Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis was first described in 2005 in association with ovarian teratoma. The diagnostic workup of this common autoimmune encephalitis includes cerebrospinal fluid analysis, electroencephalography, magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (FDG-PET). In addition to standard diagnostics, we performed metabolic investigations using proton magnet resonance spectroscopy (1H-MRS). We describe the case of a non-limbic anti-NMDAR encephalitis with a long course of disease (21 months). Laboratory diagnostics showed antibodies against NMDAR; an MRI revealed unspecific findings. 1H-MRS indicated a hypoglutamatergic state in the left prefrontal cortex associated with a left hemispherical hypometabolism on FDG-PET. Despite the long course of disease, immunosuppressive therapy with methylprednisolone and azathioprine led to almost complete remission of clinical symptoms. Clinical improvement developed in parallel with remarkable normalization of cerebral glucose metabolism on FDG-PET. This case of long-lasting extra-limbic anti-NMDAR encephalitis is of high clinical relevance. First, it illustrates that a very good outcome is possible even if adequate therapy is started only 21 months after the onset of severe symptoms. Second, it provides valuable insights into the pathophysiology of such anti-NMDAR encephalitis; these insights prove that anti-NMDAR encephalitis is linked not only to hyperglutamatergic signals but also to hypoglutamatergic states. These findings, contradictory at first glance, can be integrated within the model of excitatory/inhibitory imbalance and local area network inhibition.

Autism spectrum disorder (ASD) is a neurodevelopmental disease characterized by difficulties in social communication, unusually restricted, repetitive behavior and interests, and specific abnormalities in language and perception. The precise etiology of ASD is still unknown and probably heterogeneous. In a subgroup of patients, toxic environmental exposure might lead to an imbalance between oxidative stress and anti-oxidant systems. Previous serum and postmortem studies measuring levels of glutathione (GSH), the main cellular free radical scavenger in the brain, have supported the hypothesis that this compound might play a role in the pathophysiology of autism. Using the method of single-voxel proton magnetic resonance spectroscopy (MRS), we analyzed the GSH signal in the dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (DLPFC) of 24 ASD patients with normal or above average IQs and 18 matched control subjects. We hypothesized that we would find decreased GSH concentrations in both regions. We did not find overall group differences in neurometabolites including GSH, neither in the dorsal ACC (Wilks’ lambda test; p = 0.429) nor in the DLPFC (p = 0.288). In the dACC, we found a trend for decreased GSH signals in ASD patients (p = 0.076). We were unable to confirm our working hypothesis regarding decreased GSH concentrations in the ASD group. Further studies combining MRS, serum, and cerebrospinal fluid measurements of GSH metabolism including other regions of interest or even whole brain spectroscopy are needed.

Purpose: To evaluate the impact of heating‐induced frequency drifts on single‐voxel spectroscopy and to demonstrate correction strategies based on the interleaved reference scan technique.Materials and Methods: Frequency drifts induced by gradient heating are assessed for two clinical 3 Tesla (T) whole body MR systems. The interleaved reference scan (IRS) method is used for correcting these frequency drifts in 1H spectra in vitro and in vivo. For severely drift‐affected spectroscopy experiments, a feedback‐based version of the IRS sequence is proposed, which adds the functionality of a frequency lock to prevent a degradation of the water suppression.Results: It is shown that the line widths of the spectral resonances can be largely reduced with the interleaved reference scan method, resulting in considerably improved peak resolution and signal‐to‐noise ratio. The feedback‐based IRS method additionally allows for stable water suppression, even in the presence of very strong frequency drifts.Conclusion: If spectroscopy scans are combined with imaging scans with a high gradient duty cycle such as diffusion‐weighted imaging or functional MRI, a drift correction with IRS can considerably improve the validity of data analysis in research studies. J. Magn. Reson. Imaging 2011;33:748–754.

Motion‐induced artifacts are much harder to recognize in magnetic resonance spectroscopic imaging than in imaging experiments and can therefore lead to erroneous interpretation. A method for prospective motion correction based on an optical tracking system has recently been proposed and has already been successfully applied to single voxel spectroscopy. In this work, the utility of prospective motion correction in combination with retrospective phase correction is evaluated for spectroscopic imaging in the human brain. Retrospective phase correction, based on the interleaved reference scan method, is used to correct for motion‐induced frequency shifts and ensure correct phasing of the spectra across the whole spectroscopic imaging slice. It is demonstrated that the presented correction methodology can reduce motion‐induced degradation of spectroscopic imaging data. Magn Reson Med, 2011.

This review presents the changes that the imaging of articular cartilage has undergone throughout the last decades. It highlights that the expectation is no longer to image the structure and associated functions of articular cartilage but, instead, to devise methods for generating non-invasive, function-depicting images with quantitative information that is useful for detecting the early, pre-clinical stage of diseases such as primary or post-traumatic osteoarthritis (OA/PTOA). In this context, this review summarizes (a) the structure and function of articular cartilage as a molecular imaging target, (b) quantitative MRI for non-invasive assessment of articular cartilage composition, microstructure, and function with the current state of medical diagnostic imaging, (c), non-destructive imaging methods, (c) non-destructive quantitative articular cartilage live-imaging methods, (d) artificial intelligence (AI) classification of degeneration and prediction of OA progression, and (e) our contribution to this field, which is an AI-supported, non-destructive quantitative optical biopsy for early disease detection that operates on a digital tissue architectural fingerprint. Collectively, this review shows that articular cartilage imaging has undergone profound changes in the purpose and expectations for which cartilage imaging is used; the image is becoming an AI-usable biomarker with non-invasive quantitative functional information. This may aid in the development of translational diagnostic applications and preventive or early therapeutic interventions that are yet beyond our reach.