Brain atrophy in multiple sclerosis: therapeutic, cognitive and clinical impact

Rojas, Juan Ignacio; Patrucco, Liliana; Miguez, Jimena; Cristiano, Edgardo

doi:10.1590/0004-282X20160015

Juan Ignacio Rojas

Hospital Italiano Buenos Aires, Centro de Esclerosis Múltiple de Buenos Aires (CEMBA), Buenos Aires, Argentina.

Liliana Patrucco

Hospital Italiano Buenos Aires, Centro de Esclerosis Múltiple de Buenos Aires (CEMBA), Buenos Aires, Argentina.

Jimena Miguez

Hospital Italiano Buenos Aires, Centro de Esclerosis Múltiple de Buenos Aires (CEMBA), Buenos Aires, Argentina.

Edgardo Cristiano

Hospital Italiano Buenos Aires, Centro de Esclerosis Múltiple de Buenos Aires (CEMBA), Buenos Aires, Argentina.

Correspondence
: Juan Ignacio Rojas;Center of multiple sclerosis of Buenos Aires (CEMBA), Italian Hospital of Buenos Aires; Gascón 450 C1181ACH Buenos Aires, Argentina; E-mail:juan.rojas@hospitalitaliano.org.ar

Conflicts of Interest: Juan Ignacio Rojas has received honoraria from Novartis as a scientific advisor. He has received travel grants and attended courses and conferences on behalf of Merck-Serono Argentina, Novartis Argentina.

Liliana Patrucco has received honoraria for scientific and research grants from Teva Tuteur, Merck Serono, Biogen Idec and Bayer Schering.

J. Miguez declares no conflict of interest.

Edgardo Cristiano has received fees for consultations as a scientific advisory board member and for travel to meetings, conferences and clinical trials of the following companies: Avanir, Bayer, Biogen, Merck, Novartis and Teva.

Technique	Degree of automation	Characteristics	Limitations
BSI	Semi-automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissue
www.sourceforge.net/projects/bsintegral/	Semi-automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissue
FIRST	Automated	Volumetry and analysis of deep gray matter	Analysis in a certain time point
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/	Automated	Volumetry and analysis of deep gray matter	Analysis in a certain time point
FreeSurfer	Automated or manual	Volumetry of deep gray matter; cortical thickness; simultaneous analysis in multiple time points	Prolonged calculation time needed
http://freesurfer.net/	Automated or manual		Prolonged calculation time needed
Nifty-Seg	Automated	Measures cortical thickness	Analysis in a certain time point
http://cmic.cs.ucl.ac.uk/home/software/	Automated	Measures cortical thickness	Analysis in a certain time point
SepINRIA	Automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissues
http://www-sop.inria.fr/asclepios/software/SepINRIA/	Automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissues
SIENA	Automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissues
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/	Automated	Measures changes in brain volume using pairs of images	Does not distinguish between brain tissues
SIENA-R	Automated	Analysis of brain focal atrophy in groups of patients using pairs of images	Does not distinguish between brain tissues
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/	Automated		Does not distinguish between brain tissues
SPM-Longitudinal VBM	Automated	Analysis of brain focal atrophy in groups of patients using pairs of images	Can only be applied in a group
www.fil.ion.ucl.ac.uk/spm/	Automated		Can only be applied in a group
TOADS-CRUISE	Automated	Measurement of cortical thickness changes	-
www.nitrc.org/projects/toads-cruise/	Automated	Measurement of cortical thickness changes	-

Author	Aim of the study	N patients	Result variable	Brain atrophy measurement (software used)	Comment
Jacobsen et al.²³	Assess atrophy as marker of progression of physical disability in 5-10 year follow up	81 with MS	Disease progression measured by EDSS	Longitudinal PBVC and tissue specific transversal volumes changes (SIENA, SIENAX y FIRST)	Patients with disability progression have more putaminal and cortical brain atrophy.
Hofstetter et al.²⁴	Assess gray matter changes as a marker of disability progression.	239 with MS	EDSS progression and MSFC worsening	Longitudinal changes in gray matter (VBM SPM5)	Physical disability was associated with greater gray matter atrophy.
Pérez-Miralles et al.⁵	Evaluate brain atrophy as prognostic factor in CIS	176 with CIS	MS conversion in patients with CIS	Changes in PBVC (SIENA)	The decrease in global brain volume foresaw MS conversion in patients with CIS
Zivadinov et al.²⁵	Assess atrophy of the thalamus as prognostic factor in CIS	216 with CIS	Conversion to MS in patients with CIS	PBVC and subcortical structures changes (SIENA y FIRST)	Atrophy of the thalamus and of global brain structures was associated with an increase in the risk of conversion to MS in patients with CIS
Popescu et al.²⁶	Evaluate whether brain atrophy predicts physical disability in a 10 year follow up period	261 with MS	Disability progression quantified by EDSS	PBVC longitudinal changes and transversal measurements (SIENA/SIENAX)	Brain atrophy might play a significant role in predicting long term disability in patients with MS
Rojas et al.²⁷	Assess if brain atrophy predicts physical disability in a 7 year follow up period.	26 with RRMS	Physical disability progression measured by EDSS	PBVC longitudinal changes (SIENA)	Greater brain atrophy during the early stages of the disease was associated with greater physical disability during follow up
Di Filippo et al.¹⁸	Evaluate if brain atrophy during the first year of CIS predicted the clinical status at 6 year follow up	99 with CIS	Physical disability progression measured by EDSS and MS conversion	Longitudinal changes in PBVC (SIENA)	Brain atrophy was associated with MS conversion in patients with CIS, and not with physical disability during follow up.
Lukas et al.²⁸	Assess the predictive value of central atrophy in relation to the risk of physical impairment in early stages of the disease	54 with MS	Physical disability progression measured by EDSS	PBVC and PVVC longitudinal changes (SIENA)	Greater PVVC reduction was the physical disability predictor factor in the mean term
Horakova et al.²⁹	Evaluate the predictive value of gray and white matter atrophy in physical disability	181 with RRMS	Physical disability progression measured by EDSS	Longitudinal and transversal PBVC changes (SIENA y SIENAX)	Decrease in total brain and gray matter volume was associated with greater physical deterioration
Fisher et al.³⁰	Assess the impact of gray matter atrophy in physical disability	70 MS	Disability progression measured by EDSS	Measurement of segmental volumes (BPF ad. Hoc software Cleveland Clinic)	Gray matter atrophy related with more physical impairment during follow up.
Fisniku et al.²¹	Correlation between brain atrophy and physical disability	73 with CIS followed for 20 years	Physical disability measured by EDSS	Segmental volumes measurements (SIENAX y VBM-SPM2)	Gray matter atrophy correlated with more physical disability in a 20 year follow up.
Jasperse et al.³¹	Evaluate the correlation between brain volume changes and physical and cognitive disability	79 with MS	Physical disability measured by EDSS, changes in MSFC	Regional changes in brain volume and PBVC (SIENA)	Central atrophy implied more physical disability, whereas involvement of complex functions correlated with central and peripheral atrophy.
Charil et al.³²	Cortical atrophy relates to physical disability progression	425 with MS	Physical disability progression measured by EDSS	Segmental cortical atrophy (INSECT software)	Atrophy of interconnected areas of the brain might be associated with motor disability in involved patients.
Turner et al.³³	Assess the correlation between changes in brain volume and physical disability after 4 years.	38 with MS	Physical disability progression measured by EDSS	Changes in PBVC and in ventricular volume	More significant brain atrophy during follow up correlated with more physical disability.
Bakshi et al.³⁴	Evaluate the correlation of changes in brain volume with physical disability	149 with MS	Physical disability progression measured EDSS	Regional atrophy (BPF).	Brain atrophy related to physical worsening in patients with severe involvement.

Author	Aim of the study	N patients with RMMS	Result variable	Brain atrophy measurement (software used)	Comment
Cruz Gómez et al.³⁸	Correlation between brain atrophy and fatigue	60	Fatigue measured by fatigue severity scale	Segmental atrophy by VBM-SPM8	In patients with fatigue there was a reduction in segmentary gray and white matter volume when compared to controls.
Amato et al.³⁹	Evaluate the relationship between cognitive reserve and brain atrophy in patients with RRMS	52	Cognitive reserve was assessed through a score that included education, IQ and pre morbid activities	Segmental brain volumes and longitudinal PBVC changes (SIENAX and SIENA)	The cognitive reserve might compensate structural damage, however, with damage and atrophy progression, this compensation is lost.
Batista et al.⁴⁰	Determine if atrophy of the thalamus and basal ganglia play a role in the speed to process information in RRMS (SPI)	86	Complete neuropsychologic tests, PASAT and SDMT.	Segmentary subcortical subglobal volumes (SIENAX and FIRST)	Information processing alterations was related to greater atrophy of subcortical structures that include the thalamus and the caudate.
Calabrese et al.⁴¹	Evaluate if atrophy of cortical and deep gray matter structures relates to fatigue in patients with RRMS	152	Fatigue measured by the fatigue impact scale	Segmental subcortical volumes (FreeSurfer)	Segmental atrophies were related to greater fatigue in RRMS.
Pellicano et al.⁴²	Assess the correlation between cortical and subcortical regional atrophy in RRMS.	24	Fatige measured by the fatigue impact scale	Cortical and subcortical segmental brain atrophy (FreeSurfer)	Parietal cortex atrophy was significantly related to fatigue in patients with RRMS
Sumowski et al.⁴³	Evaluate the effect of brain atrophy on the cognitive reserve	38	Information processing	Third ventricle enlargement (manual processing)	Brain atrophy showed negative effects on information processing that was partially attenuated by the cognitive reserve.
Mineev et al.⁴⁴	Assess correlation between cognitive deterioration and brain atrophy	65	Extended neuropsychologic assessment	Manually measured brain volumes	Greater brain atrophy correlated with greater cognitive involvement in patients with RRMS
Sanchez et al.⁴⁵	Evaluate the correlation between brain atrophy and cognitive deterioration in RRMS	52	Extended neuropsychologic assessment.	Subcortical global and segmental atrophy (manual processing of the bicaudate space and of the third ventricle diameter)	Central ventricle atrophy was the best predictor for global cognitive deterioration in this group of patients with RRMS.
Houtchens et al.⁴⁶	Assess if thalamic atrophy correlates with cognitive deterioration in RRMS	79	Extended neuropsychologic assessment.	BPF and subcortical brain volumes using JIM software	Thalamic atrophy might be a sensitive biomarker of neurodegeneration and cognitive impact
Tekok-Kilic et al.⁴⁷	Evaluate the correlation between gray matter atrophy and cognitive involvement in RRMS	59	Extended neuropsychologic assessment.	Brain segmental volumetry (SABRE software)	Thalamic atrophy might be a sensitive biomarker of neurodegeneration and cognitive impact
Tedeschi et al.⁴⁸	Assess the correlation of fatigue with white and gray matter atrophy	222	Fatige measured by the fatigue impact scale	Brain total and segmental volumes	Greater fatigue was observed with greater brain atrophy.
Sanfilipo et al.⁴⁹	Evaluate correlation of gray and white matter atrophy with cognitive deterioration in RRMS	40	Extended neuropsychologic assessment	Cortical and subcortical brain total and segmental volumes (SPM99)	Gray and white matter atrophy contribute independently to cognitive deterioration in RRMS
Lazeron et al.⁵⁰	Assess the correlation between brain atrophy and cognitive deterioration in RRMS	82	Rao short battery tests	Segmental and total brain volume (BPF local software)	Cognitive deterioration in MS depends moderately on brain structural damage.
Edwards et al.⁵¹	Evaluate the association between cognitive deterioration and supra – tentorial brain atrophy.	40	Extended neuropsychologic assessment	Segmental and total brain volume (BPF)	White matter atrophy correlated with worse cognitive performance, probably reflecting the effect of axonal subcortical damage and myelin loss.
Zivadinov et al.⁵²	Evaluate if cognitive deterioration in early stages of MS correlates with brain volume loss	53 in early disease stages	Extended neuropsychologic assessment	Total brain volume (semiautomatic local program)	In early stages of the disease, cognitive deterioration correlated signifcantly with total brain volume loss probably due to axonal loss.

Year	Trial	Control arm	Treatment arm	N	Brain volumen measurement	Effect of atrophy *
1999	MSCRG⁶¹	Placebo	IFNb-1ª 6 MIU	301	BPF	0.50
2006	AFFIRM⁶²	Placebo	Natalizumab	942	BPF	0.56
2006	SENTINEL⁶³	IFNb-1ª 30 Mcg	IFNbeta 1-a 30 mcg + natalizumab 300 mg	1171	BPF	0.77
2008	REGARD⁶⁴	GA	IFNbeta-1a-44 mcg	764	SIENA	1.28
2009	BEYOND⁶⁵	GA	IFNbeta-1a-250	1347	SIENA	0.90
2009	BEYOND⁶⁵	GA	IFNbeta-1a-500	1345	SIENA	0.80
2010	FREEDOMS⁵⁸	Placebo	FTY 0.5 mg	843	SIENA	0.63
2010	FREEDOMS⁵⁸	Placebo	FTY 1.25 mg	847	SIENA	0.55
2010	CLARITY⁶⁶	Placebo	Cladribine 3.5 mg	870	SIENA	0.81
2010	CLARITY⁶⁶	Placebo	Cladribine 5.25 mg	893	SIENA	0.81
2011	TEMSO⁵⁵	Placebo	Teriflunomide 7 mg	728	BPF	1.0
2011	TEMSO⁵⁵	Placebo	Teriflunomide 14 mg	721	BPF	1.0
2012	DEFINE⁵⁶	Placebo	BG-12 240 mg t.i.d	818	SIENA	0.70
2012	DEFINE⁵⁶	Placebo	BG-12 240 mg 3 daily	824	SIENA	0.83
2012	CONFIRM⁵⁷	Placebo	BG-12 240 mg t.i.d	722	SIENA	0.94
			BG-12 240 mg 3 daily	708		0.97
			GA	713		0.84
2012	MSCARE-I⁶⁷	IFNbeta-1ª	Alemtuzumab	821	BPF	0.50
2012	MSCARE-II⁶⁸	IFNbeta-1ª	Alemtuzumab	1187	BPF	0.63
2012	FREEDOMS-II⁶⁹	placebo	FTY 0.5 mg	757	SIENA	0.70
2012	FREEDOMS-II⁶⁹	placebo	FTY 1.25 mg	757	SIENA	0.52

[1] Correspondence
: Juan Ignacio Rojas;Center of multiple sclerosis of Buenos Aires (CEMBA), Italian Hospital of Buenos Aires; Gascón 450 C1181ACH Buenos Aires, Argentina; E-mail:juan.rojas@hospitalitaliano.org.ar

Brasil

Brasil

Brain atrophy in multiple sclerosis: therapeutic, cognitive and clinical impact

Atrofia cerebral en esclerosis múltiple: impacto clínico, cognitivo y terapéutico

ABSTRACT