Dorsolateral prefrontal cortex N-acetylaspartate/total creatine (NAA/tCr) loss in male recreational cannabis users.

BACKGROUND: Cannabinoids present neurotoxic and neuroprotective properties in in vitro studies, inconsistent alterations in human neuroimaging studies, neuropsychological deficits, and an increased risk for psychotic episodes. METHODS: Proton magnetic resonance spectroscopy ((1)H-MRS), neuropsychological testing, and hair analysis for cannabinoids was performed in 13 male nontreatment-seeking recreational cannabis users and 13 male control subjects. RESULTS: A significantly diminished N-acetylaspartate/total creatine (NAA/tCr) ratio in the dorsolateral prefrontal cortex (DLPFC) was observed in cannabis users (p = .0003). The NAA/tCr in the putamen/globus pallidum region correlated significantly with cannabidiol (R(2) = .66, p = .004). Results of the Wisconsin Card Sorting test, Trail making Test, and D2 test for attention were influenced by cannabinoids. CONCLUSIONS: Chronic recreational cannabis use is associated with an indication of diminished neuronal and axonal integrity in the DLPFC in this study. As chronic cannabis use is a risk factor for psychosis, these results are interesting because diminished NAA/tCr ratios in the DLPFC and neuropsychological deficits were also reported in schizophrenia. The strong positive correlation of NAA/tCr and cannabidiol in the putamen/globus pallidum is in line with neuroprotective properties of cannabidiol, which were also observed in in vitro model studies of Parkinson's disease.     

Fast MR Spectroscopic Imaging Technologies and Data Reconstruction Methods

MRSI plays a more and more important role in clinical application. In this paper, we compare several fast MRSI technologies and data reconstruction methods. For the conventional phase encoding MRSI, the data reconstruction using FFT is simple. But the data acquisition is very time consuming and thus prohibitive in clinical settings. Up to now, the MRSI technologies based on echo-planar, spiral trajectories and sensitivity encoding are the fastest in data acquisition, but their data reconstruction is complex. EPSI reconstruction uses shift of odd and even echoes. Spiral SI uses gridding FFT. SENSE-SI, a new approach to reducing the acquisition time, uses the distinct spatial sensitivities of the individual coil elements to recover the missing encoding information. These improvements in data acquisition and image reconstruction provide a potential value of metabolic imaging as a clinical tool.     

Stratification of the aggressiveness of prostate cancer using pre‐biopsy multiparametric MRI (mpMRI)

Risk stratification, based on the Gleason score (GS) of a prostate biopsy, is an important decision‐making tool in prostate cancer management. As low‐grade disease may not need active intervention, the ability to identify aggressive cancers on imaging could limit the need for prostate biopsies. We assessed the ability of multiparametric MRI (mpMRI) in pre‐biopsy risk stratification of men with prostate cancer. One hundred and twenty men suspected to have prostate cancer underwent mpMRI (diffusion MRI and MR spectroscopic imaging) prior to biopsy. Twenty‐six had cancer and were stratified into three groups based on GS: low grade (GS ≤ 6), intermediate grade (GS = 7) and high grade (GS ≥ 8). A total of 910 regions of interest (ROIs) from the peripheral zone (PZ, range 25–45) were analyzed from these 26 patients. The metabolite ratio [citrate/(choline + creatine)] and apparent diffusion coefficient (ADC) of voxels were calculated for the PZ regions corresponding to the biopsy cores and compared with histology. The median metabolite ratios for low‐grade, intermediate‐grade and high‐grade cancer were 0.29 (range: 0.16, 0.61), 0.17 (range: 0.13, 0.32) and 0.13 (range: 0.05, 0.23), respectively (p = 0.004). The corresponding mean ADCs (×10^–3 mm²/s) for low‐grade, intermediate‐grade and high‐grade cancer were 0.99 ± 0.08, 0.86 ± 0.11 and 0.69 ± 0.12, respectively (p < 0.0001). The combined ADC and metabolite ratio model showed strong discriminatory ability to differentiate subjects with GS ≤ 6 from subjects with GS ≥ 7 with an area under the curve of 94%. These data indicate that pre‐biopsy mpMRI may stratify PCa aggressiveness noninvasively. As the recent literature data suggest that men with GS ≤ 6 cancer may not need radical therapy, our data may help limit the need for biopsy and allow informed decision making for clinical intervention. Copyright © 2015 John Wiley & Sons, Ltd.     

Elliptical localization with pulsed second‐order fields (ECLIPSE) for robust lipid suppression in proton MRSI

Proton MRSI has great clinical potential for metabolic mapping of the healthy and pathological human brain. Unfortunately, the promise has not yet been fully achieved due to numerous technical challenges related to insufficient spectral quality caused by magnetic field inhomogeneity, insufficient RF transmit power and incomplete lipid suppression. Here a robust, novel method for lipid suppression in ¹H MRSI is presented. The method is based on 2D spatial localization of an elliptical region of interest using pulsed second‐order spherical harmonic (SH) magnetic fields. A dedicated, high‐amplitude second‐order SH gradient setup was designed and constructed, containing coils to generate Z2, X2Y2 and XY magnetic fields. Simulations and phantom MRI results are used to demonstrate the principles of the method and illustrate the manifestation of chemical shift displacement. ¹H MRSI on human brain in vivo demonstrates high quality, robust suppression of extracranial lipids. The method allows a wide range of inner or outer volume selection or suppression and should find application in MRSI, reduced‐field‐of‐view MRI and single‐volume MRS.     

Whole‐body radiofrequency coil for 31P MRSI at 7 T

Widespread use of ultrahigh‐field ³¹P MRSI in clinical studies is hindered by the limited field of view and non‐uniform radiofrequency (RF) field obtained from surface transceivers. The non‐uniform RF field necessitates the use of high specific absorption rate (SAR)‐demanding adiabatic RF pulses, limiting the signal‐to‐noise ratio (SNR) per unit of time. Here, we demonstrate the feasibility of using a body‐sized volume RF coil at 7 T, which enables uniform excitation and ultrafast power calibration by pick‐up probes. The performance of the body coil is examined by bench tests, and phantom and in vivo measurements in a 7‐T MRI scanner. The accuracy of power calibration with pick‐up probes is analyzed at a clinical 3‐T MR system with a close to identical ¹H body coil integrated at the MR system. Finally, we demonstrate high‐quality three‐dimensional ³¹P MRSI of the human body at 7 T within 5 min of data acquisition that includes RF power calibration. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatially matched in vivo and ex vivo MR metabolic profiles of prostate cancer – investigation of a correlation with Gleason score

MR metabolic profiling of the prostate is promising as an additional diagnostic approach to separate indolent from aggressive prostate cancer. The objective of this study was to assess the relationship between the Gleason score and the metabolic biomarker (choline + creatine + spermine)/citrate (CCS/C) measured by ex vivo high‐resolution magic angle spinning MRS (HR‐MAS MRS) and in vivo MRSI, and to evaluate the correlation between in vivo‐ and ex vivo‐measured metabolite ratios from spatially matched prostate regions. Patients (n = 13) underwent in vivo MRSI prior to radical prostatectomy. A prostate tissue slice was snap‐frozen shortly after surgery and the locations of tissue samples (n = 40) collected for ex vivo HR‐MAS were matched to in vivo MRSI voxels (n = 40). In vivo MRSI was performed on a 3T clinical MR system and ex vivo HR‐MAS on a 14.1T magnet. Relative metabolite concentrations were calculated by LCModel fitting of in vivo spectra and by peak integration of ex vivo spectra. Spearman's rank correlations (ρ) between CCS/C from in vivo and ex vivo MR spectra, and with their corresponding Gleason score, were calculated. There was a strong positive correlation between the Gleason score and CCS/C measured both in vivo and ex vivo (ρ = 0.77 and ρ = 0.69, respectively; p < 0.001), and between in vivo and ex vivo metabolite ratios from spatially matched regions (ρ = 0.67, p < 0.001). Our data indicate that MR metabolic profiling is a potentially useful tool for the assessment of cancer aggressiveness. Moreover, the good correlation between in vivo‐ and ex vivo‐measured CCS/C demonstrates that our method is able to bridge MRSI and HR‐MAS molecular analysis. Copyright © 2012 John Wiley & Sons, Ltd.     

Extraction of artefactual MRS patterns from a large database using non-negative matrix factorization

Despite the success of automated pattern recognition methods in problems of human brain tumor diagnostic classification, limited attention has been paid to the issue of automated data quality assessment in the field of MRS for neuro-oncology. Beyond some early attempts to address this issue, the current standard in practice is MRS quality control through human (expert-based) assessment. One aspect of automatic quality control is the problem of detecting artefacts in MRS data. Artefacts, whose variety has already been reviewed in some detail and some of which may even escape human quality control, have a negative influence in pattern recognition methods attempting to assist tumor characterization. The automatic detection of MRS artefacts should be beneficial for radiology as it guarantees more reliable tumor characterizations, as well as the development of more robust pattern recognition-based tumor classifiers and more trustable MRS data processing and analysis pipelines. Feature extraction methods have previously been used to help distinguishing between good and bad quality spectra to apply subsequent supervised pattern recognition techniques. In this study, we apply feature extraction differently and use a variant of a method for blind source separation, namely Convex Non-Negative Matrix Factorization, to unveil MRS signal sources in a completely unsupervised way. We hypothesize that, while most sources will correspond to the different tumor patterns, some of them will reflect signal artefacts. The experimental work reported in this paper, analyzing a combined short and long echo time ¹H-MRS database of more than 2000 spectra acquired at 1.5T and corresponding to different tumor types and other anomalous masses, provides a first proof of concept that points to the possible validity of this approach.