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Subcortical structural abnormalities in female neuromyelitis optica patients with neuropathic pain

Published:October 05, 2019DOI:https://doi.org/10.1016/j.msard.2019.101432

      Highlights

      • Providing structural MRI markers to unveil the pathophysiology underlying female NMO patients.
      • The first structural morphology study of NMO patients with pain.
      • Provide new insights for pain mechanism in NMO patients.

      Abstract

      Neuromyelitis optica (NMO) is a disease characterised by severe relapses of optic neuritis and longitudinally extensive transverse myelitis and it has a strong female predilection. Pain is one of the most typical symptom in NMO. However, few studies have been conducted to examine the neuropathic pain mechanism of NMO patients or gender-specific effects using magnetic resonance imaging technique. A total of 38 female patients with NMO, 28 with pain (NMOWP) and 10 without pain (NMOWoP), were classified using the Brief Pain Inventory (BPI); 22 healthy females were also recruited. We used the FSL Image Registration and Segmentation Toolbox (FIRST) for subcortical region volumes quantifications, and voxel-based morphometry analysis for cortical gray matter (GM) volume, to examine the brain morphology in NMOWP patients. In addition, correlation test between structural measurements of NMO patients and clinical indexes was also performed. The results showed: 1) no significant differences in cortical GM density between the NMOWP and NMOWoP groups; 2) significantly smaller hippocampus and pallidum volumes in the NMOWP group compared with the NMOWoP group; 3) significant negative correlation between the average BPI and volumes of the accumbens nucleus and thalamus in NMO patients. These results revealed that structural abnormality exists in NMO female patients who have pain, with significant implications for our understanding of the brain morphology in NMO patients with pain.

      Keywords

      1. Introduction

      Neuromyelitis optica (NMO) is an autoimmune inflammatory demyelinating disorder of the central nervous system that affects the optic nerve and spinal cord (
      • Wingerchuk D.M.
      • Lennon V.A.
      • Pittock S.J.
      • Lucchinetti C.F.
      • Weinshenker B.G.
      Revised diagnostic criteria for neuromyelitis optica.
      ). The current evidence supports a high female predominance in neuromyelitis optica (
      • Kim S.M.
      • Waters P.
      • Woodhall M.
      • Kim Y.J.
      • Kim J.A.
      • Cheon S.Y.
      • Lee S.
      • Jo S.R.
      • Kim D.G.
      • Jung K.C.
      • Lee K.W.
      • Sung J.J.
      • Park K.S.
      Gender effect on neuromyelitis optica spectrum disorder with aquaporin4-immunoglobulin G.
      ;
      • Wingerchuk D.M.
      Neuromyelitis optica: effect of gender.
      ), with a reasonably consistent female to male gender ratio of >3:1 reported from samples of diverse racial and regional populations worldwide (
      • Wingerchuk D.M.
      Neuromyelitis optica: effect of gender.
      ). Female gender has also been reported to be associated with a relapsing course and familial disease (
      • Wingerchuk D.M.
      • Lennon V.A.
      • Lucchinetti C.F.
      • Pittock S.J.
      • Weinshenker B.G.
      The spectrum of neuromyelitis optica.
      ). However, the effect of gender in patients with NMO has not been fully evaluated.
      Patients often describe pain as their most disabling symptom and more than 80% of patients with NMO experience pain (
      • Kanamori Y.
      • Nakashima I.
      • Takai Y.
      • Nishiyama S.
      • Kuroda H.
      • Takahashi T.
      • Kanaoka-Suzuki C.
      • Misu T.
      • Fujihara K.
      • Itoyama Y.
      Pain in neuromyelitis optica and its effect on quality of life: a cross-sectional study.
      ;
      • Simpson A.C.
      Psychology in neuromyelitis optica, transverse myelitis, and multiple sclerosis: a cross-sectional study of fatigue, pain, and depression associated with disability.
      ). A study comparing patients with NMO and multiple sclerosis (MS), another more common central nervous system autoimmune inflammatory disorder, showed that current pain was twice as prevalent and three times more severe in patients with NMO than in a random sample of MS patients. In addition, patients with NMO used four times the amount of pain medication as MS patients (
      • Qian P.
      • Lancia S.
      • Alvarez E.
      • Klawiter E.C.
      • Cross A.H.
      • Naismith R.T.
      Association of neuromyelitis optica with severe and intractable pain.
      ). This polypharmacy does not result in effective management of pain but instead can result in side effects from pain medication, such as cognitive dysfunction and fatigue.
      There is already a lot of evidence to suggest that NMO patients have a large number of structural abnormalities. These studies include the brain biopsy (
      • Pittock S.J.
      • Lennon V.A.
      • Krecke K.
      • Wingerchuk D.M.
      • Lucchinetti C.F.
      • Weinshenker B.G.
      Brain abnormalities in neuromyelitis optica.
      ), clinicopathological results (
      • O'Riordan J.I.
      • Gallagher H.L.
      • Thompson A.J.
      • Howard R.S.
      • Kingsley D.P.
      • Thompson E.J.
      • McDonald W.I.
      • Miller D.H.
      Clinical, CSF, and MRI findings in Devic's neuromyelitis optica.
      ), and brain magnetic resonance imaging (MRI) (
      • Duan Y.Y.
      • Liu Y.
      • Liang P.P.
      • Jia X.Q.
      • Yu C.S.
      • Qin W.
      • Sun H.
      • Liao Z.Y.
      • Ye J.
      • Li K.C.
      Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study.
      ;
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ). For example, NMO was thought to preferentially affect the optic nerves and spinal cord but rarely brain magnetic resonance imaging (MRI) abnormalities (
      • Wingerchuk D.M.
      • Lennon V.A.
      • Pittock S.J.
      • Lucchinetti C.F.
      • Weinshenker B.G.
      Revised diagnostic criteria for neuromyelitis optica.
      ). However, many studies have subsequently shown different abnormalities in the brain MR images of patients with NMO (for a review, please see Barnett et al. (
      • Barnett Y.
      • Sutton I.J.
      • Ghadiri M.
      • Masters L.
      • Zivadinov R.
      • Barnett M.H.
      Conventional and advanced imaging in neuromyelitis optica.
      )). Furthermore, both brain biopsy and clinicopathological results have also shown a variety of brain MRI lesions in patients with NMO (
      • O'Riordan J.I.
      • Gallagher H.L.
      • Thompson A.J.
      • Howard R.S.
      • Kingsley D.P.
      • Thompson E.J.
      • McDonald W.I.
      • Miller D.H.
      Clinical, CSF, and MRI findings in Devic's neuromyelitis optica.
      ;
      • Pittock S.J.
      • Lennon V.A.
      • Krecke K.
      • Wingerchuk D.M.
      • Lucchinetti C.F.
      • Weinshenker B.G.
      Brain abnormalities in neuromyelitis optica.
      ). Recently, voxel-based morphometry (VBM) has been widely used to non-invasively measure longitudinal changes in gray matter (GM) density using MRI in patients with NMO (
      • Chanson J.B.
      • Lamy J.
      • Rousseau F.
      • Blanc F.
      • Collongues N.
      • Fleury M.
      • Armspach J.P.
      • Kremer S.
      • de Seze J.
      White matter volume is decreased in the brain of patients with neuromyelitis optica.
      ;
      • Duan Y.Y.
      • Liu Y.
      • Liang P.P.
      • Jia X.Q.
      • Yu C.S.
      • Qin W.
      • Sun H.
      • Liao Z.Y.
      • Ye J.
      • Li K.C.
      Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study.
      ;
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ). Duan et al. (
      • Duan Y.Y.
      • Liu Y.
      • Liang P.P.
      • Jia X.Q.
      • Yu C.S.
      • Qin W.
      • Sun H.
      • Liao Z.Y.
      • Ye J.
      • Li K.C.
      Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study.
      ) documented regional GM atrophy in the frontal cortex, temporal cortex, right inferior parietal lobule, and right insula of patients with NMO, as compared with controls. When compared with MS patients, significant GM volume atrophy was present in the thalamus, caudate, mammillary bodies, parahippocampal gyrus, right hippocampus, and right insula of NMO patients. Chanson et al. (
      • Chanson J.B.
      • Lamy J.
      • Rousseau F.
      • Blanc F.
      • Collongues N.
      • Fleury M.
      • Armspach J.P.
      • Kremer S.
      • de Seze J.
      White matter volume is decreased in the brain of patients with neuromyelitis optica.
      ) observed volume loss in the thalamus of patients with NMO compared with controls. Using a similar VBM method, Pichiecchio et al. (
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ) found a reduction of GM volume in the motor and visual cortices and regions associated with executive and language functions in patients with NMO versus healthy controls (HCs).
      Although all the studies mentioned above provide evidence for the structural alterations in NMO patients, whether these structural changes are related to the pain of NMO? In factor, accumulating evidence from brain structural imaging studies has supported that chronic pain could induce changes in brain gray matter volume. For example, another chronic pathologic pain disorder such as trigeminal neuralgia (
      • Li M.
      • Yan J.
      • Li S.
      • Wang T.
      • Zhan W.
      • Wen H.
      • Ma X.
      • Zhang Y.
      • Tian J.
      • Jiang G.
      Reduced volume of gray matter in patients with trigeminal neuralgia.
      ) has been detected pain related abnormalities in gray matter volume. Our previous study showed altered pain processing pathways in migraine patients with cutaneous allodynia (
      • Wang T.
      • Chen N.
      • Zhan W.
      • Liu J.
      • Zhang J.
      • Liu Q.
      • Huang H.
      • He L.
      • Zhang J.
      • Gong Q.
      Altered effective connectivity of posterior thalamus in migraine with cutaneous allodynia: a resting-state fMRI study with Granger causality analysis.
      ). However, to our knowledge, no research to date has analyzed structural MRI in NMO patients with pain. Therefore, to examine whether cortical or subcortical abnormalities exist in NMO patients with or without pain, we used the FSL toolbox to examine the brain morphology in NMO patients with pain in the present study. We hypothesized that there are structurally altered regions in NMO patients with pain, and that these regions are located in the pain processing pathways.

      2. Materials and methods

      2.1 Participants

      The study was approved by the Medical Ethics Committee of West China Hospital, Sichuan University. All patients were examined by specialists in neurology and the diagnosis of NMO was based on the revised diagnostic criteria for NMO proposed in 2015 by Wingerchuk et al. (
      • Wingerchuk D.M.
      • Banwell B.
      • Bennett J.L.
      • Cabre P.
      • Carroll W.
      • Chitnis T.
      • de Seze J.
      • Fujihara K.
      • Greenberg B.
      • Jacob A.
      • Jarius S.
      • Lana-Peixoto M.
      • Levy M.
      • Simon J.H.
      • Tenembaum S.
      • Traboulsee A.L.
      • Waters P.
      • Wellik K.E.
      • Weinshenker B.G.
      International consensus diagnostic criteria for neuromyelitis optica spectrum disorders.
      ). All patients were seropositive for aquaporin-4 (AQP4)-IgG. None of the participating patients with NMO had a history of glaucoma, diabetes, or retinal disease, which might otherwise affect MRI measurements, and none of them had been treated with related medications (e.g., corticosteroids and immunosuppressants) within 3 months of the MR images being obtained.
      Thirty eight right-handed female patients with NMO were enrolled in the study. A total 23 of the 38 patients with NMO had experienced optic neuritis (ON). Patients with ON had not experienced an attack at least 3 months prior to scanning. Number of ON episodes were available for a subset of patients. Six patients had typical lesions of NMO. The mean age of these six patients was 39.3 ± 11.4 years (range, 29–60 years). One patient had small lesions in the anterior horn of the bilateral lateral ventricle; another patient had multiple flaky lesions in bilateral optic radiation and bilateral periventricular white matter. A third patient had slight lesions around the bilateral ventricles, three ventricle, and hypothalamus; another patient had multiple flaky lesions around the middle line of the left cerebral frontal lobe, as well as scattered spotted and flaky lesions of the white matter in the bilateral frontal lobe and left parietal lobe. A fifth patient had multiple lesions of the white matter in the right frontal lobe; and the final patient had small abnormal white matter lesions in the genu of the corpus callosum and bilateral ventricular paraventricular white matter. Spinal MRI showed that 32 patients had spinal cord lesions; 24 of these patients had a C or T spinal cord lesion in more than three vertebral segments.
      Twenty two healthy age- and handedness-matched female volunteers with no history of neurologic disorders and normal neurologic examination findings were enrolled as controls. Potential participants were excluded if they had any contraindications to MRI, previous brain injury, any neurologic disorder other than NMO, any psychiatric disorder, or if they had any acute or chronic pain disorder other than NMO.

      2.2 Clinical parameters

      One neurologist (Z.L.) performed the neurologic examinations in all participants and generated the clinical characteristics for each participant. The short form Brief Pain Inventory (BPI) was administrated, to classify all enrolled NMO patients into two groups: NMO patients with pain (NMOWP) or without pain (NMOWoP). The BPI is one of the most widely used tools to assess clinical pain (

      Cleeland, C., 2009. The brief pain inventory user guide.

      ). Patients respond using four numerical rating scales. Each scale is presented as a row of equidistant numbers, where 0 = “no pain” and 10 = “pain as bad as you can imagine”. The four questions focus on 1) the worst pain patients have experienced in the past 24 h, 2) the least amount of pain patients have experienced in the past 24 h, 3) the amount of pain patients experience on average, and 4) the amount of pain patients are currently experiencing while completing the survey. We calculated the BPI score by averaging the four pain severity scores. For all patients, the Kurtzke Expanded Disability Status Scale (EDSS) (
      • Kurtzke J.F.
      Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).
      ) was also administered to quantify disability status. In addition, to evaluate the cognitive ability of patients, Montreal Cognitive Assessment (MoCA) were also administrated among patients. Multiple Sclerosis Quality of Life-54 (MSQOL-54) was used to estimate the patients’ life quality. This 54-item instrument generates 12 subscales and which were then used to calculate two summary scores, i.e. the physical health composite score and the mental health composite score. The former was calculated by the weighted sum of physical function, health perceptions, energy, role limitations-physical, pain, sexual function, social function, and health distress, and measured the physical quality of patients’ life. The later was the weighted sum of health distress, overall quality of life, emotional well-being, role limitations-emotional, and cognitive function, and reflected the mental or emotional health of patients’ life (
      • Stern B.
      • Hojs Fabjan T.
      • Rener-Sitar K.
      • Zaletel-Kragelj L.
      Validation of the Slovenian version of multiple sclerosis quality of life (MSQOL-54) instrument.
      ).

      2.3 Data acquisition

      Imaging of all participants was performed using a GE MR750 3.0T scanner (General Electric, Fairfield, CT, USA) with an eight-channel head coil, located at the University of Electronic Science and Technology of China (UESTC). All participants provided their written informed consent, as required by the Institutional Review Board of UESTC. Tightly padded clamps were used to minimize head motion. The anatomical images were scanned using a T1-weighted three-dimensional (3D) fast spoiled gradient recalled echo. Each anatomical scan has 192 axial slices with the following parameters: spatial resolution = 0.75 mm × 0.75 mm × 1 mm, slice thickness 1.0 mm, no gap, field of view = 256 mm × 256 mm, flip angle 8, repetition time = 5.16 ms, echo time = 1.7 ms, inversion time = 450 ms, receiver bandwidth 31.25 Hz/pixel. We also included other MRI sequences such as T2*-weighted fast gradient recalled echo, fluid attenuation and inversion recovery, susceptibility-weighted imaging, resting state functional MRI, diffusion tensor imaging, spin-echo T2-weighted cube, as per standard protocols, to exclude the presence of other structural lesions or provide data for the follow-up study.

      2.4 Voxel-based morphometry

      Structural data were analyzed with the FMRIB Software Library voxel-based morphometry (FSL-VBM) version 5.0 (
      • Douaud G.
      • Smith S.
      • Jenkinson M.
      • Behrens T.
      • Johansen-Berg H.
      • Vickers J.
      • James S.
      • Voets N.
      • Watkins K.
      • Matthews P.M.
      • James A.
      Anatomically related grey and white matter abnormalities in adolescent-onset schizophrenia.
      ), http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM), following an optimized VBM protocol (
      • Good C.D.
      • Johnsrude I.S.
      • Ashburner J.
      • Henson R.N.
      • Friston K.J.
      • Frackowiak R.S.
      A voxel-based morphometric study of ageing in 465 normal adult human brains.
      ) within FSL tools (
      NeuroImage
      Advances in functional and structural MR image analysis and implementation as FSL.
      ). First, structural images were brain-extracted and GM-segmented before being registered to the MNI 152 standard space (2 mm) using non-linear registration (
      • Andersson J.L.R.
      • Jenkinson M.
      • Smith S.
      Non-Linear Registration, Aka Spatial Normalisation FMRIB Technical Report TR07JA2.
      ). The resulting images were averaged and flipped along the x-axis to create a left-right symmetric, study-specific GM template. Second, all native GM images were non-linearly registered to this study-specific template and "modulated" to correct for local expansion (or contraction) owing to the non-linear component of the spatial transformation. The modulated GM images were then smoothed with an isotropic Gaussian kernel with a sigma of 3.5 mm. Finally, a voxelwise general linear model (GLM) was applied using permutation-based nonparametric testing (5000 permutations), correcting for multiple comparisons across space using the threshold-free cluster enhancement (TFCE), with P values less than 0.05. In addition, to investigate the correlation between BPI as well as the NMO duration and the VBM alteration in the NMOWP group, the analysis was carried out using a GLM with categorical variables as fixed effects, the age, and MoCA score as covariates.

      2.5 FSL-FIRST

      The FSL-Image Registration and Segmentation Toolbox (FSL-FIRST) (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIRST) was used to delineate subcortical structures and measure their volumes (
      • Patenaude B.
      • Smith S.M.
      • Kennedy D.N.
      • Jenkinson M.
      A bayesian model of shape and appearance for subcortical brain segmentation.
      ). The segmented subcortical structures included the bilateral nucleus accumbens, hippocampus, amygdala, caudate, putamen, globus pallidus, and thalamus. The brainstem was excluded because the shape model used in FIRST extended beyond the inferior boundary of the images. Left and right volumes were averaged for each of seven subcortical structures. The averaged volumes were then normalized by dividing the total intracranial volume (TIV, estimated using the SIENAX tool of FSL), which were further used for the group analysis. After automated segmentation using the software, the segmentations were manually checked to confirm the proper segmentation of all the subcortical structures.

      2.6 Statistical analysis

      Independent sample t-tests and Fisher's exact tests were performed for demographic and clinical variables using IBM SPSS version 24.0 (IBM Corp., Armonk, NY, USA), with a significance level of <0.05.
      For the FIRST analysis, group comparison of the segmented subcortical structures was performed using age, EDSS score, physical health composite score, and mental health composite score as covariates of no interest in the statistical design using IBM SPSS software, and the threshold was set at P value less than 0.007 (7 brain regions, corrected for multiple comparisons using Bonferroni correction). Analysis of the relationship between volumes of the structures with BPI and NMO duration was done using Pearson's product-moment correlation, with a significance level of <0.05.

      3. Results

      3.1 Demographic and clinical characteristics

      The mean age among NMO patients and HCs was 44.39 ± 12.12 years and 39.62 ± 9.23 years respectively (Mean ± Standard Deviation). There was no significant difference in age between the NMO and HCs (P = 0.122). Of the total of 38 patients with NMO, 28 were classified as NMOWP and 10 as NMOWoP, according to BPI score. The average BPI score of the NMOWP group was >0 (range, 2–8), and that of the NMOWoP = 0, with a significant difference (P < 0.001) between the two groups. The demographic and clinical characteristics of the two NMO groups are given in Table 1. There were no significant differences in sex, NMO duration, ON duration, EDSS, physical health composite score, and mental health composite score between the two groups (P > 0.05). However, the age and MoCA score difference between the groups was significant (P < 0.05). To avoid the impact of bias caused by age and MoCA score difference, group analyses of the other variables were conducted by adding them as covariates.
      Table 1Demographic and clinical characteristics of NMO patients with pain and without pain.
      CharacteristicsNMO with pain (n = 28)NMO without pain (n = 10)P value
      Age (year, mean ± SD)48.07 ± 10.7134.10±10.000.001
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Sex (female\male)28\010\01
      Fisher's exact test.
      NMO duration (years, mean ± SD)5.32 ± 4.767.07 ± 3.990.307
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      ON duration (years, mean ± SD)3.00 ± 3.633.64 ± 3.970.639
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      BPI (mean ± SD)4.75 ± 2.190.00 ± 0.00<0.001
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      EDSS (mean ± SD)3.59 ± 1.933.35 ± 2.000.741
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      MoCA score (mean ± SD)23.00 ± 3.8426.70 ± 2.310.007
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Physical health composite score (mean ± SD)43.06 ± 18.5557.53 ± 19.820.045
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Mental health composite score (mean ± SD)55.48 ± 17.0764.07 ± 21.950.213
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Sleep quality (mean ± SD)7.61 ± 3.626.60 ± 4.670.489
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Number of episodes of transverse myelitis (mean ± SD)2.86 ± 2.593.50 ± 2.420.498
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Number of myelitis attacks (mean ± SD)5.21 ± 3.976.10 ± 4.460.561
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Time since last episode of transverse myelitis (year, mean ± SD)1.86 ± 1.981.40 ± 1.170.497
      independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.
      Abbreviations: SD, standard deviation; NMO, neuromyelitis optica; ON, optic neuritis; BPI, Brief Pain Inventory; EDSS, Expanded Disability Status Scale; MoCA, Montreal Cognitive Assessment.
      a Fisher's exact test.
      b independent-sample t-test. The time since last episode of transverse myelitis equals the last magnetic resonance examination date minus the last episode date of transverse myelitis.

      3.2 Voxel-based morphometry

      Table 2 summarizes the significant clusters from the VBM analysis. In the comparison of patients with NMO versus HCs, large clusters of decreased GM were found in the occipital lobe (visual processing area, including the bilateral calcarine gyrus, lingual gyrus, left fusiform gyrus, right inferior occipital gyrus), temporal lobe (including the bilateral middle temporal gyrus, right inferior and superior temporal gyrus), and medial frontal cortex (including the bilateral medial superior frontal gyrus, supplementary motor area, middle cingulum, gyrus rectus and left middle frontal gyrus) (Fig. 1A). Significant clusters of higher GM density were found in patients with NMO compared with the HCs (P < 0.01). As shown in Fig. 1B, these regions include many subcortical regions such as the bilateral thalamus and its adjoining regions including the hippocampus, parahippocampal gyrus, brainstem, mammillary bodies, midbrain, and optic tract. Unexpectedly, further subgroup analysis of NMO patients with and without pain demonstrated no significant increases or decreases in cortical GM density, and there was no significant effect of BPI.
      Table 2Brain structures with volumetric alteration in NMO patients, compared with HCs.
      LocationPeak MNIMaximum Z valueCluster size
      NMO patients < HCs
      B Calcarine gyrus, R Cerebelum_Crus1, B Lingual gyrus, L Cerebelum_Crus2, L Cerebelum.6, L Fusiform gyrus0, −90, −60.99976954
      R Middle temporal gyrus, R Inferior temporal gyrus, R Inferior occipital gyrus, R Superior temporal gyrus52, −56, 120.99928282
      B Supplementary motor area, B Middle cingulum0, 8, 460.99916229
      B Medial superior frontal gyrus−2, 58, 100.9968559
      L Middle temporal gyrus−60, −26, −40.9959927
      L Middle frontal gyrus−28, 26, 460.9950717
      B Gyrus rectus2, 36, −240.9940627
      NMO patients > HCs
      R Cerebelum_4_5, R Cerebelum_6, R Cerebelum_3, R Lingual gyrus2, −20, −220.9998649
      L Cerebelum_4_5, L Fusiform gyrus, L Lingual gyrus, L Cerebelum_6, L Cerebelum_3−22, −48, −160.9998386
      B Thalamus, Midbrain, B Brainstem, B Hippocampus, Mammillary bodies, Parahippocampal gyrus, Optic tract
      L Caudate, Midline nucleus12, −30, −20.99982470
      L Caudate, L Putamen−14, 26, 00.9998948
      R Caudate8, 18, 80.9998413
      R Putamen28, −10, 60.9976121
      Suprathreshold voxels after threshold-free cluster enhancement (TFCE)-correction (P < 0.01) for multiple comparisons using voxel-based morphometry analysis between NMO patients and HCs. Abbreviations: HC, healthy controls; MNI, Montreal Neurological Institute; B, bilateral; L, left; R, right.
      Fig 1
      Fig. 1Areas of decreased (blue, A) and increased (red, B) gray matter volume in voxel-based morphometry analysis of patients with neuromyelitis optica (NMO) compared with HCs. B, bilateral; L, left; R, right; GR, gyrus rectus; MTG, middle temporal gyrus; CG, calcarine gyrus; mSFG, medial superior frontal gyrus; MFG, middle frontal gyrus; SMA, supplementary motor area.(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

      3.3 Subcortical structures

      To find differences in the subcortical GM volumes between the NMOWP and NMOWoP groups, we further conducted multivariable subgroup analyses, where the subcortical regions served as the dependent variable; the pain group the fixed factor; and age, EDSS, physical health composite score, and mental health composite score served as covariates. Subcortical structure volume analysis revealed that the NMOWP group had significant enlargement of the hippocampus (P = 0.0012) and globus pallidus (P = 0.001) compared with the NMOWoP group.
      Pearson correlation analysis of the GM volume of subcortical structures and clinical indexes showed that the nucleus accumbens (r = –0.378, P = 0.016) and thalamus (r = –0.322, P = 0.042) were negatively correlated with the average BPI; the hippocampus was positively correlated with the age of NMO patients (r = 0.502, P = 0.001) and negatively correlated with the mental health composite score (r = –0.362, P = 0.022); the globus pallidus was positively correlated (r = 0.398, P = 0.011) and the putamen negatively correlated with the age of NMO patients (r = –0.431, P = 0.006); and the amygdala was positively correlated with the EDSS (r = 0.361, P = 0.022).

      4. Discussion

      Limited studies of anatomical structures have been performed to examine whether structural measurements in NMO patients, with pain or without pain, are altered. What's more, relatively few NMO studies focus specifically upon female. In the present study, we conducted cortical and subcortical GM analysis using MRI data of female NMO patients with and without pain, and correlation analysis of clinical indexes with the structural measurements. The main findings of this study were as follows: 1) there were no significant differences in cortical GM density between the NMOWP and NMOWoP groups; 2) there were significantly smaller hippocampus and pallidum volumes in the NMOWP group than in the NMOWoP group; 3) there was significant negative correlation between the average BPI and volumes of the accumbens nucleus and thalamus in patients with NMO; 4) large areas of significantly altered cortical and subcortical GM density were observed in NMO patients but not in controls, which is consistent with previous MRI studies of patients with NMO (
      • Chanson J.B.
      • Lamy J.
      • Rousseau F.
      • Blanc F.
      • Collongues N.
      • Fleury M.
      • Armspach J.P.
      • Kremer S.
      • de Seze J.
      White matter volume is decreased in the brain of patients with neuromyelitis optica.
      ;
      • Duan Y.Y.
      • Liu Y.
      • Liang P.P.
      • Jia X.Q.
      • Yu C.S.
      • Qin W.
      • Sun H.
      • Liao Z.Y.
      • Ye J.
      • Li K.C.
      Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study.
      ;
      • Filippi M.
      • Rocca M.A.
      • Moiola L.
      • Martinelli V.
      • Ghezzi A.
      • Capra R.
      • Salvi F.
      • Comi G.
      MRI and magnetization transfer imaging changes in the brain and cervical cord of patients with Devic's neuromyelitis optica.
      ).
      The aim of present study was to investigate the pathophysiological mechanisms of pain symptoms in female patients with NMO. For this purpose, we performed cortical GM and subcortical volumetric analysis in NMOWP and NMOWoP patient groups. Although the results revealed no significant alteration of cortical GM density in the two groups, the NMOWP group presented significantly smaller hippocampus and globus pallidus volumes than did the NMOWoP group. Few studies have reported the implication of these two regions in NMO. However, many other pain-related studies have evaluated the role of the hippocampus in pain processing in humans and animals (
      • Bingel U.
      • Quante M.
      • Knab R.
      • Bromm B.
      • Weiller C.
      • Buchel C.
      Subcortical structures involved in pain processing: evidence from single-trial fMRI.
      ;
      • Duric V.
      • McCarson K.E.
      Persistent pain produces stress-like alterations in hippocampal neurogenesis and gene expression.
      ;
      • Schweinhardt P.
      • Lee M.
      • Tracey I.
      Imaging pain in patients: is it meaningful?.
      ;
      • Zimmerman M.E.
      • Pan J.W.
      • Hetherington H.P.
      • Lipton M.L.
      • Baigi K.
      • Lipton R.B.
      Hippocampal correlates of pain in healthy elderly adults a pilot study.
      ). The hippocampus plays an important role in a variety of physiological processes including memory, mood, and stress (
      • Price J.L.
      • Drevets W.C.
      Neurocircuitry of mood disorders.
      ;
      • Zimmerman M.E.
      • Pan J.W.
      • Hetherington H.P.
      • Katz M.J.
      • Verghese J.
      • Buschke H.
      • Derby C.A.
      • Lipton R.B.
      Hippocampal neurochemistry, neuromorphometry, and verbal memory in nondemented older adults.
      ). Neuroimaging studies have shown that the hippocampus is activated in response to painful stimuli in healthy volunteers (
      • Bingel U.
      • Quante M.
      • Knab R.
      • Bromm B.
      • Weiller C.
      • Buchel C.
      Subcortical structures involved in pain processing: evidence from single-trial fMRI.
      ). The function of the globus pallidus is involved in the regulation of voluntary movement. Previous studies have revealed that movement-related activity in the globus pallidus is conveyed to the motor cortex via the thalamus (i.e., GP-thalamic neurons), thereby participating in the control of movement (
      • Nambu A.
      • Yoshida S.
      • Jinnai K.
      Projection on the motor cortex of thalamic neurons with pallidal input in the monkey.
      ,
      • Nambu A.
      • Yoshida S.
      • Jinnai K.
      Movement-related activity of thalamic neurons with input from the globus pallidus and projection to the motor cortex in the monkey.
      ) with the thalamus serving as a relay station of sensory information. Pain is a highly complex and subjective experience that is not only related to nociceptive input but also cognitive and emotional factors. Subcortical structures are substantially involved in different processes that are closely linked to pain processing, e.g., motor preparation, autonomic responses, affective components, and learning (
      • Bingel U.
      • Quante M.
      • Knab R.
      • Bromm B.
      • Weiller C.
      • Buchel C.
      Subcortical structures involved in pain processing: evidence from single-trial fMRI.
      ). Therefore, it is highly probable that the involvement of the hippocampus and globus pallidus in NMO patients with pain can be attributed to the negative emotional processing associated with pain. Furthermore, the correlation analysis in the present study showed that the hippocampus is negatively correlated with the mental health composite score of NMO patients, which provides evidence of hippocampus involvement in the emotional processing of pain. A commonly reported region in pain processing and modulation (
      • Bingel U.
      • Tracey I.
      Imaging CNS modulation of pain in humans.
      ), no significant volumetric alteration in the amygdala was observed in the present study; however, correlation analysis showed that the amygdala is positively correlated with EDSS score, which is used to quantify disability in patients with NMO. In summary, structural abnormality of the hippocampus, globus pallidus, and amygdala in NMO patients may be associated with the emotional component of pain processing.
      Pearson correlation analysis revealed that the GM volume of the nucleus accumbens and thalamus was negatively correlated with the average BPI. This indicates that the severer the pain in NMO patients, the smaller the volume of the nucleus accumbens and thalamus. As mentioned above, the thalamus acts a relay station of sensory input, and it is at the center of the pain modulation pathway. Therefore, the involvement of the thalamus in NMO patients with pain is reasonable. The nucleus accumbens in combination with the olfactory tubercle form the ventral striatum. The nucleus accumbens is anatomically connected with the thalamus. The nucleus accumbens projects to the medial dorsal nucleus of the dorsal thalamus through the globus pallidus, and the dorsal thalamus in turn projects to the prefrontal cortex as well as the striatum (
      • Salgado S.
      • Kaplitt M.G.
      The nucleus accumbens: a comprehensive review.
      ). Therefore, it is highly probable that the nucleus accumbens, globus pallidus, and the thalamus share the same pain modulation pathway, implicating these structures in the emotional component of pain processing. However, further study is needed to provide evidence for this inference, including functional or effective connectivity analysis based on regions of interest (the nucleus accumbens, globus pallidus, and thalamus).
      We found substantial cortical structural alteration in NMO patients compared with the HCs. This result is consistent with those of previous studies that have described neuroimaging abnormalities in normal-appearing GM in NMO (
      • Duan Y.Y.
      • Liu Y.
      • Liang P.P.
      • Jia X.Q.
      • Yu C.S.
      • Qin W.
      • Sun H.
      • Liao Z.Y.
      • Ye J.
      • Li K.C.
      Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study.
      ;
      • Eshaghi A.
      • Wottschel V.
      • Cortese R.
      • Calabrese M.
      • Sahraian M.A.
      • Thompson A.J.
      • Alexander D.C.
      • Ciccarelli O.
      Gray matter MRI differentiates neuromyelitis optica from multiple sclerosis using random forest.
      ;
      • Hyun J.W.
      • Park G.
      • Kwak K.
      • Jo H.J.
      • Joung A.
      • Kim J.H.
      • Lee S.H.
      • Kim S.
      • Lee J.M.
      • Kim S.H.
      • Kim H.J.
      Deep gray matter atrophy in neuromyelitis optica spectrum disorder and multiple sclerosis.
      ;
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ). The abnormal regions encompass the motor (including the bilateral medial superior frontal gyrus, supplementary motor area, middle cingulum, gyrus rectus, and left middle frontal gyrus), sensory (including the bilateral medial superior frontal gyrus, supplementary motor area, middle cingulum, gyrus rectus, and left middle frontal gyrus), and visual (including the bilateral calcarine gyrus, lingual gyrus, fusiform gyrus, right inferior occipital gyrus) pathways. There were also clusters of increased GM density in subcortical regions, such as the bilateral thalamus, and its adjoining regions including the hippocampus, parahippocampal gyrus, brainstem, mammillary bodies, midbrain, caudate, optic tract, and midline nucleus. The motor and visual cortex are usually implicated in NMO. This is understandable, because NMO is an idiopathic inflammatory demyelinating disorder that is thought to preferentially affect the optic nerves and spinal cord (
      • Barnett Y.
      • Sutton I.J.
      • Ghadiri M.
      • Masters L.
      • Zivadinov R.
      • Barnett M.H.
      Conventional and advanced imaging in neuromyelitis optica.
      ). In consistent with us, Pichiecchio (
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ) reported a significant density and volume reduction of the sensorimotor cortex and visual cortex, which may be attributed to anterograde degeneration of the specific pathways deriving from the macroscopically damaged optic nerve. Furthermore, in the present study, we found abnormality in the optic tract, which is directly correlated with visual processing. As for the thalamus and its adjoining regions, in accordance with our study, Hyun and colleagues (
      • Hyun J.W.
      • Park G.
      • Kwak K.
      • Jo H.J.
      • Joung A.
      • Kim J.H.
      • Lee S.H.
      • Kim S.
      • Lee J.M.
      • Kim S.H.
      • Kim H.J.
      Deep gray matter atrophy in neuromyelitis optica spectrum disorder and multiple sclerosis.
      ) reported mild regional reductions in the thalamic volume of patients with NMO versus HCs. Lesions within the thalamus are typically described in patients with NMO (
      • Nakajima H.
      • Fujiki Y.
      • Ito T.
      • Kitaoka H.
      • Takahashi T.
      Anti-aquaporin-4 antibody-positive neuromyelitis optica presenting with syndrome of inappropriate antidiuretic hormone secretion as an initial manifestation.
      ;
      • Pichiecchio A.
      • Tavazzi E.
      • Poloni G.
      • Ponzio M.
      • Palesi F.
      • Pasin M.
      • Piccolo L.
      • Tosello D.
      • Romani A.
      • Bergamaschi R.
      • Piccolo G.
      • Bastianello S.
      Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach.
      ;
      • von Glehn F.
      • Jarius S.
      • Cavalcanti Lira R.P.
      • Alves Ferreira M.C.
      • von Glehn F.H.
      • Costa E.C.S.M.
      • Beltramini G.C.
      • Bergo F.P.
      • Farias A.S.
      • Brandao C.O.
      • Wildemann B.
      • Damasceno B.P.
      • Cendes F.
      • Santos L.M.
      • Yasuda C.L.
      Structural brain abnormalities are related to retinal nerve fiber layer thinning and disease duration in neuromyelitis optica spectrum disorders.
      ). The thalamic volume loss in NMO may be attributed to thalamic lesions in some NMO patients who were recruited in their study. Eshaghi and colleagues (
      • Eshaghi A.
      • Wottschel V.
      • Cortese R.
      • Calabrese M.
      • Sahraian M.A.
      • Thompson A.J.
      • Alexander D.C.
      • Ciccarelli O.
      Gray matter MRI differentiates neuromyelitis optica from multiple sclerosis using random forest.
      ) used brain GM imaging measures to distinguish NMO from MS. Those authors showed that volumes of the parahippocampal gyri and left middle frontal gyrus were smaller in patients with NMO as compared with HCs, and serve as the most important variables for this classification. These findings suggest that significant brain structural abnormality exists in patients with NMO.
      Participant age may have led to some heterogeneity in our results. In the present study, NMOWP patients were older than NMOWoP ones. Although we regressed the age factor in our GM imaging analysis, we are still unsure whether age affected our findings. Although correlation analysis showed that volumes of both the hippocampus and globus pallidus were significantly positively correlated with age, deep GM volumetric analysis showed that NMOWP patients had smaller volumes in these regions than NMOWoP patients. Therefore, it seems that regression of the age covariance decreased the heterogeneity owing to age, to some extent.
      There are several limitations in the present study. First, there were nearly three times as many NMOWP patients as NMOWoP patients, so the proportions were not at the suggested 1:1 ratio. Because pain is the most common symptom in patients with NMO, more patients in this group are needed to balance the proportion of participants. Second, two patients had GM lesions in cortical regions, such as the frontal and parietal lobe, which may affect the results of VBM analysis, although no cortical regions remained after TFCE correction in the comparison of NMOWP versus NMOWoP patients. In future studies, patients with GM lesions should be excluded when there is a large patient sample size. Finally, the current report is a cross-sectional study. Whether abnormalities of the structures are altered by pain remains unclear; therefore, futher longitudinal investigation is needed.

      5. Conclusions

      In summary, without the interference of gender, we found subcortical, but not cortical, morphological alterations in NMO female patients with pain. Moreover, the average BPI, a widely used pain measurement toolbox, was negatively correlated with volumes of the accumbens nucleus and thalamus in patients with NMO. These results have significant implications for the understanding of brain morphology in NMO patients with pain.

      6. Ethics statement

      This study was carried out in accordance with the recommendations of Institutional Review Board of University of Electronic Science and Technology of China with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The study was also approved by the Medical Ethics Committee of West China Hospital, Sichuan University.

      Declaration of Competing Interest

      The authors declare that they have no conflicts of interest regarding the publication of this paper.

      Acknowledgments

      This work was supported by National Natural Science Foundation [grant number 61806029], the Chengdu University of Information Engineering Research Fund [grant number KYTZ201719], and the Project of Sichuan Provincial Education Hall [grant number 18ZA0089, 2018Z065].

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