546791
research-article2014
MSJ0010.1177/1352458514546791Multiple Sclerosis JournalM Pardini, L Bonzano
MULTIPLE SCLEROSIS MSJ JOURNAL
Research Paper
Cingulum bundle alterations underlie subjective fatigue in multiple sclerosis Matteo Pardini, Laura Bonzano, Maurizio Bergamino, Giulia Bommarito, Paola Feraco, Abitha Murugavel, Marco Bove, Giampaolo Brichetto, Antonio Uccelli, Gianluigi Mancardi and Luca Roccatagliata
Abstract Objective: To evaluate the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework. Methods: Seventy seven subjects with relapsing–remitting MS were recruited in the study and underwent subjective fatigue evaluations and a diffusion MRI scan. Firstly, local white matter Fractional Anisotropy values were correlated with subjective fatigue scores using a voxel-wise approach. The long-range loss of connectivity due to structural damage in the white matter voxels thus associated with subjective fatigue was then assessed using the Network Modification (NeMo) package. Results: A voxel-wise regression analysis with fatigue scores revealed a significant association between structural damage and fatigue levels in two discrete white matter clusters, both included in the left cingulate bundle. The connectivity analysis revealed that damage in these clusters was associated with loss of structural connectivity in the anterior and medial cingulate cortices, dorsolateral prefrontal areas and in the left caudate. Discussion: Our data point to the cingulum bundle and its projections as the key network involved in subjective fatigue perception in MS. More generally, these results suggest the potential of the connectionist framework to generate coherent models of the neural basis of complex symptomatology in MS.
Keywords: White matter, diffusion tensor imaging, fatigue, cingulum bundle Date received: 19 June 2014; revised: 16 July 2014; accepted: 16 July 2014
Introduction Subjective fatigue is a pervasive sense of tiredness that significantly impacts everyday functioning and represents a frequent and disabling feature of multiple sclerosis (MS), reported by more than 80% of patients during the course of the disease.1 Despite its relevance, subjective fatigue remains to date a poorly understood phenomenon, thus hampering the possibilities to develop effective and personalized treatment strategies for this frequent symptom. Neuroimaging techniques have provided a number of significant but incomplete and partly contradictory characterizations of the neural substrate of MS-related fatigue, pointing toward diffuse damage (white matter lesion load, whole brain grey matter volume)2 and focal structural abnormalities (especially localized to
the prefrontal and deep gray matter structures and related tracts, posterior cortices, forceps minor, anterior capsule and callosal white matter)1,3–9 as the possible neural basis of fatigue in this patient population. While the significant differences in the anatomical localization of the putative key areas for MS-related fatigue in the aforementioned studies could be related to methodological differences in subject selection and data analysis, it is usually argued that the observed heterogeneity of the results is mainly due to the multifaceted nature of subjective fatigue and by the difficulty to assess a purely subjective symptom .1 Here, we propose that it is possible to reconcile the differences in the suggested neural basis of MS-related fatigue through a paradigm shift toward the connectionist model. According to the connectionist paradigm, cognitive symptomatology could derive from
Multiple Sclerosis Journal 2015, Vol. 21(4) 442–447 DOI: 10.1177/ 1352458514546791 © The Author(s), 2014. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Correspondence to: Luca Roccatagliata Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Largo Daneo 3, 16132 Genoa, Italy. lroccatagliata@neurologia. unige.it Matteo Pardini Laura Bonzano Maurizio Bergamino Giulia Bommarito Paola Feraco Abitha Murugavel Gianluigi Mancardi Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Italy/ Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Italy Marco Bove Section of Human Physiology and Centro Polifunzionale di Scienze Motorie, University of Genoa, Italy Giampaolo Brichetto Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy Antonio Uccelli University of Genoa, Italy Luca Roccatagliata Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa/San Martino University Hospital/ University of Genoa, Genoa, Italy
442 http://msj.sagepub.com
M Pardini, L Bonzano et al. disruption of the integrated workings of different brain areas.10 Indeed, inside this paradigm damage in different structures of the network could lead to similar clinical presentations. To this aim we decided to use a multi-step approach to analyse the relationship of white matter structural integrity/subjective fatigue levels in a large cohort of subjects with MS. Given our hypothesis of the potential of the connectionist approach to meaningfully integrate the different areas associated with fatigue in a single coherent network we firstly used a whole-brain analysis approach to identify all white matter clusters associated with fatigue, using a lenient statistical threshold to maximize the number of possible areas, and then combined an atlas-based approach with the analysis of the pattern of connectivity loss to identify the possible neural network associated with fatigue perception. Methods Subject selection Seventy seven patients (age: 40.8±10.0 years, disease duration: 9.4±8.4 years) with relapsing–remitting MS and mild-to-moderate disability (Expanded Disability Status Scale – EDSS score11 (2.0±1.2)) were included in this study. These patients were recruited consecutively among the subjects with MS presenting to the MS Clinic of the University of Genoa subjectively reporting fatigue as important symptom affecting their quality of life. Clinical relapses, changes in the EDSS score or corticosteroid use in the 6 months preceding the study were considered as exclusion criteria for this study. Moreover, patients with medical or psychiatric causes of fatigue including sleep and mood disorders or with a positive history for psychiatric, neurological or medical co-morbidities were not considered eligible for the study. The presence of current or past comorbidities was assessed by revision of the relevant medical charts and discussions with the treating physicians. Regarding the presence of psychiatric comorbidities all subjects were evaluated at enrollment by clinicians who were expert in the neuropsychiatric symptomatology in MS both with the clinical interview and using where appropriate psychometric instruments such as the Structured Clinical Interview for DSM-IV Axis I Disorders (http://www.scid4.org). Subjective fatigue evaluation All enrolled subjects completed the Modified Fatigue Impact Scale (MFIS),12 a 21-item structured selfreport questionnaire included in the Multiple Sclerosis Quality of Life Inventory (MSQLI).13 The MFIS is a
modified form of the Fatigue Impact Scale based on items derived from interviews with patients with MS concerning how fatigue impacts their lives, and it is focused on a quantitative evaluation of the effects of fatigue on everyday functioning. The MFIS total score range is 0 to 84, with higher scores representing higher levels of fatigue. MFIS values higher than 37 are thought to be associated with disabling levels of fatigue.12 MRI acquisition MRI was performed on a 1.5 Tesla scanner (Signa Excite; GE Healthcare, Milwaukee, WI, USA) with a standard transmit-receive head coil. Conventional MRI included: axial proton density (PD)/T2 (TR/TE/ Flip Angle = 2500 ms / 128 ms / 90, field of view = 25 × 25 cm, matrix = 256 × 256), coronal T1 3D SPoiled Gradient Recalled (SPGR) (TR/TE/Flip Angle = 22.0 ms / 7.0 ms / 20, field of view = 26 × 26 cm, matrix = 256 × 192). Diffusion Tensor Imaging (DTI) was performed by using single-shot spin-echo echo-planar imaging (TR/TE/Flip Angle = 14000 ms / 90 ms / 90, field of view = 24 × 24 cm, matrix = 128×128) with diffusion gradients applied in 15 non-collinear directions (b value = 1000 sec/mm2) and two images without diffusion gradients. Diffusion data pre-processing DTI data were processed using FDT included in FSL.14 Pre-processing steps included correction for eddy current distortions and motion artifacts. Fractional anisotropy (FA) parametric maps were obtained for all subjects and were then realigned into MNI common space, using the nonlinear registration tool IRKT included in the TBSS 15 pipeline and then smoothed with a 4-mm full-width at half-maximum (FWHM) isotropic Gaussian kernel. Given our focus on the role of major associative pathways in fatigue, we then masked each FA map with the smoothed white matter skeletonized template included in FSL. Lastly, we extracted whole brain skeletonized white matter mean FA values from all subjects. Skeletonized FA maps thus obtained were then analyzed in SPM 8 using a whole-brain voxel-wise analysis with global fatigue score as covariate. Voxel-wise analysis of diffusion data We considered as significant those voxels included in the smoothed white matter skeletonized mask which survived an uncorrected threshold of p
research-article2014
MSJ0010.1177/1352458514546791Multiple Sclerosis JournalM Pardini, L Bonzano
MULTIPLE SCLEROSIS MSJ JOURNAL
Research Paper
Cingulum bundle alterations underlie subjective fatigue in multiple sclerosis Matteo Pardini, Laura Bonzano, Maurizio Bergamino, Giulia Bommarito, Paola Feraco, Abitha Murugavel, Marco Bove, Giampaolo Brichetto, Antonio Uccelli, Gianluigi Mancardi and Luca Roccatagliata
Abstract Objective: To evaluate the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework. Methods: Seventy seven subjects with relapsing–remitting MS were recruited in the study and underwent subjective fatigue evaluations and a diffusion MRI scan. Firstly, local white matter Fractional Anisotropy values were correlated with subjective fatigue scores using a voxel-wise approach. The long-range loss of connectivity due to structural damage in the white matter voxels thus associated with subjective fatigue was then assessed using the Network Modification (NeMo) package. Results: A voxel-wise regression analysis with fatigue scores revealed a significant association between structural damage and fatigue levels in two discrete white matter clusters, both included in the left cingulate bundle. The connectivity analysis revealed that damage in these clusters was associated with loss of structural connectivity in the anterior and medial cingulate cortices, dorsolateral prefrontal areas and in the left caudate. Discussion: Our data point to the cingulum bundle and its projections as the key network involved in subjective fatigue perception in MS. More generally, these results suggest the potential of the connectionist framework to generate coherent models of the neural basis of complex symptomatology in MS.
Keywords: White matter, diffusion tensor imaging, fatigue, cingulum bundle Date received: 19 June 2014; revised: 16 July 2014; accepted: 16 July 2014
Introduction Subjective fatigue is a pervasive sense of tiredness that significantly impacts everyday functioning and represents a frequent and disabling feature of multiple sclerosis (MS), reported by more than 80% of patients during the course of the disease.1 Despite its relevance, subjective fatigue remains to date a poorly understood phenomenon, thus hampering the possibilities to develop effective and personalized treatment strategies for this frequent symptom. Neuroimaging techniques have provided a number of significant but incomplete and partly contradictory characterizations of the neural substrate of MS-related fatigue, pointing toward diffuse damage (white matter lesion load, whole brain grey matter volume)2 and focal structural abnormalities (especially localized to
the prefrontal and deep gray matter structures and related tracts, posterior cortices, forceps minor, anterior capsule and callosal white matter)1,3–9 as the possible neural basis of fatigue in this patient population. While the significant differences in the anatomical localization of the putative key areas for MS-related fatigue in the aforementioned studies could be related to methodological differences in subject selection and data analysis, it is usually argued that the observed heterogeneity of the results is mainly due to the multifaceted nature of subjective fatigue and by the difficulty to assess a purely subjective symptom .1 Here, we propose that it is possible to reconcile the differences in the suggested neural basis of MS-related fatigue through a paradigm shift toward the connectionist model. According to the connectionist paradigm, cognitive symptomatology could derive from
Multiple Sclerosis Journal 2015, Vol. 21(4) 442–447 DOI: 10.1177/ 1352458514546791 © The Author(s), 2014. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Correspondence to: Luca Roccatagliata Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Largo Daneo 3, 16132 Genoa, Italy. lroccatagliata@neurologia. unige.it Matteo Pardini Laura Bonzano Maurizio Bergamino Giulia Bommarito Paola Feraco Abitha Murugavel Gianluigi Mancardi Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Italy/ Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Italy Marco Bove Section of Human Physiology and Centro Polifunzionale di Scienze Motorie, University of Genoa, Italy Giampaolo Brichetto Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy Antonio Uccelli University of Genoa, Italy Luca Roccatagliata Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa/San Martino University Hospital/ University of Genoa, Genoa, Italy
442 http://msj.sagepub.com
M Pardini, L Bonzano et al. disruption of the integrated workings of different brain areas.10 Indeed, inside this paradigm damage in different structures of the network could lead to similar clinical presentations. To this aim we decided to use a multi-step approach to analyse the relationship of white matter structural integrity/subjective fatigue levels in a large cohort of subjects with MS. Given our hypothesis of the potential of the connectionist approach to meaningfully integrate the different areas associated with fatigue in a single coherent network we firstly used a whole-brain analysis approach to identify all white matter clusters associated with fatigue, using a lenient statistical threshold to maximize the number of possible areas, and then combined an atlas-based approach with the analysis of the pattern of connectivity loss to identify the possible neural network associated with fatigue perception. Methods Subject selection Seventy seven patients (age: 40.8±10.0 years, disease duration: 9.4±8.4 years) with relapsing–remitting MS and mild-to-moderate disability (Expanded Disability Status Scale – EDSS score11 (2.0±1.2)) were included in this study. These patients were recruited consecutively among the subjects with MS presenting to the MS Clinic of the University of Genoa subjectively reporting fatigue as important symptom affecting their quality of life. Clinical relapses, changes in the EDSS score or corticosteroid use in the 6 months preceding the study were considered as exclusion criteria for this study. Moreover, patients with medical or psychiatric causes of fatigue including sleep and mood disorders or with a positive history for psychiatric, neurological or medical co-morbidities were not considered eligible for the study. The presence of current or past comorbidities was assessed by revision of the relevant medical charts and discussions with the treating physicians. Regarding the presence of psychiatric comorbidities all subjects were evaluated at enrollment by clinicians who were expert in the neuropsychiatric symptomatology in MS both with the clinical interview and using where appropriate psychometric instruments such as the Structured Clinical Interview for DSM-IV Axis I Disorders (http://www.scid4.org). Subjective fatigue evaluation All enrolled subjects completed the Modified Fatigue Impact Scale (MFIS),12 a 21-item structured selfreport questionnaire included in the Multiple Sclerosis Quality of Life Inventory (MSQLI).13 The MFIS is a
modified form of the Fatigue Impact Scale based on items derived from interviews with patients with MS concerning how fatigue impacts their lives, and it is focused on a quantitative evaluation of the effects of fatigue on everyday functioning. The MFIS total score range is 0 to 84, with higher scores representing higher levels of fatigue. MFIS values higher than 37 are thought to be associated with disabling levels of fatigue.12 MRI acquisition MRI was performed on a 1.5 Tesla scanner (Signa Excite; GE Healthcare, Milwaukee, WI, USA) with a standard transmit-receive head coil. Conventional MRI included: axial proton density (PD)/T2 (TR/TE/ Flip Angle = 2500 ms / 128 ms / 90, field of view = 25 × 25 cm, matrix = 256 × 256), coronal T1 3D SPoiled Gradient Recalled (SPGR) (TR/TE/Flip Angle = 22.0 ms / 7.0 ms / 20, field of view = 26 × 26 cm, matrix = 256 × 192). Diffusion Tensor Imaging (DTI) was performed by using single-shot spin-echo echo-planar imaging (TR/TE/Flip Angle = 14000 ms / 90 ms / 90, field of view = 24 × 24 cm, matrix = 128×128) with diffusion gradients applied in 15 non-collinear directions (b value = 1000 sec/mm2) and two images without diffusion gradients. Diffusion data pre-processing DTI data were processed using FDT included in FSL.14 Pre-processing steps included correction for eddy current distortions and motion artifacts. Fractional anisotropy (FA) parametric maps were obtained for all subjects and were then realigned into MNI common space, using the nonlinear registration tool IRKT included in the TBSS 15 pipeline and then smoothed with a 4-mm full-width at half-maximum (FWHM) isotropic Gaussian kernel. Given our focus on the role of major associative pathways in fatigue, we then masked each FA map with the smoothed white matter skeletonized template included in FSL. Lastly, we extracted whole brain skeletonized white matter mean FA values from all subjects. Skeletonized FA maps thus obtained were then analyzed in SPM 8 using a whole-brain voxel-wise analysis with global fatigue score as covariate. Voxel-wise analysis of diffusion data We considered as significant those voxels included in the smoothed white matter skeletonized mask which survived an uncorrected threshold of p
