Functional Neuroimaging Biomarkers in Migraine: Diagnostic, Prognostic and Therapeutic Implications

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

BACKGROUND

Non-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment.

METHODS

Propensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine.

RESULTS

One hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders.

CONCLUSIONS

Our findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

Functional MRI and Diffusion Tensor Imaging in Migraine: A Review of Migraine Functional and White Matter Microstructural Changes

Migraine is a complex and heterogenous disorder whose disease mechanisms remain disputed. This narrative review summarizes functional MRI (fMRI) and diffusion tensor imaging (DTI) findings and interprets their association with migraine symptoms and subtype to support and expand our current understanding of migraine pathophysiology. Our PubMed search evaluated and included fMRI and DTI studies involving comparisons between migraineurs vs healthy controls, migraineurs with vs without aura, and episodic vs chronic migraineurs. Migraineurs demonstrate changes in functional connectivity (FC) and regional activation in numerous pain-related networks depending on migraine phase, presence of aura, and chronicity. Changes to diffusion indices are observed in major cortical white matter tracts extending to the brainstem and cerebellum, more prominent in chronic migraine and associated with FC changes. Reported changes in FC and regional activation likely relate to pain processing and sensory hypersensitivities. Diffuse white matter microstructural changes in dysfunctional cortical pain and sensory pathways complement these functional differences. Interpretations of reported fMRI and DTI measure trends have not achieved a clear consensus due to inconsistencies in the migraine neuroimaging literature. Future fMRI and DTI studies should establish and implement a uniform methodology that reproduces existing results and directly compares migraineurs with different subtypes. Combined fMRI and DTI imaging may provide better pathophysiological explanations for nonspecific FC and white matter microstructural differences.

A state-of-the-art review of functional magnetic resonance imaging technique integrated with advanced statistical modeling and machine learning for primary headache diagnosis

Primary headache is a very common and burdensome functional headache worldwide, which can be classified as migraine, tension-type headache (TTH), trigeminal autonomic cephalalgia (TAC), and other primary headaches. Managing and treating these different categories require distinct approaches, and accurate diagnosis is crucial. Functional magnetic resonance imaging (fMRI) has become a research hotspot to explore primary headache. By examining the interrelationships between activated brain regions and improving temporal and spatial resolution, fMRI can distinguish between primary headaches and their subtypes. Currently the most commonly used is the cortical brain mapping technique, which is based on blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI). This review sheds light on the state-of-the-art advancements in data analysis based on fMRI technology for primary headaches along with their subtypes. It encompasses not only the conventional analysis methodologies employed to unravel pathophysiological mechanisms, but also deep-learning approaches that integrate these techniques with advanced statistical modeling and machine learning. The aim is to highlight cutting-edge fMRI technologies and provide new insights into the diagnosis of primary headaches.

Arterial spin labeling MRI applied to migraine: current insights and future perspectives

INTRODUCTION

Advanced neuroimaging techniques have extensively contributed to elucidate the complex mechanisms underpinning the pathophysiology of migraine, a neurovascular disorder characterized by episodes of headache associated with a constellation of non-pain symptoms. The present manuscript, summarizing the most recent progresses of the arterial spin labelling (ASL) MRI techniques and the most significant findings from ASL studies conducted in migraine, is aimed to clarify how ASL investigations are contributing to the evolving insight on migraine pathophysiology and their putative role in migraine clinical setting. ASL techniques, allowing to quantitatively demonstrate changes in cerebral blood flow (CBF) both during the attacks and in the course of interictal period, could represent the melting point between advanced neuroimaging investigations, conducted with pure scientific purposes, and conventional neuroimaging approaches, employed in the diagnostic decision-making processes.

MAIN BODY

Converging ASL evidences have demonstrated that abnormal CBF, exceeding the boundaries of a single vascular territory, with biphasic trend dominated by an initial hypoperfusion (during the aura phenomenon but also in the first part of the headache phase) followed by hyperperfusion, characterizes migraine with aura attack and can represent a valuable clinical tool in the differential diagnosis from acute ischemic strokes and epileptic seizures. Studies conducted during migraine without aura attacks are converging to highlight the involvement of dorsolateral pons and hypothalamus in migraine pathophysiology, albeit not able to disentangle their role as "migraine generators" from mere attack epiphenomenon. Furthermore, ASL findings tend to support the presence of perfusion abnormalities in brain regions known to be involved in aura ignition and propagation as well as in areas involved in multisensory processing, in both patients with migraine with aura and migraine without aura.

CONCLUSION

Although ASL studies have dramatically clarified quality and timing of perfusion abnormalities during migraine with aura attacks, the same cannot be said for perfusion changes during migraine attacks without aura and interictal periods. Future studies with more rigorous methodological approaches in terms of study protocol, ASL technique and sample selection and size are mandatory to exploit the possibility of better understanding migraine pathophysiology and identifying neuroimaging biomarkers of each migraine phase in different migraine phenotypes.

Bridging the gap between preclinical scientists, clinical researchers, and clinicians: From animal research to clinical practice

BACKGROUND

Collaborations amongst researchers and clinicians with complementary areas of expertise enhance knowledge for everyone and can lead to new discoveries. To facilitate these interactions, shared language and a general understanding of how colleagues in different subfields of headache and headache research approach their work are needed.

METHODS

This narrative review focuses on research methods applied in animal studies, human studies including clinical trials, and provides an overview of clinical practice.

RESULTS

For animal studies, we describe concepts needed to evaluate the quality and relevance of preclinical studies. For human research, fundamental concepts of neuroimaging, quantitative sensory testing, genetic and epidemiological research methods, and clinical research methodology that are commonly used in headache research are summarized. In addition, we provide an understanding of what guides headache clinicians, and summarize the practical approach to migraine management in adults and children.

CONCLUSIONS

It is hoped that this review facilitates further dialogue between clinicians and researchers that will help guide future research efforts and implementation of research findings into clinical practice.

Functional connectivity changes during migraine treatment with electroacupuncture at Shuaigu (GB8)

OBJECTIVE

To investigate the changes in the functional connectivity (FC) in the right insula between migraine without aura (MWoA) and healthy controls by using resting-state functional magnetic resonance imaging (rs-fMRI), and to observe the instant alteration of FC in MWoA during electroacupuncture (EA) stimulation at Shuaigu (GB8).

METHODS

A total of 30 patients with MWoA (PM group) and 30 healthy controls (HC group) underwent rs-fMRI scans. The PM group underwent a second rs-fMRI scan while receiving EA at GB8. The right insula subregions, including the ventral anterior insula (vAI), dorsal anterior insula (dAI) and posterior insula (PI), were selected as the seed points for FC analysis.

RESULTS

Aberrant FC, including dAI with right postcentral gyrus, PI with left precuneus, was found among PM before EA (PMa), PM during EA (PMb) and HC. Meanwhile, decreased FC between dAI and the right postcentral gyrus was found in the PMa compared to the HC and PMb. Increased FC between the PI and left precuneus was found in the PMa compared to the HC and PMb. Correlation analysis showed that the FC value of the right postcentral gyrus in PMa was negatively correlated with the scores of Hamilton Rating Scale for Depression and Hamilton Rating Scale for Anxiety. The FC value of the left precuneus in PMa was positively correlated with the visual analogue scale score.

CONCLUSION

The alteration of FC between the right insula subregions and multiple brain regions may be an important index for MWoA. EA at GB8 was able to adjust the FC between the right insula subregions and parietal lobe, namely, the right dAI and right postcentral gyrus, and the right PI and left precuneus, thereby rendering an instant effect in the management of MWoA.

Circadian Variation of Migraine Attack Onset Affects fMRI Brain Response to Fearful Faces

Background

Previous studies suggested a circadian variation of migraine attack onset, although, with contradictory results – possibly because of the existence of migraine subgroups with different circadian attack onset peaks. Migraine is primarily a brain disorder, and if the diversity in daily distribution of migraine attack onset reflects an important aspect of migraine, it may also associate with interictal brain activity. Our goal was to assess brain activity differences in episodic migraine subgroups who were classified according to their typical circadian peak of attack onset.

Methods

Two fMRI studies were conducted with migraine without aura patients (n = 31 in Study 1, n = 48 in Study 2). Among them, three subgroups emerged with typical Morning, Evening, and Varying start of attack onset. Whole brain activity was compared between the groups in an implicit emotional processing fMRI task, comparing fearful, sad, and happy facial stimuli to neutral ones.

Results

In both studies, significantly increased neural activation was detected to fearful (but not sad or happy) faces. In Study 1, the Evening start group showed increased activation compared to the Morning start group in regions involved in emotional, self-referential (left posterior cingulate gyrus, right precuneus), pain (including left middle cingulate, left postcentral, left supramarginal gyri, right Rolandic operculum) and sensory (including bilateral superior temporal gyrus, right Heschl’s gyrus) processing. While in Study 2, the Morning start group showed increased activation compared to the Varying start group at a nominally significant level in regions with pain (right precentral gyrus, right supplementary motor area) and sensory processing (bilateral paracentral lobule) functions.

Conclusion

Our fMRI studies suggest that different circadian attack onset peaks are associated with interictal brain activity differences indicating heterogeneity within migraine patients and alterations in sensitivity to threatening fearful stimuli. Circadian variation of migraine attack onset may be an important characteristic to address in future studies and migraine prophylaxis.

White matter abnormalities and multivariate pattern analysis in anti-NMDA receptor encephalitis

OBJECTIVE

This study aimed to investigate white matter (WM) microstructural alterations and their relationship correlation with disease severity in anti-NMDA receptor (NMDAR) encephalitis. Multivariate pattern analysis (MVPA) was applied to discriminate between patients and healthy controls and explore potential imaging biomarkers.

METHODS

Thirty-two patients with anti-NMDAR encephalitis and 26 matched healthy controls underwent diffusion tensor imaging. Tract-based spatial statistics and atlas-based analysis were used to determine WM microstructural alterations between the two groups. MVPA, based on a machine-learning algorithm, was applied to classify patients and healthy controls.

RESULTS

Patients exhibited significantly reduced fractional anisotropy in the corpus callosum, fornix, cingulum, anterior limb of the internal capsule, and corona radiata. Moreover, mean diffusivity was increased in the anterior corona radiata and body of the corpus callosum. On the other hand, radial diffusivity was increased in the anterior limb of the internal capsule, cingulum, corpus callosum, corona radiata, and fornix. WM changes in the cingulum, fornix, and retrolenticular part of the internal capsule were correlated with disease severity. The accuracy, sensitivity, and specificity of fractional anisotropy-based classification were each 78.33%, while they were 67.71, 65.83, and 70% for radial diffusivity.

CONCLUSION

Widespread WM lesions were detected in anti-NMDAR encephalitis. The correlation between WM abnormalities and disease severity suggests that these alterations may serve a key role in the pathophysiological mechanisms of anti-NMDAR encephalitis. The combination of tract-based spatial statistics and MVPA may provide more specific and complementary information at the group and individual levels.

Characteristics of N400 component elicited in patients who have migraine with aura

Background

This study aimed to examine the N400 effect and event-related potentials (ERPs) elicited from congruent and incongruent stimuli in patients who have migraines with aura (MwA).

Methods

A total of 33 MwA patients and 20 healthy controls (HCs) were studied. They were balanced in age (35.12 ± 8.94 vs 34.70 ± 9.59 years, p = 0.872) and sex (69.7 vs 75.0% females, p = 0.761). ERPs were measured in response to both stimuli, where pictures were preceded with an object name that either matched or mismatched with the object. Averaged amplitudes, peaks, peak latencies, difference waves and topography were compared between MwA and HCs.

Results

MwA patients had significantly lower averaged amplitudes at the Fz and F4 sites during incongruent stimuli, as well as reduced peaks at the C3 and Pz sites. Topography showed a more widespread N400 effect over scalp relative to HCs. The difference ERP waveforms did not differ in the N400 effect between groups, but the P600 effect was significantly stronger in the HCs group relative to the MwA group at the Pz (6.52 ± 2.57 vs. 3.50 ± 3.15, p = 0.001) and P4 (5.86 ± 2.79 vs. 3.95 ± 3.64, p = 0.040) sites.

Conclusions

Picture-word matching tasks could serve as a potential new method for the investigation of semantic processing in MwA patients.