High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI

Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of structurally identified and yet-undefined metabolites across tissue cryosections. While numerous software packages enable pixel-by-pixel imaging of individual metabolites, the research community lacks a discovery tool that images all metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs informs discovery of unanticipated molecules contributing to shared metabolic pathways, uncovers hidden metabolic heterogeneity across cells and tissue subregions, and indicates single-timepoint flux through pathways of interest. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling and instrument drift, markedly enhances spatial image resolution, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent tool to enhance knowledge obtained from current spatial metabolite profiling technologies.

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

PURPOSE

We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level.

METHODS

The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0-4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency.

RESULTS

The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout.

CONCLUSIONS

We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems.

7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading

INTRODUCTION

With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients.

METHODS

We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status.

RESULTS

Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy.

CONCLUSIONS

We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.

Whole-brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism

Deuterium metabolic imaging (DMI) is an emerging magnetic resonance technique, for non-invasive mapping of human brain glucose metabolism following oral or intravenous administration of deuterium-labeled glucose. Regional differences in glucose metabolism can be observed in various brain pathologies, such as Alzheimer's disease, cancer, epilepsy or schizophrenia, but the achievable spatial resolution of conventional phase-encoded DMI methods is limited due to prolonged acquisition times rendering submilliliter isotropic spatial resolution for dynamic whole brain DMI not feasible. The purpose of this study was to implement non-Cartesian spatial-spectral sampling schemes for whole-brain 2H FID-MR Spectroscopic Imaging to assess time-resolved metabolic maps with sufficient spatial resolution to reliably detect metabolic differences between healthy gray and white matter regions. Results were compared with lower-resolution DMI maps, conventionally acquired within the same session. Six healthy volunteers (4 m/2 f) were scanned for ~90 min after administration of 0.8 g/kg oral [6,6']-2H glucose. Time-resolved whole brain 2H FID-DMI maps of glucose (Glc) and glutamate + glutamine (Glx) were acquired with 0.75 and 2 mL isotropic spatial resolution using density-weighted concentric ring trajectory (CRT) and conventional phase encoding (PE) readout, respectively, at 7 T. To minimize the effect of decreased signal-to-noise ratios associated with smaller voxels, low-rank denoising of the spatiotemporal data was performed during reconstruction. Sixty-three minutes after oral tracer uptake three-dimensional (3D) CRT-DMI maps featured 19% higher (p = .006) deuterium-labeled Glc concentrations in GM (1.98 ± 0.43 mM) compared with WM (1.66 ± 0.36 mM) dominated regions, across all volunteers. Similarly, 48% higher (p = .01) 2H-Glx concentrations were observed in GM (2.21 ± 0.44 mM) compared with WM (1.49 ± 0.20 mM). Low-resolution PE-DMI maps acquired 70 min after tracer uptake featured smaller regional differences between GM- and WM-dominated areas for 2H-Glc concentrations with 2.00 ± 0.35 mM and 1.71 ± 0.31 mM, respectively (+16%; p = .045), while no regional differences were observed for 2H-Glx concentrations. In this study, we successfully implemented 3D FID-MRSI with fast CRT encoding for dynamic whole-brain DMI at 7 T with 2.5-fold increased spatial resolution compared with conventional whole-brain phase encoded (PE) DMI to visualize regional metabolic differences. The faster metabolic activity represented by 48% higher Glx concentrations was observed in GM- compared with WM-dominated regions, which could not be reproduced using whole-brain DMI with the low spatial resolution protocol. Improved assessment of regional pathologic alterations using a fully non-invasive imaging method is of high clinical relevance and could push DMI one step toward clinical applications.

Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory

Purpose

1.1 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 due to 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

1.2Analytical 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 six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory.

Results

1.3Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's 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 improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar.

Conclusion

1.4By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality.

A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients

This paper investigated the correlation between magnetic resonance spectroscopic imaging (MRSI) and magnetic resonance fingerprinting (MRF) in glioma patients by comparing neuro-oncological markers obtained from MRSI to T1/T2 maps from MRF. Data from 12 consenting patients with gliomas were analyzed by defining hotspots for T1, T2, and various metabolic ratios, and comparing them using Sørensen-Dice similarity coefficients (DSCs) and the distances between their centers of intensity (COIDs). The median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were the highest for Gln/tNAA (T1: 0.75, T2: 0.80, tumor: 0.78), followed by Gly/tNAA (T1: 0.57, T2: 0.62, tumor: 0.54) and tCho/tNAA (T1: 0.61, T2: 0.58, tumor: 0.45). The median values in the tumor hotspot were T1 = 1724 ms, T2 = 86 ms, Gln/tNAA = 0.61, Gly/tNAA = 0.28, Ins/tNAA = 1.15, and tCho/tNAA = 0.48, and, in the peritumoral region, were T1 = 1756 ms, T2 = 102 ms, Gln/tNAA = 0.38, Gly/tNAA = 0.20, Ins/tNAA = 1.06, and tCho/tNAA = 0.38, and, in the NAWM, were T1 = 950 ms, T2 = 43 ms, Gln/tNAA = 0.16, Gly/tNAA = 0.07, Ins/tNAA = 0.54, and tCho/tNAA = 0.20. The results of this study constitute the first comparison of 7T MRSI and 3T MRF, showing a good correspondence between these methods.

Implementation of a 7T Epilepsy Task Force consensus imaging protocol for routine presurgical epilepsy work-up: effect on diagnostic yield and lesion delineation

OBJECTIVE

Recently, the 7 Tesla (7 T) Epilepsy Task Force published recommendations for 7 T magnetic resonance imaging (MRI) in patients with pharmaco-resistant focal epilepsy in pre-surgical evaluation. The objective of this study was to implement and evaluate this consensus protocol with respect to both its practicability and its diagnostic value/potential lesion delineation surplus effect over 3 T MRI in the pre-surgical work-up of patients with pharmaco-resistant focal onset epilepsy.

METHODS

The 7 T MRI protocol consisted of T1-weighted, T2-weighted, high-resolution-coronal T2-weighted, fluid-suppressed, fluid-and-white-matter-suppressed, and susceptibility-weighted imaging, with an overall duration of 50 min. Two neuroradiologists independently evaluated the ability of lesion identification, the detection confidence for these identified lesions, and the lesion border delineation at 7 T compared to 3 T MRI.

RESULTS

Of 41 recruited patients > 12 years of age, 38 were successfully measured and analyzed. Mean detection confidence scores were non-significantly higher at 7 T (1.95 ± 0.84 out of 3 versus 1.64 ± 1.19 out of 3 at 3 T, p = 0.050). In 50% of epilepsy patients measured at 7 T, additional findings compared to 3 T MRI were observed. Furthermore, we found improved border delineation at 7 T in 88% of patients with 3 T-visible lesions. In 19% of 3 T MR-negative cases a new potential epileptogenic lesion was detected at 7 T.

CONCLUSIONS

The diagnostic yield was beneficial, but with 19% new 7 T over 3 T findings, not major. Our evaluation revealed epilepsy outcomes worse than ILAE Class 1 in two out of the four operated cases with new 7 T findings.

Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.

Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging

OBJECTIVE

This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging (CEST-MRI).

METHODS

Three sets of Z-spectrum data with saturation power (B1) values of 1.5, 2.5, and 3.5 µT, respectively, were acquired from 17 patients with ischemic stroke. Multiple contrasts contributing to the Z-spectrum, including fitted amide proton transfer (APTfitted), +2 ppm peak (CEST@2ppm), concomitantly fitted APTfitted and CEST@2ppm (APT&CEST@2ppm), semisolid magnetization transfer contrast (MT), aliphatic nuclear Overhauser effect (NOE), and direct saturation of water (DSW), were fitted with 4 and 5 Lorentzian functions, respectively. The CEST metrics were compared between ischemic lesions and contralateral normal white matter (CNWM), and the correlation between the CEST metrics and the apparent diffusion coefficient (ADC) was assessed. The differences in the Z-spectrum metrics under varied B1 values were also investigated.

RESULTS

Ischemic lesions showed increased APTfitted, CEST@2ppm, APT&CEST@2ppm, NOE, and DSW as well as decreased MT. APT&CEST@2ppm, MT, and DSW showed a significant correlation with ADC [APT&CEST@2ppm at the 3 B1 values: R=0.584/0.467/0.551; MT at the 3 B1 values: R=-0.717/-0.695/-0.762 (4-parameter fitting), R=-0.734/-0.711/-0.785 (5-parameter fitting); DSW of 4-/5-parameter fitting: R=0.794/0.811 (2.5 µT), R=0.800/0.790 (3.5 µT)]. However, the asymmetric analysis of amide proton transfer (APTasym) could not differentiate the lesions from CNWM and showed no correlation with ADC. Furthermore, the Z-spectrum contrasts varied with B1.

CONCLUSION

The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.

Ultrahigh-field MRI: where it really makes a difference

BACKGROUND

Currently, two major magnetic resonance (MR) vendors provide commercial 7‑T scanners that are approved by the Food and Drug Administration (FDA) for clinical application. There is growing interest in ultrahigh-field MRI because of the improved clinical results in terms of morphological detail, as well as functional and metabolic imaging capabilities.

MATERIALS AND METHODS

The 7‑T systems benefit from a higher signal-to-noise ratio, which scales supralinearly with field strength, a supralinear increase in the blood oxygenation level dependent (BOLD) contrast for functional MRI and susceptibility weighted imaging (SWI), and the chemical shift increases linearly with field strength with consequently higher spectral resolution.

RESULTS

In multiple sclerosis (MS), 7‑T imaging enables visualization of cortical lesions, the central vein sign, and paramagnetic rim lesions, which may be beneficial for the differential diagnosis between MS and other neuroinflammatory diseases in challenging and inconclusive clinical presentations and are seen as promising biomarkers for prognosis and treatment monitoring. The recent development of high-resolution proton MR spectroscopic imaging in clinically reasonable scan times has provided new insights into tumor metabolism and tumor grading as well as into early metabolic changes that may precede inflammatory processes in MS. This technique also improves the detection of epileptogenic foci in the brain. Multi-nuclear clinical applications, such as sodium imaging, have shown great potential for the evaluation of repair tissue quality after cartilage transplantation and in the monitoring of newly developed cartilage regenerative drugs for osteoarthritis.

CONCLUSION

For special clinical applications, such as SWI in MS, MR spectroscopic imaging in tumors, MS and epilepsy, and sodium imaging in cartilage repair, 7T may become a new standard.

Using Single-Voxel Magnetic Resonance Spectroscopy Data Acquired at 1.5T to Classify Multivoxel Data at 3T: A Proof-of-Concept Study

In vivo magnetic resonance spectroscopy (MRS) has two modalities, single-voxel (SV) and multivoxel (MV), in which one or more contiguous grids of SVs are acquired.

PURPOSE

To test whether MV grids can be classified with models trained with SV.

METHODS

Retrospective study. Training dataset: Multicenter multiformat SV INTERPRET, 1.5T. Testing dataset: MV eTumour, 3T. Two classification tasks were completed: 3-class (meningioma vs. aggressive vs. normal) and 4-class (meningioma vs. low-grade glioma vs. aggressive vs. normal). Five different methods were tested for feature selection. The classification was implemented using linear discriminant analysis (LDA), random forest, and support vector machines. The evaluation was completed with balanced error rate (BER) and area under the curve (AUC) on both sets. The accuracy in class prediction was calculated by developing a solid tumor index (STI) and segmentation accuracy with the Dice score.

RESULTS

The best method was sequential forward feature selection combined with LDA, with AUCs = 0.95 (meningioma), 0.89 (aggressive), 0.82 (low-grade glioma), and 0.82 (normal). STI was 66% (4-class task) and 71% (3-class task) because two cases failed completely and two more had suboptimal STI as defined by us.

DISCUSSION

The reasons for failure in the classification of the MV test set were related to the presence of artifacts.

Magnetic resonance spectroscopic correlates of progression free and overall survival in "glioblastoma, IDH-wildtype, WHO grade-4"

Background

The 2021 World Health Organization (WHO) Central Nervous System (CNS) Tumor Classification has suggested that isocitrate dehydrogenase wildtype (IDH-wt) WHO grade-2/3 astrocytomas with molecular features of glioblastoma should be designated as "Glioblastoma, IDH-wildtype, WHO grade-4." This study analyzed the metabolic correlates of progression free and overall survival in "Glioblastoma, IDH-wildtype, WHO grade-4" patients using short echo time single voxel ¹H-MRS.

Methods

Fifty-seven adult patients with hemispheric glioma fulfilling the 2021 WHO CNS Tumor Classification criteria for "Glioblastoma, IDH-wildtype, WHO grade-4" at presurgery time point were included. All patients were IDH1/2-wt and TERTp-mut. ¹H-MRS was performed on a 3 T MR scanner and post-processed using LCModel. A Mann-Whitney U test was used to assess the metabolic differences between gliomas with or without contrast enhancement and necrosis. Cox regression analysis was used to assess the effects of age, extent of resection, presence of contrast enhancement and necrosis, and metabolic intensities on progression-free survival (PFS) and overall survival (OS). Machine learning algorithms were employed to discern possible metabolic patterns attributable to higher PFS or OS.

Results

Contrast enhancement (p = 0.015), necrosis (p = 0.012); and higher levels of Glu/tCr (p = 0.007), GSH/tCr (p = 0.019), tCho/tCr (p = 0.032), and Glx/tCr (p = 0.010) were significantly associated with shorter PFS. Additionally, necrosis (p = 0.049), higher Glu/tCr (p = 0.039), and Glx/tCr (p = 0.047) were significantly associated with worse OS. Machine learning models differentiated the patients having longer than 12 months OS with 81.71% accuracy and the patients having longer than 6 months PFS with 77.41% accuracy.

Conclusion

Glx and GSH have been identified as important metabolic correlates of patient survival among "IDH-wt, TERT-mut diffuse gliomas" using single-voxel ¹H-MRS on a clinical 3 T MRI scanner.

A vision of 14 T MR for fundamental and clinical science

OBJECTIVE

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

RESEARCH FIELDS

The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

CONCLUSIONS

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.

Operando NMR metabolomics of a microfluidic cell culture

In this work we demonstrate the use of microfluidic NMR for in situ culture and quantitative analysis of metabolism in hepatocellular carcinoma (HCC) cell lines. A hydrothermal heating system is used to enable continuous in situ NMR observation of HCC cell culture over a 24 h incubation period. This technique is nondestructive, non-invasive and can measure millimolar concentrations at microlitre volumes, within a few minutes and in precisely controlled culture conditions. This is sufficient to observe changes in primary energy metabolism, using around 500-3500 cells per device, and with a time resolution of 17 min. The ability to observe intracellular responses in a time-resolved manner provides a more detailed view of a biological system and how it reacts to stimuli. This capability will allow detailed metabolomic studies of cell-culture based cancer models, enabling quantification of metabolic reporgramming, the metabolic tumor microenvironment, and the metabolic interplay between cancer- and immune cells.

Stereotactic Magnetic Resonance-Guided Adaptive and Non-Adaptive Radiotherapy on Combination MR-Linear Accelerators: Current Practice and Future Directions

Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care.

Lesion-Specific Metabolic Alterations in Relapsing-Remitting Multiple Sclerosis Via 7 T Magnetic Resonance Spectroscopic Imaging

BACKGROUND

Magnetic resonance spectroscopic imaging (MRSI) of the brain enables in vivo assessment of metabolic alterations in multiple sclerosis (MS). This provides complementary insights into lesion pathology that cannot be obtained via T1- and T2-weighted conventional magnetic resonance imaging (cMRI).

PURPOSE

The aims of this study were to assess focal metabolic alterations inside and at the periphery of lesions that are visible or invisible on cMRI, and to correlate their metabolic changes with T1 hypointensity and the distance of lesions to cortical gray matter (GM).

METHODS

A 7 T MRSI was performed on 51 patients with relapsing-remitting MS (30 female/21 male; mean age, 35.4 ± 9.9 years). Mean metabolic ratios were calculated for segmented regions of interest (ROIs) of normal-appearing white matter, white matter lesions, and focal regions of increased mIns/tNAA invisible on cMRI. A subgroup analysis was performed after subdividing based on T1 relaxation and distance to cortical GM. Metabolite ratios were correlated with T1 and compared between different layers around cMRI-visible lesions.

RESULTS

Focal regions of, on average, 2.8-fold higher mIns/tNAA than surrounding normal-appearing white matter and with an appearance similar to that of MS lesions were found, which were not visible on cMRI (ie, ~4% of metabolic hotspots). T1 relaxation was positively correlated with mIns/tNAA ( P ≤ 0.01), and negatively with tNAA/tCr ( P ≤ 0.01) and tCho/tCr ( P ≤ 0.01). mIns/tCr was increased outside lesions, whereas tNAA/tCr distributions resembled macroscopic tissue damage inside the lesions. mIns/tCr was -21% lower for lesions closer to cortical GM ( P ≤ 0.05).

CONCLUSIONS

7 T MRSI allows in vivo visualization of focal MS pathology not visible on cMRI and the assessment of metabolite levels in the lesion center, in the active lesion periphery and in cortical lesions. This demonstrated the potential of MRSI to image mIns as an early biomarker in lesion development.

Application of 7T MRS to High-Grade Gliomas

MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.

Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging have shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, ¹H FID MRSI by correcting for T₁-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg^-1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T₁-corrections for water are common in MRSI studies; however, most studies use either averaged T₁-relaxation times to correct for T₁-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T₁-corrections for metabolites in addition to water. Utilizing averaged T₁-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T₁-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works.

Spectroscopic imaging of D-2-hydroxyglutarate and other metabolites in pre-surgical patients with IDH-mutant lower-grade gliomas

Purpose

Prognostically favorable IDH-mutant gliomas are known to produce oncometabolite D-2-hydroxyglutarate (2HG). In this study, we investigated metabolite-based features of patients with grade 2 and 3 glioma using 2HG-specific in vivo MR spectroscopy, to determine their relationship with image-guided tissue pathology and predictive role in progression-free survival (PFS).

Methods

Forty-five patients received pre-operative MRIs that included 3-D spectroscopy optimized for 2HG detection. Spectral data were reconstructed and quantified to compare metabolite levels according to molecular pathology (IDH1R132H, 1p/19q, and p53); glioma grade; histological subtype; and T2 lesion versus normal-appearing white matter (NAWM) ROIs. Levels of 2HG were correlated with other metabolites and pathological parameters (cellularity, MIB-1) from image-guided tissue samples using Pearson’s correlation test. Metabolites predictive of PFS were evaluated with Cox proportional hazards models.

Results

Quantifiable levels of 2HG in 39/42 (93%) IDH+ and 1/3 (33%) IDH– patients indicated a 91.1% apparent detection accuracy. Myo-inositol/total choline (tCho) showed reduced values in astrocytic (1p/19q-wildtype), p53-mutant, and grade 3 (vs. 2) IDH-mutant gliomas (p < 0.05), all of which exhibited higher proportions of astrocytomas. Compared to NAWM, T2 lesions displayed elevated 2HG+ γ-aminobutyric acid (GABA)/total creatine (tCr) (p < 0.001); reduced glutamate/tCr (p < 0.001); increased myo-inositol/tCr (p < 0.001); and higher tCho/tCr (p < 0.001). Levels of 2HG at sampled tissue locations were significantly associated with tCho (R = 0.62; p = 0.002), total NAA (R = − 0.61; p = 0.002) and cellularity (R = 0.37; p = 0.04) but not MIB-1. Increasing levels of 2HG/tCr (p = 0.0007, HR 5.594) and thresholding (≥ 0.905, median value; p = 0.02) predicted adverse PFS.

Conclusion

In vivo 2HG detection can reasonably be achieved on clinical scanners and increased levels may signal adverse PFS.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors

Simple Summary

Magnetic resonance spectroscopic imaging is an imaging method that can map the distribution of multiple biochemicals in the human brain in one scan. Using stronger magnetic fields, such as 7 Tesla, allows for higher resolution images and more biochemical maps. To test these results, we compared it to positron emission tomography, the established clinical standard for metabolic imaging. This comparison mainly looked at the overlap between regions with increased signal between both methods. We found that the molecules glutamine and glycine, only mappable at 7 Tesla, corresponded better to positron emission tomography than the commonly used choline.

Abstract

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives

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.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Objective

To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.

Methods

The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).

Results

The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.

Conclusion

Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain

Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

Phosphorus magnetic resonance spectroscopic imaging (³¹P MRSI) is of particular interest for investigations of patients with brain tumors as it enables to non-invasively assess altered energy and phospholipid metabolism in vivo. However, the limited sensitivity of ³¹P MRSI hampers its broader application at clinical field strengths. This study aimed to identify the additional value of ³¹P MRSI in patients with glioma at ultra-high B₀ = 7T, where the increase in signal-to-noise ratio may foster its applicability for clinical research. High-quality, 3D ³¹P MRSI datasets with an effective voxel size of 5.7 ml were acquired from the brains of seven patients with newly diagnosed glioma. An optimized quantification model was implemented to reliably extract an extended metabolic profile, including low-concentrated metabolites such as extracellular inorganic phosphate, nicotinamide adenine dinucleotide [NAD(H)], and uridine diphosphoglucose (UDPG), which may act as novel tumor markers; a background signal was extracted as well, which affected measures of phosphomonoesters beneficially. Application of this model to the MRSI datasets yielded high-resolution maps of 12 different ³¹P metabolites, showing clear metabolic differences between white matter (WM) and gray matter, and between healthy and tumor tissues. Moreover, differences between tumor compartments in patients with high-grade glioma (HGG), i.e., gadolinium contrast-enhancing/necrotic regions (C+N) and peritumoral edema, could also be suggested from these maps. In the group of patients with HGG, the most significant changes in metabolite intensities were observed in C+N compared to WM, i.e., for phosphocholine +340%, UDPG +54%, glycerophosphoethanolamine −45%, and adenosine-5′-triphosphate −29%. Furthermore, a prominent signal from mobile phospholipids appeared in C+N. In the group of patients with low-grade glioma, only the NAD(H) intensity changed significantly by −28% in the tumor compared to WM. Besides the potential of ³¹P MRSI at 7T to provide novel insights into the biochemistry of gliomas in vivo, the attainable spatial resolutions improve the interpretability of ³¹P metabolite intensities obtained from malignant tissues, particularly when only subtle differences compared to healthy tissues are expected. In conclusion, this pilot study demonstrates that ³¹P MRSI at 7T has potential value for the clinical research of glioma.

Extensive Brain Pathologic Alterations Detected with 7.0-T MR Spectroscopic Imaging Associated with Disability in Multiple Sclerosis

Background MR spectroscopic imaging (MRSI) allows in vivo assessment of brain metabolism and is of special interest in multiple sclerosis (MS), where morphologic MRI cannot depict major parts of disease activity. Purpose To evaluate the ability of 7.0-T MRSI to depict and visualize pathologic alterations in the normal-appearing white matter (NAWM) and cortical gray matter (CGM) in participants with MS and to investigate their relation to disability. Materials and Methods Free-induction decay MRSI was performed at 7.0 T. Participants with MS and age- and sex-matched healthy controls were recruited prospectively between January 2016 and December 2017. Metabolic ratios were obtained in white matter lesions, NAWM, and CGM regions. Subgroup analysis for MS-related disability based on Expanded Disability Status Scale (EDSS) scores was performed using analysis of covariance. Partial correlations were applied to explore associations between metabolic ratios and disability. Results Sixty-five participants with MS (mean age ± standard deviation, 34 years ± 9; 34 women) and 20 age- and sex-matched healthy controls (mean age, 32 years ± 7; 11 women) were evaluated. Higher signal intensity of myo-inositol (mI) with and without reduced signal intensity of N-acetylaspartate (NAA) was visible on metabolic images in the NAWM of participants with MS. A higher ratio of mI to total creatine (tCr) was observed in the NAWM of the centrum semiovale of all MS subgroups, including participants without disability (marginal mean ± standard error, healthy controls: 0.78 ± 0.04; EDSS 0-1: 0.86 ± 0.03 [P = .02]; EDSS 1.5-3: 0.95 ± 0.04 [P < .001]; EDSS ≥3.5: 0.94 ± 0.04 [P = .001]). A lower ratio of NAA to tCr was found in MS subgroups with disabilities, both in their NAWM (marginal mean ± standard error, healthy controls: 1.46 ± 0.04; EDSS 1.5-3: 1.33 ± 0.03 [P = .03]; EDSS ≥3.5: 1.30 ± 0.04 [P = .01]) and CGM (marginal mean ± standard error, healthy controls: 1.42 ± 0.05; EDSS ≥3.5: 1.23 ± 0.05 [P = .006]). mI/NAA correlated with EDSS (NAWM of centrum semiovale: r = 0.47, P < .001; parietal NAWM: r = 0.43, P = .002; frontal NAWM: r = 0.34, P = .01; frontal CGM: r = 0.37, P = .004). Conclusion MR spectroscopic imaging at 7.0 T allowed in vivo visualization of multiple sclerosis pathologic findings not visible at T1- or T2-weighted MRI. Metabolic abnormalities in the normal-appearing white matter and cortical gray matter were associated with disability. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Barker in this issue.

Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI

There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian ¹ H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D ¹ H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.

Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T

PURPOSE

Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.

METHODS

We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs.

RESULTS

Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate.

DISCUSSION

We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B₀ /B₁ -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.

High-Resolution Magnetic Resonance Spectroscopic Imaging using a Multi-Encoder Attention U-Net with Structural and Adversarial Loss

Common to most medical imaging techniques, the spatial resolution of Magnetic Resonance Spectroscopic Imaging (MRSI) is ultimately limited by the achievable SNR. This work presents a deep learning method for 1H-MRSI spatial resolution enhancement, based on the observation that multi-parametric MRI images provide relevant spatial priors for MRSI enhancement. A Multi-encoder Attention U-Net (MAU-Net) architecture was constructed to process a MRSI metabolic map and three different MRI modalities through separate encoding paths. Spatial attention modules were incorporated to automatically learn spatial weights that highlight salient features for each MRI modality. MAU-Net was trained based on in vivo brain imaging data from patients with high-grade gliomas, using a combined loss function consisting of pixel, structural and adversarial loss. Experimental results showed that the proposed method is able to reconstruct high-quality metabolic maps with a high-resolution of 64×64 from a low-resolution of 16 × 16, with better performance compared to several baseline methods.

MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.

Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo

Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.

Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients

OBJECTIVES

To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI).

METHODS

One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses.

RESULTS

DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications.

CONCLUSIONS

Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients.

KEY POINTS

• Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.