Neuroimaging studies described brain structural changes that comprise the mechanisms underlying individual differences in migraine development and maintenance. However, whether such interindividual variability in migraine was observed in a pretreatment scan is a predisposition for subsequent hypoalgesia to placebo treatment that remains largely unclear. Using T1-weighted imaging, we investigated this issue in 50 healthy controls (HC) and 196 patients with migraine without aura (MO). An 8-week double-blinded, randomized, placebo-controlled acupuncture was used, and we only focused on the data from the sham acupuncture group. Eighty patients participated in an 8-weeks sham acupuncture treatment, and were subdivided (50% change in migraine days from baseline) into recovering (MOr) and persisting (MOp) patients. Optimized voxel-based morphometry (VBM) and functional connectivity analysis were performed to evaluate brain structural and functional changes. At baseline, MOp and MOr had similar migraine activity, anxiety and depression; reduced migraine days were accompanied by decreased anxiety in MOr. In our findings, the MOr group showed a smaller volume in the left medial prefrontal cortex (mPFC), and decreased mPFC-related functional connectivity was found in the default mode network. Additionally, the reduction in migraine days after placebo treatment was significantly associated with the baseline gray matter volume of the mPFC which could also predict post-treatment groups with high accuracy. It indicated that individual differences for the brain structure in the pain modulatory system at baseline served as a substrate on how an individual facilitated or diminished hypoalgesia responses to placebo treatment in migraineurs. Hum Brain Mapp 38:4386-4397, 2017. © 2017 Wiley Periodicals, Inc.

To investigate whether interindividual variability of white matter (WM) tract microstructure of the medial prefrontal cortex (mPFC)-amygdala circuit could predict 8-week placebo treatment outcomes in patients with migraine without aura (MO) using diffusion tensor imaging (DTI) with a tractography atlas-based analysis algorithm and a linear support vector machine algorithm. This study received institutional review board approval, and all subjects gave informed consent. One hundred and twenty-four MO had an 8-week sham acupuncture treatment. Patients were subdivided into recovering (MOr, >50% improvement in migraine attack frequency after treatment) and persisting (MOp, <50% reduction in number of migraine days). Neuroimaging was collected via magnetic resonance imaging (MRI) in all subjects. Patients were imaged during the interictal phase of migraine (at least 72 hr after, and not within 24 hr of a migraine) before the treatment. WM microstructures were quantified along the selected fiber pathway and were used to evaluate the discrimination performance for classifying MOr and MOp. The combined features of diffusion measures from vertices along the pathways of the mPFC-amygdala accurately discriminated MOr from MOp migraineurs with an accuracy of 84.0% (p < .005, permutation test). The most discriminative WM features that contributed to the classification were located in the external capsule and ACC/mPFC. Our findings suggested that the variability of placebo treatment outcomes in migraineurs could be predicted from priori diffusion measures along the fiber pathways of the mPFC-amygdala, which may demonstrate a potential of WM neuroimaging features as imaging markers for identifying placebo responders in migraine patients.

Primary dysmenorrhea (PD), as characterized by painful menstrual cramps without organic causes, is associated with central sensitization and brain function changes. Previous studies showed the integrated role of the default mode network (DMN) in the pain connectome and its key contribution on how an individual perceives and copes with pain disorders. Here, we aimed to investigate whether the cingulum bundle connecting hub regions of the DMN was disrupted in young women with PD. Diffusion tensor imaging was obtained in 41 PD patients and 41 matched healthy controls (HC) during their periovulatory phase. The production of prostaglandins (PGs) was obtained in PD patients during their pain-free and pain phases. As compared with HC, PD patients had similar scores of pain intensity, anxiety, and depression in their pain-free phase. However, altered white matter properties mainly located in the posterior section of the cingulum bundle were observed in PD. Besides PGs being related to menstrual pain, a close relationship was found between the white matter properties of the cingulum bundle during the pain-free phase and the severity of the menstrual pain in PD patients. Our study suggested that PD had trait changes of white matter integrities in the cingulum bundle that persisted beyond the time of menstruation. We inferred that altered anatomical connections may lead to less-flexible communication within the DMN, and/or between the DMN and other pain-related brain networks, which may result in the central susceptibility to develop chronic pain conditions in PD's later life. Hum Brain Mapp 38:4430-4443, 2017. © 2017 Wiley Periodicals, Inc.

Individual differences of brain changes of neural communication and integration in the modular architecture of the human brain network exist for the repeated migraine attack and physical or psychological stressors. However, whether the interindividual variability in the migraine brain connectome predicts placebo response to placebo treatment is still unclear. Using DTI and graph theory approaches, we systematically investigated the topological organization of white matter networks in 71 patients with migraine without aura (MO) and 50 matched healthy controls at three levels: global network measure, nodal efficiency, and nodal intramodule/intermodule efficiency. All patients participated in an 8-week sham acupuncture treatment to induce analgesia. In our results, 30% (n = 21) of patients had 50% change in migraine days from baseline after placebo treatment. At baseline, abnormal increased network integration was found in MO patients as compared with the HC group, and the increased global efficiency before starting clinical treatment was associated with their following placebo response. For nodal efficiency, significantly increased within-subnetwork nodal efficiency and intersubnetwork connectivity of the hippocampus and middle frontal gyrus in patients' white matter network were correlated with the responses of follow-up placebo treatment. Our findings suggested that the trait-like individual differences in pain-related maladaptive stress interfered with and diminished the capacity of chronic pain modulation differently, and the placebo response for treatment could be predicted from a prior white matter network modular structure in migraineurs. Hum Brain Mapp 38:5250-5259, 2017. © 2017 Wiley Periodicals, Inc.

To develop a machine learning model to investigate the discriminative power of whole-brain gray-matter (GM) images derived from primary dysmenorrhea (PDM) women and healthy controls (HCs) during the pain-free phase and further evaluate the predictive ability of contributing features in predicting the variance in menstrual pain intensity. Sixty patients with PDM and 54 matched female HCs were recruited from the local university. All participants underwent the head and pelvic magnetic resonance imaging scans to calculate GM volume and myometrium-apparent diffusion coefficient (ADC) during their periovulatory phase. Questionnaire assessment was also conducted. A support vector machine algorithm was used to develop the classification model. The significance of model performance was determined by the permutation test. Multiple regression analysis was implemented to explore the relationship between discriminative features and intensity of menstrual pain. Demographics and myometrium ADC-based classifications failed to pass the permutation tests. Brain-based classification results demonstrated that 75.44% of subjects were correctly classified, with 83.33% identification of the patients with PDM (P < 0.001). In the regression analysis, demographical indicators and myometrium ADC accounted for a total of 29.37% of the variance in pain intensity. After regressing out these factors, GM features explained 60.33% of the remaining variance. Our results suggested that GM volume can be used to discriminate patients with PDM and HCs during the pain-free phase, and neuroimaging features can further predict the variance in the intensity of menstrual pain, which may provide a potential imaging marker for the assessment of menstrual pain intervention.

End-stage renal disease (ESRD) is a common complicated disorder that is generally associated with an altered central nervous system and cognitive impairment. Neuroimaging studies have recorded aberrant brain circuits in patients with ESRD that were closely associated with abnormal clinical manifestations. However, whether the altered interaction was within and/or between these circuits is largely unclear. We investigated brain topological organization and/or module interaction by employing resting-state functional magnetic resonance imaging (rs-fMRI) and modularity network analysis in 24 patients with ESRD and 20 age- and gender-matched healthy control (HC) subjects. Stroop task was used to evaluate the performance of cognitive control in all subjects. At the global level, ESRD patients exhibited significantly decreased global and local efficiency which were mainly related to abnormal functional connectivity of the amygdala and inferior frontal gyrus (IFG). Stepwise regression analysis was applied to estimate the relationships between network efficiency and blood biochemistry level (urea, creatine, phosphate, Ca, hematocrit, cystatin, hemoglobin levels, parathyroid hormone, K and Na), and only the hematocrit level was significantly associated with global efficiency in patients with ESRD. At the modular level, we discovered an aberrant brain interaction between the amygdala- and IFG-related circuits in the ESRD group, and the regional efficiency of the amygdala was observably relative to the performance of cognitive control in patients with ESRD. Our results suggested that ESRD exhibited aberrant brain functional topological organization and module-level interaction between the affective and cognitive control circuits, providing crucial insights into the pathophysiological mechanism of ESRD patients.

Depression and cognitive control deficits were frequently reported in concurrent end-stage renal disease (ESRD) patients. Neuroimaging studies indicated depression could be a risk factor for cognitive control deficits, and amygdala-related circuitry may play a critical role in this abnormal interaction. To investigate the potential relationship between depressive symptoms and cognitive control reduction in ESRD patients, T1-weighted and resting fMRI images were obtained in 29 ESRD patients and 29 healthy controls. Voxel-based morphometry (VBM), structural covariance (SC) analysis based on grey matter volume (GMV), and functional connectivity (FC) analysis were adopted. All subjects performed the Beck Depression Inventory (BDI) assessment and Stroop test. The patients also underwent blood biochemistry tests (urea, creatinine, phosphate, Ca2, hematocrit, cystatin, hemoglobin). Compared with controls, GMV reductions were found mainly in the anterior cingulate cortex (ACC) and bilateral amygdala, and decreased SC was found between the amygdala and ACC in ESRD patients. This indicated that structural changes in the amygdala may be related to the GMV alterations in the ACC. Additionally, decreased FC between the amygdala and ACC was revealed in ESRD patients. Negative correlation was found between the FC of the amygdala-ACC and reaction delay during the Stroop test, but this correlation disappeared after controlling BDI. Stepwise regression analysis showed that the low level of hemoglobin was contributed to the reduced FC of the amygdala-ACC in ESRD patients. Our results demonstrated the abnormal interaction between depressive mood and cognitive control deficits in ESRD patients.

We aimed to investigate the neurovascular coupling (NVC) dysfunction in end-stage renal disease (ESRD) patients related with cognitive impairment. Twenty-five ESRD patients and 22 healthy controls were enrolled. To assess the NVC dysfunctional pattern, resting-state functional MRI and arterial spin labeling were explored to estimate the coupling of spontaneous neuronal activity and cerebral blood perfusion based on amplitude of low-frequency fluctuation (ALFF)-cerebral blood flow (CBF), fractional ALFF (fALFF)-CBF, regional homogeneity (ReHo)-CBF, and degree centrality (DC)-CBF correlation coefficients. Multivariate partial least-squares correlation and mediation analyses were used to evaluate the relationship among NVC dysfunctional pattern, cognitive impairment and clinical characteristics. The NVC dysfunctional patterns in ESRD patients were significantly decreased in 34 brain regions compared with healthy controls. The decreased fALFF-CBF coefficients in the cingulate gyrus (CG) were associated positively with lower kinetic transfer/volume urea (Kt/V) and lower short-term memory scores, and were negatively associated with higher serum urea. The relationship between Kt/V and memory deficits of ESRD patients was partially mediated by the fALFF-CBF alteration of the CG. These findings reveal the NVC dysfunction may be a potential neural mechanism for cognitive impairment in ESRD. The regional NVC dysfunction may mediate the impact of dialysis adequacy on memory function.