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Research Article: Study Protocol Systematic Review

Cortical thickness in chronic pain

A protocol for systematic review and meta-analysis

Ma, HaiRong MDa; Sheng, LiQin MDa; Chen, Fei MDb; Yuan, CongHu MDc; Dai, ZhenYu MDb; Pan, PingLei MDd,e,∗

Author Information
doi: 10.1097/MD.0000000000021499
  • Open

Abstract

1 Introduction

Chronic pain (CP) is defined as pain that persists or recurs for more than 3 months.[1,2] CP is highly prevalent worldwide and has emerged as a major global public health.[3,4] CP adversely affects a person's physical function and quality of life and causes a substantial societal economic burden.[3,4] Although CP is heterogeneous in forms and in etiologies; there is convergent evidence that CP may share a common pathophysiology associated with central nervous system reorganizations. Numerous studies using a variety of non-invasive neuroimaging techniques in vivo have demonstrated CP-related brain alterations in the neurochemical profile, regional gray matter (GM), regional spontaneous activity, functional connectivity and networks.[5–16] The key altered brain areas, including the sensorimotor, prefrontal, cingulate, and insular cortices in the sensorimotor network, default mode network, and salience network, were not only involved in sensory processing, but also in cognitive-affective processing, which have helped us to understand the maladaptive neurobiological mechanisms leading to the development of CP.[17]

Cortical thickness (CTh) via surface-based morphometry (SBM) analysis of high-resolution 3-dimensional anatomical magnetic resonance imaging (MRI) data is a valid method to study the structure of brain GM.[18] Compared to voxel-based morphometry (VBM) that provides a mixed measure of GM including cortical surface area or cortical folding as well as cortical thickness,[18] SBM may be more sensitive to detect subtle brain structural differences between groups.[18,19] VBM and SBM are complementary methods for the observation of brain morphometry.[18,20,21] Several meta-analyses of VBM studies have shown consistent evidence of GM volume/density alterations in CP.[5–10,22,23] In the last decade, increasing studies have employed SBM to measure CTh difference between patients with CP and pain-free controls and provided important insights into the brain basis of CP. However, the findings from these studies were inconsistent and have not been quantitatively reviewed. It remains unknown whether CP with different subtypes shares common CTh alterations and what the pattern of its characterized alterations is. For this purpose, meta-analysis is essential for the synthesis of the findings from these CTh studies.

Coordinate-based meta-analysis (CBMA) is a useful technique to detect consistency of brain alterations across neuroimaging studies in a particular disorder for a specific question. In the present study, we will use Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)[24,25] to perform this CBMA of CTh studies in CP.

2 Methods

2.1 Literature search strategies

Three major electronic medical databases: PubMed, Web of Science, and Embase were searched for eligible studies published in English from each database's inception to April 3, 2020. The following terms were used for the searches: ((chronic pain) OR (chronic myofascial pain) OR (chronic headache∗) OR (chronic migraine∗) OR (burning mouth syndrome) OR (temporomandibular joint disorder∗) OR (neck pain) OR (shoulder pain) OR (phantom limb pain) OR (chronic thoracic pain) OR (chronic chest pain) OR (chronic back pain) OR (chronic knee pain) OR (chronic ankle pain) OR (chronic epicondylalgia∗) OR (chronic abdominal pain) OR (chronic visceral pain) OR (chronic pelvic pain syndrome) OR (neuropathic pain) OR (trigeminal neuralgia) OR neuralgia OR (postherpetic neuralgia) OR (complex regional pain syndrome) OR fibromyalgia OR (ankylosing spondylitis) OR (chronic epigastric pain syndrome) OR (irritable bowel syndrome) OR (inflammatory bowel disease) OR (Crohn disease) OR (chronic bladder pain syndrome) OR (chronic testicular pain) OR (functional dyspepsia) OR (musculoskeletal pain) OR (chronic widespread pain) OR (chronic whiplash-associated disorder) OR arthritis OR (somatoform pain) AND ((cortical thickness) OR (cortical thinning) OR (surface-based morphometry)). Neither article language nor publication time was limited. In addition, manual searches were conducted within the reference lists of the included studies and any relevant review articles.

This protocol was prepared based on the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P).[26]

2.2 Eligibility criteria

2.2.1 Inclusion criteria

The studies have to meet the following inclusion criteria:

  • (1) studies that investigated regional CTh differences between patients with CP and matched pain-free controls at the whole-brain cortical level;
  • (2) studies with non-significant results and studies with significant findings that reported brain clusters in standard Montreal Neurological Institute (MNI) or Talairach space;
  • (3) an original article published in English in a peer-reviewed journal.

2.2.2 Exclusion criteria

Publications will be excluded if:

  • (1) the sample size was fewer than 7 either in the CP group or the pain-free group;
  • (2) three-dimensional coordinates of significant CTh results were not reported;
  • (3) the studies only employed regions of interest analysis or global CTh analysis;
  • (4) a direct pain-free compassion group was lacked;
  • (5) the patient sample was overlapped with the another one with a larger sample size;
  • (6) no baseline comparison was performed in case of a longitudinal study;
  • (7) the pain duration was less than 3 months;
  • (8) studies investigated experimental pain or acute pain;
  • (9) the publications were conference abstracts, research protocols, case reports, letters, reviews, and editorials.

Figure 1 presents the flowchart of study selection following the PRISMA.[27]

Figure 1
Figure 1:
Flowchart of study selection following the PRISMA. CTh = cortical thickness, HC = healthy control, PRISMA = Preferred Reporting Items for Systematic review and Meta-Analysis, ROI = region of interest.

2.3 Data extraction

Data abstracted from the eligible studies will be: the first author's name, year of publication, sample size, age, sex distribution, CP subtype, pain duration, pain intensity, magnetic resonance imaging (MRI) scanner manufacturer and platform, field strength, head coil, MRI sequence, repetition time (TR)/echo time (TE), voxel size, imaging processing software package, smooth kernel, statistical model, covariate, statistical threshold, peak coordinates, height of the peaks (t-values, z-values, or P-values), their stereotactic reference space (MNI or Talairach), and quality control.

2.4 Quality assessment

Quality assessment of each included study will be performed using a 12-point checklist based on a previous CTh meta-analysis (details in Table 1).[28] The items utilized for the quality assessment were categorized into 3 parts: subjects (4 points), methods for imaging acquisition and analysis (5 points), and results and conclusions (3 points).

Table 1
Table 1:
The checklist of quality assessment for the included cortical thickness studies.

Two investigators will independently perform literature search, study selection, data extraction, and quality assessment. Any disagreements will be resolved by a consensus-based discussion.

2.5 Main coordinate-based meta-analysis (CBMA)

The SDM-PSI software package (version 6.21, https://www.sdmproject.com/) will be employed to conducted this main CBMA to identify consistent CTh differences between patients with CP and pain-free controls. The detailed processing steps can be found in the SDM-PSI reference manual (https://www.sdmproject.com/manual/) and other publications.[24,25,29] To obtain the meta-analytic results, a correction for multiple comparison: threshold-free cluster enhancement family wise error rate (TFCE FWER) with a P < .05 and a minimum cluster size ≥ 10 voxels, will be utilized.[24,25]

2.6 Reliability analysis

Sensitivity analysis will be conducted to assess the stability of the results identified in the main CBMA.

Heterogeneity analysis of significant results will be performed using the I2 statistic.

Publication bias will be examined using the Egger test.[30] A threshold at P < .05 will be considered significant.

2.7 Subgroup analysis

Subgroup CBMA will be performed in clinical subtypes, different MRI field strengths (3.0T and 1.5T MRI), and different software packages for CTh analysis if the corresponding number of the datasets is sufficient (n ≥ 10).

2.8 Meta-regression analysis

Meta-regression analyses will be carried out to examine if regional CTh alterations across studies were confounded by age, gender, pain duration, and pain intensity if they were available from at least 10 datasets. Threshold-free cluster enhancement family wise error rate (TFCE FWER) with a P < .05 and a minimum cluster size ≥ 10 voxels will be employed to determine statistical significance.[24,25]

2.9 Ethics and dissemination

Because we will use data from published studies, no Ethics approval or patient consent is required in this meta-analysis. We will publish the results of this meta-analysis in a peer-reviewed scientific journal.

3 Discussion

To the best of our knowledge, this will be the first CBMA of SBM studies that characterizes brain CTh alterations in CP. The reliability and reproducibility of the results from neuroimaging research have been increasingly concerned.[31] Many confounding factors, such as small sample size, variety in sample characters and etiologies, and differences in magnetic resonance imaging (MRI) scanner manufacturer and platform, field strength, imaging data acquisition parameter, imaging processing software package, smooth kernel, statistical model, covariate, and statistical threshold used, may cause the low reliability and reproducibility. Further investigations are necessary to reduce these impacts. This CBMA will provide quantitative evidence of common brain cortical morphometry of CP. The findings will help us to understand the neural basis underlying CP.

Author contributions

Conceptualization: HaiRong Ma, ZhenYu Dai, PingLei Pan

Data curation: HaiRong Ma, LiQin Sheng

Formal analysis: HaiRong Ma, LiQin Sheng

Funding acquisition: PingLei Pan

Investigation: HaiRong Ma, LiQin Sheng, Fei Chen

Methodology: LiQin Sheng, CongHu Yuan

Project administration: Fei Chen

Resources: LiQin Sheng, Fei Chen, CongHu Yuan

Software: LiQin Sheng

Supervision: ZhenYu Dai

Validation: Fei Chen, PingLei Pan

Visualization: LiQin Sheng, HaiRong Ma

Writing – original draft: HaiRong Ma

Writing – review & editing: ZhenYu Dai, PingLei Pan

References

[1]. Treede RD, Rief W, Barke A, et al. Chronic pain as a symptom or a disease: the IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11). Pain 2019;160:19–27.
[2]. Treede RD, Rief W, Barke A, et al. A classification of chronic pain for ICD-11. Pain 2015;156:1003–7.
[3]. Fayaz A, Croft P, Langford RM, et al. Prevalence of chronic pain in the UK: a systematic review and meta-analysis of population studies. BMJ Open 2016;6:e010364:1-12.
[4]. Goldberg DS, McGee SJ. Pain as a global public health priority. BMC Public Health 2011;11:770:1-5.
[5]. Smallwood RF, Laird AR, Ramage AE, et al. Structural brain anomalies and chronic pain: a quantitative meta-analysis of gray matter volume. J Pain 2013;14:663–75.
[6]. Cauda F, Palermo S, Costa T, et al. Gray matter alterations in chronic pain: a network-oriented meta-analytic approach. Neuroimage Clin 2014;4:676–86.
[7]. Pan PL, Zhong JG, Shang HF, et al. Quantitative meta-analysis of grey matter anomalies in neuropathic pain. Eur J Pain 2015;19:1224–31.
[8]. Shi H, Yuan C, Dai Z, et al. Gray matter abnormalities associated with fibromyalgia: a meta-analysis of voxel-based morphometric studies. Semin Arthritis Rheum 2016;46:330–7.
[9]. Yuan C, Shi H, Pan P, et al. Gray matter abnormalities associated with chronic back pain: a meta-analysis of voxel-based morphometric studies. Clin J Pain 2017;33:983–90.
[10]. Tatu K, Costa T, Nani A, et al. How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study. Neuroimage Clin 2018;18:15–30.
[11]. Yin Y, He S, Xu J, et al. The neuro-pathophysiology of temporomandibular disorders-related pain: a systematic review of structural and functional MRI studies. J Headache Pain 2020;21:78:1-20.
[12]. Schmidt-Wilcke T. Neuroimaging of chronic pain. Best Pract Res Clin Rheumatol 2015;29:29–41.
[13]. Malfliet A, Coppieters I, Van Wilgen P, et al. Brain changes associated with cognitive and emotional factors in chronic pain: a systematic review. Eur J Pain 2017;21:769–86.
[14]. Pfannmöller J, Lotze M. Review on biomarkers in the resting-state networks of chronic pain patients. Brain Cogn 2019;131:4–9.
[15]. Zhao X, Xu M, Jorgenson K, et al. Neurochemical changes in patients with chronic low back pain detected by proton magnetic resonance spectroscopy: a systematic review. Neuroimage Clin 2017;13:33–8.
[16]. Levins KJ, Drago T, Roman E, et al. Magnetic resonance spectroscopy across chronic pain disorders: a systematic review protocol synthesising anatomical and metabolite findings in chronic pain patients. Syst Rev 2019;8:338:1-7.
[17]. Davis KD, Flor H, Greely HT, et al. Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations. Nat Rev Neurol 2017;13:624–38.
[18]. Hutton C, Draganski B, Ashburner J, et al. A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging. Neuroimage 2009;48:371–80.
[19]. Lai KL, Niddam DM, Fuh JL, et al. Cortical morphological changes in chronic migraine in a Taiwanese cohort: surface- and voxel-based analyses. Cephalalgia 2020;40:575–85.
[20]. Wolf RC, Hildebrandt V, Schmitgen MM, et al. Aberrant gray matter volume and cortical surface in paranoid-type delusional disorder. Neuropsychobiology 2020;79:335–44.
[21]. Wu Y, Wu X, Wei Q, et al. Differences in cerebral structure associated with depressive symptoms in the elderly with Alzheimer's disease. Front Aging Neurosci 2020;12:107:1-8.
[22]. Lin C, Lee SH, Weng HH. Gray matter atrophy within the default mode network of fibromyalgia: a meta-analysis of voxel-based morphometry studies. Biomed Res Int 2016;2016:7296125:1-9.
[23]. Tench CR, Tanasescu R, Constantinescu CS, et al. Coordinate based random effect size meta-analysis of neuroimaging studies. Neuroimage 2017;153:293–306.
[24]. Albajes-Eizagirre A, Solanes A, Fullana MA, et al. Meta-analysis of voxel-based neuroimaging studies using seed-based d mapping with permutation of subject images (SDM-PSI). J Vis Exp 2019;27:153:e59841:1-7.
[25]. Albajes-Eizagirre A, Solanes A, Vieta E, et al. Voxel-based meta-analysis via permutation of subject images (PSI): theory and implementation for SDM. Neuroimage 2019;186:174–84.
[26]. Shamseer L, Moher D, Clarke M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 2015;350:g7647:1-25.
[27]. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009;6:e1000097:1-6.
[28]. Li Q, Zhao Y, Chen Z, et al. Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder. Neuropsychopharmacology 2020;45:703–12.
[29]. Dahlgren K, Ferris C, Hamann S. Neural correlates of successful emotional episodic encoding and retrieval: an SDM meta-analysis of neuroimaging studies. Neuropsychologia 2020;143:107495:1-19.
[30]. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629–34.
[31]. Nichols TE, Das S, Eickhoff SB, et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat Neurosci 2017;20:299–303.
Keywords:

chronic pain; coordinate-based meta-analysis; cortical thickness; gray matter; seed-based d mapping with permutation of subject images

Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc.