1H Magnetic Resonance Spectroscopic Imaging Research Articles

1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain.

Impaired glucose metabolism in the brain has been linked to several neurological disorders. Positron emission tomography and carbon-13 magnetic resonance spectroscopic imaging (MRSI) can be used to quantify the metabolism of glucose, but these methods involve exposure to radiation, cannot quantify downstream metabolism, or have poor spatial resolution. Deuterium MRSI (2H-MRSI) is a non-invasive and safe alternative for the quantification of the metabolism of 2H-labelled substrates such as glucose and their downstream metabolic products, yet it can only measure a limited number of deuterated compounds and requires specialized hardware. Here we show that proton MRSI (1H-MRSI) at 7 T has higher sensitivity, chemical specificity and spatiotemporal resolution than 2H-MRSI. We used 1H-MRSI in five volunteers to differentiate glutamate, glutamine, γ-aminobutyric acid and glucose deuterated at specific molecular positions, and to simultaneously map deuterated and non-deuterated metabolites. 1H-MRSI, which is amenable to clinically available magnetic-resonance hardware, may facilitate the study of glucose metabolism in the brain and its potential roles in neurological disorders.

Early Metabolic Changes in 1H-MRSI Predictive for Survival in Patients With Newly Diagnosed High-grade Glioma.

The purpose of this study was to evaluate the association of specific threshold values for changes in metabolic metrics measured from 1H magnetic resonance spectroscopic imaging (MRSI) to survival of patients with high-grade glioma treated with multimodality therapy. Forty-four patients with newly diagnosed high-grade glioma were prospectively enrolled. Serial MRI and MRSI scans provided measures of tumor choline, creatine, and N-acetylaspartate (NAA). Cox regression analyses adjusted for patient age, KPS, and delivery of concurrent chemotherapy were used to assess the association of changes in metabolic metrics with survival. Median follow-up time for patients at risk was 13.4 years. Overall survival (OS) was longer in patients with ≤20% increase (vs. >20%) in normalized choline (p=0.024) or choline/NAA (p=0.024) from baseline to week 4 of RT. During this period, progression-free survival (PFS) was longer in patients with ≤40% increase (vs. >40%) in normalized choline (p=0.013). Changes in normalized creatine, choline/creatine, and NAA/creatine from baseline to mid-RT were not associated with OS. From baseline to post-RT, changes in metabolic metrics were not associated with OS or PFS. Threshold values for serial changes in choline metrics on mid-RT MRSI associated with OS and PFS were identified. Metabolic metrics at post-RT did not predict for these survival endpoints. These findings suggest a potential clinical role for MRSI to provide an early assessment of treatment response and could enable risk-adapted therapy in clinical trial development and clinical practice.

Diffusion Tensor Imaging Revealed Microstructural Changes in Normal-Appearing White Matter Regions in Relapsing-Remitting Multiple Sclerosis.

BackgroundAxons and myelin sheaths are the physical foundation for white matter (WM) to perform normal functions. Our previous study found the metabolite abnormalities in frontal, parietal, and occipital normal-appearing white matter (NAWM) regions in relapsing–remitting multiple sclerosis (RRMS) patients by applying a 2D 1H magnetic resonance spectroscopic imaging method. Since the metabolite changes may associate with the microstructure changes, we used the diffusion tensor imaging (DTI) method to assess the integrity of NAWM in this study.MethodDiffusion tensor imaging scan was performed on 17 clinically definite RRMS patients and 21 age-matched healthy controls on a 3.0-T scanner. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were extracted from 19 predefined regions of interest (ROIs), which were generated by removing a mask of manually drawn probabilistic lesion map from the Johns Hopkins University white-matter atlas. The mean values of FA, MD, AD, and RD were compared between different groups in the same ROIs.ResultsA probabilistic lesion map was successfully generated, and the lesion regions were eliminated from the WM atlas. We found that the RRMS patients had significantly lower FA in the entire corpus callosum (CC), bilateral of anterior corona radiata, and right posterior thalamic radiation (PTR). At the same time, RRMS patients showed significantly higher MD in the bilateral anterior corona radiata and superior corona radiata. Moreover, all AD values increased, and the bilateral external capsule, PTR, and left tapetum NAWM show statistical significance. What is more, all NAWM tracts showed increasing RD values in RRMS patients, and the bilateral superior corona radiata, the anterior corona radiata, right PTR, and the genu CC reach statistical significance.ConclusionOur study revealed widespread microstructure changes in NAWM in RRMS patients through a ready-made WM atlas and probabilistic lesion map. These findings support the hypothesis of demyelination, accumulation of inflammatory cells, and axonal injury in NAWM for RRMS. The DTI-based metrics could be considered as potential non-invasive biomarkers of disease severity.

Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection

BackgroundCurrent multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading.MethodsForty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient.ResultsThe addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01).ConclusionThe inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

The Correlation Between Caffeine Intake and Brain Health in Cognitively Normal Healthy Older Adults

Abstract Objectives Caffeine is associated with brain health, and it is suggested to lower the risk of neurological diseases. This cross-sectional study aimed to investigate the association between caffeine intake and concentration of brain metabolites in healthy older adults. Methods Caffeine intake was determined in 60 cognitively normal, healthy older adults aged between 60–85 years (61.9% women) using a 7-day food record (7D) that was collected seven days prior to their Magnetic Resonance scan. The 7D was entered in the Nutrition Data System for Research (NDS-R version 2012) for nutrient analysis. Brain metabolites [N-acetylaspartate, creatine, total choline, glutamate + glutamine, and myo-inositol (mI)] were measured using a 1H magnetic resonance spectroscopic imaging method at 3T. All metabolites were quantified using LCModel analysis software and concentrations are shown as a ratio to creatine. Measurements were presented as mean ± standard deviation and n(%). We assessed the relationship between caffeine intake and brain metabolite concentrations by multiple linear regression, adjusting for age and sex. Statistical analyses were performed using SPSS (v25, IBM) with significance of P ≤ 0.05. Results Participants had a mean age of 69.3 ± 7.3 years. Mean caffeine intake among the participants was 152.17 ± 133.79mg/d (range: 0–635.98mg/d). There was a significant correlation between caffeine and mI (β = 0.443; P = 0.001). The remaining metabolites were not correlated with caffeine intake. Conclusions Higher caffeine intake in older adults was associated with higher brain mI concentrations. The metabolic link between brain mI concentrations and neurological diseases is still unclear, thus, future studies are necessary regarding the mechanism for the impact of caffeine on brain metabolism. Funding Sources This study is supported by funding from National Dairy Council (IYC). The Hoglund Brain Imaging Center is supported by grants from the NIH (C76 HF00201, P30 HD002528, S10 RR29577, UL1 TR000001, and P30AG035982) and the Hoglund Family Foundation.

NIMG-27. THRESHOLD VALUES OF EARLY METABOLIC CHANGES IN 1H MRSI METABOLIC METRICS PREDICTIVE FOR SURVIVAL IN PATIENTS WITH NEWLY DIAGNOSED HIGH-GRADE GLIOMA

Abstract BACKGROUND The purpose of this study was to evaluate the association of specific threshold values for changes in metabolic metrics measured from 1H magnetic resonance spectroscopic imaging (MRSI) to survival of patients with high-grade glioma treated with multimodality therapy. METHODS Forty-four patients with newly diagnosed high-grade glioma were prospectively enrolled. Serial MRI and MRS scans were performed at baseline, week 4 of radiation therapy (RT), and two months post-RT to measure tumor choline, creatine, and N-acetylaspartate (NAA) normalized to contralateral normal brain. Serial changes in metabolites were assessed using the Wilcoxon signed-rank test. Cox regression analyses adjusted for patient age, KPS, and delivery of concurrent chemotherapy were used to assess the association of changes in metabolic metrics with survival. RESULTS Median follow-up time was 13.4 years, and vital status was available for 95.1% of patients. Mean normalized choline, creatine and choline/creatine decreased significantly after baseline to post-RT in the overall group of patients (all P &amp;lt; 05). Overall survival (OS) was longer in patients with ≤ 20% increase (vs. &amp;gt; 20%) in normalized choline (P = .024) or choline/NAA (P = .024) from baseline to week 4 of RT. During this period, progression-free survival (PFS) was longer in with patients ≤ 40% increase (vs. &amp;gt; 40%) in normalized choline (P = .013). From mid-RT to post-RT, ≤ 40% decrease (vs. &amp;gt; 40%) in normalized choline/NAA (P &amp;lt; .001) or choline/creatine (P = .014), or ≤ 40% increase (vs. &amp;gt; 40%) in NAA/creatine (P = .030) were associated with reduced median OS. CONCLUSIONS Threshold values for serial changes in choline metrics on MRSI associated with OS and PFS were identified. These findings suggest a potential clinical role for MRSI to provide an early assessment of treatment response, and could enable risk-adapted therapy in clinical trial development and clinical practice.

Altered neurometabolism in major depressive disorder: A whole brain 1H-magnetic resonance spectroscopic imaging study at 3T

IntroductionMajor depressive disorder (MDD) is a severe mental disorder with a neurobiological basis that is poorly understood. Several studies demonstrated widespread, functional and neurometabolic alterations in MDD. However, little is known about whole brain neurometabolic alterations in MDD. MethodThirty-two patients with MDD and 32 paired on a one-to-one basis healthy controls (CTRL) underwent 1H-whole brain spectroscopic (1H-WBS) imaging. Lobar and cerebellar metabolite concentrations of brain N-acetylaspartate (NAA), total choline (tCho), total creatine (tCr), glutamine (Gln), glutamate (Glu), and myo-Inositol (mI) were assessed in patients and controls. ResultsDecreased NAA, tCho, and tCr were found in the right frontal and right parietal lobe in MDD compared to CTRL, and to a lesser extent in the left frontal lobe. Furthermore, in MDD increased glutamine was observed in the right frontal lobe and bitemporal lobes, and increased glutamate in the cerebellum. ConclusionAltered global neurometabolism examined using 1H-WBS imaging in MDD may be interpreted as signs of neuronal dysfunction, altered energy metabolism, and oligodendrocyte dysfunction. In particular, the parallel decrease in NAA, tCr and tCho in the same brain regions may be indicative of neuronal dysfunction that may be counterbalanced by an increase of the neuroprotective metabolite glutamine. Future prospective investigations are warranted to study the functional importance of these findings.

Metabolic effects of a prolonged, very-high-dose dietary fructose challenge in healthy subjects

Increased fructose intake has been associated with metabolic consequences such as impaired hepatic lipid metabolism and development of nonalcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the role of fructose in glucose and lipid metabolism in the liver, heart, skeletal muscle, and adipose tissue. Ten healthy subjects (age: 28±19 y; BMI: 22.2±0.7 kg/m2) underwent comprehensive metabolic phenotyping prior to and 8 wk following a high-fructose diet (150 g daily). Eleven patients with NAFLD (age: 39.4±3.95 y; BMI: 28.4±1.25) were characterized as "positive controls." Insulin sensitivity was analyzed by a 2-step hyperinsulinemic euglycemic clamp, and postprandial interorgan crosstalk of lipid and glucose metabolism was evaluated, by determining postprandial hepatic and intra-myocellular lipid and glycogen accumulation, employing magnetic resonance spectroscopy (MRS) at 7 T. Myocardial lipid content and myocardial function were assessed by 1H MRS imaging and MRI at 3 T. High fructose intake resulted in lower intake of other dietary sugars and did not increase total daily energy intake. Ectopic lipid deposition and postprandial glycogen storage in the liver and skeletal muscle were not altered. Postprandial changes in hepatic lipids were measured [Δhepatocellular lipid (HCL)_healthy_baseline: -15.9±10.7 compared with ± ΔHCL_healthy_follow-up: -6.9±4.6; P=0.17] and hepatic glycogen (Δglycogen_baseline: 64.4±14.1 compared with Δglycogen_follow-up: 51.1±9.8; P=0.42). Myocardial function and myocardial mass remained stable. As expected, impaired hepatic glycogen storage and increased ectopic lipid storage in the liver and skeletal muscle were observed in insulin-resistant patients with NAFLD. Ingestion of a high dose of fructose for 8 wk was not associated with relevant metabolic consequences in the presence of a stable energy intake, slightly lower body weight, and potentially incomplete absorption of the orally administered fructose load. This indicated that young, metabolically healthy subjects can at least temporarily compensate for increased fructose intake. This trial was registered at www.clinicaltrials.gov as NCT02075164.

Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning.

Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique that provides biochemical information from in vivo tissues. The 1H spectra acquired from several spatial regions are quantified to yield metabolite concentrations reflective of tissue metabolism. However, since these metabolites are found in tissues at very low concentrations, SI is often acquired with limited spatial resolution. In this work, we test the hypothesis that deep learning is able to upscale low resolution SI, together with the T1-weighted (T1w) image, to reconstruct high resolution SI. We report on a novel densely connected UNet (D-UNet) architecture capable of producing super-resolution spectroscopic images. The inputs for the D-UNet are the T1w image and the low resolution SI image while the output is the high resolution SI. The results of the D-UNet are compared both qualitatively and quantitatively to simulated and in vivo high resolution SI. It is found that this deep learning approach can produce high quality spectroscopic images and reconstruct entire 1H spectra from low resolution acquisitions, which can greatly advance the current SI workflow.

A multitransmit external body array combined with a 1 H and 31 P endorectal coil to enable a multiparametric and multimetabolic MRI examination of the prostate at 7T.

Purpose In vivo 1H and 31P magnetic resonance spectroscopic imaging (MRSI) provide complementary information on the biology of prostate cancer. In this work we demonstrate the feasibility of performing multiparametric imaging (mpMRI) and 1H and 31P spectroscopic imaging of the prostate using a 31P and 1H endorectal radiofrequency coil (ERC) in combination with a multitransmit body array at 7 Tesla (T).MethodsAn ERC with a 31P transceiver loop coil and 1H receive (Rx) asymmetric microstrip (31P/1H ERC) was designed, constructed and tested in combination with an external 8‐channel 1H transceiver body array coil (8CH). Electromagnetic field simulations and measurements and in vivo temperature measurements of the ERC were performed for safety validation. In addition, the signal‐to‐noise (SNR) benefit of the 1H microstrip with respect to the 8CH was evaluated. Finally, the feasibility of the setup was tested in one volunteer and three patients with prostate cancer by performing T2‐weighted and diffusion‐weighted imaging in combination with 1H and 31P spectroscopic imaging.ResultsElectromagnetic field simulations of the 31P loop coil showed no differences in the E‐ and B‐fields of the 31P/1H ERC compared with a previously safety validated ERC without 1H microstrip. The hotspot of the specific absorption rate (SAR) at the feed point of the 31P/1H ERC loop coil was 9.42 W/kg when transmitting on 31P at 1 W. Additional in vivo measurements showed a maximum temperature increase at the SAR hotspot of 0.7°C over 6 min on 31P at 1.9 W transmit (Tx) power, indicating safe maximum power levels. When transmitting with the external 1H body array at 40W for 2:30 min, the temperature increase around the ERC was < 0.3°C. Up to 3.5 cm into the prostate the 1H microstrip of the ERC provided higher SNR than the 8CH. The total coil combination allowed acquisition of an mpMRI protocol and the assessment of 31P and 1H metabolites of the prostate in all test subjects.ConclusionWe developed a setup with a 31P transceiver and 1H Rx endorectal coil in combination with an 8‐channel transceiver external body array coil and demonstrated its safety and feasibility for obtaining multiparametric imaging and 1H and 31P MRSI at 7T in patients with prostate cancer within one MR examination.

Effects of the antidepressant medication duloxetine on brain metabolites in persistent depressive disorder: A randomized, controlled trial.

BackgroundTo assess whether patients with Persistent Depressive Disorder (PDD) have abnormal levels of N-acetyl-aspartate (NAA) and whether those levels normalize following treatment with the antidepressant medication duloxetine. Furthermore, we conducted post hoc analyses of other important brain metabolites to understand better the cellular and physiological determinants for changes in NAA levels.MethodsWe acquired proton (1H) magnetic resonance spectroscopic imaging (MRSI) data on a 3 Tesla (3T), GE Magnetic Resonance Imaging (MRI) scanner in 41 patients (39.9±10.4 years, 22 males) with PDD at two time points: before the start and at the end of a 10-week, placebo-controlled, double-blind, randomized controlled trial (RCT) of the antidepressant medication duloxetine. Patients were randomized such that 21 patients received the active medication and 20 patients received placebo during the 10 week period of the trial. In addition, we acquire 1H MRSI data once in 29 healthy controls (37.7±11.2 years, 17 males).FindingsPatients had significantly higher baseline concentrations of NAA across white matter (WM) pathways and subcortical gray matter, and in direct proportion to the severity of depressive symptoms. NAA concentrations declined in duloxetine-treated patients over the duration of the trial in the direction toward healthy values, whereas concentrations increased in placebo-treated patients, deviating even further away from healthy values. Changes in NAA concentration did not mediate medication effects on reducing symptom severity, however; instead, changes in symptom severity partially mediated the effects of medication on NAA concentration, especially in the caudate and putamen.InterpretationThese findings, taken together, suggest that PDD is not a direct consequence of elevated NAA concentrations, but that a more fundamental pathophysiological process likely causes PDD and determines the severity of its symptoms. The findings also suggest that although duloxetine normalized NAA concentrations in patients, it did so by modulating the severity of depressive symptoms. Medication presumably reduced depressive symptoms through other, as yet unidentified, brain processes.Trial registrationClinicalTrials.gov NCT00360724.

The additive role of 1H-magnetic resonance spectroscopic imaging to ensure pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

PurposeTo assess the role of 1H-magnetic resonance spectroscopy (1H-MRS) in the confirmation of pathological complete response after neoadjuvant chemotherapy in breast cancer.Material and methodsForty-seven cases (53.72 ± 8.53 years) were evaluated using magnetic resonance imaging (MRI) and 1H-MRS with choline (Cho) signal-to-noise ratio (SNR) measured followed by histopathology and ROC analyses.ResultsTwelve patients had complete response, and 35 patients had residual disease. Mean age was 53.72 ± 8.53 years. The mean tumour size before neoadjuvant chemotherapy (NAC) was 4.21 ± 0.99 cm and after NAC was 0.9 ± 0.44 cm.Positive total choline signal (tCho) was detected in all cases. The mean Cho SNR before NAC was 9.53 ± 1.7 and after NAC was 2.53 ± 1.3. The Cho SNR cut-off point differentiating between pathologic complete response (pCR) and the non pCR was 1.95. Dynamic MRI showed 83.3% sensitivity, 65.7% specificity, 45.5% positive predictive value, 92.0% negative predictive value, and 70.2% diagnostic accuracy. Combined evaluation done by using the dynamic MRI and 1H-MRS showed 91.5% diagnostic accuracy with 75.0% sensitivity, 97.1% specificity, 75% positive predictive value, and 91.9% negative predictive value. ROC curves of Cho SNR showed statistically significant differences between non pCR and pCR with AUC was 0.955, 82.9% sensitivity, 91.7% specificity, 96.7% positive predictive value, 64.7% negative predictive value, and 85.11% diagnostic accuracy.Conclusions1H-MRS improves the diagnostic accuracy in the prediction of the pCR after NAC.

Tissue-type mapping of gliomas.

PurposeTo develop a statistical method of combining multimodal MRI (mMRI) of adult glial brain tumours to generate tissue heterogeneity maps that indicate tumour grade and infiltration margins.Materials and methodsWe performed a retrospective analysis of mMRI from patients with histological diagnosis of glioma (n = 25). 1H Magnetic Resonance Spectroscopic Imaging (MRSI) was used to label regions of “pure” low- or high-grade tumour across image types. Normal brain and oedema characteristics were defined from healthy controls (n = 10) and brain metastasis patients (n = 10) respectively. Probability density distributions (PDD) for each tissue type were extracted from intensity normalised proton density and T2-weighted images, and p and q diffusion maps. Superpixel segmentation and Bayesian inference was used to produce whole-brain tissue-type maps.ResultsTotal lesion volumes derived automatically from tissue-type maps correlated with those from manual delineation (p < 0.001, r = 0.87). Large high-grade volumes were determined in all grade III & IV (n = 16) tumours, in grade II gemistocytic rich astrocytomas (n = 3) and one astrocytoma with a histological diagnosis of grade II. For patients with known outcome (n = 20), patients with survival time < 2 years (3 grade II, 2 grade III and 10 grade IV) had a high-grade volume significantly greater than zero (Wilcoxon signed rank p < 0.0001) and also significantly greater high grade volume than the 5 grade II patients with survival >2 years (Mann Witney p = 0.0001). Regions classified from mMRI as oedema had non-tumour-like 1H MRS characteristics.Conclusions1H MRSI can label tumour tissue types to enable development of a mMRI tissue type mapping algorithm, with potential to aid management of patients with glial tumours.

MultiNet PyGRAPPA: Multiple neural networks for reconstructing variable density GRAPPA (a 1H FID MRSI study)

Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool for mapping metabolite levels across the brain, however, it generally suffers from long scan times. This severely hinders its application in clinical settings. Additionally, the presence of nuisance signals (e.g. the subcutaneous lipid signals close to the skull region in brain metabolite mapping) makes it challenging to apply conventional acceleration techniques to shorten the scan times. The goal of this work is, therefore, to increase the overall applicability of high resolution metabolite mapping using 1H MRSI by introducing a novel GRAPPA acceleration acquisition/reconstruction technique. An improved reconstruction method (MultiNet) is introduced that uses machine learning, specifically neural networks, to reconstruct accelerated data. The method is further modified to use more neural networks with nonlinear hidden layers and is then combined with a variable density undersampling scheme (MultiNet PyGRAPPA) to enable higher in-plane acceleration factors of R = 5.6 and R = 7 for a non-lipid suppressed ultra-short TR and TE 1H FID MRSI sequence. The proposed method is evaluated for high resolution metabolite mapping of the human brain at 9.4T. The results show that the proposed method is superior to conventional GRAPPA: there is no significant residual lipid aliasing artifact in the images when the proposed MultiNet method is used. Furthermore, the MultiNet PyGRAPPA acquisition/reconstruction method with R = 5.6 results in reproducible high resolution metabolite maps (with an in-plane matrix size of 64 × 64) that can be acquired in 2.8 min on 9.4T. In conclusion, using multiple neural networks to predict the missing points in GRAPPA reconstruction results in a more reliable data recovery while keeping the noise levels under control. Combining this high fidelity reconstruction with variable density undersampling (MultiNet PyGRAPPA) enables higher in-plane acceleration factors even for non-lipid suppressed 1H FID MRSI, without introducing any structured aliasing artifact in the image.

Carbonic anhydrase IX is a pH-stat that sets an acidic tumour extracellular pH in vivo

BackgroundTumour carbonic anhydrase IX (CAIX), a hypoxia-inducible tumour-associated cell surface enzyme, is thought to acidify the tumour microenvironment by hydrating CO2 to form protons and bicarbonate, but there is no definitive evidence for this in solid tumours in vivo.MethodsWe used 1H magnetic resonance spectroscopic imaging (MRSI) of the extracellular pH probe imidazolyl succinic acid (ISUCA) to measure and spatially map extracellular pH in HCT116 tumours transfected to express CAIX and empty vector controls in SCID mice. We also measured intracellular pH in situ with 31P MRS and measured lactate in freeze-clamped tumours.ResultsCAIX-expressing tumours had 0.15 pH-unit lower median extracellular pH than control tumours (pH 6.71 tumour vs pH 6.86 control, P = 0.01). Importantly, CAIX expression imposed an upper limit for tumour extracellular pH at 6.93. Despite the increased lactate concentration in CAIX-expressing tumours, 31P MRS showed no difference in intracellular pH, suggesting that CAIX acidifies only the tumour extracellular space.ConclusionsCAIX acidifies the tumour microenvironment, and also provides an extracellular pH control mechanism. We propose that CAIX thus acts as an extracellular pH-stat, maintaining an acidic tumour extracellular pH that is tolerated by cancer cells and favours invasion and metastasis.

Tensor-Based Method for Residual Water Suppression in 1H Magnetic Resonance Spectroscopic Imaging.

Magnetic resonance spectroscopic imaging (MRSI) signals are often corrupted by residual water and artifacts. Residual water suppression plays an important role in accurate and efficient quantification of metabolites from MRSI. A tensor-based method for suppressing residual water is proposed. A third-order tensor is constructed by stacking the Löwner matrices corresponding to each MRSI voxel spectrum along the third mode. A canonical polyadic decomposition is applied on the tensor to extract the water component and to, subsequently, remove it from the original MRSI signals. The proposed method applied on both simulated and in-vivo MRSI signals showed good water suppression performance. The tensor-based Löwner method has better performance in suppressing residual water in MRSI signals as compared to the widely used subspace-based Hankel singular value decomposition method. A tensor method suppresses residual water simultaneously from all the voxels in the MRSI grid and helps in preventing the failure of the water suppression in single voxels.

High-Quality 3-Dimensional 1H Magnetic Resonance Spectroscopic Imaging of the Prostate Without Endorectal Receive Coil Using A Semi-LASER Sequence.

Inclusion of 3-dimensional H magnetic resonance spectroscopic imaging (3D-H-MRSI) in routine multiparametric MRI of the prostate requires good quality spectra and easy interpretable metabolite maps of the whole organ obtained without endorectal coil in clinically feasible acquisition times. We evaluated if a semi-LASER pulse sequence with gradient offset independent adiabaticity refocusing pulses (GOIA-sLASER) for volume selection can meet these requirements. Thirteen patients with suspicion of prostate cancer and 1 patient known to have prostate cancer were examined at 3 T with a multichannel body-receive coil. A 3D-H-MRSI sequence with GOIA-sLASER volume selection (echo time, 88 milliseconds) was added to a routine clinical multiparametric MRI examination of these patients. Repetition times from 630 to 1000 milliseconds and effective voxel sizes of approximately 0.9 and 0.6 cm were tested. Spectral components were quantified by LCModel software for quality assessment and to construct choline and citrate maps. Three-dimensional MRSI of the prostate was successfully performed in all patients in measurement times of 5 to 10 minutes. Analysis of the multiparametric MRI examination or of biopsies did not reveal malignant tissue in the prostate of the 13 patients. In 1404 evaluated voxels acquired from 13 patients, the citrate resonance could be fitted with a high reliability (Cramér-Rao lower bound <30%), 100% for 7 × 7 × 7-mm voxels and 96 ± 7 in 6 × 6 × 6-mm voxels. The percentage of 7 × 7 × 7-mm voxels in which the choline signal was fitted with Cramér-Rao lower bound of less than 30% was approximately 50% at a TR of 630 milliseconds and increased to more than 80% for TRs of 800 milliseconds and above. In the patient with prostate cancer, choline was detectable throughout the prostate in spectra recorded at a TR of 700 milliseconds. The homogeneous B1 field over the prostate of the receive coil enabled the generation of whole organ metabolite maps, revealing choline and citrate variations between areas with normal prostate tissue, seminal vesicles, proliferative benign prostatic hyperplasia, and tumor. The good signal-to-noise ratio and low chemical shift artifacts of GOIA-sLASER at an echo time of 88 milliseconds enable acquisition of high-quality 3D-H-MRSI of the prostate without endorectal coil in less than 10 minutes. This facilitates reconstruction of easy interpretable, quantitative metabolite maps for routine clinical applications of prostate MRSI.

A minimum-phase Shinnar-Le Roux spectral-spatial excitation RF pulse for simultaneous water and lipid suppression in 1H-MRSI of body extremities

PurposeTo develop a spectral-spatial (SPSP) excitation RF pulse for simultaneous water and lipid suppression in proton (1H) magnetic resonance spectroscopic imaging (MRSI) of body extremities. MethodsAn SPSP excitation pulse is designed to excite Creatine (Cr) and Choline (Cho) metabolite signals while suppressing the overwhelming water and lipid signals. The SPSP pulse is designed using a recently proposed multidimensional Shinnar-Le Roux (SLR) RF pulse design method. A minimum-phase spectral selectivity profile is used to minimize signal loss from T2⁎ decay. ResultsThe performance of the SPSP pulse is evaluated via Bloch equation simulations and phantom experiments. The feasibility of the proposed method is demonstrated using three-dimensional, short repetition-time, free induction decay-based 1H-MRSI in the thigh muscle at 3T. ConclusionThe proposed SPSP excitation pulse is useful for simultaneous water and lipid suppression. The proposed method enables new applications of high-resolution 1H-MRSI in body extremities.

Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation

1H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.

3D characterization of gas phase reactors with regularly and irregularly structured monolithic catalysts by NMR imaging and modeling

A heterogeneously catalyzed gas phase reaction process was characterized regarding temperature and concentration profiles by means of three dimensional (3D) 1H magnetic resonance spectroscopic imaging (MRSI), using the exothermal ethylene hydrogenation as an example. Here, temperature mapping was achieved by using specifically designed thermometers filled with ethylene glycol.The impact of heat and mass transfer on the process performance was investigated by using two different monolithic catalysts with completely different heat and mass transfer characteristics: a regularly structured honeycomb monolith and a irregularly structured open-cell foam packing. The influence of these characteristics on the reaction zones within the monolithic catalysts was demonstrated by simulations that were based on 2D reactor models.To evaluate the applicability of temperature and concentration mapping by 1H MRSI for model validation, a predictive two dimensional model of the process was applied. The resulting simulations of temperature profiles and concentration distributions were in very good agreement with the experimental data with deviations below 9%. Conventional mass spectroscopic measurements provided further evidence of the accuracy of 3D MRSI measurements as well as the 2D reactor model.