KALPANA: Advanced Spectroscopic Signal Processing Platform for Improved Accuracy to Aid in Early Diagnosis of Brain Disorders in Clinical Setting

Linewidth-related bias in modelled concentration estimates from GABA-edited 1H-MRS

J-difference-edited MRS is widely used to study GABA in the human brain. Editing for low-concentration target molecules (such as GABA) typically exhibits lower signal-to-noise ratio (SNR) than conventional non-edited MRS, varying with acquisition region, volume and duration. Moreover, spectral lineshape may be influenced by age-, pathology-, or brain-region-specific effects of metabolite T2, or by task-related blood-oxygen level dependent (BOLD) changes in functional MRS contexts. Differences in both SNR and lineshape may have systematic effects on concentration estimates derived from spectral modelling. The present study characterises the impact of lineshape and SNR on GABA+ estimates from different modelling algorithms: FSL-MRS, Gannet, LCModel, Osprey, spant and Tarquin. Publicly available multi-site GABA-edited data (222 healthy subjects from 20 sites; conventional MEGA-PRESS editing; TE = 68 ms) were pre-processed with a standardised pipeline, then filtered to apply controlled levels of Lorentzian and Gaussian linebroadening and SNR reduction. Increased Lorentzian linewidth was associated with a 2-5% decrease in GABA+ estimates per Hz, observed consistently (albeit to varying degrees) across datasets and most algorithms. Weaker, often opposing effects were observed for Gaussian linebroadening. Variations are likely caused by differing baseline parametrization and lineshape constraints between models. Effects of linewidth on other metabolites (e.g., Glx and tCr) varied, suggesting that a linewidth confound may persist after scaling to an internal reference. These findings indicate a potentially significant confound for studies where linewidth may differ systematically between groups or experimental conditions, e.g. due to T2 differences between brain regions, age, or pathology, or varying T2* due to BOLD-related changes. We conclude that linewidth effects need to be rigorously considered during experimental design and data processing, for example by incorporating linewidth into statistical analysis of modelling outcomes or development of appropriate lineshape matching algorithms.

Glutathione Depletion and Concomitant Elevation of Susceptibility in Patients with Parkinson's Disease: State-of-the-Art MR Spectroscopy and Neuropsychological Study

Parkinson's disease (PD) is characterized by extrapyramidal motor disturbances and nonmotor cognitive impairments which impact activities of daily living. Although the etiology of PD is still obscure, autopsy reports suggest that oxidative stress (OS) is one of the important factors in the pathophysiology of PD. In the current study, we have investigated the impact of OS in PD by measuring the antioxidant glutathione (GSH) levels from the substantia nigra (SN), left hippocampus (LH) and neurotransmitter γ-amino butyric acid (GABA) levels from SN region. Concomitant quantitative susceptibility mapping (QSM) from SN and LH was also acquired from thirty-eight PD patients and 30 age-matched healthy controls (HC). Glutathione levels in the SN region decreased significantly and susceptibility increased significantly in PD compared to HC. Nonsignificant depletion of GABA was observed in the SN region. GSH levels in the LH region were depleted significantly, but LH susceptibility did not alter in the PD cohort compared to HC. Neuropsychological and physical assessment demonstrated significant impairment of cognitive functioning in PD patients compared to HC. GSH depletion was negatively correlated to motor function performance. Multivariate receiver operating characteristic (ROC) curve analysis on the combined effect of GSH, GABA, and susceptibility in the SN region yielded an improved diagnostic accuracy of 86.1% compared to individual diagnostic accuracy based on GSH (65.8%), GABA (57.5%), and susceptibility (69.6%). This is the first comprehensive report in PD demonstrating significant GSH depletion as well as concomitant iron enhancement in the SN region.

SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform

Multimodal neuroimaging data of various brain disorders provides valuable information to understand brain function in health and disease. Various neuroimaging-based databases have been developed that mainly consist of volumetric magnetic resonance imaging (MRI) data. We present the comprehensive web-based neuroimaging platform "SWADESH" for hosting multi-disease, multimodal neuroimaging, and neuropsychological data along with analytical pipelines. This novel initiative includes neurochemical and magnetic susceptibility data for healthy and diseased conditions, acquired using MR spectroscopy (MRS) and quantitative susceptibility mapping (QSM) respectively. The SWADESH architecture also provides a neuroimaging database which includes MRI, MRS, functional MRI (fMRI), diffusion weighted imaging (DWI), QSM, neuropsychological data and associated data analysis pipelines. Our final objective is to provide a master database of major brain disease states (neurodegenerative, neuropsychiatric, neurodevelopmental, and others) and to identify characteristic features and biomarkers associated with such disorders.

Quantitation of Brain and Blood Glutathione and Iron in Healthy Age Groups Using Biophysical and In Vivo MR Spectroscopy: Potential Clinical Application

The antioxidant glutathione (GSH) and pro-oxidant iron levels play a balancing role in the modulation of oxidative stress (OS). There is a significant depletion of GSH in the left hippocampus (LH) in patients with Alzheimer's disease (AD) with concomitant elevation of iron level. However, the correlation of GSH and iron distribution patterns between the brain and the peripheral system (blood) is not yet known. We measured GSH and magnetic susceptibility (e.g., iron) in the LH region along with GSH in plasma and iron in serum across four age groups consisting of healthy volunteers (age range 18-72 y, n = 70). We report non-variability of the mean GSH in the plasma and LH region across mentioned age groups. The mean iron level in the LH region does not change, but the iron level in the serum in the 51-72 y age group increases non-significantly. Regression analysis of our data indicated that GSH and iron levels (both in blood and in brain) are not related to age. This research pave the way for the identification of a risk/susceptibility biomarker for AD and Parkinson's disease from the evaluation of GSH (in plasma) and iron (in serum) levels concomitantly.

Distribution Pattern of Closed and Extended Forms of Glutathione in the Human Brain: MR Spectroscopic Study

Glutathione (GSH) is a potent antioxidant synthesized de novo in cells and helps to detoxify free radicals in the brain and other organs. In vitro NMR studies from various research groups have reported primarily two sets of chemical shifts (2.80 or 2.96 ppm) of Cys-βCH₂ depending on GSH sample preparation in either inert or oxygenated environments. A multi-center in vivo MRS human study has also validated the presence of two types of GSH conformer in the human brain. Our study is aimed at investigating the distribution patterns of the two GSH conformers from five brain regions, namely, ACC (anterior cingulate cortex), PCC (posterior cingulate cortex), LPC (left parietal cortex), LH (left hippocampus), and CER (cerebellum). GSH was measured using a 3T MRI scanner using MEGA-PRESS pulse sequence in healthy young male and female populations (M/F = 5/9; age 32.8 ± 5.27 years). We conclude that the closed GSH conformer (characteristic NMR shift signature: Cys H_α 4.40-H_β 2.80 ppm) is more abundant than the extended GSH form (characteristic NMR shift signature Cys H_α 4.56-H_β 2.95 ppm). Closed conformer has a non-uniform distribution (ACC < CER < LH < PCC < LPC) in the healthy brain. On the contrary, the extended form of GSH has a uniform distribution in various anatomical regions.

Schizophrenia, Bipolar and Major Depressive Disorders: Overview of Clinical Features, Neurotransmitter Alterations, Pharmacological Interventions, and Impact of Oxidative Stress in the Disease Process

Psychiatric disorders are one of the leading causes of disability worldwide and affect the quality of life of both individuals and the society. The current understanding of these disorders points toward receptor dysfunction and neurotransmitter imbalances in the brain. Treatment protocols are hence oriented toward normalizing these imbalances and ameliorating the symptoms. However, recent literature has indicated the possible role of depleted levels of antioxidants like glutathione (GSH) as well as an alteration in the levels of the pro-oxidant, iron in the pathogenesis of major psychiatric diseases, viz., schizophrenia (Sz), bipolar disorder (BD), and major depressive disorder (MDD). This review aims to highlight the involvement of oxidative stress (OS) in these psychiatric disorders. An overview of the clinical features, neurotransmitter abnormalities, and pharmacological treatments concerning these psychiatric disorders has also been presented. Furthermore, it attempts to synthesize literature from existing magnetic resonance spectroscopy (MRS) and quantitative susceptibility mapping (QSM) studies for these disorders, assessing GSH and iron, respectively. This manuscript is a sincere attempt to stimulate research discussion to advance the knowledge base for further understanding of the pathoetiology of Sz, BD, and MDD.

Hippocampal glutathione depletion with enhanced iron level in patients with mild cognitive impairment and Alzheimer’s disease compared with healthy elderly participants

Oxidative stress has been implicated in Alzheimer’s disease, and it is potentially driven by the depletion of primary antioxidant, glutathione, as well as elevation of the pro-oxidant, iron. Present study evaluates glutathione level by magnetic resonance spectroscopy, iron deposition by quantitative susceptibility mapping in left hippocampus, as well as the neuropsychological scores of healthy old participants (N = 25), mild cognitive impairment (N = 16) and Alzheimer’s disease patients (N = 31). Glutathione was found to be significantly depleted in mild cognitive impaired (P &lt; 0.05) and Alzheimer’s disease patients (P &lt; 0.001) as compared with healthy old participants. A significant higher level of iron was observed in left hippocampus region for Alzheimer’s disease patients as compared with healthy old (P &lt; 0.05) and mild cognitive impairment (P &lt; 0.05). Multivariate receiver-operating curve analysis for combined glutathione and iron in left hippocampus region provided diagnostic accuracy of 82.1%, with 81.8% sensitivity and 82.4% specificity for diagnosing Alzheimer’s disease patients from healthy old participants. We conclude that tandem glutathione and iron provides novel avenue to investigate further research in Alzheimer’s disease.

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

In Vivo 13C Magnetic Resonance Spectroscopy for Assessing Brain Biochemistry in Health and Disease

Magnetic resonance spectroscopy (MRS) is a non-invasive technique that contributes to the elucidation of brain biochemistry. ¹³C MRS enables the detection of specific neurochemicals and their neuroenergetic correlation with neuronal function. The synergistic outcome of ¹³C MRS and the infusion of ¹³C-labeled substrates provide an understanding of neurometabolism and the role of glutamate/gamma-aminobutyric acid (GABA) neurotransmission in diseases, such as Alzheimer's disease, schizophrenia, and bipolar disorder. Moreover, ¹³C MRS provides a window into the altered flux rate of different pathways, including the tricarboxylic acid cycle (TCA) and the glutamate/glutamine/GABA cycle, in health and in various diseases. Notably, the metabolic flux rate of the TCA cycle often decreases in neurodegenerative diseases. Additionally, ¹³C MRS can be used to investigate several psychiatric and neurological disorders as it directly reflects the real-time production and alterations of key brain metabolites. This review aims to highlight the chronology, the technological advancements, and the applications of ¹³C MRS in various brain diseases.

Hippocampal Glutathione Depletion and pH Increment in Alzheimer's Disease: An in vivo MRS Study

BACKGROUND

Oxidative stress plays a major role in Alzheimer's disease (AD) pathogenesis, and thus, antioxidant glutathione (GSH) has been actively investigated in mitigating the oxidative load. Significant hippocampal GSH depletion has been correlated with cognitive impairment in AD. Furthermore, postmortem studies indicated alterations in cellular-energy metabolism and hippocampal pH change toward alkalinity in AD.

OBJECTIVE

Concurrent analysis of hippocampal GSH and pH interplay in vivo on the same individual is quite unclear and hence requires investigation to understand the pathological events in AD.

METHODS

Total 39 healthy old (HO), 22 mild cognitive impairment (MCI), and 37 AD patients were recruited for hippocampal GSH using 1H-MRS MEGA-PRESS and pH using 2D 31P-MRSI with dual tuned (1H/31P) transmit/receive volume head coil on 3T-Philips scanner. All MRS data processing using KALPANA package and statistical analysis were performed MedCalc, respectively and NINS-STAT package.

RESULTS

Significant GSH depletion in the left and right hippocampus (LH and RH) among MCI and AD study groups as compared to HO was observed, whereas pH increased significantly in the LH region between HO and AD. Hippocampal GSH level negatively correlated with pH in both patient groups. The ROC analysis on the combined effect of GSH and pH in both hippocampal regions give accuracy for MCI (LH: 78.27%; RH: 86.96%) and AD (LH: 88%; RH: 78.26%) groups differentiating from HO.

CONCLUSION

Outcomes from this study provide further insights to metabolic alterations in terms of concurrent assessment of hippocampal GSH and pH levels in AD pathogenesis, aiding in early diagnosis of MCI and AD.

PRATEEK: Integration of Multimodal Neuroimaging Data to Facilitate Advanced Brain Research

BACKGROUND

In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiles, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological diseases.

OBJECTIVE

To develop a processing scheme for multimodal data integration in a seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.g., Alzheimer's disease).

METHODS

A multimodal data integration scheme has been developed to integrate the outcomes from multiple neuroimaging data (fMRI, MEG, MRS, and QSM) spatially. Furthermore, the entire scheme has been incorporated into a user-friendly toolbox- "PRATEEK".

RESULTS

The proposed methodology and toolbox has been tested for viability among fourteen healthy young participants. The data-integration scheme was tested for bilateral occipital cortices as the regions of interest and can also be extended to other anatomical regions. Overlap percentage from each combination of two modalities (fMRI-MRS, MEG-MRS, fMRI-QSM, and fMRI-MEG) has been computed and also been qualitatively assessed for combinations of the three (MEG-MRS-QSM) and four (fMRI-MEG-MRS-QSM) modalities.

CONCLUSION

This user-friendly toolbox minimizes the need of an expertise in handling different neuroimaging tools for processing and analyzing multimodal data. The proposed scheme will be beneficial for clinical studies where geometric information plays a crucial role for advance brain research.

ANSH: Multimodal Neuroimaging Database Including MR Spectroscopic Data From Each Continent to Advance Alzheimer's Disease Research

Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting millions of people worldwide. The etiology of AD is not known, and intense research involving multimodal neuroimaging data (e.g., MRI, functional MRI, PET etc.) is extensively used to identify the causal molecular process for AD. In this context, various imaging-based databases accessible to researchers globally, are useful for an independent analysis. Apart from MRI-based brain imaging data, the neurochemical data using magnetic resonance spectroscopy (MRS) provide early molecular processes before the structural or functional changes are manifested. The existing imaging-based databases in AD lack the integration of MRS modality and, thus, limits the availability of neurochemical information to the AD research community. This perspective is an initiative to bring attention to the development of the neuroimaging database, "ANSH," that includes brain glutathione (GSH), gamma aminobutyric acid (GABA) levels, and other neurochemicals along with MRI-based information for AD, mild cognitive impairment (MCI), and healthy subjects. ANSH is supported by a JAVA-based workflow environment and python providing a simple, dynamic, and distributed platform with data security. The platform consists of two-tiered architecture for data collection and management further supporting quality control, report generation for analyzed data, and data backup with a dedicated storage system. The ANSH database aims to present a single neuroimaging data platform incorporating diverse data types from healthy control and patient groups to provide better insights pertaining to disease progression. This data management platform provides flexible data sharing across users with continuous project monitoring. The development of ANSH platform will facilitate collaborative research and multi-site data sharing across the globe.