Functional MRS with J-edited lactate in human motor cortex at 4 T

Functional Magnetic Resonance Spectroscopy of Prolonged Motor Activation using Conventional and Spectral GLM Analyses

Background

Functional MRS (fMRS) is a technique used to measure metabolic changes in response to increased neuronal activity, providing unique insights into neurotransmitter dynamics and neuroenergetics. In this study we investigate the response of lactate and glutamate levels in the motor cortex during a sustained motor task using conventional spectral fitting and explore the use of a novel analysis approach based on the application of linear modelling directly to the spectro-temporal fMRS data.

Methods

fMRS data were acquired at a field strength of 3 Tesla from 23 healthy participants using a short echo-time (28ms) semi-LASER sequence. The functional task involved rhythmic hand clenching over a duration of 8 minutes and standard MRS preprocessing steps, including frequency and phase alignment, were employed. Both conventional spectral fitting and direct linear modelling were applied, and results from participant-averaged spectra and metabolite-averaged individual analyses were compared.

Results

We observed a 20% increase in lactate in response to the motor task, consistent with findings at higher magnetic field strengths. However, statistical testing showed some variability between the two averaging schemes and fitting algorithms. While lactate changes were supported by the direct spectral modelling approach, smaller increases in glutamate (2%) were inconsistent. Exploratory spectral modelling identified a 4% decrease in aspartate, aligning with conventional fitting and observations from prolonged visual stimulation.

Conclusion

We demonstrate that lactate dynamics in response to a prolonged motor task are observed using short-echo time semi-LASER at 3 Tesla, and that direct linear modelling of fMRS data is a useful complement to conventional analysis. Future work includes mitigating spectral confounds, such as scalp lipid contamination and lineshape drift, and further validation of our novel direct linear modelling approach through experimental and simulated datasets.

Large-scale animal model study uncovers altered brain pH and lactate levels as a transdiagnostic endophenotype of neuropsychiatric disorders involving cognitive impairment

Increased levels of lactate, an end-product of glycolysis, have been proposed as a potential surrogate marker for metabolic changes during neuronal excitation. These changes in lactate levels can result in decreased brain pH, which has been implicated in patients with various neuropsychiatric disorders. We previously demonstrated that such alterations are commonly observed in five mouse models of schizophrenia, bipolar disorder, and autism, suggesting a shared endophenotype among these disorders rather than mere artifacts due to medications or agonal state. However, there is still limited research on this phenomenon in animal models, leaving its generality across other disease animal models uncertain. Moreover, the association between changes in brain lactate levels and specific behavioral abnormalities remains unclear. To address these gaps, the International Brain pH Project Consortium investigated brain pH and lactate levels in 109 strains/conditions of 2294 animals with genetic and other experimental manipulations relevant to neuropsychiatric disorders. Systematic analysis revealed that decreased brain pH and increased lactate levels were common features observed in multiple models of depression, epilepsy, Alzheimer's disease, and some additional schizophrenia models. While certain autism models also exhibited decreased pH and increased lactate levels, others showed the opposite pattern, potentially reflecting subpopulations within the autism spectrum. Furthermore, utilizing large-scale behavioral test battery, a multivariate cross-validated prediction analysis demonstrated that poor working memory performance was predominantly associated with increased brain lactate levels. Importantly, this association was confirmed in an independent cohort of animal models. Collectively, these findings suggest that altered brain pH and lactate levels, which could be attributed to dysregulated excitation/inhibition balance, may serve as transdiagnostic endophenotypes of debilitating neuropsychiatric disorders characterized by cognitive impairment, irrespective of their beneficial or detrimental nature.

Recent Trends in Nanocarrier-Based Drug Delivery System for Prostate Cancer

Prostate cancer remains a significant global health concern, requiring innovative approaches for improved therapeutic outcomes. In recent years, nanoparticle-based drug delivery systems have emerged as promising strategies to address the limitations of conventional cancer chemotherapy. The key trends include utilizing nanoparticles for enhancing drug delivery to prostate cancer cells. Nanoparticles have some advantages such as improved drug solubility, prolonged circulation time, and targeted delivery of drugs. Encapsulation of chemotherapeutic agents within nanoparticles allows for controlled release kinetics, reducing systemic toxicity while maintaining therapeutic efficacy. Additionally, site-specific accumulation within the prostate tumor microenvironment is made possible by the functionalization of nanocarrier with targeted ligands, improving therapeutic effectiveness. This article highlights the basics of prostate cancer, statistics of prostate cancer, mechanism of multidrug resistance, targeting approach, and different types of nanocarrier used for the treatment of prostate cancer. It also includes the applications of nanocarriers for the treatment of prostate cancer and clinical trial studies to validate the safety and efficacy of the innovative drug delivery systems. The article focused on developing nanocarrier-based drug delivery systems, with the goal of translating these advancements into clinical applications in the future.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Lactate: A Theranostic Biomarker for Metabolic Psychiatry?

Alterations in neurometabolism and mitochondria are implicated in the pathophysiology of psychiatric conditions such as mood disorders and schizophrenia. Thus, developing objective biomarkers related to brain mitochondrial function is crucial for the development of interventions, such as central nervous system penetrating agents that target brain health. Lactate, a major circulatory fuel source that can be produced and utilized by the brain and body, is presented as a theranostic biomarker for neurometabolic dysfunction in psychiatric conditions. This concept is based on three key properties of lactate that make it an intriguing metabolic intermediate with implications for this field: Firstly, the lactate response to various stimuli, including physiological or psychological stress, represents a quantifiable and dynamic marker that reflects metabolic and mitochondrial health. Second, lactate concentration in the brain is tightly regulated according to the sleep-wake cycle, the dysregulation of which is implicated in both metabolic and mood disorders. Third, lactate universally integrates arousal behaviours, pH, cellular metabolism, redox states, oxidative stress, and inflammation, and can signal and encode this information via intra- and extracellular pathways in the brain. In this review, we expand on the above properties of lactate and discuss the methodological developments and rationale for the use of functional magnetic resonance spectroscopy for in vivo monitoring of brain lactate. We conclude that accurate and dynamic assessment of brain lactate responses might contribute to the development of novel and personalized therapies that improve mitochondrial health in psychiatric disorders and other conditions associated with neurometabolic dysfunction.

Increased brain 1H-MRS glutamate and lactate signals following maximal aerobic capacity exercise in young healthy males: an exploratory study

Physical exercise involves increased neuronal activity of many brain structures, but 1H-MRS investigations on the effects of human brain glutamate (Glu) concentrations on acute exercise have been sparse. Previous studies consistently found increases in brain lactate (Lac) concentrations following graded exercise up to 85% of the predicted maximal heart rate. However, the reported effects on brain concentrations of glutamine and glutamate were not consistent. This study aimed to determine the effect of acute intense graded maximal exercise on 1H-MRS signals related to concentrations of Glu, glutamate+glutamine (Glx), and Lac. Young adult males were randomly divided into two groups and subjected to 1H-MRS when resting (NE) or shortly after cessation of the intense graded exercise intended to pass the anaerobic threshold (E). 1H-MRS spectra were acquired from the large voxel encompassing the occipito-parietal cortex only once. Estimates of Glu, Glx, and Lac concentrations were calculated in institutional units by normalizing to a spectroscopic signal originating from creatine-containing compounds (Cr). Concentrations of Glu, Glx, and Lac were respectively 11%, 12.6%, and 48.5% higher in E than in NE (p < 0.001). The increased brain Lac signal in the exercising group indicated that in our experiment, vigorous exercise resulted in passing the anaerobic threshold and lactate apparently entered the brain. Concomitantly glutamate-related resonance signals from the vicinity of the occipito-parietal cortex were significantly increased; physiological mechanisms underlying these phenomena require further study. Future studies should evaluate whether the normalization rate of these concentrations is a marker of general physical fitness.

Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease

Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Real-Time Semi-Automated and Automated Voxel Placement using fMRI Targets for Repeated Acquisition Magnetic Resonance Spectroscopy

BACKGROUND

Currently, magnetic resonance spectroscopy (MRS) is dependent on the investigative team to manually prescribe, or demarcate, the desired tissue volume-of-interest. The need for a new method to automate precise voxel placements is warranted to improve the utility and interpretability of MRS data.

NEW METHOD

We propose and validate robust and real-time methods to automate MRS voxel placement using functionally defined coordinates within the prefrontal cortex. Data were collected and analyzed using two independent prospective studies: 1) two independent imaging days with each consisting of a multi-session sandwich design (MRS data only collected on one of the days determined based on scan time) and 2) a longitudinal design. Participants with fibromyalgia syndrome (N = 50) and major depressive disorder (N = 35) underwent neuroimaging. MRS acquisitions were acquired at 3-tesla. Evaluation of the reproducibility of spatial location and tissue segmentation was assessed for: 1) manual, 2) semi-automated, and 3) automated voxel prescription approaches RESULTS: Variability of voxel grey and white matter tissue composition was reduced using automated placement protocols. Spatially, post- to pre-voxel center-of-gravity distance was reduced and voxel overlap increased significantly across datasets using automated compared to manual procedures COMPARISON WITH EXISTING METHODS: Manual prescription, the current standard in the field, can produce inconsistent data across repeated acquisitions. Using automated voxel placement, we found reduced variability and more consistent voxel placement across multiple acquisitions CONCLUSIONS: These results demonstrate the within subject reliability and reproducibility of a method for reducing variability introduced by spatial inconsistencies during MRS acquisitions. The proposed method is a meaningful advance toward improved consistency of MRS data in neuroscience and can be utilized for multi-session and longitudinal studies.

Multinuclear Magnetic Resonance Spectroscopy at Ultra-High-Field: Assessing Human Cerebral Metabolism in Healthy and Diseased States

The brain is a highly energetic organ. Although the brain can consume metabolic substrates, such as lactate, glycogen, and ketone bodies, the energy metabolism in a healthy adult brain mainly relies on glucose provided via blood. The cerebral metabolism of glucose produces energy and a wide variety of intermediate metabolites. Since cerebral metabolic alterations have been repeatedly implicated in several brain disorders, understanding changes in metabolite levels and corresponding cell-specific neurotransmitter fluxes through different substrate utilization may highlight the underlying mechanisms that can be exploited to diagnose or treat various brain disorders. Magnetic resonance spectroscopy (MRS) is a noninvasive tool to measure tissue metabolism in vivo. ¹H-MRS is widely applied in research at clinical field strengths (≤3T) to measure mostly high abundant metabolites. In addition, X-nuclei MRS including, ¹³C, ²H, ¹⁷O, and ³¹P, are also very promising. Exploiting the higher sensitivity at ultra-high-field (>4T; UHF) strengths enables obtaining unique insights into different aspects of the substrate metabolism towards measuring cell-specific metabolic fluxes in vivo. This review provides an overview about the potential role of multinuclear MRS (¹H, ¹³C, ²H, ¹⁷O, and ³¹P) at UHF to assess the cerebral metabolism and the metabolic insights obtained by applying these techniques in both healthy and diseased states.

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate

ABSTRACT

Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

The future is 2D: spectral-temporal fitting of dynamic MRS data provides exponential gains in precision over conventional approaches

PURPOSE

Many MRS paradigms produce 2D spectral-temporal datasets, including diffusion-weighted, functional, and hyperpolarized and enriched (carbon-13, deuterium) experiments. Conventionally, temporal parameters-such as T₂ , T₁ , or diffusion constants-are assessed by first fitting each spectrum independently and subsequently fitting a temporal model (1D fitting). We investigated whether simultaneously fitting the entire dataset using a single spectral-temporal model (2D fitting) would improve the precision of the relevant temporal parameter.

METHODS

We derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi-echo experiment designed to estimate metabolite T₂ s, and a functional MRS experiment designed to estimate fractional change ( δ $$ \delta $$ ) in metabolite concentrations. We investigated the dependence of the relative standard deviation (SD) of T₂ in multi-echo and δ $$ \delta $$ in functional MRS.

RESULTS

When peaks were spectrally distant, 2D fitting improved precision by approximately 20% relative to 1D fitting, regardless of the experiment and other parameter values. These gains increased exponentially as peaks drew closer. Dependence on temporal model parameters was weak to negligible.

CONCLUSION

Our results strongly support a 2D approach to MRS fitting where applicable, and particularly in nuclei such as hydrogen and deuterium, which exhibit substantial spectral overlap.

Imaging and spectroscopic methods to investigate adult neurogenesis in vivo: New models and new avenues

Adult neurogenesis (AN) can be defined as the birth and development of new neurons in adulthood. Until the 1990s, AN was deemed not to happen after birth. Gradually, several groups demonstrated that specific zones of the brain of various species had a neurogenic potential. AN could be the key to treating a large range of neurodegenerative, neuropsychiatric, and metabolic diseases, with a better understanding of the mechanisms allowing for regeneration of new neurons. Despite this promising prospect, the existence of AN has not been validated in vivo in humans and therefore remains controversial. Moreover, the weight of AN-induced plasticity against other mechanisms of brain plasticity is not known, adding to the controversy. In this review, we would like to show that recent technical advances in brain MR imaging methods combined with improved models can resolve the debate.

Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics

While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) 1H-MRS techniques. While short TE 1H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) 1H-MRS with longer TE to filter overlapping resonances. The 1H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE 1H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.

Edited magnetic resonance spectroscopy in the neonatal brain

J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.

Metabolic underpinnings of activated and deactivated cortical areas in human brain

Neuroimaging with functional MRI (fMRI) identifies activated and deactivated brain regions in task-based paradigms. These patterns of (de)activation are altered in diseases, motivating research to understand their underlying biochemical/biophysical mechanisms. Essentially, it remains unknown how aerobic metabolism of glucose to lactate (aerobic glycolysis) and excitatory-inhibitory balance of glutamatergic and GABAergic neuronal activities vary in these areas. In healthy volunteers, we investigated metabolic distinctions of activating visual cortex (VC, a task-positive area) using a visual task and deactivating posterior cingulate cortex (PCC, a task-negative area) using a cognitive task. We used fMRI-guided J-edited functional MRS (fMRS) to measure lactate, glutamate plus glutamine (Glx) and γ-aminobutyric acid (GABA), as indicators of aerobic glycolysis and excitatory-inhibitory balance, respectively. Both lactate and Glx increased upon activating VC, but did not change upon deactivating PCC. Basal GABA was negatively correlated with BOLD responses in both brain areas, but during functional tasks GABA decreased in VC upon activation and GABA increased in PCC upon deactivation, suggesting BOLD responses in relation to baseline are impacted oppositely by task-induced inhibition. In summary, opposite relations between BOLD response and GABAergic inhibition, and increases in aerobic glycolysis and glutamatergic activity distinguish the BOLD response in (de)activated areas.

High temporal resolution functional magnetic resonance spectroscopy in the mouse upon visual stimulation

Functional magnetic resonance spectroscopy (fMRS) quantifies metabolic variations upon presentation of a stimulus and can therefore provide complementary information compared to activity inferred from functional magnetic resonance imaging (fMRI). Improving the temporal resolution of fMRS can be beneficial to clinical applications where detailed information on metabolism can assist the characterization of brain function in healthy and sick populations as well as for neuroscience applications where information on the nature of the underlying activity could be potentially gained. Furthermore, fMRS with higher temporal resolution could benefit basic studies on animal models of disease and for investigating brain function in general. However, to date, fMRS has been limited to sustained periods of activation which risk adaptation and other undesirable effects. Here, we performed fMRS experiments in the mouse with high temporal resolution (12 s), and show the feasibility of such an approach for reliably quantifying metabolic variations upon activation. We detected metabolic variations in the superior colliculus of mice subjected to visual stimulation delivered in a block paradigm at 9.4 T. A robust modulation of glutamate is observed on the average time course, on the difference spectra and on the concentration distributions during active and recovery periods. A general linear model is used for the statistical analysis, and for exploring the nature of the modulation. Changes in NAAG, PCr and Cr levels were also detected. A control experiment with no stimulation reveals potential metabolic signal "drifts" that are not correlated with the functional activity, which should be taken into account when analyzing fMRS data in general. Our findings are promising for future applications of fMRS.

Flexible MEGA editing scheme with asymmetric adiabatic pulses applied for T 2 measurement of lactate in human brain

PURPOSE

A flexible MEGA editing scheme which decouples the editing efficiency from TE is proposed and the utility of asymmetric adiabatic pulses for this new technique is explored. It is demonstrated that the method enables robust T 2 measurement of lactate in healthy human brain.

METHODS

The proposed variation of the MEGA scheme applies editing pulses in both acquired spectra, ensuring that the difference in J-evolution of the target resonance leads to maximal signal yield in the difference spectrum for arbitrary TE. A MEGA-sLASER sequence is augmented with asymmetric adiabatic editing pulses for enhanced flexibility and immunity to B 1 + miscalibration and inhomogeneities. The technique is validated and optimized for flexible lactate editing via a simple analytical model, numerical simulations and in vitro experiments. The T 2 relaxation constant of lactate is determined in vivo via multiple-TE measurements with the proposed method and a dedicated postprocessing and quantification approach.

RESULTS

Asymmetric adiabatic editing pulses improve robustness and facilitate efficient J-editing in sequences or protocols with strong timing constraints. Single voxel measurements using the proposed MEGA scheme in the occipital cortex of six healthy subjects yield a relaxation constant of T 2 = 171 ± 19  ms for the methyl resonance of lactate at a field strength of 3T.

CONCLUSIONS

The proposed MEGA editing scheme allows for novel kinds of J-editing experiments and promises to be an asset to robust T 2 measurement of lactate and potentially other J-coupled metabolites in vivo.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Systems Biology of Cancer Metastasis

Cancer metastasis is no longer viewed as a linear cascade of events but rather as a series of concurrent, partially overlapping processes, as successfully metastasizing cells assume new phenotypes while jettisoning older behaviors. The lack of a systemic understanding of this complex phenomenon has limited progress in developing treatments for metastatic disease. Because metastasis has traditionally been investigated in distinct physiological compartments, the integration of these complex and interlinked aspects remains a challenge for both systems-level experimental and computational modeling of metastasis. Here, we present some of the current perspectives on the complexity of cancer metastasis, the multiscale nature of its progression, and a systems-level view of the processes underlying the invasive spread of cancer cells. We also highlight the gaps in our current understanding of cancer metastasis as well as insights emerging from interdisciplinary systems biology approaches to understand this complex phenomenon.

Improved detection of lactate and β-hydroxybutyrate using MEGA-sLASER at 3 T

Lactate and β-hydroxybutyrate are important MRS-visible biomarkers for the energy metabolism of the human brain. A major obstacle for their unambiguous detection and quantification in vivo is their inherently low concentration and spectral overlap with resonances from lipids and macromolecules. In this work, we demonstrate the improved detectability of lactate and β-hydroxybutyrate with MEGA-sLASER compared to MEGA-PRESS at the clinical field strength of 3 T. The method is validated by numerical simulations, in vitro measurements and in vivo experiments on healthy subjects. It is demonstrated that MEGA-sLASER offers an SNR increase of approximately 70% for lactate and β-hydroxybutyrate detection compared to MEGA-PRESS in various brain regions. This increased SNR translates into reduced Cramér-Rao lower bounds for quantification and enables a more robust detection of subtle changes in the (brain) energy metabolism. The sensitivity of the method for detection of β-hydroxybutyrate concentration changes is demonstrated through measurements before and during a ketogenic diet while the sensitivity for detection of lactate concentration changes is shown by measurements before and after an intensive anaerobic exercise.