Conventional Magnetic Resonance Spectroscopy Research Articles

Diffusion kurtosis imaging for different brain masses characterization

BackgroundDiffusion kurtosis imaging is an advanced magnetic resonance imaging technique that reveals additional information on the microstructure and micro-dynamics of different brain masses without the need for contrast agents. The aim of this study was to provide a comprehensive analysis of the role of MRI diffusion kurtosis and to compare it with magnetic resonance spectroscopy (MRS) and dynamic susceptibility contrast perfusion (DSC) in characterizing different brain masses, including gliomas, recurrent tumors, radiation necrosis, abscesses, and infarctions. Sixty-six patients with intracranial brain masses were enrolled in this prospective study. All patients were examined by conventional MRI sequences, DSC perfusion, MRS, and diffusion kurtosis imaging, with implemented b values which were 200, 500, 1000, 1500 and 2000s/mm2.ResultsMean kurtosis (MK) was higher (P < 0.001) in recurrent brain tumors than in radiation-induced necrosis; the optimal MK cutoff value for differentiation between them was 642 with 91.3% sensitivity and 85.7% specificity. Mean kurtosis was also higher (P < 0.001) in high-grade gliomas than in low-grade gliomas; the optimal MK cutoff value for differentiation between them was 639 with 91.6% sensitivity and 85.71% specificity. There was a good level of agreement between ADC and MD within the studied cases, with a correlation coefficient r = 0.815. MK had more sensitivity and specificity in differentiation between high- and low-grade gliomas, as well as RIN and tumoral recurrence, than MRS and DSC.ConclusionsDiffusion kurtosis imaging stands as an integral, noninvasive, and noncontrast tool for the characterization of various brain masses. It augments the capabilities of traditional and advanced MRI techniques, providing a deeper understanding of the microstructural changes in brain tissues.

Clinical value of magnetic resonance spectroscopy in assessment of early curing impact of concurrent chemoradiotherapy after high-grade glioma surgery

Background/Aim. High-grade glioma (HGG) is an interstitial cell-derived primary tumor of the nervous system. The current guidelines for the diagnosis and treatment of glioma recommend the maximum safe range of tumor resection for treatment methods. Adjuvant concurrent chemoradiotherapy is recommended after surgery, followed by six cycles of single-drug chemotherapy, temozolomide. Evaluation of the early efficacy of concurrent chemoradiotherapy after HGG surgery, especially for patients with a high risk of recurrence, is a crucial step in enhancing the treatment efficiency for patients diagnosed with HGG. In this study, we investigated the clinical utility of magnetic resonance (MR) spectroscopy (MRS) in assessing the early curing impact of concurrent chemoradiotherapy following HGG surgery. Methods. A total of 50 patients with incomplete resection or suspected residual postoperative HGG, treated in the radiotherapy department of our hospital between January 2016 and June 2021, were selected for routine concurrent chemoradiotherapy. Conventional MR imaging and MRS were performed one week prior to treatment and one month after treatment to assess changes in specific brain metabolites. All 50 patients were followed up for 6 to 12 months. Based on the follow-up results, the patients were divided into two groups: the tumor recurrence group and the tumor suppression group. One month after the end of the treatment, the differences in levels of brain metabolites between the two groups were analyzed using MRS. Results. The levels of N-acetylaspartate (NAA) and creatine (Cr) increased after radiotherapy, while choline (Cho) peak value, and Cho/Cr, NAA/Cr, and Cho/NAA ratios decreased compared to pre-treatment levels. There were statistically significant differences in the NAA peak value, and Cho/Cr, and Cho/NAA ratios in the tumor enhancement area before and after treatment (p &lt; 0.05). There were also statistically significant differences in Cho/Cr ratio in the peritumoral edema area before and after treatment (p &lt; 0.05). Conclusion. After concurrent chemoradiotherapy, MRS can be used to detect early metabolic changes in the tumor enhancement and peritumoral edema areas of HGG.

A rapid method for phosphocreatine-weighted imaging in muscle using double saturation power-chemical exchange saturation transfer.

Monitoring the variation in phosphocreatine (PCr) levels following exercise provides valuable insights into muscle function. Chemical exchange saturation transfer (CEST) has emerged as a sensitive method with which to measure PCr levels in muscle, surpassing conventional MR spectroscopy. However, existing approaches for quantifying PCr CEST signals rely on time-consuming fitting methods that require the acquisition of the entire or a section of the CEST Z-spectrum. Additionally, traditional fitting methods often necessitate clear CEST peaks, which may be challenging to obtain at low magnetic fields. This paper evaluated the application of a new model-free method using double saturation power (DSP), termed DSP-CEST, to estimate the PCr CEST signal in muscle. The DSP-CEST method requires the acquisition of only two or a few CEST signals at the PCr frequency offset with two different saturation powers, enabling rapid dynamic imaging. Additionally, the DSP-CEST approach inherently eliminates confounding signals, offering enhanced robustness compared with fitting methods. Furthermore, DSP-CEST does not demand clear CEST peaks, making it suitable for low-field applications. We evaluated the capability of DSP-CEST to enhance the specificity of PCr CEST imaging through simulations and experiments on muscle tissue phantoms at 4.7 T. Furthermore, we applied DSP-CEST to animal leg muscle both before and after euthanasia and observed successful reduction of confounding signals. The DSP-CEST signal still has contaminations from a residual magnetization transfer (MT) effect and an aromatic nuclear Overhauser enhancement effect, and thus only provides a PCr-weighted imaging. The residual MT effect can be reduced by a subtraction of DSP-CEST signals at 2.6 and 5 ppm. Results show that the residual MT-corrected DSP-CEST signal at 2.6 ppm has significant variation in postmortem tissues. By contrast, both the CEST signal at 2.6 ppm and a conventional Lorentzian difference analysis of CEST signal at 2.6 ppm demonstrate no significant variation in postmortem tissues.

Deuterium MR spectroscopy: potential applications in oncology research.

Metabolic imaging in clinical practice has long relied on PET with fluorodeoxyglucose (FDG), a radioactive tracer. However, this conventional method presents inherent limitations such as exposure to ionizing radiation and potential diagnostic uncertainties, particularly in organs with heightened glucose uptake like the brain. This review underscores the transformative potential of traditional deuterium MR spectroscopy (MRS) when integrated with gradient techniques, culminating in an advanced metabolic imaging modality known as deuterium MRI (DMRI). While recent advancements in hyperpolarized MRS hold promise for metabolic analysis, their widespread clinical usage is hindered by cost constraints and the availability of hyperpolarizer devices or facilities. DMRI, also denoted as deuterium metabolic imaging (DMI), represents a pioneering, single-shot, and noninvasive paradigm that fuses conventional MRS with nonradioactive deuterium-labelled substrates. Extensively tested in animal models and patient cohorts, particularly in cases of brain tumours, DMI's standout feature lies in its seamless integration into standard clinical MRI scanners, necessitating only minor adjustments such as radiofrequency coil tuning to the deuterium frequency. DMRI emerges as a versatile tool for quantifying crucial metabolites in clinical oncology, including glucose, lactate, glutamate, glutamine, and characterizing IDH mutations. Its potential applications in this domain are broad, spanning diagnostic profiling, treatment response monitoring, and the identification of novel therapeutic targets across diverse cancer subtypes.

Magnetic Resonance Spectroscopy Findings of Intracranial Chondroma and Chondrosarcoma with a Non-skull Base Origin: A Report of Two Cases

Introduction: Intracranial chondroma and chondrosarcoma are very rare tumors that mainly originate from the base of the skull. Advanced neuroimaging studies, including magnetic resonance spectroscopy (MRS), play a pivotal role in both tumor diagnosis and presurgical planning. Case Presentation: We present two cases of intracranial cartilaginous tumors, including a chondroma and a chondrosarcoma, both of which presented with severe headaches. Due to inconclusive conventional MRI and MRS results, they were both primarily diagnosed as intra-axial brain tumors. However, pathological reports later confirmed the diagnosis of a chondroma and a chondrosarcoma. Conclusion: Based on the present findings, the use of advanced neuroimaging techniques, such as MRS, may improve diagnostic accuracy. We believe that MRS can play a significant role in the surgical planning of similar cases. Also, reporting rare cases worldwide can contribute to the improvement of radiographic diagnosis.

Characterizing Various Posterior Fossa Tumors in Children and Adults With Diffusion-Weighted Imaging and Spectroscopy.

Background Theposterior fossa is situated between thetentorium cerebelli above and the foramen magnum below. Vital structures like the cerebellum, the pons, and the medulla are situated within it; hence, tumors within the posterior fossa are considered one of the most critical brain lesions. Children are more likely to develop posterior fossa tumors than adults. Diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) sequences along with the conventional MRI helpin providing additional information in the characterization of the various posterior fossa tumors. We hereby present a series of 30 patients with clinically suspected posterior fossa masses who underwent preoperative MRI. Objectives This study aims to differentiate the neoplastic from non-neoplastic posterior fossa mass by evaluating the diffusion restriction pattern on DWI, quantifying the apparent diffusion coefficient (ADC) map in various posterior fossa tumors, and comparing the different metabolites of various posterior fossa tumors on MRS. Results Out of the 30 patients with posterior fossa lesions, 18 were males and 12 were females. Eight of them were in the pediatric age group, while twenty-two of them were adults. Metastasis was the most common posterior fossa lesionin our study sample and was found in six patients (20%), followed by vestibular schwannomas (17%) and arachnoid cysts (13%), meningiomas, medulloblastoma, and pilocytic astrocytoma (10% each) and epidermoid, ependymoma, and hemangioblastoma (7% each). The mean ADC value of benign tumors was higher than that of malignant tumors, and this difference was found to be significant (p = 0.012). The cut-off ADC value 1.21x 10-3mm2/s had a sensitivity of 81.82% and specificity of 80.47%. MRS metabolites played an additional role in differentiating benign from malignant tumors. Conclusion A combination of conventional MRI, DWI,ADC values, and MRS metabolites showed good diagnostic accuracy to differentiate between the various posterior fossa neoplastic tumors both in adults and children.

MP-PCA denoising for diffusion MRS data: promises and pitfalls

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4 T in rat brain and at 3 T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.

Low Unsaturated Fatty Acids Level in the Vertebral Bone Marrow of Postmenopausal Osteoporosis: A Pilot 2D iDQC-MRS on 3.0 T Study.

Unsaturated fatty acids (UFAs) of bone marrow play a critical role in osteoporosis. However, it is difficult to resolve the UFA, especially in the presence of trabecular bone, using conventional magnetic resonance spectroscopy (MRS) methods. To preliminarily compare the bone marrow fatty acids (FAs) composition in the presence of trabecular bone of postmenopausal osteoporosis (PMOP) and healthy controls (HC). Prospective. Total thirty-six postmenopausal women were recruited with CT-confirmed PMOP (n=19) and HC (n=17). A 3 T scanner. Localized 2D intermolecular double-quantum coherence-based MRS (iDQC-MRS). In addition to the conventional water and fat peaks, another four crossing peaks of the FAs were well resolved from the L4 vertebral bone marrow using iDQC-MRS technique: allylic methylene (2.0 ppm), terminal methylene (2.2ppm), diallylic methylene (2.7ppm), and olefinic (5.3ppm). The monounsaturated fatty acids (MOFA) and polyunsaturated fatty acids (PUFAs) were then calculated. Differences between PMOP and HC were investigated using the analysis of a t-test, and the relationships were investigated using regression analysis. MOFAs and PUFAs fractions were significantly lower in the PMOP group compared to the HC group. In contrast, the saturated FAs fraction is significantly higher in the PMOP group. Additionally, decreased PUFAs, MOFAs were moderately negatively correlated with the volumetric bone mineral density (vBMD) in the PMOP group. Furthermore, increased SFAs in PMOP were strongly associated with vBMD. Using spectra resolution enhanced 2D iDQC-MRS technique, we observed low unsaturated FAs levels in the vertebral bone marrow of the PMOP patients. The reduced unsaturated FAs levels in PMOP may be associated with dysfunction of the balance between osteoblastogenesis and osteoclastogenesis. 1.

Glutamate, GABA and glutathione in adults with persistent post-concussive symptoms

Persistent post-concussive symptoms (PPCS) are debilitating and endure beyond the usual recovery period after mild traumatic brain injury (mTBI). Altered neurotransmission, impaired energy metabolism and oxidative stress have been examined acutely post-injury but have not been explored extensively in those with persistent symptoms. Specifically, the antioxidant glutathione (GSH) and the excitatory and inhibitory metabolites, glutamate (Glu) and γ-aminobutyric acid (GABA), are seldom studied together in the clinical mTBI literature. While Glu can be measured using conventional magnetic resonance spectroscopy (MRS) methods at 3 Tesla, GABA and GSH require the use of advanced MRS methods. Here, we used the recently established Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) to simultaneously measure GSH and GABA and short-echo time point resolved spectroscopy (PRESS) to measure Glu to gain new insight into the pathophysiology of PPCS. Twenty-nine adults with PPCS (mean age: 45.69 years, s.d.: 10.73, 22 females, 7 males) and 29 age- and sex-matched controls (mean age: 43.69 years, s.d.: 11.00) completed magnetic resonance spectroscopy scans with voxels placed in the anterior cingulate and right sensorimotor cortex. Relative to controls, anterior cingulate Glu was significantly reduced in PPCS. Higher anterior cingulate GABA was significantly associated with a higher number of lifetime mTBIs, suggesting GABA may be upregulated with repeated incidence of mTBI. Furthermore, GSH in both regions of interest was positively associated with symptoms of sleepiness and headache burden. Collectively, our findings suggest that the antioxidant defense system is active in participants with PPCS, however this may be at the expense of other glutamatergic functions such as cortical excitation and energy metabolism.

A noise-immune reinforcement learning method for early diagnosis of neuropsychiatric systemic lupus erythematosus.

The neuropsychiatric systemic lupus erythematosus (NPSLE), a severe disease that can damage the heart, liver, kidney, and other vital organs, often involves the central nervous system and even leads to death. Magnetic resonance spectroscopy (MRS) is a brain functional imaging technology that can detect the concentration of metabolites in organs and tissues non-invasively. However, the performance of early diagnosis of NPSLE through conventional MRS analysis is still unsatisfactory. In this paper, we propose a novel method based on genetic algorithm (GA) and multi-agent reinforcement learning (MARL) to improve the performance of the NPSLE diagnosis model. Firstly, the proton magnetic resonance spectroscopy (1H-MRS) data from 23 NPSLE patients and 16 age-matched healthy controls (HC) were standardized before training. Secondly, we adopt MARL by assigning an agent to each feature to select the optimal feature subset. Thirdly, the parameter of SVM is optimized by GA. Our experiment shows that the SVM classifier optimized by feature selection and parameter optimization achieves 94.9% accuracy, 91.3% sensitivity, 100% specificity and 0.87 cross-validation score, which is the best score compared with other state-of-the-art machine learning algorithms. Furthermore, our method is even better than other dimension reduction ones, such as SVM based on principal component analysis (PCA) and variational autoencoder (VAE). By analyzing the metabolites obtained by MRS, we believe that this method can provide a reliable classification result for doctors and can be effectively used for the early diagnosis of this disease.

Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus by Deep Learning Enhanced Magnetic Resonance Spectroscopy

The neuropsychiatric systemic lupus erythematosus (NPSLE) has higher disability and mortality rates, which is one of the main causes of death in systemic lupus erythematosus (SLE) patients. Magnetic resonance spectroscopy (MRS) can detect the changes of metabolites in different intracranial areas in vivo in patients with SLE, so as to provide evidence for the early diagnosis of NPSLE. Different from the conventional single-voxel MRS, which can only screen one brain region with one metabolic change, we simultaneously detect 13 kinds of intracranial metabolic changes in nine brain regions by multivoxel proton MRS (MVS). We use a recursive feature elimination algorithm to select the most related metabolites for better identifying NPSLE. To accurately diagnosis NPSLE by these intracranial metabolites, we train a support vector machine deep stacked network (SVM-DSN) for quantitative analysis of these metabolites. Comparing with the conventional statistic method, which is about 70% of accuracy, the proposed model achieves 97.5% of accuracy for NPSLE diagnosis. We conclude the trained SVM-DSN can effectively analyze the metabolites obtained by multivoxel proton MRS for NPSLE diagnosis, which may help to early diagnosis and intervention of NPSLE, and alleviate the bias of manual screening.

Prospective frequency and motion correction for edited 1H magnetic resonance spectroscopy

The major inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and the dominant antioxidant glutathione (GSH) both play a crucial role in brain functioning and are involved in several neurodegenerative and psychiatric diseases. Magnetic resonance spectroscopy (MRS) is a unique way to measure these neurometabolites non-invasively, but the measurement is highly sensitive to head movements, and especially in specific patient groups, motion stabilization in MRS could be valuable. Conventional MRS is acquired at relatively short echo times (TE), however, for unambiguous detection of GABA and GSH, spectral editing techniques are typically used. These depend on longer TEs and use frequency selective spectral editing pulses to separate the low-intensity peaks of GABA and GSH from overlapping resonances, but results in further increased motion sensitivity. Low-intensity metabolite peaks are usually edited one-by-one, however, simultaneous editing of multiple metabolites can be achieved using a Hadamard scheme, resulting in a substantial reduction in scan time. To investigate and correct for motion sensitivity in both conventional short-TE MRS (PRESS) and edited MRS (HERMES), we implemented a navigator-based prospective motion correction strategy including reacquisition of corrupted data. PRESS and HERMES spectra were acquired without motion, with motion with correction (repeated twice), and with motion without correction. Results indicate that when sufficient retrospective outlier removal is used, no significant differences in concentration and spectral quality were observed between motion conditions, even without prospective correction. HERMES spectral editing data showed to be more sensitive to motion, as significant differences in metabolite estimates and variability of spectral quality measures were observed for tCr, GABA+ and GSH when only retrospective outlier removal was applied. When using both prospective and retrospective correction, spectral quality was improved to almost the level of the no-motion acquisition. No differences in metabolite ratios for GABA and GSH could be observed when using motion correction. In conclusion, edited MRS showed to be more prone to motion artifacts, and prospective motion correction can restore most of the spectral quality in both conventional and edited MRS.

Localized Prediction of Glutamate from Whole-Brain Functional Connectivity of the Pregenual Anterior Cingulate Cortex.

Local measures of neurotransmitters provide crucial insights into neurobiological changes underlying altered functional connectivity in psychiatric disorders. However, noninvasive neuroimaging techniques such as magnetic resonance spectroscopy (MRS) may cover anatomically and functionally distinct areas, such as p32 and p24 of the pregenual anterior cingulate cortex (pgACC). Here, we aimed to overcome this low spatial specificity of MRS by predicting local glutamate and GABA based on functional characteristics and neuroanatomy in a sample of 88 human participants (35 females), using complementary machine learning approaches. Functional connectivity profiles of pgACC area p32 predicted pgACC glutamate better than chance (R2 = 0.324) and explained more variance compared with area p24 using both elastic net and partial least-squares regression. In contrast, GABA could not be robustly predicted. To summarize, machine learning helps exploit the high resolution of fMRI to improve the interpretation of local neurometabolism. Our augmented multimodal imaging analysis can deliver novel insights into neurobiology by using complementary information.SIGNIFICANCE STATEMENT Magnetic resonance spectroscopy (MRS) measures local glutamate and GABA noninvasively. However, conventional MRS requires large voxels compared with fMRI, because of its inherently low signal-to-noise ratio. Consequently, a single MRS voxel may cover areas with distinct cytoarchitecture. In the largest multimodal 7 tesla machine learning study to date, we overcome this limitation by capitalizing on the spatial resolution of fMRI to predict local neurotransmitters in the PFC. Critically, we found that prefrontal glutamate could be robustly and exclusively predicted from the functional connectivity fingerprint of one of two anatomically and functionally defined areas that form the pregenual anterior cingulate cortex. Our approach provides greater spatial specificity on neurotransmitter levels, potentially improving the understanding of altered functional connectivity in mental disorders.

Detection of fatty acid composition of trabecular bone marrow by localized iDQC MRS at 3 T: A pilot study in healthy volunteers

BackgroundAlthough a growing body of research shows that the bone marrow adipose tissue (BMAT) may play an essential role in bone inflammation and energy metabolism, available noninvasive methods for distinguishing different fatty acids in BMAT are still limited, in spite of their potential to provide novel biomarkers for bone related diseases. PurposeTo assess the ability of a localized intermolecular double quantum coherence (iDQC) spectroscopy sequence to resolve more fatty acid peaks than conventional MR spectroscopy (MRS), like polyunsaturated fatty acids (PUFA), from the human BMAT in the presence of trabecular bone; To preliminarily investigate whether the fatty acids composition is different between different regions and groups. ResultsCompared with conventional MRS results, additional four fatty acids peaks were well resolved using the proposed method in human BMAT in the presence of trabecular bone. In addition, a different fat composition was found between distal femur and proximal tibia: fat was more unsaturated (vinyl, *p < 0.01; diallylic, *p < 0.01) in distal femur bone marrow than in proximal tibia, and this higher unsaturation level was caused by PUFA (r = 0.67, diallylic, *p < 0.01). No significant difference in fatty acid composition were found either between left and right legs, or between female and male in the healthy young subjects studied. ConclusionThis study demonstrated that the unsaturated fatty acids information of human BMAT in the presence of trabecular bone can be clearly identified with the localized iDQC at 3 T. The resolved peaks, especially PUFA, may serve as additional diagnostic biomarkers for BMAT related diseases in the future.

Gaucher disease status and treatment assessment: pilot study using magnetic resonance spectroscopy bone marrow fat fractions in pediatric patients

ObjectiveTo assess magnetic resonance spectroscopy (MRS) bone marrow fat fractions' ability to discern between untreated Gaucher disease patients and healthy controls based on assessment of bone marrow infiltration and evaluate response to enzyme replacement therapy (ERT) on serial imaging. MethodsThis retrospective case-controlled study compared conventional MRI and bone marrow MRS findings in six pediatric and young adult Gaucher disease patients with age- and sex-matched controls, examining femoral neck and lumbar spine bone marrow fat fractions and bone marrow burden (BMB) scores. Separate analysis of six patients with serial imaging on ERT was performed with analysis of fat fractions, BMB scores, organ volumes, and serum chitotriosidase. ResultsUntreated patients had significantly lower femoral and lumbar spine fat fractions than controls (0.32 versus 0.67, p = 0.041 and 0.17 versus 0.34, p = 0.041, respectively). Total BMB scores were significantly higher in patients (8.0 versus 3.5, p = 0.015). In patients on ERT with average follow-up of 3.5 years, femoral neck fat fraction was the sole significant predictor of treatment duration (R square: 0.804, p < 0.001) when adjusted for age. Femoral neck fat fraction also correlated with lumbar spine fat fraction, liver volume and chitotriosidase (p < 0.05). MRS test-retest reliability was excellent (Pearson correlations: 0.96, 0.99; p-values <0.001). BMB inter-rater reliability was good overall with an intra-class correlation coefficient of 0.79 for total score, although lumbar spine score reliability was poor at 0.45. ConclusionMRS-derived bone marrow fat fractions appear capable of detecting Gaucher disease severity and monitoring treatment-related changes as a predictor of ERT duration in pediatric and young adult patients.

Potential clinical impact of multiparametric quantitative MR spectroscopy in neurological disorders: A review and analysis.

Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders. A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter. Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases. Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.

High-resolution two-dimensional 1H J-resolved MRS measurements on in vivo samples.

Magnetic resonance spectroscopy (MRS) provides a noninvasive tool for metabolite characterization of in vivo biological samples. Conventional MRS measurements on biological samples generally suffer from field inhomogeneity caused by intrinsic magnetic susceptibility variations inside samples. Compared to one-dimensional MRS, two-dimensional (2D) J-resolved spectroscopy enables resolving J couplings along one of the spectral dimension and benefits to metabolite identification and analyses. Intermolecular double-quantum coherences (iDQC) has been proven to be insensitive to magnetic field inhomogeneity, herein we propose a MRS approach based on iDQC evolution and optimal echo sampling scheme to achieve high-resolution 2D J-resolved measurements on biological samples. The applicability of the proposed method is evaluated with experiments on an ex vivo pig brain tissue and an in vivo rat brain tissue. Compared to conventional MRS method which is sensitive to field inhomogeneity inside investigated biological tissues, the proposed method holds immunity to this field inhomogeneity and the quality of resulting spectra may not be influenced by localized voxel size variation. The signal to noise ratio enhancement of the proposed method benefitting from the optimal echo signal sampling is verified with a solution experiment. The new method provides a promising way for high-resolution MRS measurements on biological samples. In combination with fast acquisition strategy, it may find some promising biomedical applications.

Advanced MRI analysis to detect white matter brain injury in growth restricted newborn lambs.

BackgroundFetal growth restriction (FGR) is a serious pregnancy complication associated with increased risk of adverse neurodevelopment and neuromorbidity. Current imaging techniques, including conventional magnetic resonance imaging (MRI), are not sensitive enough to detect subtle structural abnormalities in the FGR brain. We examined whether advanced MRI analysis techniques have the capacity to detect brain injury (particularly white matter injury) caused by chronic hypoxia-induced fetal growth restriction in newborn preterm lambs.MethodsSurgery was undertaken in twin bearing pregnant ewes at 88–90 days gestation (term = 150 days) to induce FGR in one fetus. At 127 days gestation (~32 weeks human brain development), FGR and control (appropriate for gestational age, AGA) lambs were delivered by caesarean section, intubated and ventilated. Conventional and advanced brain imaging was conducted within the first two hours of life using a 3T MRI scanner. T1-weighted (T1w) and T2-weighted (T2w) structural imaging, magnetic resonance spectroscopy (MRS), and diffusion MRI (dMRI) data were acquired. Diffusion tensor imaging (DTI) modelling and analysis of dMRI data included the following regions of interest (ROIs): subcortical white matter, periventricular white matter, cerebellum, hippocampus, corpus callosum and thalamus. Fixel-based analysis of 3-tissue constrained spherical deconvolution (CSD) of the dMRI data was performed and compared between FGR and AGA lambs. Lambs were euthanised immediately after the scans and brain histology performed in the regions of interest to correlate with imaging.ResultsFGR and AGA lamb (body weight, mean (SD): 2.2(0.5) vs. 3.3(0.3) kg, p = .002) MRI brain scans were analysed. There were no statistically significant differences observed between the groups in conventional T1w, T2w or MRS brain data. Mean, axial and radial diffusivity, and fractional anisotropy indices obtained from DTI modelling also did not show any statistically significant differences between groups in the ROIs. Fixel-based analysis of 3-tissue CSD, however, did reveal a decrease in fibre cross-section (FC, p < .05) but not in fibre density (FD) or combined fibre density and cross-section (FDC) in FGR vs. AGA lamb brains. The specific tracts that showed a decrease in FC were in the regions of the periventricular white matter, hippocampus and cerebellar white matter, and were supported by histological evidence of white matter hypomyelination and disorganisation in corresponding FGR lamb brain regions.ConclusionsThe neuropathology associated with FGR in neonatal preterm lambs is subtle and imaging detection may require advanced MRI and tract-based analysis techniques. Fixel-based analysis of 3-tissue CSD demonstrates that the preterm neonatal FGR brain shows evidence of macrostructural (cross-sectional) deficits in white matter subsequent to altered antenatal development. These findings can inform analysis of similar brain pathology in neonatal infants.

Exogenous Amino Acid-Loaded Nanovehicles: Stepping across Endogenous Magnetic Resonance Spectroscopy.

Magnetic resonance spectroscopy (MRS) allows the assessment of metabolic contents and biochemical information in vivo. It provides essential compositional information in the diagnosis and monitoring of central nervous system (CNS) diseases, especially brain tumors. Conventional MRS is usually confined to endogenous metabolites that may lack specificity for certain disease such as differentiating glioma from other tumor and non-tumorous lesions. Therefore, exogenous MRS contrast agents (CAs) that may improve the sensitivity and specificity of MRS are highly desirable for its clinical use. In this work, a novel MRS CA, β-alanine loaded hollow mesoporous silica nanospheres, with a high biosafety profile and characteristic MRS spectrum was synthesized and investigated. This new CA is further tested to realize the accurate functional MRS diagnosis of brain glioma with high sensitivity. The general approach of synthesizing disease specific CA for MRS may lead to a new era of molecular imaging.

3T proton MR Spectroscopy evaluation of spinal cord lesions.

Objective:The objective of this study was to evaluate intramedullary spinal cord lesions using magnetic resonance spectroscopy and correlate the results with histo-pathological examination (HPE).Materials and Methods:Approval for this study was obtained from our institute ethical committee. Overall, 50 patients were recruited (29 male and 21 female), with a maximum age of 53 years and minimum age of 7 years. The mean age group of the study was 33 years. Standard magnetic resonance imaging (MRI) spine was done on a Siemens Skyra 3Tesla MRI scanner. MR Spectroscopy (MRS) was performed for all patients with intramedullary spinal lesions after getting written consent. It was performed using single-voxel method. The change in the metabolite peak was observed in each case and the results were compared with HPE. These collected data were analyzed using SPSS 16.0 version. Descriptive statistics, frequency analysis, and percentage analysis were used for categorical variables; and for continuous variables, mean and standard deviation were analyzed. McNemar's test was used to find the significance between conventional MRI MRS. In the above statistical tool, the probability value 0.05 is considered as significant level.Results:From our study, we observed that by applying routine MRI sequences alone, we could only detect around 58% of the cases correctly. However, when MRS was done along with the conventional MR imaging, the number of cases detected significantly increased to 84%. By applying McNemar's test and comparing the conventional MRI and MRS with HPE, it was found that statistically significant difference exists with P value of 0.007.Conclusion:MRS of the spinal cord is a promising tool for research and diagnosis because it can provide additional information complementary to other non-invasive imaging methods. It is an emerging tool and adds new biomarker information for characterization of spinal cord tumors, to differentiate benign from malignant lesions and to prevent unnecessary biopsies and surgeries.