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A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions.

ABSTRACT: Identification of predictive neuroimaging markers of pain intensity changes is a crucial issue to better understand macroscopic neural mechanisms of pain. Although a single connection between the medial prefrontal cortex and nucleus accumbens has been suggested as a powerful marker, how the complex interactions on a large-scale brain network can serve as the markers is underexplored. Here, we aimed to identify a set of functional connections predictive of longitudinal changes in pain intensity using large-scale brain networks. We re-analyzed previously published resting-state functional magnetic resonance imaging data of 49 subacute back pain (SBP) patients. We built a network-level model that predicts changes in pain intensity over one year by combining independent component analysis and a penalized regression framework. Connections involving top-down pain modulation, multisensory integration, and mesocorticolimbic circuits were identified as predictive markers for pain intensity changes. Pearson's correlations between actual and predicted pain scores were r?=?0.33-0.72, and group classification results between SBP patients with persisting pain and recovering patients, in terms of area under the curve (AUC), were 0.89/0.75/0.75 for visits four/three/two, thus outperforming the previous work (AUC 0.83/0.73/0.67). This study identified functional connections important for longitudinal changes in pain intensity in SBP patients, providing provisional markers to predict future pain using large-scale brain networks.

SUBMITTER: Park BY

PROVIDER: S-EPMC7567066 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions.

Park Bo-Yong BY Lee Jae-Joong JJ Kim Hong Ji HJ Woo Choong-Wan CW Park Hyunjin H

Scientific reports 20201015 1

Identification of predictive neuroimaging markers of pain intensity changes is a crucial issue to better understand macroscopic neural mechanisms of pain. Although a single connection between the medial prefrontal cortex and nucleus accumbens has been suggested as a powerful marker, how the complex interactions on a large-scale brain network can serve as the markers is underexplored. Here, we aimed to identify a set of functional connections predictive of longitudinal changes in pain intensity u ...[more]

PMID: 33060726

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Project description:Back pain represents a substantial burden globally, ranking first in a recent assessment among causes of years lived with disability. Though back pain is widely studied among working age adults, there are gaps with respect to basic descriptive epidemiology among seniors, especially in the United States. Our goal was to describe how pain, function and health-related quality of life vary by demographic and geographic factors among seniors presenting to primary care providers with new episodes of care for back pain.We examined baseline data from the Back pain Outcomes using Longitudinal Data (BOLD) registry, the largest inception cohort to date of seniors presenting to a primary care provider for back pain. The sample included 5,239 patients ? 65 years old with a new primary care visit for back pain at three integrated health systems (Northern California Kaiser-Permanente, Henry Ford Health System [Detroit], and Harvard Vanguard Medical Associates [Boston]). We examined differences in patient characteristics across healthcare sites and associations of patient sociodemographic and clinical characteristics with baseline patient-reported measures of pain, function, and health-related quality of life.Patients differed across sites in demographic and other characteristics. The Detroit site had more African-American patients (50%) compared with the other sites (7-8%). The Boston site had more college graduates (68%) compared with Detroit (20%). Female sex, lower educational status, African-American race, and older age were associated with worse functional disability as measured by the Roland-Morris Disability Questionnaire. Except for age, these factors were also associated with worse pain.Baseline pain and functional impairment varied substantially with a number of factors in the BOLD cohort. Healthcare site was an important factor. After controlling for healthcare site, lower education, female sex, African-American race, and older age were associated with worse physical disability and all of these factors except age were associated with worse pain.Clinical Trials.gov NCT01776242; Registration date: June 13, 2012.

Dataset Information

A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions.

Publications

A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions.

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