Altered orientation dispersion index of white matter in individuals with insomnia during the COVID-19 pandemic: A study combining neuroimaging technique and Mendelian randomization.

STUDY OBJECTIVES: Coronavirus disease 2019 (COVID-19) can lead to insomnia. However, associations between COVID-19-caused insomnia and white matter (WM) changes are unclear. METHODS: All subjects had ever been infected with COVID-19. We investigated 89 insomniacs (29 chronic insomniacs, 33 new-onset insomniacs, 27 aggravated insomniacs) and 44 matched non-insomnia participants. Neurite orientation dispersion and density imaging (NODDI) was performed to identify micro-structural alterations of WM, and twelve scales related to sleeping status, memory, attention, learning, emotional status, and executive functions were used. Then, correlations between insomnia/cognitive-behavioral functions and diffusion metrics were tested. To eliminate influence of pre-COVID-19 factors on insomnia, causal relationships between COVID-19 and WM changes were validated by Mendelian randomization (MR) analysis. The significant brain regions of COVID-19-caused insomnia were intersected results of tract-based spatial statistics (TBSS) and MR analyses. RESULTS: Compared to non-insomnia group, insomnia group and its subgroups including post-COVID-19 aggravated or unchanged chronic insomnia group had higher orientation dispersion index (ODI) in extensive brain regions. The left superior longitudinal fasciculus (SLF), left posterior thalamic radiation (PTR), and left cingulate gyrus (CG) were specific brain regions in COVID-19-induced insomnia aggravation. After Bonferroni correction, partial correlation analyses within insomnia group showed that ODI in left SLF was positively correlated with Pittsburgh sleep quality index (PSQI), insomnia severity index (ISI), and self-rating anxiety scale (SAS) scores; ODI in the left PTR was positively correlated with PSQI and ISI scores. CONCLUSIONS: This study is a continuation of our previous research, which provided potential biomarkers for COVID-19-induced insomnia.

Gray Matter Thickness and Subcortical Nuclear Volume in Men After SARS-CoV-2 Omicron Infection.

Importance: The clinical manifestations and effects on the brain of the SARS-CoV-2 Omicron variant in the acute postinfection phase remain unclear. Objective: To investigate the pathophysiological mechanisms underlying clinical symptoms and changes to gray matter and subcortical nuclei among male patients after Omicron infection and to provide an imaging basis for early detection and intervention. Design, Setting, and Participants: In this cohort study, a total of 207 men underwent health screening magnetic resonance imaging scans between August 28 and September 18, 2022; among them, 98 provided complete imaging and neuropsychiatric data. Sixty-one participants with Omicron infection were reevaluated after infection (January 6 to 14, 2023). Neuropsychiatric data, clinical symptoms, and magnetic resonance imaging data were collected in the acute post-Omicron period, and their clinical symptoms were followed up after 3 months. Gray matter indexes and subcortical nuclear volumes were analyzed. Associations between changes in gray matter and neuropsychiatric data were evaluated with correlation analyses. Exposures: Gray matter thickness and subcortical nuclear volume change data were compared before and after Omicron infection. Main Outcomes and Measures: The gray matter indexes and subcutaneous nuclear volume were generated from the 3-dimensional magnetization-prepared rapid acquisition gradient echo and were calculated with imaging software. Results: Ninety-eight men underwent complete baseline data collection; of these, 61 (mean [SD] age, 43.1 [9.9] years) voluntarily enrolled in post-Omicron follow-up and 17 (mean [SD] age, 43.5 [10.0] years) voluntarily enrolled in 3-month follow-up. Compared with pre-Omicron measures, Beck Anxiety Inventory scores were significantly increased (median, 4.50 [IQR, 1.00-7.00] to 4.00 [IQR, 2.00-9.75]; P = .006) and depressive distress scores were significantly decreased (median, 18.00 [IQR, 16.00-20.22] to 16.00 [IQR, 15.00-19.00]; P = .003) at the acute post-Omicron follow-up. Fever, headache, fatigue, myalgia, cough, and dyspnea were the main symptoms during the post-Omicron follow-up; among the participants in the 3-month follow-up, fever (11 [64.7%] vs 2 [11.8%]; P = .01), myalgia (10 [58.8%] vs 3 (17.6%]; P = .04), and cough (12 [70.6%] vs 4 [23.5%]; P = .02) were significantly improved. The gray matter thickness in the left precuneus (mean [SD], 2.7 [0.3] to 2.6 [0.2] mm; P < .001) and right lateral occipital region (mean [SD], 2.8 [0.2] to 2.7 [0.2] and 2.5 [0.2] to 2.5 [0.2] mm; P < .001 for both) and the ratio of the right hippocampus volume to the total intracranial volume (mean [SD]. 0.003 [0.0003] to 0.003 [0.0002]; P = .04) were significantly reduced in the post-Omicron follow-up. The febrile group had reduced sulcus depth of the right inferior parietal region compared with the nonfebrile group (mean [SD], 3.9 [2.3] to 4.8 [1.1]; P = .048. In the post-Omicron period, the thickness of the left precuneus was negatively correlated with the Beck Anxiety Inventory scores (r = -0.39; P = .002; false discovery rate P = .02), and the ratio of the right hippocampus to the total intracranial volume was positively correlated with the Word Fluency Test scores (r = 0.34; P = .007). Conclusions and Relevance: In this cohort study of male patients infected with the Omicron variant, the duration of symptoms in multiple systems after infection was short. Changes in gray matter thickness and subcortical nuclear volume injury were observed in the post-Omicron period. These findings provide new insights into the emotional and cognitive mechanisms of an Omicron infection, demonstrate its association with alterations to the nervous system, and verify an imaging basis for early detection and intervention of neurological sequelae.

Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction.

Drug abuse is a serious problem worldwide. Owing to intermittent intake of certain substances and the early inconspicuous clinical symptoms, this brings huge challenges for timely diagnosing addiction status and preventing substance use disorders (SUDs). As a non-invasive technique, neuroimaging can capture neurobiological signatures of abnormality in multiple brain regions caused by drug consumption in each clinical stage, like parenchymal morphology alteration as well as aberrant functional activity and connectivity of cerebral areas, making it realizable to diagnosis, prediction and even preemptive therapy of addiction. Machine learning (ML) algorithms primarily used for classification have been extensively applied in analysing medical imaging datasets. Significant neurobiological characteristics employed and revealed by classifiers were used to diagnose addictive states and predict initiation and vulnerability to drug usage, treatment abstinence, relapse and resilience of addicts and the risk of SUD. In this review, we summarize application of ML methods in neuroimaging focusing on addicts' diagnosis of clinical status and risk prediction and elucidate the discriminative neurobiological features from brain electrophysiological, morphological and functional perspectives that contribute most to the classifier, finally highlighting the auxiliary role of ML in addiction treatment.

Dynamic white matter changes in recovered COVID-19 patients: a two-year follow-up study.

Background and purpose: Long COVID with regard to the neurological system deserves more attention, as a surge of treated patients are being discharged from the hospital. As the dynamic changes in white matter after two years remain unknown, this characteristic was the focus of this study. Methods: We investigated 17 recovered COVID-19 patients at two years after discharge. Diffusion tensor imaging, neurite orientation dispersion and density imaging were performed to identify white matter integrity and changes from one to two years after discharge. Data for 13 revisited healthy controls were collected as a reference. Subscales of the Wechsler Intelligence scale were used to assess cognitive function. Repeated-measures ANOVA was used to detect longitudinal changes in 17 recovered COVID-19 patients and 13 healthy controls after one-year follow-up. Correlations between diffusion metrics, cognitive function, and other clinical characteristics (i.e., inflammatory factors) were also analyzed. Results: Longitudinal analysis showed the recovery trends of large-scale brain regions, with small-scale brain region deterioration from one year to two years after SARS-CoV-2 infection. However, persistent white matter abnormalities were noted at two years after discharge. Longitudinal changes of cognitive function showed no group difference. But cross-sectional cognitive difference between recovered COVID-19 patients and revisited HCs was detected. Inflammation levels in the acute stage correlated positively with white matter abnormalities and negatively with cognitive function. Moreover, the more abnormal the white matter was at two years, the greater was the cognitive deficit present. Conclusion: Recovered COVID-19 patients showed longitudinal recovery trends of white matter. But also had persistent white matter abnormalities at two years after discharge. Inflammation levels in the acute stage may be considered predictors of cognition and white matter integrity, and the white matter microstructure acts as a biomarker of cognitive function in recovered COVID-19 patients. These findings provide an objective basis for early clinical intervention.

Two-year follow-up of brain structural changes in patients who recovered from COVID-19: A prospective study.

The long-term effects of COVID-19 on brain structure remain unclear. A prospective study was conducted to explore the changes in brain structure in COVID-19 survivors at one and two years after discharge (COVID-19one, COVID-19two). The difference in gray matter volume (GMV) was analyzed using the voxel-based morphometry method, and correlation analyses were conducted. The dynamic changes in clinical sequelae varied. The GMVs in the cerebellum and vermis were reduced in COVID-19one and COVID-19two, positively correlated with lymphocyte count, and negatively correlated with neutrophil count, neutrophil/lymphocyte ratio (COVID-19one), and systemic immune-inflammation index (COVID-19two). The decreased GMVs in the left middle frontal gyrus, inferior frontal gyrus of the operculum, right middle temporal gyrus, and inferior temporal gyrus returned to normal in COVID-19two. The decreased GMV in the left frontal lobe was negatively correlated with the Athens Insomnia Scale (AIS). The GMV in the left temporal lobe was aggravated in COVID-19two and positively correlated with C-reactive protein. In conclusion, GMV recovery coexisted with injury, which was associated with AIS and inflammatory factors. This may shed some light on the dynamic changes in brain structure and the possible predictors that may be related to GMV changes in COVID-19two.

Cell mechanical responses to subcellular perturbations generated by ultrasound and targeted microbubbles.

The inherently dynamic and anisotropic microenvironment of cells imposes not only global and slow physical stimulations on cells but also acute and local perturbations. However, cell mechanical responses to transient subcellular physical signals remain unclear. In this study, acoustically activated targeted microbubbles were used to exert mechanical perturbations to single cells. The cellular contractile force was sensed by elastic micropillar arrays, while the pillar deformations were imaged using brightfield high-speed video microscopy at a frame rate of 1k frames per second for the first 10s and then confocal fluorescence microscopy. Cell mechanical responses are accompanied by cell membrane integrity changes. Both processes are determined by the perturbation strength generated by microbubble volumetric oscillations. The instantaneous cellular traction force relaxation exhibits two distinct patterns, correlated with two cell fates (survival or permanent damage). The mathematical modeling unveils that force-induced actomyosin disassembly leads to gradual traction force relaxation in the first few seconds. The perturbation may also influence the far end subcellular regions from the microbubbles and may propagate into connected cells with attenuations and delays. This study carefully characterizes the cell mechanical responses to local perturbations induced by ultrasound and microbubbles, advancing our understanding of the fundamentals of cell mechano-sensing, -responsiveness, and -transduction. STATEMENT OF SIGNIFICANCE: Subcellular physical perturbations commonly exist but haven't been fully explored yet. The subcellular perturbation generated by ultrasound and targeted microbubbles covers a wide range of strength, from mild, intermediate to intense, providing a broad biomedical relevance. With µm2 spatial sensing ability and up to 1ms temporal resolution, we present spatiotemporal details of the instantaneous cellular contractile force changes followed by attenuated and delayed global responses. The correlation between the cell mechanical responses and cell fates highlights the important role of the instantaneous mechanical responses in the entire cellular reactive processes. Supported by mathematical modeling, our work provides new insights into the dynamics and mechanisms of cell mechanics.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders.

Background: Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD). Aims: This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM). Methods: One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8-month follow-up of abstinence. CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ (HCQfollow-up-HCQbaseline). Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD. Results: CPM could predict craving changes induced by long-term abstinence, as shown by a significant correlation between predicted and actual HCQfollow-up (r=0.417, p<0.001) and changes in HCQ (negative: r=0.334, p=0.002；positive: r=0.233, p=0.038). Identified craving-related prediction networks included the somato-motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal-parietal network (FPN)-SMN, FPN-DMN and FPN-SALN and increased connectivity of subcortical network (SCN)-DMN, SCN-SALN and SCN-SMN were positively correlated with craving levels. Conclusions: These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.

Longitudinal resting-state functional connectivity changes in the insular subdivisions of abstinent individuals with opioid use disorder.

The insular cortex plays a critical role in reward circuitry involved with drug craving in substance use disorders. This study aimed to investigate whether opioid use disorder exhibit functional alterations in the insular circuitry after abstinence. Sixty-one opioid use disorder underwent resting-state and 3D-T1-weighted magnetic resonance imaging and completed craving questionnaires at baseline and after 8 months of abstinence. Changes in resting-state functional connectivity in the insular cortex and their correlations with craving were analyzed. Craving was reduced at follow-up compared with baseline. Compared with that at baseline, there was significantly increased resting-state functional connectivity between the right insular cortex and the superior frontal gyrus/anterior cingulate gyrus (family-wise error corrected) at follow-up. Changes in the functional connectivity of the right dorsal anterior insula/posterior insula with the bilateral superior frontal gyrus were negatively correlated with changes in craving. Our results demonstrated the presence of changes in functional connectivity of the insula in opioid use disorder after protracted abstinence, providing novel evidence of a correlation between craving changes and changes in the neurocircuitry of insular cortex subdivision after abstinence. This study reveals the possibility of neuroplasticity after protracted abstinence, providing insight for future abstinence therapies and rehabilitation procedures for patients with substance use disorders.

Potential brain recovery of frontostriatal circuits in heroin users after prolonged abstinence: A preliminary study.

Neuroscientists have devoted efforts to explore potential brain recovery after prolonged abstinence in heroin users (HU). However, not much is known about whether frontostriatal circuits can recover after prolonged abstinence in HU. An eight-month longitudinal study was carried out for HU. Two MRI scans were obtained at baseline (HU1) and 8-month follow-up (HU2). The functional and structural connectivities of dorsal and ventral frontostriatal pathways were measured by resting-state functional connectivity (RSFC) and diffusion tensor imaging (DTI). Correlation analyses were employed to reveal the associations between neuroimaging and behavioral changes. Results suggested that relative to healthy controls (HCs), HU1 showed lower fractional anisotropy (FA) in the right dorsolateral prefrontal cortex (DLPFC)-to-caudate tracts and medial orbitofrontal cortex (mOFC)-to-nucleus accumbens (NAc) tracts as well as decreased RSFC in the left mOFC-NAc circuits. Longitudinal results revealed reduced craving and enhanced cognitive control in HU2 compared with HU1. After prolonged abstinence, HU2 showed increased FA values in the right DLPFC-caudate and mOFC-NAc tracts as well as increased RSFC strength in the bilateral mOFC-NAc circuits compared with HU1. In addition, changes in RSFC and FA values in the right mOFC-NAc circuit were negatively correlated with craving score changes. Similarly, negative correlations were also found between changes of RSFC in the bilateral DLPFC-caudate circuits and TMT-A scores. We provided scientific evidence for brain recovery of the dorsal and ventral frontostriatal circuits in HU after prolonged abstinence, and these circuits may be potential neuroimaging biomarkers for cognition and craving changes.

Recovery of superior frontal gyrus cortical thickness and resting-state functional connectivity in abstinent heroin users after 8 months of follow-up.

Compared with healthy controls, heroin users (HUs) show evidence of structural and functional brain alterations. However, little is known about the possibility of brain recovery after protracted heroin abstinence. The purpose of this study was to investigate whether brain recovery is possible after protracted abstinence in HUs. A total of 108 subjects with heroin addiction completed structural and functional scans, and 61 of those subjects completed 8-month follow-up scans. Resting-state data and 3D-T1 MR images were collected for all participants, first at baseline and again after 8 months. Cognitive function and craving were measured by the Trail Making Test-A (TMT-A) and Visual Analog Scale for Craving, respectively. The cortical thickness and resting-state functional connectivity (RSFC) differences were then analyzed and compared between baseline and follow-up, and correlations were obtained between neuroimaging and behavioral changes. HUs demonstrated improved cognition (shorter TMT-A time) and reduced craving at the follow-up (HU2) relative to baseline (HU1), and the cortical thickness in the bilateral superior frontal gyrus (SFG) was significantly greater at HU2 than at HU1. Additionally, the RSFC of the left SFG with the inferior frontal gyrus (IFG), insula, and nucleus accumbens and that of the right SFG with the IFG, insula and orbitofrontal cortex (OFC) were increased at HU2. The changes in TMT-A time were negatively correlated with the RSFC changes between the left SFG and the bilateral IFG, the bilateral caudate, and the right insula. The changes in craving were negatively correlated with the RSFC changes between the left OFC and the bilateral SFG. Our results demonstrated that impaired frontal-limbic neurocircuitry can be partially restored, which might enable improved cognition as well as reduced craving in substance-abusing individuals. We provided novel scientific evidence for the partial recovery of brain circuits implicated in cognition and craving after protracted abstinence.

Changes in ALFF and ReHo values in methamphetamine abstinent individuals based on the Harvard-Oxford atlas: A longitudinal resting-state fMRI study.

Methamphetamine (MA) abuse has become a global public health problem due to damage to various systems throughout the body, especially the central nervous system. However, the differences in resting-state brain function between short-term and long-term abstinence, the pros and cons of treatments, and the relationship between resting-state brain function and behavioral tests are unknown. Sixty-three MA abstinent individuals were followed up for nearly 1 year and treated with three different methods. The amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) based on the Harvard-Oxford atlas (HOA) were measured by resting-state functional magnetic resonance imaging (fMRI). Impulsivity was evaluated by the Barratt Impulsivity Scale-11 (BIS-11). Brain regions with significant increases in ALFF and ReHo values in the long-term abstinent group compared to the short-term abstinent group were around the right frontal pole (McKetin et al., 2012, https://doi.org/10.1111/j.1360-0443.2012.03933.x) and right middle frontal gyrus (Wang et al., 2015, https://doi.org/10.1371/journal.pone.0133431). There were no significant differences among the three groups that experienced long-term abstinence. The changes in ALFF and ReHo in the right middle frontal gyrus were significantly associated with BIS total scores, BIS attention scores, and BIS nonplanning scores. The right middle frontal gyrus is a critical region in MA long-term abstinent individuals exposed to therapeutic intervention, and this region may be useful, when combined with BIS-11, as a potential biomarker to identify the effect of abstinence with therapeutic intervention in MA individuals.

Survivors of COVID-19 exhibit altered amplitudes of low frequency fluctuation in the brain: a resting-state functional magnetic resonance imaging study at 1-year follow-up.

Although some short-term follow-up studies have found that individuals recovering from coronavirus disease 2019 (COVID-19) exhibit anxiety, depression, and altered brain microstructure, their long-term physical problems, neuropsychiatric sequelae, and changes in brain function remain unknown. This observational cohort study collected 1-year follow-up data from 22 patients who had been hospitalized with COVID-19 (8 males and 11 females, aged 54.2 ± 8.7 years). Fatigue and myalgia were persistent symptoms at the 1-year follow-up. The resting state functional magnetic resonance imaging revealed that compared with 29 healthy controls (7 males and 18 females, aged 50.5 ± 11.6 years), COVID-19 survivors had greatly increased amplitude of low-frequency fluctuation (ALFF) values in the left precentral gyrus, middle frontal gyrus, inferior frontal gyrus of operculum, inferior frontal gyrus of triangle, insula, hippocampus, parahippocampal gyrus, fusiform gyrus, postcentral gyrus, inferior parietal angular gyrus, supramarginal gyrus, angular gyrus, thalamus, middle temporal gyrus, inferior temporal gyrus, caudate, and putamen. ALFF values in the left caudate of the COVID-19 survivors were positively correlated with their Athens Insomnia Scale scores, and those in the left precentral gyrus were positively correlated with neutrophil count during hospitalization. The long-term follow-up results suggest that the ALFF in brain regions related to mood and sleep regulation were altered in COVID-19 survivors. This can help us understand the neurobiological mechanisms of COVID-19-related neuropsychiatric sequelae. This study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University (approval No. 2020S004) on March 19, 2020.

Persistent white matter changes in recovered COVID-19 patients at the 1-year follow-up.

There is growing evidence that severe acute respiratory syndrome coronavirus 2 can affect the CNS. However, data on white matter and cognitive sequelae at the 1-year follow-up are lacking. Therefore, we explored these characteristics in this study. We investigated 22 recovered coronavirus disease 2019 (COVID-19) patients and 21 matched healthy controls. Diffusion tensor imaging, diffusion kurtosis imaging and neurite orientation dispersion and density imaging were performed to identify white matter changes, and the subscales of the Wechsler Intelligence scale were used to assess cognitive function. Correlations between diffusion metrics, cognitive function and other clinical characteristics were then examined. We also conducted subgroup analysis based on patient admission to the intensive care unit. The corona radiata, corpus callosum and superior longitudinal fasciculus had a lower volume fraction of intracellular water in the recovered COVID-19 group than in the healthy control group. Patients who had been admitted to the intensive care unit had lower fractional anisotropy in the body of the corpus callosum than those who had not. Compared with the healthy controls, the recovered COVID-19 patients demonstrated no significant decline in cognitive function. White matter tended to present with fewer abnormalities for shorter hospital stays and longer follow-up times. Lower axonal density was detected in clinically recovered COVID-19 patients after 1 year. Patients who had been admitted to the intensive care unit had slightly more white matter abnormalities. No significant decline in cognitive function was found in recovered COVID-19 patients. The duration of hospital stay may be a predictor for white matter changes at the 1-year follow-up.

Neuropsychiatric symptoms associated with the COVID-19 and its potential nervous system infection mechanism: the role of imaging in the study.

The epidemic of coronavirus disease 2019 (COVID-19) has broken the normal spread mode of respiratory viruses, namely, mainly spread in winter, resulting in over 230 million confirmed cases of COVID-19. Many studies have shown that severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can affect the nervous system by varying degrees. In this review, we look at the acute neuropsychiatric impacts of COVID-19 patients, including acute ischemic stroke, encephalitis, acute necrotizing encephalopathy, dysosmia, and epilepsy, as well as the long-term neuropsychiatric sequelae of COVID-19 survivors: mental disorder and neurodegenerative diseases. In particular, this review discusses long-term changes in brain structure and function associated with COVID-19 infection. We believe that the traditional imaging sequences are important in the acute phase, while the nontraditional imaging sequences are more meaningful for the detection of long-term neuropsychiatric sequelae. These long-term follow-up changes in structure and function may also help us understand the causes of neuropsychiatric symptoms in COVID-19 survivors. Finally, we review previous studies and discuss some potential mechanisms of SARS-CoV-2 infection in the nervous system. Continuous focus on neuropsychiatric sequelae and a comprehensive understanding of the long-term impacts of the virus to the nervous system is significant for formulating effective sequelae prevention and management strategies, and may provide important clues for nervous system damage in future public health crises.

Brainstem Congestion Due to Dural Arteriovenous Fistula at the Craniocervical Junction: Case Report and Review of the Literature.

BACKGROUND: Dural arteriovenous fistulas (DAVFs) at the craniocervical junction are rare. Clinical manifestations range from acute or chronic myelopathy to subarachnoid hemorrhage to brainstem dysfunction. We encountered 4 cases of DAVFs at the craniocervical junction with progressive brainstem dysfunction and investigated the typical magnetic resonance imaging (MRI) features using T2-weighting imaging, susceptibility-weighted imaging, diffusion-weighted imaging, and contrast-enhanced imaging. Literature review revealed 10 case reports of DAVFs at the craniocervical junction manifesting with brainstem dysfunction. CASE DESCRIPTION: Four patients presented with DAVFs at the craniocervical junction with progressive brainstem dysfunction. Two patients underwent midline suboccipital craniotomy and C1 laminectomy, and 1 patient underwent transarterial endovascular embolization with Onyx 18 under general anesthesia. All neurologic deficits gradually improved after the operation. In the fourth case, the patient received conservative treatment and did not undergo any surgical procedure. MRI showed high signal intensity on T2-weighted imaging, magnetic resonance angiography, and magnetic resonance venography. Abnormal dilated vessels and flow-void signs around the lesions were detected on susceptibility-weighted imaging and contrast-enhanced images. Two cases revealed no abnormalities and had improved neurological deficits than those showed on diffusion-weighted imaging. CONCLUSIONS: Susceptibility-weighted imaging, diffusion-weighted imaging, or contrast-enhanced scanning should be used during MRI examination of patients with progressive brainstem dysfunction to differentiate DAVFs at the craniocervical junction from other diseases, such as glioma or infection. Prompt diagnosis using MRI is of great significance in producing good functional outcomes of the patients.