Structural imaging studies of patients with chronic pain: an anatomical likelihood estimate meta-analysis

Henn, Alina T.; Larsen, Bart; Frahm, Lennart; Xu, Anna; Adebimpe, Azeez; Scott, J. Cobb; Linguiti, Sophia; Sharma, Vaishnavi; Basbaum, Allan I.; Corder, Gregory; Dworkin, Robert H.; Edwards, Robert R.; Woolf, Clifford J.; Habel, Ute; Eickhoff, Simon B.; Eickhoff, Claudia R.; Wagels, Lisa; Satterthwaite, Theodore

doi:10.1097/j.pain.0000000000002681

Cited by 15 publications

(14 citation statements)

References 143 publications

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“…The most common indication for scan in the SLIP dataset was headache: the lifelong prevalence of headache is reported at >95% in the general population, and most scans for headache without focal neurological symptoms are unremarkable (Jordan and Flanders 2020). Similarly, research case-control studies of quantitative anatomical MRI phenotypes in headache including migraine have generally been inconclusive (Sheng et al 2021; Henn et al 2022).…”

Section: Discussionmentioning

confidence: 99%

Brain growth charts of “clinical controls” for quantitative analysis of clinically acquired brain MRI

Schabdach

Schmitt

Sotardi

et al. 2023

Preprint

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Background: Brain MRIs acquired in clinical settings represent a valuable and underutilized scientific resource for investigating neurodevelopment. Utilization of these clinical scans has been limited because of their clinical acquisition and technical heterogeneity. These barriers have curtailed the interpretability and scientific value of retrospective studies of clinically acquired brain MRIs, compared to studies of prospectively acquired research quality brain MRIs. Purpose: To develop a scalable and rigorous approach to generate clinical brain growth chart models, to benchmark neuroanatomical differences in clinical MRIs, and to validate clinically-derived brain growth charts against those derived from large-scale research studies. Materials and Methods: We curated a set of clinical MRI Scans with Limited Imaging Pathology (SLIP) - so-called "clinical controls" - from an urban pediatric healthcare system acquired between 2005 and 2020. The curation process included manual review of signed radiology reports, as well as automated and manual quality review of images without gross pathology. We measured global and regional volumetric imaging phenotypes in the SLIP sample using two alternative, advanced image processing pipelines, and quantitatively compared clinical brain growth charts to research brain growth charts derived from >123,000 MRIs. Results: The curated SLIP dataset included 372 patients scanned between the ages of 28 days post-birth and 22.2 years across nine 3T MRI scanners. Clinical brain growth charts were highly similar to growth charts derived from large-scale research datasets, in terms of the normative developmental trajectories predicted by the models. The clinical indication of the scans did not significantly bias the output of clinical brain charts. Tens of thousands of additional healthcare system scans meet inclusion criteria to be included in future brain growth charts. Conclusion: Brain charts derived from clinical-controls are highly similar to brain charts from research-controls, suggesting that curated clinical scans could be used to supplement research datasets.

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Section: Discussionmentioning

confidence: 99%

Brain growth charts of “clinical controls” for quantitative analysis of clinically acquired brain MRI

Schabdach

Schmitt

Sotardi

et al. 2023

Preprint

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“…For thresholding, we applied p < 0.05 family-wise error (FWE) corrected for multiple comparisons for the whole brain. We additionally applied a region-of-interest (ROI) analysis thresholded with p ≤ 0.05 FWE-correction for the ROI, using a composite anatomical mask of brain regions showing reduced GMV in patients with chronic pain according to a recent meta-analysis (Henn et al, 2023). The following regions were included using the ROI tool of the Anatomy Toolbox, version 3 (Eickhoff et al, 2005(Eickhoff et al, , 2007: bilateral amygdala (Amunts et al, 2005), thalamus (Behrens et al, 2003), hippocampus (Amunts et al, 2005), anterior cingulate cortex (Palomero-Gallagher et al, 2015), frontal pole, area Fp2 (Bludau et al, 2014) and insula (Neuromorphometrics).…”

Section: Statistical Analysesmentioning

confidence: 99%

“…However, most studies investigating structural alterations in chronic pain conditions have been done in small groups of subjects, and validation of outcomes is lacking. Henn et al (Henn et al, 2023) recently calculated a comprehensive ALE meta-analysis including a large sample of experiments that fulfilled certain methodological standards (sufficient sample size, control for multiple comparisons, whole-brain analytical approach) across different pain conditions. There were no significant clusters when correcting for multiple comparisons, but using exploratory threshold-free cluster enhancement analyses, there was less GMV in chronic pain in the amygdala, thalamus, hippocampus, insula, anterior cingulate cortex and inferior frontal gyrus.…”

Section: Introductionmentioning

confidence: 99%

“…These may lead to persistent structural changes, which can include an increase or a decrease in the density of synaptic spines, degeneration or regeneration of axons leading to aberrant connectivity, degeneration of neurons and proliferation of astrocytes and microglia (Kuner, 2010). On a macrolevel, grey matter volume changes as well as changes of white matter, cortical thickness and surface have been observed in many studies investigating different chronic pain conditions (for a recent review and ALE‐meta‐analysis using structural neuroimaging data see Henn et al, 2023). Grey matter reorganization could serve as a diagnostic biomarker for chronic pain, if validated and stable as long as the chronic pain persists and if it differs between chronic pain and other negative mood states (Reckziegel et al, 2019) or psychosocial factors (Cohen & Mao, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Chronic pain is associated with less grey matter volume in the anterior cingulum, anterior and posterior insula and hippocampus across three different chronic pain conditions

Neumann

Domín

Schmidt

et al. 2023

European Journal of Pain

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BackgroundChronic pain of different aetiologies and localization has been associated with less grey matter volume (GMV) in several cortical and subcortical brain areas. Recent meta‐analyses reported low reproducibility of GMV alterations between studies and pain syndromes.MethodsTo investigate GMV in common chronic pain conditions defined by body location (chronic back pain, n = 174; migraine, n = 92; craniomandibular disorder, n = 39) compared to controls (n = 296), we conducted voxel‐based morphometry and determined GMV from high‐resolution cranial MRIs obtained in an epidemiologic survey. Mediation analyses were performed between the presence of chronic pain and GMV testing the mediators stress and mild depression. The predictability of chronic pain was investigated with binomial logistic regression.ResultsWhole‐brain analyses yielded reduced GMV within the left anterior insula and the anterior cingulate cortex, for a ROI approach additionally the left posterior insula and left hippocampus showing less GMV across all patients with chronic pain. The relationship of pain with GMV in the left hippocampus was mediated by self‐reported stressors in the last 12 months. Binomial logistic regression revealed a predictive effect for GMV in the left hippocampus and left anterior insula/temporal pole for the presence of chronic pain.ConclusionsChronic pain across three different pain conditions was characterized by less GMV in brain regions consistently described for different chronic pain conditions before. Less GMV in the left hippocampus mediated by experienced stress during the last year might be related to altered pain learning mechanisms in chronic pain patients.SignificanceGrey matter reorganization could serve as a diagnostic biomarker for chronic pain. In a large cohort, we here replicated findings of less grey matter volume across three pain conditions in the left anterior and posterior insula, anterior cingulate and left hippocampus. Less hippocampal grey matter was mediated by experienced stress.

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“…Seventy-five of these addressed potential alterations in gray matter and 20 focused on cortical thickness. (See Henn et al, 2023. )…”

mentioning

confidence: 99%

Does Chronic Pain Alter Brain Structure?

2023

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Structural imaging studies of patients with chronic pain: an anatomical likelihood estimate meta-analysis

Abstract: Supplemental Digital Content is Available in the Text.

Cited by 15 publications

References 143 publications

Brain growth charts of “clinical controls” for quantitative analysis of clinically acquired brain MRI

Brain growth charts of “clinical controls” for quantitative analysis of clinically acquired brain MRI

Chronic pain is associated with less grey matter volume in the anterior cingulum, anterior and posterior insula and hippocampus across three different chronic pain conditions

Does Chronic Pain Alter Brain Structure?

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