Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

Purpose: To evaluate the performance of novel spiral MRSI and tissue segmentation pipeline of the brain, to investigate neurometabolic changes in normal-appearing white matter (NAWM) and white matter lesions (WML) of stable relapsing remitting multiple sclerosis (RRMS) compared to healthy controls (HCs). Methods: Spiral 3D MRSI using LASER-GOIA-W [16,4] was undertaken on 16 RRMS patients and 9 HCs, to acquire MRSI data from a large volume of interest (VOI) 320 cm(3) and analyzed using LCModel. MRSI data and voxel tissue segmentation were compared between the two cohorts using t-tests. Support vector machine (SVM) was used to classify tissue types and assessed by accuracy, sensitivity and specificity. Results: Compared to HCs, RRMS demonstrated a statistically significant reduction in all mean brain tissues and increase in CSF volume. Within VOI, WM decreased (-10%) and CSF increased (41%) in RRMS compared to HCs (p < 0.001). MRSI revealed that total creatine (tCr) ratios of N-acetylaspartate and glutamate+glutamine in WML were significantly lower than NAWM-MS (-9%, -8%) and HCs (-14%, -10%), respectively. Myo-inositol/tCr in WML was significantly higher than NAWM-MS (14%) and HCs (10%). SVM of MRSI yielded accuracy, sensitivity and specificity of 86%, 95%, and 70%, respectively for HCs vs WML, which were higher than HC vs NAWM and WML vs NAWM models. Conclusion: This study demonstrates the benefit of MRSI in evaluating MS neurometabolic changes in NAWM. SVM of MRSI data in the MS brain may be suited for clinical monitoring and progression of MS patients. Longitudinal MRSI studies are warranted.

The original article contained errors in the Fig. 1 caption. The incorrect sentence, “The region highlighted by the white box is expanded in Fig. 3” was corrected to, “The region highlighted by the white box is expanded in Fig. 2.” This has been corrected in the HTML and PDF of the article.

Posttraumatic stress disorder (PTSD) is a trauma and stressor-related disorder that results in complex somatic, cognitive, affective and behavioural effects, after exposure to traumatic event(s). Conventional imaging (T1 and T2 weighted magnetic resonance imaging) has little to offer in the way of diagnosis of mental health conditions such as PTSD and there is currently no objective diagnostic test available. Magnetic resonance spectroscopy (MRS) allows for non-invasive measurement of metabolites and neurochemicals in the brain using a conventional MRI scanner and offers the potential to predict, diagnose and monitor PTSD. This systematic review summarises the results of 24 MRS studies, performed between 1998 and 2017, to measure neurochemical differences, occurring as a consequence of PTSD. The most consistent finding in subjects with PTSD is lower N-acetylaspartate levels in the hippocampus and anterior cingulate cortex, with and without atrophic change. More recent studies, using more advanced techniques and modern hardware, have shown evidence of glutamatergic dysfunction and differences in gamma-aminobutyric acid levels in the brain of patients with PTSD. Conflicting results have been reported in choline-containing metabolites and there is emerging evidence of glutathione being affected. Myo-inositol and creatine are unchanged in the majority of studies.

Partial volume effects have the potential to cause inaccuracies when quantifying metabolites using proton magnetic resonance spectroscopy (MRS). In order to correct for cerebrospinal fluid content, a spectroscopic voxel needs to be segmented according to different tissue contents. This article aims to detail how automated partial volume segmentation can be undertaken and provides a software framework for researchers to develop their own tools. While many studies have detailed the impact of partial volume correction on proton magnetic resonance spectroscopy quantification, there is a paucity of literature explaining how voxel segmentation can be achieved using freely available neuroimaging packages.

Women carrying the BRCA1 and BRCA2 gene mutations exhibited lipid and metabolite profiles consistent with very early deregulation recorded earlier in cancer cell models. The deregulation was different for BRCA1 and BRCA2. Here we report a longitudinal study where these same women are monitored every six month using the L-COSY MRS method and every 12 month with contrast enhanced MRI. For most women in the study the biomarkers remained relatively stable over time. Of the 6 BRCA1 and 10 BRCA2 patients examined, one BRCA1 patient and one BRCA2 patient showed further deregulation

A growing body of literature has indicated that fucose‐α(1–2)‐galactose sugars are implicated in the molecular mechanisms that underlie neuronal development, learning and memory in the human brain. An understanding of the in vivo roles played by these terminal fucose residues has been hampered by the lack of technology to non‐invasively monitor their levels in the human brain. We have implemented in vivo two‐dimensional MRS technology to examine the human brain in a 3‐T clinical MR scanner, and report that six fucose‐α(1–2)‐galactose residues and free α‐fucose are available for inspection. Fucose‐α(1–3)‐galactose residues cannot yet be assigned using this technology as they resonate under the water resonance. This new application offers an unprecedented insight into the molecular mechanisms by which fucosylated sugars contribute to neuronal processes and how they alter during development, ageing and disease. Copyright © 2014 John Wiley & Sons, Ltd.

In vivo 2D L-COSY identifies premalignant changes in women at high risk of developing breast cancer that are not seen by routine imaging, and allows women to be identified as MR spectroscopy Low Risk or MR spectroscopy High Risk according to changes recorded. Changes in the MR spectroscopy High Risk group include deregulation of lipid pathways and increased levels of metabolites. If these changes are confirmed in larger populations, it is possible that this information will allow women at increased clinical risk for breast cancer an objective means to monitor changes that may be taking place in their breast tissue.