MS
Published
2022

48. Unmutated IGHV1-69 CLL Clone Displays a Distinct Gene Expression Profile by a Comparative qRT-PCR Assay

Author

Mimmi, Selena, primary, Maisano, Domenico, additional, Dattilo, Vincenzo, additional, Gentile, Massimo, additional, Chiurazzi, Federico, additional, D’Ambrosio, Alessandro, additional, Zimbo, Annamaria, additional, Nisticò, Nancy, additional, Aloisio, Annamaria, additional, Vecchio, Eleonora, additional, Fiume, Giuseppe, additional, Iaccino, Enrico, additional, and Quinto, Ileana, additional

Published
2022
Full Text
View/download PDF

49. Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set.

Author

Marzi, Chiara, d'Ambrosio, Alessandro, Diciotti, Stefano, Bisecco, Alvino, Altieri, Manuela, Filippi, Massimo, Rocca, Maria Assunta, Storelli, Loredana, Pantano, Patrizia, Tommasin, Silvia, Cortese, Rosa, De Stefano, Nicola, Tedeschi, Gioacchino, and Gallo, Antonio

Subjects
*MAGNETIC resonance imaging, *MACHINE learning, *MULTIPLE sclerosis, *GRAY matter (Nerve tissue), *INFORMATION processing
Abstract

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T‐MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

50. Multicenter data harmonization for regional brain atrophy and application in multiple sclerosis.

Author

Pagani, Elisabetta, Storelli, Loredana, Pantano, Patrizia, Petsas, Nikolaos, Tedeschi, Gioacchino, Gallo, Antonio, De Stefano, Nicola, Battaglini, Marco, Rocca, Maria A., Filippi, Massimo, for the INNI Network, Valsasina, Paola, Sibilia, Mauro, Preziosa, Paolo, Bisecco, Alvino, d'Ambrosio, Alessandro, Altieri, Manuela, Capuano, Rocco, Tommasin, Silvia, and Ruggieri, Serena

Subjects
CEREBRAL atrophy, DATA harmonization, MULTIPLE sclerosis, DATA libraries, VOXEL-based morphometry
Abstract

Background: In multiple sclerosis (MS), determination of regional brain atrophy is clinically relevant. However, analysis of large datasets is rare because of the increased variability in multicenter data. Purpose: To compare different methods to correct for center effects. To investigate regional gray matter (GM) volume in relapsing–remitting MS in a large multicenter dataset. Methods: MRI scans of 466 MS patients and 279 healthy controls (HC) were retrieved from the Italian Neuroimaging Network Initiative repository. Voxel-based morphometry was performed. The center effect was accounted for with different methods: (a) no correction, (b) factor in the statistical model, (c) ComBat method and (d) subsampling procedure to match single-center distributions. By applying the best correction method, GM atrophy was assessed in MS patients vs HC and according to clinical disability, disease duration and T2 lesion volume. Results were assessed voxel-wise using general linear model. Results: The average residuals for the harmonization methods were 5.03 (a), 4.42 (b), 4.26 (c) and 2.98 (d). The comparison between MS patients and HC identified thalami and other deep GM nuclei, the cerebellum and several cortical regions. At single-center analysis, the thalami were always involved, whereas different other regions were found in each center. Cerebellar atrophy correlated with clinical disability, while deep GM nuclei atrophy correlated with T2-lesion volume. Conclusion: Harmonization based on subsampling more effectively decreased the residuals of the statistical model applied. In comparison with findings from single-center analysis, the multicenter results were more robust, highlighting the importance of data repositories from multiple centers. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results