Keywords: DWI/DTI/DKI, Brain, glymphatic system, along perivascular space, clinical fatigue

Motivation: Glymphatic abnormalities have been reported in several neurodegenerative disorders. However, glymphatic function has not been thoroughly investigated in multiple sclerosis, especially its relationship with clinical fatigue.
 

Goal(s): We aimed to investigate glymphatic system function in multiple sclerosis and to evaluate its association with clinical fatigue. 

Approach: We prospectively enrolled 36 multiple sclerosis patients and 31 healthy controls. All subjects underwent diffusion tensor imaging, and the along perivascular space (ALPS) indexes were calculated. Correlations between ALPS indexes and clinical fatigue parameters were analyzed.

Results: The brain glymphatic system is impaired in multiple sclerosis. Impaired glymphatic function was associated with multiple sclerosis-related fatigue.

Impact: Non-invasive diffusion-based imaging approach could be used as a proxy for displaying an impaired glymphatic system in multiple sclerosis patients, suggesting that glymphatic impairment may be a pathological mechanism underpinning clinical fatigue. 

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Motivation: Differentiation between functioning and non-functioning pituitary adenoma (PA) is clinically relevant. Feasibility of their microstructural differentiation is undetermined.

Goal(s): To investigate whether the time-dependent diffusion MRI can distinguish functioning from non-functioning PA.

Approach: Twenty-four patients with functioning and 30 with non-functioning PA were examined. Pituitary DWI was performed using inner FOV EPI based on 2D-selective radiofrequency excitations with oscillating (diffusion time=7.1ms) and pulsed (36.3ms) gradient preparations. ADC change (cADC) and relative ADC change (rcADC) between two diffusion-times were calculated.

Results: cADC was significantly higher in functioning than in non-functioning PAs (P=0.012), showing that time-dependent diffusion MRI can distinguish them.

Impact: Our results clarified that there are microstructural differences between functional and non-functional pituitary adenomas. Time-dependent diffusion MRI of the pituitary gland can detect their microstructural characteristics, providing clues as to their imaging differentiation.

Keywords: DWI/DTI/DKI, Diffusion Tensor Imaging

Motivation: The five-year survival of pediatric CNS tumors has increased from 57% in 1975 to 77% in 2015. Despite these improvements, survivors are at risk for cognitive sequelae resulting from disease and treatment exposures.

Goal(s): Evaluate the correlations between substructure white matter integrity and neurocognitive outcomes. 

Approach: The current study examined associations between longitudinal change in substructure DTI and neurocognitive outcomes in 61 pediatric brain tumor patients.

Results: Moderate correlations were found between mean diffusivity in the middle cerebellar peduncle and working memory, fractional anisotropy in the inferior cerebellar peduncle and intelligence quotient, and axial diffusivity in the corpus callosum and processing speed.

Impact: Quantifying the correlation between longitudinal change in substructure DTI and cognitive outcomes in pediatric brain tumor patients will aid radiation oncologists in the pursuit of substructure-informed treatment planning by limiting dose to brain substructures sensitive to specific neurocognitive domains.

Keywords: Diffusion Analysis & Visualization, Kidney

Motivation: Glymphatic function assessed by diffusion tensor image analysis along the perivascular space (DTI-ALPS) index might be associated with cognitive function.

Goal(s): To examine the glymphatic function in patients who receive regular hemodialysis and its relationship with clinical indices.

Approach: Partial correlation analysis was applied to assess the relationship between ALPS index and clinical markers with age and sex as covariates.

Results: Left ALPS index is positively correlated with immediate recall scores after adjusting for age and gender.

Impact: Glymphatic function and hemoglobin levels are associated with memory dysfunction in hemodialysis patients, offering a potential way to improve memory function in this population.

Keywords: Microstructure, Epilepsy

Motivation: Radiological assessment of focal cortical dysplasia (FCD), the most common form of drug-resistant paediatric epilepsy, remains challenging on conventional MRI.

Goal(s): Our goal was to test whether tensor-valued diffusion encoding, which provides metrics related to size variance and microscopic anisotropy, can be used to detect and characterise FCD. 

Approach: Paediatric patients were scanned with a prototype tensor-valued diffusion encoding sequence and parameter estimates were visually and statistically compared.

Results: While the diffusion maps provide no strong contrast compared to structural images, our statistical results reflect FCD microstructural heterogeneity when comparing FCD and homotopic grey matter regions.

Impact: Comparison of tensor-valued diffusion encoding parameters reflects FCD heterogeneity, potentially relating to lesion subtype. Despite weak contrast for FCD detection at present, this method could aid in vivo FCD characterisation in radiological assessment workflow prior to surgery.

Keywords: DWI/DTI/DKI, Brain, Glymphatic system

Motivation: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the brain and leads to diffusion impairment. 

Goal(s): To evaluate the alterations of glymphatic function in AD and explore its association with cognition and blood biomarkers. 

Approach: We investigate the functionality of  glymphatic system (GS) in patients with AD using diffusion tensor imaging analysis along with the perivascular space (DTI-ALPS). 
 

Results: Individuals with AD had a significantly lower ALPS index compared to the healthy controls. Moreover, the decreased ALPS index was associated with impaired cognitive function, as reflected through the Mini-Mental State Examination (MMSE) score and higher blood biomarker ptau-181 levels. 

Impact: The results demonstrate that the feasibility of DTI-ALPS, which can be used for research on glymphatic system function in AD patients. ALPS-index is expected to become a promising imaging marker and may provide novel targets for clinical diagnosis of AD.  

Keywords: Microstructure, Microstructure

Motivation: Relaxation-Diffusion Spectrum Imaging (RDSI) characterizes tissue apparent relaxation coefficients and factors out the effects of intra-voxel orientation heterogeneity. However, it needs to be clarified how RDSI has potential in neurosurgical research.

Goal(s): We aim to investigate how RDSI can be conducive to characterizing tissue abnormalities in various neurosurgical patients.

Approach: We presented two RDSI-derived indices, R2RF and RICR, to characterize tissue abnormalities. We examined the indices with an in vivo dataset, acquired using a clinical scanner, involving eight different health conditions.

Results: R2RF and RICR have potential in lesion grading and treatment response evaluation.

Impact: Our study promises to improve its clinical applicability and enhance our understanding of glioma biology and treatment response.

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques, MAPMRI

Motivation: To better understand the pathophysiological progression mechanism of childhood basic-type IXT and develop an accurate approach for early diagnosis. 

Goal(s): To find a valuable tool in reflecting the pathological changes of the visual center pathway in IXT children. 

Approach: A voxel-wise analysis was performed for MAPMRI-derived parameters between IXT patients and health controls, and a DTI analysis was used as reference.

Results: Compared with DTI, MAPMRI-derived parameters demonstrated significant differences in more brain regions associated with visual cortex. Brain regions with microstructural changes include MOG.R, SOG.R, IOG.R, and MTG.R.

Impact: We firstly explored MAPMRI’s value in detecting abnormal pathological changes of the primary and higher visual center, and the ocular movement pathway in children with basic IXT. This discovery enhances comprehension of IXT's pathology and offers insights for early diagnosis.

Keywords: DWI/DTI/DKI, Neurodegeneration, HIV

Motivation: Neurocognitive impairment in HIV and compromised neuronal integrity are characterized by varying metabolite levels. However, ADC values of metabolites have not been reported.

Goal(s): To measure the metabolite ADC values at multiple locations in the brain and compare between HIV+ and healthy control groups.

Approach: Use a diffusion weighted radial echo planar spectroscopic imaging technique with single-shot diffusion trace-weighted scheme to measure the metabolite ADC values.

Results: Statistically significant variations were observed in Water and tCr ADCs. Further analysis of metabolite ratios showed significantly reduced tNAA and increased tCr and tCho in HIV patients compared to HC.

Impact: Metabolite ADC values in HIV brain compared to HC is demonstrated using single-shot diffusion trace-weighted DW-REPSI. Statistically significant variations were observed in Water and tCr ADCs. Metabolite ratios showed significantly reduced tNAA and increased tCr and tCho in HIV patients.

Keywords: Microstructure, Microstructure

Motivation: To investigate tumour-associated diffusion hyperintensities

Goal(s): Might provide some insight into tumour environment leading to restricted diffusion.

Approach: Extended diffusion range, with b-values from 0 to 10000 and two echo times, allowing for NNLS decomposition of diffusion spectra and T2 mapping.

Results: Restricted diffusion characterised.

Impact: Possibly relevant to  tumour cell migration and associated changes in the extracellular matrix.

Keywords: Diffusion Modeling, Neuro

Motivation: Many cortical pathologies are invisible via conventional MRI, making it difficult for clinicians to correctly diagnose and treat patients.

Goal(s): Our aim was to optimize advanced MRI acquisitions, making them sensitive to subtle cortical pathologies while at the same time reducing acquisition times to clinically-feasible durations.

Approach: We calculated the combined relaxation-diffusion signal to encompass surface relaxivity and T₂ effects. We used Monte-Carlo simulations to model the signal from healthy and pathological cortical neurons for different PGSE schemes.

Results: Our optimized sequences can distinguish pathology associated with focal cortical dysplasia from healthy tissue, and differentiate between focal cortical dysplasia subcategories.  

Impact: We calculate the combined relaxation-diffusion signal encompassing surface relaxivity and T₂ effects, and use it in Monte-Carlo simulations to optimize MRI sequences for subtle cortical lesion detection. Our methodology can be used by researchers to investigate other cortical pathologies.

Keywords: Diffusion Modeling, Tumor, OGSE

Motivation: Different clinical managements are required for brain tumors such as glioblastoma, meningioma and metastases, with existing MRI techniques showing limitations in distinguishing them.

Goal(s): The study aims to validate the utility of td-dMRI to enhance the accuracy of brain tumors characterization, using the IMPULSED model to distinguish microstructural distinctions.

Approach: We used td-dMRI to explore microstructural mapping in glioblastoma, meningioma, and lung cancer patients with brain metastases by IMPULSED model, focusing on the parameters D_ex, d, and v_in to differentiate these brain tumors.

Results: The cell size and extracellular diffusivity of these tumors are distinctly different.

Impact: This study demonstrated that td-dMRI can non-invasively differentiate between glioblastomas, meningiomas and metastases. It proposes a potential change in diagnostic protocols, offering a pathway to more personalized management while reducing reliance on contrast agents.

Keywords: Diffusion Acquisition, Diffusion Tensor Imaging

Motivation: High-resolution DWI plays a crucial role in brain tumor diagnosis. Previous studies have introduced two high-resolution distortion-free DWI techniques: PSF and BLADE. However, no one has yet compared the two in brain MR imaging.

Goal(s): To compare the image quality of PSF and BLADE in high-resolution DWI.

Approach: In this study, scan parameters were adjusted to achieve the optimized image quality for PSF and BLADE. Subsequently, scans were performed on patients, and the final image quality was compared.

Results: With scanning times being similar, PSF exhibits a superior SNR compared to BLADE while its performance is suboptimal at the boundaries of brain tissues.

Impact: A preliminary comparison of the image quality between PSF and BLADE has been conducted, paving the way for more in-depth clinical research in areas such as diagnostic accuracy and imaging quality control.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Motivation: The diffusion dispersion rate (DDR, slope of diffusion with frequency of oscillating-gradient-spin-echo - OGSE) has been probed in animal stroke models and healthy human brain, but has not been explored in human acute ischemic stroke.

Goal(s): Our goal is to map DDR in human stroke and explore its insight on the biophysical mechanisms related to reduced diffusion in stroke.

Approach: DDR maps using OGSE 25/40/50Hz were acquired in 12 acute ischemic stroke patients.

Results: DDR is significantly higher in ischemic lesions relative to contralateral white matter, and is highest in brain regions with presumably larger axons.

Impact: The application of oscillating-gradient-spin-echo diffusion MRI with different oscillating frequencies highlights greater diffusion time effects in acute stroke than healthy tissue, which agrees with earlier preclinical ischemia models, and implicates changes of short range microstructural disorder (e.g. beading).

Keywords: Simulation/Validation, Diffusion/other diffusion imaging techniques, MR-linac, image-guided radiation therapy, repeatability

Motivation: In order to use DWI on MR-linacs to adapt head and neck cancer radiotherapy treatment plans based on response, the variability in ADC must be characterized.

Goal(s): To quantify the repeatability of ADC on a 1.5T MR-linac in a large cohort (37 head and neck cancer patients).

Approach: Patients were imaged with echo planar imaging-DWI twice before the start of radiotherapy. Mean ADC values of primary tumors and lymph nodes were compared across time points using repeatability metrics.

Results: Repeatability coefficients were 53.0%/35.5% for tumors/nodes, indicating that this DWI sequence is insufficient for detecting clinically significant ADC changes and must be further optimized.

Impact: Our DWI test-retest results demonstrate that the current widely implemented EPI-DWI sequence for head and neck cancers on 1.5T MR-linacs has substantial ADC variability across time points and needs to be further refined.

Keywords: Microstructure, Microstructure, Model fitting, Brain Tumours

Motivation: Complex multi-compartment models of diffusion MRI, as the recent adaptation of VERDICT-MRI for brain tumours, can provide important microstructural information, but traditional fitting is time-consuming and may not be accurate.

Goal(s): To explore the feasibility of deep-learning-based fitting of VERDICT for brain tumours.

Approach: We fit the VERDICT model to data from 15 glioma patients using both traditional and deep-learning approaches. We compared the resulting parameters between the two methods and with histology.

Results: VERDICT estimates from deep-learning and traditional fitting showed a good correlation and reflected histology features. The deep-learning fitting was much faster once the model was trained.

Impact: We have successfully used deep learning to fit the complex VERDICT model for brain tumour microstructure. As deep-learning fitting is much faster and potentially more precise than traditional methods, this could facilitate the clinical application of VERDICT for brain tumours.