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Gasparini, Mauro

0000-0001-8011-4005

Mayo Clinic

Politecnico di Torino

Citations 3

The Current Diagnostic Performance of MRI-Based Radiomics for Glioma Grading: A Meta-Analysis
Skogen, Karoline , Zeppieri, Marco , Ugga, Lorenzo , Brinjikji, Waleed , Maria, Lucio De , Ponzio, Francesco , Cho, Hwan-ho , Tsougos, Ioannis , Gasparini, Mauro , Ius, Tamara , Panciani, Pier Paolo , Fontanella, Marco Maria , Agosti, Edoardo

Journal of Integrative Neuroscience | May 17, 2024 | Volume: 23 | Issue: 5 | Pages: No page available

10.31083/j.jin2305100 Get It

Background: Multiple radiomics models have been proposed for grading glioma using different algorithms, features, and sequences of magnetic resonance imaging. The research seeks to assess the present overall performance of radiomics for grading glioma. Methods: A systematic literature review of the databases Ovid MEDLINE PubMed, and Ovid EMBASE for publications published on radiomics for glioma grading between 2012 and 2023 was performed. The systematic review was carried out following the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Results: In the meta-analysis, a total of 7654 patients from 40 articles, were assessed. R-package mada was used for modeling the joint estimates of specificity (SPE) and sensitivity (SEN). Pooled event rates across studies were performed with a random-effects meta-analysis. The heterogeneity of SPE and SEN were based on the χ2 test. Overall values for SPE and SEN in the differentiation between high-grade gliomas (HGGs) and low-grade gliomas (LGGs) were 84% and 91%, respectively. With regards to the discrimination between World Health Organization (WHO) grade 4 and WHO grade 3, the overall SPE was 81% and the SEN was 89%. The modern non-linear classifiers showed a better trend, whereas textural features tend to be the best-performing (29%) and the most used. Conclusions: Our findings confirm that present radiomics’ diagnostic performance for glioma grading is superior in terms of SEN and SPE for the HGGs vs. LGGs discrimination task when compared to the WHO grade 4 vs. 3 task.
P112/92  The current diagnostic performance of MRI-based radiomics for glioma grading
Skogen, Karoline , Ugga, Lorenzo , Brinjikji, Waleed , Maria, Lucio De , Ponzio, Francesco , Agosti, Edoardo , Cho, Hwan-ho , Tsougos, Ioannis , Gasparini, Mauro , Panciani, Pier Paolo , Fontanella, Marco Maria

Abstracts | August 21, 2023 | Volume: No volume available | Issue: No issue available | Pages: A58.2-A58

10.1136/jnis-2023-esmint.142 Get It

Impact of Aspirin on Takotsubo Syndrome: A Propensity Score-Based Analysis of the InterTAK Registry
Gili, Sebastiano , Bertaina, Maurizio , Iannaccone, Mario , Cammann, Victoria L. , Vece, Davide Di , Saglietto, Andrea , Szawan, Konrad A. , Frangieh, Antonio H. , Boffini, Beatrice, Annaratone, Margherita, Sarcon, Annahita, Levinson, Rena A. , Franke, Jennifer , Napp, L. Christian , Münzel, Thomas , Knorr, Maike, Heiner, Susanne, Katus, Hugo A. , Burgdorf, Christof , Tschöpe, Carsten , Pieske, Burkert , Rajan, Lawrence, Michels, Guido, Pfister, Roman , Cuneo, Alessandro , Jacobshagen, Claudius, Karakas, Mahir , Köenig, Wolfgang , Rottbauer, Wolfgang , Said, Samir M., Banning, Adrian , Cuculi, Florim , Kobza, Richard , Fischer, Thomas, Vasankari, Tuija , Airaksinen, Juhani , Opolski, Grzegorz , Dworakowski, Rafał , MacCarthy, Philip , Osswald, Stefan , Galiuto, Leonarda , Franz, Wolfgang M., Empen, Klaus , Felix, Stephan B. , El‐Battrawy, Ibrahim , Akın, İbrahim , Borggrefe, Martin, Kozel, Martin , Widimský, Petr , Gilyarova, Ekaterina, Gilyarov, Mikhail , Biondi‐Zoccai, Giuseppe , Winchester, David E. , Ukena, Christian , Prasad, Abhiram , Böhm, Michael , Bossone, Eduardo , Citro, Rodolfo , Lüscher, Thomas F. , Ghadri, Jelena R. , Templin, Christian , Gilyarov, Mikhail , Bossone, Eduardo , Citro, Rodolfo , El-Battrawy, Ibrahim , Prasad, Abhiram , Tschöpe, Carsten , Koenig, Wolfgang , Banning, Adrian , Kobza, Richard , Gilyarov, Mikhail , Ukena, Christian , D’Ascenzo, Fabrizio , Kato, Ken , Jaguszewski, Miłosz , Noutsias, Michel , Schunkert, Heribert , Thiele, Hölger , Bauersachs, Johann , Hasenfuß, Gerd , Braun-Dullaeus, Ruediger Christian , Kaiser, Christoph A. , Crea, Filippo , Dichtl, Wolfgang , Delmas, Clément , Lairez, Olivier , Horowitz, John D. , Toušek, Petr , Shilova, Alexandra S. , Neuhaus, Michael, Bax, Jeroen J. , Mario, Carlo Di , Gasparini, Mauro , Ruschitzka, Frank T. , Rinaldi, Mauro , Ferrari, Gaetano Maria De

European Journal of Heart Failure | December 21, 2019 | Volume: 22 | Issue: 2 | Pages: 330-337

10.1002/ejhf.1698 Get It

Abstract Aims The aim of the present study was to investigate the impact of aspirin on prognosis in takotsubo syndrome (TTS). Methods and results Patients from the International Takotsubo (InterTAK) Registry were categorized into two groups based on aspirin prescription at discharge. A comparison of clinical outcomes between groups was performed using an adjusted analysis with propensity score (PS) stratification; results from the unadjusted analysis were also reported to note the effect of the PS adjustment. Major adverse cardiac and cerebrovascular events (MACCE: a composite of death, myocardial infarction, TTS recurrence, stroke or transient ischaemic attack) were assessed at 30-day and 5-year follow-up. A total of 1533 TTS patients with known status regarding aspirin prescription at discharge were included. According to the adjusted analysis based on PS stratification, aspirin was not associated with a lower hazard of MACCE at 30-day [hazard ratio (HR) 1.24, 95% confidence interval (CI) 0.50–3.04, P = 0.64] or 5-year follow-up (HR 1.11, 95% CI 0.78–1.58, P = 0.58). These results were confirmed by sensitivity analyses performed with alternative PS-based methods, i.e. covariate adjustment and inverse probability of treatment weighting. Conclusion In the present study, no association was found between aspirin use in TTS patients and a reduced risk of MACCE at 30-day and 5-year follow-up. These findings should be confirmed in adequately powered randomized controlled trials. ClinicalTrials.gov Identifier: NCT01947621.