Keywords: Blood Vessels, Blood vessels, White matter hyperintensity, hemodynamic

Motivation: The morphology of cerebral arteries contributes to the development of white matter hyperintensity (WMH), yet the influence of arterial blood flow on WMH remains unclear.

Goal(s): Identify associations of cerebral arterial flow features with WMH.

Approach: 2631 individuals were involved. Arterial flow features were obtained using the individual-specific simplified hemodynamic model. WMHs were quantified from T2-FLAIR images.

Results: Both increased mean flow rate and pressure were associated with increased WMH volume. Adjacent Lesion Terminal Arterial Branches exhibited greater length, tortuosity, lower mean flow rates and pressure drops.

Impact: The hemodynamic features surrounding WMH exhibited significant difference compared to distant arteries. Such morphology and corresponding hemodynamic changes might contribute to the development of WMH.

Keywords: Vessels, Atherosclerosis, Carotid artery, Hemodynamic, Geometric

Motivation: Carotid artery geometry and hemodynamics are considered as potential imaging markers of atherosclerotic plaque formation risk.

Goal(s): 4D flow MRI has been widely used in large blood vessels of the heart, with relatively few applications in head and neck blood vessels.

Approach: This study, 4D flow MRI was used to evaluate the carotid artery hemodynamics, and the geometric characteristics were fused to explore the hemodynamic and geometric mechanism of carotid plaque formation.

Results: The large bifurcation angle and the low tortuosity are geometric risk factors for carotid bifurcation plaque formation. Low PG and low WSS are hemodynamic factors promoting plaque formation.

Impact: 4D flow MRI can directly measure very comprehensive hemodynamic parameters in vivo from any direction and angle during different cardiac cycles, and can visualize blood flow direction and status. However, it is not widely accepted in clinical practice.

Keywords: Vessels, Blood vessels, Systemic Lupus Erythematosus

Motivation: To observe the inflammatory changes of cerebral vessels in patients with early SLE  by high-resolution magnetic resonance vessel wall imaging , and analyze its relationship with disease activity and small vessel disease.

Goal(s): Aimed to evaluate the potential of HR-VWI in predicting the development and clinical severity of brain lesions.

Approach: The imaging features of inflammatory changes of cerebral vessel wall in each group were observed and the vasculitis score was calculated. The correlation between vasculitis score and disease activity in SLE patients was analyzed.

Results: As the severity of cerebral vasculitis increases, the disease activity and neuropsychiatric symptoms of SLE patients also increase.

Impact: This study is the first to use HR-VWI to observe cerebral vessel wall lesions in large-scale early SLE patients, which has the potential to be used as an imaging biomarker to predict the development of brain lesions.

Keywords: Peripheral Nerves, Brain

Motivation: DSC MRI may provide clues to predict hemifacial spasm (HFS) re-appearing phenomenon after surgery (HFSrapas) after microvascular decompression (MVD).

Goal(s): To predict HFSrapas with DSC parameter indices using a machine learning analysis

Approach: Sixty patients who underwent MVD for HFS were enrolled. DSC parameters were used to predict HFSrapas using a ROC curve and machine learning methods.

Results: The rCBF value was significantly decreased in the reappearing group. The extraction fraction parameter was best predicted by the Navie Bayes (NB) model.

Impact: DSC perfusion MRI is a useful tool to predict HFS recurrence before intra-operation and helps neurosurgeons anticipate possible problems during MVD surgery.

Keywords: White Matter, Elastography, IVIM,virtual-MRE,brain,Elastography

Motivation: The IVIM-based Virtual Elastography conversion formula based on liver data has been established and verified, but there are no studies using brain MRE data and IVIM data to explore the correlation between the two and establish the relevant conversion formula.

Goal(s): This study aims to validate the relationship between shear stiffness and sADC under different combinations of b-values and derive a conversion formula for vMRE in the brain.

Approach: IVIM and MRE data were collected and quantified in healthy adults.

Results: The correlation between sADC and  shear stiffness has been confirmed, and the conversion formula of each brain region has been preliminarily established.

Impact: In this study, the feasibility of brain vMRE was verified for the first time based on brain MRE and IVIM data, and the conversion formulas of different brain regions were preliminatively established.

Keywords: Other Neurodegeneration, Diabetes

Motivation: The dynamic interaction of time changes in the brain to explore the role of T2DM in brain damage and cognitive decline.

Goal(s): To investigate how the dynamic network reconfiguration in T2DM patients and the effect of abnormal blood glucose on the internal network of the brain.

Approach: Dynamic functional connectivity analyses and multi-layer network analysis were performed to evaluate the nodal flexibility, network stability and temporal variability of network efficiency.

Results: The capability to communicate within or between functional networks connectivity and flexibility are impaired in T2DM and linked to blood glucose levels.

Impact: This study is the first to investigate brain injury in T2DM patients by integrating dynamic connectivity and topological features. Dynamic functional connectivity could be a useful imaging biomarker to monitor cognitive changes in T2DM in the future.

Keywords: Other Neurodegeneration, fMRI (resting state), breast cancer; δ-catenin; regional homogeneity; degree centrality

Motivation: Recent studies have shown that high expression of δ-catenin in breast cancer is often indicative of a poor prognosis. There is a lack of studies on δ-catenin and abnormal brain function.

Goal(s): We hypothesized that high δ-catenin expressers have more severe brain function abnormalities.

Approach: We prospectively and rigorously recruited 66 patients with newly diagnosed breast cancer who underwent BOLD fMRI scanning and image analysis before and after chemotherapy.

Results: Results found that abnormal local neural synchronization in brain was more severely impaired after chemotherapy in breast cancer patients with high δ-catenin expression, compared with those with low expression.

Impact: The analysis results demonstrated that high δ-catenin expression was associated with extensive localized neural synchronization and functional abnormalities after chemotherapy. This contributes to further understanding of the deeper mechanisms of δ-catenin involvement in altered brain function in breast cancer.

Keywords: fMRI Analysis, Brain

Motivation: To evaluate the effect of gadolinium-based contrast agents (GBCAs) injection on the deep cerebral cortical nuclei using a non-invasive method.

Goal(s): To evaluate the magnetic susceptibility alteration in deep brain nuclei before and after Gadobutrol injection based on quantitative susceptibility mapping (QSM).

Approach: Magnetic susceptibility values of the brain stem and 14 subcortical nuclei were extracted from QSM image, and then compared before and after enhancement.

Results: Magnetic susceptibility in the left amygdala, right hippocampus and pallidum differed between pre- and post-enhancement. QSM is an effective and accurate technique to evaluate the magnetic susceptibility of deep brain nuclei before and after enhancement.

Impact: Susceptibility in specific deep gray matter altered after a single administration of Gadobutrol, which reflects differential sensitivity to gadolinium-based contrast agents. QSM acquired by multi-parametric sequence may be an effective method to detect small quantities of Gadobutrol deposition.

Keywords: Other Neurodegeneration, DSC & DCE Perfusion

Motivation: It is estimated that approximately 30% of cancer patients have detectable cognitive impairment before treatment. Despite these reports of cancer-related cognitive impairment, the mechanisms behind these phenomena remain unclear.

Goal(s): To investigate the relationship between blood-brain barrier (BBB) integrity, cerebral cortex volume, and cognitive dysfunction in untreated lung cancer  (LC) patients with non-brain metastases.

Approach: 3D anatomical imaging and DCE-MRI imaging were performed. Cognitive function was assessed using Montreal Cognitive Assessment (MoCA).

Results: We observed an association between BBB leakiness and altered brain structure and cognitive function.

Impact: These findings also suggest that BBB damage may be one of the mechanisms contributing to cognitive impairment in lung cancer patients.

Keywords: White Matter, Microstructure, Thalamus, SWI

Motivation: The in-vivo study of the Thalamic Reticular Nucleus is of fundamental interest and relies on the development of a pipeline for visualising and segmenting the structure.

Goal(s): Presented is a a potential framework for inducing contrast at the TRN boundary that can guide future studies in creating functional maps of the TRN.

Approach: T₁ weighted FLASH and susceptibility weighted imaging paradigms are explored in a number of participants and a novel segmentation approach is tested on these data sets.

Results: The TRN is visible to a variable degree in all participants and size stable masks of the structure are produced. 

Impact: This work is a stepping stone in the creation of a robust framework for visualising and segmenting the Thalamic Reticular Nucleus. It can help guide future studies which seek to explore the TRN function in-vivo.

Keywords: Infectious Disease, COVID-19, ME/CFS, hippocampus, infectious disease

Motivation: To study hippocampal atrophy in  long COVID and Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS patients). 

Goal(s): Our goal was to investigate hippocampal atrophy in long COVID and ME/CFS patients.

Approach: We used T1-weighted MP2RAGE data from 7T MRI and used FreeSurfer to estimate hippocampal subfield volumes in long COVID and ME/CFS patients. 

Results: We found that hippocampal subfield volumes were larger in long COVID and ME/CFS patients compared to HC. 

Impact: Our study showed atypical hippocampal atrophy in long COVID and ME/CFS patients indicating that existing brain research findings in ME/CFS patients may help better understand the neurological dysfunction in long COVID patients. 

Keywords: Other Neurodegeneration, Diabetes, diabetic kidney disease; hypothalamic

Motivation: The hypothalamus plays an important role in the progression of renal damage in diabetic kidney disease (DKD) patients, but the relationship between hypothalamic structure and renal function is currently unclear.

Goal(s): To investigate the relationship between hypothalamic structure and impaired renal function in DKD patients.

Approach: The hypothalamic subregion volume in DKD patients was quantitatively analyzed using T1-weighted magnetization prepared rapid gradient-echo MRI. The relationship between renal function and hypothalamic subregion volume was also explored.

Results: During DKD progression, reduced volume in the anterior-superior area of the hypothalamus, especially the paraventricular nucleus, was associated with worsening renal function.

Impact: The volume of the anterior-superior area of the hypothalamus may provide useful neuroimaging evidence of renal function damage in DKD patients, supporting the kidney-brain axis theory of DKD.

Keywords: Prenatal, Brain, Fetal spina bifida; deep learning; segmentation; brain development

Motivation: Spina bifida occurs during the first gestational month and causes lifelong disabilities. If fetuses with spina bifida are left undiagnosed or untreated, spinal cord defects are translated into brain abnormalities.

Goal(s): Our goal is to annotate brain regions in fetal MRIs to study typical and atypical fetal brain development in spina bifida.

Approach: We developed a deep learning fetal brain MRI segmentation method and modeled growth to statistically compare brain volumes of normal and pathological cohorts.

Results:  Our segmentation method reliably annotates fetal brain MRIs. We observed significant increase in the ventricles and significant reduction of the cerebellum in fetuses with spina bifida.

Impact: Fetal brain MRI segmentation with our segmentation model enables precise delineation of brain tissues and anatomical structures, allowing early detection of aberrant brain development due to congenital defects such as spina bifida.

Keywords: Infectious Disease, Infectious disease

Motivation: Portable, low-field MRI systems may represent the only viable strategy to monitor neurological manifestations of infectious diseases, such as Nipah virus (NiV), in vivo, and in low-resource settings.

Goal(s): To determine the optimal resolution for lesion detection at 0.05T and compare texture and area markers between 3T and 0.05T

Approach: We acquired 3T MR images of three NiV-exposed NHPs, simulated corresponding low-field images for lesion segmentation.

Results: We determined a minimum resolution requirement of 1.5 x 1.5 x 2 mm³ at 0.05T to manually segment NiV-induced brain lesions on T2w images and that 0.05T texture matches better with 3T data than lesion area.

Impact: The study determined the optimal resolution and textural feature required to monitor NiV-affected patients through prospective imaging at 0.05T to track lesions caused by NiV. It showed that textural was more consistent between the two field strengths than lesion area.

Keywords: Structural Connectivity, Elastography, gradient strength

Motivation: Enhancing the propagation efficiency of shear waves in deep tissues, improving the sensitivity of motion-sensitive sequences to small shear wave displacements, optimizing  inversion algorithms can enhance the quality of MRE images and increase the reliability of the results. Gradient strengt is one of the important factors affecting MRE images quality.

Goal(s): The aim of this study is to investigate the role of gradient field strength in whole-brain MRE images.

Approach: Keeping other parameters constant, varying the gradient strength of MRE yields parameter maps that are quantitatively compared.

Results: Increasing the gradient field strength appropriately can enhance the motion encoding of whole-brain MRE images.

Impact: Appropriate gradient field strength settings contribute to improving the quality of MRE images and enhancing the reliability of results

Keywords: White Matter, Quantitative Imaging

Motivation: Provide evidence for the positive effect of Mindfulness on sleep quality, and investigate the corresponding neuronal changes in the white matter.

Goal(s): Quantify the improvement in sleep quality following Mindfulness meditation in subjects suffering from sleep disorders, and correlate these to change in quantitative T₁, T₂ and proton-density values.

Approach: Meditation naïve subjects underwent MRI scans and filled sleep-quality questionnaires before and after participating in an 8-week MBSR course. Waitlist control group was scanned at the same time-points without intervention.

Results: Sleep quality improved significantly in the MBSR group, compared to controls. No changes were observed in qMRI values in the white matter.

Impact: Discover the psychological-physiological mechanism underlying the improvement of sleep following mindfulness practice; introduce new ways to study the effects of mindfulness; advance better and more personalized treatment plans for insomnia/sleep disorders.