Delineation between different components of chronic pain using dimension reduction – an ASL fMRI ASL fMRI study in hand osteoarthritis

摘要

Abstract Background Traditional psychometric measures aimed at characterizing the pain experience often show considerable overlap, due to interlinked affective and modulatory processes under central nervous system control. Neuroimaging studies have been employed to investigate this complexity of pain processing, in an attempt to provide a quantifiable, adjunctive description of pain perception. In this exploratory study, we examine psychometric and neuroimaging data from 38 patients with painful osteoarthritis of the carpometacarpal joint. We had two aims: first, to utilize principal component analysis ( PCA ) as a dimension reduction strategy across multiple self‐reported endpoints of pain, cognitive and affective functioning; second, to investigate the relationship between identified dimensions and regional cerebral blood flow ( rCBF ) as an indirect measure of brain activity underpinning their ongoing pain experiences. Methods Psychometric data were collected using validated questionnaires. Quantitative estimates of rCBF were acquired using pseudo‐continuous arterial spin‐labelled functional magnetic resonance imaging. Results Two principal components were identified that accounted for 73% of data variance; one related to pain scores and a second to psychological traits. Voxel‐wise multiple regression analysis revealed a significant negative association between the ‘pain score’ component and rCBF to a right temporal lobe cluster, including the amygdala and the parahippocampal cortex. Conclusion We suggest this association may represent a coping mechanism that aims to reduce fear‐related pain‐anxiety. Further investigation of central brain processing mechanisms in osteoarthritis‐related pain may offer insights into more effective therapeutic strategies. Significance This study demonstrates that dimension reduction using PCA allows insight into pain perception and its affective components in relation to brain activation patterns in patients with painful hand osteoarthritis.