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Öz G, Cocozza S, Henry PG, Lenglet C, Deistung A, Faber J, Schwarz AJ, Timmann D, Van Dijk KRA, Harding IH. MR Imaging in Ataxias: Consensus Recommendations by the Ataxia Global Initiative Working Group on MRI Biomarkers. Cerebellum 2024; 23:931-945. [PMID: 37280482 PMCID: PMC11102392 DOI: 10.1007/s12311-023-01572-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/18/2023] [Indexed: 06/08/2023]
Abstract
With many viable strategies in the therapeutic pipeline, upcoming clinical trials in hereditary and sporadic degenerative ataxias will benefit from non-invasive MRI biomarkers for patient stratification and the evaluation of therapies. The MRI Biomarkers Working Group of the Ataxia Global Initiative therefore devised guidelines to facilitate harmonized MRI data acquisition in clinical research and trials in ataxias. Recommendations are provided for a basic structural MRI protocol that can be used for clinical care and for an advanced multi-modal MRI protocol relevant for research and trial settings. The advanced protocol consists of modalities with demonstrated utility for tracking brain changes in degenerative ataxias and includes structural MRI, magnetic resonance spectroscopy, diffusion MRI, quantitative susceptibility mapping, and resting-state functional MRI. Acceptable ranges of acquisition parameters are provided to accommodate diverse scanner hardware in research and clinical contexts while maintaining a minimum standard of data quality. Important technical considerations in setting up an advanced multi-modal protocol are outlined, including the order of pulse sequences, and example software packages commonly used for data analysis are provided. Outcome measures most relevant for ataxias are highlighted with use cases from recent ataxia literature. Finally, to facilitate access to the recommendations by the ataxia clinical and research community, examples of datasets collected with the recommended parameters are provided and platform-specific protocols are shared via the Open Science Framework.
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Affiliation(s)
- Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA.
| | - Sirio Cocozza
- UNINA Department of Advanced Biomedical Sciences, University of Naples Federico II , Naples, Italy
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Andreas Deistung
- Department for Radiation Medicine, University Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | | | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Koene R A Van Dijk
- Digital Sciences and Translational Imaging, Early Clinical Development, Pfizer, Inc., Cambridge, MA, USA
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Australia
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Öz G, Cocozza S, Henry PG, Lenglet C, Deistung A, Faber J, Schwarz AJ, Timmann D, Van Dijk KRA, Harding IH. Correction to: MR Imaging in Ataxias: Consensus Recommendations by the Ataxia Global Initiative Working Group on MRI Biomarkers. Cerebellum 2024; 23:946-947. [PMID: 37581744 PMCID: PMC11102403 DOI: 10.1007/s12311-023-01589-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Affiliation(s)
- Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA.
| | - Sirio Cocozza
- UNINA Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Andreas Deistung
- Department for Radiation Medicine, University Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | | | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Koene R A Van Dijk
- Digital Sciences and Translational Imaging, Early Clinical Development, Pfizer, Inc., Cambridge, MA, USA
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Australia
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Pontillo G, Tranfa M, Scaravilli A, Monti S, Capuano I, Riccio E, Rizzo M, Brunetti A, Palma G, Pisani A, Cocozza S. In vivo demonstration of globotriaosylceramide brain accumulation in Fabry Disease using MR Relaxometry. Neuroradiology 2024:10.1007/s00234-024-03380-5. [PMID: 38771548 DOI: 10.1007/s00234-024-03380-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/13/2024] [Indexed: 05/22/2024]
Abstract
PURPOSE How to measure brain globotriaosylceramide (Gb3) accumulation in Fabry Disease (FD) patients in-vivo is still an open challenge. The objective of this study is to provide a quantitative, non-invasive demonstration of this phenomenon using quantitative MRI (qMRI). METHODS In this retrospective, monocentric cross-sectional study conducted from November 2015 to July 2018, FD patients and healthy controls (HC) underwent an MRI scan with a relaxometry protocol to compute longitudinal relaxation rate (R1) maps to evaluate gray (GM) and white matter (WM) lipid accumulation. In a subgroup of 22 FD patients, clinical (FAbry STabilization indEX -FASTEX- score) and biochemical (residual α-galactosidase activity) variables were correlated with MRI data. Quantitative maps were analyzed at both global ("bulk" analysis) and regional ("voxel-wise" analysis) levels. RESULTS Data were obtained from 42 FD patients (mean age = 42.4 ± 12.9, M/F = 16/26) and 49 HC (mean age = 42.3 ± 16.3, M/F = 28/21). Compared to HC, FD patients showed a widespread increase in R1 values encompassing both GM (pFWE = 0.02) and WM (pFWE = 0.02) structures. While no correlations were found between increased R1 values and FASTEX score, a significant negative correlation emerged between residual enzymatic activity levels and R1 values in GM (r = -0.57, p = 0.008) and WM (r = -0.49, p = 0.03). CONCLUSIONS We demonstrated the feasibility and clinical relevance of non-invasively assessing cerebral Gb3 accumulation in FD using MRI. R1 mapping might be used as an in-vivo quantitative neuroimaging biomarker in FD patients.
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Affiliation(s)
- Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Serena Monti
- Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Ivana Capuano
- Department of Public Health, University of Naples "Federico II", Naples, Italy
| | - Eleonora Riccio
- Institute for Biomedical Research and Innovation, National Research Council, Palermo, Italy
| | - Manuela Rizzo
- Department of Public Health, University of Naples "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Giuseppe Palma
- Institute of Nanotechnology, National Research Council, Lecce, Italy
| | - Antonio Pisani
- Department of Public Health, University of Naples "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
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Harding IH, Nur Karim MI, Selvadurai LP, Corben LA, Delatycki MB, Monti S, Saccà F, Georgiou-Karistianis N, Cocozza S, Egan GF. Localized Changes in Dentate Nucleus Shape and Magnetic Susceptibility in Friedreich Ataxia. Mov Disord 2024. [PMID: 38644761 DOI: 10.1002/mds.29816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 03/07/2024] [Accepted: 04/01/2024] [Indexed: 04/23/2024] Open
Abstract
BACKGROUND The dentate nuclei of the cerebellum are key sites of neuropathology in Friedreich ataxia (FRDA). Reduced dentate nucleus volume and increased mean magnetic susceptibility, a proxy of iron concentration, have been reported by magnetic resonance imaging studies in people with FRDA. Here, we investigate whether these changes are regionally heterogeneous. METHODS Quantitative susceptibility mapping data were acquired from 49 people with FRDA and 46 healthy controls. The dentate nuclei were manually segmented and analyzed using three dimensional vertex-based shape modeling and voxel-based assessments to identify regional changes in morphometry and susceptibility, respectively. RESULTS Individuals with FRDA, relative to healthy controls, showed significant bilateral surface contraction most strongly at the rostral and caudal boundaries of the dentate nuclei. The magnitude of this surface contraction correlated with disease duration, and to a lesser extent, ataxia severity. Significantly greater susceptibility was also evident in the FRDA cohort relative to controls, but was instead localized to bilateral dorsomedial areas, and also correlated with disease duration and ataxia severity. CONCLUSIONS Changes in the structure of the dentate nuclei in FRDA are not spatially uniform. Atrophy is greatest in areas with high gray matter density, whereas increases in susceptibility-reflecting iron concentration, demyelination, and/or gliosis-predominate in the medial white matter. These findings converge with established histological reports and indicate that regional measures of dentate nucleus substructure are more sensitive measures of disease expression than full-structure averages. Biomarker development and therapeutic strategies that directly target the dentate nuclei, such as gene therapies, may be optimized by targeting these areas of maximal pathology. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Muhammad Ikhsan Nur Karim
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
| | - Louisa P Selvadurai
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Louise A Corben
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, Australia
- Department of Pediatrics, University of Melbourne, Parkville, Australia
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Martin B Delatycki
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, Australia
- Department of Pediatrics, University of Melbourne, Parkville, Australia
| | - Serena Monti
- Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Francesco Saccà
- Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Nellie Georgiou-Karistianis
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Australia
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5
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De Michele G, Maione L, Cocozza S, Tranfa M, Pane C, Galatolo D, De Rosa A, De Michele G, Saccà F, Filla A. Ataxia and Hypogonadism: a Review of the Associated Genes and Syndromes. Cerebellum 2024; 23:688-701. [PMID: 36997834 DOI: 10.1007/s12311-023-01549-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/20/2023] [Indexed: 04/01/2023]
Abstract
The association of hypogonadism and cerebellar ataxia was first recognized in 1908 by Gordon Holmes. Since the seminal description, several heterogeneous phenotypes have been reported, differing for age at onset, associated features, and gonadotropins levels. In the last decade, the genetic bases of these disorders are being progressively uncovered. Here, we review the diseases associating ataxia and hypogonadism and the corresponding causative genes. In the first part of this study, we focus on clinical syndromes and genes (RNF216, STUB1, PNPLA6, AARS2, SIL1, SETX) predominantly associated with ataxia and hypogonadism as cardinal features. In the second part, we mention clinical syndromes and genes (POLR3A, CLPP, ERAL1, HARS, HSD17B4, LARS2, TWNK, POLG, ATM, WFS1, PMM2, FMR1) linked to complex phenotypes that include, among other features, ataxia and hypogonadism. We propose a diagnostic algorithm for patients with ataxia and hypogonadism, and we discuss the possible common etiopathogenetic mechanisms.
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Affiliation(s)
- Giovanna De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy.
| | - Luigi Maione
- Department of Endocrinology and Reproductive Diseases, Paris-Saclay University, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin Bicetre, Paris, France
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, Federico II University, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, Federico II University, Naples, Italy
| | - Chiara Pane
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Daniele Galatolo
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
| | - Anna De Rosa
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Giuseppe De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Francesco Saccà
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Alessandro Filla
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
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6
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Scaravilli A, Tranfa M, Pontillo G, Brais B, De Michele G, La Piana R, Saccà F, Santorelli FM, Synofzik M, Brunetti A, Cocozza S. A Review of Brain and Pituitary Gland MRI Findings in Patients with Ataxia and Hypogonadism. Cerebellum 2024; 23:757-774. [PMID: 37155088 DOI: 10.1007/s12311-023-01562-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/26/2023] [Indexed: 05/10/2023]
Abstract
The association of cerebellar ataxia and hypogonadism occurs in a heterogeneous group of disorders, caused by different genetic mutations often associated with a recessive inheritance. In these patients, magnetic resonance imaging (MRI) plays a pivotal role in the diagnostic workflow, with a variable involvement of the cerebellar cortex, alone or in combination with other brain structures. Neuroimaging involvement of the pituitary gland is also variable. Here, we provide an overview of the main clinical and conventional brain and pituitary gland MRI imaging findings of the most common genetic mutations associated with the clinical phenotype of ataxia and hypogonadism, with the aim of helping neuroradiologists in the identification of these disorders.
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Affiliation(s)
- Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
- Department of Electrical Engineering and Information Technology (DIETI), University of Naples "Federico II", Naples, Italy
| | - Bernard Brais
- Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, Montreal, Canada
| | - Giovanna De Michele
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Roberta La Piana
- Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, Montreal, Canada
| | - Francesco Saccà
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Tubingen, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Center for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Strasse 27, 72076, Tubingen, Germany
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
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Montella A, Tranfa M, Scaravilli A, Barkhof F, Brunetti A, Cole J, Gravina M, Marrone S, Riccio D, Riccio E, Sansone C, Spinelli L, Petracca M, Pisani A, Cocozza S, Pontillo G. Assessing brain involvement in Fabry disease with deep learning and the brain-age paradigm. Hum Brain Mapp 2024; 45:e26599. [PMID: 38520360 PMCID: PMC10960551 DOI: 10.1002/hbm.26599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 12/23/2023] [Accepted: 01/07/2024] [Indexed: 03/25/2024] Open
Abstract
While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain-age paradigm to assess whether FD patients' brains appear older than normal and to validate brain-predicted age difference (brain-PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index (FASTEX) was recorded as a measure of disease severity. Using minimally preprocessed 3D T1-weighted brain scans of healthy subjects from eight publicly available sources (N = 2160; mean age = 33 years [range 4-86]), we trained a model predicting chronological age based on a DenseNet architecture and used it to generate brain-age predictions in the internal cohort. Within a linear modeling framework, brain-PAD was tested for age/sex-adjusted associations with diagnostic group (FD vs. HC), FASTEX score, and both global and voxel-level neuroimaging measures. We studied 52 FD patients (40.6 ± 12.6 years; 28F) and 58 HC (38.4 ± 13.4 years; 28F). The brain-age model achieved accurate out-of-sample performance (mean absolute error = 4.01 years, R2 = .90). FD patients had significantly higher brain-PAD than HC (estimated marginal means: 3.1 vs. -0.1, p = .01). Brain-PAD was associated with FASTEX score (B = 0.10, p = .02), brain parenchymal fraction (B = -153.50, p = .001), white matter hyperintensities load (B = 0.85, p = .01), and tissue volume reduction throughout the brain. We demonstrated that FD patients' brains appear older than normal. Brain-PAD correlates with FD-related multi-organ damage and is influenced by both global brain volume and white matter hyperintensities, offering a comprehensive biomarker of (neurological) disease severity.
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Affiliation(s)
- Alfredo Montella
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | - Mario Tranfa
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | | | - Frederik Barkhof
- NMR Research Unit, Queen Square MS Centre, Department of NeuroinflammationUCL Institute of NeurologyLondonUK
- Department of Radiology and Nuclear MedicineMS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Dementia Research CentreUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Arturo Brunetti
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | - James Cole
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Dementia Research CentreUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Michela Gravina
- Department of Electrical Engineering and Information Technology (DIETI)University “Federico II”NaplesItaly
| | - Stefano Marrone
- Department of Electrical Engineering and Information Technology (DIETI)University “Federico II”NaplesItaly
| | - Daniele Riccio
- Department of Electrical Engineering and Information Technology (DIETI)University “Federico II”NaplesItaly
| | - Eleonora Riccio
- Department of Public Health, Nephrology UnitUniversity “Federico II”NaplesItaly
| | - Carlo Sansone
- Department of Electrical Engineering and Information Technology (DIETI)University “Federico II”NaplesItaly
| | - Letizia Spinelli
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | - Maria Petracca
- Department of Neurosciences and Reproductive and Odontostomatological SciencesUniversity “Federico II”NaplesItaly
- Department of Human NeurosciencesSapienza University of RomeRomeItaly
| | - Antonio Pisani
- Department of Public Health, Nephrology UnitUniversity “Federico II”NaplesItaly
| | - Sirio Cocozza
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | - Giuseppe Pontillo
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
- NMR Research Unit, Queen Square MS Centre, Department of NeuroinflammationUCL Institute of NeurologyLondonUK
- Department of Radiology and Nuclear MedicineMS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Department of Electrical Engineering and Information Technology (DIETI)University “Federico II”NaplesItaly
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Rovira À, Ben Salem D, Geraldo AF, Cappelle S, Del Poggio A, Cocozza S, Saatci I, Zlatareva D, Lojo S, Quattrocchi CC, Morales Á, Yousry T. Go Green in Neuroradiology: towards reducing the environmental impact of its practice. Neuroradiology 2024; 66:463-476. [PMID: 38353699 DOI: 10.1007/s00234-024-03305-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/03/2024] [Indexed: 02/23/2024]
Abstract
Raising public awareness about the relevance of supporting sustainable practices is required owing to the phenomena of global warming caused by the rising production of greenhouse gases. The healthcare sector generates a relevant proportion of the total carbon emissions in developed countries, and radiology is estimated to be a major contributor to this carbon footprint. Neuroradiology markedly contributes to this negative environmental effect, as this radiological subspecialty generates a high proportion of diagnostic and interventional imaging procedures, the majority of them requiring high energy-intensive equipment. Therefore, neuroradiologists and neuroradiological departments are especially responsible for implementing decisions and initiatives able to reduce the unfavourable environmental effects of their activities, by focusing on four strategic pillars-reducing energy, water, and helium use; properly recycling and/or disposing of waste and residues (including contrast media); encouraging environmentally friendly behaviour; and reducing the effects of ionizing radiation on the environment. The purpose of this article is to alert neuroradiologists about their environmental responsibilities and to analyse the most productive strategic axes, goals, and lines of action that contribute to reducing the environmental impact associated with their professional activities.
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Affiliation(s)
- Àlex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain.
| | | | - Ana Filipa Geraldo
- Diagnostic Neuroradiology Unit, Department of Radiology, Centro Hospitalar Vila Nova de Gaia/Espinho (CHVNG/E), Porto, Portugal
| | - Sarah Cappelle
- Department of Radiology, University Hospitals Leuven, Louvain, Belgium
| | - Anna Del Poggio
- Department of Neuroradiology and CERMAC, San Raffaele Hospital, Milan, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples, "Federico II", Naples, Italy
| | - Isil Saatci
- Section of Neurointervention, Neuroradiology, Private Koru Hospitals, Ankara, Turkey
| | - Dora Zlatareva
- Department of Radiology, Medical University Sofia, Sofia, Bulgaria
| | - Sara Lojo
- Department of Radiology, Hospital Álvaro Cunqueiro, Vigo, Spain
| | - Carlo Cosimo Quattrocchi
- Centre for Medical Sciences CISMed, University of Trento, Trento, Italy
- Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, Trento, Italy
| | - Ángel Morales
- Department of Radiology, Hospital Universitario Donostia, San Sebastián, Spain
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK
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9
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Cocozza S, Palma G. Of editorial processes, AI models, and medical literature: the Magnetic Resonance Audiometry experiment. Eur Radiol 2024:10.1007/s00330-024-10668-w. [PMID: 38451324 DOI: 10.1007/s00330-024-10668-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/24/2024] [Accepted: 02/01/2024] [Indexed: 03/08/2024]
Abstract
The potential of artificial intelligence (AI) in the field of medical research is unquestionable. Nevertheless, the scientific community has raised several concerns about a possible fraudulent use of these tools that might be used to generate inaccurate or, in extreme cases, erroneous messages that could find their way into the literature. In this experiment, we asked a generative AI program to write a technical report on a non-existing Magnetic Resonance Imaging technique called Magnetic Resonance Audiometry, receiving in return a full seemingly technically sound report, substantiated by equations and references. We have submitted this report to an international peer-reviewed indexed journal, passing the first round of review with only minor changes requested. With this experiment, we showed that the current peer-review system, already burdened by the overwhelming increase in number of publications, might be not ready to also handle the explosion of these techniques, showing the urgent need for the entire community to address both the issue of generative AI in scientific literature and probably a more profound discussion on the entire peer-review process. CLINICAL RELEVANCE STATEMENT: Generative AI models are shown to be able to create a full manuscript without any human intervention that can survive peer-review. Given the explosion of these techniques, a profound discussion on the entire peer-review process by the scientific community is mandatory. KEY POINTS: • The scientific community has raised several concerns about a possible fraudulent use of AI in scientific literature. • We asked a generative AI program to write a technical report on a non-existing technique, receiving in return a full technically sound report, substantiated by equations and references, that passed peer-review. • This experiment showed that the current peer-review system might be not ready to handle the explosion of generative AI techniques, advising for a profound discussion on the entire peer-review process.
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Affiliation(s)
- Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
| | - Giuseppe Palma
- Institute of Nanotechnology, National Research Council, Lecce, Italy
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Scaravilli A, Tranfa M, Pontillo G, Brais B, De Michele G, La Piana R, Saccà F, Santorelli FM, Synofzik M, Brunetti A, Cocozza S. CHARON: An Imaging-Based Diagnostic Algorithm to Navigate Through the Sea of Hereditary Degenerative Ataxias. Cerebellum 2024:10.1007/s12311-024-01677-y. [PMID: 38436911 DOI: 10.1007/s12311-024-01677-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/23/2024] [Indexed: 03/05/2024]
Abstract
The complexity in diagnosing hereditary degenerative ataxias lies not only in their rarity, but also in the variety of different genetic conditions that can determine sometimes similar and overlapping clinical findings. In this light, Magnetic Resonance Imaging (MRI) plays a key role in the evaluation of these conditions, being a fundamental diagnostic tool needed not only to exclude other causes determining the observed clinical phenotype, but also to proper guide to an adequate genetic testing. Here, we propose an MRI-based diagnostic algorithm named CHARON (Characterization of Hereditary Ataxias Relying On Neuroimaging), to help in disentangling among the numerous, and apparently very similar, hereditary degenerative ataxias. Being conceived from a neuroradiological standpoint, it is based primarily on an accurate evaluation of the observed MRI findings, with the first and most important being the pattern of cerebellar atrophy. Along with the evaluation of the presence, or absence, of additional signal changes and/or supratentorial involvement, CHARON allows for the identification of a small groups of ataxias sharing similar imaging features. The integration of additional MRI findings, demographic, clinical and laboratory data allow then for the identification of typical, and in some cases pathognomonic, phenotypes of hereditary ataxias.
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Affiliation(s)
- Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Bernard Brais
- Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, Montreal, Canada
| | - Giovanna De Michele
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Roberta La Piana
- Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, Montreal, Canada
| | - Francesco Saccà
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Center for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
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Tranfa M, Scaravilli A, Pastore C, Montella A, Lanzillo R, Kimura M, Jasperse B, Morra VB, Petracca M, Pontillo G, Brunetti A, Cocozza S. The impact of image contrast, resolution and reader expertise on black hole identification in Multiple Sclerosis. Neuroradiology 2024:10.1007/s00234-024-03310-5. [PMID: 38374410 DOI: 10.1007/s00234-024-03310-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
OBJECTIVES In the neuroradiological work-up of Multiple Sclerosis (MS), the detection of "black holes" (BH) represent an information of undeniable importance. Nevertheless, different sequences can be used in clinical practice to evaluate BH in MS. Aim of this study was to investigate the possible impact of different sequences, resolutions, and levels of expertise on the intra- and inter-rater reliability identification of BH in MS. METHODS Brain MRI scans of 85 MS patients (M/F = 22/63; mean age = 36.0 ± 10.2 years) were evaluated in this prospective single-center study. The acquisition protocol included a 3 mm SE-T1w sequence, a 1 mm 3D-GrE-T1w sequence from which a resliced 3 mm sequence was also obtained. Images were evaluated independently by two readers of different expertise at baseline and after a wash-out period of 30 days. The intraclass correlation coefficient (ICC) was calculated as an index of intra and inter-reader reliability. RESULTS For both readers, the intra-reader ICC analysis showed that the 3 mm SE-T1w and 3 mm resliced GrE-T1w images achieved an excellent performance (both with an ICC ≥ 0.95), while 1 mm 3D-GrE-T1w scans achieved a moderate one (ICC < 0.90). The inter-reader analysis showed that each of the three sequences achieved a moderate performance (all ICCs < 0.90). CONCLUSIONS The 1 mm 3D-GrE-T1w sequence seems to be prone to a greater intra-reader variability compared to the 3 mm SE-T1w, with this effect being driven by the higher spatial resolution of the first sequence. To ensure reliability levels comparable with the standard SE-T1w in BH count, an assessment on a 3 mm resliced GrE-T1w sequence should be recommended.
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Affiliation(s)
- Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Chiara Pastore
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Alfredo Montella
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Margareth Kimura
- Research Department of Universidade de Uberaba (UNIUBE), Uberaba, Brazil
- Departament of Radiology and Diagnostic Imaging of Universidade Federal Do Triângulo Mineiro (UFTM), Uberaba, Brazil
| | - Bas Jasperse
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Vincenzo Brescia Morra
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Maria Petracca
- Department of Human Neurosciences, Sapienza University, Rome, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
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Lamsma J, Raine A, Kia SM, Cahn W, Arold D, Banaj N, Barone A, Brosch K, Brouwer R, Brunetti A, Calhoun VD, Chew QH, Choi S, Chung YC, Ciccarelli M, Cobia D, Cocozza S, Dannlowski U, Dazzan P, de Bartolomeis A, Di Forti M, Dumais A, Edmond JT, Ehrlich S, Evermann U, Flinkenflügel K, Georgiadis F, Glahn DC, Goltermann J, Green MJ, Grotegerd D, Guerrero-Pedraza A, Ha M, Hong EL, Hulshoff Pol H, Iasevoli F, Kaiser S, Kaleda V, Karuk A, Kim M, Kircher T, Kirschner M, Kochunov P, Kwon JS, Lebedeva I, Lencer R, Marques TR, Meinert S, Murray R, Nenadić I, Nguyen D, Pearlson G, Piras F, Pomarol-Clotet E, Pontillo G, Potvin S, Preda A, Quidé Y, Rodrigue A, Rootes-Murdy K, Salvador R, Skoch A, Sim K, Spalletta G, Spaniel F, Stein F, Thomas-Odenthal F, Tikàsz A, Tomecek D, Tomyshev A, Tranfa M, Tsogt U, Turner JA, van Erp TGM, van Haren NEM, van Os J, Vecchio D, Wang L, Wroblewski A, Nickl-Jockschat T. Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium. medRxiv 2024:2024.02.04.24302268. [PMID: 38370846 PMCID: PMC10871467 DOI: 10.1101/2024.02.04.24302268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. Methods This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. Results Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. Conclusions This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.
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Affiliation(s)
- Jelle Lamsma
- Department of Criminology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Adrian Raine
- Department of Criminology, University of Pennsylvania, Philadelphia, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
| | - Seyed M. Kia
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dominic Arold
- Division of Psychological and Social Medicine and Developmental Neurosciences, TU Dresden, Germany
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Annarita Barone
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, USA
| | - Rachel Brouwer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
| | - Qian H. Chew
- Department of Research, Institute of Mental Health, Singapore
| | - Sunah Choi
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Jeonju, South Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, South Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea
| | - Mariateresa Ciccarelli
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Derin Cobia
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, USA
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Paola Dazzan
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Andrea de Bartolomeis
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Marta Di Forti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Alexandre Dumais
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Institut Philippe-Pinel, Montreal, Canada
| | - Jesse T. Edmond
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
- Department of Psychology, Georgia State University, Atlanta, USA
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, TU Dresden, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, TU Dresden, Germany
| | - Ulrika Evermann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Switzerland
| | - David C. Glahn
- Department of Psychiatry, Harvard Medical School, Harvard, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, USA
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Melissa J. Green
- Neuroscience Research Australia, Randwick, Australia
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Elliot L. Hong
- Department of Psychiatry and Behavioral Science, UTHealth Houston, Houston, USA
| | - Hilleke Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Psychology, Utrecht University, Utrecht, the Netherlands
| | - Felice Iasevoli
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Stefan Kaiser
- Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Vasily Kaleda
- Department of Youth Psychiatry, Mental Health Research Center, Moscow, Russia
| | - Andriana Karuk
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Switzerland
- Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Peter Kochunov
- Department of Psychiatry and Behavioral Science, UTHealth Houston, Houston, USA
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russia
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - Tiago R. Marques
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
- Institute of Clinical Sciences, Imperial College London, London, UK
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Dana Nguyen
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Barcelona, Spain
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Stéphane Potvin
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Centre de Recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
| | - Yann Quidé
- Neuroscience Research Australia, Randwick, Australia
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Amanda Rodrigue
- Department of Psychiatry, Harvard Medical School, Harvard, USA
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
- Department of Psychology, Georgia State University, Atlanta, USA
| | - Raymond Salvador
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Barcelona, Spain
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
| | - Kang Sim
- Department of Research, Institute of Mental Health, Singapore
| | | | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | | | - Andràs Tikàsz
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Centre de Recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russia
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Uyanga Tsogt
- Department of Psychiatry, Jeonbuk National University, Jeonju, South Korea
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, USA
| | - Theo G. M. van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, USA
| | - Neeltje E. M. van Haren
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC Sophia, Rotterdam, the Netherlands
| | - Jim van Os
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Lei Wang
- Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, USA
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, University of Iowa, Iowa City, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, USA
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Di Stasi M, Cocozza S, Buccino S, Paolella C, Di Napoli L, D'Amico A, Melis D, Ugga L, Villano G, Ruocco M, Scala I, Brunetti A, Elefante A. The role of unidentified bright objects in the neurocognitive profile of neurofibromatosis type 1 children: a volumetric MRI analysis. Acta Neurol Belg 2024; 124:223-230. [PMID: 37733157 PMCID: PMC10874314 DOI: 10.1007/s13760-023-02381-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 09/07/2023] [Indexed: 09/22/2023]
Abstract
PURPOSE Cognitive impairment is described in 80% of Neurofibromatosis type 1 (NF1) patients. Brain focal areas of T2w increased signal intensity on MRI, the so-called Unidentified Bright Objects (UBOs) have been hypothesized to be related to cognitive dysfunction, although conflicting results are available in literature. Here, we investigated the possible relation between UBOs' volume, cognitive impairment, and language disability in NF1 patients. MATERIAL AND METHODS In this retrospective study, clinical and MRI data of 21 NF1 patients (M/F = 12/9; mean age 10.1 ± 4.5) were evaluated. Brain intellectual functioning and language abilities were assessed with specific scales, while the analyzed MRI sequences included axial 2D-T2-weighted and FLAIR sequences. These images were used independently for UBOs segmentation with a semiautomatic approach and obtained volumes were normalized for biparietal diameters to take into account for brain volume. Possible differences in terms of normalized UBOs volumes were probed between cognitively affected and preserved patients, as well as between subjects with or without language impairment. RESULTS Patients cognitively affected were not different in terms of UBOs volume compared to those preserved (p = 0.35 and p = 0.30, for T2-weighted and FLAIR images, respectively). Similarly, no differences were found between patients with and without language impairment (p = 0.47 and p = 0.40, for the two sequences). CONCLUSIONS The relation between UBOs and cognition in children with NF1 has been already investigated in literature, although leading to conflicting results. Our study expands the current knowledge, showing a lack of correlation between UBOs volume and both cognitive impairment and language disability in NF1 patients.
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Affiliation(s)
- Martina Di Stasi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
- Department of Diagnostic and Interventional Neuroradiology, University Hospital "San Giovanni di Dio e Ruggi di Aragona", Salerno, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
| | - Sara Buccino
- Department of Maternal and Child Health, Federico II University Hospital, Naples, Italy
| | - Chiara Paolella
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Linda Di Napoli
- Department of Maternal and Child Health, Federico II University Hospital, Naples, Italy
| | | | - Daniela Melis
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Gianmichele Villano
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Manuel Ruocco
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Iris Scala
- Department of Maternal and Child Health, Federico II University Hospital, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
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Cagol A, Cortese R, Barakovic M, Schaedelin S, Ruberte E, Absinta M, Barkhof F, Calabrese M, Castellaro M, Ciccarelli O, Cocozza S, De Stefano N, Enzinger C, Filippi M, Jurynczyk M, Maggi P, Mahmoudi N, Messina S, Montalban X, Palace J, Pontillo G, Pröbstel AK, Rocca MA, Ropele S, Rovira À, Schoonheim MM, Sowa P, Strijbis E, Wattjes MP, Sormani MP, Kappos L, Granziera C. Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis. JAMA Neurol 2024; 81:143-153. [PMID: 38079177 PMCID: PMC10714285 DOI: 10.1001/jamaneurol.2023.4737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/06/2023] [Indexed: 02/13/2024]
Abstract
Importance Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures MS/CIS vs non-MS conditions. Main Outcomes and Measures Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Health Sciences, University of Genova, Genova, Italy
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center, Basel, Switzerland
| | - Martina Absinta
- Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- National Institute for Health and Care Research (NIHR) University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Sirio Cocozza
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maciej Jurynczyk
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Pietro Maggi
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
- Neuroinflammation Imaging Lab, Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Nima Mahmoudi
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Silvia Messina
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
- Division of Neurology, St Michael’s Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Jacqueline Palace
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Giuseppe Pontillo
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Anne-Katrin Pröbstel
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Departments of Biomedicine and Clinical Research, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - Maria A. Rocca
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Menno M. Schoonheim
- Multiple Sclerosis Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Eva Strijbis
- Multiple Sclerosis Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Mike P. Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Maria Pia Sormani
- Department of Health Sciences, University of Genova, Genova, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Policlinico San Martino, Genova, Italy
| | - Ludwig Kappos
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
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15
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Alkhalifa A, Chen S, Hasiloglu ZI, Filosto M, Cali E, Houlden H, Sgobbi de Souza P, Alavi A, Goizet C, Stevanin G, Taithe F, Nicita F, Vasco G, Tozza S, Cocozza S, Carboni N, Figus A, Wu J, Basak AN, Brais B, Rouleau G, La Piana R. White matter abnormalities in 15 subjects with SPG76. J Neurol 2023; 270:5784-5792. [PMID: 37578488 DOI: 10.1007/s00415-023-11918-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 07/27/2023] [Accepted: 07/30/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND AND OBJECTIVES Hereditary spastic paraplegias (HSPs) are heterogenous genetic disorders characterized by progressive pyramidal tract involvement. SPG76 is a recently identified form of HSP, caused by biallelic calpain-1 (CAPN1) variants. The most frequently described MRI abnormality in SPG76 is mild cerebellar atrophy and non-specific white matter abnormalities were reported in only one case. Following the identification of prominent white matter abnormalities in a subject with CAPN1 variants, which delayed the diagnosis, we aimed to verify the presence of MRI patterns of white matter involvement specific to this HSP. METHODS We performed a retrospective radiological qualitative analysis of 15 subjects with SPG76 (4 previously unreported) initially screened for white matter involvement. Moreover, we performed quantitative analyses in our proband with available longitudinal studies. RESULTS We observed bilateral, periventricular white matter involvement in 12 subjects (80%), associated with multifocal subcortical abnormalities in 5 of them (33.3%). Three subjects (20%) presented only multifocal subcortical involvement. Longitudinal quantitative analyses of our proband revealed increase in multifocal white matter lesion count and increased area of periventricular white matter involvement over time. DISCUSSION SPG76 should be added to the list of HSPs with associated white matter abnormalities. We identified periventricular white matter involvement in subjects with SPG76, variably associated with multifocal subcortical white matter abnormalities. These findings, in the presence of progressive spastic paraparesis, can mislead the diagnostic process towards an acquired white matter disorder.
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Affiliation(s)
- Abdulrahman Alkhalifa
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada
- Bahrain Defence Force Royal Medical Services, Military Hospital, Riffa, Bahrain
| | - Shihan Chen
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada
| | - Zehra Isik Hasiloglu
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada
| | - Massimiliano Filosto
- Department of Clinical and Experimental Sciences, University of Brescia, NeMO-Brescia Clinical Center for Neuromuscular Diseases, Brescia, Italy
| | - Elisa Cali
- Department of Neuromuscular Disease, University College London; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Henry Houlden
- Department of Neuromuscular Disease, University College London; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Paulo Sgobbi de Souza
- Department of Neurology and Neurosurgery, Division of Neuromuscular Diseases, Universidade Federal de São Paulo, Sao Paulo, Brazil
| | - Afagh Alavi
- University of Social Welfare and Rehabilitation Sciences, Genetics Research Center, Tehran, Iran
| | - Cyril Goizet
- NRGEN Team, Univ. Bordeaux, CNRS, INCIA, UMR 5287, EPHE, 33000, Bordeaux, France
- Centre de Référence Maladies Rares Neurogénétique, Service de Génétique Médicale, Bordeaux University Hospital (CHU Bordeaux), Bordeaux, France
| | - Giovanni Stevanin
- Centre de Référence Maladies Rares Neurogénétique, Service de Génétique Médicale, Bordeaux University Hospital (CHU Bordeaux), Bordeaux, France
| | - Frederic Taithe
- Service de Neurologie, Hôpital Gabriel Montpied, CHU de Clermont-Ferrand, Clermont-Ferrand, France
| | - Francesco Nicita
- Genetics and Rare Diseases Research Division, Unit of Neuromuscular and Neurodegenerative Diseases, Bambino Gesù Hospital, IRCCS, Rome, Italy
| | - Gessica Vasco
- Department of Neurosciences, Unit of Neurorehabilitation, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Stefano Tozza
- Department of Neuroscience and Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Nicola Carboni
- Department of Neurology, San Francesco Hospital, Nuoro, Italy
| | - Andrea Figus
- Department of Radiology, San Francesco Hospital, Nuoro, Italy
| | - Jianjun Wu
- National Center for Neurological Disorders and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - A Nazli Basak
- Translational Medicine Research Center-NDAL, School of Medicine, Koc University, Istanbul, Turkey
| | - Bernard Brais
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Canada
| | - Guy Rouleau
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Canada
| | - Roberta La Piana
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, H3A 2B4, Canada.
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Canada.
- Department of Diagnostic Radiology, McGill University, Montreal, QC, Canada.
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16
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Omlor W, Rabe F, Fuchs S, Cecere G, Homan S, Surbeck W, Kallen N, Georgiadis F, Spiller T, Seifritz E, Weickert T, Bruggemann J, Weickert C, Potkin S, Hashimoto R, Sim K, Rootes-Murdy K, Quide Y, Houenou J, Banaj N, Vecchio D, Piras F, Piras F, Spalletta G, Salvador R, Karuk A, Pomarol-Clotet E, Rodrigue A, Pearlson G, Glahn D, Tomecek D, Spaniel F, Skoch A, Kirschner M, Kaiser S, Kochunov P, Fan FM, Andreassen OA, Westlye LT, Berthet P, Calhoun VD, Howells F, Uhlmann A, Scheffler F, Stein D, Iasevoli F, Cairns MJ, Carr VJ, Catts SV, Di Biase MA, Jablensky A, Green MJ, Henskens FA, Klauser P, Loughland C, Michie PT, Mowry B, Pantelis C, Rasser PE, Schall U, Scott R, Zalesky A, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Di Giorgio A, Thomopoulos SI, Jahanshad N, Thompson PM, van Erp T, Turner J, Homan P. Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study. bioRxiv 2023:2023.09.22.559032. [PMID: 37961617 PMCID: PMC10634976 DOI: 10.1101/2023.09.22.559032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Objective Schizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. Methods This meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. Results We found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. Conclusions Higher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.
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17
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Pontillo G, Cocozza S. The rising role of magnetic resonance imaging biomarkers in diagnosing multiple sclerosis. Eur Radiol 2023; 33:8043-8045. [PMID: 37191920 DOI: 10.1007/s00330-023-09738-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/03/2023] [Accepted: 05/08/2023] [Indexed: 05/17/2023]
Affiliation(s)
- Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
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18
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Demir AU, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Rheenen TEV, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos S, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TG, Cheng W, Feng J. Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia. medRxiv 2023:2023.10.11.23296862. [PMID: 37873296 PMCID: PMC10593004 DOI: 10.1101/2023.10.11.23296862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, 305-8575, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L. Rodrigue
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R. Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Min Tae M. Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Centre for Addiction and Mental Health, Toronto, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Sophia Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi’an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, 92697-3950, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | | | | | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- School of Data Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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19
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Torella A, Ricca I, Piluso G, Galatolo D, De Michele G, Zanobio M, Trovato R, De Michele G, Zeuli R, Pane C, Cocozza S, Saccà F, Santorelli FM, Nigro V, Filla A. A new genetic cause of spastic ataxia: the p.Glu415Lys variant in TUBA4A. J Neurol 2023; 270:5057-5063. [PMID: 37418012 PMCID: PMC10511369 DOI: 10.1007/s00415-023-11816-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/06/2023] [Accepted: 06/07/2023] [Indexed: 07/08/2023]
Abstract
Tubulinopathies encompass neurodevelopmental disorders caused by mutations in genes encoding for different isotypes of α- and β-tubulins, the structural components of microtubules. Less frequently, mutations in tubulins may underlie neurodegenerative disorders. In the present study, we report two families, one with 11 affected individuals and the other with a single patient, carrying a novel, likely pathogenic, variant (p. Glu415Lys) in the TUBA4A gene (NM_006000). The phenotype, not previously described, is that of spastic ataxia. Our findings widen the phenotypic and genetic manifestations of TUBA4A variants and add a new type of spastic ataxia to be taken into consideration in the differential diagnosis.
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Affiliation(s)
- Annalaura Torella
- Department of Precision Medicine, University of Campania, Luigi Vanvitelli, Caserta, Italy
- Telethon Institute of Genetics and Medicine, Pozzuoli, Italy
| | - Ivana Ricca
- Molecular Medicine, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Giulio Piluso
- Department of Precision Medicine, University of Campania, Luigi Vanvitelli, Caserta, Italy
| | | | - Giuseppe De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | - Mariateresa Zanobio
- Department of Precision Medicine, University of Campania, Luigi Vanvitelli, Caserta, Italy
| | - Rosanna Trovato
- Molecular Medicine, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Giovanna De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | - Roberta Zeuli
- Department of Precision Medicine, University of Campania, Luigi Vanvitelli, Caserta, Italy
| | - Chiara Pane
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | - Sirio Cocozza
- Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy
| | - Francesco Saccà
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | | | - Vincenzo Nigro
- Department of Precision Medicine, University of Campania, Luigi Vanvitelli, Caserta, Italy
- Telethon Institute of Genetics and Medicine, Pozzuoli, Italy
| | - Alessandro Filla
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy.
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20
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Tranfa M, Iuzzolino VV, Perrella P, Carotenuto A, Pontillo G, Moccia M, Cocozza S, Elefante A, Lanzillo R, Brunetti A, Brescia Morra V, Petracca M. Exploring the relation between reserve and fatigue in multiple sclerosis. Mult Scler Relat Disord 2023; 76:104842. [PMID: 37392716 DOI: 10.1016/j.msard.2023.104842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/07/2023] [Accepted: 06/19/2023] [Indexed: 07/03/2023]
Abstract
INTRODUCTION Intellectual enrichment and brain reserve modulate the expression of cognitive and motor disability in multiple sclerosis (MS). Their association with fatigue, one of the most debilitating and common symptoms of MS, has never been explored. MATERIALS AND METHODS Forty-eight MS patients underwent clinical and MRI examination at baseline and after 1 year. Physical and cognitive MS-related fatigue were evaluated via Modified Fatigue Impact subscales (MFIS-P and MFIS-C). Differences in reserve indexes between fatigued and non-fatigued patients were tested. The relationship between clinico-demographic features, global brain structural damage, indexes of reserve (age-adjusted intracranial volume and cognitive reserve index) and fatigue were tested via correlations and hierarchical linear/binary logistic regression, to predict MFIS-P and MFIS-C (at baseline) or new-onset fatigue and meaningful worsening in MFIS (at follow-up). RESULTS At baseline, although a significant difference was identified for cognitive reserve questionnaire between fatigued and non-fatigued patients (18.19 ± 4.76 versus 15.15 ± 3.56, p = 0.015), only depression accounted for significant variance in MFIS-P and MFIS-C (R2=0.248, p = 0.002; R2=0.252, p<0.001). MFIS-T, MFIS-P and MFIS-C changes over time were associated to depression changes over time (r = 0.56, r = 0.55, and r = 0.57, respectively; all p<0.001). Indexes of reserve did not differ between non-fatigued patients and patients developing new-onset fatigue at follow-up. None of the baseline features was able to predict the new-onset fatigue or meaningful worsening in MFIS at follow-up. CONCLUSIONS Among the explored features, only depression was strongly associated to both physical and cognitive fatigue. Intellectual enrichment and brain reserve did not seem to affect fatigue symptoms in MS patients.
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Affiliation(s)
- Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Valentina Virginia Iuzzolino
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Pierpaolo Perrella
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Antonio Carotenuto
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples "Federico II", Naples, Italy; Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Radiology and Nuclear Medicine, VU Medical Centre, Amsterdam, the Netherlands
| | - Marcello Moccia
- Department of Molecular Medicine and Medical Biotechnology, University of Naples "Federico II", Naples, Italy; Multiple Sclerosis Unit, AOU "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Maria Petracca
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy
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21
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van Rootselaar AF, Cocozza S, Aronica E, Striano P. Familial Adult Myoclonus Epilepsy: neuroimaging and neuropathological findings. Epilepsia 2023. [PMID: 37096373 DOI: 10.1111/epi.17628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 04/26/2023]
Abstract
Familial adult myoclonus epilepsy (FAME) is characterized by cortical myoclonus and often epileptic seizures, but the pathophysiology of this condition remains uncertain. Here, we review the neuroimaging and neuropathological findings in FAME. Imaging findings, including functional MRI, are in line with a cortical origin of involuntary tremulous movements (cortical myoclonic tremor) and indicate a complex pattern of cerebellar functional connectivity. Scarce neuropathological reports, mainly from single families, provide evidence of morphological changes in the Purkinje cells. Cerebellar changes seem to be part of the syndrome, in at least some FAME pedigrees. Cortical hyperexcitability in FAME, resulting in the cardinal clinical symptoms might be the result of decreased cortical inhibition via the cerebellothalamocortical loop. The pathological findings might share some similarities with other pentanucleotide repeat disorders. The relation with genetic findings in FAME needs to be elucidated.
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Affiliation(s)
- Anne-Fleur van Rootselaar
- Amsterdam UMC location University of Amsterdam, Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Italy
| | - Eleonora Aronica
- Amsterdam UMC location University of Amsterdam, Department of Neuropathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Stichting Epilepsie Instellingen Nederland, Heemstede, The Netherlands
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini member of ERN-Epicare, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
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22
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Scaravilli A, Tranfa M, Pontillo G, Falco F, Criscuolo C, Moccia M, Monti S, Lanzillo R, Brescia Morra V, Palma G, Petracca M, Tedeschi E, Elefante A, Brunetti A, Cocozza S. MR Imaging Signs of Gadolinium Retention Are Not Associated with Long-Term Motor and Cognitive Outcomes in Multiple Sclerosis. AJNR Am J Neuroradiol 2023; 44:396-402. [PMID: 36863844 PMCID: PMC10084901 DOI: 10.3174/ajnr.a7807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 02/04/2023] [Indexed: 03/04/2023]
Abstract
BACKGROUND AND PURPOSE The long-term impact of gadolinium retention in the dentate nuclei of patients undergoing administration of seriate gadolinium-based contrast agents is still widely unexplored. The aim of this study was to evaluate the impact of gadolinium retention on motor and cognitive disability in patients with MS during long-term follow-up. MATERIALS AND METHODS In this retrospective study, clinical data were obtained from patients with MS followed in a single center from 2013 to 2022 at different time points. These included the Expanded Disability Status Scale score to evaluate motor impairment and the Brief International Cognitive Assessment for MS battery to investigate cognitive performances and their respective changes with time. The association with qualitative and quantitative MR imaging signs of gadolinium retention (namely, the presence of dentate nuclei T1-weighted hyperintensity and changes in longitudinal relaxation R1 maps, respectively) was probed using different General Linear Models and regression analyses. RESULTS No significant differences in motor or cognitive symptoms emerged between patients showing dentate nuclei hyperintensity and those without visible changes on T1WIs (P = .14 and 0.92, respectively). When we tested possible relationships between quantitative dentate nuclei R1 values and both motor and cognitive symptoms, separately, the regression models including demographic, clinical, and MR imaging features explained 40.5% and 16.5% of the variance, respectively, without any significant effect of dentate nuclei R1 values (P = .21 and 0.30, respectively). CONCLUSIONS Our findings suggest that gadolinium retention in the brains of patients with MS is not associated with long-term motor or cognitive outcomes.
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Affiliation(s)
- A Scaravilli
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
| | - M Tranfa
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
| | - G Pontillo
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
- Electrical Engineering and Information Technology (G.P.)
| | - F Falco
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
| | - C Criscuolo
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
| | - M Moccia
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
| | - S Monti
- Institute of Biostructure and Bioimaging (S.M.), National Research Council, Naples, Italy
| | - R Lanzillo
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
| | - V Brescia Morra
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
| | - G Palma
- Institute of Nanotechnology (G.P.), National Research Council, Lecce, Italy
| | - M Petracca
- Neurosciences and Reproductive and Odontostomatological Sciences (F.F., C.C., M.M., R.L., V.B.M., M.P.), University of Naples "Federico II," Naples, Italy
- Department of Human Neurosciences (M.P.), Sapienza University of Rome, Rome, Italy
| | - E Tedeschi
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
| | - A Elefante
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
| | - A Brunetti
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
| | - S Cocozza
- From the Departments of Advanced Biomedical Sciences (A.S., M.T., G.P., E.T., A.E., A.B., S.C.)
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Ugga L, Franca RA, Scaravilli A, Solari D, Cocozza S, Tortora F, Cavallo LM, De Caro MDB, Elefante A. Neoplasms and tumor-like lesions of the sellar region: imaging findings with correlation to pathology and 2021 WHO classification. Neuroradiology 2023; 65:675-699. [PMID: 36799985 PMCID: PMC10033642 DOI: 10.1007/s00234-023-03120-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/15/2023] [Indexed: 02/18/2023]
Abstract
The sellar region represents a complex anatomical area, composed of multiple structures of different embryological derivation, including the skull base and the pituitary gland, along with vascular, nervous, and meningeal structures. Masses arising in this region include benign and malignant lesions arising from the pituitary gland itself, but also from vestigial embryological residues or surrounding tissues, that may require different therapeutic approaches. While assessing sellar region masses, the combination of clinical presentation and imaging features is fundamental to define hypotheses about their nature. MR represents the imaging modality of choice, providing information about the site of the lesion, its imaging features, and relation with adjacent structures, while CT is useful to confirm the presence of lesion calcifications or to reveal tumor invasion of bony structures. The aim of this pictorial review is to provide an overview of the common neoplasms and tumor-like conditions of the sellar region, according to the 2021 WHO Classification of Tumors of the Central Nervous System (fifth edition), with an emphasis on the radiologic-pathologic correlation. After a brief introduction on the anatomy of this region and the imaging and pathological techniques currently used, the most relevant MRI characteristics, clinical findings, and pathological data, including histologic and molecular features, will be shown and discussed, with the aim of facilitating an appropriate differential diagnosis among these entities.
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Affiliation(s)
- Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Raduan Ahmed Franca
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
| | - Domenico Solari
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Fabio Tortora
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Luigi Maria Cavallo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Andrea Elefante
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
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Iasevoli F, D’Ambrosio L, Ciccarelli M, Barone A, Gaudieri V, Cocozza S, Pontillo G, Brunetti A, Cuocolo A, de Bartolomeis A, Pappatà S. Altered Patterns of Brain Glucose Metabolism Involve More Extensive and Discrete Cortical Areas in Treatment-resistant Schizophrenia Patients Compared to Responder Patients and Controls: Results From a Head-to-Head 2-[18F]-FDG-PET Study. Schizophr Bull 2023; 49:474-485. [PMID: 36268829 PMCID: PMC10016407 DOI: 10.1093/schbul/sbac147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND HYPOTHESIS Treatment resistant schizophrenia (TRS) affects almost 30% of patients with schizophrenia and has been considered a different phenotype of the disease. In vivo characterization of brain metabolic patterns associated with treatment response could contribute to elucidate the neurobiological underpinnings of TRS. Here, we used 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) to provide the first head-to-head comparative analysis of cerebral glucose metabolism in TRS patients compared to schizophrenia responder patients (nTRS), and controls. Additionally, we investigated, for the first time, the differences between clozapine responders (Clz-R) and non-responders (Clz-nR). STUDY DESIGN 53 participants underwent FDG-PET studies (41 patients and 12 controls). Response to conventional antipsychotics and to clozapine was evaluated using a standardized prospective procedure based on PANSS score changes. Maps of relative brain glucose metabolism were processed for voxel-based analysis using Statistical Parametric Mapping software. STUDY RESULTS Restricted areas of significant bilateral relative hypometabolism in the superior frontal gyrus characterized TRS compared to nTRS. Moreover, reduced parietal and frontal metabolism was associated with high PANSS disorganization factor scores in TRS (P < .001 voxel level uncorrected, P < .05 cluster level FWE-corrected). Only TRS compared to controls showed significant bilateral prefrontal relative hypometabolism, more extensive in CLZ-nR than in CLZ-R (P < .05 voxel level FWE-corrected). Relative significant hypermetabolism was observed in the temporo-occipital regions in TRS compared to nTRS and controls. CONCLUSIONS These data indicate that, in TRS patients, altered metabolism involved discrete brain regions not found affected in nTRS, possibly indicating a more severe disrupted functional brain network associated with disorganization symptoms.
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Affiliation(s)
- Felice Iasevoli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Luigi D’Ambrosio
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Valeria Gaudieri
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
- UNESCO Chair on Health Education and Sustainable Development - University of Naples Federico II, Naples, Italy
| | - Sabina Pappatà
- Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145, Naples, Italy
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Tranfa M, Iasevoli F, Cocozza S, Ciccarelli M, Barone A, Brunetti A, de Bartolomeis A, Pontillo G. Neural substrates of verbal memory impairment in schizophrenia: A multimodal connectomics study. Hum Brain Mapp 2023; 44:2829-2840. [PMID: 36852587 PMCID: PMC10089087 DOI: 10.1002/hbm.26248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/20/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023] Open
Abstract
While verbal memory is among the most compromised cognitive domains in schizophrenia (SZ), its neural substrates remain elusive. Here, we explored the structural and functional brain network correlates of verbal memory impairment in SZ. We acquired diffusion and resting-state functional MRI data of 49 SZ patients, classified as having preserved (VMP, n = 22) or impaired (VMI, n = 26) verbal memory based on the List Learning task, and 55 healthy controls (HC). Structural and functional connectivity matrices were obtained and analyzed to assess associations with disease status (SZ vs. HC) and verbal memory impairment (VMI vs. VMP) using two complementary data-driven approaches: threshold-free network-based statistics (TFNBS) and hybrid connectivity independent component analysis (connICA). TFNBS showed altered connectivity in SZ patients compared with HC (p < .05, FWER-corrected), with distributed structural changes and functional reorganization centered around sensorimotor areas. Specifically, functional connectivity was reduced within the visual and somatomotor networks and increased between visual areas and associative and subcortical regions. Only a tiny cluster of increased functional connectivity between visual and bilateral parietal attention-related areas correlated with verbal memory dysfunction. Hybrid connICA identified four robust traits, representing fundamental patterns of joint structural-functional connectivity. One of these, mainly capturing the functional connectivity profile of the visual network, was significantly associated with SZ (HC vs. SZ: Cohen's d = .828, p < .0001) and verbal memory impairment (VMP vs. VMI: Cohen's d = -.805, p = .01). We suggest that aberrant connectivity of sensorimotor networks may be a key connectomic signature of SZ and a putative biomarker of SZ-related verbal memory impairment, in consistency with bottom-up models of cognitive disruption.
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Affiliation(s)
- Mario Tranfa
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Felice Iasevoli
- Section of Psychiatry - Unit of Treatment Resistant Psychosis - Laboratory of Molecular and Translational Psychiatry - Department of Neuroscience, Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Unit of Treatment Resistant Psychosis - Laboratory of Molecular and Translational Psychiatry - Department of Neuroscience, Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Unit of Treatment Resistant Psychosis - Laboratory of Molecular and Translational Psychiatry - Department of Neuroscience, Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Unit of Treatment Resistant Psychosis - Laboratory of Molecular and Translational Psychiatry - Department of Neuroscience, Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy.,Staff of UNESCO Chair on Health Education and Sustainable Development, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.,Department of Electrical Engineering and Information Technology (DIETI), University "Federico II", Naples, Italy
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Pontillo G, Petracca M, Monti S, Quarantelli M, Lanzillo R, Costabile T, Carotenuto A, Tortora F, Elefante A, Morra VB, Brunetti A, Palma G, Cocozza S. Correction to: Clinical correlates of R1 relaxometry and magnetic susceptibility changes in multiple sclerosis: a multi-parameter quantitative MRI study of brain iron and myelin. Eur Radiol 2023; 33:2277. [PMID: 36482219 PMCID: PMC9935686 DOI: 10.1007/s00330-022-09279-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini 5, 80131, Naples, Italy. .,Department of Electrical Engineering and Information Technology, University "Federico II", Naples, Italy.
| | - Maria Petracca
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Serena Monti
- grid.429699.90000 0004 1790 0507Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Mario Quarantelli
- grid.429699.90000 0004 1790 0507Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Roberta Lanzillo
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Teresa Costabile
- Multiple Sclerosis Centre, II Division of Neurology, Department of Clinical and Experimental Medicine, “Luigi Vanvitelli” University, Naples, Italy
| | - Antonio Carotenuto
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Fabio Tortora
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Andrea Elefante
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Vincenzo Brescia Morra
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Giuseppe Palma
- grid.5326.20000 0001 1940 4177Institute of Nanotechnology, National Research Council, Lecce, Italy
| | - Sirio Cocozza
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
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Romeo V, Stanzione A, Ugga L, Cuocolo R, Cocozza S, Quarantelli M, Chawla S, Farina D, Golay X, Parker G, Shukla-Dave A, Thoeny H, Vidiri A, Brunetti A, Surlan-Popovic K, Bisdas S. Clinical indications and acquisition protocol for the use of dynamic contrast-enhanced MRI in head and neck cancer squamous cell carcinoma: recommendations from an expert panel. Insights Imaging 2022; 13:198. [PMID: 36528678 PMCID: PMC9759606 DOI: 10.1186/s13244-022-01317-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/19/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The clinical role of perfusion-weighted MRI (PWI) in head and neck squamous cell carcinoma (HNSCC) remains to be defined. The aim of this study was to provide evidence-based recommendations for the use of PWI sequence in HNSCC with regard to clinical indications and acquisition parameters. METHODS Public databases were searched, and selected papers evaluated applying the Oxford criteria 2011. A questionnaire was prepared including statements on clinical indications of PWI as well as its acquisition technique and submitted to selected panelists who worked in anonymity using a modified Delphi approach. Each panelist was asked to rate each statement using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Statements with scores equal or inferior to 5 assigned by at least two panelists were revised and re-submitted for the subsequent Delphi round to reach a final consensus. RESULTS Two Delphi rounds were conducted. The final questionnaire consisted of 6 statements on clinical indications of PWI and 9 statements on the acquisition technique of PWI. Four of 19 (21%) statements obtained scores equal or inferior to 5 by two panelists, all dealing with clinical indications. The Delphi process was considered concluded as reasons entered by panelists for lower scores were mainly related to the lack of robust evidence, so that no further modifications were suggested. CONCLUSIONS Evidence-based recommendations on the use of PWI have been provided by an independent panel of experts worldwide, encouraging a standardized use of PWI across university and research centers to produce more robust evidence.
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Affiliation(s)
- Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Renato Cuocolo
- Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Italy.,Interdepartmental Research Center on Management and Innovation in Healthcare - CIRMIS, University of Naples Federico II, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, PA, USA
| | - Davide Farina
- Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK
| | - Geoff Parker
- Department of Computer Science, Centre for Medical Image Computing, Queen Square Institute of Neurology, University College London, London, UK
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Departments of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Harriet Thoeny
- Department of Radiology, Cantonal Hospital Fribourg, University of Fribourg, Fribourg, Switzerland
| | - Antonello Vidiri
- Department of Radiology and Diagnostic Imaging, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Sotirios Bisdas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK. .,Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK.
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28
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Tranfa M, Pontillo G, Petracca M, Brunetti A, Tedeschi E, Palma G, Cocozza S. Quantitative MRI in Multiple Sclerosis: From Theory to Application. AJNR Am J Neuroradiol 2022; 43:1688-1695. [PMID: 35680161 DOI: 10.3174/ajnr.a7536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/22/2022] [Indexed: 02/01/2023]
Abstract
Quantitative MR imaging techniques allow evaluating different aspects of brain microstructure, providing meaningful information about the pathophysiology of damage in CNS disorders. In the study of patients with MS, quantitative MR imaging techniques represent an invaluable tool for studying changes in myelin and iron content occurring in the context of inflammatory and neurodegenerative processes. In the first section of this review, we summarize the physics behind quantitative MR imaging, here defined as relaxometry and quantitative susceptibility mapping, and describe the neurobiological correlates of quantitative MR imaging findings. In the second section, we focus on quantitative MR imaging application in MS, reporting the main findings in both the gray and white matter compartments, separately addressing macroscopically damaged and normal-appearing parenchyma.
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Affiliation(s)
- M Tranfa
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - G Pontillo
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.) .,Electrical Engineering and Information Technology (G. Pontillo), University of Naples "Federico II," Naples, Italy
| | - M Petracca
- Department of Human Neurosciences (M.P.), Sapienza University of Rome, Rome, Italy
| | - A Brunetti
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - E Tedeschi
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - G Palma
- Institute of Nanotechnology (G. Palma), National Research Council, Lecce, Italy
| | - S Cocozza
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
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29
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Gabusi I, Pontillo G, Petracca M, Battocchio M, Bosticardo S, Costabile T, Daducci A, Pane C, Riccio E, Pisani A, Brunetti A, Schiavi S, Cocozza S. Structural disconnection and functional reorganization in Fabry disease: a multimodal MRI study. Brain Commun 2022; 4:fcac187. [PMID: 35912136 PMCID: PMC9327118 DOI: 10.1093/braincomms/fcac187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 05/17/2022] [Accepted: 07/20/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Central nervous system involvement in Fabry disease, a rare systemic X-linked lysosomal storage disorder, is characterized by the presence of heterogeneous but consistent functional and microstructural changes. Nevertheless, knowledge about the degree and extension of macro-scale brain connectivity modifications is to date missing. In this work, we performed connectomic analyses of diffusion and resting-state functional MRI to investigate changes of both structural and functional brain organization in Fabry disease, as well as to explore the relationship between the two and their clinical correlates. In this retrospective cross-sectional study, 46 patients with Fabry disease (28F, 42.2 ± 13.2years) and 49 healthy controls (21F, 42.3 ± 16.3years) were included. All subjects underwent an MRI examination including anatomical, diffusion and resting-state functional sequences. Images were processed to obtain quantitative structural and functional connectomes, where the connections between regions of interest were weighted by the total intra-axonal signal contribution of the corresponding bundle and by the correlation between blood-oxygen level–dependent time series, respectively. We explored between-group differences in terms of both global network properties, expressed with graph measures and specific connected subnetworks, identified using a network-based statistics approach. As exploratory analyses, we also investigated the possible association between cognitive performance and structural and functional connectome modifications at both global and subnetwork level in a subgroup of patients (n = 11). Compared with healthy controls, patients with Fabry disease showed a significantly reduced global efficiency (P = 0.005) and mean strength (P < 0.001) in structural connectomes, together with an increased modularity (P = 0.005) in functional networks. As for the network-based statistics analysis, a subnetwork with decreased structural connectivity in patients with Fabry disease compared with healthy controls emerged, with eight nodes mainly located at the level of frontal or deep grey-matter areas. When probing the relation between altered global network metrics and neuropsychological tests, correlations emerged between the structural and functional disruption with results at verbal and working memory tests, respectively. Furthermore, structural disruption at subnetwork level was associated with worse executive functioning, with a significant moderation effect of functional changes suggesting a compensation mechanism. Taken together, these results further expand the current knowledge about brain involvement in Fabry disease, showing widespread structural disconnection and functional reorganization, primarily sustained by loss in axonal integrity and correlating with cognitive performance.
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Affiliation(s)
- Ilaria Gabusi
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona , Verona 37134 , Italy
- Department of Advanced Biomedical Sciences, University “Federico II” , Naples 80131 , Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University “Federico II” , Naples 80131 , Italy
- Department of Electrical Engineering and Information Technology (DIETI), University “Federico II” , Naples 80125 , Italy
| | - Maria Petracca
- Department of Human Neuroscience, Sapienza University of Rome , Rome 00189 , Italy
| | - Matteo Battocchio
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona , Verona 37134 , Italy
- Department of Computer Science, University of Sherbrooke , Sherbrooke, QC J1K 2R1 , Canada
| | - Sara Bosticardo
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona , Verona 37134 , Italy
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk), University Hospital Basel and University of Basel , Basel 4001 , Switzerland
| | - Teresa Costabile
- Department of Clinical and Experimental Medicine, Multiple Sclerosis Centre, II Division of Neurology, ‘'Luigi Vanvitelli” University , Naples 80138 , Italy
| | - Alessandro Daducci
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona , Verona 37134 , Italy
| | - Chiara Pane
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II” , Naples 80131 , Italy
| | - Eleonora Riccio
- Department of Public Health, Nephrology Unit, University “Federico II” , Naples 80131 , Italy
| | - Antonio Pisani
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II” , Naples 80131 , Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University “Federico II” , Naples 80131 , Italy
| | - Simona Schiavi
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona , Verona 37134 , Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa , Genoa 16132 , Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University “Federico II” , Naples 80131 , Italy
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Pontillo G, Penna S, Cocozza S, Quarantelli M, Gravina M, Lanzillo R, Marrone S, Costabile T, Inglese M, Morra VB, Riccio D, Elefante A, Petracca M, Sansone C, Brunetti A. Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach. Eur Radiol 2022; 32:5382-5391. [PMID: 35284989 PMCID: PMC9279232 DOI: 10.1007/s00330-022-08610-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/30/2021] [Accepted: 01/23/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVES To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived volumetric features using unsupervised machine learning. METHODS The 3-T brain MRIs of relapsing-remitting pwMS including 3D-T1w and FLAIR-T2w sequences were retrospectively collected, along with Expanded Disability Status Scale (EDSS) scores and long-term (10 ± 2 years) clinical outcomes (EDSS, cognition, and progressive course). From the MRIs, volumes of demyelinating lesions and 116 atlas-defined gray matter regions were automatically segmented and expressed as z-scores referenced to external populations. Following feature selection, baseline MRI-derived biomarkers entered the Subtype and Stage Inference (SuStaIn) algorithm, which estimates subgroups characterized by distinct patterns of biomarker evolution and stages within subgroups. The trained model was then applied to longitudinal MRIs. Stability of subtypes and stage change over time were assessed via Krippendorf's α and multilevel linear regression models, respectively. The prognostic relevance of SuStaIn classification was assessed with ordinal/logistic regression analyses. RESULTS We selected 425 pwMS (35.9 ± 9.9 years; F/M: 301/124), corresponding to 1129 MRI scans, along with healthy controls (N = 148; 35.9 ± 13.0 years; F/M: 77/71) and external pwMS (N = 80; 40.4 ± 11.9 years; F/M: 56/24) as reference populations. Based on 11 biomarkers surviving feature selection, two subtypes were identified, designated as "deep gray matter (DGM)-first" subtype (N = 238) and "cortex-first" subtype (N = 187) according to the atrophy pattern. Subtypes were consistent over time (α = 0.806), with significant annual stage increase (b = 0.20; p < 0.001). EDSS was associated with stage and DGM-first subtype (p ≤ 0.02). Baseline stage predicted long-term disability, transition to progressive course, and cognitive impairment (p ≤ 0.03), with the latter also associated with DGM-first subtype (p = 0.005). CONCLUSIONS Unsupervised learning modelling of brain MRI-derived volumetric features provides a biologically reliable and prognostically meaningful stratification of pwMS. KEY POINTS • The unsupervised modelling of brain MRI-derived volumetric features can provide a single-visit stratification of multiple sclerosis patients. • The so-obtained classification tends to be consistent over time and captures disease-related brain damage progression, supporting the biological reliability of the model. • Baseline stratification predicts long-term clinical disability, cognition, and transition to secondary progressive course.
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Affiliation(s)
- Giuseppe Pontillo
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy ,grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Simone Penna
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Mario Quarantelli
- grid.5326.20000 0001 1940 4177Institute of Biostructure and Bioimaging, National Research Council, Naples, Italy
| | - Michela Gravina
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Roberta Lanzillo
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Stefano Marrone
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Teresa Costabile
- Multiple Sclerosis Centre, II Division of Neurology, Department of Clinical and Experimental Medicine, “Luigi Vanvitelli” University, Naples, Italy
| | - Matilde Inglese
- grid.5606.50000 0001 2151 3065Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy ,grid.410345.70000 0004 1756 7871Ospedale Policlinico San Martino IRCCS, Genoa, Italy
| | - Vincenzo Brescia Morra
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Daniele Riccio
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Andrea Elefante
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
| | - Maria Petracca
- grid.4691.a0000 0001 0790 385XDepartment of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, Naples, Italy
| | - Carlo Sansone
- grid.4691.a0000 0001 0790 385XDepartment of Electrical Engineering and Information Technology (DIETI), University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Via Pansini 5, 80131 Naples, Italy
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Schilling KG, Rheault F, Petit L, Hansen CB, Nath V, Yeh FC, Girard G, Barakovic M, Rafael-Patino J, Yu T, Fischi-Gomez E, Pizzolato M, Ocampo-Pineda M, Schiavi S, Canales-Rodríguez EJ, Daducci A, Granziera C, Innocenti G, Thiran JP, Mancini L, Wastling S, Cocozza S, Petracca M, Pontillo G, Mancini M, Vos SB, Vakharia VN, Duncan JS, Melero H, Manzanedo L, Sanz-Morales E, Peña-Melián Á, Calamante F, Attyé A, Cabeen RP, Korobova L, Toga AW, Vijayakumari AA, Parker D, Verma R, Radwan A, Sunaert S, Emsell L, De Luca A, Leemans A, Bajada CJ, Haroon H, Azadbakht H, Chamberland M, Genc S, Tax CMW, Yeh PH, Srikanchana R, Mcknight CD, Yang JYM, Chen J, Kelly CE, Yeh CH, Cochereau J, Maller JJ, Welton T, Almairac F, Seunarine KK, Clark CA, Zhang F, Makris N, Golby A, Rathi Y, O'Donnell LJ, Xia Y, Aydogan DB, Shi Y, Fernandes FG, Raemaekers M, Warrington S, Michielse S, Ramírez-Manzanares A, Concha L, Aranda R, Meraz MR, Lerma-Usabiaga G, Roitman L, Fekonja LS, Calarco N, Joseph M, Nakua H, Voineskos AN, Karan P, Grenier G, Legarreta JH, Adluru N, Nair VA, Prabhakaran V, Alexander AL, Kamagata K, Saito Y, Uchida W, Andica C, Abe M, Bayrak RG, Wheeler-Kingshott CAMG, D'Angelo E, Palesi F, Savini G, Rolandi N, Guevara P, Houenou J, López-López N, Mangin JF, Poupon C, Román C, Vázquez A, Maffei C, Arantes M, Andrade JP, Silva SM, Calhoun VD, Caverzasi E, Sacco S, Lauricella M, Pestilli F, Bullock D, Zhan Y, Brignoni-Perez E, Lebel C, Reynolds JE, Nestrasil I, Labounek R, Lenglet C, Paulson A, Aulicka S, Heilbronner SR, Heuer K, Chandio BQ, Guaje J, Tang W, Garyfallidis E, Raja R, Anderson AW, Landman BA, Descoteaux M. Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset? Neuroimage 2021; 243:118502. [PMID: 34433094 PMCID: PMC8855321 DOI: 10.1016/j.neuroimage.2021.118502] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 08/10/2021] [Accepted: 08/21/2021] [Indexed: 10/20/2022] Open
Abstract
White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.
| | | | - Laurent Petit
- Groupe dImagerie Neurofonctionnelle, Institut Des Maladies Neurodegeneratives, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Colin B Hansen
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Vishwesh Nath
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, United States
| | - Gabriel Girard
- CIBM Center for BioMedical Imaging, Lausanne, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK), Department of Medicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland
| | - Jonathan Rafael-Patino
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Thomas Yu
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Elda Fischi-Gomez
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Marco Pizzolato
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | | | - Simona Schiavi
- Department of Computer Science, University of Verona, Italy
| | | | | | - Cristina Granziera
- Translational Imaging in Neurology (ThINK), Department of Medicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland
| | - Giorgio Innocenti
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jean-Philippe Thiran
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology & Neurosurgery, UCL Hospitals NHS Foundation Trust, London, United Kingdom
| | - Stephen Wastling
- Lysholm Department of Neuroradiology, National Hospital for Neurology & Neurosurgery, UCL Hospitals NHS Foundation Trust, London, United Kingdom
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Maria Petracca
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom
| | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Vejay N Vakharia
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom
| | - Helena Melero
- Departamento de Psicobiología y Metodología en Ciencias del Comportamiento - Universidad Complutense de Madrid, Spain Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | - Lidia Manzanedo
- Facultad de Ciencias de la Salud, Universidad Rey Juan Carlos, Madrid, Spain
| | - Emilio Sanz-Morales
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | - Ángel Peña-Melián
- Departamento de Anatomía, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Fernando Calamante
- Sydney Imaging and School of Biomedical Engineering, The University of Sydney, Sydney, Australia
| | - Arnaud Attyé
- School of Biomedical Engineering, The University of Sydney, Sydney, Australia
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Laura Korobova
- Center for Integrative Connectomics, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | | | - Drew Parker
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Ragini Verma
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Ahmed Radwan
- KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium
| | - Stefan Sunaert
- KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium
| | - Louise Emsell
- KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000, Leuven, Belgium
| | | | | | - Claude J Bajada
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, University of Malta, Malta
| | - Hamied Haroon
- Division of Neuroscience & Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | | | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Ping-Hong Yeh
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Rujirutana Srikanchana
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Colin D Mcknight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Joseph Yuan-Mou Yang
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Suite (NACIS), Royal Children's Hospital, Parkville, Melbourne, Australia
| | - Jian Chen
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Claire E Kelly
- Victorian Infant Brain Studies, Murdoch Children's Research Institute, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University & Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | | | - Jerome J Maller
- MRI Clinical Science Specialist, General Electric Healthcare, Australia
| | | | - Fabien Almairac
- Neurosurgery department, Hôpital Pasteur, University Hospital of Nice, Côte d'Azur University, France
| | - Kiran K Seunarine
- Developmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London
| | - Chris A Clark
- Developmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London
| | - Fan Zhang
- Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Nikos Makris
- Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexandra Golby
- Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yogesh Rathi
- Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lauren J O'Donnell
- Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yihao Xia
- University of Southern California, Keck School of Medicine, Neuroimaging and Informatics Institute, Los Angeles, California, United States
| | - Dogu Baran Aydogan
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Yonggang Shi
- University of Southern California, Keck School of Medicine, Neuroimaging and Informatics Institute, Los Angeles, California, United States
| | | | - Mathijs Raemaekers
- UMC Utrecht Brain Center, Department of Neurology&Neurosurgery, Utrecht, the Netherlands
| | - Shaun Warrington
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK
| | - Stijn Michielse
- Department of Neurosurgery, School for Mental Health and Neuroscience, Maastricht University
| | | | - Luis Concha
- Universidad Nacional Autonoma de Mexico, Institute of Neurobiology, Mexico City, Mexico
| | - Ramón Aranda
- Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE-UT3), Cátedras-CONACyT, Ensenada, Mexico
| | | | | | - Lucas Roitman
- Department of Psychology, Stanford University, Stanford, California, USA
| | - Lucius S Fekonja
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Navona Calarco
- Kimel Family Translational Imaging-Genetics Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Michael Joseph
- Kimel Family Translational Imaging-Genetics Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Hajer Nakua
- Kimel Family Translational Imaging-Genetics Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Aristotle N Voineskos
- Kimel Family Translational Imaging-Genetics Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | | | | | | | | | - Veena A Nair
- University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan
| | - Masahiro Abe
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo Japan
| | - Roza G Bayrak
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Giovanni Savini
- Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Nicolò Rolandi
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Pamela Guevara
- Universidad de Concepción, Faculty of Engineering, Concepción, Chile
| | - Josselin Houenou
- Université Paris-Saclay, CEA, CNRS, Neurospin, Gif-sur-Yvette, France
| | | | | | - Cyril Poupon
- Université Paris-Saclay, CEA, CNRS, Neurospin, Gif-sur-Yvette, France
| | - Claudio Román
- Universidad de Concepción, Faculty of Engineering, Concepción, Chile
| | - Andrea Vázquez
- Universidad de Concepción, Faculty of Engineering, Concepción, Chile
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Mavilde Arantes
- Department of Biomedicine, Unit of Anatomy, Faculty of Medicine of the University of Porto, Al. Professor Hernâni Monteiro, Porto, Portugal
| | - José Paulo Andrade
- Department of Biomedicine, Unit of Anatomy, Faculty of Medicine of the University of Porto, Al. Professor Hernâni Monteiro, Porto, Portugal
| | - Susana Maria Silva
- Department of Biomedicine, Unit of Anatomy, Faculty of Medicine of the University of Porto, Al. Professor Hernâni Monteiro, Porto, Portugal
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303, United States
| | - Eduardo Caverzasi
- Neurology Department UCSF Weill Institute for Neurosciences, University of California, San Francisco
| | - Simone Sacco
- Neurology Department UCSF Weill Institute for Neurosciences, University of California, San Francisco
| | - Michael Lauricella
- Memory and Aging Center. UCSF Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Franco Pestilli
- Department of Psychology, The University of Texas at Austin, TX 78731, USA
| | - Daniel Bullock
- Department of Psychology, The University of Texas at Austin, TX 78731, USA
| | - Yang Zhan
- Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Edith Brignoni-Perez
- Developmental-Behavioral Pediatrics Division, Department of Pediatrics, Stanford School of Medicine, Stanford, CA, United States
| | - Catherine Lebel
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada, T2N 1N4
| | - Jess E Reynolds
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada, T2N 1N4
| | - Igor Nestrasil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Amy Paulson
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Stefania Aulicka
- Department of Paediatric Neurology, University Hospital and Medicine Faculty, Masaryk University, Brno, Czech Republic
| | | | - Katja Heuer
- Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, Paris, France
| | - Bramsh Qamar Chandio
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Javier Guaje
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Wei Tang
- Department of Computer Science, Indiana University, Bloomington, IN, USA
| | | | - Rajikha Raja
- University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Adam W Anderson
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
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Petracca M, Cutter G, Cocozza S, Freeman L, Kangarlu J, Margoni M, Moro M, Krieger S, El Mendili MM, Droby A, Wolinsky JS, Lublin F, Inglese M. Cerebellar pathology and disability worsening in relapsing-remitting multiple sclerosis: A retrospective analysis from the CombiRx trial. Eur J Neurol 2021; 29:515-521. [PMID: 34695274 DOI: 10.1111/ene.15157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/27/2021] [Accepted: 10/21/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND PURPOSE Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype. AIM We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype. METHODS Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25-foot walk test [T25FWT] score worsening, nine-hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage. RESULTS Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001). CONCLUSION Among the explored outcomes, single time-point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest.
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Affiliation(s)
- Maria Petracca
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Human Neurosciences, Sapienza University, Rome, Italy
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Sirio Cocozza
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Houston, Texas, USA
| | - John Kangarlu
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Monica Margoni
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Padova Neuroscience Centre, University of Padua, Padua, Italy
| | - Matteo Moro
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy
| | - Stephen Krieger
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mohamed Mounir El Mendili
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Aix Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Amgad Droby
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Sagol School for Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Jerry S Wolinsky
- University of Texas Health Science Center at Houston (UTHealth), Houston, Texas, USA
| | - Fred Lublin
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genoa, Genoa, Italy.,Ospedale Policlinico San Martino, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Genoa, Italy
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Petracca M, Pontillo G, Monti S, Quarantelli M, Lanzillo R, Costabile T, Carotenuto A, Tortora F, Elefante A, Morra VB, Palma G, Cocozza S, Brunetti A. Clinical relevance of atrophy, myelin and iron brain microstructural alterations in multiple sclerosis: A multi-parameter MRI study. J Neurol Sci 2021. [DOI: 10.1016/j.jns.2021.118169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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34
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Pontillo G, Tommasin S, Cuocolo R, Petracca M, Petsas N, Ugga L, Carotenuto A, Pozzilli C, Iodice R, Lanzillo R, Quarantelli M, Brescia Morra V, Tedeschi E, Pantano P, Cocozza S. A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis. AJNR Am J Neuroradiol 2021; 42:1927-1933. [PMID: 34531195 DOI: 10.3174/ajnr.a7274] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 07/12/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Conventional MR imaging explains only a fraction of the clinical outcome variance in multiple sclerosis. We aimed to evaluate machine learning models for disability prediction on the basis of radiomic, volumetric, and connectivity features derived from routine brain MR images. MATERIALS AND METHODS In this retrospective cross-sectional study, 3T brain MR imaging studies of patients with multiple sclerosis, including 3D T1-weighted and T2-weighted FLAIR sequences, were selected from 2 institutions. T1-weighted images were processed to obtain volume, connectivity score (inferred from the T2 lesion location), and texture features for an atlas-based set of GM regions. The site 1 cohort was randomly split into training (n = 400) and test (n = 100) sets, while the site 2 cohort (n = 104) constituted the external test set. After feature selection of clinicodemographic and MR imaging-derived variables, different machine learning algorithms predicting disability as measured with the Expanded Disability Status Scale were trained and cross-validated on the training cohort and evaluated on the test sets. The effect of different algorithms on model performance was tested using the 1-way repeated-measures ANOVA. RESULTS The selection procedure identified the 9 most informative variables, including age and secondary-progressive course and a subset of radiomic features extracted from the prefrontal cortex, subcortical GM, and cerebellum. The machine learning models predicted disability with high accuracy (r approaching 0.80) and excellent intra- and intersite generalizability (r ≥ 0.73). The machine learning algorithm had no relevant effect on the performance. CONCLUSIONS The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.
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Affiliation(s)
- G Pontillo
- From the Departments of Advanced Biomedical Sciences (G.P., L.U., E.T., S.C.).,Electrical Engineering and Information Technology (G.P., M.Q.)
| | - S Tommasin
- Department of Human Neuroscience (S.T., C.P., P.P.), Sapienza University of Rome, Rome, Italy
| | - R Cuocolo
- Clinical Medicine and Surgery (R.C.) .,Laboratory of Augmented Reality for Health Monitoring (R.C.)
| | - M Petracca
- Department of Electrical Engineering and Information Technology, and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P., A.C., R.I., R.L., V.B.M.), University of Naples "Federico II," Naples, Italy
| | - N Petsas
- Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologico Mediterraneo (N.P., P.P.), Pozzilli, Italy
| | - L Ugga
- From the Departments of Advanced Biomedical Sciences (G.P., L.U., E.T., S.C.)
| | - A Carotenuto
- Department of Electrical Engineering and Information Technology, and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P., A.C., R.I., R.L., V.B.M.), University of Naples "Federico II," Naples, Italy
| | - C Pozzilli
- Department of Human Neuroscience (S.T., C.P., P.P.), Sapienza University of Rome, Rome, Italy
| | - R Iodice
- Department of Electrical Engineering and Information Technology, and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P., A.C., R.I., R.L., V.B.M.), University of Naples "Federico II," Naples, Italy
| | - R Lanzillo
- Department of Electrical Engineering and Information Technology, and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P., A.C., R.I., R.L., V.B.M.), University of Naples "Federico II," Naples, Italy
| | - M Quarantelli
- Electrical Engineering and Information Technology (G.P., M.Q.).,Institute of Biostructure and Bioimaging (M.Q.), National Research Council, Naples, Italy
| | - V Brescia Morra
- Department of Electrical Engineering and Information Technology, and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P., A.C., R.I., R.L., V.B.M.), University of Naples "Federico II," Naples, Italy
| | - E Tedeschi
- From the Departments of Advanced Biomedical Sciences (G.P., L.U., E.T., S.C.)
| | - P Pantano
- Department of Human Neuroscience (S.T., C.P., P.P.), Sapienza University of Rome, Rome, Italy.,Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologico Mediterraneo (N.P., P.P.), Pozzilli, Italy
| | - S Cocozza
- From the Departments of Advanced Biomedical Sciences (G.P., L.U., E.T., S.C.)
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35
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Harding IH, Chopra S, Arrigoni F, Boesch S, Brunetti A, Cocozza S, Corben LA, Deistung A, Delatycki M, Diciotti S, Dogan I, Evangelisti S, França MC, Göricke SL, Georgiou-Karistianis N, Gramegna LL, Henry PG, Hernandez-Castillo CR, Hutter D, Jahanshad N, Joers JM, Lenglet C, Lodi R, Manners DN, Martinez ARM, Martinuzzi A, Marzi C, Mascalchi M, Nachbauer W, Pane C, Peruzzo D, Pisharady PK, Pontillo G, Reetz K, Rezende TJR, Romanzetti S, Saccà F, Scherfler C, Schulz JB, Stefani A, Testa C, Thomopoulos SI, Timmann D, Tirelli S, Tonon C, Vavla M, Egan GF, Thompson PM. Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group. Ann Neurol 2021; 90:570-583. [PMID: 34435700 PMCID: PMC9292360 DOI: 10.1002/ana.26200] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 08/19/2021] [Accepted: 08/21/2021] [Indexed: 01/24/2023]
Abstract
Objective Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. Methods A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole‐brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. Results The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5–2.6). Cerebellar gray matter alterations were most pronounced in lobules I–VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax = 0.35) and peduncles (rmax = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax = −0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. Interpretation FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570–583
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Affiliation(s)
- Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia.,Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
| | - Sidhant Chopra
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.,School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Filippo Arrigoni
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Sylvia Boesch
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Louise A Corben
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia.,Bruce Lefroy Centre, Murdoch Children's Research Institute, Parkville, VIC, Australia.,University of Melbourne, Parkville, VIC, Australia
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Halle (Saale), Germany.,Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Martin Delatycki
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi,", University of Bologna, Bologna, Italy
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute, Molecular Neuroscience and Neuroimaging, Research Center Jülich, Jülich, Germany
| | - Stefania Evangelisti
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Marcondes C França
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Laura L Gramegna
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Institute of Neurological Sciences of Bologna, Functional and Molecular Neuroimaging Unit, Bologna, Italy
| | - Pierre-Gilles Henry
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - Carlos R Hernandez-Castillo
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.,CONACYT-Institute of Neuroethology, University of Veracruz, Xalapa, Mexico
| | - Diane Hutter
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA
| | - James M Joers
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - Christophe Lenglet
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Institute of Neurological Sciences of Bologna, Bologna, Italy
| | - David N Manners
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Alberto R M Martinez
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Andrea Martinuzzi
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Center, Conegliano, Italy
| | - Chiara Marzi
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi,", University of Bologna, Bologna, Italy
| | - Mario Mascalchi
- Department of Clinical and Experimental Biomedical Sciences "Mario Serio,", University of Florence, Florence, Italy.,Clinical Epidemiology Unit, ISPRO, Oncological Network, Prevention and Research Institute, Florence, Italy
| | | | - Chiara Pane
- NSRO Department, University of Naples Federico II, Naples, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Pramod K Pisharady
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.,Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute, Molecular Neuroscience and Neuroimaging, Research Center Jülich, Jülich, Germany
| | - Thiago J R Rezende
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute, Molecular Neuroscience and Neuroimaging, Research Center Jülich, Jülich, Germany
| | - Francesco Saccà
- NSRO Department, University of Naples Federico II, Naples, Italy
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Jörg B Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute, Molecular Neuroscience and Neuroimaging, Research Center Jülich, Jülich, Germany
| | - Ambra Stefani
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Testa
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA
| | - Dagmar Timmann
- Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Stefania Tirelli
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Institute of Neurological Sciences of Bologna, Functional and Molecular Neuroimaging Unit, Bologna, Italy
| | - Marinela Vavla
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Center, Conegliano, Italy
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.,School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA
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36
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Porcu M, Cocco L, Cocozza S, Pontillo G, Operamolla A, Defazio G, Suri JS, Brunetti A, Saba L. The association between white matter hyperintensities, cognition and regional neural activity in healthy subjects. Eur J Neurosci 2021; 54:5427-5443. [PMID: 34327745 DOI: 10.1111/ejn.15403] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 07/03/2021] [Accepted: 07/24/2021] [Indexed: 11/29/2022]
Abstract
White matter hyperintensities (WMH) are common findings that can be found in physiological ageing. Several studies suggest that the disruption of white matter tracts included in WMH could induce abnormal functioning of the respective linked cortical structures, with consequent repercussion on the cerebral functions, included the cognitive sphere. In this cross-sectional research, we analysed the effects of the total WMH burden (tWMHb) on resting-state functional magnetic resonance imaging (rs-fMRI) and cognition. Functional and structural MR data, as well as the scores of the trail making test subtests A (TMT-A) and B (TMT-B) of 75 healthy patients, were extracted from the public available Leipzig Study for Mind-Body-Emotion Interactions dataset. tWMHb was extracted from structural data. Spearman's correlation analyses were made for investigating correlations between WMHb and the scores of the cognitive tests. The fractional amplitude of low-frequency fluctuations (fALFF) method was applied for analysing the rs-fMRI data, adopting a multiple regression model for studying the effects of tWMHb on brain activity. Three different subanalyses were conducted using different statistical methods. We observed statistically significant correlations between WMHb and the scores of the cognitive tests. The fALFF analysis revealed that tWMHb is associated with the reduction of regional neural activity of several brain areas (in particular the prefrontal cortex, precuneus and cerebellar crus I/II). We conclude that our findings clarify better the relationships between WMH and cognitive impairment, evidencing that tWMHb is associated with impairments of the neurocognitive function in healthy subjects by inducing a diffuse reduction of the neural activity.
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Affiliation(s)
- Michele Porcu
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
| | - Luigi Cocco
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
| | - Sirio Cocozza
- Department of Neuroradiology, University of Napoli "Federico II", Napoli, Italy
| | - Giuseppe Pontillo
- Department of Neuroradiology, University of Napoli "Federico II", Napoli, Italy
| | | | - Giovanni Defazio
- Department of Neurology, University of Cagliari, Cagliari, Italy
| | - Jasjit S Suri
- Stroke Diagnosis and Monitoring Division, AtheroPoint™, Roseville, California, USA
| | - Arturo Brunetti
- Department of Neuroradiology, University of Napoli "Federico II", Napoli, Italy
| | - Luca Saba
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
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37
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De Michele G, Galatolo D, Galosi S, Mignarri A, Silvestri G, Casali C, Leuzzi V, Ricca I, Barghigiani M, Tessa A, Cioffi E, Caputi C, Riso V, Dotti MT, Saccà F, De Michele G, Cocozza S, Filla A, Santorelli FM. Episodic ataxia and severe infantile phenotype in spinocerebellar ataxia type 14: expansion of the phenotype and novel mutations. J Neurol 2021; 269:1476-1484. [PMID: 34292398 PMCID: PMC8857164 DOI: 10.1007/s00415-021-10712-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 07/08/2021] [Accepted: 07/10/2021] [Indexed: 12/30/2022]
Abstract
Introduction Spinocerebellar ataxia type 14 (SCA14) is a dominantly inherited neurological disorder characterized by slowly progressive cerebellar ataxia. SCA14 is caused by mutations in PRKCG, a gene encoding protein kinase C gamma (PKCγ), a master regulator of Purkinje cells development. Methods We performed next-generation sequencing targeted resequencing panel encompassing 273 ataxia genes in 358 patients with genetically undiagnosed ataxia. Results We identified fourteen patients in ten families harboring nine pathogenic heterozygous variants in PRKCG, seven of which were novel. We encountered four patients with not previously described phenotypes: one with episodic ataxia, one with a spastic paraparesis dominating her clinical manifestations, and two children with an unusually severe phenotype. Conclusions Our study broadens the genetic and clinical spectrum of SCA14. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-021-10712-5.
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Affiliation(s)
- Giovanna De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Daniele Galatolo
- Istituto Di Ricovero E Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
| | - Serena Galosi
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Andrea Mignarri
- Department of Medicine, Surgery and Neuroscience, Neurology and Neurometabolic Unit, University of Siena, Siena, Italy
| | - Gabriella Silvestri
- Department of Neurosciences, Faculty of Medicine and Surgery, Catholic University of Sacred Heart, Rome, Italy
- Neurology Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Carlo Casali
- Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - Vincenzo Leuzzi
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Ivana Ricca
- Istituto Di Ricovero E Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
| | - Melissa Barghigiani
- Istituto Di Ricovero E Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
| | - Alessandra Tessa
- Istituto Di Ricovero E Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
| | - Ettore Cioffi
- Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - Caterina Caputi
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Vittorio Riso
- Department of Neurosciences, Faculty of Medicine and Surgery, Catholic University of Sacred Heart, Rome, Italy
- Neurology Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Maria Teresa Dotti
- Department of Medicine, Surgery and Neuroscience, Neurology and Neurometabolic Unit, University of Siena, Siena, Italy
| | - Francesco Saccà
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Giuseppe De Michele
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, Federico II University, Naples, Italy
| | - Alessandro Filla
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy.
| | - Filippo M Santorelli
- Istituto Di Ricovero E Cura a Carattere Scientifico (IRCCS), Fondazione Stella Maris, Pisa, Italy
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38
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Tortora M, Tranfa M, D’Elia AC, Pontillo G, Petracca M, Bozzao A, Caranci F, Cervo A, Cosottini M, Falini A, Longo M, Manara R, Muto M, Porcu M, Roccatagliata L, Todeschini A, Saba L, Brunetti A, Cocozza S, Elefante A. Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis. Diagnostics (Basel) 2021; 11:diagnostics11081310. [PMID: 34441245 PMCID: PMC8394408 DOI: 10.3390/diagnostics11081310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/15/2021] [Accepted: 07/19/2021] [Indexed: 11/23/2022] Open
Abstract
(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients’ care in MS.
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Affiliation(s)
- Mario Tortora
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Anna Chiara D’Elia
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Maria Petracca
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, 80131 Naples, Italy;
- Department of Human Neurosciences, Sapienza University of Rome, 00189 Rome, Italy
| | - Alessandro Bozzao
- Neuroradiology Unit, NESMOS Department, Sapienza University of Rome, 00189 Rome, Italy;
| | - Ferdinando Caranci
- Department of Medicine of Precision, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy;
| | - Amedeo Cervo
- Department of Neuroradiology, ASST Grande Ospedale Metropolitano Niguarda, 20121 Milan, Italy;
| | - Mirco Cosottini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy;
| | - Andrea Falini
- Neuroradiology Department, IRCCS San Raffaele Hospital and University, 20132 Milan, Italy;
| | - Marcello Longo
- Neuroradiology Unit, Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, 98124 Messina, Italy;
| | - Renzo Manara
- Department of Neurosciences, University of Padua, 35121 Padua, Italy;
| | - Mario Muto
- Diagnostic and Interventional Neuroradiology, Cardarelli Hospital, 80131 Naples, Italy;
| | - Michele Porcu
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari, 09124 Cagliari, Italy; (M.P.); (L.S.)
| | - Luca Roccatagliata
- Department of Health Sciences, University of Genova, 16132 Genova, Italy;
- Neuroradiology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Alessandra Todeschini
- Neuroradiology Unit, Department of Neuroscience, Nuovo Ospedale Civile S. Agostino Estense, 41126 Modena, Italy;
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari, 09124 Cagliari, Italy; (M.P.); (L.S.)
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
- Correspondence:
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
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Castaldo A, De Lucia DR, Pontillo G, Gatti M, Cocozza S, Ugga L, Cuocolo R. State of the Art in Artificial Intelligence and Radiomics in Hepatocellular Carcinoma. Diagnostics (Basel) 2021; 11:1194. [PMID: 34209197 PMCID: PMC8307071 DOI: 10.3390/diagnostics11071194] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/24/2021] [Accepted: 06/24/2021] [Indexed: 12/12/2022] Open
Abstract
The most common liver malignancy is hepatocellular carcinoma (HCC), which is also associated with high mortality. Often HCC develops in a chronic liver disease setting, and early diagnosis as well as accurate screening of high-risk patients is crucial for appropriate and effective management of these patients. While imaging characteristics of HCC are well-defined in the diagnostic phase, challenging cases still occur, and current prognostic and predictive models are limited in their accuracy. Radiomics and machine learning (ML) offer new tools to address these issues and may lead to scientific breakthroughs with the potential to impact clinical practice and improve patient outcomes. In this review, we will present an overview of these technologies in the setting of HCC imaging across different modalities and a range of applications. These include lesion segmentation, diagnosis, prognostic modeling and prediction of treatment response. Finally, limitations preventing clinical application of radiomics and ML at the present time are discussed, together with necessary future developments to bring the field forward and outside of a purely academic endeavor.
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Affiliation(s)
- Anna Castaldo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (A.C.); (D.R.D.L.); (G.P.); (S.C.); (L.U.)
| | - Davide Raffaele De Lucia
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (A.C.); (D.R.D.L.); (G.P.); (S.C.); (L.U.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (A.C.); (D.R.D.L.); (G.P.); (S.C.); (L.U.)
| | - Marco Gatti
- Radiology Unit, Department of Surgical Sciences, University of Turin, 10124 Turin, Italy;
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (A.C.); (D.R.D.L.); (G.P.); (S.C.); (L.U.)
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (A.C.); (D.R.D.L.); (G.P.); (S.C.); (L.U.)
| | - Renato Cuocolo
- Department of Clinical Medicine and Surgery, University of Naples “Federico II”, 80131 Naples, Italy
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40
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Tommasin S, Cocozza S, Taloni A, Giannì C, Petsas N, Pontillo G, Petracca M, Ruggieri S, De Giglio L, Pozzilli C, Brunetti A, Pantano P. Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis. J Neurol 2021; 268:4834-4845. [PMID: 33970338 PMCID: PMC8563671 DOI: 10.1007/s00415-021-10605-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 05/05/2021] [Accepted: 05/05/2021] [Indexed: 01/22/2023]
Abstract
Objectives To evaluate the accuracy of a data-driven approach, such as machine learning classification, in predicting disability progression in MS. Methods We analyzed structural brain images of 163 subjects diagnosed with MS acquired at two different sites. Participants were followed up for 2–6 years, with disability progression defined according to the expanded disability status scale (EDSS) increment at follow-up. T2-weighted lesion load (T2LL), thalamic and cerebellar gray matter (GM) volumes, fractional anisotropy of the normal appearing white matter were calculated at baseline and included in supervised machine learning classifiers. Age, sex, phenotype, EDSS at baseline, therapy and time to follow-up period were also included. Classes were labeled as stable or progressed disability. Participants were randomly chosen from both sites to build a sample including 50% patients showing disability progression and 50% patients being stable. One-thousand machine learning classifiers were applied to the resulting sample, and after testing for overfitting, classifier confusion matrix, relative metrics and feature importance were evaluated. Results At follow-up, 36% of participants showed disability progression. The classifier with the highest resulting metrics had accuracy of 0.79, area under the true positive versus false positive rates curve of 0.81, sensitivity of 0.90 and specificity of 0.71. T2LL, thalamic volume, disability at baseline and administered therapy were identified as important features in predicting disability progression. Classifiers built on radiological features had higher accuracy than those built on clinical features. Conclusions Disability progression in MS may be predicted via machine learning classifiers, mostly evaluating neuroradiological features. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-021-10605-7.
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Affiliation(s)
- Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.
| | - Sirio Cocozza
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Alessandro Taloni
- Institute for Complex Systems, Italian National Research Council, Rome, Italy
| | - Costanza Giannì
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy
| | | | - Giuseppe Pontillo
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy.,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Maria Petracca
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Dipartimento di Neuroscienze, Scienze Riproduttive e Odontostomatologiche, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Serena Ruggieri
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Laura De Giglio
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Neurology Unit, Medicine Department, San Filippo Neri Hospital, Rome, Italy
| | - Carlo Pozzilli
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy
| | - Arturo Brunetti
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Department of Radiology, IRCCS NEUROMED, Pozzilli, Italy
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41
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Pontillo G, Petracca M, Monti S, Quarantelli M, Criscuolo C, Lanzillo R, Tedeschi E, Elefante A, Brescia Morra V, Brunetti A, Cocozza S, Palma G. Unraveling Deep Gray Matter Atrophy and Iron and Myelin Changes in Multiple Sclerosis. AJNR Am J Neuroradiol 2021; 42:1223-1230. [PMID: 33888456 DOI: 10.3174/ajnr.a7093] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 01/11/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND AND PURPOSE Modifications of magnetic susceptibility have been consistently demonstrated in the subcortical gray matter of MS patients, but some uncertainties remain concerning the underlying neurobiological processes and their clinical relevance. We applied quantitative susceptibility mapping and longitudinal relaxation rate relaxometry to clarify the relative contribution of atrophy and iron and myelin changes to deep gray matter damage and disability in MS. MATERIALS AND METHODS Quantitative susceptibility mapping and longitudinal relaxation rate maps were computed for 91 patients and 55 healthy controls from MR images acquired at 3T. Applying an external model, we estimated iron and myelin concentration maps for all subjects. Subsequently, changes of deep gray matter iron and myelin concentration (atrophy-dependent) and content (atrophy-independent) were investigated globally (bulk analysis) and regionally (voxel-based and atlas-based thalamic subnuclei analyses). The clinical impact of the observed MRI modifications was evaluated via regression models. RESULTS We identified reduced thalamic (P < .001) and increased pallidal (P < .001) mean iron concentrations in patients with MS versus controls. Global myelin and iron content in the basal ganglia did not differ between the two groups, while actual iron depletion was present in the thalamus (P < .001). Regionally, patients showed increased iron concentration in the basal ganglia (P ≤ .001) and reduced iron and myelin content in thalamic posterior-medial regions (P ≤ .004), particularly in the pulvinar (P ≤ .001). Disability was predicted by thalamic volume (B = -0.341, P = .02), iron concentration (B = -0.379, P = .005) and content (B = -0.406, P = .009), as well as pulvinar iron (B = -0.415, P = .003) and myelin (B = -0.415, P = .02) content, independent of atrophy. CONCLUSIONS Quantitative MRI suggests an atrophy-related iron increase within the basal ganglia of patients with MS, along with an atrophy-independent reduction of thalamic iron and myelin correlating with disability. Absolute depletions of thalamic iron and myelin may represent sensitive markers of subcortical GM damage, which add to the clinical impact of thalamic atrophy in MS.
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Affiliation(s)
- G Pontillo
- From the Departments of Advanced Biomedical Sciences (G.P., E.T., A.E., A.B., S.C.)
| | - M Petracca
- Neurosciences and Reproductive and Odontostomatological Sciences (M.P., C.C., R.L., V.B.M.), University "Federico II," Naples, Italy
| | - S Monti
- Institute of Biostructure and Bioimaging, (S.M., M.Q., G.P.) National Research Council, Naples, Italy
| | - M Quarantelli
- Institute of Biostructure and Bioimaging, (S.M., M.Q., G.P.) National Research Council, Naples, Italy
| | - C Criscuolo
- Neurosciences and Reproductive and Odontostomatological Sciences (M.P., C.C., R.L., V.B.M.), University "Federico II," Naples, Italy
| | - R Lanzillo
- Neurosciences and Reproductive and Odontostomatological Sciences (M.P., C.C., R.L., V.B.M.), University "Federico II," Naples, Italy
| | - E Tedeschi
- From the Departments of Advanced Biomedical Sciences (G.P., E.T., A.E., A.B., S.C.)
| | - A Elefante
- From the Departments of Advanced Biomedical Sciences (G.P., E.T., A.E., A.B., S.C.)
| | - V Brescia Morra
- Neurosciences and Reproductive and Odontostomatological Sciences (M.P., C.C., R.L., V.B.M.), University "Federico II," Naples, Italy
| | - A Brunetti
- From the Departments of Advanced Biomedical Sciences (G.P., E.T., A.E., A.B., S.C.)
| | - S Cocozza
- From the Departments of Advanced Biomedical Sciences (G.P., E.T., A.E., A.B., S.C.)
| | - G Palma
- Institute of Biostructure and Bioimaging, (S.M., M.Q., G.P.) National Research Council, Naples, Italy
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Schiavi S, Petracca M, Sun P, Fleysher L, Cocozza S, El Mendili MM, Signori A, Babb JS, Podranski K, Song SK, Inglese M. Non-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis. Brain 2021; 144:213-223. [PMID: 33253366 DOI: 10.1093/brain/awaa381] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 08/12/2020] [Accepted: 08/21/2020] [Indexed: 02/06/2023] Open
Abstract
The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.
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Affiliation(s)
- Simona Schiavi
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Italy.,Ospedale Policlinico San Martino-IRCCS, Genoa, Italy
| | - Maria Petracca
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Peng Sun
- Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sirio Cocozza
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Alessio Signori
- Department of Health Sciences, University of Genoa, Genoa, Italy
| | - James S Babb
- Department of Radiology, Center for Biomedical Imaging, New York University, Langone Medical Center, New York, USA
| | - Kornelius Podranski
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sheng-Kwei Song
- Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Biomedical Engineering, Washington University, St. Louis, MO, USA.,Biomedical MR Laboratory, Washington University School of Medicine, St. Louis, MO, USA
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Italy.,Ospedale Policlinico San Martino-IRCCS, Genoa, Italy
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Russo C, Pontillo G, Saccà F, Riccio E, Cocozza S, Pane C, Tedeschi E, Pisani A, Pappatà S. Nonvascular Parkinsonism in Fabry Disease: Results From Magnetic Resonance and Dopamine Transporter Imaging. J Neuropathol Exp Neurol 2021; 80:476-479. [PMID: 33837397 DOI: 10.1093/jnen/nlab030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Camilla Russo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Francesco Saccà
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Eleonora Riccio
- Department of Public Health, Nephrology Unit, University of Naples "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Chiara Pane
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Enrico Tedeschi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Antonio Pisani
- Department of Public Health, Nephrology Unit, University of Naples "Federico II", Naples, Italy
| | - Sabina Pappatà
- Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy
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Vola EA, Petracca M, Cocozza S, De Angelis M, Carotenuto A, Pontillo G, Morra VB, Tedeschi E, Lanzillo R. Possible progressive multifocal leukoencephalopathy and active multiple sclerosis under dimethyl fumarate: the central role of MRI in informing therapeutic decisions. BMC Neurol 2021; 21:146. [PMID: 33820529 PMCID: PMC8020541 DOI: 10.1186/s12883-021-02165-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 03/22/2021] [Indexed: 01/20/2023] Open
Abstract
Background Progressive multifocal leukoencephalopathy (PML) can rarely occur in Multiple Sclerosis (MS) patients undergoing dimethyl fumarate (DMF) treatment. Our case stresses the limits of current diagnostic and stratification risk criteria, highlighting the potential role of Magnetic Resonance Imaging (MRI) in advising clinical choices. Case presentation A 54 years old MS male patient treated with DMF, after 3 years of clinical stability developed a subacute clinical worsening. He had no severe lymphopenia but MRI signs suggestive of a coexistence of PML and MS activity. Although his viral title was negative, DMF was discontinued, with clinical and radiological improvement. Conclusions This case highlights the challenges behind PML diagnosis, especially in patients not fulfilling the risk stratification criteria and that might present with concurrent disease activity, stressing the potential role of MRI in informing therapeutic decisions.
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Affiliation(s)
- Elena Augusta Vola
- Department of Advanced Biomedical Sciences, "Federico II" University, Naples, Italy
| | - Maria Petracca
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, "Federico II" University, Naples, Italy.
| | - Marcello De Angelis
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University, Naples, Italy
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, "Federico II" University, Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University, Naples, Italy
| | - Enrico Tedeschi
- Department of Advanced Biomedical Sciences, "Federico II" University, Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University, Naples, Italy
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Cocozza S, Pontillo G, De Michele G, Di Stasi M, Guerriero E, Perillo T, Pane C, De Rosa A, Ugga L, Brunetti A. Conventional MRI findings in hereditary degenerative ataxias: a pictorial review. Neuroradiology 2021; 63:983-999. [PMID: 33733696 PMCID: PMC8213578 DOI: 10.1007/s00234-021-02682-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 02/25/2021] [Indexed: 12/15/2022]
Abstract
Purpose Cerebellar ataxias are a large and heterogeneous group of disorders. The evaluation of brain parenchyma via MRI plays a central role in the diagnostic assessment of these conditions, being mandatory to exclude the presence of other underlying causes in determining the clinical phenotype. Once these possible causes are ruled out, the diagnosis is usually researched in the wide range of hereditary or sporadic ataxias. Methods We here propose a review of the main clinical and conventional imaging findings of the most common hereditary degenerative ataxias, to help neuroradiologists in the evaluation of these patients. Results Hereditary degenerative ataxias are all usually characterized from a neuroimaging standpoint by the presence, in almost all cases, of cerebellar atrophy. Nevertheless, a proper assessment of imaging data, extending beyond the mere evaluation of cerebellar atrophy, evaluating also the pattern of volume loss as well as concomitant MRI signs, is crucial to achieve a proper diagnosis. Conclusion The integration of typical neuroradiological characteristics, along with patient’s clinical history and laboratory data, could allow the neuroradiologist to identify some conditions and exclude others, addressing the neurologist to the more appropriate genetic testing.
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Affiliation(s)
- Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy.
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy.,Department of Electrical Engineering and Information Technology, University of Naples "Federico II", Naples, Italy
| | - Giovanna De Michele
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Martina Di Stasi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy
| | - Elvira Guerriero
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy
| | - Teresa Perillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy
| | - Chiara Pane
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Anna De Rosa
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini, 5, 80131, Naples, Italy
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Petracca M, Pontillo G, Moccia M, Carotenuto A, Cocozza S, Lanzillo R, Brunetti A, Brescia Morra V. Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis. Brain Sci 2021; 11:346. [PMID: 33803287 PMCID: PMC8000635 DOI: 10.3390/brainsci11030346] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/02/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.
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Affiliation(s)
- Maria Petracca
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
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47
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Affiliation(s)
- Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
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48
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Ugga L, Pontillo G, Cuocolo R, Cocozza S, Brunetti A. MRI Linear Measurements in Normal Pressure Hydrocephalus Versus Progressive Supranuclear Palsy. Mov Disord 2021; 35:2121. [PMID: 33463765 DOI: 10.1002/mds.28330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 11/12/2022] Open
Affiliation(s)
- Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Renato Cuocolo
- Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
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Di Risi T, Vinciguerra R, Cuomo M, Della Monica R, Riccio E, Cocozza S, Imbriaco M, Duro G, Pisani A, Chiariotti L. DNA methylation impact on Fabry disease. Clin Epigenetics 2021; 13:24. [PMID: 33531072 PMCID: PMC7852133 DOI: 10.1186/s13148-021-01019-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 01/25/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Fabry disease (FD) is a rare X-linked disease caused by mutations in GLA gene with consequent lysosomal accumulation of globotriaosylceramide (Gb3). Women with FD often show highly heterogeneous symptoms that can manifest from mild to severe phenotype. MAIN BODY The phenotypic variability of the clinical manifestations in heterozygous women with FD mainly depends on the degree and direction of inactivation of the X chromosome. Classical approaches to measure XCI skewness might be not sufficient to explain disease manifestation in women. In addition to unbalanced XCI, allele-specific DNA methylation at promoter of GLA gene may influence the expression levels of the mutated allele, thus impacting the onset and the outcome of FD. In this regard, analyses of DNA methylation at GLA promoter, performed by approaches allowing distinction between mutated and non-mutated allele, may be much more informative. The aim of this review is to critically evaluate recent literature articles addressing the potential role of DNA methylation in the context of FD. Although up to date relatively few works have addressed this point, reviewing all pertinent studies may help to evaluate the importance of DNA methylation analysis in FD and to develop new research and technologies aimed to predict whether the carrier females will develop symptoms. CONCLUSIONS Relatively few studies have addressed the complexity of DNA methylation landscape in FD that remains poorly investigated. The hope for the future is that ad hoc and ultradeep methylation analyses of GLA gene will provide epigenetic signatures able to predict whether pre-symptomatic female carriers will develop symptoms thus helping timely interventions.
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Affiliation(s)
- Teodolinda Di Risi
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Roberta Vinciguerra
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Mariella Cuomo
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Molecular Medicine and Medical Biotechnology, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Rosa Della Monica
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
| | - Eleonora Riccio
- Institute for Biomedical Research and Innovation, National Research Council of Italy (IRIB CNR), Palermo, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Giovanni Duro
- Institute for Biomedical Research and Innovation, National Research Council of Italy (IRIB CNR), Palermo, Italy
| | - Antonio Pisani
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Lorenzo Chiariotti
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy.
- Department of Molecular Medicine and Medical Biotechnology, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy.
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50
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Cennamo G, Montorio D, Santoro C, Cocozza S, Spinelli L, Di Risi T, Riccio E, Russo C, Pontillo G, Esposito R, Imbriaco M, Pisani A. The Retinal Vessel Density as a New Vascular Biomarker in Multisystem Involvement in Fabry Disease: An Optical Coherence Tomography Angiography Study. J Clin Med 2020; 9:jcm9124087. [PMID: 33352849 PMCID: PMC7766384 DOI: 10.3390/jcm9124087] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/11/2020] [Accepted: 12/16/2020] [Indexed: 12/13/2022] Open
Abstract
In this study, we evaluated the possible relationship between the changes in retinal vessel density (VD) by optical coherence tomography angiography (OCTA) and the vascular alterations involving renal, cardiovascular and central nervous systems in patients affected by Fabry disease (FD). In 50 FD patients, the retinal superficial capillary plexus (SCP) and deep capillary plexus (DCP) in macular region were evaluated by OCTA examination. The patients also underwent a brain magnetic resonance imaging scan, renal and echocardiographic examinations with quantification of systolic pulmonary arterial pressure (PAPs) and left atrial volume index (LAVi). The VD of SCP and DCP was inversely related with E/e’ ratio, LAVi, interventricular septal thickness, global longitudinal strain (GLS) and PAPs (p < 0.05). No relationship was found, with a multivariate analysis, between OCTA parameters and kidney function and neuroradiological signs of central nervous system involvement. OCTA could be a new vascular biomarker in FD, revealing a strong correlation between retinal capillary damage and myocardial impairment, possibly preceding both renal dysfunction and cerebrovascular involvement.
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Affiliation(s)
- Gilda Cennamo
- Eye Clinic, Public Health Department, University of Naples “Federico II”, 80131 Naples, Italy
- Correspondence:
| | - Daniela Montorio
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples “Federico II”, 80131 Naples, Italy;
| | - Ciro Santoro
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Letizia Spinelli
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Teodolinda Di Risi
- CEINGE—Advanced Biotechnologies, 80145 Naples, Italy;
- Department of Public Medicine, University Federico II, 80131 Naples, Italy; (E.R.); (A.P.)
| | - Eleonora Riccio
- Department of Public Medicine, University Federico II, 80131 Naples, Italy; (E.R.); (A.P.)
| | - Camilla Russo
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
| | - Roberta Esposito
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, Federico II University Hospital, 80131 Naples, Italy; (C.S.); (S.C.); (L.S.); (C.R.); (G.P.); (R.E.); (M.I.)
| | - Antonio Pisani
- Department of Public Medicine, University Federico II, 80131 Naples, Italy; (E.R.); (A.P.)
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