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Naughton P, Enright F, Lucey B. Infectious mononucleosis: new concepts in clinical presentation, epidemiology, and host response. Curr Opin Infect Dis 2024; 37:157-163. [PMID: 38529804 DOI: 10.1097/qco.0000000000001012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
PURPOSE OF REVIEW Infectious mononucleosis (IM) is an infectious disease that presents clinically in only a small percentage of individuals despite almost universal infection with the causative agent. Here, we review the latest concepts in the clinical presentation, epidemiology, and host response of this disease. RECENT FINDINGS Several recently published papers/reviews describe IM as a condition caused by one of several etiologic agents including, cytomegalovirus (HHV-5), Roseola virus (HHV-6) and Toxoplasmosis amongst others; this review focuses on IM as solely caused by the human herpes virus 4 (HHV-4). Since the initial discovery of the virus in the 1960s and its subsequent discovery as the primary etiologic agent for IM it has been associated with several human cancers and autoimmune disorders. Recent published findings show a correlation between HHV-4 and the autoimmune disorder, multiple sclerosis (MS), suggesting earlier IM could possibly act as a causative factor. Considering the important links being made with IM to so many cancers and autoimmune disorders it is surprising that a standard investigative procedure has yet to be determined for this disease. A standard approach to the investigation of IM would ensure more cases are diagnosed, particularly atypical cases, this would benefit epidemiological studies, and more immediately help practitioners distinguish viral from bacterial throat infections, enabling them to treat accordingly. SUMMARY The understanding of the latest concepts in clinical presentation, epidemiology and host response to IM would benefit greatly from the introduction of a standard procedure for its investigation and diagnosis.
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Affiliation(s)
- Patrick Naughton
- Department of Biological Sciences, Munster Technological University, Rossa Avenue, Bishopstown
- Department of Haematology
| | - Frances Enright
- Department of Paediatrics, Mercy University Hospital, Grenville Place, Cork, Ireland
| | - Brigid Lucey
- Department of Biological Sciences, Munster Technological University, Rossa Avenue, Bishopstown
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Faustino R, Lopes C, Jantarada A, Mendonça A, Raposo R, Ferrão C, Freitas J, Mateus C, Pinto A, Almeida E, Gomes N, Marques L, Palavra F. Neuroimaging characterization of multiple sclerosis lesions in pediatric patients: an exploratory radiomics approach. Front Neurosci 2024; 18:1294574. [PMID: 38370435 PMCID: PMC10869542 DOI: 10.3389/fnins.2024.1294574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/15/2024] [Indexed: 02/20/2024] Open
Abstract
Introduction Multiple sclerosis (MS), a chronic inflammatory immune-mediated disease of the central nervous system (CNS), is a common condition in young adults, but it can also affect children. The aim of this study was to construct radiomic models of lesions based on magnetic resonance imaging (MRI, T2-weighted-Fluid-Attenuated Inversion Recovery), to understand the correlation between extracted radiomic features, brain and lesion volumetry, demographic, clinical and laboratorial data. Methods The neuroimaging data extracted from eleven scans of pediatric MS patients were analyzed. A total of 60 radiomic features based on MR T2-FLAIR images were extracted and used to calculate gray level co-occurrence matrix (GLCM). The principal component analysis and ROC analysis were performed to select the radiomic features, respectively. The realized classification task by the logistic regression models was performed according to these radiomic features. Results Ten most relevant features were selected from data extracted. The logistic regression applied to T2-FLAIR radiomic features revealed significant predictor for multiple sclerosis (MS) lesion detection. Only the variable "contrast" was statistically significant, indicating that only this variable played a significant role in the model. This approach enhances the classification of lesions from normal tissue. Discussion and conclusion Our exploratory results suggest that the radiomic models based on MR imaging (T2-FLAIR) may have a potential contribution to characterization of brain tissues and classification of lesions in pediatric MS.
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Affiliation(s)
- Ricardo Faustino
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
- Faculty of Science, Institute of Biophysics and Biomedical Engineering, University of Lisbon, Lisbon, Portugal
- Biomedical Research Group, Faculty of Engineering, Faculty of Veterinary Medicine NICiTeS, Lusófona University, Lisbon, Portugal
| | - Cristina Lopes
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Afonso Jantarada
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Ana Mendonça
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Rafael Raposo
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Cristina Ferrão
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Joana Freitas
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Constança Mateus
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Ana Pinto
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Ellen Almeida
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Nuno Gomes
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Liliana Marques
- Neuroimaging and Biomedicine Research Group, Medical Imaging and Radiotherapy Research Unit, CrossI&D: Lisbon Research Center, Portuguese Red Cross Higher Health School (ESSCVP), Lisbon, Portugal
| | - Filipe Palavra
- Centre for Child Development – Neuropediatrics Unit, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Laboratory of Pharmacology and Experimental Therapeutics, Faculty of Medicine, Coimbra Institute for Clinical and Biomedical Research, University of Coimbra, Coimbra, Portugal
- Clinical Academic Center of Coimbra, Coimbra, Portugal
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Sacco S, Virupakshaiah A, Papinutto N, Schoeps VA, Akula A, Zhao H, Arona J, Stern WA, Chong J, Hart J, Zamvil SS, Sati P, Henry RG, Waubant E. Susceptibility-based imaging aids accurate distinction of pediatric-onset MS from myelin oligodendrocyte glycoprotein antibody-associated disease. Mult Scler 2023; 29:1736-1747. [PMID: 37897254 PMCID: PMC10687802 DOI: 10.1177/13524585231204414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/07/2023] [Accepted: 09/13/2023] [Indexed: 10/30/2023]
Abstract
BACKGROUND Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) and pediatric-onset multiple sclerosis (POMS) share clinical and magnetic resonance imaging (MRI) features but differ in prognosis and management. Early POMS diagnosis is essential to avoid disability accumulation. Central vein sign (CVS), paramagnetic rim lesions (PRLs), and central core lesions (CCLs) are susceptibility-based imaging (SbI)-related signs understudied in pediatric populations that may help discerning POMS from MOGAD. METHODS T2-FLAIR and SbI (three-dimensional echoplanar imaging (3D-EPI)/susceptibility-weighted imaging (SWI) or similar) were acquired on 1.5T/3T scanners. Two readers assessed CVS-positive rate (%CVS+), and their average score was used to build a receiver operator curve (ROC) assessing the ability to discriminate disease type. PRLs and CCLs were identified using a consensual approach. RESULTS The %CVS+ distinguished 26 POMS cases (mean age 13.7 years, 63% females, median EDSS 1.5) from 14 MOGAD cases (10.8 years, 35% females, EDSS 1.0) with ROC = 1, p < 0.0001, (cutoff 41%). PRLs were only detectable in POMS participants (mean 2.1±2.3, range 1-10), discriminating the two conditions with a sensitivity of 69% and a specificity of 100%. CCLs were more sensitive (81%) but less specific (71.43%). CONCLUSION The %CVS+ and PRLs are highly specific markers of POMS. After proper validation on larger multicenter cohorts, consideration should be given to including such imaging markers for diagnosing POMS at disease onset.
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Affiliation(s)
- Simone Sacco
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Akash Virupakshaiah
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Nico Papinutto
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Vinicius A Schoeps
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Amit Akula
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Haojun Zhao
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Jennifer Arona
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - William A Stern
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Janet Chong
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Janace Hart
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Scott S Zamvil
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Roland G Henry
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Emmanuelle Waubant
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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Papetti L, Panella E, Monte G, Ferilli MAN, Tarantino S, Checchi MP, Valeriani M. Pediatric Onset Multiple Sclerosis and Obesity: Defining the Silhouette of Disease Features in Overweight Patients. Nutrients 2023; 15:4880. [PMID: 38068737 PMCID: PMC10707944 DOI: 10.3390/nu15234880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/13/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
Obesity has been suggested as an environmental risk factor for multiple sclerosis (MS) and may negatively effect the progression of the disease. The aim of this study is to determine any correlation between overweight/obesity and the clinical and neuroradiological features at the onset of pediatric onset multiple sclerosis (POMS). Were included patients referred to the POMS Unit of the Bambino Gesù Children's Hospital between June 2012 and June 2021. The diagnosis of MS with an onset of less than 18 years was required. For all included subjects, we considered for the analysis the following data at the onset of symptoms: general data (age, sex, functional system compromised by neurological signs, weight and height), brain and spinal magnetic resonance imaging (MRI), cerebrospinal fluid exams. We identified 55 pediatric cases of POMS and divided them into two groups according to the body mass index (BMI): 60% were healthy weight (HW) and 40% were overweight/obese (OW/O). OW/O patients experienced a two-year age difference in disease onset compared to the HW patients (12.7 ± 3.8 years vs. 14.6 ± 4.1 years; p < 0.05). Onset of polyfocal symptoms was seen more frequently in OW/O patients than in HW (72.7% vs. 21.2%; p < 0.05). The pyramidal functions were involved more frequently in the OW/O group than in the HW group (50% vs. 25%; p < 0.005). Black holes were detected more frequently in OW/O patients in onset MRI scans compared to the HW group (50% vs. 15.5%; p < 0.05). Our findings suggest that being overweight/obese affects the risk of developing MS at an earlier age and is associated with an unfavorable clinical-radiological features at onset. Weight control can be considered as a preventive/therapeutic treatment.
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Affiliation(s)
- Laura Papetti
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
| | - Elena Panella
- Child Neurology and Psychiatry Unit, Systems Medicine Department, Hospital of Rome, Tor Vergata University, 00133 Rome, Italy;
| | - Gabriele Monte
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
| | - Michela Ada Noris Ferilli
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
| | - Samuela Tarantino
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
| | - Martina Proietti Checchi
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
| | - Massimiliano Valeriani
- Developmental Neurology Unit, Bambino Gesù Children’s Hospital, IRCCS, 00165 Rome, Italy; (G.M.); (M.A.N.F.); (S.T.); (M.P.C.); (M.V.)
- Center for Sensory Motor Interaction, Aalborg University, DK-9220 Aalborg, Denmark
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