Acta Neurol Belg DOI 10.1007/s13760-014-0338-3
ORIGINAL ARTICLE
A quantitative evaluation of damage in normal appearing white matter in patients with multiple sclerosis using diffusion tensor MR imaging at 3 T Georgios Gratsias • Eftychia Kapsalaki • Styliani Kogia • Efthimios Dardiotis Vaia Tsimourtou • Eleftherios Lavdas • Evanthia Kousi • Aimilia Pelekanou • Georgios M. Hadjigeorgiou • Ioannis Fezoulidis
•
Received: 7 February 2014 / Accepted: 14 July 2014 Ó Belgian Neurological Society 2014
Abstract The white matter (WM) of the brain is damaged in multiple sclerosis (MS), even in areas that appear normal on standard MR imaging. The purpose of our study is to evaluate the damage of normal appearing white matter (NAWM) in patients with MS. In our study, 84 MS patients and 42 healthy adults underwent a routine brain MRI, including also diffusion tensor imaging (DTI). All studies were performed on a 3 T MRI scanner. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained. The DTI parameters of NAWM were correlated with expanded disability status scales (EDSS) scores. Our results showed statistically significant differences in FA and ADC values between MS plaques and the symmetrical NAWM, as also between NAWM and the respective white matter in controls. The ADC values of the NAWM correlated with the EDSS scores. The present
G. Gratsias E. Kapsalaki S. Kogia E. Lavdas I. Fezoulidis Department of Radiology, University of Thessaly, Larissa, Thessaly, Greece G. Gratsias (&) E. Kapsalaki S. Kogia E. Dardiotis V. Tsimourtou E. Lavdas E. Kousi G. M. Hadjigeorgiou I. Fezoulidis University Hospital of Larissa, Mezourlo, Larissa, Greece e-mail: [email protected] E. Dardiotis V. Tsimourtou G. M. Hadjigeorgiou Department of Neurology, University of Thessaly, Larissa, Thessaly, Greece E. Kousi Department of Medical Physics, University of Thessaly, Larissa, Thessaly, Greece A. Pelekanou 4th Department of Internal Medicine, Attikon University Hospital, 1 Rimini Str., Athens, Attika, Greece
study demonstrated damage of the NAWM in MS patients, using DTI in 3.0 T. DTI may be used in the detection of subtle damage of the white matter. Keywords White matter diseases Multiple sclerosis Diffusion tensor imaging Anisotropy
Introduction Multiple sclerosis (MS) is the most common demyelinating disease, affecting 2.5 million people worldwide and the most common neurological disorder within the northern hemisphere in young adults, with a prevalence of 0.1 % [1]. The clinical course is heterogeneous, ranging from benign disease, in which patients live an almost normal life, to severe and devastating disease that may shorten life. Demyelination, axonal loss, remyelination, and inflammation are key components of MS pathology in the human central nervous system (CNS) [2]. Different MS disease courses as well as varying therapeutic regimens require early detection of axonal loss. Magnetic resonance imaging (MRI) has proven to be the imaging technique of choice in establishing the diagnosis, as underlined by the revised McDonald criteria of the international panel on the diagnosis of multiple sclerosis, as well as, for disease monitoring [3]. It is well known that white matter (WM) in MS is damaged, even in areas that appear normal on standard MRI sequences as T2 fast spin echo (FSE) weighted images, fluid attenuated inversion recovery (FLAIR), and proton density (PD) sequences. The relationship between the pathological abnormalities occurring in MS, i.e., inflammation, demyelination, axonal damage, and gliosis is intricate. A possible explanation for damage in normal
123
Acta Neurol Belg
appearing white matter (NAWM) is Wallerian degeneration [4]. Acute axonal damage is secondary to axon transection in the setting of inflammatory demyelination [5], while progressive axonal degeneration may be related to lack of trophic support from oligodendroglia and myelin [6]. Advanced MRI techniques have shown the potential ability to depict and quantify changes in lesions and NAWM. Diffusion tensor imaging (DTI) besides measuring the degree of diseased white matter more accurately than T2 FSE weighted imaging, may also detect abnormalities earlier than does T2 FSE weighted imaging [7]. More specifically, DTI parameters, as apparent diffusion coefficient (ADC) and fractional anisotropy (FA), may represent important indicators of neuronal structure and its loss, in patients suffering from MS [8]. FA reflects the prevalence of diffusivity along one spatial direction [9], whereas ADC is the MR imaging—measured diffusion coefficient of CNS tissues and is, therefore, lower than that in free water. Hence, pathologic processes that result in a decrease of restricting barriers can determine an increase of the ADC values [10]. Expanded disability status scale (EDSS) quantifies disability in MS with respect to eight functional systems by allowing the neurologist to assign a functional system score (FSS) in each of these. EDSS steps 0–3.5 refer to patients with MS who are fully ambulatory, EDSS steps 4.0–9.5 are defined by the impairment to movement. Correlation between EDSS and DTI parameters of NAWM, as FA and ADC, have shown conflicting results, with poor [11] or strong [12] correlation of EDSS and DTI parameters, depending on the study. In a literature search, we found a relatively small number of reports, using a magnetic field of 3 T or higher in estimating NAWM in a large group of MS patients and controls. The purpose of our study is to evaluate in a quantitative manner the damage of NAWM in patients with MS, using advanced MRI techniques as DTI at 3 T, in a large group of patients and controls.
Methods In our prospective clinical study, we included 84 patients with a clinical diagnosis of definite MS. In our patient group, 51 females and 33 males were included aging from 18 to 45 years. Females were 18–45 years (mean 33.9 years) whereas males were 19–45 years (mean 35.1 years). Forty-two healthy age and sex matched adults were also examined with the same imaging protocol and represented our control group. The control group consisted of 27 females (age range 18–44 years, mean 27.2 years) and 15 males (age range 18–45 years, mean 26 years). The
123
MRI study was performed as part of their routine yearly follow-up imaging study and at every clinical relapse. Clinical and laboratory data were recorded for all participants, including the EDSS scores, for the quantification of the degree of impairment of the patients. The mean value of EDSS was 2.5 (range 0–8), the mean disease duration was 5.6 years (range 1–19 years), and the mean age of disease onset in our study cohort was 27.4 years (range 18–42 years). Concerning the subtype of MS, 75 patients suffered from relapsing remitting (RR) MS (89 %), five patients had primary progressive (PP) MS (6 %), and four patients secondary progressive (SP) MS (5 %). The patients of this study were treated in the neurology clinic of our hospital. The MRI studies were performed on a 3 T MR scanner (GE, HdX, GE Healthcare, USA) using an eight-channel coil as a phased-array receiver and a body coil for transmission. Parallel imaging has been used, with array spatial sensitivity technique (R factor: 2). The brain MRI protocol included axial and sagittal T1SE sequences, axial T1 SE, T2 FSE, PD and FLAIR sequences, sagittal 3D FLAIR images (CUBE) and DTI. After administration of gadolinium (0.1 mmol/kg Gadopentetate dimeglumine), T1 SE sequences in axial, sagittal and coronal planes as well as a 3D SPoiled GRadient Echo (SPGR) sequence were obtained. DTI acquisitions were performed using an axial singleshot SE echo-planar imaging (EPI) sequence along 32 different geometric directions, using a b value of 1000 s/ mm2 (4 mm thickness, 0.4 mm gap, TR/TE 8.000/101 ms, 27 sections, matrix 128 9 128, FOV 260 9 260 mm and NEX 1). The scan duration for DTI was 3.36 min. All patients and controls were fully cooperative, as a result no motion artifacts occurred. Acquisition parameters were optimized to provide the best signal-to-noise ratio for estimation of diffusion tensors. All data were transferred at an independent workstation and were analyzed using Functool software, provided by the manufacturer. Qualitative assessment of all images was performed evaluating imaging MS findings according to McDonald criteria. Contrast enhancing lesions and black holes were also noted and excluded from our measurements for homogeneity reasons. Quantitative measurements were also performed. FA and ADC were measured in multiple MS plaques, regardless their size, and in the symmetrical NAWM. In patients with more than 20 MS, plaques a maximum of ten lesions were measured on each hemisphere. Data were analyzed with the Functool processing system provided by the manufacturer. More specifically, a round-shaped ROI of 25–30 mm2 area was placed in the center of 237 MS lesions located in the periventricular white matter, in the corpus callosum (genu, body and splenium), the centrum
Acta Neurol Belg
semiovale and the corona radiata and in the symmetrical NAWM. The DTI parameters of NAWM were correlated with the EDSS scores of the patients. We also measured the FA and ADC values from the corresponding areas of WM of the control group, by placing 210 round-shaped ROIs in the periventricular white matter, the corpus callosum, the centrum semiovale, and the corona radiata, in both hemispheres symmetrically. Statistical analysis was performed by employing SPSS 15.0. Comparisons between groups of ROIs were performed using the t test. Any p value lower than 0.05 was considered statistically significant. Informed consent was obtained from all our patients and volunteers. This study was approved by the ethics committee of our hospital.
Results We placed round-shaped ROIs of 25–30 mm2 area in FA and ADC maps, measuring the FA and ADC values from the center of 237 MS lesions and from the contralateral NAWM of our patient group. The lesions were mainly distributed in the periventricular white matter, the corpus callosum (CC), the centrum semiovale, and the corona radiata. The contralateral NAWM had no obvious pathology in FLAIR and T2 FSE sequences (Fig. 1a–c). Both FA and ADC measurements were parameters with normal distribution. We found lower FA values in the MS plaques (average FA value 0.2285, SD 0,072) in comparison to the values obtained from the symmetrical NAWM (average FA value 0.4645, SD 0,095) in our patient group. The difference was statistically significant (p \ 0.05). We also found lower FA values in the NAWM of the patients in comparison to the respective WM FA values in controls (average FA value 0.7455, SD 0,075) (p \ 0.05). The FA results are depicted in Fig. 2 and Table 1. Higher ADC values (average ADC value 1.2292 9 10-3 mm2/s, SD 0,271) were found in the MS plaques in comparison with the symmetrical NAWM ADC values (average ADC value 0.8067 9 10-3 mm2/s, SD 0,105) (p \ 0.05) in our patient group. Higher ADC values were also found in the NAWM of the patients in comparison to the respective WM ADC values in controls (average ADC value 0.7265 9 10-3 mm2/s, SD 0,052) (p \ 0.05). The ADC results are depicted in Fig. 3 and Table 2. Statistical analysis correlating DTI in NAWM with EDSS scores of our patient cohort revealed a tendency toward a correlation between EDSS and ADC. However, no statistical significance was established between EDSS scores and ADC measurements or between FA measurements and EDSS scores (Fig. 4).
Mo statistical analysis was attempted between the different forms of MS (RRMS, PPMS, SPMS) due to the small number of patients in the PPMS and SPMS subgroups.
Discussion This study was conducted to assess the diagnostic value of DTI in estimating NAWM of MS patients. It has been reported that NAWM may be abnormal in patients with MS [12–18]. Several studies also reported that NAWM may have variable microstructural changes, which are more prominent near the obvious MS plaques [12–18]. Dziedzic et al. report that Wallerian degeneration is a major component of axonal pathology in the periplaque white matter in early MS. It may contribute to radiological changes observed in early MS and most likely plays a major role in the development of disability [13]. It is of paramount importance to detect microstructural alterations of NAWM in MS patients, since it may contribute in the prognosis and the course of the disease. Normal appearing white matter abnormality may be attributed to axonal degeneration, due to proximity to WM lesions [14]. However, damage may not be due to Wallerian degenatation but due to the microglial activation without axonal damage [14].Pathological studies report that true normal appearing white matter presents activated microglia despite the absence of axonal pathology or myelin loss [14, 15]. DTI discloses the presence of abnormalities in the NAWM and gray matter (GM) of patients with MS [16]. DTI features and clinical severity of patients who have established MS seem to be interrelated [17]. According to Ceccarelli [18], myelin and axonal loss in NAWM lead to increased mean diffusivity by causing a net loss of structural barriers, and reduced FA by altering the physiological organization of structural barriers to water molecular motion. Sigal et al., focusing in the corpus callosum (CC), concluded that changes in ADC and specifically in transverse diffusivity represent microstructural damage in RRMS and positively correlate with clinical disease activity and progression [12]. Rovaris et al. [19] examined the relationship between DTI metrics and cognition in RRMS patients with mild neurological disability. Modest but significant correlations were found between mean brain diffusivity and cognitive tests measuring memory, speed of information processing, and verbal fluency [19]. Elevated radial diffusivity during gadolinium enhancement was associated with increased risk for development of a persistent black hole, a surrogate of severe demyelination and axonal injury. A relationship between the burden of chronic black holes and increasing disability has been established, supporting its
123
Acta Neurol Belg b Fig. 1 DTI image a, measurements of FA b and ADC c in a lesion
and in the NAWM of a patient with MS. Regions of interest (ROIs) of 26 mm2 are placed in the center of a lesion in the left external capsule and in the symmetrical NAWM of the contralateral hemisphere. DTI Diffusion tensor imaging, FA fractional anisotropy, ADC apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis
Fig. 2 Depiction of statistic correlation between FA measurements in MS lesions, in NAWM of MS patients and in the respective WM of controls. The graph displays the significant differences in FA measurements, with the lowest values found in the MS lesions and the highest values in the WM of controls. The FA values in the NAWM of MS patients were intermediate. FA fractional anisotropy, NAWM normal appearing white matter, WM white matter, MS multiple sclerosis
clinical relevance [20]. Ongoing studies are investigating the utility of DTI in monitoring treatment efficacy [21]. In our present study, we evaluated in both a qualitative and
123
quantitative manner the depiction of NAWM of MS patients. Our results, in line with reports from other studies [22–26], show that NAWM is indeed affected in the patients with MS, regardless of its identification on conventional MR images. Using DTI, both FA and ADC values were statistically differentiated from the corresponding values of the MS lesions as well as the values of normal individuals. The FA values of NAWM were decreased in comparison with the FA values of the symmetrical WM of the control group and increased compared with the FA values of the MS lesions. The results of our study are in agreement with the results of other investigators. Andrade et al. [22] reported that patients with MS show difference in the FA values of the plaques, peri-plaques, and NAWM around the plaques when compared to the normal white matter of controls [22], while Rueda et al. [23] found a significant decrease in the FA in all regions of the normal appearing CC, suggesting that there is a subtle and diffuse abnormality in the CC despite its normal appearance on conventional MR imaging [23]. The ADC values of NAWM were increased in comparison to the ADC values of the symmetrical WM of the
Acta Neurol Belg Table 1 FA measurements in MS lesions, in the NAWM of patients and in the WM of controls
Table 2 ADC measurements in MS lesions, in the NAWM of patients and in the WM of controls
FA
M
Mean
SD
ADC (9 10-3 mm2/s)
M
Mean
SD
MS lesions
237
0.2285
0.072
MS lesions
237
1.2292
0.271
NAWM
237
0.4645
0.095
NAWM
237
0.8067
0.105
Controls
210
0.7455
0.075
Controls
210
0.7265
0.052
p value between FA in MS lesions and NAWM \0.05
p value between ADC in MS lesions and NAWM \0.05
p value between FA in NAWM and controls \0.05
p value between ADC in NAWM and controls \0.05
FA Fractional anisotropy, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
ADC Apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
Fig. 3 Depiction of statistic correlation between ADC measurements in MS lesions, in NAWM of MS patients and in the respective WM of controls. The graph displays the significant differences in ADC measurements, with the highest values found in the MS lesions and the lowest values in the WM of controls. The ADC values in the NAWM of MS patients were intermediate. ADC Apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
Fig. 4 Depiction of statistic correlation between EDSS and FA-ADC measurements in NAWM of MS patients. The EDSS values are in the y axis. The graph displays a tendency to correlation between ADC values and EDSS scores. No similar findings came of the correlation between FA values and EDSS scores. FA Fractional anisotropy, ADC apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, EDSS expanded disability status scale
controls’ group and decreased in comparison with the ADC values of the MS lesions. Our results are in accordance with those of previous studies, which reported increased ADC values within both T2-visible lesions and the NAWM [24]. Werring et al. [25] found an increase in ADC values of the prelesional NAWM and the homologous contralateral NAWM, whereas Yurtsever et al. [26] demonstrated that ADC values of NAWM in MS patients were higher than the values of normal population. In conclusion, DTI performed on a 3.0 T scanner in a significant group of patients and controls (84 patients and 42 healthy adults, respectively), can detect and demonstrate in a quantitative and qualitative manner, the damage of NAWM in MS patients, a type of pathology that cannot be detected with conventional MRI sequences. Quantitative evaluation of microstructural damage in NAWM, by FA and ADC, provides measurements of the
integrity of the white matter. Therefore, DTI may be used in the early detection of subtle white matter damage in MS patients and as a predictive indicator of the clinical outcome and the response to treatment, in clinical trials of patients with MS. Conflict of interest of interest.
The authors declare that they have no conflict
References 1. Pugliatti M, Sotgiu S, Rosati G (2002) The worldwide prevalence of multiple sclerosis. Clin Neurol Neurosurg 104:182–191 2. Sati P, Cross A, Luo J, Hildebolt CF, Yablonskiy DA (2010) In vivo quantitative evaluation of brain tissue damage in multiple sclerosis using gradient echo plural contrast imaging technique. Neuroimage 51:1089–1097 3. Polman CH, Reingold SC, Edan G et al (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the McDonald criteria. Ann Neurol 58:840–846
123
Acta Neurol Belg 4. Ciccarelli O, Werring D, Barker G, Griffin CM, Wheeler-Kingshott CA, Miller DH, Thompson AJ (2003) A study of the mechanisms of normal appearing white matter damage in multiple sclerosis using diffusion tensor imaging-evidence of Wallerian degeneration. J Neurol 250:287–292 5. Kuhlmann T, Lingfeld G, Bitsch A, Schuchardt J, Bru¨ck W (2002) Acute axonal damage in multiple sclerosis is most extensive in early disease stages and decreases over time. Brain 125:2202–2212 6. Kornek B, Storch MK, Weissert R, Wallstroem E, Stefferl A, Olsson T, Linington C, Schmidbauer M, Lassmann H (2000) Multiple sclerosis and chronic autoimmune encephalomyelitis: a comparative quantitative study of axonal injury in active, inactive and remyelinated lesions. Am J Pathol 157:267–276 7. Rovaris M, Gass A, Bammer R, Hickman SJ, Ciccarelli O, Miller DH, Filippi M (2005) Diffusion MRI in multiple sclerosis. Neurology 65:1526–1532 8. Sijens P, Irwan R, Potze J, Mostert JP, De Keyser J, Oudkerk M (2006) Relationships between brain water content and diffusion tensor imaging parameters (apparent diffusion coefficient and fractional anisotropy) in multiple sclerosis. Eur Radiol 16:898–904 9. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G (1996) Diffusion tensor MR imaging of the human brain. Radiology 201:637–648 10. Rovaris M, Agosta F, Pagani E, Filippi M (2009) Diffusion tensor MR imaging. Neuroimag Clin N Am 19:37–43 11. Tian W, Zhu T, Zhong J, Liu X, Rao P, Segal BM, Ekholm S (2012) Progressive decline in fractional anisotropy on serial DTI examinations of the corpus callosum: a putative marker of disease activity and progression in SPMS. Neuroradiology 54:287–297 12. Sigal T, Shmuel M, Mark D, Gil H, Anat A (2012) Diffusion tensor imaging of corpus callosum integrity in multiple sclerosis: correlation with disease variables. J Neuroimaging 22:33–37 13. Dziedzic T, Metz I, Dallenga T, Ko¨nig FB, Mu¨ller S, Stadelmann C, Bru¨ck W (2010) Wallerian degeneration: a major component of early axonal pathology in multiple sclerosis. Brain Pathol 5:976–985 14. Moll NM, Riietsch AM, Thomas S, Ransohoff AJ, Lee JC, Fox R, Chang A, Ransohoff RM, Fisher E (2011) Multiple sclerosis NAWM: pathology-imaging correlations. Ann Neurol 70:764–773 15. Fillippi M, Rocca M, Barkhof F et al (2012) Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 11:349–360
123
16. Kim DS, Garwood M (2003) High-field magnetic resonance techniques for brain research. Curr Opin Neurobiol 13:612–619 17. Rocca MA, Cercignani M, Iannucci G, Comi G, Filippi M (2000) Weekly diffusion-weighted imaging of normal-appearing white matter in MS. Neurology 55:882–884 18. Ceccarelli A, Rocca M, Falini A, Tortorella P, Pagani E, Rodegher M, Comi G, Scotti G, Filippi M (2007) Normal-appearing white and grey matter damage in MS. a volumetric and diffusion tensor MRI study at 3.0 Tesla. J Neurol 254:513–518 19. Rovaris M, Iannucci G, Falautano M, Possa F, Martinelli V, Comi G, Filippi M (2002) Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 195:103–109 20. Naismith RT (2005) Cross AH multiple sclerosis and black holes: connecting the pixels. Arch Neurol 62:1666–1668 21. Fox RJ, Cronin T, Lin J, Wang X, Sakaie K, Ontaneda D, Mahmoud SY, Lowe MJ, Phillips MD (2011) Measuring myelin repair and axonal loss with diffusion tensor imaging. AJNR Am J Neuroradiol 32:85–91 22. Andrade RE, Gasparetto EL, Cruz LC Jr, Ferreira FB, Domingues RC, Marchiori E, Domingues RC (2007) Evaluation of white matter in patients with multiple sclerosis through diffusion tensor magnetic resonance imaging. Arq Neuropsiquiatr 65:561–564 23. Rueda F, Hygino L, Domingues R, Vasconcelos CC, Papais-Alvarenga RM, Gasparetto EL (2008) Diffusion tensor MR imaging evaluation of the corpus callosum of patients with multiple sclerosis. Arq Neuropsiquiatr 66(3A):449–453 24. Horsfield MA, Larsson HB, Jones DK, Gass A (1998) Diffusion magnetic resonance imaging in multiple sclerosis. J Neurol Neurosurg Psychiatr 64(Suppl 1):S80–84 25. Werring DJ, Brassat D, Droogan AG, Clark CA, Symms MR, Barker GJ, MacManus DG, Thompson AJ, Miller DH (2000) The pathogenesis of lesions and normal-appearing white matter changes in multiple sclerosis. a serial diffusion MRI study. Brain 123:1667–1776 26. Yurtsever I, Hakyemez B, Taskapilioglu O, Erdogan C, Turan OF, Parlak M (2008) The contribution of diffusion-weighted MR imaging in multiple sclerosis during acute attack. Eur J Radiol 65:421–426
ORIGINAL ARTICLE
A quantitative evaluation of damage in normal appearing white matter in patients with multiple sclerosis using diffusion tensor MR imaging at 3 T Georgios Gratsias • Eftychia Kapsalaki • Styliani Kogia • Efthimios Dardiotis Vaia Tsimourtou • Eleftherios Lavdas • Evanthia Kousi • Aimilia Pelekanou • Georgios M. Hadjigeorgiou • Ioannis Fezoulidis
•
Received: 7 February 2014 / Accepted: 14 July 2014 Ó Belgian Neurological Society 2014
Abstract The white matter (WM) of the brain is damaged in multiple sclerosis (MS), even in areas that appear normal on standard MR imaging. The purpose of our study is to evaluate the damage of normal appearing white matter (NAWM) in patients with MS. In our study, 84 MS patients and 42 healthy adults underwent a routine brain MRI, including also diffusion tensor imaging (DTI). All studies were performed on a 3 T MRI scanner. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained. The DTI parameters of NAWM were correlated with expanded disability status scales (EDSS) scores. Our results showed statistically significant differences in FA and ADC values between MS plaques and the symmetrical NAWM, as also between NAWM and the respective white matter in controls. The ADC values of the NAWM correlated with the EDSS scores. The present
G. Gratsias E. Kapsalaki S. Kogia E. Lavdas I. Fezoulidis Department of Radiology, University of Thessaly, Larissa, Thessaly, Greece G. Gratsias (&) E. Kapsalaki S. Kogia E. Dardiotis V. Tsimourtou E. Lavdas E. Kousi G. M. Hadjigeorgiou I. Fezoulidis University Hospital of Larissa, Mezourlo, Larissa, Greece e-mail: [email protected] E. Dardiotis V. Tsimourtou G. M. Hadjigeorgiou Department of Neurology, University of Thessaly, Larissa, Thessaly, Greece E. Kousi Department of Medical Physics, University of Thessaly, Larissa, Thessaly, Greece A. Pelekanou 4th Department of Internal Medicine, Attikon University Hospital, 1 Rimini Str., Athens, Attika, Greece
study demonstrated damage of the NAWM in MS patients, using DTI in 3.0 T. DTI may be used in the detection of subtle damage of the white matter. Keywords White matter diseases Multiple sclerosis Diffusion tensor imaging Anisotropy
Introduction Multiple sclerosis (MS) is the most common demyelinating disease, affecting 2.5 million people worldwide and the most common neurological disorder within the northern hemisphere in young adults, with a prevalence of 0.1 % [1]. The clinical course is heterogeneous, ranging from benign disease, in which patients live an almost normal life, to severe and devastating disease that may shorten life. Demyelination, axonal loss, remyelination, and inflammation are key components of MS pathology in the human central nervous system (CNS) [2]. Different MS disease courses as well as varying therapeutic regimens require early detection of axonal loss. Magnetic resonance imaging (MRI) has proven to be the imaging technique of choice in establishing the diagnosis, as underlined by the revised McDonald criteria of the international panel on the diagnosis of multiple sclerosis, as well as, for disease monitoring [3]. It is well known that white matter (WM) in MS is damaged, even in areas that appear normal on standard MRI sequences as T2 fast spin echo (FSE) weighted images, fluid attenuated inversion recovery (FLAIR), and proton density (PD) sequences. The relationship between the pathological abnormalities occurring in MS, i.e., inflammation, demyelination, axonal damage, and gliosis is intricate. A possible explanation for damage in normal
123
Acta Neurol Belg
appearing white matter (NAWM) is Wallerian degeneration [4]. Acute axonal damage is secondary to axon transection in the setting of inflammatory demyelination [5], while progressive axonal degeneration may be related to lack of trophic support from oligodendroglia and myelin [6]. Advanced MRI techniques have shown the potential ability to depict and quantify changes in lesions and NAWM. Diffusion tensor imaging (DTI) besides measuring the degree of diseased white matter more accurately than T2 FSE weighted imaging, may also detect abnormalities earlier than does T2 FSE weighted imaging [7]. More specifically, DTI parameters, as apparent diffusion coefficient (ADC) and fractional anisotropy (FA), may represent important indicators of neuronal structure and its loss, in patients suffering from MS [8]. FA reflects the prevalence of diffusivity along one spatial direction [9], whereas ADC is the MR imaging—measured diffusion coefficient of CNS tissues and is, therefore, lower than that in free water. Hence, pathologic processes that result in a decrease of restricting barriers can determine an increase of the ADC values [10]. Expanded disability status scale (EDSS) quantifies disability in MS with respect to eight functional systems by allowing the neurologist to assign a functional system score (FSS) in each of these. EDSS steps 0–3.5 refer to patients with MS who are fully ambulatory, EDSS steps 4.0–9.5 are defined by the impairment to movement. Correlation between EDSS and DTI parameters of NAWM, as FA and ADC, have shown conflicting results, with poor [11] or strong [12] correlation of EDSS and DTI parameters, depending on the study. In a literature search, we found a relatively small number of reports, using a magnetic field of 3 T or higher in estimating NAWM in a large group of MS patients and controls. The purpose of our study is to evaluate in a quantitative manner the damage of NAWM in patients with MS, using advanced MRI techniques as DTI at 3 T, in a large group of patients and controls.
Methods In our prospective clinical study, we included 84 patients with a clinical diagnosis of definite MS. In our patient group, 51 females and 33 males were included aging from 18 to 45 years. Females were 18–45 years (mean 33.9 years) whereas males were 19–45 years (mean 35.1 years). Forty-two healthy age and sex matched adults were also examined with the same imaging protocol and represented our control group. The control group consisted of 27 females (age range 18–44 years, mean 27.2 years) and 15 males (age range 18–45 years, mean 26 years). The
123
MRI study was performed as part of their routine yearly follow-up imaging study and at every clinical relapse. Clinical and laboratory data were recorded for all participants, including the EDSS scores, for the quantification of the degree of impairment of the patients. The mean value of EDSS was 2.5 (range 0–8), the mean disease duration was 5.6 years (range 1–19 years), and the mean age of disease onset in our study cohort was 27.4 years (range 18–42 years). Concerning the subtype of MS, 75 patients suffered from relapsing remitting (RR) MS (89 %), five patients had primary progressive (PP) MS (6 %), and four patients secondary progressive (SP) MS (5 %). The patients of this study were treated in the neurology clinic of our hospital. The MRI studies were performed on a 3 T MR scanner (GE, HdX, GE Healthcare, USA) using an eight-channel coil as a phased-array receiver and a body coil for transmission. Parallel imaging has been used, with array spatial sensitivity technique (R factor: 2). The brain MRI protocol included axial and sagittal T1SE sequences, axial T1 SE, T2 FSE, PD and FLAIR sequences, sagittal 3D FLAIR images (CUBE) and DTI. After administration of gadolinium (0.1 mmol/kg Gadopentetate dimeglumine), T1 SE sequences in axial, sagittal and coronal planes as well as a 3D SPoiled GRadient Echo (SPGR) sequence were obtained. DTI acquisitions were performed using an axial singleshot SE echo-planar imaging (EPI) sequence along 32 different geometric directions, using a b value of 1000 s/ mm2 (4 mm thickness, 0.4 mm gap, TR/TE 8.000/101 ms, 27 sections, matrix 128 9 128, FOV 260 9 260 mm and NEX 1). The scan duration for DTI was 3.36 min. All patients and controls were fully cooperative, as a result no motion artifacts occurred. Acquisition parameters were optimized to provide the best signal-to-noise ratio for estimation of diffusion tensors. All data were transferred at an independent workstation and were analyzed using Functool software, provided by the manufacturer. Qualitative assessment of all images was performed evaluating imaging MS findings according to McDonald criteria. Contrast enhancing lesions and black holes were also noted and excluded from our measurements for homogeneity reasons. Quantitative measurements were also performed. FA and ADC were measured in multiple MS plaques, regardless their size, and in the symmetrical NAWM. In patients with more than 20 MS, plaques a maximum of ten lesions were measured on each hemisphere. Data were analyzed with the Functool processing system provided by the manufacturer. More specifically, a round-shaped ROI of 25–30 mm2 area was placed in the center of 237 MS lesions located in the periventricular white matter, in the corpus callosum (genu, body and splenium), the centrum
Acta Neurol Belg
semiovale and the corona radiata and in the symmetrical NAWM. The DTI parameters of NAWM were correlated with the EDSS scores of the patients. We also measured the FA and ADC values from the corresponding areas of WM of the control group, by placing 210 round-shaped ROIs in the periventricular white matter, the corpus callosum, the centrum semiovale, and the corona radiata, in both hemispheres symmetrically. Statistical analysis was performed by employing SPSS 15.0. Comparisons between groups of ROIs were performed using the t test. Any p value lower than 0.05 was considered statistically significant. Informed consent was obtained from all our patients and volunteers. This study was approved by the ethics committee of our hospital.
Results We placed round-shaped ROIs of 25–30 mm2 area in FA and ADC maps, measuring the FA and ADC values from the center of 237 MS lesions and from the contralateral NAWM of our patient group. The lesions were mainly distributed in the periventricular white matter, the corpus callosum (CC), the centrum semiovale, and the corona radiata. The contralateral NAWM had no obvious pathology in FLAIR and T2 FSE sequences (Fig. 1a–c). Both FA and ADC measurements were parameters with normal distribution. We found lower FA values in the MS plaques (average FA value 0.2285, SD 0,072) in comparison to the values obtained from the symmetrical NAWM (average FA value 0.4645, SD 0,095) in our patient group. The difference was statistically significant (p \ 0.05). We also found lower FA values in the NAWM of the patients in comparison to the respective WM FA values in controls (average FA value 0.7455, SD 0,075) (p \ 0.05). The FA results are depicted in Fig. 2 and Table 1. Higher ADC values (average ADC value 1.2292 9 10-3 mm2/s, SD 0,271) were found in the MS plaques in comparison with the symmetrical NAWM ADC values (average ADC value 0.8067 9 10-3 mm2/s, SD 0,105) (p \ 0.05) in our patient group. Higher ADC values were also found in the NAWM of the patients in comparison to the respective WM ADC values in controls (average ADC value 0.7265 9 10-3 mm2/s, SD 0,052) (p \ 0.05). The ADC results are depicted in Fig. 3 and Table 2. Statistical analysis correlating DTI in NAWM with EDSS scores of our patient cohort revealed a tendency toward a correlation between EDSS and ADC. However, no statistical significance was established between EDSS scores and ADC measurements or between FA measurements and EDSS scores (Fig. 4).
Mo statistical analysis was attempted between the different forms of MS (RRMS, PPMS, SPMS) due to the small number of patients in the PPMS and SPMS subgroups.
Discussion This study was conducted to assess the diagnostic value of DTI in estimating NAWM of MS patients. It has been reported that NAWM may be abnormal in patients with MS [12–18]. Several studies also reported that NAWM may have variable microstructural changes, which are more prominent near the obvious MS plaques [12–18]. Dziedzic et al. report that Wallerian degeneration is a major component of axonal pathology in the periplaque white matter in early MS. It may contribute to radiological changes observed in early MS and most likely plays a major role in the development of disability [13]. It is of paramount importance to detect microstructural alterations of NAWM in MS patients, since it may contribute in the prognosis and the course of the disease. Normal appearing white matter abnormality may be attributed to axonal degeneration, due to proximity to WM lesions [14]. However, damage may not be due to Wallerian degenatation but due to the microglial activation without axonal damage [14].Pathological studies report that true normal appearing white matter presents activated microglia despite the absence of axonal pathology or myelin loss [14, 15]. DTI discloses the presence of abnormalities in the NAWM and gray matter (GM) of patients with MS [16]. DTI features and clinical severity of patients who have established MS seem to be interrelated [17]. According to Ceccarelli [18], myelin and axonal loss in NAWM lead to increased mean diffusivity by causing a net loss of structural barriers, and reduced FA by altering the physiological organization of structural barriers to water molecular motion. Sigal et al., focusing in the corpus callosum (CC), concluded that changes in ADC and specifically in transverse diffusivity represent microstructural damage in RRMS and positively correlate with clinical disease activity and progression [12]. Rovaris et al. [19] examined the relationship between DTI metrics and cognition in RRMS patients with mild neurological disability. Modest but significant correlations were found between mean brain diffusivity and cognitive tests measuring memory, speed of information processing, and verbal fluency [19]. Elevated radial diffusivity during gadolinium enhancement was associated with increased risk for development of a persistent black hole, a surrogate of severe demyelination and axonal injury. A relationship between the burden of chronic black holes and increasing disability has been established, supporting its
123
Acta Neurol Belg b Fig. 1 DTI image a, measurements of FA b and ADC c in a lesion
and in the NAWM of a patient with MS. Regions of interest (ROIs) of 26 mm2 are placed in the center of a lesion in the left external capsule and in the symmetrical NAWM of the contralateral hemisphere. DTI Diffusion tensor imaging, FA fractional anisotropy, ADC apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis
Fig. 2 Depiction of statistic correlation between FA measurements in MS lesions, in NAWM of MS patients and in the respective WM of controls. The graph displays the significant differences in FA measurements, with the lowest values found in the MS lesions and the highest values in the WM of controls. The FA values in the NAWM of MS patients were intermediate. FA fractional anisotropy, NAWM normal appearing white matter, WM white matter, MS multiple sclerosis
clinical relevance [20]. Ongoing studies are investigating the utility of DTI in monitoring treatment efficacy [21]. In our present study, we evaluated in both a qualitative and
123
quantitative manner the depiction of NAWM of MS patients. Our results, in line with reports from other studies [22–26], show that NAWM is indeed affected in the patients with MS, regardless of its identification on conventional MR images. Using DTI, both FA and ADC values were statistically differentiated from the corresponding values of the MS lesions as well as the values of normal individuals. The FA values of NAWM were decreased in comparison with the FA values of the symmetrical WM of the control group and increased compared with the FA values of the MS lesions. The results of our study are in agreement with the results of other investigators. Andrade et al. [22] reported that patients with MS show difference in the FA values of the plaques, peri-plaques, and NAWM around the plaques when compared to the normal white matter of controls [22], while Rueda et al. [23] found a significant decrease in the FA in all regions of the normal appearing CC, suggesting that there is a subtle and diffuse abnormality in the CC despite its normal appearance on conventional MR imaging [23]. The ADC values of NAWM were increased in comparison to the ADC values of the symmetrical WM of the
Acta Neurol Belg Table 1 FA measurements in MS lesions, in the NAWM of patients and in the WM of controls
Table 2 ADC measurements in MS lesions, in the NAWM of patients and in the WM of controls
FA
M
Mean
SD
ADC (9 10-3 mm2/s)
M
Mean
SD
MS lesions
237
0.2285
0.072
MS lesions
237
1.2292
0.271
NAWM
237
0.4645
0.095
NAWM
237
0.8067
0.105
Controls
210
0.7455
0.075
Controls
210
0.7265
0.052
p value between FA in MS lesions and NAWM \0.05
p value between ADC in MS lesions and NAWM \0.05
p value between FA in NAWM and controls \0.05
p value between ADC in NAWM and controls \0.05
FA Fractional anisotropy, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
ADC Apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
Fig. 3 Depiction of statistic correlation between ADC measurements in MS lesions, in NAWM of MS patients and in the respective WM of controls. The graph displays the significant differences in ADC measurements, with the highest values found in the MS lesions and the lowest values in the WM of controls. The ADC values in the NAWM of MS patients were intermediate. ADC Apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, WM white matter
Fig. 4 Depiction of statistic correlation between EDSS and FA-ADC measurements in NAWM of MS patients. The EDSS values are in the y axis. The graph displays a tendency to correlation between ADC values and EDSS scores. No similar findings came of the correlation between FA values and EDSS scores. FA Fractional anisotropy, ADC apparent diffusion coefficient, NAWM normal appearing white matter, MS multiple sclerosis, EDSS expanded disability status scale
controls’ group and decreased in comparison with the ADC values of the MS lesions. Our results are in accordance with those of previous studies, which reported increased ADC values within both T2-visible lesions and the NAWM [24]. Werring et al. [25] found an increase in ADC values of the prelesional NAWM and the homologous contralateral NAWM, whereas Yurtsever et al. [26] demonstrated that ADC values of NAWM in MS patients were higher than the values of normal population. In conclusion, DTI performed on a 3.0 T scanner in a significant group of patients and controls (84 patients and 42 healthy adults, respectively), can detect and demonstrate in a quantitative and qualitative manner, the damage of NAWM in MS patients, a type of pathology that cannot be detected with conventional MRI sequences. Quantitative evaluation of microstructural damage in NAWM, by FA and ADC, provides measurements of the
integrity of the white matter. Therefore, DTI may be used in the early detection of subtle white matter damage in MS patients and as a predictive indicator of the clinical outcome and the response to treatment, in clinical trials of patients with MS. Conflict of interest of interest.
The authors declare that they have no conflict
References 1. Pugliatti M, Sotgiu S, Rosati G (2002) The worldwide prevalence of multiple sclerosis. Clin Neurol Neurosurg 104:182–191 2. Sati P, Cross A, Luo J, Hildebolt CF, Yablonskiy DA (2010) In vivo quantitative evaluation of brain tissue damage in multiple sclerosis using gradient echo plural contrast imaging technique. Neuroimage 51:1089–1097 3. Polman CH, Reingold SC, Edan G et al (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the McDonald criteria. Ann Neurol 58:840–846
123
Acta Neurol Belg 4. Ciccarelli O, Werring D, Barker G, Griffin CM, Wheeler-Kingshott CA, Miller DH, Thompson AJ (2003) A study of the mechanisms of normal appearing white matter damage in multiple sclerosis using diffusion tensor imaging-evidence of Wallerian degeneration. J Neurol 250:287–292 5. Kuhlmann T, Lingfeld G, Bitsch A, Schuchardt J, Bru¨ck W (2002) Acute axonal damage in multiple sclerosis is most extensive in early disease stages and decreases over time. Brain 125:2202–2212 6. Kornek B, Storch MK, Weissert R, Wallstroem E, Stefferl A, Olsson T, Linington C, Schmidbauer M, Lassmann H (2000) Multiple sclerosis and chronic autoimmune encephalomyelitis: a comparative quantitative study of axonal injury in active, inactive and remyelinated lesions. Am J Pathol 157:267–276 7. Rovaris M, Gass A, Bammer R, Hickman SJ, Ciccarelli O, Miller DH, Filippi M (2005) Diffusion MRI in multiple sclerosis. Neurology 65:1526–1532 8. Sijens P, Irwan R, Potze J, Mostert JP, De Keyser J, Oudkerk M (2006) Relationships between brain water content and diffusion tensor imaging parameters (apparent diffusion coefficient and fractional anisotropy) in multiple sclerosis. Eur Radiol 16:898–904 9. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G (1996) Diffusion tensor MR imaging of the human brain. Radiology 201:637–648 10. Rovaris M, Agosta F, Pagani E, Filippi M (2009) Diffusion tensor MR imaging. Neuroimag Clin N Am 19:37–43 11. Tian W, Zhu T, Zhong J, Liu X, Rao P, Segal BM, Ekholm S (2012) Progressive decline in fractional anisotropy on serial DTI examinations of the corpus callosum: a putative marker of disease activity and progression in SPMS. Neuroradiology 54:287–297 12. Sigal T, Shmuel M, Mark D, Gil H, Anat A (2012) Diffusion tensor imaging of corpus callosum integrity in multiple sclerosis: correlation with disease variables. J Neuroimaging 22:33–37 13. Dziedzic T, Metz I, Dallenga T, Ko¨nig FB, Mu¨ller S, Stadelmann C, Bru¨ck W (2010) Wallerian degeneration: a major component of early axonal pathology in multiple sclerosis. Brain Pathol 5:976–985 14. Moll NM, Riietsch AM, Thomas S, Ransohoff AJ, Lee JC, Fox R, Chang A, Ransohoff RM, Fisher E (2011) Multiple sclerosis NAWM: pathology-imaging correlations. Ann Neurol 70:764–773 15. Fillippi M, Rocca M, Barkhof F et al (2012) Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 11:349–360
123
16. Kim DS, Garwood M (2003) High-field magnetic resonance techniques for brain research. Curr Opin Neurobiol 13:612–619 17. Rocca MA, Cercignani M, Iannucci G, Comi G, Filippi M (2000) Weekly diffusion-weighted imaging of normal-appearing white matter in MS. Neurology 55:882–884 18. Ceccarelli A, Rocca M, Falini A, Tortorella P, Pagani E, Rodegher M, Comi G, Scotti G, Filippi M (2007) Normal-appearing white and grey matter damage in MS. a volumetric and diffusion tensor MRI study at 3.0 Tesla. J Neurol 254:513–518 19. Rovaris M, Iannucci G, Falautano M, Possa F, Martinelli V, Comi G, Filippi M (2002) Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 195:103–109 20. Naismith RT (2005) Cross AH multiple sclerosis and black holes: connecting the pixels. Arch Neurol 62:1666–1668 21. Fox RJ, Cronin T, Lin J, Wang X, Sakaie K, Ontaneda D, Mahmoud SY, Lowe MJ, Phillips MD (2011) Measuring myelin repair and axonal loss with diffusion tensor imaging. AJNR Am J Neuroradiol 32:85–91 22. Andrade RE, Gasparetto EL, Cruz LC Jr, Ferreira FB, Domingues RC, Marchiori E, Domingues RC (2007) Evaluation of white matter in patients with multiple sclerosis through diffusion tensor magnetic resonance imaging. Arq Neuropsiquiatr 65:561–564 23. Rueda F, Hygino L, Domingues R, Vasconcelos CC, Papais-Alvarenga RM, Gasparetto EL (2008) Diffusion tensor MR imaging evaluation of the corpus callosum of patients with multiple sclerosis. Arq Neuropsiquiatr 66(3A):449–453 24. Horsfield MA, Larsson HB, Jones DK, Gass A (1998) Diffusion magnetic resonance imaging in multiple sclerosis. J Neurol Neurosurg Psychiatr 64(Suppl 1):S80–84 25. Werring DJ, Brassat D, Droogan AG, Clark CA, Symms MR, Barker GJ, MacManus DG, Thompson AJ, Miller DH (2000) The pathogenesis of lesions and normal-appearing white matter changes in multiple sclerosis. a serial diffusion MRI study. Brain 123:1667–1776 26. Yurtsever I, Hakyemez B, Taskapilioglu O, Erdogan C, Turan OF, Parlak M (2008) The contribution of diffusion-weighted MR imaging in multiple sclerosis during acute attack. Eur J Radiol 65:421–426
