Intracortical lesions by 3T magnetic resonance imaging and correlation with cognitive impairment in...

Intracortical Lesions by 3T Magnetic Resonance Imaging andCorrelation with Cognitive Impairment in Multiple Sclerosis

Flavia Nelson, MD,Department of Neurology, University of Texas-Houston, Health Science Center, Houston, Texas,USA

Sushmita Datta, Ph.D,Department of Diagnostic and Interventional Imaging, University of Texas-Houston, HealthScience Center, Houston, Texas, USA

Nereyda Garcia, BS,Department of Neurology, University of Texas-Houston, Health Science Center, Houston, Texas,USA

Nigel L. Rozario, MS,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA

Francisco Perez, Ph.D,Department of Neurology, Baylor College of Medicine, Houston, Texas, USA

Gary Cutter, Ph.D,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA

Ponnada A. Narayana, Ph.D., M.Sc., andDepartment of Diagnostic and Interventional Imaging, University of Texas-Houston, HealthScience Center, Houston, Texas, USA

Jerry S. Wolinsky, MDDepartment of Neurology, University of Texas-Houston, Health Science Center, Houston, Texas,USA

AbstractBackground—Accurate classification of MS lesions in the brain cortex may be important inunderstanding their impact on cognitive impairment. Improved accuracy in identification/classification of cortical lesions was demonstrated in a study combining two MRI sequences:double inversion recovery (DIR) and T1-weighted phase-sensitive inversion recovery (PSIR).

Objective—To evaluate the role of intracortical lesions (IC) in MS related cognitive impairment(CI) and compare it to the role of mixed (MX), juxtacortical (JX), the sum of IC + MX and withtotal lesions as detected on DIR/PSIR images. Correlations between CI and brain atrophy, diseaseseverity and disease duration were also sought.

Methods—39 patients underwent extensive neuropsychological testing and were classified into:normal and impaired. Images were obtained on a 3T scanner and cortical lesions were assessedblind to the cognitive status of the subjects.

Results—238 cortical lesions were identified (130 IC, 108 MX) in 82% of the patients, 39 JXlesions were also identified. Correlations between CI and MX lesions alone (p=0.010) and with

Corresponding Author: Flavia Nelson, MD, Address: 6431 Fannin Street, MSB 7.220, Houston, Texas 77030, Telephone:(713)500-7058, Fax: (713)500-7040, Flavia.M.Nelson@uth.tmc.edu.

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Published in final edited form as:Mult Scler. 2011 September ; 17(9): 1122–1129. doi:10.1177/1352458511405561.

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the sum of IC + MX lesions (p=0.030) were found. A correlation between severity of CI andEDSS was also seen (p=0.009).

Conclusion—Cortical lesions play an important role in CI. However our results suggest thatlesions that remain contained within the cortical ribbon do not play a more important role thanones extending into the adjacent white matter; furthermore the size of the cortical lesion, and notthe tissue specific location, may better explain their correlation with CI.

Keywordscortical lesions; multiple sclerosis; cognitive impairment; brain atrophy

IntroductionCognitive impairment (CI) is prevalent among patients with multiple sclerosis (MS). Acontrolled long-term natural history study showed an increase in CI from 26 to 56% over aten-year interval and it also showed that nearly half of all MS patients will develop CIduring their lifetime [1], some early in the disease course [2]. The form or degree of CI doesnot correlate with the disease course [3]. CI is an important cause of disability in many MSpatients with minimal or no other physical impairment. Current diagnostic tools fordocumenting CI (neuropsychological testing) are limited in their availability, expensive andnot often included in insurance coverage. This prevents patients from being objectivelydiagnosed and treated with medication and behavior modification (cognitive rehabilitation,coping skills and counseling) that could potentially prolong their ability to maintainfinancial and social independence. The absence of documented cognitive abnormalities mayalso prevent them from qualifying for long term disability. Patients with mild CI are oftenable to work if adjustments are made. However, as the severity of CI increases they are oftenencouraged to quit, or terminated with no other option but to apply for long term disability.This has an important economic impact on both the individual and the health care system.Baseline testing on MS patients has shown deficits on tasks of verbal memory, abstractreasoning and linguistic processes and on tasks of attention and short term spatial memory[4]. Cross-sectional studies have also shown relative decline on tasks of recent memory,processing speed, attention, visual-spatial abilities, and executive functions which representworking memory[5].

Conventional and nonconventional MRI measures have been correlated with CI in MS.These include: whole brain atrophy [6–7], cortical volume [8], lesion load [9], and diffusionanisotropy [10]. Rao et al. examined a number of MRI variables including total lesion area,ventricular-brain ratio and size of the corpus callosum. They found total lesion area waspredictive of dysfunction in memory, abstract and conceptual reasoning, language andvisuospatial problem solving [4]. Another study found a correlation with lesion burden infrontal and non-frontal regions and attention, memory, planning, problem solving, andconceptual reasoning [11]. In a different study the MS functional composite (MSFC) scoredid not significantly correlate with T2 or T1 lesion load [12]. Volumes of white matter [13]and T2 hyperintense lesions in deep gray matter nuclei [14] also correlated with overallcognitive functioning. In a recent study of 550 mildly disabled MS patients tested at baseline(327 of whom underwent MRI assessments), CI (defined as impaired performance in ≥3cognitive tests) was present in approximately 20% of all patients. In the subgroup thatunderwent MRI, T2 and T1 lesion volumes were significantly higher in patients with CI thanthose without [15]. Although the above studies have provided important information on MRImeasures and correlation with CI, there is no consensus if these findings can or should beused as an MRI risk indicator of functional impairment.

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The suggested association between cortical/juxtacortical lesions and CI in MS has also beenexplored but is less than convincing. Lazeron et al, observed a correlation, albeit weak,between juxtacortical lesions on brain MRI and the Cognitive Impairment Index [16]. Charilet al, observed a correlation between CI and lesions at the GM-WM junction of associative,limbic and prefrontal cortices [17]. A recent study found that the impact of neocorticallesions on CI is not independent from white matter disease [18]. Correlations have also beenfound between specific gray matter volumes in the cerebral cortex and cognitive test results.Portaccio et al, found that neocortical volume loss was significantly associated with worseperformance on cognition measures over time; no such correlation was found between totalbrain or T2 lesion volumes [19].

Direct visualization of intracortical lesions is suboptimal on conventional MRI asdemonstrated by combined post-mortem MRI and histopathology studies [20–21], reflectinglimitations of imaging methods [22]. The sensitivity of detecting lesions present in thecortex was substantially improved by combining two novel pulse sequences; doubleinversion recovery (DIR) and T1-weighed phase sensitive inversion recovery (PSIR) [23].DIR imaging does not allow detection of all lesions potentially present in the cortex, but thissequence undoubtedly provides a more complete picture of the “cortical” disease burden inMS [23–27]. This picture is strengthened by the confirmation of lesion presence on the PSIRimages. When obtained using a 3T magnet, the superior GM/WM contrast and cleardelineation of lesion borders seen on PSIR also allows for a more accurate classification.Although 3D magnetization prepared rapid acquisition gradient echo (MPRAGE) has beenshown to be an excellent sequence that provides important qualitative details forclassification of cortical lesions, it does not seem to be the most sensitive for cortical lesiondetection. The high spatial resolution of this sequence is helpful to evaluate details (i.e.lesion borders) but when used for detection purposes only, lesion presence is less obviousthan on DIR/PSIR. The large number of slices also makes it visually difficult and extremelytime consuming for the evaluator [25]. DIR/PSIR remain the best combination for improveddetection and satisfactory classification of cortical gray matter lesions in MS at 3T and arepresently reasonably accessible by the MS scientific community [23–25]. (Figure 1)

In this study we proposed that intracortical lesions (IC) defined as total confinement withinthe cortical ribbon, might play a more important role in cognition when compared withmixed (MX), defined as present mostly in the cortex but with some subcortical extensionand juxtacortical (JX), mostly present in the subcortical region with clear extension into thecortex. We have used the advanced MR pulse sequences shown to increase lesion detectionand classification accuracy to examine this hypothesis.

Materials and MethodsForty patients recruited were evaluated for evidence of CI within the year prior to the MRIscan by a neuropsychologist with extensive experience in MS. The subjects were drawnfrom an existing database at Baylor Neuropsychologists, Department of Neurology, BaylorCollege of Medicine Houston, TX. Recruitment extended from 2005 to 2008. A full batteryof neuropsychological (NP) tests was performed in 40 MS patients (one later had to beexcluded due to poor MR image quality). The NP tests results were then correlated withlesion number independently by type (IC, MX and JX). We also evaluated the correlation ofCI with the sum of IC + MX which we called cortical lesions (CL). JX lesions were notconsidered to be “cortical” but their impact on cognition was also evaluated bothindependently and within the category total lesions (IC + MX + JX). Other correlationsincluded the number of lesions by type with individual neuropsychological test scores andcorrelations between CI and measures of brain atrophy using Normalized CSF (nCSF), theexpanded disability status scale (EDSS) and disease duration (DD).

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Neuropsychological assessmentA comprehensive battery of standardized psychological tests that evaluated a broad range ofneurocognitive functions was administered. This included (listed by cognitive domainsevaluated):

Memory Functions—Wechsler Memory Scale-R (WMS-R) and Rey Auditory VerbalLearning Test (RAVLT).

Intelligence and Cognitive Functions—Wechsler Adult Intelligence Scale III (WAIS-III).

Language Functions—Aphasia Screening Test and Controlled Oral Association(COWA).

Motor Functions—Finger Tapping Test; (FTT), Grooved Pegboard Test (GPV), andHand Dynamometer Gripped Strength Test (GPT).

Attention and Tracking Functions—Paced Auditory Serial Addition Test (PASAT),Stroop Neuropsychological Screening Test, and Trail Making Test.

Executive Functions—Wisconsin Card Sorting Test (WCST).

Emotional Functioning—Minnesota Multiphasic Personality Inventory

From the various standard scores obtained, the data was interpreted using the followingstandard scores of cognitive functions usually impacted in MS:

• WAIS-III – Working Memory Index and Processing Speed of Information Index.

• WMS – R – General Memory Index and Delayed Recall Index.

• WCST - % errors; 5 perseverative responses; % of perseverative errors; % of non-perseverative errors and % conceptual level responses.

• COWA

• GPT dominant and non-dominant hand performance.

• FTT dominant and non-dominant hand performance.

• MMPI-2 Depression Scale

• PASAT

The clinical interpretation of the neuropsychological data for each patient was based on anintegrated test pattern analysis approach that takes into account standard test scores for eachpatient accounting for their specific demographics and medical data. The results for eachpatient were assessed relying on normative data and standard scores that facilitate theidentification of patterns of scores consistent with deficits in test performance associatedwith brain dysfunction [28].

Impairment was defined as patterns of impairment in two or more tests in comparison withestablished normative data. Individual test results were classified as normal if the standardscore did not deviate from the normative data. Borderline impairment was classified asbelow 1 standard deviation (SD) from the normative data. Mild impairment was classified as1.5 SD below the normative data. Moderate impairment was classified as 2 SD below themean. Severe impairment was classified as 3 SD from the mean normative data. The specific

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classification of each patient was made by a board certified neuropsychologist withextensive experience in the evaluation of cognitive functions in patients with MS. Since CIin MS is generally not homogeneous and there is great variability from patient to patient, theneuropsychologist used his clinical judgment in classifying each patient following thecriteria established.

Inclusion/exclusion criteriaPatient eligibility was established based on NP test results and criteria as follows:

Inclusion criteria—1) clinically definite relapsing remitting (RR), secondary progressive(SP) or primary progressive (PP) MS by McDonald criteria [29], 2) NP evaluationperformed within one year from enrollment, 3) age 18 to 50 (to avoid confounding effects ofage related dementia), 4) EDSS score 6.5 or less, 5) brain MRI consistent with the clinicaldiagnosis of MS.

Exclusion Criteria—1) contraindications for MRI (pace makers, metal implants,claustrophobia etc.), 2) history of clinical relapse or a high dose steroid treatment in thethree months prior to study, 3) history of drug or alcohol abuse, 4) acute or uncontrolleddepression within three months from testing, and 5) history of cytotoxic orimmunosuppressive treatments.

Once eligibility was established, recruitment was done by telephone call or invitation letter.Eligible patients were referred for one imaging session. For quality assurance, patienteligibility (by inclusion/exclusion criteria and standard MRI findings) was confirmed priorto enrollment. Informed consent was obtained prior to imaging session. All personnel asidefrom the neuropsychologist were blind to the subject’s cognitive status. Theneuropsychologist was blind to the MRI findings. Each patient enrolled attended a two hoursession that included: 1) collection of demographics and disease history, 2) neurologicalexam, 3) EDSS score assessment, and 4) MRI of the brain without gadolinium.

MR ImagingEach patient underwent an MRI of the brain according to a standard protocol that includedthe optimized sequences DIR/PSIR [30, 31] for detection of CL. MRI scans were performedon a Philips 3T Intera scanner with a Quasar Plus gradient system (maximum gradientamplitude 80 mT/m, slew rate 200 T/m/s) and a six channel SENSE-compatible head coil.Following the tripilot scan for locating the brain region, images were acquired withparameters as listed in Table 1. The entire MRI protocol was completed in less than onehour.

Quantitative MRI AnalysisAll MRI analysis, including segmentation for tissue quantization was performed using thesoftware developed in-house [32]. In brief, all images acquired in different series (FLAIR,dual echo, T1-images etc.) were retrospectively aligned [33]. Images were stripped of theextrameningeal tissues [34], filtered using the anisotropic diffusion filter [35], corrected forthe bias field [36] and intensity normalized [37]. Segmentation of GM, WM, and lesionvolume were based on the dual echo and FLAIR, images using the hidden Markov randomfield – expectation maximization (HMRF-EM) algorithm and Parzen window classification[32]. Normalized CSF (nCSF) volume was used as the measure of whole brain atrophy [38].

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Lesion detection and classificationCL were identified on DIR and validated on PSIR as previously detailed [23]. Forclassification purposes an MRI specific lesion classification was created: lesions weredefined as (a) IC if total confinement within the cortical ribbon was seen, (b) MX if theywere present mostly in the cortex but with some (~25%) subcortical extension and (c) JX ifmostly present in the subcortical region with clear extension (~25%) into the cortex. Lesionclassification was done without knowledge of the neuropsychological test results (Figure 1).

Statistical AnalysesPoisson regression models were first used to evaluate for evidence of an association betweenCI and each different type of lesions. Negative Binomial regression was preferred as itexplained the variation in the number of lesions better than the Poisson model. Since therewere some patients with no lesions the Negative Binomial regression approach allowed foroutcomes (lesions) with a large number of zero counts and for adjustment of covariates.Given the small sample size of 39 patients, the CI categories (normal, borderline, mild,moderate and severe) were collapsed into two groups: normal and impaired.

In our first analysis the normal group included only normal subjects, while the subjects inthe borderline category were included in the impaired group. Each group was evaluated forcorrelations between each type of lesion individually (IC, MX, JX), with CL only (CL= IC +MX) and with total lesions (IC+MX+JX). A second analysis was done with the borderlinegroup classified as “normal” for comparison.

ResultsA total of 238 CL (130 IC, 108 MX) were visualized on DIR/PSIR in 82% of the evaluablepatients; 39 JX lesions were also identified. The proportion of patients with 0 lesions in allof the above categories was 20%. The MS patients were classified into four CI categories asfollows: 11 as normal, 9 as borderline, 11 as mild, 7 as moderate and 1 as severe. Totallesion number grouped by degree of impairment showed: normal 32, borderline 38, mild115, moderate 85 and severe 7 (Table 2).

Based on Negative Binomial regression, correlations between CI and MX, CL (IC + MX),and total lesions (IC + MX + JX) were all significant. There were no important associationsseen between IC or JX lesions and CI, independently as seen in table 3.

We also considered the fact that patients meeting criteria for the borderline category couldpotentially be misclassified as “impaired” when functionally they were closer to the“normal” group. Therefore, a second analysis was done this time classifying the borderlinepatients under the “normal” category. When the borderline cases were incorporated in thenormal group, as seen in the table below (Table 4), all correlations strengthened and weresimilar in significance to the first analysis.

Also found was a correlation between severity of CI and EDSS (p = 0.009), but nonebetween CI and DD or CI and nCSF (as a measure of brain atrophy) independently (Table5).On a different analysis of correlations between CI and each component of the NPevaluation a correlation was seen between number of MX and JX lesions and the PSIcomponent of the WAIS test (p = 0.039, p = 0.026). This test measures informationprocessing speed.

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DiscussionThis study compared the presence, number and type of cortical and JX lesions in MSsubjects with different degrees of CI to those MS subjects with unimpaired or normalcognition based on an extensive NP evaluation. The NP battery of tests was interpreted bythe same experienced neuropsychologist over the duration of the study, without anyknowledge of the MRI findings. A combination of DIR and PSIR imaging sequences wasused for accurate lesion detection/classification. Statistically significant correlations betweenMX as well as between CL (MX + IC) and CI were found. This association did not changewhen the JX lesions were added (IC+MX+JX). While our working hypothesis was thatcareful lesion classification between purely IC, MX and JX lesions using advanced MRItechniques might help isolate the impact of IC lesions on the presence of associated CI, itsimpact was found to be of less importance than the presence of MX lesions. The potentialexplanation for this may be that MX lesions tend to be larger in size. Another considerationis the fact that despite the improved detection capabilities of these advanced techniques weare still not capturing all IC lesions present.

Another goal of the study was to determine if correlations existed between the degree of CIand measures of DD, EDSS and brain atrophy. In this study, the only statistically significantcorrelation that was found was with disease severity as measured by EDSS. This isconsistent with the findings from other studies [39].

Strong evidence exists of a relationship between cognitive dysfunction and ventricularenlargement in patients with MS [39]. A relationship between significantly smallerparenchymal brain volumes and brain parenchymal fractions has also been observed inpatients with CI compared with those who are cognitively intact [40]. As in other areas ofMS research however, results are conflicting. In our study, atrophy alone was shown to beless important as a contributing factor to CI. It is possible that the relatively small subjectcohort that was studied may explain this apparent discrepancy in our findings. Thestatistically significant correlations seen between CL and specific tests like the PSIcomponent of the WAIS test support that information processing speed is more commonlyaffected by MS related CI.

A possible limitation of this study includes small cohort size and the significant variabilityin the number of CL found in these patients. The variability of CL presence between MSsubjects is quite consistent with previous post mortem histopathological studies byBrownwell and Hughes [41]. In our study there was clearly a significant increase in the totalnumber of IC lesions in the patients with mild and moderate CI (115 and 85 respectively)when compared with the borderline and normal (32 and 38), based on this the lowcorrelation between purely IC lesions and CI was somewhat unexpected. We suspect that thevariability in IC lesion number between patients interfered with our ability to establishstronger correlations. The fact that a stronger correlation between CI and MX lesions wasseen is not completely unexpected since IC lesions tend to be smaller. The strong correlationfound between CL (IC + MX) and CI could also be explained by the fact that it represents alarger area of cortical damage which includes interconnecting neurons present in the gray/white matter junction. Interestingly JX lesions also tend to be larger in size when comparedto IC but no clear correlation was observed with these lesions characterized for minimalinvasion of the cortical ribbon.

Our findings strongly suggest that CL both IC and MX play a more significant role incognitive dysfunction than JX lesions and measures of atrophy. More importantly, if ourobservations can be confirmed in a larger cohort in a prospective study, MRI couldpotentially be used as a biomarker for diagnosis, and management of CI in MS. Larger

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studies are needed to confirm these observations as are trials to evaluate the effect ofimmunomodulators on cortical lesion behavior and CI. Further efforts to advance ourunderstanding of the pathophysiological basis of cognitive dysfunction in MS needcontinued refinement and future application of combined advanced imaging techniques suchas MTR, DTI that may shed more light on the importance of the integrity of neural networksto the preservation cognitive function in MS are currently underway at our institution as arefunctional MRI (fMRI) studies for CI evaluation.

AcknowledgmentsThis work was primarily supported by NIH grant RO1EB002095-04S1 (PAN) and in part by the ClaytonFoundation for Research (JSW). The purchase of the 3T scanner is partially supported by the NIH grant S10RR19186 (PAN). We also would like to acknowledge Vipulkumar Patel for invaluable assistance with imagescanning and protocol optimization.

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Figure 1.Examples of Cortical lesions

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Tabl

e 1

MR

I acq

uisi

tion

para

met

ers

Imag

e ac

quis

ition

par

amet

ers f

or M

RI p

ulse

sequ

ence

s in

the

MS

prot

ocol

Sequ

ence

Plan

eT

R m

sec

TE

mse

cT

I mse

cIm

age

mat

rix

FOV

mm

Slic

e m

mSE

NSE

PSIR

axia

l43

0013

400

256×

256

240

3no

DIR

axia

l15

000

2534

00/3

2551

2×51

224

03

2

T1W

axia

l60

09.

2-

256×

256

240

3no

Dua

l-ech

o FS

Eax

ial

6800

10/9

0-

256×

256

240

3

FLA

IRax

ial

10,0

0080

2600

256×

256

240

32

PSIR

= ph

ase

sens

itive

inve

rsio

n re

cove

ry, D

IR=

doub

le in

vers

ion

reco

very

, W=

wei

ghte

d, F

SE =

fast

spin

ech

o, F

LAIR

= flu

id a

ttenu

ated

inve

rsio

n re

cove

ry

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Table 2

Number of lesions by type and degree of cognitive impairment

CI. Category IC lesions MX lesions JX lesions Total lesions

Normal (11) 21 5 6 32

Borderline (9) 22 10 6 38

Mild (11) 58 44 13 115

Moderate (7) 25 48 12 85

Severe (1) 4 1 2 7

Total (39) 130 108 39 277

CI= cognitive impairment, IC= intracortical, MX= mixed; mainly cortical with clear but minimal extension into the WM, JX= juxtacortical; mainlysubcortical with clear extension into the cortex.

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Table 3

Cognitive impairment and lesions by type

COGNITIVE IMPAIRMENT(mild, moderate, severe and borderline) vs. normal

Intracortical (IC) [w=1.80; p=0.179]

Mixed (MX) [w=6.71; p=0.010]

Juxtacortical (JX) [w=1.34; p=0.247]

Cortical lesions (IC + MX) [w=4.70; p=0.030]

Total lesions (IC + MX + JX) [w=4.48; p=0.034]

w=Walds Chi-Square statistic; p=P-value

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Table 4

Cognitive impairment and lesions by type 2nd Analysis

COGNITIVE IMPAIRMENT(mild, moderate, severe) vs. (borderline, normal)

Intracortical (IC) [w=2.71; p=0.100]

Mixed (MX) [w=8.76; p=0.003]

Juxtacortical (JX) [w=2.45; p=0.118]

Cortical (IC + MX) [w=6.67; p=0.010]

Total lesions (IC + MX + JX) [w=6.47; p=0.011]

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Table 5

Correlations between cognitive impairment and EDSS, disease duration and nCSF as a measure of atrophy.

N r p

Disease Duration 37 0.01856 0.9132

EDSS 38 0.41783 0.0090

nCSF 35 −0.18503 0.2873

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