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Proton magnetic resonance spectroscopic imaging (1H‐MRSI) is a powerful tool that enables the multidimensional non‐invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in 1H‐MRSI has led to increased interest in post‐processing‐based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise‐reduction techniques, Marchenko–Pastur principal component analysis (MP‐PCA) based denoising and low‐rank total generalized variation (LR‐TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T fast in vivo 1H‐FID‐MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise‐reduction strategies were conducted using Monte Carlo simulations. Results showed that both denoising techniques increased the apparent signal‐to‐noise ratio (SNR) while preserving noise properties in each spectrum for both in vivo and Monte Carlo datasets. Relative metabolite concentrations were not significantly altered by either method and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted for lower‐concentration metabolites. Our study provided a framework for how to evaluate the performance of MP‐PCA and LR‐TGV methods for preclinical 1H‐FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low‐concentration metabolites. [ABSTRACT FROM AUTHOR]

Abstract The pathophysiology underlying the post-acute sequelae of COVID-19 remains understudied and poorly understood, particularly in healthy adults with a history of mild infection. Chronic neuroinflammation may underlie these enduring symptoms, but studying neuroinflammatory phenomena in vivo is challenging, especially without a comparable pre-COVID-19 dataset. In this study, we present a unique dataset of 10 otherwise healthy individuals scanned before and after experiencing mild COVID-19. Two emerging MR-based methods were used to map pre- to post-COVID-19 brain temperature and free water changes. Post-COVID-19 brain temperature and free water increases, which are indirect biomarkers of neuroinflammation, were found in structures functionally associated with olfactory, cognitive, and memory processing. The largest pre- to post-COVID brain temperature increase was observed in the left olfactory tubercle (p = 0.007, 95% CI [0.48, 3.01]), with a mean increase of 1.75 °C. Notably, the olfactory tubercle is also the region of the primary olfactory cortex where participants with chronic olfactory dysfunction showed the most pronounced increases as compared to those without lingering olfactory dysfunction (adjusted p FDR = 0.0189, 95% CI [1.42, 5.27]). These preliminary insights suggest a potential link between neuroinflammation and chronic cognitive and olfactory dysfunction following mild COVID-19, although further investigations are needed to improve our understanding of what underlies these phenomena.

Gamma‐hydroxy‐butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß‐amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high‐resolution atlas‐based 1H‐magnetic resonance spectroscopic imaging (MRSI) at ultra‐high magnetic field strength of 7 Tesla for gray matter‐specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß‐burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein‐E‐epsilon‐4‐allele (APOE4) (p = 0.01‐0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = ‐0.48; p = 0.02; ß = ‐0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4‐dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention. Highlights: Gray matter‐specific metabolic imaging with high‐resolution atlas‐based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß‐amyloid burden, in an APOE4‐dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD. [ABSTRACT FROM AUTHOR]

The pathophysiology underlying the post-acute sequelae of COVID-19 remains understudied and poorly understood, particularly in healthy adults with a history of mild infection. Chronic neuroinflammation may underlie these enduring symptoms, but studying neuroinflammatory phenomena in vivo is challenging, especially without a comparable pre-COVID-19 dataset. In this study, we present a unique dataset of 10 otherwise healthy individuals scanned before and after experiencing mild COVID-19. Two emerging MR-based methods were used to map pre- to post-COVID-19 brain temperature and free water changes. Post-COVID-19 brain temperature and free water increases, which are indirect biomarkers of neuroinflammation, were found in structures functionally associated with olfactory, cognitive, and memory processing. The largest pre- to post-COVID brain temperature increase was observed in the left olfactory tubercle (p = 0.007, 95% CI [0.48, 3.01]), with a mean increase of 1.75 °C. Notably, the olfactory tubercle is also the region of the primary olfactory cortex where participants with chronic olfactory dysfunction showed the most pronounced increases as compared to those without lingering olfactory dysfunction (adjusted pFDR = 0.0189, 95% CI [1.42, 5.27]). These preliminary insights suggest a potential link between neuroinflammation and chronic cognitive and olfactory dysfunction following mild COVID-19, although further investigations are needed to improve our understanding of what underlies these phenomena. [ABSTRACT FROM AUTHOR]

Simple Summary: Magnetic resonance spectroscopic imaging (MRSI) plays an increasingly important role in the non-invasive diagnosis and treatment planning of gliomas. This study introduces an innovative head coil array with integrated high-order B0 shimming capabilities to enhance its clinical utility. The head coil array can effectively correct the main B0 field inhomogeneity in the brain, resulting in improved whole-brain coverage and data quality for 3D-MRSI while reducing variations in shimming across different subjects. The ultimate goal is to promote the routine clinical use of whole-brain MRSI. The spectral quality of magnetic resonance spectroscopic imaging (MRSI) can be affected by strong magnetic field inhomogeneities, posing a challenge for 3D-MRSI's widespread clinical use with standard scanner-equipped 2nd-order shim coils. To overcome this, we designed an empirical unified shim–RF head coil (32-ch RF receive and 51-ch shim) for 3D-MRSI improvement. We compared its shimming performance and 3D-MRSI brain coverages against the standard scanner shim (2nd-order spherical harmonic (SH) shim coils) and integrated parallel reception, excitation, and shimming (iPRES) 32-ch AC/DC head coil. We also simulated a theoretical 3rd-, 4th-, and 5th-order SH shim as a benchmark to assess the UNIfied shim–RF coil (UNIC) improvements. In this preliminary study, the whole-brain coverage was simulated by using B0 field maps of twenty-four healthy human subjects (n = 24). Our results demonstrated that UNIC substantially improves brain field homogeneity, reducing whole-brain frequency standard deviations by 27% compared to the standard 2nd-order scanner shim and 17% compared to the iPRES shim. Moreover, UNIC enhances whole-brain coverage of 3D-MRSI by up to 34% compared to the standard 2nd-order scanner shim and up to 13% compared to the iPRES shim. UNIC markedly increases coverage in the prefrontal cortex by 147% and 47% and in the medial temporal lobe and temporal pole by 29% and 13%, respectively, at voxel resolutions of 1.4 cc and 0.09 cc for 3D-MRSI. Furthermore, UNIC effectively reduces variations in shim quality and brain coverage among different subjects compared to scanner shim and iPRES shim. Anticipated advancements in higher-order shimming (beyond 6th order) are expected via optimized designs using dimensionality reduction methods. [ABSTRACT FROM AUTHOR]

Motivation: 31P magnetic resonance spectroscopic imaging (31P MRSI) is a powerful technique for investigating the metabolic effects of treatments for heart failure in vivo, allowing a better understanding of their mechanism of action in patient cohorts. Unfortunately, cardiac 31P MRSI is fundamentally limited by low SNR, which leads to compromises in acquisition, such as no cardiac or respiratory gating or low spatial resolution, in order to achieve reasonable scan times. Spectroscopy with linear algebra modeling (SLAM) reconstruction may be able to address these challenges and therefore improve repeatability by incorporating a segmented localizer into the reconstruction. Methods: Six healthy volunteers were scanned twice in a test-retest procedure to allow quantification of repeatability. Each scan consisted of anatomical localizers and two acquisition-weighted (AW) 31P MRSI acquisitions, which were acquired with and without cardiac gating. Five patients with heart failure with a preserved ejection fraction were then scanned with the same 31P MRSI sequence without cardiac gating. All 31P MRSI datasets were reconstructed with both conventional Fourier transform (FT)-based reconstruction and SLAM reconstruction, which were compared statistically. The effect of shifting the 31P MRSI acquisition field of view was also investigated. Results: In the healthy volunteer cohort, the spectral fit of the SLAM reconstructions had significantly improved Cramer-Rao lower bounds (CRLBs) compared to the FT-based reconstruction of non-cardiac gated data, as well as improved coefficients of variability and repeatability. The SLAM reconstruction found a significant difference in the PCr/ATP ratio between the healthy volunteer and patient cohorts, which the FT-based reconstruction did not find. Furthermore, the SLAM reconstruction was less influenced by the placement of the field of view (FOV) of the 31P MRSI acquisition in post hoc analysis. Discussion: The experimental benefits of the SLAM reconstruction for AW data were demonstrated by the improvements in fit confidence and repeatability seen in the healthy volunteer cohort and post hoc FOV analysis. The benefit of SLAM reconstruction of AW data for clinical studies was then illustrated by the patient cohort, which suggested improved sensitivity to clinically significant changes in the PCr/ATP ratio. [ABSTRACT FROM AUTHOR]

Whether brain temperature noninvasively extracted by magnetic resonance imaging has a role in identifying brain changes in the later phases of mild to moderate traumatic brain injury (TBI) is not known. This prospective study aimed to evaluate if TBI patients in subacute and chronic phases had altered brain temperature measured by whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) and if the measurable brain temperature had any relationship with cognitive function scores. WB-MRSI was performed on eight TBI patients and fifteen age- and sex-matched control subjects. Brain temperature (T) was extracted from the brain's major metabolites and compared between the two groups. The T of the patients was tested for correlation with cognitive function test scores. The results showed significantly lower brain temperature in the TBI patients (p < 0.05). Brain temperature derived from N-acetylaspartate (TNAA) strongly correlated with the 2 s paced auditory serial addition test (PASAT-2s) score (p < 0.05). The observation of lower brain temperature in TBI patients may be due to decreased metabolic activity resulting from glucose and oxygen depletion. The correlation of brain temperature with PASAT-2s may imply that noninvasive brain temperature may become a noninvasive index reflecting cognitive performance. [ABSTRACT FROM AUTHOR]

BackgroundMonitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time-point and those who remained clinically stable.MethodsForty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed.ResultsThirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients.ConclusionsLrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.

Motivation:31P magnetic resonance spectroscopic imaging (31P MRSI) is a powerful technique for investigating the metabolic effects of treatments for heart failure in vivo, allowing a better understanding of their mechanism of action in patient cohorts. Unfortunately, cardiac 31P MRSI is fundamentally limited by low SNR, which leads to compromises in acquisition, such as no cardiac or respiratory gating or low spatial resolution, in order to achieve reasonable scan times. Spectroscopy with linear algebra modeling (SLAM) reconstruction may be able to address these challenges and therefore improve repeatability by incorporating a segmented localizer into the reconstruction.Methods: Six healthy volunteers were scanned twice in a test–retest procedure to allow quantification of repeatability. Each scan consisted of anatomical localizers and two acquisition-weighted (AW) 31P MRSI acquisitions, which were acquired with and without cardiac gating. Five patients with heart failure with a preserved ejection fraction were then scanned with the same 31P MRSI sequence without cardiac gating. All 31P MRSI datasets were reconstructed with both conventional Fourier transform (FT)-based reconstruction and SLAM reconstruction, which were compared statistically. The effect of shifting the 31P MRSI acquisition field of view was also investigated.Results: In the healthy volunteer cohort, the spectral fit of the SLAM reconstructions had significantly improved Cramer–Rao lower bounds (CRLBs) compared to the FT-based reconstruction of non-cardiac gated data, as well as improved coefficients of variability and repeatability. The SLAM reconstruction found a significant difference in the PCr/ATP ratio between the healthy volunteer and patient cohorts, which the FT-based reconstruction did not find. Furthermore, the SLAM reconstruction was less influenced by the placement of the field of view (FOV) of the 31P MRSI acquisition in post hoc analysis.Discussion: The experimental benefits of the SLAM reconstruction for AW data were demonstrated by the improvements in fit confidence and repeatability seen in the healthy volunteer cohort and post hoc FOV analysis. The benefit of SLAM reconstruction of AW data for clinical studies was then illustrated by the patient cohort, which suggested improved sensitivity to clinically significant changes in the PCr/ATP ratio.

Whether brain temperature noninvasively extracted by magnetic resonance imaging has a role in identifying brain changes in the later phases of mild to moderate traumatic brain injury (TBI) is not known. This prospective study aimed to evaluate if TBI patients in subacute and chronic phases had altered brain temperature measured by whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) and if the measurable brain temperature had any relationship with cognitive function scores. WB-MRSI was performed on eight TBI patients and fifteen age- and sex-matched control subjects. Brain temperature (T) was extracted from the brain’s major metabolites and compared between the two groups. The T of the patients was tested for correlation with cognitive function test scores. The results showed significantly lower brain temperature in the TBI patients (p < 0.05). Brain temperature derived from N-acetylaspartate (TNAA) strongly correlated with the 2 s paced auditory serial addition test (PASAT-2s) score (p < 0.05). The observation of lower brain temperature in TBI patients may be due to decreased metabolic activity resulting from glucose and oxygen depletion. The correlation of brain temperature with PASAT-2s may imply that noninvasive brain temperature may become a noninvasive index reflecting cognitive performance.

Abstract With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.

Traumatic brain injury (TBI) can lead to a variety of comorbidities, including chronic pain. Although brain tissue metabolite alterations have been extensively examined in several chronic pain populations, it has received less attention in people with TBI. Thus, the primary aim of this study was to compare brain tissue metabolite levels in people with TBI and chronic pain (n = 16), TBI without chronic pain (n = 17), and pain-free healthy controls (n = 31). The metabolite data were obtained from participants using whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) at 3 Tesla. The metabolite data included N-acetylaspartate, myo-inositol, total choline, glutamate plus glutamine, and total creatine. Associations between N-acetylaspartate levels and pain severity, neuropathic pain symptom severity, and psychological variables, including anxiety, depression, post-traumatic stress disorder (PTSD), and post-concussive symptoms, were also explored. Our results demonstrate N-acetylaspartate, myo-inositol, total choline, and total creatine alterations in pain-related brain regions such as the frontal region, cingulum, postcentral gyrus, and thalamus in individuals with TBI with and without chronic pain. Additionally, NAA levels in the left and right frontal lobe regions were positively correlated with post-concussive symptoms; and NAA levels within the left frontal region were also positively correlated with neuropathic pain symptom severity, depression, and PTSD symptoms in the TBI with chronic pain group. These results suggest that neuronal integrity or density in the prefrontal cortex, a critical region for nociception and pain modulation, is associated with the severity of neuropathic pain symptoms and psychological comorbidities following TBI. Our data suggest that a combination of neuronal loss or dysfunction and maladaptive neuroplasticity may contribute to the development of persistent pain following TBI, although no causal relationship can be determined based on these data. [ABSTRACT FROM AUTHOR]

In in vivo 1H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate 1H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) can lead to a variety of comorbidities, including chronic pain. Although brain tissue metabolite alterations have been extensively examined in several chronic pain populations, it has received less attention in people with TBI. Thus, the primary aim of this study was to compare brain tissue metabolite levels in people with TBI and chronic pain (n = 16), TBI without chronic pain (n = 17), and pain-free healthy controls (n = 31). The metabolite data were obtained from participants using whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) at 3 Tesla. The metabolite data included N-acetylaspartate, myo-inositol, total choline, glutamate plus glutamine, and total creatine. Associations between N-acetylaspartate levels and pain severity, neuropathic pain symptom severity, and psychological variables, including anxiety, depression, post-traumatic stress disorder (PTSD), and post-concussive symptoms, were also explored. Our results demonstrate N-acetylaspartate, myo-inositol, total choline, and total creatine alterations in pain-related brain regions such as the frontal region, cingulum, postcentral gyrus, and thalamus in individuals with TBI with and without chronic pain. Additionally, NAA levels in the left and right frontal lobe regions were positively correlated with post-concussive symptoms; and NAA levels within the left frontal region were also positively correlated with neuropathic pain symptom severity, depression, and PTSD symptoms in the TBI with chronic pain group. These results suggest that neuronal integrity or density in the prefrontal cortex, a critical region for nociception and pain modulation, is associated with the severity of neuropathic pain symptoms and psychological comorbidities following TBI. Our data suggest that a combination of neuronal loss or dysfunction and maladaptive neuroplasticity may contribute to the development of persistent pain following TBI, although no causal relationship can be determined based on these data.

Objective: To investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition. Methods: 7 T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 ± 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), “non-iron” (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions (“rim”: distinct rim-shaped iron accumulation; “area”: iron deposition across the entire lesions; “transition”: transition between “area” and “rim” accumulation shape), and for lesion layers of “non-iron” and “rim” lesions. Furthermore, newly emerging “non-iron” and “iron” lesions were compared longitudinally, as measured before their appearance and one year later. Results: Thirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, “area” lesions exhibited a 65% higher mIns/tNAA (p = 0.035) than “rim” lesions. Comparing lesion layers of both “non-iron” and “rim” lesions, a steeper metabolic gradient of mIns/tNAA (“non-iron” +15%, “rim” +40%) and tNAA/tCr (“non-iron” −15%, “rim” −35%) was found in “iron” lesions, with the lesion core showing +22% higher mIns/tNAA (p = 0.005) and –23% lower tNAA/tCr (p = 0.048) in “iron” compared to “non-iron” lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in “iron” lesions (year 0: p = 0.013, year 1: p = 0.041) as opposed to “non-iron” lesions (year 0: p = 0.022, year 1: p = 0.231). Conclusion: 7 T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring.

pH is a tightly regulated physiological parameter that is often altered in diseased states like cancer. The development of biosensors that can be used to non-invasively image pH with hyperpolarized (HP) magnetic resonance spectroscopic imaging has therefore recently gained tremendous interest. However, most of the known HP-sensors have only individually and not comprehensively been analyzed for their biocompatibility, their pH sensitivity under physiological conditions, and the effects of chemical derivatization on their logarithmic acid dissociation constant (pKa). Proteinogenic amino acids are biocompatible, can be hyperpolarized and have at least two pH sensitive moieties. However, they do not exhibit a pH sensitivity in the physiologically relevant pH range. Here, we developed a systematic approach to tailor the pKa of molecules using modifications of carbon chain length and derivatization rendering these molecules interesting for pH biosensing. Notably, we identified several derivatives such as [1-13C]serine amide and [1-13C]-2,3-diaminopropionic acid as novel pH sensors. They bear several spin-1/2 nuclei (13C, 15N, 31P) with high sensitivity up to 4.8 ppm/pH and we show that 13C spins can be hyperpolarized with dissolution dynamic polarization (DNP). Our findings elucidate the molecular mechanisms of chemical shift pH sensors that might help to design tailored probes for specific pH in vivo imaging applications.

Three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) is a powerful non-invasive tool for characterizing spatial variations in metabolic profiles for patients with glioma. Metabolic parameters obtained using this technique have been shown to predict treatment response, disease progression, and transformation to a more malignant phenotype. The availability of ultra-high-field MR systems has the potential to improve the characterization of metabolites. The purpose of this study was to compare the metabolite profiles acquired with conventional long echo time (TE) MRSI at 3T with those obtained with short TE MRSI at 3T and 7T in patients with glioma. The data acquisition parameters were optimized separately for each echo time and field strength to obtain volumetric coverage within clinically feasible data acquisition times of 5-10 min. While a higher field strength did provide better detection of metabolites with overlapping peaks, spatial coverage was reduced and the use of inversion recovery to reduce lipid precluded the detection of lipid in regions of necrosis. For serial evaluation of large, heterogeneous lesions, the use of 3T short TE MRSI may thus be preferred. Despite the limited number of metabolites that it is able to detect, the use of 3T long TE MRSI gives the best contrast in choline/N-acetyl aspartate between normal appearing brain and tumor and also allows the separate detection of lactate and lipid. It may therefore be preferred for serial evaluation of patients with high-grade glioma and for detection of malignant transformation in patients with low-grade glioma.

Purpose: To evaluate the use of hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging (HP-13C MRSI) for quantitative measurement of early changes in glycolytic metabolism and its ability to predict response to pan-tyrosine kinase inhibitor (Pan-TKI) therapy in gastric cancer (GCa).Procedures: Pan-TKI afatinib-sensitive NCI-N87 and resistant SNU16 human GCa cells were assessed for GLUT1, hexokinase-II (HKII), lactate dehydrogenase (LDHA), phosphorylated AKT (pAKT), and phosphorylated MAPK (pMAPK) at 0-72 h of treatment with 0.1 μM afatinib. Subcutaneous NCI-N87 tumor-bearing nude mice underwent [18F]FDG PET/MRI and HP-13C MRSI at baseline and 4 days after treatment with afatinib 10 mg/kg/day or vehicle (n = 10/group). Changes in PET and HP-13C MRSI metabolic parameters were compared between the two groups. Imaging findings were correlated with tumor growth and histopathology over 3 weeks of treatment.Results: In vitro analysis showed a continuous decrease in LDHA, pAKT, and pMAPK in NCI-N87 compared to SNU16 cells within 72 h of treatment with afatinib, without a significant change in GLUT1 and HKII in either cell type. [18F]FDG PET of NCI-N87 tumors showed no significant change in PET measures at baseline and day 4 of treatment in either treatment group (SUVmean day 4/day 0: 2.7 ± 0.42/2.34 ± 0.38, p = 0.57 in the treated group vs. 1.73 ± 0.66/2.24 ± 0.43, p = 0.4 in the control group). HP-13C MRSI demonstrated significantly decreased lactate-to-pyruvate ratio (L/P) in treated tumors (L/P day 4/day 0: 0.83 ± 0.30/1.10 ± 0.20, p = 0.012 vs. 0.94 ± 0.20/0.98 ± 0.30, p = 0.75, in the treated vs. control group, respectively). Response to afatinib was confirmed with decreased tumor size over 3 weeks (11.10 ± 16.50 vs. 293.00 ± 79.30 mm3, p < 0.001, treated group vs. control group, respectively) and histopathologic evaluation.Conclusions: HP-13C MRSI is a more representative biomarker of early metabolic changes in response to pan-TKI in GCa than [18F]FDG PET and could be used for early prediction of response to targeted therapies. [ABSTRACT FROM AUTHOR]

Individuals with first-episode schizophrenia (FES) typically present with acute psychotic symptoms. Though antipsychotic drugs are the mainstay for treatment, the neurobiology underlying successful treatment remains largely elusive. Recent evidence from functional connectivity studies highlights the insula as a key structure in the neural mechanism of response. However, molecular contributions to response across insular regions remain largely unknown. We used 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to measure glutamate (Glu), Glutamine (Gln), and GABA from anterior and posterior regions of the insula across antipsychotic treatment. A total of 36 participants were examined, including 15 individuals with FES and moderate to severe psychosis who were scanned at two time points, while starting and after 6 weeks of antipsychotic treatment. Symptoms were carefully monitored across the study period to characterize treatment response. GABA, Glu, and Gln levels were calculated relative to creatine in anterior and posterior insular regions, bilaterally. In relation to psychotic symptom reduction, we observed a significant increase in Glu across all insular regions with (p < 0.001), but no corresponding changes in Gln or GABA. In group analyses, the FES cohort showed lower levels of Glu (p < 0.001) and GABA (p = 0.02) at baseline. Finally, in exploratory analyses, treatment remitters demonstrated a normalization of lower insular Glu levels across treatment, unlike non-remitters. Overall, these findings contribute to our understating of molecular changes associated with antipsychotic response and demonstrate abnormalities specific to the insula in FES. [ABSTRACT FROM AUTHOR]

Purpose: Proton ( 1 H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency because of their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time., Methods: Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in 6 min in a 2D slice in the brain. An elliptical phase-encoding sequence was measured in one volunteer in 22 min, and a 3D sequence was measured in one volunteer within 19 min. The SNR per-unit-time, linewidth, Cramer-Rao lower bounds (CRLBs), lipid contamination, and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory., Results: Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an SNR per-unit-time increase of up to 12% compared to rosette's and 23% compared to elliptical phase-encoding, dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in vivo, and phantom data. The CRLBs of γ-aminobutyric acid and N-acetylaspartylglutamate improved non-significantly for the modified rosette trajectory, whereas the linewidths and lipid contamination remained similar., Conclusion: By optimizing the shape of the rosette trajectory, the modified rosette trajectories achieved higher SNR per-unit-time and enhanced data quality at the same scan time., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Proton magnetic resonance spectroscopic imaging ( 1 H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in 1 H-MRSI has led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, Marchenko-Pastur principal component analysis (MP-PCA) based denoising and low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T fast in vivo 1 H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio (SNR) while preserving noise properties in each spectrum for both in vivo and Monte Carlo datasets. Relative metabolite concentrations were not significantly altered by either method and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted for lower-concentration metabolites. Our study provided a framework for how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1 H-FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low-concentration metabolites., (© 2024 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

Introduction: Altered neurometabolism, detectable via proton magnetic resonance spectroscopic imaging ( 1 H-MRSI), is spatially heterogeneous and underpins cognitive impairments in Alzheimer's disease (AD). However, the spatial relationships between neurometabolic topography and cognitive impairment in AD remain unexplored due to technical limitations., Methods: We used a novel whole-brain high-resolution 1 H-MRSI technique, with simultaneously acquired 18 F-florbetapir positron emission tomography (PET) imaging, to investigate the relationship between neurometabolic topography and cognitive functions in 117 participants, including 22 prodromal AD, 51 AD dementia, and 44 controls., Results: Prodromal AD and AD dementia patients exhibited spatially distinct reductions in N-acetylaspartate, and increases in myo-inositol. Reduced N-acetylaspartate and increased myo-inositol were associated with worse global cognitive performance, and N-acetylaspartate correlated with five specific cognitive scores. Neurometabolic topography provides biological insights into diverse cognitive dysfunctions., Discussion: Whole-brain high-resolution 1 H-MRSI revealed spatially distinct neurometabolic topographies associated with cognitive decline in AD, suggesting potential for noninvasive brain metabolic imaging to track AD progression., Highlights: Whole-brain high-resolution 1 H-MRSI unveils neurometabolic topography in AD. Spatially distinct reductions in NAA, and increases in mI, are demonstrated. NAA and mI topography correlates with global cognitive performance. NAA topography correlates with specific cognitive performance., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications. [ABSTRACT FROM AUTHOR]

Proton magnetic resonance spectroscopic imaging (1H‐MRSI) provides a noninvasive, spatially resolved evaluation of brain metabolism. However, there are some limitations of 1H‐MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB‐based open‐source data analysis software for three‐dimensional 1H‐MRSI, called Oryx‐MRSI, which includes modules for visualization of raw 1H‐MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx‐MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx‐MRSI is publicly available at https://github.com/Computational-Imaging-LAB/Oryx-MRSI along with six example datasets. [ABSTRACT FROM AUTHOR]

Background: Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies. Purpose: To develop absolute quantification for whole‐brain MRSI in glioma patients. Study Type: Prospective. Population: Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms. Field Strength/Sequence: A 3 T; Adiabatic spin‐echo spiral 3D MRSI with real‐time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi‐echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE). Assessment: Absolute quantification was performed for five brain metabolites (total N‐acetyl‐aspartate [NAA]/creatine/choline, glutamine + glutamate, myo‐inositol) and the oncometabolite 2‐hydroxyglutarate using a custom‐built 4x‐ERETIC/8x‐receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured. Statistical Tests: ERETIC and internal water methods for metabolite quantification were compared using Bland–Altman (BA) analysis and the nonparametric Mann–Whitney test. P < 0.05 was considered statistically significant. Results: ERETIC could be integrated in receive arrays and inductive coupling dominated (5–886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification. Conclusion: Our results indicate that ERETIC integrated with receive arrays and whole‐brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients. Evidence Level: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

This prospective study aimed to evaluate the variation in magnetic resonance spectroscopic imaging (MRSI)-observed brain metabolite concentrations according to anatomical location, sex, and age, and the relationships among regional metabolite distributions, using short echo time (TE) whole-brain MRSI (WB-MRSI). Thirty-eight healthy participants underwent short TE WB-MRSI. The major metabolite ratios, i.e., N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, glutamate + glutamine (Glx)/Cr, and myoinositol (mI)/Cr, were calculated voxel-by-voxel. Their variations according to anatomical regions, sex, and age, and their relationship to each other were evaluated by using repeated-measures analysis of variance, t-tests, and Pearson's product-moment correlation analyses. All four metabolite ratios exhibited widespread regional variation across the cerebral hemispheres (corrected p < 0.05). Laterality between the two sides and sex-related variation were also shown (p < 0.05). In several regions, NAA/Cr and Glx/Cr decreased and mI/Cr increased with age (corrected p < 0.05). There was a moderate positive correlation between NAA/Cr and mI/Cr in the insular lobe and thalamus and between Glx/Cr and mI/Cr in the parietal lobe (r ≥ 0.348, corrected p ≤ 0.025). These observations demand age- and sex- specific regional reference values in interpreting these metabolites, and they may facilitate the understanding of glial-neuronal interactions in maintaining homeostasis. [ABSTRACT FROM AUTHOR]

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients. [ABSTRACT FROM AUTHOR]

ObjectivesOur aim was to evaluate differences in metabolite levels between unmedicated patients with major depressive disorder (MDD) and healthy controls, to assess changes in metabolites in patients after they completed an 8-week course of mindfulness-based cognitive therapy (MBCT), and to exam the correlation between metabolites and depression severity.Materials and methodsSixteen patients with MDD and ten age- and gender-matched healthy controls were studied using 3D short echo-time (20 ms) magnetic resonance spectroscopic imaging (MRSI) at 7 Tesla. Relative metabolite ratios were estimated in five regions of interest corresponding to insula, anterior cingulate cortex (ACC), caudate, putamen, and thalamus.ResultsIn all cases, MBCT reduced severity of depression. The ratio of total choline-containing compounds/total creatine (tCr) in the right caudate was significantly increased compared to that in healthy controls, while ratios of N-acetyl aspartate (NAA)/tCr in the left ACC, myo-inositol/tCr in the right insula, and glutathione/tCr in the left putamen were significantly decreased. At baseline, the severity of depression was negatively correlated with my-inositol/tCr in the left insula and putamen. The improvement in depression severity was significantly associated with changes in NAA/tCr in the left ACC.ConclusionsThis study has successfully evaluated regional differences in metabolites for patients with MDD who received MBCT treatment and in controls using 7 Tesla MRSI.

MR spectroscopic imaging (MRSI) noninvasively maps the metabolism of human brains. In particular, the imaging of D‐2‐hydroxyglutarate (2HG) produced by glioma isocitrate dehydrogenase (IDH) mutations has become a key application in neuro‐oncology. However, the performance of full field‐of‐view MRSI is limited by B0 spatial nonuniformity and lipid artifacts from tissues surrounding the brain. Array coils that multiplex RF‐receive and B0‐shim electrical currents (AC/DC mixing) over the same conductive loops provide many degrees of freedom to improve B0 uniformity and reduce lipid artifacts. AC/DC coils are highly efficient due to compact design, requiring low shim currents (<2 A) that can be switched fast (0.5 ms) with high interscan reproducibility (10% coefficient of variation for repeat measurements). We measured four tumor patients and five volunteers at 3 T and show that using AC/DC coils in addition to the vendor‐provided second‐order spherical harmonics shim provides 19% narrower spectral linewidth, 6% higher SNR, and 23% less lipid content for unrestricted field‐of‐view MRSI, compared with the vendor‐provided shim alone. We demonstrate that improvement in MRSI data quality led to 2HG maps with higher contrast‐to‐noise ratio for tumors that coincide better with the FLAIR‐enhancing lesions in mutant IDH glioma patients. Smaller Cramér–Rao lower bounds for 2HG quantification are obtained in tumors by AC/DC shim, corroborating with simulations that predicted improved accuracy and precision for narrower linewidths. AC/DC coils can be used synergistically with optimized acquisition schemes to improve metabolic imaging for precision oncology of glioma patients. Furthermore, this methodology has broad applicability to other neurological disorders and neuroscience. [ABSTRACT FROM AUTHOR]

A proton-frequency-transparent (PFT) birdcage RF coil that contains carbon-proton switching circuits (CPSCs) is presented to acquire 13C MR signals, which, in turn, enable 1H imaging with existing 1H RF coils without being affected by a transparent 13C birdcage RF coil. CPSCs were installed in the PFT 13C birdcage RF coil to cut the RF coil circuits during 1H MR imaging. Finite-difference time-domain (FDTD) electromagnetic (EM) simulations were performed to verify the performance of the proposed CPSCs. The performance of the PFT 13C birdcage RF coil with CPSCs was verified via phantom and in vivo MR studies. In the phantom MR studies, 1H MR images and 13C MR spectra were acquired and compared with each other using the 13C birdcage RF coil with and without the CPSCs. For the in vivo MR studies, hyperpolarized 13C cardiac MRS and MRSI of swine were performed. The proposed PFT 13C birdcage RF coil with CPSCs led to a percent image uniformity (PIU) reduction of 1.53% in the proton MR images when compared with the case without it. FDTD EM simulations revealed PIU reduction of 0.06% under the same conditions as the phantom MR studies. Furthermore, an SNR reduction of 5.5% was observed at 13C MR spectra of corn-oil phantom using the PFT 13C birdcage RF coil with CPSCs compared with that of the 13C birdcage RF coil without CPSCs. Utilizing the PFT 13C birdcage RF coil, 13C-enriched compounds were successfully acquired via in vivo hyperpolarized 13C MRS/MRSI experiments. In conclusion, the applicability and utility of the proposed 16-leg low-pass PFT 13C birdcage RF coil with CPSCs were verified via 1H MR imaging and hyperpolarized 13C MRS/MRSI studies using a 3.0 T MRI system. [ABSTRACT FROM AUTHOR]

In in vivo 1H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate 1H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps.

Purpose: To develop a new method to generate synthetic MR spectroscopic imaging (MRSI) data for training machine learning models., Methods: This study targeted routine MRI examination protocols with single voxel spectroscopy (SVS). A novel model derived from pix2pix generative adversarial networks was proposed to generate synthetic MRSI data using MRI and SVS data as inputs. T1- and T2-weighted, SVS, and reference MRSI data were acquired from healthy brains with clinically available sequences. The proposed model was trained to generate synthetic MRSI data. Quantitative evaluation involved the calculation of the mean squared error (MSE) against the reference and metabolite ratio value. The effect of the location of and the number of the SVS data on the quality of the synthetic MRSI data was investigated using the MSE., Results: The synthetic MRSI data generated from the proposed model were visually closer to the reference. The 95% confidence interval (CI) of the metabolite ratio value of synthetic MRSI data overlapped with the reference for seven of eight metabolite ratios. The MSEs tended to be lower in the same location than in different locations. The MSEs among groups of numbers of SVS data were not significantly different., Conclusion: A new method was developed to generate MRSI data by integrating MRI and SVS data. Our method can potentially increase the volume of MRSI data training for other machine learning models by adding SVS acquisition to routine MRI examinations.

BackgroundThe purpose of this study was to evaluate the feasibility of using a short echo time, three-dimensional H-1 magnetic resonance spectroscopic imaging (MRSI) sequence at 7 Tesla (T) to assess the metabolic signature of lesions for patients with glioma.MethodsTwenty-nine patients with glioma were studied. MRSI data were obtained using CHESS water suppression, spectrally selective adiabatic inversion-recovery pulses and automatically prescribed outer-volume-suppression for lipid suppression, and spin echo slice selection (echo time = 30 ms). An interleaved flyback echo-planar trajectory was applied to shorten the total acquisition time (∼10 min). Relative metabolite ratios were estimated in tumor and in normal-appearing white and gray matter (NAWM, GM).ResultsLevels of glutamine, myo-inositol, glycine, and glutathione relative to total creatine (tCr) were significantly increased in the T2 lesions for all tumor grades compared with those in the NAWM (P

1H‐MRSI is commonly performed with gradient phase encoding, due to its simplicity and minimal radio frequency (RF) heating (specific absorption rate). Its two well‐known main problems—(i) "voxel bleed" due to the intrinsic point‐spread function, and (ii) chemical shift displacement error (CSDE) when slice‐selective RF pulses are used, which worsens with increasing volume of interest (VOI) size—have long become accepted as unavoidable. Both problems can be mitigated with Hadamard multislice RF encoding. This is demonstrated and quantified with numerical simulations, in a multislice phantom and in five healthy young adult volunteers at 3 T, targeting a 2‐cm thick temporal lobe VOI through the bilateral hippocampus. This frequently targeted region (e.g. in epilepsy and Alzheimer's disease) is subject to strong, 1‐2 ppm.cm‐1 regional B0, susceptibility gradients that can dramatically reduce the signal‐to‐noise ratio (SNR) and water suppression effectiveness. The chemical shift imaging (CSI) sequence used a 3‐ms Shinnar–Le Roux (SLR) 90° RF pulse, acquiring eight steps in the slice direction. The Hadamard sequence acquired two overlapping slices using the same SLR 90° pulses, under twofold stronger gradients that proportionally halved the CSDE. Both sequences used 2D 20 × 20 rosette spectroscopic imaging (RSI) for in‐plane spatial localization and both used RF and gradient performance characteristics that are easily met by all modern MRI instruments. The results show that Hadamard spectroscopic imaging (HSI) suffered dramatically less signal bleed within the VOI compared with CSI (<1% vs. approximately 26% in simulations; and 5%–8% vs. >50%) in a phantom specifically designed to test these effects. The voxels' SNR per unit volume per unit time was also 40% higher for HSI. In a group of five healthy volunteers, we show that HSI with in‐plane 2D‐RSI facilitates fast, 3D multivoxel encoding at submilliliter spatial resolution, over the bilateral human hippocampus, in under 10 min, with negligible CSDE, spectral and spatial contamination and more than 6% improved SNR per unit time per unit volume. [ABSTRACT FROM AUTHOR]

PurposeTo determine the ability of multiparametric MR imaging to predict disease progression in patients with prostate cancer managed by active surveillance.MethodsSixty-four men with biopsy-proven prostate cancer managed by active surveillance were included in this HIPPA compliant, IRB approved study. We reviewed baseline MR imaging scans for the presence of a suspicious findings on T2-weighted imaging, MR spectroscopic imaging (MRSI), and diffusion-weighted MR imaging (DWI). The Gleason grades at subsequent biopsy were recorded. A Cox proportional hazard model was used to determine the predictive value of MR imaging for Gleason grades, and the model performance was described using Harrell's C concordance statistic and 95% confidence intervals (CIs).ResultsThe Cox model that incorporated T2-weighted MR imaging, DWI, and MRSI showed that only T2-weighted MR imaging and DWI are independent predictors of biopsy upgrade (T2; HR = 2.46; 95% CI 1.36-4.46; P = 0.003-diffusion; HR = 2.76; 95% CI 1.13-6.71; P = 0.03; c statistic = 67.7%; 95% CI 61.1-74.3). There was an increasing rate of Gleason score upgrade with a greater number of concordant findings on multiple MR sequences (HR = 2.49; 95% CI 1.72-3.62; P

Abstract Background Glioblastoma, a high-grade glial infiltrating tumor, is the most frequent malignant brain tumor in adults and carries a dismal prognosis. External beam radiotherapy (EBRT) increases overall survival but this is still low due to local relapses, mostly occurring in the irradiation field. As the ratio of spectra of choline/N acetyl aspartate> 2 (CNR2) on MR spectroscopic imaging has been described as predictive for the site of local relapse, we hypothesized that dose escalation on these regions would increase local control and hence global survival. Methods/design In this multicenter prospective phase III trial for newly diagnosed glioblastoma, 220 patients having undergone biopsy or surgery are planned for randomization to two arms. Arm A is the Stupp protocol (EBRT 60 Gy on contrast enhancement + 2 cm margin with concomitant temozolomide (TMZ) and 6 months of TMZ maintenance); Arm B is the same treatment with an additional simultaneous integrated boost of intensity-modulated radiotherapy (IMRT) of 72Gy/2.4Gy delivered on the MR spectroscopic imaging metabolic volumes of CHO/NAA > 2 and contrast-enhancing lesions or resection cavity. Stratification is performed on surgical and MGMT status. Discussion This is a dose-painting trial, i.e. delivery of heterogeneous dose guided by metabolic imaging. The principal endpoint is overall survival. An online prospective quality control of volumes and dose is performed in the experimental arm. The study will yield a large amount of longitudinal multimodal MR imaging data including planning CT, radiotherapy dosimetry, MR spectroscopic, diffusion and perfusion imaging. Trial registration NCT01507506, registration date December 20, 2011.

Introduction Majority of the elderly male population suffers from prostatism due to enlargement of the prostate as a result of what is now regarded as male climacteric. For standardizing multiparametric magnetic resonance imaging (MRI) of the prostate, the European Society of Urogenital Radiology published Prostate Imaging Reporting and Data System (PI-RADS) in 2012. Magnetic resonance spectroscopic imaging (MRSI) uses a strong magnetic field to obtain metabolic information that identifies the relative concentrations of various metabolites in the cell cytoplasm and the extracellular space. Prostate carcinoma is associated with proportionately lower levels of citrate and higher levels of choline and creatine than are seen in benign prostatic hyperplasia (BPH) or in normal prostate. This difference can be detected by MRSI. Aim This study has been undertaken with the objective of finding how reliable MRI is in establishing the diagnosis of lesions of prostate and to correlate the histopathological (HPE) findings of transrectal ultrasound (TRUS)–guided targeted prostate biopsy with the PI-RADS scoring (Version 2) on MRI in patients. Also, the study evaluates the accuracy of MRSI in the detection of prostatic carcinoma in men with elevated prostate-specific antigen (PSA) levels. Materials and Methods A prospective study was undertaken at a tertiary care hospital during a period of 2 years from May 2017 to April 2019 on 50 patients with PSA > 4 ng/dL and with palpable lesion on digital rectal examination. MRI and MRSI were performed with a 1.5-Tesla body MRI system. The pelvic phased-array coil was used for both excitation and signal reception. Imaging was done using standard protocols. Histological material was obtained from prostate chippings from transurethral resection of prostate. Results Fifty patients with elevated PSA levels underwent MRI, MRSI, TRUS-guided biopsy and documented PI-RADS scores. Eight patients had PI-RADS 1 score, 2 patients had PI-RADS 2 score, 8 patients had PI-RADS 3 score, 14 patients had PI-RAD 4 score, and 18 patients had PI-RADS 5 score. Thirty-two patients with PI-RADS 4 and PI-RADS 5 on imaging showed positive for malignancy on HPE, showing significant association on Chi-square test with X2 = 16.412 and p < 0.001 (statistically significant). MRSI detected 36 patients on biopsy proven cases of carcinoma (sensitivity 89.5%, specificity 64%, and accuracy 88%). Conclusion This study showed a very good correlation between positivity of prostate carcinoma on HPE and higher PI-RADS (4 and 5, respectively). PI-RADS overall score had 94% sensitivity compared with components such as diffusion-weighted imaging (DWI, 78%) and T2 hypointensity (72%). MRSI is more sensitive and specific compared with T2-weighted images alone.

This prospective study aimed to evaluate the variation in magnetic resonance spectroscopic imaging (MRSI)-observed brain metabolite concentrations according to anatomical location, sex, and age, and the relationships among regional metabolite distributions, using short echo time (TE) whole-brain MRSI (WB-MRSI). Thirty-eight healthy participants underwent short TE WB-MRSI. The major metabolite ratios, i.e., N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, glutamate + glutamine (Glx)/Cr, and myoinositol (mI)/Cr, were calculated voxel-by-voxel. Their variations according to anatomical regions, sex, and age, and their relationship to each other were evaluated by using repeated-measures analysis of variance, t-tests, and Pearson’s product-moment correlation analyses. All four metabolite ratios exhibited widespread regional variation across the cerebral hemispheres (corrected p < 0.05). Laterality between the two sides and sex-related variation were also shown (p < 0.05). In several regions, NAA/Cr and Glx/Cr decreased and mI/Cr increased with age (corrected p < 0.05). There was a moderate positive correlation between NAA/Cr and mI/Cr in the insular lobe and thalamus and between Glx/Cr and mI/Cr in the parietal lobe (r ≥ 0.348, corrected p ≤ 0.025). These observations demand age- and sex- specific regional reference values in interpreting these metabolites, and they may facilitate the understanding of glial-neuronal interactions in maintaining homeostasis.

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state‐of‐the‐art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor‐provided MRSI implementations, and identifies areas which need further technical development. [ABSTRACT FROM AUTHOR]

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.

BackgroundThe objective of this study was to examine the predictive value of parameters of 3D (1)H magnetic resonance spectroscopic imaging (MRSI) prior to treatment with radiation/chemotherapy (baseline) and at a postradiation 2-month follow-up (F2mo) in relationship to 6-month progression-free survival (PFS6) and overall survival (OS).MethodsSixty-four patients with newly diagnosed glioblastoma multiforme (GBM) being treated with radiation and concurrent chemotherapy were involved in this study. Evaluated were metabolite indices and metabolite ratios. Logistic linear regression and Cox proportional hazards models were utilized to evaluate PFS6 and OS, respectively. These analyses were adjusted by age and MR scanner field strength (1.5 T or 3 T). Stepwise regression was performed to determine a subset of the most relevant variables.ResultsAssociated with shorter PFS6 were a decrease in the ratio of N-acetyl aspartate to choline-containing compounds (NAA/Cho) in the region with a Cho-to-NAA index (CNI) >3 at baseline and an increase of the CNI within elevated CNI regions (>2) at F2mo. Patients with higher normalized lipid and lactate at either time point had significantly worse OS. Patients who had larger volumes with abnormal CNI at F2mo had worse PFS6 and OS.ConclusionsOur study found more 3D MRSI parameters that predicted PFS6 and OS for patients with GBM than did anatomic, diffusion, or perfusion imaging, which were previously evaluated in the same population of patients.

Gamma-hydroxy-butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß-amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high-resolution atlas-based 1 H-magnetic resonance spectroscopic imaging (MRSI) at ultra-high magnetic field strength of 7 Tesla for gray matter-specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß-burden ( ß  = 0.60, p  < 0.05; ß  = 0.64, p  < 0.02), with positive effect modification by apolipoprotein-E-epsilon-4-allele (APOE4) ( p  = 0.01-0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance ( ß  = -0.48; p  = 0.02; ß  = -0.50; p  = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4-dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention., Highlights: Gray matter-specific metabolic imaging with high-resolution atlas-based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß-amyloid burden, in an APOE4-dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD., Competing Interests: See COI disclosure forms. Author disclosures are available in the supporting information., (© 2024 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objectives: Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in a patient cohort of 23 high-grade gliomas (HGG). Materials and methods: We preoperatively measured 23 patients with histologically verified HGGs (17 male, 8 female, age 53 ± 15) with an MRSI sequence based on concentric ring trajectories with a 64 × 64 × 39 measurement matrix, and a 3.4 × 3.4 × 3.4 mm3 nominal voxel volume in 15 min. Quantification used a basis-set of 17 components including N-acetyl-aspartate (NAA), total choline (tCho), total creatine (tCr), glutamate (Glu), glutamine (Gln), glycine (Gly) and 2-hydroxyglutarate (2HG). The resultant metabolic images were evaluated for their reliability as well as their quality and compared to spatially segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast enhanced + edema, peritumoral) based on clinical data and also compared to histopathology (e.g., grade, IDH-status). Results: Eighteen of the patient measurements were considered usable. In these patients, ten metabolites were quantified with acceptable quality. Gln, Gly, and tCho were increased and NAA and tCr decreased in nearly all tumor regions, with other metabolites such as serine, showing mixed trends. Overall, there was a reliable characterization of metabolic tumor areas. We also found heterogeneity in the metabolic images often continued into the peritumoral region. While 2HG could not be satisfyingly quantified, we found an increase of Glu in the contrast-enhancing region of IDH-wildtype HGGs and a decrease of Glu in IDH1-mutant HGGs. Conclusions: We successfully demonstrated high-resolution 7T 3D-MRSI in HGG patients, showing metabolic differences between tumor regions and peritumoral tissue for multiple metabolites. Increases of tCho, Gln (related to tumor metabolism), Gly (related to tumor proliferation), as well as decreases in NAA, tCr, and others, corresponded very well to clinical tumor segmentation, but were more heterogeneous and often extended into the peritumoral region.

A proton-frequency-transparent (PFT) birdcage RF coil that contains carbon-proton switching circuits (CPSCs) is presented to acquire 13C MR signals, which, in turn, enable 1H imaging with existing 1H RF coils without being affected by a transparent 13C birdcage RF coil. CPSCs were installed in the PFT 13C birdcage RF coil to cut the RF coil circuits during 1H MR imaging. Finite-difference time-domain (FDTD) electromagnetic (EM) simulations were performed to verify the performance of the proposed CPSCs. The performance of the PFT 13C birdcage RF coil with CPSCs was verified via phantom and in vivo MR studies. In the phantom MR studies, 1H MR images and 13C MR spectra were acquired and compared with each other using the 13C birdcage RF coil with and without the CPSCs. For the in vivo MR studies, hyperpolarized 13C cardiac MRS and MRSI of swine were performed. The proposed PFT 13C birdcage RF coil with CPSCs led to a percent image uniformity (PIU) reduction of 1.53% in the proton MR images when compared with the case without it. FDTD EM simulations revealed PIU reduction of 0.06% under the same conditions as the phantom MR studies. Furthermore, an SNR reduction of 5.5% was observed at 13C MR spectra of corn-oil phantom using the PFT 13C birdcage RF coil with CPSCs compared with that of the 13C birdcage RF coil without CPSCs. Utilizing the PFT 13C birdcage RF coil, 13C-enriched compounds were successfully acquired via in vivo hyperpolarized 13C MRS/MRSI experiments. In conclusion, the applicability and utility of the proposed 16-leg low-pass PFT 13C birdcage RF coil with CPSCs were verified via 1H MR imaging and hyperpolarized 13C MRS/MRSI studies using a 3.0 T MRI system.

Impaired oxygen and cellular metabolism is a hallmark of ischaemic injury in acute stroke. Magnetic resonance spectroscopic imaging (MRSI) has long been recognized as a potentially powerful tool for non-invasive metabolic imaging. Nonetheless, long acquisition time, poor spatial resolution, and narrow coverage have limited its clinical application. Here we investigated the feasibility and potential clinical utility of rapid, high spatial resolution, near whole-brain 3D metabolic imaging based on a novel MRSI technology. In an 8-min scan, we simultaneously obtained 3D maps of N-acetylaspartate and lactate at a nominal spatial resolution of 2.0 × 3.0 × 3.0 mm3 with near whole-brain coverage from a cohort of 18 patients with acute ischaemic stroke. Serial structural and perfusion MRI was used to define detailed spatial maps of tissue-level outcomes against which high-resolution metabolic changes were evaluated. Within hypoperfused tissue, the lactate signal was higher in areas that ultimately infarcted compared with those that recovered (P < 0.0001). Both lactate (P < 0.0001) and N-acetylaspartate (P < 0.001) differed between infarcted and other regions. Within the areas of diffusion-weighted abnormality, lactate was lower where recovery was observed compared with elsewhere (P < 0.001). This feasibility study supports further investigation of fast high-resolution MRSI in acute stroke. [ABSTRACT FROM AUTHOR]

Objective: To enable non-invasive dynamic metabolic mapping in rodent model studies of mitochondrial function using 31P-MR spectroscopic imaging (MRSI). Methods: We developed a novel method for high-resolution dynamic 31P-MRSI. The method synergistically integrates physics-based models of spectral structures, biochemical modeling of molecular dynamics, and subspace learning to capture spatiospectral variations. Fast data acquisition was achieved using rapid spiral trajectories and sparse sampling of (k, t, T)-space; image reconstruction was accomplished using a low-rank tensor-based framework. Results: The proposed method provided high-resolution dynamic metabolic mapping in rat hindlimb at spatial and temporal resolutions of 4 ${}\times \text{4} \times{}$ 2 mm3 and 1.28 s, respectively. This allowed for in vivo mapping of the time-constant of phosphocreatine resynthesis, a well established index of mitochondrial oxidative capacity. Multiple rounds of in vivo experiments were performed to demonstrate reproducibility, and in vitro experiments were used to validate the accuracy of the estimated metabolite maps. Conclusions: A new model-based method is proposed to achieve high-resolution dynamic 31P-MRSI. The proposed method's ability to delineate metabolic heterogeneity was demonstrated in rat hindlimb. Significance: Abnormal mitochondrial metabolism is a key cellular dysfunction in many prevalent diseases such as diabetes and heart disease; however, current understanding of mitochondrial function is mostly gained from studies on isolated mitochondria under nonphysiological conditions. The proposed method has the potential to open new avenues of research by allowing in vivo and longitudinal studies of mitochondrial dysfunction in disease development and progression. [ABSTRACT FROM AUTHOR]