Multi voxel magnetic resonance spectroscopic imaging (MRSI) is an important imaging tool that combines imaging and spectroscopic techniques. MRSI of the human brain has been beneficially applied to different clinical applications in neurology, particularly in neurooncology but also in multiple sclerosis, stroke and epilepsy. However, a major challenge in conventional MRSI is the longer acquisition time required for adequate signal to be collected. Fast MRSI of the brain in vivo is an alternative approach to reduce scanning time and make MRSI more clinically suitable.Fast MRSI can be categorised into spiral, echo-planar, parallel and turbo imaging techniques, each with its own strengths. After a brief introduction on the basics of non-invasive examination (1H-MRS) and localization techniques principles, different fast MRSI techniques will be discussed from their initial development to the recent innovations with particular emphasis on their capacity to record neurochemical changes in the brain in a variety of pathologies.The clinical applications of whole brain fast spectroscopic techniques, can assist in the assessment of neurochemical changes in the human brain and help in understanding the roles they play in disease. To give a good example of the utilities of these techniques in clinical context, MRSI application in multiple sclerosis was chosen. The available up to date and relevant literature is discussed and an outline of future research is presented.

Background Due to the histological heterogeneity of the central gland, accurate detection of central gland prostate cancer remains a challenge. Purpose To evaluate the efficacy of in vivo 3D 1H MR spectroscopic imaging (3D 1H MRSI) with a semi‐localized adiabatic selective refocusing (sLASER) sequence and gradient‐modulated offset‐independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low‐ vs. high‐risk cancer, 3) low‐ vs. intermediate‐risk cancer, and 4) intermediate‐ vs. high‐risk cancer voxels. Study Type Prospective. Subjects Thirty‐six patients with biopsy‐proven central gland prostate cancer. Field Strength/Sequence 3T MRI / 3D 1H MRSI using GOIA‐sLASER. Assessment Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and 1H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing. Statistical Tests Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset. Results High‐quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low‐ vs. high‐risk cancer and low‐ vs. intermediate‐risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate‐ vs. high‐risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%. Data Conclusion The GOIA‐sLASER sequence with an external phased‐array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low‐ vs. high‐risk cancer, and low‐ vs. intermediate‐risk cancer. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1926–1936.

Background Two‐dimensional localized correlation spectroscopy (2D L‐COSY) is a research tool that has been applied to evaluate in vivo metabolic activity in many neurological and oncological disorders. Circadian mediators such as brain temperature, hydration, and osmotic regulation have been claimed to change metabolic profiles. Purpose To evaluate the diurnal variability of neuro‐metabolites with 2D L‐COSY in healthy subjects using a 3 T scanner. Study Type Crossover. Population/Phantom Ten healthy subjects and magnetic resonance spectroscopy‐high definition (MRS‐HD) sphere or “Braino.” Field Strength/Sequence: 3 T/2D L‐COSY MRS. Assessment In vivo 2D L‐COSY measurements were performed on ten healthy subjects (5 M/5F, mean age 36.1 ± 7.7 years) repeatedly at three timepoints (0700, 1200, and 1700) on the same day. in vitro evaluations were performed in a similar fashion as in vivo on Braino containing selected brain metabolites at physiological concentrations and pH. 2D L‐COSY was acquired from a 27 cm3 voxel located in the posterior cingulate cortex. A total of 75 resonances were included in the analysis and spectral peak volumes were normalized to creatine. Statistical Test One‐way repeated measured analysis of variance with Bonferroni post‐hoc adjustment using SPSS software. Results In vitro data showed no statistically significant differences between different scans (P > 0.12). in vivo results showed statistically significant diurnal variations (P ≤ 0.05, F > 3.88) for 22 resonances. Bonferroni post‐hoc testing showed there was statistically significant increases in metabolite ratios between 0700 and 1700 and these include different moieties of N‐acetylaspartate, creatine, choline, myo‐inositol, lipids, fucose, glutathione, and homocarnosine. Data Conclusion 2D L‐COSY can detect diurnal physiological variability in neuro‐metabolite levels. Thus, time of the day should be considered when planning MRS studies to avoid confounding results. Level of Evidence: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:592–601.

Background: We have applied in vivo two-dimensional (2D) localized correlation spectroscopy (2D L-COSY), in treated relapsing relapsing-remitting multiple sclerosis (RRMS) to identify novel biomarkers in normal-appearing brain parenchyma. Methods: 2D L-COSY magnetic resonance spectroscopy (MRS) spectra were prospectively acquired from the posterior cingulate cortex (PCC) in 45 stable RRMS patients undergoing treatment with Fingolimod, and 40 age and sex-matched healthy control (HC) participants. Average metabolite ratios and clinical symptoms including, disability, cognition, fatigue, and mental health parameters were measured, and compared using parametric and nonparametric tests. Whole brain volume and MRS voxel morphometry were evaluated using SIENAX and the SPM LST toolbox. Results: Despite the mean whole brain lesion volume being low in this RRMS group (6.8 ml) a significant reduction in PCC metabolite to tCr ratios were identified for multiple N-acetylaspartate (NAA) signatures, gamma-aminobutyric acid (GABA), glutamine and glutamate (Glx), threonine, and isoleucine/lipid. Of the clinical symptoms measured, visuospatial function, attention, and memory were correlated with NAA signatures, Glx, and isoleucine/lipid in the brain. Conclusions: 2D L-COSY has the potential to detect metabolic alterations in the normal-appearing MS brain. Despite examining only a localised region, we could detect metabolic variability associated with symptoms.