RESUMO
Background: Chronic low back pain (cLBP) has been associated with alterations in brain functional connectivity (FC) but based upon heterogeneous populations and single network analyses. Our goal is to study a more homogeneous cLBP population and focus on multiple cross-network (CN) connectivity analysis. We hypothesize that within this population: 1) altered CN FC, involving emotion and reward/aversion functions are related to their pain levels and 2) altered relationships are dependent upon pain phenotype (constant neuropathic vs intermittent pain). Methods: In this case series, resting state fcMRI scans were obtained over a study duration of 60 months from 23 patients (13 constant neuropathic and 10 intermittent pain) with Persistent Spinal Pain Syndrome (PSPS Type 2) being considered for spinal cord stimulation (SCS) therapy at a single academic center. Images were acquired using a Discovery MR750 GE scanner. During the resting state acquisitions, they were asked to close their eyes and relax. The CN analysis was performed on 7 brain networks and compared to age-matched controls. Linear regression was used to test the correlation between CN connectivity and pain scores. Results: CN FC involving emotion networks (STM: striatum network index) was significantly lower than controls in all patients, regardless of pain phenotype (P < 0.003). Pain levels were positively correlated with emotional FC for intermittent pain but negatively correlated for constant pain. Conclusion: This is the first report of 1) altered CN FC involving emotion/reward brain circuitry in 2) a homogeneous population of cLBP patients with 3) two different pain phenotypes (constant vs intermittent) in PSPS Type 2 patients being considered for SCS. FC patterns were altered in cLBP patients as compared to controls and were characteristic for each pain phenotype. These data support fcMRI as a potential and objective tool in assessing pain levels in cLBP patients with different pain phenotypes.
RESUMO
Recent studies have demonstrated the promising capabilities of magnetic resonance imaging (MRI)-based quantitative susceptibility maps (QSM) in producing biomarkers of brain injury. The present study aims to further explore acute QSM changes in athletes after sports concussion and investigate prognostication capabilities of QSM-derived imaging metrics. The QSM were derived from neurological MRI data acquired on a cohort (n = 78) of concussed male American football athletes within 48 h of injury. The MRI-derived QSM values in subcortical gray and white matter compartments after concussion showed differences relative to a matched uninjured control group (white matter: z = 3.04, p = 0.002, subcortical gray matter: z = -2.07, p = 0.04). Subcortical gray matter QSM MRI measurements also correlated strongly with duration of symptoms (ρ = -0.46, p = 0.002) within a subcohort of subjects who had symptom durations for at least one week (n = 39). The acute QSM MRI metrics showed promising prognostication capabilities, with subcortical gray matter compartment QSM values yielding a mean classification area under the curve performance of 0.78 when predicting symptoms of more than two weeks in duration. The results of the study reproduce previous acute post-concussion group QSM findings and provide promising initial prognostication capabilities of acute QSM measurements in a post-concussion setting.
