| 16:00 | | IntroductionMalgorzata Marjanska University of Minnesota, United States |
| 16:12 | 0252.
 | Metabolite-cycling at 14.1T: sequence implementation and initial explorations using SPECIAL and diffusion-weighted SPECIAL Jessie Mosso1,2, André Döring1,2, Roland Kreis3,4, Cristina Cudalbu1,2, and Bernard Lanz1,2
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, 2Animal Imaging and Technology, EPFL, Lausanne, Switzerland, 3Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, 4Translational Imaging Center, sitem-insel, Bern, Switzerland Keywords: Spectroscopy, Brain, MRS, metabolite-cycling, sequence development, SPECIAL, diffusion, DW-MRS, downfield Motivation: Water suppression leads to saturation of exchanging protons which biases metabolite concentration estimates and prevents the study of downfield resonances in the 1H spectrum. Goal(s): Apply metabolite-cycling (MC) to study these resonances with high sensitivity using the short-TE, full-intensity SPECIAL sequence at ultra-high field on an animal scanner. Approach: The MC pulse was optimized for 14.1T. MC SPECIAL and MC diffusion-weighted SPECIAL were implemented and tested in vivo. Results: Underestimation of specific upfield metabolite concentrations with water-suppressed SPECIAL compared to MC SPECIAL was observed. Downfield resonances attribution was further validated with diffusion-weighted acquisitions, uniquely showing the presence of macromolecules in the 6.5-7.5ppm region. Impact: The introduction of
metabolite-cycling in the short echo-time, full intensity SPECIAL and
diffusion-weighted SPECIAL 1H MRS sequences at 14.1T paves the way
for in-depth exploration of the downfield resonances of the 1H
spectrum with high sensitivity on animal scanners. |
| 16:24 | 0253.
 | Robust Volumetric Diffusion-Weighted MRSI via Time-Resolved Phase Reconstruction and Correction Zepeng Wang1,2, Bradley P. Sutton1,2,3, and Fan Lam1,2,3
1Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States Keywords: Spectroscopy, Spectroscopy, Diffusion, Quantitative Imaging Motivation: To address the long-standing phase correction challenge and enhance the robustness for diffusion-weighted MRSI. Goal(s): To correct the significant phase variations due to macroscopic and microscopic motions in in vivo diffusion-weighted MRSI acquisition. Approach: We developed a novel fast diffusion-weighted MRSI sequence integrating time-resolved, sparsely sampled, volumetric phase navigators, a subspace-based phase image reconstruction, and a sensitivity-encoded phase-corrected reconstruction. The corrected diffusion-weighted MRSI data were processed by state-of-the-art subspace-based spatiospectral processing methods. Results: Improved data quality, diffusion-weighted spatiospectral reconstruction and metabolite-specific diffusion parameter estimation achieved by the proposed method are demonstrated using in vivo data. Impact: A novel integrative acquisition and
reconstruction solution for robust, phase-corrected 3D in vivo diffusion-weighted
MRSI was presented, an important step towards developing diffusion-weighted MRSI for its translation to quantitative,
molecule-specific microstructural imaging. |
| 16:36 | 0254.
 | Multilayer Metabolic Networks of Mesial Temporal Lobe Epilepsy: Insights from Simultaneous PET/MRSI Hui Huang1, Miao Zhang2, Yibo Zhao3,4, Wen Jin3,4, Yudu Li3,5, Bingyang Cai1, Jiwei Li1, Zhi-Pei Liang3,4, Biao Li2, and Jie Luo1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, 2Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 3Department of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, Urbana, IL, United States, 4Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, United States, 5National Center for Supercomputing Applications, University of Illinois at Urbana Champaign, Urbana, IL, United States Keywords: Epilepsy, Metabolism, PET/MR Motivation: How chronic epilepsy impacts the interplay between neuronal metabolites and inter-regional metabolic connectivity remains unclear. Goal(s): To identify neurometabolic imaging biomarkers for epilepsy progression using PET/MRSI. Approach: Forty-eight patients with drug-resistant mesial temporal lobe epilepsy and fifteen patients with extratemporal epilepsy underwent simultaneous high-resolution MRSI and FDG PET. Moderation effects of disease duration were evaluated for multiple brain regions; multilayer metabolic networks were constructed to investigate metabolic changes of NAA, FDG and their interplay. Results: We found disease duration moderated changes in the interplay between NAA and FDG. Metabolic networks form distinct modules in short duration and long duration groups. Impact: This is
the first simultaneous PET/MRSI study to investigate multilayer metabolic
network associated with disease duration of mTLE, which could offer a
comprehensive view of neurometabolic profile, facilitating the exploration of
imaging markers in epileptic lesion detection and disease progression. |
| 16:48 | 0255.
 | Imaging brain metabolic alterations of multiple sclerosis using fast high-resolution 3D-CRT-MRSI at 7T Eva Niess1,2, Assunta Dal-Bianco3, Lukas Hingerl1, Bernhard Strasser1, Alexandra Lipka1, Fabian Niess1, Stanislav Motyka1,2, Anna Petrova1,3, Gilbert Hangel1,4, Paulus Rommer3, Siegfried Trattnig1, and Wolfgang Bogner1,2
1High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 2Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 3Department of Neurology, Medical University of Vienna, Vienna, Austria, 4Department of Neurosurgery, Medical University of Vienna, Vienna, Austria Keywords: Multiple Sclerosis, Brain, MR Spectroscopic Imaging Motivation: MR spectroscopy offers biomarkers like myo-inositol and N-acetylasparate that can better predict disability progression and clinical status in multiple sclerosis. However, traditional MR spectroscopic imaging faces challenges like limited resolution and lengthy acquisition times, hampering its clinical utility. Goal(s): This study aimed to assess a novel 7T 3D-concentric-ring-trajectory-readout MRSI, addressing these limitations, for reliable metabolic marker imaging in MS. Approach: Metabolic images were obtained from 26 MS patients and compared with 13 healthy controls. Results: Altered brain metabolism in MS was effectively visualized across a large brain volume, revealing significant differences in metabolite levels within normal-appearing white matter. Impact: We showcase extensive, high-resolution brain metabolic mapping of multiple sclerosis within a clinically viable timeframe. This can enhance disease monitoring and improve the assessment of treatment effectiveness. |
| 17:00 | 0256.
 | CHEAP and SLOW: a comprehensive acquisition protocol for downfield, upfield, and spectral editing 1H-MRSI at 7T Guodong Weng1,2, Piotr Radojewski1,2, and Johannes Slotboom1,2
1Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland, 2Translational Imaging Center, sitem-insel, Bern, Switzerland, Bern, Switzerland Keywords: Spectroscopy, High-Field MRI, downfield, Spectral editing, MRSI Motivation: Integration of downfield, upfield, and spectral editing MRSI in clinical studies Goal(s): Generate high resolution downfield (0.37 ml) and upfield (0.2 ml) in vivo MRSI at 7T Approach: CHEAP-ESPI and SLOW-EPSI were used for downfield and upfield (spectral editing) MRSI, respectively, in two healthy volunteers and one glioma patient. Results: A 4-minute acquisition with CHEAP-EPSI suffices for downfield MRSI (ATP/GSH+ and NAA+), while a 9-minute acquisition with SLOW-EPSI is adequate for upfield (NAA) and spectral editing (2HG, GABA, and Glx) MRSI. Impact: The combination of CHEAP-EPSI and SLOW-EPSI enables the measurement of downfield, upfield, and edited 3D MRSI within approximately 13 minutes, making it readily integrable into clinical routine examinations or scientific studies. |
| 17:12 | 0257.
 | Selective measurement of glycine in human brain by optimal control method at 7 T Ying Liu1, Jiaxiang Xin2, Yifan Yuan3, Caixia Fu4, Ying-Hua Chu2, Da-Xiu Wei5, Ye-Feng Yao5, and He Wang1
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2MR Research Collaboration Team, Siemens Healthineers Ltd, Shanghai, China, 3Huashan Hospital, Fudan University, Shanghai, China, 4MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 5Physics Department and Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China Keywords: Pulse Sequence Design, Spectroscopy Motivation: Glycine is key neurotransmitter associated with the the pathogenesis and imaging of gliomas, yet the non-invasive quantification of it remains a challenge. Goal(s): To selectively measure glycine in human brain. Approach: A new pulse sequence was developed, utilizing optimal control techniques to selectively detect glycine signals while effectively suppressing myo-inositol signals. Results: Experimental results from both phantom models and glioma patient studies confirm the selective detection of glycine. Preliminary data indicate a relationship between glycine signal intensities and glioma distributions. Impact: The use of the developed pulse sequence for the selective
measurement of glycine in the human brain may provide possibility for more
accurate assessment of glioma aggressiveness. |
| 17:24 | 0258.
 | In Vivo Detection of Lactate and its T2 in the Resting Human Brain by Transverse Relaxation Encoding with Narrowband Decoupling Li An1, Maria Ferraris Araneta1, Tara Turon1, Christopher S Johnson1, Sungtak Hong1, John A Derbyshire1, and Jun Shen1
1National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States Keywords: Spectroscopy, Spectroscopy, MRS; lactate; glutamate Motivation: The published T2 relaxation times in healthy brains are highly inconsistent. Goal(s): To reliably measure T2 relaxation times of lactate and glutamate. Approach: A new editing pulse was crafted and incorporated into the TREND technique for simultaneous homonuclear decoupling of lactate and glutamate at 7 Tesla. Results: The concentrations and T2 relaxation times of lactate and glutamate were measured in vivo with low CVs and CRLBs. Impact: As lactate and glutamate are the markers of glycolysis and oxidative
metabolism, respectively, this technique can be used for clinical MRS studies
of the biophysical aspects of cerebral metabolic alterations or abnormalities. |
| 17:36 | 0259.
 | A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression Wonil Lee1,2, Yue Zhuo1,2, Thibault Marin1,2, Paul Kyu Han1,2, Didi Chi1,2, Georges El Fakhri3, and Chao Ma1,2
1Radiology, Massachusetts General Hospital, Boston, MA, United States, 2Radiology, Harvard Medical School, Boston, MA, United States, 3School of Medicine, Yale University, Boston, MA, United States Keywords: Spectroscopy, Data Processing, MRSI nuisance signal removal Motivation: Unsuppressed water and lipid signals are several orders of magnitude stronger than the metabolite signals in MRSI, imposing significant challenges in MRSI data processing and image reconstruction. Goal(s): To develop a novel deep learning-based method for nuisance signal removal from MRSI data acquired without suppression. Approach: A neural network with a U-net structure was designed to remove nuisance signals in MRSI, where the input of the network was the Hankel matrix formed by the time-domain MRSI signal. Results: The proposed method was validated using in vivo MRSI data, showing superior performance over the conventional method. Impact: A deep learning-based method is proposed for nuisance signal removal in MRSI. It could enable MRSI without water or lipid suppression with robust performance in practical settings. |
| 17:48 | 0260.
 | Accelerated 3D Metabolite T1 Mapping Using Variable-Flip-Angle FID MRSI Yibo Zhao1,2, Rong Guo1,3, Yudu Li1,4, Wen Jin1,2, Brad Sutton1,4,5, Chao Ma6, Georges El Fakhri7, Yao Li8, Jie Luo8, and Zhi-Pei Liang1,2
1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3Siemens Medical Solutions USA, Inc., Urbana, IL, United States, 4National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 5Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 6Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, 7Yale School of Medicine, New Haven, CT, United States, 8School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China Keywords: Spectroscopy, Spectroscopy Motivation: Metabolite T1 values are needed for T1 correction in short-TR MRSI data. Due to the prolonged scan time, metabolite T1 measurement has been limited to single-voxel or single-slice experiments so far. Goal(s): To develop a novel method for 3D metabolite T1 mapping in a practically feasible scan time. Approach: We used a variable-flip-angle short-TR MRSI to achieve rapid metabolite T1 mapping. The high-dimensional data space was undersampled in a variable-density manner. Associated data processing challenges were solved by generalized-series and low-rank-tensor modelling. Results: Simulation, phantom and healthy subject results demonstrated the feasibility of accelerated 3D metabolite T1 mapping. Impact: The proposed method
enables 3D metabolite T1 mapping within a clinically feasible scan time (15
min). This method can be used to correct T1 weighting effects in accelerated
short-TR MRSI experiments, producing more quantitative results. |