Helge J. Zöllner

Are you afraid of loosing your MRS data during a MRS application study? Check out our new preprint on bioRxiv. Here we present a continuous automated MRS analysis workflow. This workflow integrates automated data sorting, conversion to NIfTI-MRS, analysis in Osprey, and automated reproting of the results. [Read More]

Over the last year we have been working on a new generalized linear-combination modeling in Osprey. Generalized means that every modeling decision can be controlled by the user through a single interface json file. The implementation also allows for modeling of arbitrary 2D experiments. [Read More]

Happy to share my new research on J-difference GABA-edited MRS in HE published in Metabolic Brain Disease. Here we applied GABA-edited MRS to explore metabolic alterations in the cerebello-thalamo-cortical loop in patients with hepatic encephalopthy. GABA+ levels were significanly altered in cerebellum and motor cortex and strongly correlated with critical flicker frequency, motor performance scores and blood ammonia levels. [Read More]

Do we have to rethink our statistical analysis approaches for 1H-MRS studies? This work by James Prisciandaro suggests that more than half of the total variability in metabolite estimates are explained by a single common factor. The Big PRESS dataset was processed in Osprey and metabolite estimation was performed in LCModel. [Read More]

New work in NeuroImage from my colleague Tao Gong about the neurometabolic timecourse of healthy aging measured with short TE MRS. This large cross-sectional cohort showed significant correlations for tCho, tCr, mI, and sI in CSO and for NAAG, tCho, tCr, and Gln in PCC. The data was analyzed in Osprey. [Read More]