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5 results on '"MESH : Artifacts"'

1. Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs

Author

Jef Vandemeulebroucke, Simon Rit, Jan Kybic, Patrick Clarysse, David Sarrut, Calvat, Pascal, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Center for Machine Perception, Czech Technical University in Prague ( CTU ), 4 - Imagerie Tomographique et Radiothérapie, Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), CCIN2P3, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Czech Technical University in Prague (CTU), and Electronics and Informatics

Subjects
Time Factors, respiratory motion, MESH : Movement, MESH : Four-Dimensional Computed Tomography, Movement, MESH : Lung, Diaphragm, Physics::Medical Physics, MESH: Movement, MESH : Models, Biological, Thoracic Radiotherapy, Models, Biological, MESH : Artifacts, 4D Ct, Deformable Registration, Image Processing, Computer-Assisted, Organ Motion, MESH: Lung, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Four-Dimensional Computed Tomography, 4-Dimensional Computed-Tomography, Lung, Ct, Deformations, MESH: Respiration, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Four-Dimensional Computed Tomography, Respiration, MESH: Time Factors, MESH: Models, Biological, MESH: Image Processing, Computer-Assisted, MESH : Respiration, Mr-Images, MESH: Artifacts, MESH: Diaphragm, Nonrigid Registration, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Reconstruction, MESH : Diaphragm, Artifacts, MESH : Image Processing, Computer-Assisted, Model, MESH : Time Factors
Abstract

International audience; PURPOSE: Four-dimensional computed tomography (4D CT) can provide patient-specific motion information for radiotherapy planning and delivery. Motion estimation in 4D CT is challenging due to the reduced image quality and the presence of artifacts. We aim to improve the robustness of deformable registration applied to respiratory-correlated imaging of the lungs, by using a global problem formulation and pursuing a restrictive parametrization for the spatiotemporal deformation model. METHODS: A spatial transformation based on free-form deformations was extended to the temporal domain, by explicitly modeling the trajectory using a cyclic temporal model based on B-splines. A global registration criterion allowed to consider the entire image sequence simultaneously and enforce the temporal coherence of the deformation throughout the respiratory cycle. To ensure a parametrization capable of capturing the dynamics of respiratory motion, a prestudy was performed on the temporal dimension separately. The temporal parameters were tuned by fitting them to diaphragm motion data acquired for a large patient group. Suitable properties were retained and applied to spatiotemporal registration of 4D CT data. Registration results were validated using large sets of landmarks and compared to consecutive spatial registrations. To illustrate the benefit of the spatiotemporal approach, we also assessed the performance in the presence of motion-induced artifacts. RESULTS: Cubic B-splines gave better or similar fitting results as lower orders and were selected because of their inherently stronger regularization. The fitting and registration errors increased gradually with the temporal control point spacing, representing a trade-off between achievable accuracy and sensitivity to noise and artifacts. A piecewise smooth trajectory model, allowing for a discontinuous change of speed at end-inhale, was found most suitable to account for the sudden changes of motion at this breathing phase. The spatiotemporal modeling allowed a reduction of the number of parameters of 45%, while maintaining registration accuracy within 0.1 mm. The approach reduced the sensitivity to artifacts. CONCLUSIONS: Spatiotemporal registration can provide accurate motion estimation for 4D CT and improves the robustness to artifacts.

Published
2011

2. Non-local MRI upsampling

Author

Antonio Buades, Pierrick Coupé, D. Louis Collins, Vladimir S. Fonov, José V. Manjón, Montserrat Robles, ITACA, Universidad Politécnica de Valencia, McConnell Brain Imaging Centre ( MNI ), Montreal Neurological Institute [Montréal], McGill University-McGill University, Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS ), Dpt Matemàtiques i Informàtica, Universitat Illes Balears, Universitat Politècnica de València (UPV), McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), and Coupé, Pierrick

Subjects
[INFO.INFO-IM] Computer Science [cs]/Medical Imaging, MESH: Signal Processing, Computer-Assisted, MESH : Artifacts, 030218 nuclear medicine & medical imaging, MESH: Magnetic Resonance Imaging, Upsampling, 0302 clinical medicine, Image scaling, Computer vision, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Image resolution, MESH : Algorithms, Mathematics, Signal processing, Radiological and Ultrasound Technology, [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, MESH : Image Interpretation, Computer-Assisted, Brain, Stairstep interpolation, Signal Processing, Computer-Assisted, Non-local means, Computer Graphics and Computer-Aided Design, Peak signal-to-noise ratio, Magnetic Resonance Imaging, MESH : Sample Size, MESH: Reproducibility of Results, MESH: Artifacts, Data Interpretation, Statistical, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Computer Vision and Pattern Recognition, MESH: Image Enhancement, MESH : Sensitivity and Specificity, Artifacts, Algorithms, Interpolation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Health Informatics, MESH: Algorithms, Sensitivity and Specificity, 03 medical and health sciences, MESH: Brain, MESH : Magnetic Resonance Imaging, Image Interpretation, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Radiology, Nuclear Medicine and imaging, MESH : Data Interpretation, Statistical, MESH: Sample Size, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH : Signal Processing, Computer-Assisted, MESH: Humans, business.industry, MESH : Reproducibility of Results, MESH : Humans, Reproducibility of Results, Image Enhancement, MESH: Sensitivity and Specificity, MESH : Brain, Sample Size, MESH : Image Enhancement, Artificial intelligence, business, MESH: Data Interpretation, Statistical, MESH: Image Interpretation, Computer-Assisted, 030217 neurology & neurosurgery
Abstract

International audience; In Magnetic Resonance Imaging, image resolution is limited by several factors such as hardware or time constraints. In many cases, the acquired images have to be upsampled to match a specific resolution. In such cases, image interpolation techniques have been traditionally applied. However, traditional interpolation techniques are not able to recover high frequency information of the underlying high resolution data. In this paper, a new upsampling method is proposed to recover some of this high frequency information by using a data-adaptive patch-based reconstruction in combination with a subsampling coherence constraint. The proposed method has been evaluated on synthetic and real clinical cases and compared with traditional interpolation methods. The proposed method is shown to outperform classical interpolation methods compared in terms of quantitative measures and visual observation.

Published
2010

3. New methods for MRI denoising based on sparseness and self-similarity

Author

José V. Manjón, Montserrat Robles, Pierrick Coupé, Antonio Buades, D. Louis Collins, ITACA, Universitat Politècnica de València (UPV), McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Dpt Matemàtiques i Informàtica, Universitat Illes Balears, This work has been partially supported by the Spanish Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001, the Spanish Ministry Science and Innovation through grant TIN2008-04752, and the Canadian Institutes of Health Research Industry Cda (CECR)-Gevas-OE016., Coupé, Pierrick, Universidad Politécnica de Valencia, McConnell Brain Imaging Centre ( MNI ), Montreal Neurological Institute [Montréal], McGill University-McGill University, Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), and Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS )

Subjects
[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, MESH : Artifacts, 030218 nuclear medicine & medical imaging, MESH: Magnetic Resonance Imaging, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Computer vision, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Invariant (mathematics), MESH : Algorithms, Mathematics, [STAT.AP]Statistics [stat]/Applications [stat.AP], Radiological and Ultrasound Technology, self-similarity, MESH : Image Interpretation, Computer-Assisted, DCT, Brain, Computer Graphics and Computer-Aided Design, Thresholding, Magnetic Resonance Imaging, MESH: Reproducibility of Results, MESH: Artifacts, Principal component analysis, MESH : Imaging, Three-Dimensional, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Computer Vision and Pattern Recognition, MESH : Sensitivity and Specificity, MESH: Image Enhancement, Artifacts, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, MRI, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, sparseness, Self-similarity, Mean squared error, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Noise reduction, Health Informatics, MESH: Algorithms, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, 03 medical and health sciences, MESH: Brain, Imaging, Three-Dimensional, MESH : Magnetic Resonance Imaging, Image Interpretation, Computer-Assisted, Discrete cosine transform, denoising, Humans, Radiology, Nuclear Medicine and imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Humans, business.industry, MESH : Reproducibility of Results, MESH : Humans, [ STAT.AP ] Statistics [stat]/Applications [stat.AP], Reproducibility of Results, Pattern recognition, Filter (signal processing), filtering, Image Enhancement, MESH: Sensitivity and Specificity, MESH : Brain, MESH : Image Enhancement, Artificial intelligence, business, MESH: Image Interpretation, Computer-Assisted, 030217 neurology & neurosurgery, nonlocal means
Abstract

International audience; This paper proposes two new methods for the three-dimensional denoising of magnetic resonance images that exploit the sparseness and self-similarity properties of the images. The proposed methods are based on a three-dimensional moving-window discrete cosine transform hard thresholding and a three-dimensional rotationally invariant version of the well-known nonlocal means filter. The proposed approaches were compared with related state-of-the-art methods and produced very competitive results. Both methods run in less than a minute, making them usable in most clinical and research settings.

Published
2010

4. Swallowing, arterial pulsation, and breathing induce motion artifacts in carotid artery MRI

Author

Loic Boussel, Philippe Douek, Jean Michel Serfaty, Gwenael Herigault, Michel Nonent, Alejandro de la Vega, Laboratoire Creatis, Compte Général, Hôpital Cardiovasculaire Louis Pradel ( HCLP ), Hospices Civils de Lyon ( HCL ), Philips Medical Systems ( PMS ), Philips Medical Systems, Département de radiologie [Brest] ( DR - Brest ), Centre Hospitalier Régional Universitaire de Brest ( CHRU Brest ), Groupe d'Etude de la Thrombose de Bretagne Occidentale ( GETBO ), Université de Brest ( UBO ), Département de Radiologie, Université Xavier Bichat, Hôpital Cardiovasculaire Louis Pradel (HCLP), Hospices Civils de Lyon (HCL), Philips Medical Systems (PMS), Département de radiologie [Brest] (DR - Brest), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Groupe d'Etude de la Thrombose de Bretagne Occidentale (GETBO), Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO), Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Carotid Artery Diseases, Male, MESH : Motion, MESH : Atherosclerosis, MESH : Deglutition, Pulsatile flow, MESH : Aged, MESH : Carotid Arteries, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Magnetic resonance angiography, MESH : Artifacts, 030218 nuclear medicine & medical imaging, MESH: Magnetic Resonance Imaging, MESH: Atherosclerosis, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Image Processing, Computer-Assisted, MESH : Female, MESH: Aged, MESH: Middle Aged, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, medicine.diagnostic_test, Respiration, Isocenter, Middle Aged, MESH : Adult, Magnetic Resonance Imaging, MESH: Image Processing, Computer-Assisted, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Amplitude, Carotid Arteries, MESH: Artifacts, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Pulsatile Flow, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], MESH: Pulsatile Flow, Cardiology, Breathing, Female, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, Artifacts, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, MESH : Image Processing, Computer-Assisted, Adult, medicine.medical_specialty, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, MESH: Motion, MESH : Male, Diastole, Lumen (anatomy), MESH : Pulsatile Flow, 03 medical and health sciences, Motion, Swallowing, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Internal medicine, MESH : Magnetic Resonance Imaging, [ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology, medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Radiology, Nuclear Medicine and imaging, MESH : Middle Aged, MESH : Carotid Artery Diseases, Aged, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, MESH: Respiration, MESH: Carotid Arteries, MESH: Humans, business.industry, MESH: Carotid Artery Diseases, MESH : Humans, MESH: Adult, Atherosclerosis, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, MESH: Male, Deglutition, MESH : Respiration, MESH: Deglutition, business, MESH: Female, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Purpose To identify and quantify the potential sources of motion in carotid artery imaging. Materials and Methods Two healthy volunteers and 12 patients (20–75 years old) with atherosclerotic disease were scanned on a Philips Intera 1.5T system. A single-shot balanced-fast field echo (bFFE) sequence was used to acquire real-time axial views of the carotid artery wall (three images per second). A three-step acquisition protocol was performed to analyze the three types of motion (arterial pulsation, breathing, and swallowing) separately. The isocenter carotid artery motion amplitude in either the x or y direction was measured. Radial variation in the carotid lumen between the systolic and diastolic phases was analyzed. Motion frequency was reported for each patient. Results Significant motion related to arterial pulsation (amplitude = 0.27–0.93 mm, mean = 0.6, SD = 0.19), breathing (amplitude = 0.5–3.6 mm, mean = 1.56, SD = 0.99)), and swallowing (amplitude = 1.4–9.2 mm, mean = 4.7, SD = 2.4) were visualized. Conclusion Pulsation, breathing, and swallowing are sources of significant motion in the carotid artery wall. Such motion should be considered in the future to improve carotid artery image quality. J. Magn. Reson. Imaging 2006. © 2006 Wiley-Liss, Inc.

Published
2006

5. Anomalous transverse relaxation in 1H spectroscopy in human brain at 4 Tesla

Author

Robert C. Risinger, Denis Le Bihan, S. Posse, Robert S. Balaban, Charles A. Cuenod, Department of Health and Human Services, National Institutes of Health [Bethesda] (NIH), Méthodes d'imagerie des échanges transcapillaires (LRI), IFR94-Université Paris Descartes - Paris 5 (UPD5), Laboratoire de Recherche en Imagerie LRI-EA4062, Université Paris Descartes - Paris 5 (UPD5), Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Univ Fed Rio Grande do Norte, Dept Chem (LAPET), Univ Fed Rio Grande do Norte, Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), National Institutes of Health ( NIH ), Méthodes d'imagerie des échanges transcapillaires ( LRI ), IFR94-Université Paris Descartes - Paris 5 ( UPD5 ), Université Paris Descartes - Paris 5 ( UPD5 ), National Institutes of Health [Bethesda] ( NIH ), Service NEUROSPIN ( NEUROSPIN ), Direction de Recherche Fondamentale (CEA) ( DRF (CEA) ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Univ Fed Rio Grande do Norte, Dept Chem ( LAPET ), and Le Bihan, Denis

Subjects
Intracellular Fluid, MESH : Motion, Magnetic Resonance Spectroscopy, Proton, Phosphocreatine, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Analytical chemistry, MESH : Aspartic Acid, MESH: Signal Processing, Computer-Assisted, MESH: Aspartic Acid, MESH : Artifacts, MESH : Choline, 030218 nuclear medicine & medical imaging, Choline, Diffusion, Paramagnetism, chemistry.chemical_compound, 0302 clinical medicine, Nuclear magnetic resonance, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, Fourier Analysis, MESH: Creatine, MESH: Intracellular Fluid, MESH : Hydrogen, Relaxation (NMR), MESH: Hydrogen, MESH: Choline, Brain, Pulse sequence, Signal Processing, Computer-Assisted, MESH: Diffusion, Nuclear magnetic resonance spectroscopy, Human brain, MESH : Creatine, medicine.anatomical_structure, MESH: Artifacts, MESH : Electron Spin Resonance Spectroscopy, Occipital Lobe, MESH: Image Enhancement, Artifacts, MESH: Occipital Lobe, MESH: Motion, MESH: Phosphocreatine, 03 medical and health sciences, Motion, MESH: Brain, MESH: Body Water, Body Water, medicine, Humans, Radiology, Nuclear Medicine and imaging, MESH : Phosphocreatine, Spectroscopy, MESH : Diffusion, Aspartic Acid, MESH : Signal Processing, Computer-Assisted, MESH : Body Water, MESH : Occipital Lobe, MESH: Humans, MESH: Magnetic Resonance Spectroscopy, MESH : Humans, Electron Spin Resonance Spectroscopy, Creatine, Image Enhancement, nervous system diseases, MESH : Fourier Analysis, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, chemistry, MESH : Brain, nervous system, MESH : Image Enhancement, MESH : Magnetic Resonance Spectroscopy, MESH: Electron Spin Resonance Spectroscopy, 030217 neurology & neurosurgery, MESH: Fourier Analysis, Hydrogen, MESH : Intracellular Fluid
Abstract

International audience; Longitudinal (T1) and apparent transverse relaxation times (T2) of choline-containing compounds (Cho), creatine/phosphocreatine (Cr/PCr), and N-acetyl aspartate (NAA) were measured in vivo in human brain at 4 Tesla. Measurements were performed using a water suppressed stimulated echo pulse sequence with complete outside volume presaturation to improve volume localization at short echo times. T1-values of Cho (1.2 +/- 0.1 s), Cr (1.6 +/- 0.3 s), and NAA (1.6 +/- 0.2 s) at 4 Tesla in occipital brain were only slightly larger than those reported in the literature at 1.5 Tesla. Thus, TR will not adversely affect the expected enhancement of signal-to-noise at 4 Tesla. Surprisingly, apparent T2-values of Cho (142 +/- 34 ms), Cr (140 +/- 13 ms), and NAA (185 +/- 24 ms) at 4 Tesla were significantly smaller than those at 1.5 Tesla and further decreased when increasing the mixing interval TM. Potential contributing factors, such as diffusion in local susceptibility related gradients, dipolar relaxation due to intracellular paramagnetic substances and motion effects are discussed. The results suggest that short echo time spectroscopy is advantageous to maintain signal to noise at 4 Tesla.

Published
1995

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