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Caporale AS, Chiarelli AM, Biondetti E, Villani A, Lipp I, Di Censo D, Tomassini V, Wise RG. Changes of brain parenchyma free water fraction reflect tissue damage and impaired processing speed in multiple sclerosis. Hum Brain Mapp 2024; 45:e26761. [PMID: 38895882 PMCID: PMC11187860 DOI: 10.1002/hbm.26761] [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: 05/13/2024] [Accepted: 06/02/2024] [Indexed: 06/21/2024] Open
Abstract
Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm2, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.
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Affiliation(s)
- Alessandra Stella Caporale
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Antonio Maria Chiarelli
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Alessandro Villani
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Ilona Lipp
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Davide Di Censo
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Valentina Tomassini
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- MS Centre, Department of Clinical Neurology‘SS. Annunziata’ University HospitalChietiItaly
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Richard Geoffrey Wise
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
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Zivadinov R, Pei J, Clayton D, Goldman DE, Winger RC, Cabatingan MS, Dwyer MG, Bergsland N. Evolution of atrophied T2 lesion volume in primary-progressive multiple sclerosis: results from the phase 3 ORATORIO study. J Neurol Neurosurg Psychiatry 2024; 95:536-543. [PMID: 38071574 DOI: 10.1136/jnnp-2023-332573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/20/2023] [Indexed: 12/22/2023]
Abstract
BACKGROUND Atrophied T2-lesion volume (aT2-LV) is an exploratory imaging marker in multiple sclerosis (MS) reflecting the volume of lesions subsumed into cerebrospinal fluid (CSF). OBJECTIVE To investigate the effect of ocrelizumab (OCR) versus placebo (PBO) over 120 weeks on the accumulation of aT2-LV in a double-blind placebo-controlled (DBP) phase 3, primary-progressive (PP) MS study (ORATORIO; NCT01194570). METHODS This post-hoc, MRI-blinded analysis evaluated 732 PPMS randomised to OCR (488) or PBO (244). Atrophied T2-LV was calculated by overlaying baseline T2-lesion masks on follow-up CSF maps. Clinical data from DBP and open-label extension (OLE) periods were available. Treatment effect was evaluated by a mixed-effect model with repeated measures, while logistic regression explored the association of aT2-LV at week 120 and clinical outcomes in the OLE period. RESULTS OCR treatment significantly reduced accumulation of aT2-LV compared with PBO (319.4 mm3 vs 366.1 mm3, p=0.015) at 120 weeks. OCR showed superiority over PBO in reducing aT2-LV in patients who developed confirmed disability progression (CDP) during the DBP period at 12 (CDP12) and 24 (CDP24) weeks for the composite of Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test and Timed 25-Foot Walk test. Accumulation of aT2-LV at week 120 was related to CDP12-EDSS (p=0.018) and CDP24-EDSS (p=0.022) in the OLE for the patients who were treated by PBO in the DBP only. CONCLUSIONS OCR showed a significant effect of reducing the accumulation of aT2-LV in PPMS in the DBP period and was related to CDP-EDSS in OLE only in the PBO arm.
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Affiliation(s)
- Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | | | | | | | | | | | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
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Riemer F, Skorve E, Pasternak O, Zaccagna F, Lundervold AJ, Torkildsen Ø, Myhr KM, Grüner R. Microstructural changes precede depression in patients with relapsing-remitting Multiple Sclerosis. COMMUNICATIONS MEDICINE 2023; 3:90. [PMID: 37349545 DOI: 10.1038/s43856-023-00319-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Multiple Sclerosis lesions in the brain and spinal cord can lead to different symptoms, including cognitive and mood changes. In this study we explore the temporal relationship between early microstructural changes in subcortical volumes and cognitive and emotional function in a longitudinal cohort study of patients with relapsing-remitting Multiple Sclerosis. METHODS In vivo imaging in forty-six patients with relapsing-remitting Multiple Sclerosis was performed annually over 3 years magnetic resonance imaging. Microstructural changes were estimated in subcortical structures using the free water fraction, a diffusion-based MRI metric. In parallel, patients were assessed with the Hospital Anxiety and Depression Scale amongst other tests. Predictive structural equation modeling was set up to further explore the relationship between imaging and the assessment scores. In a general linear model analysis, the cohort was split into patients with higher and lower depression scores. RESULTS Nearly all subcortical diffusion microstructure estimates at the baseline visit correlate with the depression score at the 2 years follow-up. The predictive nature of baseline free water estimates and depression subscores after 2 years are confirmed in the predictive structural equation modeling analysis with the thalamus showing the greatest effect size. The general linear model analysis shows patterns of MRI free water differences in the thalamus and amygdala/hippocampus area between participants with high and low depression score. CONCLUSIONS Our data suggests a relationship between higher levels of free-water in the subcortical structures in an early stage of Multiple Sclerosis and depression symptoms at a later stage of the disease.
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Affiliation(s)
- Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, 5021, Bergen, Norway.
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, 5021, Bergen, Norway.
| | - Ellen Skorve
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, 5021, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, 5020, Bergen, Norway
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02215, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02215, USA
| | - Fulvio Zaccagna
- Department of Imaging, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, CB2 0QQ, Cambridge, United Kingdom
- Investigative Medicine Division, Radcliffe Department of Medicine, University of Oxford, OX3 9DU, Oxford, United Kingdom
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, 5020, Bergen, Norway
| | - Øivind Torkildsen
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, 5021, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, 5020, Bergen, Norway
| | - Kjell-Morten Myhr
- Neuro-SysMed, Department of Neurology, Haukeland University Hospital, 5021, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, 5020, Bergen, Norway
| | - Renate Grüner
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, 5021, Bergen, Norway
- Department of Physics and Technology, University of Bergen, 5007, Bergen, Norway
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