Associate Professor Saadallah Ramadan

Background: Multiple Sclerosis (MS) is a complex neurodegenerative condition that is influenced by a combination of genetic and environmental factors. Included in these factors is the venous system, however, the extent to which it influences the etiology of MS has yet to be fully characterised. The aim of this review is to critically summarize the literature available concerning the venous system in MS, primarily concerning specific data on the venous pressure and blood flow in this system. Methods: A systematic review was conducted with the application of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. The advanced search functions of both the Scopus and PubMed databases were used to conduct the literature search, resulting in 136 unique articles initially identified. Applying relevant exclusion criteria, 22 of the studies were chosen for this review. Results: The selected studies were analysed for venous pressure and blood flow related findings, with 14 studies contributing data on the internal jugular vein (IJV) flow rate, 5 on blood flows of the intracranial venous sinuses, 2 on blood flow pulsatility and 6 supplying information relevant to the venous pressure (3 studies contributed to multiple areas). The general findings of the review included that the IJV flow was not significantly different between MS patients and controls, however, there were variances between stenotic (S) and non-stenotic (NS) MS patients. Due to the limited data in the other two areas defined in this review, further research is required to establish if any variances in MS are present. Conclusion: It remains unclear if there are significant differences in many flow variables between MS patients and controls considered in this review. It would be advantageous if future work in this area focused on understanding the hemodynamics of this system, primarily concerning how the flow rate, venous pressure and vascular resistance are related, and any impact that these factors have on the etiology of MS.

Background and Purpose: Fingolimod has been shown to be more effective in reducing relapse rate and disability than injectable therapies in clinical trials. An increase in N-acetylaspartate (NAA) as measured by MR spectroscopy is correlated with maintaining axonal metabolic functions. This study compared the neurometabolic and volumetric changes in relapsing-remitting multiple sclerosis (RRMS) patients on fingolimod or injectable therapies with healthy controls (HCs). Methods: Ninety-eight RRMS (52 on fingolimod, 46 on injectable therapies (27 on glatiramer acetate and 19 on interferon) were age and sex-matched to 51 HCs. RRMS patients underwent cognitive, fatigue, and mental health assessments, as well as an Expanded disability status scale (EDSS). MRI/S was acquired from the hippocampus, posterior cingulate gyrus (PCG), and prefrontal cortex (PFC). Volumetric and neurometabolic measures were compared across cohorts using a univariate general linear model and correlated with clinical severity and neuropsychological scores. Results: Clinical parameters, MR-volumetric, and neurometabolic profiles showed no differences between treatment groups (p¿>.05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (-13%), gray matter (-16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (-17%, p =.001, hippocampus), (-7%, p =.001, PCG), and (-9%, p =.001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions. Conclusion: While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.

Background: Computer-aided diagnosis can facilitate the early detection and diagnosis of multiple sclerosis (MS) thus enabling earlier interventions and a reduction in long-term MS-related disability. Recent advancements in the field of artificial intelligence (AI) have led to the improvements in the classification, quantification and identification of diagnostic patterns in medical images for a range of diseases, in particular, for MS. Importantly, data generated using AI techniques are analyzed automatically, which compares favourably with labour-intensive and time-consuming manual methods. Objective: The aim of this review is to assist MS researchers to understand current and future developments in the AI-based diagnosis and prognosis of MS. Methods: We will investigate a variety of AI approaches and various classifiers and compare the current state-of-the-art techniques in relation to lesion segmentation/detection and prognosis of disease. After briefly describing the magnetic resonance imaging (MRI) techniques commonly used, we will describe AI techniques used for the detection of lesions and MS prognosis. Results: We then evaluate the clinical maturity of these AI techniques in relation to MS. Conclusion: Finally, future research challenges are identified in a bid to encourage further improvements of the methods.

Background: Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading. Methods: Forty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient. Results: The addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01). Conclusion: The inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

Purpose: Fatigue is a common symptom in patients with multiple sclerosis (MS) with unknown pathophysiology. Dysfunction of the GABAergic/glutamatergic pathways involving inhibitory and excitatory neurotransmitters such as ¿-aminobutyric acid (GABA) and glutamine + glutamate pool (Glx) have been implicated in several neurological disorders. This study is aimed to evaluate the potential role of GABA and Glx in the origin of central fatigue in relapse remitting MS (RRMS) patients. Methods: 24 RRMS patients and 16 age- and sex-matched healthy controls (HC) were scanned using Mescher-Garwood point resolved spectroscopy (MEGA-PRESS) with a 3 T system to quantify GABA+ and Glx from prefrontal (PFC) and sensorimotor (SMC) cortices. Self-reported fatigue status was measured on all participants using the Modified Fatigue Impact Scale (MFIS). Results: RRMS patients had higher fatigue scores relative to HC (p = 0.05). Compared to HC, Glx levels in RRMS patients were significantly decreased in SMC (p = 0.04). Significant correlations were found between fatigue scores and GABA+ (r = -0.531, p = 0.008) and Glx (r = 0.511, p = 0.018) in PFC. Physical fatigue was negatively correlated with GABA+ in SMC and PFC (r = -0.428 and -0.472 respectively, p = 0.04) and positively with PFC Glx (r = 0.480, p = 0.028). Conclusion: The associations between fatigue and GABA + and Glx suggest that there might be dysregulation of GABAergic/glutamatergic neurotransmission in the pathophysiological mechanism of central fatigue in MS.

Near-infrared spectroscopy (NiRS) is a relatively new technology of brain imaging with its potential in the assessment of cerebrovascular health only recently discovered. Encouraging early results suggest that NiRS can be used as an inexpensive and portable cerebrovascular health tracking device using a recently proposed pulse relaxation function (PReFx). In this paper, we propose a new NiRS timing index, TI NiRS, of cerebrovascular health. TI NiRS is a novel use of the NiRS technology. TI NiRS is motivated by the previously proved relationship of the timing of the reflected wave with vascular resistance and compliance in the context of pressure waveforms. We correlated both TI NiRS and PReFx against age, a non-exercise cardiorespiratory fitness (CRF) index, and two existing indices of cerebrovascular health, namely transcranial Doppler (TCD) augmentation index, AI TCD, and magnetic resonance imaging (MRI) blood flow pulsatility index, PI MRI. The TI NiRS correlations with Age, CRF, PI MRI and AI TCD all are significant, i.e., r= 0.53 (p= 0.002), r= - 0.44 (p= 0.011), r= 0.45 (p= 0.012) and r= 0.46 (p= 0.010), respectively. PReFx, however, did not have significant correlations with any of the vascular health factors. The proposed timing index is a reliable indicator of cerebrovascular aging factors in the NiRS waveform.

Transcranial Doppler (TCD) blood flow velocity has been extensively used in biomedical research as it provides a cost-effective and relatively simple approach to assess changes in cerebral blood flow dynamics and track cerebrovascular health status. In this article we introduce a new TCD-based timing index, TITCD, as an indicator of vascular stiffening and vascular health. We investigate the correlations of the new index and the existing indices, namely the pulsatility index and the augmentation index, with age, cardiorespiratory fitness (CRF) and magnetic resonance imaging (MRI) blood flow pulsatility index (PIMRI). Notably, the new index showed stronger correlations with CRF (r = -0.79) and PIMRI (r = 0.53) compared with the augmentation index (r = -0.65 with CRF and no significant correlation with PIMRI) and the pulsatility index (no significant correlations with CRF or PIMRI), and a similar correlation with age as the augmentation index. The clearer relationship of the proposed timing index with vascular aging factors underlines its utility as an early indicator of vascular stiffening.

Background: Fatigue is a common and debilitating symptom in multiple sclerosis (MS). Over the past decade, a growing body of research has focussed on the pathophysiological mechanisms underlying central (cognitive and physical) fatigue in MS. The precise mechanisms causing fatigue in MS patients are complex and poorly understood, and may differ between patients. Advanced quantitative magnetic resonance imaging (MRI) techniques allow for objective assessment of disease pathology and have been used to characterise the pathophysiology of central fatigue in MS. Objective: To systematically review the existing literature of MRI-based studies assessing the pathophysiological mechanisms of MS-related central fatigue. Methods: A systematic literature search of four major databases (PubMed, Medline, Embase, Scopus and Google Scholar) was conducted to identify MRI-based studies of MS-related fatigue published in the past 20 years. Studies using the following MRI-based methods were included: structural (lesion load/atrophy), T1 relaxation time/magnetisation transfer ratio (MTR), diffusion tensor imaging (DTI), functional MRI (fMRI) and magnetic resonance spectroscopy (MRS). Results: A total of 92 studies were identified as meeting the search criteria and included for review. Structurally, regional gray/white matter atrophy, cortical thinning, decreased T1 relaxation times and reduced fractional anisotropy were associated with central fatigue in MS. Functionally, hyperactivity and reduced functional connectivity in several regional areas of frontal, parietal, occipital, temporal and cerebellum were suggested as causes of central fatigue. Biochemically, a reduction in N-acetyl aspartate/creatine and increased (glutamine+glutamate)/creatine ratios were correlated with fatigue severity in MS. Conclusion: Several advanced quantitative MRI methods have been employed in the study of central fatigue in MS. Central fatigue in MS is associated with macro/microstructural and functional changes within specific brain regions (frontal, parietal, temporal and deep gray matter) and specific pathways/networks (cortico-cortical and cortico-subcortical). Alternations in the cortico-striatal-thalamocortical (CSTC) loop are correlated with the development of fatigue in MS patients.

Background: Due to the histological heterogeneity of the central gland, accurate detection of central gland prostate cancer remains a challenge. Purpose: To evaluate the efficacy of in vivo 3D 1H MR spectroscopic imaging (3D 1H MRSI) with a semi-localized adiabatic selective refocusing (sLASER) sequence and gradient-modulated offset-independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low- vs. high-risk cancer, 3) low- vs. intermediate-risk cancer, and 4) intermediate- vs. high-risk cancer voxels. Study Type: Prospective. Subjects: Thirty-six patients with biopsy-proven central gland prostate cancer. Field Strength/Sequence: 3T MRI / 3D 1H MRSI using GOIA-sLASER. Assessment: Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and 1H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing. Statistical Tests: Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset. Results: High-quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low- vs. high-risk cancer and low- vs. intermediate-risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate- vs. high-risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%. Data Conclusion: The GOIA-sLASER sequence with an external phased-array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low- vs. high-risk cancer, and low- vs. intermediate-risk cancer. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2019;50:1926¿1936.

Summary: Neoadjuvant chemotherapy (NACT) is the standard treatment option for breast cancer as more data shows that pathologic complete response (pCR) after NACT correlates with improved prognosis. MRI is accepted as the best imaging modality for evaluating the response to NACT in many studies as compared with clinical examination and other imaging modalities. In vivo magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) studies have both emerged as potential tools to provide early response indicators based on the changes in the metabolites and the apparent diffusion coefficient (ADC) respectively. In this review article, we aim to discuss the strength and limitations of MRS and DWI in monitoring of early response breast cancer to NACT.

Purpose: To use localized correlated spectroscopy (COSY) to assess for an altered biochemical state or states in breast tissue of women with BRCA gene mutations that potentially constitute preinvasive conditions. Materials and Methods: Institutional review board approval was obtained. Participants provided written informed consent. In vivo localized COSY images were recorded at 3 T in the breast tissue of women carrying BRCA1 (n = 9) or BRCA2 (n = 14) gene mutations and were compared with images in healthy control subjects with no family history of breast cancer (n = 10). All participants underwent contrast material-enhanced MR imaging and ultrasonography (US). Statistical significance was calculated with the Mann-Whitney two-sided nonparametric test. Results: No abnormality was recorded with MR imaging or US. Metabolite levels in the BRCA1 cohort were reduced by 79% (P = .014) when compared with triglycerides level, and there was a 19% increase in lipid unsaturation and triglyceride levels (P = .027 and P = .086, respectively) when compared with cellular cholesterol level. Cholesterol level was reduced by 47% (P = .027) when compared with diallylic lipid level. Metabolite levels in the BRCA2 cohort showed increased unsaturation of 21% (P = .030) relative to triglycerides level. Comparison of the BRCA1 and BRCA2 cohorts showed a 47% (P = .002) increase in cholesterol level in the BRCA2 cohort when compared with diallylic lipid level and a 52% (P = .003) increase when compared with triglycerides level. Levels of diallylic lipid, unsaturated lipid, triglycerides, and terminal methyl on the acyl chain are reduced by 46% (P = .002), 57% (P = .003), 66% (P = .003), and 29% (P = .010), respectively, when compared with cholesterol level. Conclusion: Localized COSY recorded significant changes in women with BRCA1 and BRCA2 gene mutations when compared with control subjects. If these changes are ultimately proven to be a premalignant stage, this method may prove useful in screening.

Transcranial direct current stimulation (tDCS) is a non-invasive intervention altering neural plasticity by modulating neuronal excitability of pre- and postsynaptic neuron populations, which has been shown to improve depression symptoms and cognition. We investigated the effects of a single session of 20 min of 2 mA left-prefrontal anodal versus sham stimulation on auditory event-related potentials (ERPs) in 11 male and 5 female healthy subjects (mean age of 28.6 [SD 6.2] years) by employing a randomized single-blind crossover design. Stimulation effects on cortical glutamate (Glu) and glutamine (Glx) levels were subsequently measured in 12 of the 16 healthy subjects in a 3 T proton magnetic resonance spectroscopy scan. tDCS was associated with a significant increase of N1 amplitudes while smaller P3b amplitudes correlated with higher cortical Glu and Glx levels in the stimulated brain area when performing an auditory go/no-go discrimination task. tDCS did not change mismatch negativity, nor task performance or cortical Glu/Glx levels which, together with N1 amplitudes, depended on stimulation order ("sham" versus "active"). Increased N1 amplitudes are consistent with higher levels of cortical excitability following prefrontal anodal tDCS. The failure to replicate Glu/Glx changes with tDCS may have been masked by between-session carry-over effects while ceiling effects may have masked tDCS effects on task performance. © 2014 Elsevier GmbH. All rights reserved.

Our understanding of the roles that the amino acids glutamate (Glu) and glutamine (Gln) play in the mammalian central nervous system has increased rapidly in recent times. Many conditions are known to exhibit a disturbance in Glu-Gln equilibrium, and the exact relationships between these changed conditions and these amino acids are not fully understood. This has led to increased interest in Glu/Gln quantitation in the human brain in an array of conditions (e.g. mental illness, tumor, neuro-degeneration) as well as in normal brain function. Accordingly, this review has been undertaken to describe the increasing number of in vivo techniques available to study Glu and Gln separately, or pooled as 'Glx'. The present MRS methods used to assess Glu and Gln vary in approach, complexity, and outcome, thus the focus of this review is on a description of MRS acquisition approaches, and an indication of relative utility of each technique rather than brain pathologies associated with Glu and/or Gln perturbation. Consequently, this review focuses particularly on (1) one-dimensional 1H MRS, (2) two-dimensional 1H MRS, and (3) one-dimensional 13C MRS techniques. © 2013 John Wiley & Sons, Ltd.