An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis.

MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and molecular information for cancer diagnosis, prognosis, treatment monitoring, and patient management. This review provides an update on the use of MRS for clinical cancer management. The first section includes an overview of the principles of MRS, current methods, and conventional metabolites of interest. The remainder of the review is focused on three key areas: advances in instrumentation, specifically ultrahigh-field-strength MRI scanners and hybrid systems; emerging methods for acquisition, including deuterium imaging, hyperpolarized carbon 13 MRI and MRS, chemical exchange saturation transfer, diffusion-weighted MRS, MR fingerprinting, and fast acquisition; and analysis aided by artificial intelligence. The review concludes with future recommendations to facilitate routine use of MRS in cancer management. Keywords: MR Spectroscopy, Spectroscopic Imaging, Molecular Imaging in Oncology, Metabolic Reprogramming, Clinical Cancer Management © RSNA, 2024.

Perspective: use and reuse of NMR-based metabolomics data: what works and what remains challenging.

BACKGROUND: The National Cancer Institute issued a Request for Information (RFI; NOT-CA-23-007) in October 2022, soliciting input on using and reusing metabolomics data. This RFI aimed to gather input on best practices for metabolomics data storage, management, and use/reuse. AIM OF REVIEW: The nuclear magnetic resonance (NMR) Interest Group within the Metabolomics Association of North America (MANA) prepared a set of recommendations regarding the deposition, archiving, use, and reuse of NMR-based and, to a lesser extent, mass spectrometry (MS)-based metabolomics datasets. These recommendations were built on the collective experiences of metabolomics researchers within MANA who are generating, handling, and analyzing diverse metabolomics datasets spanning experimental (sample handling and preparation, NMR/MS metabolomics data acquisition, processing, and spectral analyses) to computational (automation of spectral processing, univariate and multivariate statistical analysis, metabolite prediction and identification, multi-omics data integration, etc.) studies. KEY SCIENTIFIC CONCEPTS OF REVIEW: We provide a synopsis of our collective view regarding the use and reuse of metabolomics data and articulate several recommendations regarding best practices, which are aimed at encouraging researchers to strengthen efforts toward maximizing the utility of metabolomics data, multi-omics data integration, and enhancing the overall scientific impact of metabolomics studies.

Association between altered metabolism and genetic mutations in human glioma.

BACKGROUND: Molecular markers for classification of gliomas include isocitrate dehydrogenase (IDH) mutations and codeletion of chromosomal arms 1p and 19q (1p/19q). While mutations in IDH enzymes result in the well-characterized production of oncometabolite 2-hydroxyglutarate, dysregulation of other metabolites in IDH tumors is less characterized. Similarly, the effects of 1p/19q codeletion on cellular metabolism are also unclear. AIM: This study aimed to quantify changes in tumor metabolites in human glioma tissue as a function of both IDH mutation and 1p/19q codeletion. METHODS AND RESULTS: Deidentified human glioma tissue and associated clinical data were obtained from the Emory University Winship Cancer Institute tissue biobank from 14 patients (WHO grades II, III, and IV; seven female and seven male). Proton (1 H) high-resolution magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy data were acquired using a 600 MHz Bruker AVANCE III NMR spectrometer. Metabolite concentrations were calculated using LCModel. Differences in metabolite concentrations as a function of IDH mutation, 1p/19q codeletion, and survival status were determined using Mann-Whitney U tests. Concentrations of alanine, glutamine, and glutamate were significantly lower in glioma tissue with IDH mutations compared to tissue with IDH wildtype. Additionally, glutamate concentration was significantly lower in glioma tissue with 1p/19q codeletion compared to intact 1p/19q. Exploratory analysis revealed alanine concentration varied significantly as a function of survival status. CONCLUSIONS: Given the emerging landscape of glioma treatments that target metabolic dysregulation, an improved understanding of altered metabolism in molecular sub-types of gliomas, including those with IDH mutation and 1p/19q codeletion, is an important consideration for treatment stratification and personalized medicine.

Predicting brain temperature in humans using bioheat models: Progress and outlook.

Brain temperature, regulated by the balance between blood circulation and metabolic heat generation, is an important parameter related to neural activity, cerebral hemodynamics, and neuroinflammation. A key challenge for integrating brain temperature into clinical practice is the lack of reliable and non-invasive brain thermometry. The recognized importance of brain temperature and thermoregulation in both health and disease, combined with limited availability of experimental methods, has motivated the development of computational thermal models using bioheat equations to predict brain temperature. In this mini-review, we describe progress and the current state-of-the-art in brain thermal modeling in humans and discuss potential avenues for clinical applications.

Characterization of visual processing in temporomandibular disorders using functional magnetic resonance imaging.

BACKGROUND AND PURPOSE: Many patients with chronic pain report hypersensitivity not only to noxious stimuli, but also to other modalities including innocuous touch, sound, and light, possibly due to differences in the processing of these stimuli. The goal of this study was to characterize functional connectivity (FC) differences between subjects with temporomandibular disorders (TMD) and pain-free controls during a visual functional magnetic resonance imaging (fMRI) task that included an unpleasant, strobing visual stimulus. We hypothesized the TMD cohort would exhibit maladaptations in brain networks consistent with multisensory hypersensitivities observed in TMD patients. METHODS: This pilot study included 16 subjects, 10 with TMD and 6 pain-free controls. Clinical pain was characterized using self-reported questionnaires. Visual task-based fMRI data were collected on a 3T MR scanner and used to determine differences in FC via group independent component analysis. RESULTS: Compared to controls, subjects with TMD exhibited abnormally increased FC between the default mode network and lateral prefrontal areas involved in attention and executive function, and impaired FC between the frontoparietal network and higher order visual processing areas. CONCLUSIONS: The results indicate maladaptation of brain functional networks, likely due to deficits in multisensory integration, default mode network function, and visual attention and engendered by chronic pain mechanisms.

Increased adiposity is associated with altered skeletal muscle energetics.

The objective of this pilot study was to characterize relationships between skeletal muscle energy metabolism and body composition in healthy adults with varied amounts and distribution of adipose tissue. In vivo muscle energetics were quantified using dynamic 31P magnetic resonance spectroscopy with knee extension exercise standardized to subject lean body mass. Spearman's correlation analysis examined relationships between muscle metabolism indices and measures of adiposity including body mass index (BMI), total body fat, and quadriceps intermuscular adipose tissue (IMAT). Post hoc partial correlations were examined controlling for additional body composition measures. Kruskal-Wallis tests with Dunn-Sidak post hoc comparisons evaluated group differences in energy metabolism based on body composition profiles (i.e., lean, normal-weight obese, and overweight-obese) and IMAT tertiles. BMI negatively correlated with end-exercise muscle pH after correcting for IMAT and total body fat (r = -0.46, P = 0.034). Total adiposity negatively correlated with maximum oxidative capacity after correcting for IMAT (r = -0.54, P = 0.013). IMAT positively correlated with muscle proton buffering capacity after correcting for total body fat (r = 0.53, P = 0.023). Body composition groups showed differences in end-exercise fall in [PCr] with normalized workload (P = 0.036; post hoc: overweight-obese < lean, P = 0.029) and maximum oxidative capacity (P = 0.021; post hoc: normal-weight obese < lean, P = 0.016). IMAT tertiles showed differences in end-exercise fall in [PCr] with normalized workload (P = 0.035; post hoc: 3rd < 1st, P = 0.047). Taken together, these results support increased adiposity is associated with reduced muscle energetic efficiency with more reliance on glycolysis, and when accompanied with reduced lean mass, is associated with reduced maximum oxidative capacity.NEW & NOTEWORTHY Skeletal muscle energy production is influenced by both lean body mass and adipose tissue but the effect of their distribution on energy metabolism is unclear. This study examined variations in quadriceps muscle energy metabolism in healthy adults with varied relative amounts of lean and adipose tissue. Results suggest increased adiposity is associated with reduced muscle energetic efficiency with more reliance on glycolysis, and when accompanied with reduced lean mass, is associated with reduced maximum oxidative capacity.

Effects of orientation-dependent susceptibility on MR chemical shift brain thermometry.

PURPOSE: The presence of orientation-dependent susceptibility artifacts in magnetic resonance chemical shift thermometry (CST) can confound accurate temperature calculations. Here, we quantify the effect of white matter (WM) tract orientation on CST due to tissue-specific susceptibility. METHODS: Twenty-nine healthy volunteers (27 ± 4 years old) were scanned on a 3 T MR scanner with a 32-channel head coil. Diffusion tensor imaging (DTI), T1-weighted imaging, and single voxel spectroscopy (SVS) for CST were acquired. Participants were then asked to rotate their head ∼3-5° (yaw or roll) to alter the orientation of WM tracts relative to the external magnetic field. After head rotation, a second SVS scan and T1-weighted imaging were acquired. The WM-fraction-normalized DTI principal eigenvector (V1) images were used to calculate the length of the x-y component of V1, which was used as a surrogate for WM tracts perpendicular to B0. A linear regression model was used to determine the relationship between the perpendicular WM tracts and brain temperature. RESULTS: Significant temperature differences between post- and pre-head rotation scans were observed for brain (-0.72 °C ± 1.36 °C, p = 0.01) but not body (0.012 °C ± 0.07 °C, p = 0.37) temperatures. The difference in brain temperature was positively associated with the corresponding change in perpendicular WM tracts after head rotation (R2 = 0.26, p = 0.005). CONCLUSION: Our results indicate WM tract orientation affects temperature calculations, suggesting artifacts from orientation-dependent susceptibility may be present in CST.

Resting-State Brain Temperature: Dynamic Fluctuations in Brain Temperature and the Brain-Body Temperature Gradient.

BACKGROUND: While fluctuations in healthy brain temperature have been investigated over time periods of weeks to months, dynamics over shorter time periods are less clear. PURPOSE: To identify physiological fluctuations in brain temperature in healthy volunteers over time scales of approximately 1 hour. STUDY TYPE: Prospective. SUBJECTS: A total of 30 healthy volunteers (15 female; 26 ± 4 years old). SEQUENCE AND FIELD STRENGTH: 3 T; T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) and semi-localized by adiabatic selective refocusing (sLASER) single-voxel spectroscopy. ASSESSMENTS: Brain temperature was calculated from the chemical shift difference between N-acetylaspartate and water. To evaluate within-scan repeatability of brain temperature and the brain-body temperature difference, 128 spectral transients were divided into two sets of 64-spectra. Between-scan repeatability was evaluated using two time periods, ~1-1.5 hours apart. STATISTICAL TESTS: A hierarchical linear mixed model was used to calculate within-scan and between-scan correlations (Rw and Rb , respectively). Significance was determined at P ≤ .05. Values are reported as the mean ± standard deviation. RESULTS: A significant difference in brain temperature was observed between scans (-0.4 °C) but body temperature was stable (P = .59). Brain temperature (37.9 ± 0.7 °C) was higher than body temperature (36.5 ± 0.5 °C) for all but one subject. Within-scan correlation was high for brain temperature (Rw  = 0.95) and brain-body temperature differences (Rw  = 0.96). Between scans, variability was high for both brain temperature (Rb  = 0.30) and brain-body temperature differences (Rb  = 0.41). DATA CONCLUSION: Significant changes in brain temperature over time scales of ~1 hour were observed. High short-term repeatability suggests temperature changes appear to be due to physiology rather than measurement error. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Topology of pain networks in patients with temporomandibular disorder and pain-free controls with and without concurrent experimental pain: A pilot study.

Temporomandibular disorders (TMD) involve chronic pain in the masticatory muscles and jaw joints, but the mechanisms underlying the pain are heterogenous and vary across individuals. In some cases, structural, functional, and metabolic changes in the brain may underlie the condition. In the present study, we evaluated the functional connectivity between 86 regions of interest (ROIs), which were chosen based on previously reported neuroimaging studies of pain and differences in brain morphology identified in an initial surface-based morphometry analysis. Our main objectives were to investigate the topology of the network formed by these ROIs and how it differs between individuals with TMD and chronic pain (n = 16) and pain-free control participants (n = 12). In addition to a true resting state functional connectivity scan, we also measured functional connectivity during a 6-min application of a noxious cuff stimulus applied to the left leg. Our principal finding is individuals with TMD exhibit more suprathreshold correlations (higher nodal degree) among all ROIs but fewer "hub" nodes (i.e., decreased betweenness centrality) across conditions and across all pain pathways. These results suggest is this pain-related network of nodes may be "over-wired" in individuals with TMD and chronic pain compared to controls, both at rest and during experimental pain.

Comparisons of healthy human brain temperature predicted from biophysical modeling and measured with whole brain MR thermometry.

Brain temperature is an understudied parameter relevant to brain injury and ischemia. To advance our understanding of thermal dynamics in the human brain, combined with the challenges of routine experimental measurements, a biophysical modeling framework was developed to facilitate individualized brain temperature predictions. Model-predicted brain temperatures using our fully conserved model were compared with whole brain chemical shift thermometry acquired in 30 healthy human subjects (15 male and 15 female, age range 18-36 years old). Magnetic resonance (MR) thermometry, as well as structural imaging, angiography, and venography, were acquired prospectively on a Siemens Prisma whole body 3 T MR scanner. Bland-Altman plots demonstrate agreement between model-predicted and MR-measured brain temperatures at the voxel-level. Regional variations were similar between predicted and measured temperatures (< 0.55 °C for all 10 cortical and 12 subcortical regions of interest), and subcortical white matter temperatures were higher than cortical regions. We anticipate the advancement of brain temperature as a marker of health and injury will be facilitated by a well-validated computational model which can enable predictions when experiments are not feasible.

Demographic reporting across a decade of neuroimaging: a systematic review.

Diversity of participants in biomedical research with respect to race, ethnicity, and biological sex is crucial, particularly given differences in disease prevalence, recovery, and survival rates between demographic groups. The objective of this systematic review was to report on the demographics of neuroimaging studies using magnetic resonance imaging (MRI). The Web of Science database was used and data collection was performed between June 2021 to November 2021; all articles were reviewed independently by at least two researchers. Articles utilizing MR data acquired in the United States, with n ≥ 10 human subjects, and published between 2010-2020 were included. Non-primary research articles and those published in journals that did not meet a quality control check were excluded. Of the 408 studies meeting inclusion criteria, approximately 77% report sex, 10% report race, and 4% report ethnicity. Demographic reporting also varied as function of disease studied, participant age range, funding, and publisher. We anticipate quantitative data on the extent, or lack, of reporting will be necessary to ensure inclusion of diverse populations in biomedical research.

Sex differences in the relationships between body composition, fat distribution, and mitochondrial energy metabolism: a pilot study.

BACKGROUND: Adiposity and mitochondrial dysfunction are related factors contributing to metabolic disease development. This pilot study examined whether in vivo and ex vivo indices of mitochondrial metabolism were differentially associated with body composition in males and females. METHODS: Thirty-four participants including 19 females (mean 27 yr) and 15 males (mean 29 yr) had body composition assessed by dual energy x-ray absorptiometry and magnetic resonance (MR) imaging. Monocyte reserve capacity and maximal oxygen consumption rate (OCR) were determined ex vivo using extracellular flux analysis. In vivo quadriceps mitochondrial function was measured using 31P-MR spectroscopy based on post-exercise recovery kinetics (τPCr). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin levels. Variables were log-transformed, and Pearson correlations and partial correlations were used for analyses. RESULTS: Mitochondrial metabolism was similar between sexes (p > 0.05). In males only, higher fat mass percent (FM%) was correlated with lower reserve capacity (r = - 0.73; p = 0.002) and reduced muscle mitochondrial function (r = 0.58, p = 0.02). Thigh subcutaneous adipose tissue was inversely related to reserve capacity in males (r = - 0.75, p = 0.001), but in females was correlated to higher maximal OCR (r = 0.48, p = 0.046), independent of FM. In females, lean mass was related to greater reserve capacity (r = 0.47, p = 0.04). In all participants, insulin (r = 0.35; p = 0.04) and HOMA-IR (r = 0.34; p = 0.05) were associated with a higher τPCr. CONCLUSIONS: These novel findings demonstrate distinct sex-dependent associations between monocyte and skeletal muscle mitochondrial metabolism with body composition. With further study, increased understanding of these relationships may inform sex-specific interventions to improve mitochondrial function and metabolic health.

Relationships between frontal metabolites and Alzheimer's disease biomarkers in cognitively normal older adults.

Elevated expression of ß-amyloid (Aß1-42) and tau are considered risk-factors for Alzheimer's disease in healthy older adults. We investigated the effect of aging and cerebrospinal fluid levels of Aß1-42 and tau on 1) frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) and 2) cognition in cognitively normal older adults (n = 144; age range 50-85). Levels of frontal gamma aminobutyric acid (GABA+) and myo-inositol relative to creatine (mI/tCr) were predicted by age. Levels of GABA+ predicted cognitive performance better than mI/tCr. Additionally, we found that frontal levels of n-acetylaspartate relative to creatine (tNAA/tCr) were predicted by levels of t-tau. In cognitively normal older adults, levels of frontal GABA+ and mI/tCr are predicted by aging, with levels of GABA+ decreasing with age and the opposite for mI/tCr. These results suggest that age- and biomarker-related changes in brain metabolites are not only located in the posterior cortex as suggested by previous studies and further demonstrate that MRS is a viable tool in the study of aging and biomarkers associated with pathological aging and Alzheimer's disease.

Changes in brain metabolites and resting-state connectivity in collegiate basketball players as a function of play time.

BACKGROUND AND PURPOSE: Magnetic resonance (MR) biomarkers are emerging for sports-related traumatic brain injury (TBI), but the effect of play time has not been characterized. Our goal was to characterize brain and inflammatory marker changes as a function of play time. METHODS: Nine male players (21±2 years old) from a single collegiate basketball team were included. MR imaging (MRI), MR spectroscopy, and plasma were collected pre, mid, and postseason. Game time played was calculated for each subject. Changes in brain volume, diffusion tensor imaging (DTI), metabolites (normalized to total creatine, tCr), temperature, structural and functional connectivity, and inflammatory markers were quantified. RESULTS: Myo-inositol/tCr in the left frontal white matter and brain temperature in the left frontal lobe varied significantly between time points. Glutamate (Glu/tCr) in the right frontal white matter and N-acetylaspartate in the posterior cingulate cortex (PCC) were negatively associated with minutes played. Midseason play time was associated with stronger blood-oxygen-level-dependent correlations between PCC and occipital areas, and weaker correlations between PCC and superior frontal connectivity. PCC Glu/tCr was positively associated with connectivity between the PCC and posterior supramarginal gyrus at preseason and with connectivity across time points among several right hemisphere regions. Volume, DTI, and inflammatory markers did not vary significantly. CONCLUSION: Given that MR parameters vary with game play time in the absence of diagnosed injury, play time should be considered as a factor in sports-related TBI research.

Characterization of dysregulated glutamine metabolism in human glioma tissue with 1H NMR.

Gliomas are one of the most common types of brain tumors. Given low survival and high treatment resistance rates, particularly for high grade gliomas, there is a need for specific biomarkers that can be used to stratify patients for therapy and monitor treatment response. Recent work has demonstrated that metabolic reprogramming, often mediated by inflammation, can lead to an upregulation of glutamine as an energy source for cancer cells. As a result, glutamine pathways are an emerging pharmacologic target. The goal of this pilot study was to characterize changes in glutamine metabolism and inflammation in human glioma samples and explore the use of glutamine as a potential biomarker. 1H high-resolution magic angle spinning nuclear magnetic resonance spectra were acquired from ex vivo glioma tissue (n = 16, grades II-IV) to quantify metabolite concentrations. Tumor inflammatory markers were quantified using electrochemiluminescence assays. Glutamate, glutathione, lactate, and alanine, as well as interleukin (IL)-1ß and IL-8, increased significantly in samples from grade IV gliomas compared to grades II and III (p ≤ .05). Following dimension reduction of the inflammatory markers using probabilistic principal component analysis, we observed that glutamine, alanine, glutathione, and lactate were positively associated with the first inflammatory marker principal component. Our findings support the hypothesis that glutamine may be a key marker for glioma progression and indicate that inflammation is associated with changes in glutamine metabolism. These results motivate further in vivo investigation of glutamine as a biomarker for tumor progression and treatment response.

Optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition.

Multi-channel phased receive arrays have been widely adopted for magnetic resonance imaging (MRI) and spectroscopy (MRS). An important step in the use of receive arrays for MRS is the combination of spectra collected from individual coil channels. The goal of this work was to implement an improved strategy termed OpTIMUS (i.e., optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition) for combining data from individual channels. OpTIMUS relies on spectral windowing coupled with a rank-R decomposition to calculate the optimal coil channel weights. MRS data acquired from a brain spectroscopy phantom and 11 healthy volunteers were first processed using a whitening transformation to remove correlated noise. Whitened spectra were then iteratively windowed or truncated, followed by a rank-R singular value decomposition (SVD) to empirically determine the coil channel weights. Spectra combined using the vendor-supplied method, signal/noise2 weighting, previously reported whitened SVD (rank-1), and OpTIMUS were evaluated using the signal-to-noise ratio (SNR). Significant increases in SNR ranging from 6% to 33% (P ≤ 0.05) were observed for brain MRS data combined with OpTIMUS compared with the three other combination algorithms. The assumption that a rank-1 SVD maximizes SNR was tested empirically, and a higher rank-R decomposition, combined with spectral windowing prior to SVD, resulted in increased SNR.

Traumatic Brain Injury Results in Dynamic Brain Structure Changes Leading to Acute and Chronic Motor Function Deficits in a Pediatric Piglet Model.

Traumatic brain injury (TBI) is a leading cause of death and disability in children. Pediatric TBI patients often suffer from crippling cognitive, emotional, and motor function deficits that have negative lifelong effects. The objective of this study was to longitudinally assess TBI pathophysiology using multi-parametric magnetic resonance imaging (MRI), gait analysis, and histological approaches in a pediatric piglet model. TBI was produced by controlled cortical impact in Landrace piglets. MRI data, including from proton magnetic resonance spectroscopy (MRS), were collected 24 hours and 12 weeks post-TBI, and gait analysis was performed at multiple time-points over 12 weeks post-TBI. A subset of animals was sacrificed 24 hours, 1 week, 4 weeks, and 12 weeks post-TBI for histological analysis. MRI results demonstrated that TBI led to a significant brain lesion and midline shift as well as microscopic tissue damage with altered brain diffusivity, decreased white matter integrity, and reduced cerebral blood flow. MRS showed a range of neurochemical changes after TBI. Histological analysis revealed neuronal loss, astrogliosis/astrocytosis, and microglia activation. Further, gait analysis showed transient impairments in cadence, cycle time, % stance, step length, and stride length, as well as long-term impairments in weight distribution after TBI. Taken together, this study illustrates the distinct time course of TBI pathoanatomic and functional responses up to 12 weeks post-TBI in a piglet TBI model. The study of TBI injury and recovery mechanisms, as well as the testing of therapeutics in this translational model, are likely to be more predictive of human responses and clinical outcomes compared to traditional small animal models.

Impact of Anti-Biofouling Surface Coatings on the Properties of Nanomaterials and Their Biomedical Applications.

Understanding and subsequently controlling non-specific interactions between engineered nanomaterials and biological environment have become increasingly important for further developing and advancing nanotechnology for biomedical applications. Such non-specific interactions, also known as the biofouling effect, mainly associate with the adsorption of biomolecules (such as proteins, DNAs, RNAs, and peptides) onto the surface of nanomaterials and the adhesion or uptake of nanomaterials by various cells. By altering the surface properties of nanomaterials the biofouling effect can lead to in situ changes of physicochemical properties, pharmacokinetics, functions, and toxicity of nanomaterials. This review provides discussions on the current understanding of the biofouling effect, the factors that affect the non-specific interactions associated with biofouling, and the impact of the biofouling effect on the performances and functions of nanomaterials. An overview of the development and applications of various anti-biofouling coating materials to preserve and improve the properties and functions of engineered nanomaterials for intended biomedical applications is also provided.