Browsing by Author "Ma, Ruoyun"

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    Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites
    (Elsevier, 2019-05) Mikkelsen, Mark; Rimbault, Daniel L.; Barker, Peter B.; Bhattacharyya, Pallab K.; Brix, Maiken K.; Buur, Pieter F.; Cecil, Kim M.; Chan, Kimberly L.; Chen, David Y.-T.; Craven, Alexander R.; Cuypers, Koen; Dacko, Michael; Duncan, Niall W.; Dydak, Ulrike; Edmondson, David A.; Ende, Gabriele; Ersland, Lars; Forbes, Megan A.; Gao, Fei; Greenhouse, Ian; Harris, Ashley D.; He, Naying; Heba, Stefanie; Hoggard, Nigel; Hsu, Tun-Wei; Jansen, Jacobus F. A.; Kangarlu, Alayar; Lange, Thomas; Lebel, R. Marc; Li, Yan; Lin, Chien-Yuan E.; Liou, Jy-Kang; Lirng, Jiing-Feng; Liu, Feng; Long, Joanna R.; Ma, Ruoyun; Maes, Celine; Moreno-Ortega, Marta; Murray, Scott O.; Noah, Sean; Noeske, Ralph; Noseworthy, Michael D.; Oeltzschner, Georg; Porges, Eric C.; Prisciandaro, James J.; Puts, Nicolaas A.; Roberts, Timothy P. L.; Sack, Markus; Sailasuta, Napapon; Saleh, Muhammad G.; Schallmo, Michael-Paul; Simard, Nicholas; Stoffers, Diederick; Swinnen, Stephan P.; Tegenthoff, Martin; Truong, Peter; Wang, Guangbin; Wilkinson, Iain D.; Wittsack, Hans-Jörg; Woods, Adam J.; Xu, Hongmin; Yan, Fuhua; Zhang, Chencheng; Zipunnikov, Vadim; Zöllner, Helge J.; Edden, Richard A. E.; Radiology and Imaging Sciences, School of Medicine
    Accurate and reliable quantification of brain metabolites measured in vivo using 1H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T1-weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels.
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    Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites
    (Radiological Society of North America, 2020-04) Považan, Michal; Mikkelsen, Mark; Berrington, Adam; Bhattacharyya, Pallab K.; Brix, Maiken K.; Buur, Pieter F.; Cecil, Kim M.; Chan, Kimberly L.; Chen, David Y.T.; Craven, Alexander R.; Cuypers, Koen; Dacko, Michael; Duncan, Niall W.; Dydak, Ulrike; Edmondson, David A.; Ende, Gabriele; Ersland, Lars; Forbes, Megan A.; Gao, Fei; Greenhouse, Ian; Harris, Ashley D.; He, Naying; Heba, Stefanie; Hoggard, Nigel; Hsu, Tun-Wei; Jansen, Jacobus F.A.; Kangarlu, Alayar; Lange, Thomas; Lebel, R. Marc; Li, Yan; Lin, Chien-Yuan E.; Liou, Jy-Kang; Lirng, Jiing-Feng; Liu, Feng; Long, Joanna R.; Ma, Ruoyun; Maes, Celine; Moreno-Ortega, Marta; Murray, Scott O.; Noah, Sean; Noeske, Ralph; Noseworthy, Michael D.; Oeltzschner, Georg; Porges, Eric C.; Prisciandaro, James J.; Puts, Nicolaas A.J.; Roberts, Timothy P.L.; Sack, Markus; Sailasuta, Napapon; Saleh, Muhammad G.; Schallmo, Michael-Paul; Simard, Nicholas; Stoffers, Diederick; Swinnen, Stephan P.; Tegenthoff, Martin; Truong, Peter; Wang, Guangbin; Wilkinson, Iain D.; Wittsack, Hans-Jörg; Woods, Adam J.; Xu, Hongmin; Yan, Fuhua; Zhang, Chencheng; Zipunnikov, Vadim; Zöllner, Helge J.; Edden, Richard A.E.; Barker, Peter B.; Radiology and Imaging Sciences, School of Medicine
    The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols.
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    Effect of Primidone on Dentate Nucleus γ-Aminobutyric Acid Concentration in Patients With Essential Tremor
    (Wolters Kluwer, 2016-01) Louis, Elan D.; Hernandez, Nora; Dyke, Jonathan P.; Ma, Ruoyun; Dydak, Ulrike; Department of Radiology and Imaging Sciences, IU School of Medicine
    OBJECTIVES: It is not known whether current use of the medication primidone affects brain γ-aminobutyric acid (GABA) concentrations. This is an important potential confound in studies of the pathophysiology of essential tremor (ET), one of the most common neurological diseases. We compared GABA concentrations in the dentate nucleus in 6 ET patients taking primidone versus 26 ET patients not taking primidone. METHODS: (1)H magnetic resonance spectroscopy was performed using a 3.0-T Siemens Tim Trio scanner. The MEGA-PRESS J-editing sequence was used for GABA detection in 2 cerebellar volumes of interest (left and right) that included the dentate nucleus. RESULTS: The right dentate GABA concentration was similar in the 2 groups (2.21 ± 0.46 [on primidone] vs 1.93 ± 0.39 [not on primidone], P = 0.15), as was the left dentate GABA concentration (1.61 ± 0.35 [on primidone] vs 1.67 ± 0.34 [not on primidone], P = 0.72). The daily primidone dose was not associated with either right or left dentate GABA concentrations (P = 0.89 and 0.76, respectively). CONCLUSIONS: We did not find a difference in dentate GABA concentrations between 6 ET patients taking daily primidone and 26 ET patients not taking primidone. Furthermore, there was no association between daily primidone dose and dentate GABA concentration. These data suggest that it is not necessary to exclude ET patients on primidone from magnetic resonance spectroscopy studies of dentate GABA concentration, and if assessment of these concentrations was to be developed as a biomarker for ET, primidone usage would not confound interpretation of the results.
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    Reproducibility and effect of tissue composition on cerebellar GABA MRS in an elderly population.
    (Wiley, 2015-10) Long, Zaiyang; Dyke, Jonathan P.; Ma, Ruoyun; Huang, Chaorui C.; Louis, Elan D.; Dydak, Ulrike; Department of Radiology and Imaging Sciences, IU School of Medicine
    Magnetic resonance spectroscopy (MRS) provides a valuable tool to non-invasively detect brain gamma-amino butyric acid (GABA) in vivo. GABAergic dysfunction has been observed in the aging cerebellum. Studying cerebellar GABA changes is of considerable interest in understanding certain age-related motor disorders. However, little is known about the reproducibility of GABA MRS in an aged population. Therefore, this study aimed to explore the feasibility and reproducibility of GABA MRS in the aged cerebellum at 3.0 Tesla and to examine the effect of differing tissue composition on GABA measurements. MRI and 1H MRS exams were performed on 10 healthy elderly volunteers (mean age 75.2 years ± 6.5 years) using a 3.0 Tesla Siemens Tim Trio scanner. Among them, 5 subjects were scanned twice to assess short-term reproducibility. The MEGA-PRESS J-editing sequence was used for GABA detection in two volumes of interest (VOIs) in left and right cerebellar dentate. MRS data processing and quantification were performed with LCModel 6.3-0L using two separate basis sets, generated from density matrix simulations using published values for chemical shifts and
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    Striatal and thalamic GABA level concentrations play differential roles for the modulation of response selection processes by proprioceptive information.
    (Elsevier, 2015-10-15) Dharmadhikari, Shalmali; Ma, Ruoyun; Yeh, Chien-Lin; Stock, Ann-Kathrin; Snyder, Sandy; Zauber, S. Elizabeth; Dydak, Ulrike; Beste, Christian; Department of Radiology and Imaging Sciences, IU School of Medicine
    The selection of appropriate responses is a complex endeavor requiring the integration of many different sources of information in fronto-striatal-thalamic circuits. An often neglected but relevant piece of information is provided by proprioceptive inputs about the current position of our limbs. This study examines the importance of striatal and thalamic GABA levels in these processes using GABA-edited magnetic resonance spectroscopy (GABAMRS) and a Simon task featuring proprioception-induced interference in healthy subjects. As a possible model of deficits in the processing of proprioceptive information, we also included Parkinson's disease (PD) patients in this study.The results show that proprioceptive information about unusual postures complicates response selection processes in controls, but not in PD patients. The well-known deficits of PD patients in processing proprioceptive information can turn into a benefit when altered proprioceptive information would normally complicate response selection processes. Striatal and thalamic GABA levels play dissociable roles in the modulation of response selection processes by proprioceptive information: Striatal GABA levels seem to be important for the general speed of responding, most likely because striatal GABA promotes response selection. In contrast, the modulation of response conflict by proprioceptive information is closely related to thalamic GABA concentrations with higher concentration being related to a smaller response conflict effect. The most likely explanation for this finding is that the thalamus is involved in the integration of sensorimotor, attentional, and cognitive information for the purpose of response formation. Yet, this effect in the thalamus vanishes when controls and PD patients were analyzed separately.