Brain morphologic abnormalities in migraine patients: an observational study

Abstract

Background: Migraine is a common neurological disorder characterized by a complex physiopathology. We assessed brain morphologic differences in migraine and the possible pathogenetic mechanism underlying this disease.Methods: We analyzed brain morphologic images of migraine patients, 14 with aura (MwA) [the mean (SD) age was 42.36 (2.95) years (range, 37-47)] and 14 without aura (MwoA) [the mean (SD) age was 43.5 (3.25) years (range, 39-50)] during episodic attack compared with health subjects balanced (HS) [the mean (SD) age was 42.5 (5.17) years (range, 34-51)]. All subjects underwent a Magnetic Resonance Imaging (MRI) examination with a scanner operating at 3.0 T and voxel based morphometry (VBM) approach was used to examine the gray matter volume (GMV). The statistical analysis to compare clinicl characteristics was performed using unpaired t-test an one-way Anova. Results: Total cerebral GMV showed a significant difference between MwA and HS (p=0.02), and between MwoA and HS (p=0.003). In addition, not significative differences were found between MwA and MwoA groups (p=0.17). We found three clusters of regions which showed significant GMV reduction in MwA compared with MwoA. MwA subjects showed a less of GMV in 4 clusters if compared with HS, and MwoA subjects showed a less of GMV in 3 clusters if compared with HS. We observed that MwA and MwoA patients had a significant reduction of GMV in the frontal and temporal lobe and the cerebellum, if compared to HS. The bilateral fusiform gyrus and the cingulate gyrus were increase in MwoA patients compared with HS.Conclusion: Our findings could provide a approach to understand possible differences in the pathogenesis of two type of migraine.

Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine

“…The research has also shown that the results of the SHAP plot and subgroup analysis are similar, both indicating that the PoCG and INS play a pivotal role in the prediction models. In recent studies using restingstate functional and structural MRI, various brain networks with functional and structural changes have been reported in patients with migraine, and show notable correlations with the clinical features [57,58]. These brain networks are consistent with the brain regions observed in this study.…”

“…Moreover, an arterial spin labeling study showed that NSAIDs achieved analgesia by inhibiting neural activity in the brain regions of the descending pain regulatory pathway [20]. In addition, patients with migraine experience a loss of volume in the left somatosensory cortex [57], suggesting larger volume of the left S1 positively contributes to predicting therapeutic outcomes, indicating a compensatory mechanism for responding to pain signals [65]. Based on our findings, we inferred that the altered functional and structural characterizations of brain regions in the descending pain regulatory pathway were involved in the neural mechanism of migraine progression and pharmacological treatment.…”