Diagnostic Utility of Integration of Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast MR Perfusion Employing Split Bolus Technique in Differentiating High-Grade Glioma.

Background : Despite documented correlation between glioma grades and dynamic contrast-enhanced (DCE) magnetic resonance (MR) perfusion-derived parameters, and its inherent advantages over dynamic susceptibility contrast (DSC) perfusion, the former remains underutilized in clinical practice. Given the inherent spatial heterogeneity in high-grade diffuse glioma (HGG) and assessment of different perfusion parameters by DCE (extravascular extracellular space volume [Ve] and volume transfer constant in unit time [k-trans]) and DSC (rCBV), integration of the two into a protocol could provide a holistic assessment. Considering therapeutic and prognostic implications of differentiating WHO grade 3 from 4, we analyzed the two grades based on a combined DCE and DSC perfusion. Methods : Perfusion sequences were performed on 3-T MR. Cumulative dose of 0.1 mmol/kg of gadodiamide, split into two equal boluses, was administered with an interval of 6 minutes between the DCE and DSC sequences. DCE data were analyzed utilizing commercially available GenIQ software. Results : Of the 41 cases of diffuse gliomas analyzed, 24 were WHO grade III and 17 grade IV gliomas (2016 WHO classification). To differentiate grade III and IV gliomas, Ve cut-off value of 0.178 provided the best combination of sensitivity (88.24%) and specificity (87.50%; AUC: 0.920; p < 0.001). A relative cerebral blood volume (rCBV) of value 3.64 yielded a sensitivity of 70.59% and specificity of 62.50% ( p = 0.018). The k-trans value, although higher in grade III than in grade IV gliomas, did not reach statistical significance ( p = 0.108). Conclusion : Uniqueness of employed combined perfusion technique, treatment naïve patients at imaging, user-friendly postprocessing software utilization, and ability of Ve and rCBV to differentiate between grade III and IV gliomas ( p < 0.05) are the strengths of the present study, contributing to the existing literature and moving a step closer to achieving accurate MR perfusion-based glioma grading.

Multi-contrast echo-planar imaging sequence (Echo-planar imaging mix) in clinical situations demanding faster MRI-brain scans.

Objectives: The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods: This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results: The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41-1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (>90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion: The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient.

Central Nonenhancement Sign in Carotid Body Tumor on CT Angiography.

Carotid body tumors are rare benign tumors that arise in the carotid space of neck typically presenting as soft to firm, painless swelling in the neck. While specific imaging characteristics have been previously described for carotid body tumors, we report a new imaging sign in three cases of carotid body tumors on computed tomography angiography.

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment.

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetry including white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above.  Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS). We stratified 1961 persons with GDS ≤9 by age and cognitive score, and randomly selected 10% from each subgroup for MRI brain volumetry. Crude volumes were standardized to reflect percentage of intracranial volume.  Results MRI volumetry studies were done in 199 individuals (F/M = 90/109; 73 with body mass index (BMI) ≥25; 44 hypertensives; 29 diabetics; mean cognitive score 76.3). Both grey and white matter volumes decreased with increasing age. WMHV increased with age and hypertension. Grey matter volume (GMV) decreased with increasing WMHV. Positive predictors of cognition included standardized hippocampal volume (HCV), urban living, education, and BMI, while WMHV and age were negative predictors. Urban dwellers had higher cognitive scores than rural, and, paradoxically, smaller HCV.  Conclusion In this study of MRI volumetry correlated with age, cognitive scores and VRFs, increasing age and WMHV predicted lower cognitive scores, whereas urban living and hippocampal volume predicted higher scores. Age and WMHV also correlated with decreasing GMV. Further study is warranted into sociodemographic and biological factors that mutually influence cognition and brain volumes, including nutritional and endocrine factors, especially at lower cognitive score bands. In this study, at the lower KCB score bins, the lack of laboratory data pertaining to nutritional and endocrine deficiencies is a drawback that reflects the logistical limitations of screening large populations at the community level. Our volumetric data which is age and cognition stratified, and takes into account the vascular risk factors associated, nevertheless constitutes important baseline data for the Indian population. Our findings could possibly contribute to the formulation of baseline criteria for defining VCI in India and could help in early diagnosis and control of cognitive decline and its key risk factors.

Cerebellar and basal ganglia structural connections in humans: Effect of aging and relation with memory and learning.

Introduction: The cerebellum and basal ganglia were initially considered anatomically distinct regions, each connected via thalamic relays which project to the same cerebral cortical targets, such as the motor cortex. In the last two decades, transneuronal viral transport studies in non-human primates showed bidirectional connections between the cerebellum and basal ganglia at the subcortical level, without involving the cerebral cortical motor areas. These findings have significant implications for our understanding of neurodevelopmental and neurodegenerative diseases. While these subcortical connections were established in smaller studies on humans, their evolution with natural aging is less understood. Methods: In this study, we validated and expanded the previous findings of the structural connectivity within the cerebellum-basal ganglia subcortical network, in a larger dataset of 64 subjects, across different age ranges. Tractography and fixel-based analysis were performed on the 3 T diffusion-weighted dataset using Mrtrix3 software, considering fiber density and cross-section as indicators of axonal integrity. Tractography of the well-established cerebello-thalamo-cortical tract was conducted as a control. We tested the relationship between the structural white matter integrity of these connections with aging and with the performance in different domains of Addenbrooke's Cognitive Examination. Results: Tractography analysis isolated connections from the dentate nucleus to the contralateral putamen via the thalamus, and reciprocal tracts from the subthalamic nucleus to the contralateral cerebellar cortex via the pontine nuclei. Control tracts of cerebello-thalamo-cortical tracts were also isolated, including associative cerebello-prefrontal tracts. A negative linear relationship was found between the fiber density of both the ascending and descending cerebellum-basal ganglia tracts and age. Considering the cognitive assessments, the fiber density values of cerebello-thalamo-putaminal tracts correlated with the registration/learning domain scores. In addition, the fiber density values of cerebello-frontal and subthalamo-cerebellar (Crus II) tracts correlated with the cognitive assessment scores from the memory domain. Conclusion: We validated the structural connectivity within the cerebellum-basal ganglia reciprocal network, in a larger dataset of human subjects, across wider age range. The structural features of the subcortical cerebello-basal ganglia tracts in human subjects display age-related neurodegeneration. Individual morphological variability of cerebellar tracts to the striatum and prefrontal cortex was associated with different cognitive functions, suggesting a functional contribution of cerebellar tracts to cognitive decline with aging. This study offers new perspectives to consider the functional role of these pathways in motor learning and the pathophysiology of movement disorders involving the cerebellum and striatum.

Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study.

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

Non-invasive assessment of cerebral hemoglobin parameters in intracranial dural arteriovenous fistula using functional near-infrared spectroscopy-A feasibility study.

Purpose: The purpose of this study was to assess the feasibility of non-invasive assessment of cerebral hemodynamics using functional near-infrared spectroscopy (fNIRS) in patients with intracranial dural arteriovenous fistula (DAVF) and to correlate the hemodynamic changes with definitive endovascular treatment. Methodology: Twenty-seven DAVF patients and 23 healthy controls underwent 20-mins task-based functional near-infrared spectroscopy and neuropsychology evaluation. The mean change in the hemoglobin concentrations obtained from the prefrontal cortex was assessed for oxyhemoglobin, deoxyhemoglobin, and oxygen saturation (HbO, HbR, and SO2, respectively). The fNIRS data were analyzed and correlated with improvement in neuropsychology scores at 1-month follow-up. Results: There was a significant reduction in HbO in the patient group, while it increased in controls (-2.57E-05 vs. 1.09E-04 mM, p < 0.001). The reduced HbO significantly improved after embolization (-2.1E-04 vs. 9.9E-04, p = 0.05, q = 0.05). In patients with aggressive DAVF (Cognard 2B and above), the change was highly significant (p < 0.001; q = 0.001). A moderate correlation was observed between MMSE scores and HbO changes (ρ = 0.4). Conclusion: fNIRS is a useful non-invasive modality for the assessment of DAVF, and could potentially assist in bedside monitoring of treatment response.

Explainable artificial intelligence model to predict brain states from fNIRS signals.

Objective: Most Deep Learning (DL) methods for the classification of functional Near-Infrared Spectroscopy (fNIRS) signals do so without explaining which features contribute to the classification of a task or imagery. An explainable artificial intelligence (xAI) system that can decompose the Deep Learning mode's output onto the input variables for fNIRS signals is described here. Approach: We propose an xAI-fNIRS system that consists of a classification module and an explanation module. The classification module consists of two separately trained sliding window-based classifiers, namely, (i) 1-D Convolutional Neural Network (CNN); and (ii) Long Short-Term Memory (LSTM). The explanation module uses SHAP (SHapley Additive exPlanations) to explain the CNN model's output in terms of the model's input. Main results: We observed that the classification module was able to classify two types of datasets: (a) Motor task (MT), acquired from three subjects; and (b) Motor imagery (MI), acquired from 29 subjects, with an accuracy of over 96% for both CNN and LSTM models. The explanation module was able to identify the channels contributing the most to the classification of MI or MT and therefore identify the channel locations and whether they correspond to oxy- or deoxy-hemoglobin levels in those locations. Significance: The xAI-fNIRS system can distinguish between the brain states related to overt and covert motor imagery from fNIRS signals with high classification accuracy and is able to explain the signal features that discriminate between the brain states of interest.

Treatable Hereditary Manganese Transport Disorder: Novel SLC30A10 Mutation and its Characteristic Neuroimaging Appearance in Two Siblings.

Hypermanganesemia with dystonia and polycythemia along with liver cirrhosis is a rare syndromic complex that is associated with a characteristic genetic mutation and a typical appearance in the T1-weighted noncontrast image. In this article, we reported the neuroimaging findings of two siblings affected by this syndrome. There are few reported cases in literature with similar findings. Diagnosing this problem will help in improving the outcomes as the condition is treatable. We reviewed the clinical and imaging findings of this condition and the differential diagnosis related to it.

High-Resolution Vessel Wall Imaging in Primary Angiitis of Central Nervous System.

BACKGROUND: High-resolution vessel wall imaging (HRVWI) can aid in differentiating the various intracranial vasculopathies, but has been sparingly used in the diagnosis of primary angiitis of central nervous system (PACNS). This study is aimed to describe the vessel wall imaging characteristics of PACNS. MATERIALS AND METHODS: Patients with confirmed diagnosis of PACNS according to the Calabrese and Mallek criteria who had abnormal HRVWI were included in this retrospective descriptive study. Magnetic resonance image of brain, conventional four-vessel cerebral digital subtraction angiogram, and HRVWI were read by a neuroradiologist. The vessel wall parameters assessed were T1W and T2W appearances, pattern of wall thickening and contrast enhancement, and remodeling index. RESULTS: HRVWI done in 21 patients with PACNS yielded abnormality in 20 (95.2%) who were included in the analysis. The mean age at presentation was 42.55 ± 9.48 years and 14 (70%) were males. The median number of vessels involved were four (range 2-12). The commonest vessels affected were proximal middle cerebral artery (70%) and internal carotid artery (55%). Vessel wall thickening was concentric, eccentric, and absent in 12 (60%), 1 (5%), and 7 (35%) patients, respectively. Vessel wall enhancement was diffuse in 17 (85%), eccentric in 1 (5%), and absent in 2 (10%) patients. One patient had T2W hyperintense stenotic lesion. Remodeling index was negative in 11 (55%) patients. CONCLUSION: Distinctive vessel wall appearances were observed by HRVWI in PACNS, concentric vessel wall thickening and enhancement being more frequent. Hence, HRVWI can be considered as an additional noninvasive imaging modality in the diagnosis of PACNS.

Relationship between Cerebral Perfusion on Arterial Spin Labeling (ASL) MRI with Brain Volumetry and Cognitive Performance in Mild Cognitive Impairment and Dementia due to Alzheimer's Disease.

CONTEXT: Cerebral blood flow (CBF) measurement using arterial spin labelling (ASL) MRI sequences has recently emerged as a prominent tool in dementia research. AIMS: To establish association between quantified regional cerebral perfusion and gray matter (GM) volumes with cognitive measures in mild cognitive impairment (MCI) and early Alzheimer's Dementia (AD), using three dimensional fast spin echo pseudo-continuous ASL MRI sequences. SETTINGS AND DESIGN: Hospital-based cross-sectional study. METHODS AND MATERIAL: Three age-matched groups, i.e., 21 cognitively normal healthy controls (HC), 20 MCI and 19 early AD patients diagnosed using neuropsychological tests and who consented for multimodality 3T MRI were recruited for the study. STATISTICAL ANALYSIS USED: Statistical parametric mapping and regions of interest (ROI) multivariate analysis of variance was used to ascertain differences between patients and controls on MRI-volumetry and ASL. Linear regression was used to assess relationship between CBF with GM atrophy and neuropsychological test measures. RESULTS: Compared to HC, patients with MCI and AD had significantly lower quantified perfusion in posterior cingulate and lingual gyri, over hippocampus in MCI, with no differences noted between MCI and AD. Atrophy over the middle temporal gyrus and hippocampus differentiated AD from MCI. No significant positive correlations were noted between perfusion and GM volumes in ROI with the exception of temporal neocortex. Significantly positive coefficient b-value (p < 0.01) were apparent between global cognition with CBF in precuneus, temporal neocortex and precuneus volume, with negative b-values noted between medial temporal CBF for global cognition and recall scores. CONCLUSIONS: ROI-based CBF measurements differentiated MCI and AD from HC; volumetry of medial and neocortical temporal GM separates AD from MCI. Correlations between CBF and neuropsychology are variable and require further longitudinal studies to gauge its predictive utility on cognitive trajectory in MCI.

Neuromitochondrial Disorders : Genomic Basis and an Algorithmic Approach to Imaging Diagnostics.

Mitochondrial disorders have been an enigma for a long time due to the varied clinical presentations. Although a genetic confirmation will be mandatory most of the time, half the number of Leigh syndrome would be negative for genetic mutations. There are a growing number of mutations in clinical practice, which escape detection on routine clinical exome sequencing. Imaging would render help in pointing towards a mitochondrial disorder. There are a few case reports which brief about specific mitochondrial mutations and their specific imaging appearance. This article tries to provide a comprehensive review on the imaging-genomic correlation of mitochondrial disorders with an objective of performing a specific genetic testing to arrive at an accurate diagnosis.

Quantitative susceptibility-weighted imaging in predicting disease activity in multiple sclerosis.

PURPOSE: Repeated use of Gadolinium (Gd) contrast for multiple sclerosis (MS) imaging leads to Gd deposition in brain. We aimed to study the utility of phase values by susceptibility weighted imaging (SWI) to assess the iron content in MS lesions to differentiate active and inactive lesions. METHODS: MS persons who underwent MRI were grouped into group 1 with active lesions and group 2 with inactive lesions based on the presence or absence of contrast enhancing lesions. Phase values of lesions (PL) and contralateral normal white matter (PN) were calculated using the SPIN software by drawing ROI. Subtracted phase values (PS = PL - PN) and iron content (PS/3) of the lesions were calculated in both groups. RESULTS: We analyzed 69 enhancing lesions from 22 patients (group 1) and 84 non-enhancing lesions from 29 patients (group 2). Mean-subtracted phase values and iron content corrected for voxels in ROI were significantly lower in enhancing lesions compared to non-enhancing lesions (p < 0.001). A cut-off value 2.8 µg/g for iron content showed area under the curve of 0.909 with good sensitivity. CONCLUSION: Quantification of iron content using SWI phase values holds promise as a biomarker to differentiate active from inactive lesions of MS.

Arterial spin labeling hyperperfusion in seizures associated with non-ketotic hyperglycaemia: is it merely a post-ictal phenomenon?

A 53-year-old chronic uncontrolled diabetic patient presented with one episode of generalized seizures followed by drowsiness and post-ictal confusion. MR imaging at admission revealed left temporal subcortical T2/FLAIR hypointensities with overlying cortical T2/FLAIR hyperintensities and increased perfusion on arterial spin labeling (ASL). Follow-up imaging at 4- and 8-week interval revealed persistent ASL hyperperfusion with significant resolution of conventional MR imaging findings. Delayed persistent ASL hyperperfusion suggests that hyperglycemia-induced increased blood-brain barrier permeability rather than a mere post-ictal phenomenon in non-ketotic hyperglycemia (NKH) and may result in long-term cognitive disturbances.

Quantitative Susceptibility Mapping: Technical Considerations and Clinical Applications in Neuroimaging.

Quantitative susceptibility mapping (QSM) is a novel magnetic resonance imaging (MRI) technique for quantifying the spatial distribution of magnetic susceptibility within an object or tissue. Recently, QSM has been widely used to study various dominant magnetic susceptibility sources in the brain, including iron and calcium. In addition, the method enables mapping of the cerebral metabolic rate of oxygen, which could act as a new metabolic biomarker for diseases that involve disruption of the brain's oxygen supply. Thus, the clinical applications of QSM are wide-reaching and hold great promise as imaging biomarkers for studying several neurological diseases. This review aims to summarize the physical concepts and potential clinical applications of QSM in neuroimaging. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Multi-Res-Attention UNet: A CNN Model for the Segmentation of Focal Cortical Dysplasia Lesions from Magnetic Resonance Images.

In this work, we have focused on the segmentation of Focal Cortical Dysplasia (FCD) regions from MRI images. FCD is a congenital malformation of brain development that is considered as the most common causative of intractable epilepsy in adults and children. To our knowledge, the latest work concerning the automatic segmentation of FCD was proposed using a fully convolutional neural network (FCN) model based on UNet. While there is no doubt that the model outperformed conventional image processing techniques by a considerable margin, it suffers from several pitfalls. First, it does not account for the large semantic gap of feature maps passed from the encoder to the decoder layer through the long skip connections. Second, it fails to leverage the salient features that represent complex FCD lesions and suppress most of the irrelevant features in the input sample. We propose Multi-Res-Attention UNet; a novel hybrid skip connection-based FCN architecture that addresses these drawbacks. Moreover, we have trained it from scratch for the detection of FCD from 3 T MRI 3D FLAIR images and conducted 5-fold cross-validation to evaluate the model. FCD detection rate (Recall) of 92% was achieved for patient wise analysis.