Concurrent alterations of white matter microstructure and functional activities in medication-free major depressive disorder

Combination of static and dynamic neural imaging features to distinguish sensorineural hearing loss: a machine learning study

Purpose

Sensorineural hearing loss (SNHL) is the most common form of sensory deprivation and is often unrecognized by patients, inducing not only auditory but also nonauditory symptoms. Data-driven classifier modeling with the combination of neural static and dynamic imaging features could be effectively used to classify SNHL individuals and healthy controls (HCs).

Methods

We conducted hearing evaluation, neurological scale tests and resting-state MRI on 110 SNHL patients and 106 HCs. A total of 1,267 static and dynamic imaging characteristics were extracted from MRI data, and three methods of feature selection were computed, including the Spearman rank correlation test, least absolute shrinkage and selection operator (LASSO) and t test as well as LASSO. Linear, polynomial, radial basis functional kernel (RBF) and sigmoid support vector machine (SVM) models were chosen as the classifiers with fivefold cross-validation. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated for each model.

Results

SNHL subjects had higher hearing thresholds in each frequency, as well as worse performance in cognitive and emotional evaluations, than HCs. After comparison, the selected brain regions using LASSO based on static and dynamic features were consistent with the between-group analysis, including auditory and nonauditory areas. The subsequent AUCs of the four SVM models (linear, polynomial, RBF and sigmoid) were as follows: 0.8075, 0.7340, 0.8462 and 0.8562. The RBF and sigmoid SVM had relatively higher accuracy, sensitivity and specificity.

Conclusion

Our research raised attention to static and dynamic alterations underlying hearing deprivation. Machine learning-based models may provide several useful biomarkers for the classification and diagnosis of SNHL.

Degree centrality-based resting-state functional magnetic resonance imaging explores central mechanisms in lumbar disc herniation patients with chronic low back pain

Objective

To investigate the central mechanism of lumbar disc herniation in patients with chronic low back pain (LDHCP) using resting-state functional magnetic resonance imaging (rs-fMRI) utilizing the Degree Centrality (DC) method.

Methods

Twenty-five LDHCP and twenty-two healthy controls (HCs) were enrolled, and rs-fMRI data from their brains were collected. We compared whole-brain DC values between the LDHCP and HC groups, and examined correlations between DC values within the LDHCP group and the Visual Analogue Score (VAS), Oswestry Dysfunction Index (ODI), and disease duration. Diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curve analysis.

Results

LDHCP patients exhibited increased DC values in the bilateral cerebellum and brainstem, whereas decreased DC values were noted in the left middle temporal gyrus and right post-central gyrus when compared with HCs. The DC values of the left middle temporal gyrus were positively correlated with VAS (r = 0.416, p = 0.039) and ODI (r = 0.405, p = 0.045), whereas there was no correlation with disease duration (p > 0.05). Other brain regions showed no significant correlations with VAS, ODI, or disease duration (p > 0.05). Furthermore, the results obtained from ROC curve analysis demonstrated that the Area Under the Curve (AUC) for the left middle temporal gyrus was 0.929.

Conclusion

The findings indicated local abnormalities in spontaneous neural activity and functional connectivity in the bilateral cerebellum, bilateral brainstem, left middle temporal gyrus, and right postcentral gyrus among LDHCP patients.

Altered functional brain network patterns in patients with migraine without aura after transcutaneous auricular vagus nerve stimulation

Transcutaneous auricular vagus nerve stimulation (taVNS) shows excellent effects on relieving clinical symptoms in migraine patients. Nevertheless, the neurological mechanisms of taVNS for migraineurs remain unclear. In recent years, voxel-wise degree centrality (DC) and functional connectivity (FC) methods were extensively utilized for exploring alterations in patterns of FC in the resting-state brain. In the present study, thirty-five migraine patients without aura and thirty-eight healthy controls (HCs) were recruited for magnetic resonance imaging scans. Firstly, this study used voxel-wise DC analysis to explore brain regions where abnormalities were present in migraine patients. Secondly, for elucidating neurological mechanisms underlying taVNS in migraine, seed-based resting-state functional connectivity analysis was employed to the taVNS treatment group. Finally, correlation analysis was performed to explore the relationship between alterations in neurological mechanisms and clinical symptoms. Our findings indicated that migraineurs have lower DC values in the inferior temporal gyrus (ITG) and paracentral lobule than in healthy controls (HCs). In addition, migraineurs have higher DC values in the cerebellar lobule VIII and the fusiform gyrus than HCs. Moreover, after taVNS treatment (post-taVNS), patients displayed increased FC between the ITG with the inferior parietal lobule (IPL), orbitofrontal gyrus, angular gyrus, and posterior cingulate gyrus than before taVNS treatment (pre-taVNS). Besides, the post-taVNS patients showed decreased FC between the cerebellar lobule VIII with the supplementary motor area and postcentral gyrus compared with the pre-taVNS patients. The changed FC of ITG-IPL was significantly related to changes in headache intensity. Our study suggested that migraine patients without aura have altered brain connectivity patterns in several hub regions involving multisensory integration, pain perception, and cognitive function. More importantly, taVNS modulated the default mode network and the vestibular cortical network related to the dysfunctions in migraineurs. This paper provides a new perspective on the potential neurological mechanisms and therapeutic targets of taVNS for treating migraine.

Unraveling the mystery of white matter in depression: A translational perspective on recent advances

BACKGROUND

Numerous cortical and subcortical structures have been studied extensively concerning alterations of their integrity as well as their neurotransmitters in depression. However, connections between these structures have received considerably less attention.

OBJECTIVE

This systematic review presents results from recent neuroimaging as well as neuropathologic studies conducted on humans and other mammals. It aims to provide evidence for impaired white matter integrity in individuals expressing a depressive phenotype.

METHODS

A systematic database search in accordance with the PRISMA guidelines was conducted to identify imaging and postmortem studies conducted on humans with a diagnosis of major depressive disorder, as well as on rodents and primates subjected to an animal model of depression.

RESULTS

Alterations are especially apparent in frontal gyri, as well as in structures establishing interhemispheric connectivity between frontal regions. Translational neuropathological findings point to alterations in oligodendrocyte density and morphology, as well as to alterations in the expression of genes related to myelin synthesis. An important role of early life adversities in the development of depressive symptoms and white matter alterations across species is thereby revealed. Data indicating that stress can interfere with physiological myelination patterns is presented. Altered myelination is most notably present in regions that are subject to maturation during the developmental stage of exposure to adversities.

CONCLUSION

Translational studies point to replicable alterations in white matter integrity in subjects suffering from depression across multiple species. Impaired white matter integrity is apparent in imaging as well as neuropathological studies. Future studies should focus on determining to what extent influencing white matter integrity is able to improve symptoms of depression in animals as well as humans.

Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis

BACKGROUND

Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain functional connectivity changes associated with adolescent depression in an effort to define an imaging-based biomarker associated with this condition.

MATERIALS AND METHODS

In total, 71 adolescents affected by major depressive disorder (MDD) and 71 age-, sex-, and education level-matched healthy controls were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) based analyses of brain voxel-wise degree centrality (DC), with a support vector machine (SVM) being used for pattern classification analyses.

RESULTS

DC patterns derived from 16-min rs-fMRI analyses were able to effectively differentiate between adolescent MDD patients and healthy controls with 95.1% accuracy (136/143), and with respective sensitivity and specificity values of 92.1% (70/76) and 98.5% (66/67) based upon DC abnormalities detected in the right cerebellum. Specifically, increased DC was evident in the bilateral insula and left lingual area of MDD patients, together with reductions in the DC values in the right cerebellum and bilateral superior parietal lobe. DC values were not significantly correlated with disease severity or duration in these patients following correction for multiple comparisons.

CONCLUSION

These results suggest that whole-brain network centrality abnormalities may be present in many brain regions in adolescent depression patients. Accordingly, these DC maps may hold value as candidate neuroimaging biomarkers capable of differentiating between adolescents who are and are not affected by MDD, although further validation of these results will be critical.

Abnormal degree centrality values as a potential imaging biomarker for major depressive disorder: A resting-state functional magnetic resonance imaging study and support vector machine analysis

OBJECTIVE

Previous studies have revealed abnormal degree centrality (DC) in the structural and functional networks in the brains of patients with major depressive disorder (MDD). There are no existing reports on the DC analysis method combined with the support vector machine (SVM) to distinguish patients with MDD from healthy controls (HCs). Here, the researchers elucidated the variations in DC values in brain regions of MDD patients and provided imaging bases for clinical diagnosis.

METHODS

Patients with MDD (N = 198) and HCs (n = 234) were scanned using resting-state functional magnetic resonance imaging (rs-fMRI). DC and SVM were applied to analyze imaging data.

RESULTS

Compared with HCs, MDD patients displayed elevated DC values in the vermis, left anterior cerebellar lobe, hippocampus, and caudate, and depreciated DC values in the left posterior cerebellar lobe, left insula, and right caudate. As per the results of the SVM analysis, DC values in the left anterior cerebellar lobe and right caudate could distinguish MDD from HCs with accuracy, sensitivity, and specificity of 87.71% (353/432), 84.85% (168/198), and 79.06% (185/234), respectively. Our analysis did not reveal any significant correlation among the DC value and the disease duration or symptom severity in patients with MDD.

CONCLUSION

Our study demonstrated abnormal DC patterns in patients with MDD. Aberrant DC values in the left anterior cerebellar lobe and right caudate could be presented as potential imaging biomarkers for the diagnosis of MDD.

Desynchronized white matter function and structure in drug-naive first-episode major depressive disorder patients

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent mental disease. Using magnetic resonance imaging (MRI), although numerous studies have revealed the alterations in structure and function of grey matter (GM), few studies focused on the synchronization of white matter (WM) structure and function in MDD. The aim of this study was to investigate whether functional and structural abnormalities of WM play an essential role in the neurobiological mechanisms of MDD.

METHODS

Gradient-echo imaging sequences at 3.0T were used to gather resting state functional MRI (rsfMRI) data, which were performed on 33 drug-naive first-episode MDD patients and 34 healthy controls (HCs). After data preprocessed, amplitude of low frequency fluctuation (ALFF) of WM was calculated. ALFF values in different frequency bands were analyzed, including typical (0.01-0.15 Hz) band, slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands. In addition, the fractional anisotropy (FA) values in WM in 23 patients and 26 HCs were examined using tract-based spatial statistics (TBSS) and tractography based on diffusion tensor imaging (DTI). Pearson correlation analysis was applied to analyze the relationships between ALFF values and Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA).

RESULTS

Compared with the HCs, MDD patients showed decreased ALFF values in posterior thalamic radiation (PTR) and superior longitudinal fasciculus (SLF) in slow-5 frequency band, no significant differences of ALFF values were found in typical and slow-4 frequency bands. In addition, there were no significant differences in FA values with TBSS analysis as well as the number of fibers in PTR and SLF with tractography analysis between two groups. Further correlation analysis showed that the ALFF value in SLF was negatively correlated with HAMA-2 score (r = -0.548, p _FDR = 0.037) in patients.

CONCLUSION

Our results indicated that WM dysfunction may be associated with the pathophysiological mechanism of depression. Our study also suggested that the functional damage of the WM may precedes the structural damage in first-episode MDD patients. Furthermore, for mental disorders, slow-5 frequency band may be a more sensitive functional indicator for early detection of abnormal spontaneous brain activity in WM.

Magnetic Resonance Imaging Studies on Acupuncture Therapy in Depression: A Systematic Review

Accumulating studies had been performed using magnetic resonance imaging (MRI) to understand the neural mechanism of acupuncture therapy for depression. However, inconsistencies remain due to differences in research designs and MRI analytical methods. Therefore, we aim to summarize the current MRI research and provide useful information for further research by identifying papers published in English and Chinese about MRI studies on acupuncture for depression up to November 2020. A total of 22 studies met the inclusion criteria, including 810 depression patients and 416 health controls (HCs). The applied designs of these studies are mainly random control trial and pre-post designs. The MRI analytical methods are mainly (fractional) amplitude of low-frequency fluctuation (fALFF/ALFF) and functional connectivity (FC), whereas a small subset of studies used voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). The most consistent functional MRI (fMRI) results showed increased N-acetylaspartate/creatine (NAA/Cr) ratios, increased ALFF in the right precuneus, decreased ALFF in the inferior frontal gyrus (IFG), and increased FC of the anterior cingulate cortex (ACC). In contrast, no significant neurological changes were identified in any of the DTI or VBM studies. However, clear, reliable conclusions cannot be drawn due to the use of different designs, analytical methods, seed points selected, types of depression, acupuncture points, and so on. Improved report specifications, well-designed studies, consistent analytical methods, and larger sample sizes will enable the field to better elucidate the underlying mechanisms of acupuncture in depressed patients.