Altered Dynamic Brain Connectivity in Individuals With Sickle Cell Disease and Chronic Pain Secondary to Hip Osteonecrosis

Abstract

Individuals with sickle cell disease (SCD) exhibit changes in static brain connectivity in rest. However, little known as chronic pain associated with hip osteonecrosis affects dynamic brain connectivity during rest and the motor imagery task. The aim of this study was to investigate the characteristics of the dynamic functional brain connectivity of individuals with SCD and chronic pain secondary to hip osteonecrosis. This is a cross-sectional study comparing the dynamic brain connectivity of healthy individuals (n = 18) with the dynamic brain connectivity of individuals with SCD and chronic pain (n = 22). Individuals with SCD and chronic pain were stratified into high- or low-intensity pain groups based on pain intensity at the time of assessment. Dynamic brain connectivity was assessed through electroencephalography in 3 stages, resting state with eyes closed, and during hip (painful for the SCD individuals) and hand (control, nonpainful) motor imagery. Average weight of the edges and full synchronization time (FST)—time required for 95% of the possible edges to appear over time during a given task—were evaluated. Regarding the average weight of the edges, individuals with SCD and high-intensity pain presented higher edge weight during hip motor imagery. The average weight of the edges correlated positively with pain intensity and depression symptoms. Individuals with SCD and chronic pain complete the cerebral network at rest more quickly (lower FST). Individuals with SCD and chronic pain/hip osteonecrosis have impaired dynamic brain network with shorter FST in rest network and more pronounced diffuse connectivity in individuals with high-intensity pain. The dynamic brain network evaluated by time-varying graphs and motif synchronization was able to identify differences between groups.

Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review

“… 102 Another cross-sectional study observed a lower “full synchronization time” (described as the time required for a network to become approximately complete) in sickle cell patients with chronic hip pain. 95 In a longitudinal study examining changes in brain activity following multimodal pain therapy, a correlation between pain decrease and theta global efficiency increase was observed. 37 A longitudinal neurofeedback study found negative correlations of changes in pain with fractional occupancy, mean dwell times, and transition probability from low to high alpha state.…”

“…Finally, 76 studies were included. 1 , 5 – 8 , 10 , 11 , 15 , 16 , 18 – 27 , 30 – 33 , 35 , 37 – 49 , 51 , 56 , 59 , 60 , 63 , 66 – 69 , 74 – 76 , 79 , 80 , 82 , 89 – 91 , 95 – 98 , 100 – 105 , 109 , 110 , 112 – 115 , 120 , 122 , 124 – 126 Figure 1 depicts the PRISMA flow diagram of study selection along with reasons for study exclusion at every stage.…”

Translational Applications of Neuroimaging

“…More importantly, it allows us to track the trajectory of pain development after applying certain therapies. This stratification of patients could serve to guide and inform future treatment and adds an additional quantitative objective measure of pain (Thibaut et al, 2017;Ahn et al, 2019;Yüksel et al, 2019;Santana et al, 2021;.…”

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

“…More importantly, it allows us to track the trajectory of pain development after applying certain therapies. This stratification of patients could serve to guide and inform future treatment and adds an additional quantitative objective measure of pain ( Thibaut et al, 2017 ; Ahn et al, 2019 ; Yüksel et al, 2019 ; Santana et al, 2021 ; Heitmann et al, 2022 ).…”