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Mahmud SZ, Denney TS, Bashir A. High-resolution proton metabolic mapping of the human brain at 7 T using free induction decay rosette spectroscopic imaging. NMR IN BIOMEDICINE 2024; 37:e5042. [PMID: 37767769 DOI: 10.1002/nbm.5042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 09/05/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) provides information about the spatial distribution of metabolites in the brain. These metabolite maps can be valuable in diagnosing central nervous system pathology. However, MRSI generally suffers from a long acquisition time, poor spatial resolution, and a low metabolite signal-to-noise ratio (SNR). Ultrahigh field strengths (≥ 7 T) can benefit MRSI with an improved SNR and allow high-resolution metabolic mapping. Non-Cartesian spatial-spectral encoding techniques, such as rosette spectroscopic imaging, can efficiently sample spatial and temporal domains, which significantly reduces the imaging time and enables high-resolution metabolic mapping in a clinically relevant scan time. In the current study, high-resolution (in-plane resolution of 2 × 2 mm2 ) mapping of proton (1 H) metabolites in the human brain at 7 T, is demonstrated. Five healthy subjects participated in the study. Using a time-efficient rosette trajectory and short TR/TE free induction decay MRSI, high-resolution maps of 1 H metabolites were obtained in a clinically relevant imaging time (6 min). Suppression of the water signal was achieved with an optimized water suppression enhanced through T1 effects approach and lipid removal was performed using L2 -regularization in the postprocessing. Spatial distributions of N-acetyl-aspartate, total choline, creatine, N-acetyl-aspartyl glutamate, myo-inositol, and glutamate were generated with Cramer-Rao lower bounds of less than 20%.
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Affiliation(s)
- Sultan Z Mahmud
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Auburn University MRI Research Center, Auburn University, Auburn, Alabama, USA
| | - Thomas S Denney
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Auburn University MRI Research Center, Auburn University, Auburn, Alabama, USA
| | - Adil Bashir
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Auburn University MRI Research Center, Auburn University, Auburn, Alabama, USA
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2
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Hatay GH, Ozturk-Isik E. Optimized multi-voxel TE-averaged PRESS for glutamate detection in the human brain at 3T. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 356:107574. [PMID: 37922677 DOI: 10.1016/j.jmr.2023.107574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 10/20/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023]
Abstract
PURPOSE To optimize possible combinations of echo times (TE) for multi-voxel TE-averaged Point RESolved Spectroscopy (PRESS) while reducing the total number of TEs required to separate glutamate (Glu) and glutamine (Gln) within a clinically feasible scan time. METHODS General Approach to Magnetic resonance Mathematical Analysis (GAMMA) was used to implement 2D J-resolved PRESS technique, and the spectra of 14 individual brain metabolites were simulated at 64 different TEs. Monte Carlo simulations were used for selecting the best TE combinations to separate Glu and Gln using TE-averaged PRESS with a total number of two, three, four and five TEs. Single-voxel 1H-MRS data were acquired using 64 different TEs from a healthy volunteer on a clinical 3T MR scanner to validate the echo time combinations selected with simulations. Additionally, 2D 1H-MRSI data of eight healthy volunteers were acquired on a clinical 3T MR scanner using four different TEs that were determined by Monte Carlo simulations. Optimized TE-averaged PRESS spectra were created by averaging the spectra acquired at selected TEs. LCModel was used for spectral quantification. A Wilcoxon signed-rank test was used to detect statistically significant differences in Glu/Gln ratios between 35 ms PRESS and optimized TE-averaged PRESS data. RESULTS Glu could be clearly separated from Gln at 2.35 ppm, using optimized TE-averaged PRESS with only four TEs (35, 37, 40, and 42 ms) that were selected through Monte Carlo simulations. Glu/Gln ratios were significantly higher in the optimized TE-averaged PRESS data of healthy volunteers than in the 35 ms PRESS data (P = 0.008). CONCLUSION Optimized multi-voxel TE-averaged PRESS enabled faster and unobstructed quantification of Glu at multiple voxels in the human brain in vivo at 3T.
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Affiliation(s)
- Gokce Hale Hatay
- Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey.
| | - Esin Ozturk-Isik
- Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey.
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Lakhani DA, Zhou X, Tao S, Westerhold EM, Eidelman BH, Singh Sandhu SJ, Middlebrooks EH. Clinical application of ultra-high resolution compressed sensing time-of-flight MR angiography at 7T to detect small vessel pathology. Neuroradiol J 2023; 36:335-340. [PMID: 36173305 PMCID: PMC10268099 DOI: 10.1177/19714009221129576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
3D time-of-flight (TOF) MR angiography (MRA) benefits from ultra-high-field MRI (≥7 T) due to improved contrast and increased signal-to-noise ratio. However, high-resolution TOF MRA at 7T usually requires longer acquisition times. In addition, relatively higher specific absorption rate (SAR) at 7T limits the choice of optimal pulse sequence parameters, especially if venous saturation is employed. Here, we illustrate the clinical application of ultra-high resolution cerebral 7T TOF MRA using compressed sensing in cases of artery of Percheron and lacunar infarcts, which showed superior resolution and exquisite details pertinent to the clinical diagnosis. The technical challenges associated with high-resolution 7T imaging were alleviated by optimization of sequence parameters and utilization of compressed sensing acceleration.
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Affiliation(s)
- Dhairya A Lakhani
- Department of Radiology, West Virginia University, Morgantown, WV, USA
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Xiangzhi Zhou
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Shengzhen Tao
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
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Mahmud SZ, Denney TS, Bashir A. Feasibility of spinal cord imaging at 7 T using rosette trajectory with magnetization transfer preparation and compressed sensing. Sci Rep 2023; 13:8777. [PMID: 37258697 DOI: 10.1038/s41598-023-35853-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/24/2023] [Indexed: 06/02/2023] Open
Abstract
MRI is a valuable diagnostic tool to investigate spinal cord (SC) pathology. SC MRI can benefit from the increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at ultra-high fields such as 7 T. However, SC MRI acquisitions with routine Cartesian readouts are prone to image artifacts caused by physiological motion. MRI acquisition techniques with non-Cartesian readouts such as rosette can help reduce motion artifacts. The purpose of this study was to demonstrate the feasibility of high-resolution SC imaging using rosette trajectory with magnetization transfer preparation (MT-prep) and compressed sensing (CS) at 7 T. Five healthy volunteers participated in the study. Images acquired with rosette readouts demonstrated reduced motion artifacts compared to the standard Cartesian readouts. The combination of multi-echo rosette-readout images improved the CNR by approximately 50% between the gray matter (GM) and white matter (WM) compared to single-echo images. MT-prep images showed excellent contrast between the GM and WM with magnetization transfer ratio (MTR) and cerebrospinal fluid normalized MT signal (MTCSF) = 0.12 ± 0.017 and 0.74 ± 0.013, respectively, for the GM; and 0.18 ± 0.011 and 0.58 ± 0.009, respectively, for the WM. Under-sampled acquisition using rosette readout with CS reconstruction demonstrated up to 6 times faster scans with comparable image quality as the fully-sampled acquisition.
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Affiliation(s)
- Sultan Z Mahmud
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA
| | - Thomas S Denney
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA
| | - Adil Bashir
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA.
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA.
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Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi‐Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney‐Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022; 88:2592-2608. [PMID: 36128894 PMCID: PMC9529952 DOI: 10.1002/mrm.29450] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 01/11/2023]
Abstract
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
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Affiliation(s)
- Rosie J. Goodburn
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | | | - Thierry L. Lefebvre
- Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Cancer Research UK Cambridge Research InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Aly Khalifa
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Tom Bruijnen
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | | | - David E. J. Waddington
- Faculty of Medicine and Health, Sydney School of Health Sciences, ACRF Image X InstituteThe University of SydneySydneyNew South WalesAustralia
| | - Eyesha Younus
- Department of Medical Physics, Odette Cancer CentreSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Eric Aliotta
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Gabriele Meliadò
- Unità Operativa Complessa di Fisica SanitariaAzienda Ospedaliera Universitaria Integrata VeronaVeronaItaly
| | - Teo Stanescu
- Department of Radiation Oncology, University of Toronto and Medical Physics, Princess Margaret Cancer CentreUniversity Health NetworkTorontoOntarioCanada
| | - Wajiha Bano
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Ali Fatemi‐Ardekani
- Department of PhysicsJackson State University (JSU)JacksonMississippiUSA
- SpinTecxJacksonMississippiUSA
- Department of Radiation OncologyCommunity Health Systems (CHS) Cancer NetworkJacksonMississippiUSA
| | - Andreas Wetscherek
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Nico van den Berg
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | - Ralph P. Mason
- Department of RadiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Petra J. van Houdt
- Department of Radiation OncologyNetherlands Cancer InstituteAmsterdamNetherlands
| | - James M. Balter
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Oliver J. Gurney‐Champion
- Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam UMCUniversity of AmsterdamAmsterdamNetherlands
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McCarthy L, Verma G, Hangel G, Neal A, Moffat BA, Stockmann JP, Andronesi OC, Balchandani P, Hadjipanayis CG. Application of 7T MRS to High-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:1378-1395. [PMID: 35618424 PMCID: PMC9575545 DOI: 10.3174/ajnr.a7502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/11/2022] [Indexed: 01/26/2023]
Abstract
MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.
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Affiliation(s)
- L McCarthy
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
| | - G Verma
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - G Hangel
- Department of Neurosurgery (G.H.)
- High-field MR Center (G.H.), Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - A Neal
- Department of Medicine (A.N.), Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
- Department of Neurology (A.N.), Royal Melbourne Hospital, Melbourne, Australia
| | - B A Moffat
- The Melbourne Brain Centre Imaging Unit (B.A.M.), Department of Radiology, The University of Melbourne, Melbourne, Australia
| | - J P Stockmann
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - O C Andronesi
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - P Balchandani
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - C G Hadjipanayis
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
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7
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Abstract
Abstract
Purpose
Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.
Methods
PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.
Results
We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.
Conclusions
Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.
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8
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Hangel G, Niess E, Lazen P, Bednarik P, Bogner W, Strasser B. Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain. Anal Biochem 2022; 638:114479. [PMID: 34838516 DOI: 10.1016/j.ab.2021.114479] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/15/2021] [Accepted: 11/16/2021] [Indexed: 12/21/2022]
Abstract
Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.
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Affiliation(s)
- Gilbert Hangel
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria; Department of Neurosurgery, Medical University of Vienna, Austria
| | - Eva Niess
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Philipp Lazen
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Petr Bednarik
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Bernhard Strasser
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria.
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9
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Klauser A, Klauser P, Grouiller F, Courvoisier S, Lazeyras F. Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI. NMR IN BIOMEDICINE 2022; 35:e4615. [PMID: 34595791 PMCID: PMC9285075 DOI: 10.1002/nbm.4615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 08/16/2021] [Accepted: 08/20/2021] [Indexed: 05/07/2023]
Abstract
There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian 1 H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D 1 H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of PsychiatryLausanne University HospitalSwitzerland
- Service of Child and Adolescent Psychiatry, Department of PsychiatryLausanne University HospitalSwitzerland
| | - Frédéric Grouiller
- Swiss Center for Affective SciencesUniversity of GenevaSwitzerland
- Laboratory of Behavioral Neurology and Imaging of Cognition, Department of Fundamental NeuroscienceUniversity of GenevaSwitzerland
| | - Sébastien Courvoisier
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - François Lazeyras
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
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Klauser A, Strasser B, Thapa B, Lazeyras F, Andronesi O. Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 331:107048. [PMID: 34438355 PMCID: PMC8717865 DOI: 10.1016/j.jmr.2021.107048] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 06/29/2021] [Accepted: 08/08/2021] [Indexed: 06/02/2023]
Abstract
Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines 1H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.
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Affiliation(s)
- Antoine Klauser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland.
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Bijaya Thapa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Francois Lazeyras
- Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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11
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Rioux JA, Hewlett M, Davis C, Bowen CV, Brewer K, Clarke SE, Beyea SD. Mapping of fatty acid composition with free-breathing MR spectroscopic imaging and compressed sensing. NMR IN BIOMEDICINE 2021; 34:e4241. [PMID: 31898379 PMCID: PMC8244113 DOI: 10.1002/nbm.4241] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 11/13/2019] [Accepted: 11/18/2019] [Indexed: 06/10/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a growing health problem, and a major challenge in NAFLD management is identifying which patients are at risk of progression to more serious disease. Simple measurements of liver fat content are not strong predictors of clinical outcome, but biomarkers related to fatty acid composition (ie, saturated vs. unsaturated fat) may be more effective. MR spectroscopic imaging (MRSI) methods allow spatially resolved, whole-liver measurements of chemical composition but are traditionally limited by slow acquisition times. In this work we present an accelerated MRSI acquisition based on spin echo single point imaging (SE-SPI), which, using appropriate sampling and compressed sensing reconstruction, allows free-breathing acquisition in a mouse model of fatty liver disease. After validating the technique's performance in oil/water phantoms, we imaged mice that had received a normal diet or a methionine and choline deficient (MCD) diet, some of which also received supplemental injections of iron to mimic hepatic iron overload. SE-SPI was more resistant to the line-broadening effects of iron than single-voxel spectroscopy measurements, and was consistently able to measure the amplitudes of low-intensity spectral peaks that are important to characterizing fatty acid composition. In particular, in the mice receiving the MCD diet, SE-SPI showed a significant decrease in a metric associated with unsaturated fat, which is consistent with the literature. This or other related metrics may therefore offer more a specific biomarker of liver health than fat content alone. This preclinical study is an important precursor to clinical testing of the proposed method. MR-based quantification of fatty acid composition may allow for improved characterization of non-alcoholic fatty liver disease. A spectroscopic imaging method with appropriate sampling strategy allows whole-liver mapping of fat composition metrics in a free-breathing mouse model. Changes in metrics like the surrogate unsaturation index (UIs) are visible in mice receiving a diet which induces fat accumulation in the liver, as compared to a normal diet; such metrics may prove useful in future clinical studies of liver disease.
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Affiliation(s)
- James A. Rioux
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Diagnostic RadiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Physics and Atmospheric ScienceDalhousie UniversityHalifaxNova ScotiaCanada
| | - Miriam Hewlett
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Medical BiophysicsUniversity of Western OntarioLondonOntarioCanada
| | - Christa Davis
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
| | - Chris V. Bowen
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Diagnostic RadiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Physics and Atmospheric ScienceDalhousie UniversityHalifaxNova ScotiaCanada
- School of Biomedical EngineeringDalhousie UniversityHalifaxNova ScotiaCanada
| | - Kimberly Brewer
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Diagnostic RadiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Physics and Atmospheric ScienceDalhousie UniversityHalifaxNova ScotiaCanada
- School of Biomedical EngineeringDalhousie UniversityHalifaxNova ScotiaCanada
| | - Sharon E. Clarke
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Diagnostic RadiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Physics and Atmospheric ScienceDalhousie UniversityHalifaxNova ScotiaCanada
| | - Steven D. Beyea
- Biomedical Translational Imaging CentreHalifaxNova ScotiaCanada
- Department of Diagnostic RadiologyDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Physics and Atmospheric ScienceDalhousie UniversityHalifaxNova ScotiaCanada
- School of Biomedical EngineeringDalhousie UniversityHalifaxNova ScotiaCanada
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Bogner W, Otazo R, Henning A. Accelerated MR spectroscopic imaging-a review of current and emerging techniques. NMR IN BIOMEDICINE 2021; 34:e4314. [PMID: 32399974 PMCID: PMC8244067 DOI: 10.1002/nbm.4314] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 05/14/2023]
Abstract
Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.
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Affiliation(s)
- Wolfgang Bogner
- High‐Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Ricardo Otazo
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew York, New YorkUSA
| | - Anke Henning
- Max Planck Institute for Biological CyberneticsTübingenGermany
- Advanced Imaging Research Center, UT Southwestern Medical CenterDallasTexasUSA
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13
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Kreis R, Boer V, Choi I, Cudalbu C, de Graaf RA, Gasparovic C, Heerschap A, Krššák M, Lanz B, Maudsley AA, Meyerspeer M, Near J, Öz G, Posse S, Slotboom J, Terpstra M, Tkáč I, Wilson M, Bogner W. Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4347. [PMID: 32808407 PMCID: PMC7887137 DOI: 10.1002/nbm.4347] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 05/20/2020] [Accepted: 05/21/2020] [Indexed: 05/04/2023]
Abstract
With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.
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Affiliation(s)
- Roland Kreis
- Department of Radiology, Neuroradiology, and Nuclear Medicine and Department of Biomedical ResearchUniversity BernBernSwitzerland
| | - Vincent Boer
- Danish Research Centre for Magnetic Resonance, Funktions‐ og Billeddiagnostisk EnhedCopenhagen University Hospital HvidovreHvidovreDenmark
| | - In‐Young Choi
- Department of Neurology, Hoglund Brain Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM)Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging & Department of Biomedical EngineeringYale UniversityNew HavenConnecticutUSA
| | | | - Arend Heerschap
- Department of Radiology and Nuclear MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Martin Krššák
- Division of Endocrinology and Metabolism, Department of Internal Medicine III & High Field MR Centre, Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET)Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Sir Peter Mansfield Imaging Centre, School of MedicineUniversity of NottinghamNottinghamUK
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Martin Meyerspeer
- Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
- High Field MR CenterMedical University of ViennaViennaAustria
| | - Jamie Near
- Douglas Mental Health University Institute and Department of PsychiatryMcGill UniversityMontrealCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Stefan Posse
- Department of NeurologyUniversity of New Mexico School of MedicineAlbuquerqueNew MexicoUSA
| | - Johannes Slotboom
- Department of Radiology, Neuroradiology, and Nuclear MedicineUniversity Hospital BernBernSwitzerland
| | - Melissa Terpstra
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Martin Wilson
- Centre for Human Brain Health and School of PsychologyUniversity of BirminghamBirminghamUK
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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14
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2-D magnetic resonance spectroscopic imaging of the pediatric brain using compressed sensing. Pediatr Radiol 2019; 49:1798-1808. [PMID: 31463513 DOI: 10.1007/s00247-019-04495-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 06/20/2019] [Accepted: 08/01/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Magnetic resonance spectroscopic imaging helps to determine abnormal brain tissue conditions by evaluating metabolite concentrations. Although a powerful technique, it is underutilized in routine clinical studies because of its long scan times. OBJECTIVE In this study, we evaluated the feasibility of scan time reduction in metabolic imaging using compressed-sensing-based MR spectroscopic imaging in pediatric patients undergoing routine brain exams. MATERIALS AND METHODS We retrospectively evaluated compressed-sensing reconstructions in MR spectroscopic imaging datasets from 20 pediatric patients (11 males, 9 females; average age: 5.4±4.5 years; age range: 3 days to 16 years). We performed retrospective under-sampling of the MR spectroscopic imaging datasets to simulate accelerations of 2-, 3-, 4-, 5-, 7- and 10-fold, with subsequent reconstructions in MATLAB. Metabolite maps of N-acetylaspartate, creatine, choline and lactate (where applicable) were quantitatively evaluated in terms of the root-mean-square error (RMSE), peak amplitudes and total scan time. We used the two-tailed paired t-test along with linear regression analysis to statistically compare the compressed-sensing reconstructions at each acceleration with the fully sampled reference dataset. RESULTS High fidelity was maintained in the compressed-sensing MR spectroscopic imaging reconstructions from 50% to 80% under-sampling, with the RMSE not exceeding 3% in any dataset. Metabolite intensities and ratios evaluated on a voxel-by-voxel basis showed no statistically significant differences and mean metabolite intensities showed high correlation compared to the fully sampled reference dataset up to an acceleration factor of 5. CONCLUSION Compressed-sensing MR spectroscopic imaging has the potential to reduce MR spectroscopic imaging scan times for pediatric patients, with negligible information loss.
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Ye JC. Compressed sensing MRI: a review from signal processing perspective. BMC Biomed Eng 2019; 1:8. [PMID: 32903346 PMCID: PMC7412677 DOI: 10.1186/s42490-019-0006-z] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 02/04/2019] [Indexed: 11/27/2022] Open
Abstract
Magnetic resonance imaging (MRI) is an inherently slow imaging modality, since it acquires multi-dimensional k-space data through 1-D free induction decay or echo signals. This often limits the use of MRI, especially for high resolution or dynamic imaging. Accordingly, many investigators has developed various acceleration techniques to allow fast MR imaging. For the last two decades, one of the most important breakthroughs in this direction is the introduction of compressed sensing (CS) that allows accurate reconstruction from sparsely sampled k-space data. The recent FDA approval of compressed sensing products for clinical scans clearly reflect the maturity of this technology. Therefore, this paper reviews the basic idea of CS and how this technology have been evolved for various MR imaging problems.
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Affiliation(s)
- Jong Chul Ye
- Department of Bio and Brain Engineering, Korea Adv. Inst. of Science & Technology (KAIST), 291 Daehak-ro, Daejeon, Korea
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16
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Vidya Shankar R, Chang JC, Hu HH, Kodibagkar VD. Fast data acquisition techniques in magnetic resonance spectroscopic imaging. NMR IN BIOMEDICINE 2019; 32:e4046. [PMID: 30637822 DOI: 10.1002/nbm.4046] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 10/30/2018] [Accepted: 10/31/2018] [Indexed: 06/09/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per TR . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.
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Affiliation(s)
- Rohini Vidya Shankar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - John C Chang
- Banner M D Anderson Cancer Center, Gilbert, AZ, USA
- School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
| | - Houchun H Hu
- Department of Radiology and Medical Imaging, Phoenix Children's Hospital, Phoenix, AZ, USA
| | - Vikram D Kodibagkar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
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Zhang J, Feng L, Otazo R, Kim SG. Rapid dynamic contrast-enhanced MRI for small animals at 7T using 3D ultra-short echo time and golden-angle radial sparse parallel MRI. Magn Reson Med 2019; 81:140-152. [PMID: 30058079 PMCID: PMC6258350 DOI: 10.1002/mrm.27357] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/02/2018] [Accepted: 04/22/2018] [Indexed: 01/18/2023]
Abstract
PURPOSE To develop a rapid dynamic contrast-enhanced MRI method with high spatial and temporal resolution for small-animal imaging at 7 Tesla. METHODS An ultra-short echo time (UTE) pulse sequence using a 3D golden-angle radial sampling was implemented to achieve isotropic spatial resolution with flexible temporal resolution. Continuously acquired radial spokes were grouped into subsets for image reconstruction using a multicoil compressed sensing approach (Golden-angle RAdial Sparse Parallel; GRASP). The proposed 3D-UTE-GRASP method with high temporal and spatial resolutions was tested using 7 mice with GL261 intracranial glioma models. RESULTS Iterative reconstruction with different temporal resolutions and regularization factors λ showed that, in all cases, the cost function decreased to less than 2.5% of its starting value within 20 iterations. The difference between the time-intensity curves of 3D-UTE-GRASP and nonuniform fast Fourier transform (NUFFT) images was minimal when λ was 1% of the maximum signal intensity of the initial NUFFT images. The 3D isotropic images were used to generate pharmacokinetic parameter maps to show the detailed images of the tumor characteristics in 3D and also to show longitudinal changes during tumor growth. CONCLUSION This feasibility study demonstrated that the proposed 3D-UTE-GRASP method can be used for effective measurement of the 3D spatial heterogeneity of tumor pharmacokinetic parameters.
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Affiliation(s)
- Jin Zhang
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Li Feng
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Ricardo Otazo
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Sungheon Gene Kim
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
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Nassirpour S, Chang P, Avdievitch N, Henning A. Compressed sensing for high-resolution nonlipid suppressed 1 H FID MRSI of the human brain at 9.4T. Magn Reson Med 2018; 80:2311-2325. [PMID: 29707804 DOI: 10.1002/mrm.27225] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 03/06/2018] [Accepted: 03/26/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra-short TR and TE 1 H FID MRSI sequence at 9.4T. METHODS X-t sparse compressed sensing reconstruction was optimized for nonlipid suppressed 1 H FID MRSI data. Coil-by-coil x-t sparse reconstruction was compared with SENSE x-t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared. RESULTS Coil-by-coil x-t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x-t sparse). For acceleration factors of up to 5, both the low-rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved. CONCLUSION By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min.
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Affiliation(s)
- Sahar Nassirpour
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Paul Chang
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Nikolai Avdievitch
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
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19
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Lee SH, Lee YH, Suh JS. Accelerating knee MR imaging: Compressed sensing in isotropic three-dimensional fast spin-echo sequence. Magn Reson Imaging 2018; 46:90-97. [DOI: 10.1016/j.mri.2017.10.018] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Revised: 10/12/2017] [Accepted: 10/31/2017] [Indexed: 11/16/2022]
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20
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Chang P, Nassirpour S, Avdievitch N, Henning A. Non-water-suppressed1H FID-MRSI at 3T and 9.4T. Magn Reson Med 2017; 80:442-451. [DOI: 10.1002/mrm.27049] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 11/21/2017] [Accepted: 11/27/2017] [Indexed: 02/04/2023]
Affiliation(s)
- Paul Chang
- Max Planck Institute for Biological Cybernetics; Tuebingen Germany
- IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen; Germany
| | - Sahar Nassirpour
- Max Planck Institute for Biological Cybernetics; Tuebingen Germany
- IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen; Germany
| | - Nikolai Avdievitch
- Max Planck Institute for Biological Cybernetics; Tuebingen Germany
- Department of Physics; University of Greifswald; Germany
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics; Tuebingen Germany
- Department of Physics; University of Greifswald; Germany
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21
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Iqbal Z, Wilson NE, Thomas MA. Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation. Sci Rep 2017; 7:6262. [PMID: 28740202 PMCID: PMC5524913 DOI: 10.1038/s41598-017-04065-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Accepted: 05/08/2017] [Indexed: 11/14/2022] Open
Abstract
1H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.
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Affiliation(s)
- Zohaib Iqbal
- University of California - Los Angeles, Radiological Sciences, Los Angeles, California, 90095, USA
| | - Neil E Wilson
- University of California - Los Angeles, Radiological Sciences, Los Angeles, California, 90095, USA
| | - M Albert Thomas
- University of California - Los Angeles, Radiological Sciences, Los Angeles, California, 90095, USA.
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22
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Heikal AA, Wachowicz K, Fallone BG. Correlation between k-space sampling pattern and MTF in compressed sensing MRSI. Med Phys 2017; 43:5626. [PMID: 27782719 DOI: 10.1118/1.4962930] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To investigate the relationship between the k-space sampling patterns used for compressed sensing MR spectroscopic imaging (CS-MRSI) and the modulation transfer function (MTF) of the metabolite maps. This relationship may allow the desired frequency content of the metabolite maps to be quantitatively tailored when designing an undersampling pattern. METHODS Simulations of a phantom were used to calculate the MTF of Nyquist sampled (NS) 32 × 32 MRSI, and four-times undersampled CS-MRSI reconstructions. The dependence of the CS-MTF on the k-space sampling pattern was evaluated for three sets of k-space sampling patterns generated using different probability distribution functions (PDFs). CS-MTFs were also evaluated for three more sets of patterns generated using a modified algorithm where the sampling ratios are constrained to adhere to PDFs. RESULTS Strong visual correlation as well as high R2 was found between the MTF of CS-MRSI and the product of the frequency-dependant sampling ratio and the NS 32 × 32 MTF. Also, PDF-constrained sampling patterns led to higher reproducibility of the CS-MTF, and stronger correlations to the above-mentioned product. CONCLUSIONS The relationship established in this work provides the user with a theoretical solution for the MTF of CS MRSI that is both predictable and customizable to the user's needs.
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Affiliation(s)
- A A Heikal
- Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada and Departments of Oncology and Physics, University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada
| | - K Wachowicz
- Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada and Department of Oncology, University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada
| | - B G Fallone
- Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada and Departments of Oncology and Physics, University of Alberta, 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada
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Hatay GH, Yildirim M, Ozturk-Isik E. Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T. Med Biol Eng Comput 2016; 55:1303-1315. [PMID: 27826817 DOI: 10.1007/s11517-016-1591-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Accepted: 10/26/2016] [Indexed: 12/23/2022]
Abstract
The purpose of this study was to apply compressed sensing method for accelerated phosphorus MR spectroscopic imaging (31P-MRSI) of human brain in vivo at 3T. Fast 31P-MRSI data of five volunteers were acquired on a 3T clinical MR scanner using pulse-acquire sequence with a pseudorandom undersampling pattern for a data reduction factor of 5.33 and were reconstructed using compressed sensing. Additionally, simulated 31P-MRSI human brain tumor datasets were created to analyze the effects of k-space sampling pattern, data matrix size, regularization parameters of the reconstruction, and noise on the compressed sensing accelerated 31P-MRSI data. The 31P metabolite peak ratios of the full and compressed sensing accelerated datasets of healthy volunteers in vivo were similar according to the results of a Bland-Altman test. The estimated effective spatial resolution increased with reduction factor and sampling more at the k-space center. A lower regularization parameter for both total variation and L1-norm penalties resulted in a better compressed sensing reconstruction of 31P-MRSI. Although the root-mean-square error increased with noise levels, the compressed sensing reconstruction was robust for up to a reduction factor of 10 for the simulated data that had sharply defined tumor borders. As a result, compressed sensing was successfully applied to accelerate 31P-MRSI of human brain in vivo at 3T.
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Affiliation(s)
- Gokce Hale Hatay
- Biomedical Engineering Institute, Bogazici University, Rasathane Cad, Kandilli Campus, Kandilli Mah., 34684, Istanbul, Turkey
| | - Muhammed Yildirim
- Biomedical Engineering Institute, Bogazici University, Rasathane Cad, Kandilli Campus, Kandilli Mah., 34684, Istanbul, Turkey
| | - Esin Ozturk-Isik
- Biomedical Engineering Institute, Bogazici University, Rasathane Cad, Kandilli Campus, Kandilli Mah., 34684, Istanbul, Turkey.
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Laruelo A, Chaari L, Tourneret JY, Batatia H, Ken S, Rowland B, Ferrand R, Laprie A. Spatio-spectral regularization to improve magnetic resonance spectroscopic imaging quantification. NMR IN BIOMEDICINE 2016; 29:918-931. [PMID: 27166741 DOI: 10.1002/nbm.3532] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 03/14/2016] [Accepted: 03/15/2016] [Indexed: 06/05/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique able to provide the spatial distribution of relevant biochemical compounds commonly used as biomarkers of disease. Information provided by MRSI can be used as a valuable insight for the diagnosis, treatment and follow-up of several diseases such as cancer or neurological disorders. Obtaining accurate metabolite concentrations from in vivo MRSI signals is a crucial requirement for the clinical utility of this technique. Despite the numerous publications on the topic, accurate quantification is still a challenging problem due to the low signal-to-noise ratio of the data, overlap of spectral lines and the presence of nuisance components. We propose a novel quantification method, which alleviates these limitations by exploiting a spatio-spectral regularization scheme. In contrast to previous methods, the regularization terms are not expressed directly on the parameters being sought, but on appropriate transformed domains. In order to quantify all signals simultaneously in the MRSI grid, while introducing prior information, a fast proximal optimization algorithm is proposed. Experiments on synthetic MRSI data demonstrate that the error in the estimated metabolite concentrations is reduced by a mean of 41% with the proposed scheme. Results on in vivo brain MRSI data show the benefit of the proposed approach, which is able to fit overlapping peaks correctly and to capture metabolites that are missed by single-voxel methods due to their lower concentrations. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Andrea Laruelo
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
- University of Toulouse, IRIT - INP-ENSEEIHT, Toulouse, France
| | - Lotfi Chaari
- University of Toulouse, IRIT - INP-ENSEEIHT, Toulouse, France
- MIRACL Laboratory, Sfax, Tunisia
| | | | - Hadj Batatia
- University of Toulouse, IRIT - INP-ENSEEIHT, Toulouse, France
| | - Soléakhéna Ken
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
- INSERM UMR1214 TONIC, Toulouse, France
| | - Ben Rowland
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Régis Ferrand
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Anne Laprie
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
- INSERM UMR1214 TONIC, Toulouse, France
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Cao P, Shin PJ, Park I, Najac C, Marco-Rius I, Vigneron DB, Nelson SJ, Ronen SM, Larson PEZ. Accelerated high-bandwidth MR spectroscopic imaging using compressed sensing. Magn Reson Med 2016; 76:369-79. [PMID: 27228088 DOI: 10.1002/mrm.26272] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Revised: 03/27/2016] [Accepted: 04/19/2016] [Indexed: 12/12/2022]
Abstract
PURPOSE To develop a compressed sensing (CS) acceleration method with a high spectral bandwidth exploiting the spatial-spectral sparsity of MR spectroscopic imaging (MRSI). METHODS Accelerations were achieved using blip gradients during the readout to perform nonoverlapped and stochastically delayed random walks in kx -ky -t space, combined with block-Hankel matrix completion for efficient reconstruction. Both retrospective and prospective CS accelerations were applied to (13) C MRSI experiments, including in vivo rodent brain and liver studies with administrations of hyperpolarized [1-(13) C] pyruvate at 7.0 Tesla (T) and [2-(13) C] dihydroxyacetone at 3.0 T, respectively. RESULTS In retrospective undersampling experiments using in vivo 7.0 T data, the proposed method preserved spectral, spatial, and dynamic fidelities with R(2) ≥ 0.96 and ≥ 0.87 for pyruvate and lactate signals, respectively, 750-Hz spectral separation, and up to 6.6-fold accelerations. In prospective in vivo experiments, with 3.8-fold acceleration, the proposed method exhibited excellent spatial localization of metabolites and peak recovery for pyruvate and lactate at 7.0 T as well as for dihydroxyacetone and its metabolic products with a 4.5-kHz spectral span (140 ppm at 3.0 T). CONCLUSIONS This study demonstrated the feasibility of a new CS approach to accelerate high spectral bandwidth MRSI experiments. Magn Reson Med 76:369-379, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Peng Cao
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Peter J Shin
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Ilwoo Park
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Chloe Najac
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Irene Marco-Rius
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
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Compressed Sensing 3-Dimensional Time-of-Flight Magnetic Resonance Angiography for Cerebral Aneurysms. Invest Radiol 2016; 51:228-35. [DOI: 10.1097/rli.0000000000000226] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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27
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Zakian KL, Hatfield W, Aras O, Cao K, Yakar D, Goldman DA, Moskowitz CS, Shukla-Dave A, Tehrani YM, Fine S, Eastham J, Hricak H. Prostate MRSI predicts outcome in radical prostatectomy patients. Magn Reson Imaging 2016; 34:674-81. [PMID: 26821278 DOI: 10.1016/j.mri.2016.01.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Revised: 01/21/2016] [Accepted: 01/22/2016] [Indexed: 01/08/2023]
Abstract
BACKGROUND New non-invasive methods are needed for sub-stratifying high-risk prostate cancer patients. Magnetic resonance spectroscopic imaging (MRSI) maps metabolites in prostate cancer, providing information on tumor aggressiveness and volume. PURPOSE To investigate the correlation between MRSI and treatment failure (TF) after radical prostatectomy (RP). METHODS Two-hundred sixty-two patients who underwent endorectal MRI/MRSI followed by RP at our institution from 2003 to 2007 were studied. MRI stage, number of voxels in the MRSI index lesion (NILV), number of high-grade voxels (NHGV), and number of voxels containing undetectable polyamines (NUPV) were derived. Clinical outcome was followed until August, 2014. Treatment failure was defined as 1) biochemical recurrence (BCR), 2) persistently detectable PSA after RP, or 3) adjuvant therapy initiated in the absence of BCR. MRI/MRSI features and clinical parameters were compared to TF by univariate Cox Proportional Hazards Regression. After backward selection, each MRSI parameter was included in a separate regression model adjusted for NCCN-based clinical risk score (CRS), number of biopsy cores positive (NPC), and MRI stage. RESULTS In univariate analysis, all clinical variables were associated with TF in addition to MRI stage, NILV, NHGV, and NUPV. In multivariate analysis, NILV, NHGV, and NUPV were also significant risk factors for TF (p=0.016, p=0.002, p=0.006, respectively). The association between the number of tumor voxels with undetectable polyamines and the probability of treatment failure has not been previously reported. The number of MRSI cancer voxels correlated with extracapsular extension (ECE) (p<0.0001). CONCLUSIONS MRSI was associated with post-radical prostatectomy treatment failure in models adjusted for the number of positive biopsy cores and clinical risk score. This is the first report that in radical prostatectomy patients MRSI has an association with treatment failure independent of the number of positive biopsy cores. MRSI may help the clinician determine whether patients with high risk disease who undergo RP are candidates for specialized additional treatment.
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Affiliation(s)
- Kristen L Zakian
- Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, NY, NY, 10065, USA.
| | | | - Omer Aras
- MSKCC, 1275 York Avenue, NY, NY, 10065, USA.
| | - Kun Cao
- MSKCC, 1275 York Avenue, NY, NY, 10065, USA.
| | - Derya Yakar
- MSKCC, 1275 York Avenue, NY, NY, 10065, USA.
| | | | | | | | | | - Samson Fine
- MSKCC, 1275 York Avenue, NY, NY, 10065, USA.
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Nagarajan R, Iqbal Z, Burns B, Wilson NE, Sarma MK, Margolis DA, Reiter RE, Raman SS, Thomas MA. Accelerated echo planar J-resolved spectroscopic imaging in prostate cancer: a pilot validation of non-linear reconstruction using total variation and maximum entropy. NMR IN BIOMEDICINE 2015; 28:1366-73. [PMID: 26346702 PMCID: PMC4618758 DOI: 10.1002/nbm.3373] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Revised: 07/16/2015] [Accepted: 07/17/2015] [Indexed: 05/27/2023]
Abstract
The overlap of metabolites is a major limitation in one-dimensional (1D) spectral-based single-voxel MRS and multivoxel-based MRSI. By combining echo planar spectroscopic imaging (EPSI) with a two-dimensional (2D) J-resolved spectroscopic (JPRESS) sequence, 2D spectra can be recorded in multiple locations in a single slice of prostate using four-dimensional (4D) echo planar J-resolved spectroscopic imaging (EP-JRESI). The goal of the present work was to validate two different non-linear reconstruction methods independently using compressed sensing-based 4D EP-JRESI in prostate cancer (PCa): maximum entropy (MaxEnt) and total variation (TV). Twenty-two patients with PCa with a mean age of 63.8 years (range, 46-79 years) were investigated in this study. A 4D non-uniformly undersampled (NUS) EP-JRESI sequence was implemented on a Siemens 3-T MRI scanner. The NUS data were reconstructed using two non-linear reconstruction methods, namely MaxEnt and TV. Using both TV and MaxEnt reconstruction methods, the following observations were made in cancerous compared with non-cancerous locations: (i) higher mean (choline + creatine)/citrate metabolite ratios; (ii) increased levels of (choline + creatine)/spermine and (choline + creatine)/myo-inositol; and (iii) decreased levels of (choline + creatine)/(glutamine + glutamate). We have shown that it is possible to accelerate the 4D EP-JRESI sequence by four times and that the data can be reliably reconstructed using the TV and MaxEnt methods. The total acquisition duration was less than 13 min and we were able to detect and quantify several metabolites.
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Affiliation(s)
- Rajakumar Nagarajan
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Zohaib Iqbal
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Brian Burns
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Neil E. Wilson
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Manoj K. Sarma
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Daniel A. Margolis
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Robert E. Reiter
- Urology, University of California Los Angeles, Los Angeles, CA, United States
| | - Steven S. Raman
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - M. Albert Thomas
- Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States
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Jaspan ON, Fleysher R, Lipton ML. Compressed sensing MRI: a review of the clinical literature. Br J Radiol 2015; 88:20150487. [PMID: 26402216 DOI: 10.1259/bjr.20150487] [Citation(s) in RCA: 194] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
MRI is one of the most dynamic and safe imaging techniques available in the clinic today. However, MRI acquisitions tend to be slow, limiting patient throughput and limiting potential indications for use while driving up costs. Compressed sensing (CS) is a method for accelerating MRI acquisition by acquiring less data through undersampling of k-space. This has the potential to mitigate the time-intensiveness of MRI. The limited body of research evaluating the effects of CS on MR images has been mostly positive with regards to its potential as a clinical tool. Studies have successfully accelerated MRI with this technology, with varying degrees of success. However, more must be performed before its diagnostic efficacy and benefits are clear. Studies involving a greater number radiologists and images must be completed, rating CS based on its diagnostic efficacy. Also, standardized methods for determining optimal imaging parameters must be developed.
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Affiliation(s)
- Oren N Jaspan
- 1 Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Roman Fleysher
- 2 The Gruss Magnetic Resonance Research Center, Department of Radiology, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Michael L Lipton
- 3 The Gruss Magnetic Resonance Research Center, Departments of Radiology, Psychiatry and Behavioral Sciences and The Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, The Bronx, NY, USA
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Maguire ML, Geethanath S, Lygate CA, Kodibagkar VD, Schneider JE. Compressed sensing to accelerate magnetic resonance spectroscopic imaging: evaluation and application to 23Na-imaging of mouse hearts. J Cardiovasc Magn Reson 2015; 17:45. [PMID: 26073300 PMCID: PMC4466859 DOI: 10.1186/s12968-015-0149-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Accepted: 05/15/2015] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Magnetic Resonance Spectroscopic Imaging (MRSI) has wide applicability for non-invasive biochemical assessment in clinical and pre-clinical applications but suffers from long scan times. Compressed sensing (CS) has been successfully applied to clinical 1H MRSI, however a detailed evaluation of CS for conventional chemical shift imaging is lacking. Here we evaluate the performance of CS accelerated MRSI, and specifically apply it to accelerate 23Na-MRSI on mouse hearts in vivo at 9.4 T. METHODS Synthetic phantom data representing a simplified section across a mouse thorax were used to evaluate the fidelity of the CS reconstruction for varying levels of under-sampling, resolution and signal-to-noise ratios (SNR). The amplitude of signals arising from within a compartment, and signal contamination arising from outside the compartment relative to noise-free Fourier-transformed (FT) data were determined. Simulation results were subsequently verified experimentally in phantoms and in three mouse hearts in vivo. RESULTS CS reconstructed MRSI data are scaled linearly relative to absolute signal intensities from the fully-sampled FT reconstructed case (R(2) > 0.8, p-value < 0.001). Higher acceleration factors resulted in a denoising of the reconstructed spectra, but also in an increased blurring of compartment boundaries, particularly at lower spatial resolutions. Increasing resolution and SNR decreased cross-compartment contamination and yielded signal amplitudes closer to the FT data. Proof-of-concept high-resolution, 3-fold accelerated 23Na-amplitude maps of murine myocardium could be obtained within ~23 mins. CONCLUSIONS Relative signal amplitudes (i.e. metabolite ratios) and absolute quantification of metabolite concentrations can be accurately determined with up to 5-fold under-sampled, CS-reconstructed MRSI. Although this work focused on murine cardiac 23Na-MRSI, the results are equally applicable to other nuclei and tissues (e.g., 1H MRSI in brain). Significant reduction in MRSI scan time will reduce the burden on the subject, increase scanner throughput, and may open new avenues for (pre-) clinical metabolic studies.
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Affiliation(s)
- Mahon L Maguire
- British Heart Foundation Experimental Magnetic Resonance Unit, Radcliffe Department of Medicine - Division of Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Sairam Geethanath
- Medical Imaging Research Centre, Dayananda Sagar College of Engineering, Bangalore, 560078, India
| | - Craig A Lygate
- British Heart Foundation Experimental Magnetic Resonance Unit, Radcliffe Department of Medicine - Division of Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK
| | - Vikram D Kodibagkar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA
| | - Jürgen E Schneider
- British Heart Foundation Experimental Magnetic Resonance Unit, Radcliffe Department of Medicine - Division of Cardiovascular Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK.
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Ganji SK, Maher EA, Choi C. In vivo (1)H MRSI of glycine in brain tumors at 3T. Magn Reson Med 2015; 75:52-62. [PMID: 25651788 DOI: 10.1002/mrm.25588] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 11/06/2014] [Accepted: 11/28/2014] [Indexed: 01/10/2023]
Abstract
PURPOSE MR spectroscopic imaging (SI) of glycine (Gly) in the human brain is challenging due to the interference of the abundant neighboring J-coupled resonances. Our aim is to accomplish reliable imaging of Gly in healthy brain and brain tumors using an optimized MR sequence scheme at 3 tesla. METHODS Two-dimensional (1)H SI was performed with a point-resolved spectroscopy scheme. An echo time of 160 ms was used for separation between Gly and myo-inositol signals. Data were collected from eight healthy volunteers and 14 subjects with gliomas. Spectra were analyzed with the linear combination model using numerically calculated basis spectra. Metabolite concentrations were estimated with reference to creatine in white matter (WM) regions at 6.4 molar concentrations (mM). RESULTS From a linear regression analysis with respect to the fractional gray matter (GM) content, the Gly concentrations in pure GM and WM in healthy brains were estimated to be 1.1 and 0.3 mM, respectively. Gly was significantly elevated in tumors. The tumor-to-contralateral Gly concentration ratio was more extensive with higher grades, showing ∼ 10-fold elevation of Gly in glioblastomas. CONCLUSION The Gly level is significantly different between GM and WM in healthy brains. Our data indicate that SI of Gly may provide a biomarker of brain tumor malignancy.
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Affiliation(s)
- Sandeep K Ganji
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Elizabeth A Maher
- Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Annette Strauss Center for Neuro-Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Changho Choi
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Birch R, Peet AC, Arvanitis TN, Wilson M. Sensitivity encoding for fast (1) H MR spectroscopic imaging water reference acquisition. Magn Reson Med 2014; 73:2081-6. [PMID: 25046769 DOI: 10.1002/mrm.25355] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2014] [Revised: 06/10/2014] [Accepted: 06/14/2014] [Indexed: 12/25/2022]
Abstract
PURPOSE Accurate and fast (1) H MR spectroscopic imaging (MRSI) water reference scans are important for absolute quantification of metabolites. However, the additional acquisition time required often precludes the water reference quantitation method for MRSI studies. Sensitivity encoding (SENSE) is a successful MR technique developed to reduce scan time. This study quantitatively assesses the accuracy of SENSE for water reference MRSI data acquisition, compared with the more commonly used reduced resolution technique. METHODS 2D MRSI water reference data were collected from a phantom and three volunteers at 3 Tesla for full acquisition (306 s); 2× reduced resolution (64 s) and SENSE R = 3 (56 s) scans. Water amplitudes were extracted using MRS quantitation software (TARQUIN). Intensity maps and Bland-Altman statistics were generated to assess the accuracy of the fast-MRSI techniques. RESULTS The average mean and standard deviation of differences from the full acquisition were 2.1 ± 3.2% for SENSE and 10.3 ± 10.7% for the reduced resolution technique, demonstrating that SENSE acquisition is approximately three times more accurate than the reduced resolution technique. CONCLUSION SENSE was shown to accurately reconstruct water reference data for the purposes of in vivo absolute metabolite quantification, offering significant improvement over the more commonly used reduced resolution technique.
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Affiliation(s)
- Rebecca Birch
- PSIBS Doctoral Training Centre, University of Birmingham, United Kingdom.,Department of Oncology, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
| | - Andrew C Peet
- Department of Oncology, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom.,School of Cancer Sciences, University of Birmingham, United Kingdom
| | - Theodoros N Arvanitis
- Department of Oncology, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom.,Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom
| | - Martin Wilson
- Department of Oncology, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom.,School of Cancer Sciences, University of Birmingham, United Kingdom
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Jambor I, Kähkönen E, Taimen P, Merisaari H, Saunavaara J, Alanen K, Obsitnik B, Minn H, Lehotska V, Aronen HJ. Prebiopsy multiparametric 3T prostate MRI in patients with elevated PSA, normal digital rectal examination, and no previous biopsy. J Magn Reson Imaging 2014; 41:1394-404. [PMID: 24956412 DOI: 10.1002/jmri.24682] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Accepted: 06/06/2014] [Indexed: 12/22/2022] Open
Abstract
PURPOSE To find the diagnostic accuracy of 3T multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted transrectal ultrasound (TRUS)-guided biopsy using visual coregistration (TB) in patients with elevated prostate-specific antigen (PSA), normal digital rectal examination, and no previous biopsy. MATERIALS AND METHODS Fifty-five patients at two institutions underwent mpMRI, consisting of anatomical T2 -weighted imaging (T2 W), diffusion-weighted imaging (DWI), proton magnetic resonance spectroscopy ((1) H-MRS), and dynamic contrast-enhanced MRI (DCE-MRI), followed by TB in addition to 12 core systematic TRUS-guided biopsy (SB). Histopathological scorings of biopsy (n = 38) and prostatectomy (n = 17) specimens were used as the reference standard for calculation of diagnostic accuracy values. Clinically significant prostate cancer (SPCa) was defined as 3 mm core length of Gleason score 3+3 or any Gleason grade 4. RESULTS The sensitivity, specificity, accuracy, and area under the curve (AUC) values for the detection of SPCa on the sextant level for T2 W+DWI+(1) H-MRS+DCE-MRI were 72%, 89%, 85%, and 0.81, respectively. The corresponding values for T2 wi+DWI were 61%, 96%, 87%, and 0.79, respectively. The overall PCa detection rate per core in 53 patients was 21% (138 of 648 cores) for SB and 43% (33 of 77 cores) for TB (P < 0.001). CONCLUSION Prebiopsy mpMRI is an accurate tool for PCa detection and biopsy targeting in patients with elevated PSA.
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Affiliation(s)
- Ivan Jambor
- Department of Diagnostic Radiology, University of Turku, Turku, Finland
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Merhej D, Ratiney H, Diab C, Khalil M, Sdika M, Prost R. Fast multidimensional NMR spectroscopy for sparse spectra. NMR IN BIOMEDICINE 2014; 27:640-655. [PMID: 24664959 DOI: 10.1002/nbm.3100] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2011] [Revised: 01/04/2014] [Accepted: 02/10/2014] [Indexed: 06/03/2023]
Abstract
Multidimensional NMR spectroscopy is widely used for studies of molecular and biomolecular structure. A major disadvantage of multidimensional NMR is the long acquisition time which, regardless of sensitivity considerations, may be needed to obtain the final multidimensional frequency domain coefficients. In this article, a method for under-sampling multidimensional NMR acquisition of sparse spectra is presented. The approach is presented in the case of two-dimensional NMR acquisitions. It relies on prior knowledge about the support in the two-dimensional frequency domain to recover an over-determined system from the under-determined system induced in the linear acquisition model when under-sampled acquisitions are performed. This over-determined system can then be solved with linear least squares. The prior knowledge is obtained efficiently at a low cost from the one-dimensional NMR acquisition, which is generally acquired as a first step in multidimensional NMR. If this one-dimensional acquisition is intrinsically sparse, it is possible to reconstruct the corresponding two-dimensional acquisition from far fewer observations than those imposed by the Nyquist criterion, and subsequently to reduce the acquisition time. Further improvements are obtained by optimizing the sampling procedure for the least-squares reconstruction using the sequential backward selection algorithm. Theoretical and experimental results are given in the case of a traditional acquisition scheme, which demonstrate reliable and fast reconstructions with acceleration factors in the range 3-6. The proposed method outperforms the CS methods (OMP, L1) in terms of the reconstruction performance, implementation and computation time. The approach can be easily extended to higher dimensions and spectroscopic imaging.
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Affiliation(s)
- Dany Merhej
- Université de Lyon, CREATIS; CNRS UMR5220; Inserm U1044; INSA-Lyon; Université Lyon 1, France; ISAE, Cnam Liban, Beirut, Lebanon
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Cao P, Wu EX. Accelerating phase-encoded proton MR spectroscopic imaging by compressed sensing. J Magn Reson Imaging 2014; 41:487-95. [PMID: 24436225 DOI: 10.1002/jmri.24553] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2013] [Accepted: 12/03/2013] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To develop a phase encoding reduction scheme based on compressed sensing (CS) for phase-encoded (1) H MR spectroscopic imaging (MRSI). MATERIALS AND METHODS Phantom and in vivo rat brain MRSI experiments were performed at 7 Tesla to examine the performance of CS approach and compare it with the full k-space acquisition. The CS undersampling was performed by acquiring a pseudorandom and density-varying subset of phase encodings. Residual water resonance was first removed from the undersampled k-space dataset before CS reconstruction. The CS reconstruction was performed by a linearized Bregman iteration procedure for efficiency in computing large scale L1 minimization. The spectral and spatial fidelity was evaluated by comparing spectral linewidths and metabolite maps and voxel-wise Bland-Altman analysis. RESULTS CS preserved the spectral resolution and metabolite content levels. No spectral broadening was observed, and the estimation biases of the metabolite content levels were no more than 4%. CS clearly preserved the boundaries of metabolite maps but led to slight loss of details in metabolite maps. CONCLUSION This study demonstrated the feasibility of the proposed CS approach to accelerate phase-encoded (1) H MRSI.
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Affiliation(s)
- Peng Cao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China; Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
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Kobus T, Wright AJ, Scheenen TWJ, Heerschap A. Mapping of prostate cancer by 1H MRSI. NMR IN BIOMEDICINE 2014; 27:39-52. [PMID: 23761200 DOI: 10.1002/nbm.2973] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Revised: 04/08/2013] [Accepted: 04/13/2013] [Indexed: 06/02/2023]
Abstract
In many studies, it has been demonstrated that (1)H MRSI of the human prostate has great potential to aid prostate cancer management, e.g. in the detection and localisation of cancer foci in the prostate or in the assessment of its aggressiveness. It is particularly powerful in combination with T2 -weighted MRI. Nevertheless, the technique is currently mainly used in a research setting. This review provides an overview of the state-of-the-art of three-dimensional MRSI, including the specific hardware required, dedicated data acquisition sequences and information on the spectral content with background on the MR-visible metabolites. In clinical practice, it is important that relevant MRSI results become available rapidly, reliably and in an easy digestible way. However, this functionality is currently not fully available for prostate MRSI, which is a major obstacle for routine use by inexperienced clinicians. Routine use requires more automation in the processing of raw data than is currently available. Therefore, we pay specific attention in this review on the status and prospects of the automated handling of prostate MRSI data, including quality control. The clinical potential of three-dimensional MRSI of the prostate is illustrated with literature examples on prostate cancer detection, its localisation in the prostate, its role in the assessment of cancer aggressiveness and in the selection and monitoring of therapy.
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Affiliation(s)
- Thiele Kobus
- Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
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Heikal AA, Wachowicz K, Fallone BG. MTF behavior of compressed sensing MR spectroscopic imaging. Med Phys 2013; 40:052302. [PMID: 23635289 DOI: 10.1118/1.4800642] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To investigate the modulation transfer function (MTF) behavior of compressed sensing (CS) MR spectroscopic imaging (MRSI) with regard to CS reconstruction weights and the acquired peak signal-to-noise ratio (SNR); which may have an effect on MTF due to the nonlinear nature of the CS reconstruction process. METHODS A specially designed phantom consisting of wedges arranged in a fan pattern was used to calculate the MTF of the MRSI scans. Arc profiles of the phantom yield a square wave with a spatial frequency inversely proportional to the radius of the profile. The MTF was derived by considering the amplitude ratio of the fundamental frequency between the ideal square wave and the reconstructed output. As compressed sensing relies on nonlinear reconstruction and a minimization algorithm that requires the definition of reconstruction weights, the behavior of the MTF with respect to the choice of reconstruction weights and peak SNR is not intuitive. As such, simulations were used to investigate the response of the MTF to CS reconstruction weights at varying peak SNRs. The resulting optimized reconstruction weight was used to reconstruct an experimental CS-MRSI scan of the phantom and compare the corresponding MTF to those of a fully sampled dataset, and a time-equivalent Nyquist-sampled low-resolution dataset. RESULTS Simulations showed that MTFs of CS-MRSI datasets varied widely with different reconstruction weights. Moreover, the response of the MTF to peak SNR was not consistent across the range of reconstruction weights. An optimized reconstruction weight was derived from the simulations and used in reconstructing the experimental dataset. The MTF of the experimental CS-MRSI dataset showed improvement over the equivalent Nyquist sampled dataset at the resolution limit of 0.1 MTF, while it suffered from reduced response at low resolutions between 0.4 and 0.8 lp/cm. CONCLUSIONS The authors have shown that in certain cases small variations in the reconstruction weights yield a measureable effect on the CS reconstructed images, particularly with regard to MTF. Furthermore, it was found that peak SNR affects CS-MRSI MTF especially at higher wavelet reconstruction weights. Accordingly, prior knowledge of the expected peak SNR is essential to optimize the CS reconstruction process. Their phantom-MTF technique provides a quantitative performance measure of MRSI sequences, through which they were able to quantify a loss of 32.4% in spatial resolution for CS-MRSI at 0.1 MTF compared to a loss of 48.6% for the time-equivalent Nyquist-sampled low-resolution scans. They also showed that CS-MRSI suffered decreased low-resolution response as opposed to the equivalent low-resolution datasets.
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Affiliation(s)
- A A Heikal
- Department of Medical Physics, Cross Cancer Institute 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada.
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Yu JX, Hallac RR, Chiguru S, Mason RP. New frontiers and developing applications in 19F NMR. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2013; 70:25-49. [PMID: 23540575 PMCID: PMC3613763 DOI: 10.1016/j.pnmrs.2012.10.001] [Citation(s) in RCA: 142] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2012] [Accepted: 10/23/2012] [Indexed: 05/06/2023]
Affiliation(s)
- Jian-Xin Yu
- Laboratory of Prognostic Radiology, Division of Advanced Radiological Sciences, Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Rami R. Hallac
- Laboratory of Prognostic Radiology, Division of Advanced Radiological Sciences, Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Srinivas Chiguru
- Laboratory of Prognostic Radiology, Division of Advanced Radiological Sciences, Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Ralph P. Mason
- Laboratory of Prognostic Radiology, Division of Advanced Radiological Sciences, Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
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