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Bugler H, Berto R, Souza R, Harris AD. Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks. Magn Reson Imaging 2024; 111:186-195. [PMID: 38744351 DOI: 10.1016/j.mri.2024.05.008] [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] [Received: 10/18/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edited magnetic resonance spectroscopy (MRS) data. METHODS An ablation study using simulated data was performed to determine the most effective input (real or complex) and convolution type (real or complex) to predict frequency and phase shifts in GABA-edited MEGA-PRESS data using CNNs. The best CNN model was subsequently compared using both simulated and in vivo data to two recently proposed deep learning (DL) methods for FPC of GABA-edited MRS. All methods were trained using the same experimental setup and evaluated using the signal-to-noise ratio (SNR) and linewidth of the GABA peak, choline artifact, and by visually assessing the reconstructed final difference spectrum. Statistical significance was assessed using the Wilcoxon signed rank test. RESULTS The ablation study showed that using complex values for the input represented by real and imaginary channels in our model input tensor, with complex convolutions was most effective for FPC. Overall, in the comparative study using simulated data, our CC-CNN model (that received complex-valued inputs with complex convolutions) outperformed the other models as evaluated by the mean absolute error. CONCLUSION Our results indicate that the optimal CNN configuration for GABA-edited MRS FPC uses a complex-valued input and complex convolutions. Overall, this model outperformed existing DL models.
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Affiliation(s)
- Hanna Bugler
- Department of Biomedical Engineering, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada.
| | - Rodrigo Berto
- Department of Biomedical Engineering, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada
| | - Roberto Souza
- Hotchkiss Brain Institute, University of Calgary,Canada; Department of Electrical and Software Engineering, University of Calgary, Canada
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada
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2
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Liu H, Autry AW, Larson PEZ, Xu D, Li Y. Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T. Tomography 2023; 9:1592-1602. [PMID: 37736980 PMCID: PMC10514830 DOI: 10.3390/tomography9050127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism. METHODS Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed. RESULTS The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers. CONCLUSION This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.
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Affiliation(s)
- Huawei Liu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94107, USA (A.W.A.); (P.E.Z.L.); (D.X.)
| | - Adam W. Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94107, USA (A.W.A.); (P.E.Z.L.); (D.X.)
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94107, USA (A.W.A.); (P.E.Z.L.); (D.X.)
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA 94107, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94107, USA (A.W.A.); (P.E.Z.L.); (D.X.)
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA 94107, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94107, USA (A.W.A.); (P.E.Z.L.); (D.X.)
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3
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Choi SH, Ryu YC, Chung JY. Baseline Correction of the Human 1H MRS(I) Spectrum Using T 2* Selective Differential Operators in the Frequency Domain. Metabolites 2022; 12:metabo12121257. [PMID: 36557294 PMCID: PMC9787948 DOI: 10.3390/metabo12121257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
The baseline distortion caused by water and fat signals is a crucial issue in the 1H MRS(I) study of the human brain. This paper suggests an effective and reliable preprocessing technique to calibrate the baseline distortion caused by the water and fat signals exhibited in the MRS spectral signal. For the preprocessing, we designed a T2* (or linewidth within the spectral signal) selective filter for the MRS(I) data based on differential filtering within the frequency domain. The number and types for the differential filtering were determined by comparing the T2* selectivity profile of each differential operator with the T2* profile of the metabolites to be suppressed within the MRS(I) data. In the performance evaluation of the proposed differential filtering, the simulation data for MRS spectral signals were used. Furthermore, the spectral signal of the human 1H MRSI data obtained by 2D free induction decay chemical shift imaging with a typical water suppression technique was also used in the performance evaluation. The absolute values of the average of the filtered dataset were quantitatively analyzed using the LCModel software. With the suggested T2* selective (not frequency selective) filtering technique, in the simulated MRS data, we removed the metabolites from the simulated MRS(I) spectral signal baseline distorted by the water and fat signal observed in the most frequency band. Moreover, in the obtained MRSI data, the quantitative analysis results for the metabolites of interest showed notable improvement in the uncertainty estimation accuracy, the CRLB (Cramer-Rao Lower Bound) levels.
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Affiliation(s)
- Sang-Han Choi
- Center for Neuroscience Imaging Research, IBS, N Center, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, Republic of Korea
| | - Yeun-Chul Ryu
- Department of Radiological Science, College of Health Science, Gachon University, 191 Hambangmoe-ro, Yeonsu-gu, Incheon 21936, Republic of Korea
- Correspondence: (Y.-C.R.); (J.-Y.C.); Tel.: +82-32-822-5361 (J.-Y.C.)
| | - Jun-Young Chung
- Department of Neuroscience, College of Medicine, Gachon University, 21, Namdong-daero 774 beon-gil, Namdong-gu, Incheon 21565, Republic of Korea
- Correspondence: (Y.-C.R.); (J.-Y.C.); Tel.: +82-32-822-5361 (J.-Y.C.)
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4
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Truszkiewicz A, Bartusik-Aebisher D, Zalejska-Fiolka J, Kawczyk-Krupka A, Aebisher D. Cellular Lactate Spectroscopy Using 1.5 Tesla Clinical Apparatus. Int J Mol Sci 2022; 23:ijms231911355. [PMID: 36232656 PMCID: PMC9570142 DOI: 10.3390/ijms231911355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/11/2022] [Accepted: 09/23/2022] [Indexed: 11/22/2022] Open
Abstract
Cellular lactate is a key cellular metabolite and marker of anaerobic glycolysis. Cellular lactate uptake, release, production from glucose and glycogen, and interconversion with pyruvate are important determinants of cellular energy. It is known that lactate is present in the spectrum of neoplasms and low malignancy (without necrotic lesions). Also, the appearance of lactate signals is associated with anaerobic glucose, mitochondrial dysfunction, and other inflammatory responses. The aim of this study was the detection of lactate in cell cultures with the use of proton magnetic resonance (1H MRS) and a 1.5 Tesla clinical apparatus (MR OPTIMA 360), characterized as a medium-field system. In this study, selected metabolites, together with cellular lactate, were identified with the use of an appropriate protocol and management algorithm. This paper describes the results obtained for cancer cell cultures. This medium-field system has proven the possibility of detecting small molecules, such as lactate, with clinical instruments. 1H MRS performed using clinical MR apparatus is a useful tool for clinical analysis.
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Affiliation(s)
- Adrian Truszkiewicz
- Department of Photomedicine and Physical Chemistry, Medical College of The University of Rzeszow, University of Rzeeszów, 35-310 Rzeszów, Poland
| | - Dorota Bartusik-Aebisher
- Department of Biochemistry and General Chemistry, Medical College of The University of Rzeszow, University of Rzeszów, 35-310 Rzeszów, Poland
| | - Jolanta Zalejska-Fiolka
- Department of Biochemistry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-055 Katowice, Poland
| | - Aleksandra Kawczyk-Krupka
- Center for Laser Diagnostics and Therapy, Department of Internal Medicine, Angiology and Physical Medicine, Medical University of Silesia in Katowice, 41-902 Bytom, Poland
| | - David Aebisher
- Department of Photomedicine and Physical Chemistry, Medical College of The University of Rzeszow, University of Rzeeszów, 35-310 Rzeszów, Poland
- Correspondence:
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5
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Stamatelatou A, Scheenen TWJ, Heerschap A. Developments in proton MR spectroscopic imaging of prostate cancer. MAGMA (NEW YORK, N.Y.) 2022; 35:645-665. [PMID: 35445307 PMCID: PMC9363347 DOI: 10.1007/s10334-022-01011-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/04/2022] [Accepted: 03/22/2022] [Indexed: 10/25/2022]
Abstract
In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Tom W J Scheenen
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
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6
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Fear EJ, Kennerley AJ, Rayner PJ, Norcott P, Roy SS, Duckett SB. SABRE hyperpolarized anticancer agents for use in
1
H MRI. Magn Reson Med 2022; 88:11-27. [PMID: 35253267 PMCID: PMC9310590 DOI: 10.1002/mrm.29166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/20/2021] [Accepted: 01/05/2022] [Indexed: 11/30/2022]
Abstract
Purpose Enabling drug tracking (distribution/specific pathways) with magnetic resonance spectroscopy requires manipulation (via hyperpolarization) of spin state populations and targets with sufficiently long magnetic lifetimes to give the largest possible window of observation. Here, we demonstrate how the proton resonances of a group of thienopyridazines (with known anticancer properties), can be amplified using the para‐hydrogen (p‐H2) based signal amplification by reversible exchange (SABRE) hyperpolarization technique. Methods Thienopyridazine isomers, including a 2H version, were synthesized in house. Iridium‐based catalysts dissolved in a methanol‐d4 solvent facilitated polarization transfer from p‐H2 gas to the target thienopyridazines. Subsequent SABRE 1H responses of hyperpolarized thienopyridazines were completed (400 MHz NMR). Pseudo‐singlet state approaches were deployed to extend magnetic state lifetimes. Proof of principle spectral‐spatial images were acquired across a range of field strengths (7T‐9.4T MRI). Results 1H‐NMR signal enhancements of −10,130‐fold at 9.4T (~33% polarization) were achieved on thieno[2,3‐d]pyridazine (T[2,3‐d]P), using SABRE under optimal mixing/field transfer conditions. 1H T1 lifetimes for the thienopyridazines were ~18‐50 s. Long‐lived state approaches extended the magnetic lifetime of target proton sites in T[2,3‐d]P from an average of 25‐40 seconds. Enhanced in vitro imaging (spatial and chemical shift based) of target T[2,3‐d]P was demonstrated. Conclusion Here, we demonstrate the power of SABRE to deliver a fast and cost‐effective route to hyperpolarization of important chemical motifs of anticancer agents. The SABRE approach outlined here lays the foundations for realizing continuous flow, hyperpolarized tracking of drug delivery/pathways.
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Affiliation(s)
| | - Aneurin J. Kennerley
- Centre for Hyperpolarisation in Magnetic Resonance (CHyM) University of York York United Kingdom
| | - Peter J. Rayner
- Centre for Hyperpolarisation in Magnetic Resonance (CHyM) University of York York United Kingdom
| | - Philip Norcott
- Research School of Chemistry Australian National University Canberra Australia
| | - Soumya S. Roy
- School of Chemistry University of Southampton Southampton United Kingdom
- Defence Science and Technology Laboratory (DSTL) Salisbury United Kingdom
| | - Simon B. Duckett
- Centre for Hyperpolarisation in Magnetic Resonance (CHyM) University of York York United Kingdom
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7
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Song Y, Lally PJ, Yanez Lopez M, Oeltzschner G, Nebel MB, Gagoski B, Kecskemeti S, Hui SCN, Zöllner HJ, Shukla D, Arichi T, De Vita E, Yedavalli V, Thayyil S, Fallin D, Dean DC, Grant PE, Wisnowski JL, Edden RAE. Edited magnetic resonance spectroscopy in the neonatal brain. Neuroradiology 2022; 64:217-232. [PMID: 34654960 PMCID: PMC8887832 DOI: 10.1007/s00234-021-02821-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/20/2021] [Indexed: 10/20/2022]
Abstract
J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter J Lally
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Yanez Lopez
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Deepika Shukla
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Tomoki Arichi
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Enrico De Vita
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas's Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London, SE1 7EH, UK
| | - Vivek Yedavalli
- Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA
| | - Sudhin Thayyil
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Baltimore, USA.,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Douglas C Dean
- Waisman Center, University of WI-Madison, Madison, WI, 53705, USA.,Department of Pediatrics, Division of Neonatology and Newborn Nursery, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA.,Department of Medical Physics, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA
| | - P Ellen Grant
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Medicine, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jessica L Wisnowski
- Children's Hospital Los Angeles, Los Angeles, CA, 90027, USA.,Department of Radiology and Fetal and Neonatal Institute, CHLA Division of Neonatology, Department of Pediatrics, Children's Hospital of Los Angeles, University of Southern California, Los Angeles, CA, 90033, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA.
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8
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Song Y, Zöllner HJ, Hui SCN, Hupfeld K, Oeltzschner G, Prisciandaro JJ, Edden R. Importance of Linear Combination Modeling for Quantification of Glutathione and γ-Aminobutyric Acid Levels Using Hadamard-Edited Magnetic Resonance Spectroscopy. Front Psychiatry 2022; 13:872403. [PMID: 35546940 PMCID: PMC9082488 DOI: 10.3389/fpsyt.2022.872403] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/07/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND J-difference-edited 1H-MR spectra require modeling to quantify signals of low-concentration metabolites. Two main approaches are used for this spectral modeling: simple peak fitting and linear combination modeling (LCM) with a simulated basis set. Recent consensus recommended LCM as the method of choice for the spectral analysis of edited data. PURPOSE The aim of this study is to compare the performance of simple peak fitting and LCM in a test-retest dataset, hypothesizing that the more sophisticated LCM approach would improve quantification of Hadamard-edited data compared with simple peak fitting. METHODS A test-retest dataset was re-analyzed using Gannet (simple peak fitting) and Osprey (LCM). These data were obtained from the dorsal anterior cingulate cortex of twelve healthy volunteers, with TE = 80 ms for HERMES and TE = 120 ms for MEGA-PRESS of glutathione (GSH). Within-subject coefficients of variation (CVs) were calculated to quantify between-scan reproducibility of each metabolite estimate. RESULTS The reproducibility of HERMES GSH estimates was substantially improved using LCM compared to simple peak fitting, from a CV of 19.0-9.9%. For MEGA-PRESS GSH data, reproducibility was similar using LCM and simple peak fitting, with CVs of 7.3 and 8.8%. GABA + CVs from HERMES were 16.7 and 15.2%, respectively for the two models. CONCLUSION LCM with simulated basis functions substantially improved the reproducibility of GSH quantification for HERMES data.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kathleen Hupfeld
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Addiction Sciences Division, Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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9
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Fatty Acid Metabolism Reprogramming in Advanced Prostate Cancer. Metabolites 2021; 11:metabo11110765. [PMID: 34822423 PMCID: PMC8618281 DOI: 10.3390/metabo11110765] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 11/01/2021] [Accepted: 11/03/2021] [Indexed: 12/23/2022] Open
Abstract
Prostate cancer (PCa) is a carcinoma in which fatty acids are abundant. Fatty acid metabolism is rewired during PCa development. Although PCa can be treated with hormone therapy, after prolonged treatment, castration-resistant prostate cancer can develop and can lead to increased mortality. Changes to fatty acid metabolism occur systemically and locally in prostate cancer patients, and understanding these changes may lead to individualized treatments, especially in advanced, castration-resistant prostate cancers. The fatty acid metabolic changes are not merely reflective of oncogenic activity, but in many cases, these represent a critical factor in cancer initiation and development. In this review, we analyzed the literature regarding systemic changes to fatty acid metabolism in PCa patients and how these changes relate to obesity, diet, circulating metabolites, and peri-prostatic adipose tissue. We also analyzed cellular fatty acid metabolism in prostate cancer, including fatty acid uptake, de novo lipogenesis, fatty acid elongation, and oxidation. This review broadens our view of fatty acid switches in PCa and presents potential candidates for PCa treatment and diagnosis.
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10
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Enoki T, Jomoto W, Yamano T, Kotoura N. [Influences of Tumor Volume and FWHM of the Water Peak and T 2* Value of Water on the Detection Rate of the Choline Peaks in Proton MR Spectroscopy of Breast Cancer at 3.0 T-MRI]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2021; 77:351-357. [PMID: 33883369 DOI: 10.6009/jjrt.2021_jsrt_77.4.351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
In proton magnetic resonance (MR) spectroscopy (1H-MRS) of the breast cancer, choline peak could be detected. The purpose of this study was to evaluate the influences of the tumor volume, full width at half maximum (FWHM) of the water peak (FWHM), and T2* value of water (T2* value) on the detection rate of the choline peaks at 3.0 T-MRI. We measured FWHM and T2* value in 109 cases, and we evaluated the effect of tumor volume on the detection rate of the choline peaks and the effect of FWHM and T2* value on the detection of choline peaks. In 1H-MRS of breast cancer at 3.0 T-MRI, the detection rate of the choline peaks improved as the tumor volume was larger. As a shimming environment when acquiring 1H-MRS of breast cancer, FWHM is preferably 57.4 Hz or less and T2* value should be 11 ms or more, and T2* value has a great influence on the detection rate of the choline peaks.
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Affiliation(s)
- Takuya Enoki
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Wataru Jomoto
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
| | - Toshiko Yamano
- Department of Radiology, Hyogo College of Medicine (Current address: Department of Radiology, Amagasaki Chuo Hospital)
| | - Noriko Kotoura
- Department of Radiological Technology, Hyogo College of Medicine College Hospital
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11
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Bartnik-Olson BL, Alger JR, Babikian T, Harris AD, Holshouser B, Kirov II, Maudsley AA, Thompson PM, Dennis EL, Tate DF, Wilde EA, Lin A. The clinical utility of proton magnetic resonance spectroscopy in traumatic brain injury: recommendations from the ENIGMA MRS working group. Brain Imaging Behav 2021; 15:504-525. [PMID: 32797399 PMCID: PMC7882010 DOI: 10.1007/s11682-020-00330-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Proton (1H) magnetic resonance spectroscopy provides a non-invasive and quantitative measure of brain metabolites. Traumatic brain injury impacts cerebral metabolism and a number of research groups have successfully used this technique as a biomarker of injury and/or outcome in both pediatric and adult TBI populations. However, this technique is underutilized, with studies being performed primarily at centers with access to MR research support. In this paper we present a technical introduction to the acquisition and analysis of in vivo 1H magnetic resonance spectroscopy and review 1H magnetic resonance spectroscopy findings in different injury populations. In addition, we propose a basic 1H magnetic resonance spectroscopy data acquisition scheme (Supplemental Information) that can be added to any imaging protocol, regardless of clinical magnetic resonance platform. We outline a number of considerations for study design as a way of encouraging the use of 1H magnetic resonance spectroscopy in the study of traumatic brain injury, as well as recommendations to improve data harmonization across groups already using this technique.
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Affiliation(s)
| | - Jeffry R Alger
- Departments of Neurology and Radiology, University of California Los Angeles, Los Angeles, CA, USA
- NeuroSpectroScopics LLC, Sherman Oaks, Los Angeles, CA, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Talin Babikian
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- UCLA Steve Tisch BrainSPORT Program, Los Angeles, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, Canada
- Child and Adolescent Imaging Research Program, Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Barbara Holshouser
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, USA
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Los Angeles, CA, USA
- Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, USC, Los Angeles, CA, USA
| | - Emily L Dennis
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Los Angeles, CA, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA
| | - David F Tate
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Alexander Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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12
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Miller JJ, Valkovič L, Kerr M, Timm KN, Watson WD, Lau JYC, Tyler A, Rodgers C, Bottomley PA, Heather LC, Tyler DJ. Rapid, B 1 -insensitive, dual-band quasi-adiabatic saturation transfer with optimal control for complete quantification of myocardial ATP flux. Magn Reson Med 2021; 85:2978-2991. [PMID: 33538063 PMCID: PMC7986077 DOI: 10.1002/mrm.28647] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 10/28/2020] [Accepted: 11/24/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE Phosphorus saturation-transfer experiments can quantify metabolic fluxes noninvasively. Typically, the forward flux through the creatine kinase reaction is investigated by observing the decrease in phosphocreatine (PCr) after saturation of γ-ATP. The quantification of total ATP utilization is currently underexplored, as it requires simultaneous saturation of inorganic phosphate ( P i ) and PCr. This is challenging, as currently available saturation pulses reduce the already-low γ-ATP signal present. METHODS Using a hybrid optimal-control and Shinnar-Le Roux method, a quasi-adiabatic RF pulse was designed for the dual saturation of PCr and P i to enable determination of total ATP utilization. The pulses were evaluated in Bloch equation simulations, compared with a conventional hard-cosine DANTE saturation sequence, before being applied to perfused rat hearts at 11.7 T. RESULTS The quasi-adiabatic pulse was insensitive to a >2.5-fold variation in B 1 , producing equivalent saturation with a 53% reduction in delivered pulse power and a 33-fold reduction in spillover at the minimum effective B 1 . This enabled the complete quantification of the synthesis and degradation fluxes for ATP in 30-45 minutes in the perfused rat heart. While the net synthesis flux (4.24 ± 0.8 mM/s, SEM) was not significantly different from degradation flux (6.88 ± 2 mM/s, P = .06) and both measures are consistent with prior work, nonlinear error analysis highlights uncertainties in the Pi -to-ATP measurement that may explain a trend suggesting a possible imbalance. CONCLUSIONS This work demonstrates a novel quasi-adiabatic dual-saturation RF pulse with significantly improved performance that can be used to measure ATP turnover in the heart in vivo.
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Affiliation(s)
- Jack J Miller
- Department of Physics, University of Oxford, Oxford, UK.,Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.,Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK.,Health, Aarhus University, Aarhus, Denmark
| | - Ladislav Valkovič
- Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK.,Department of Imaging Methods, Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Matthew Kerr
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Kerstin N Timm
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - William D Watson
- Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK
| | - Justin Y C Lau
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.,Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK
| | - Andrew Tyler
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.,Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK
| | - Christopher Rodgers
- Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK.,Wolfson Brain Imaging Centre, University of Cambridge, Oxford, UK
| | - Paul A Bottomley
- Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK.,Division of MR Research, Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lisa C Heather
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Damian J Tyler
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.,Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Headington, Oxford, UK
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13
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Tang L, Zhao Y, Li Y, Guo R, Clifford B, El Fakhri G, Ma C, Liang ZP, Luo J. Accelerated J-resolved 1 H-MRSI with limited and sparse sampling of ( k , t 1 , t 2 -space. Magn Reson Med 2020; 85:30-41. [PMID: 32726510 DOI: 10.1002/mrm.28413] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 06/13/2020] [Accepted: 06/15/2020] [Indexed: 01/18/2023]
Abstract
PURPOSE To accelerate the acquisition of J-resolved proton magnetic resonance spectroscopic imaging (1 H-MRSI) data for high-resolution mapping of brain metabolites and neurotransmitters. METHODS The proposed method used a subspace model to represent multidimensional spatiospectral functions, which significantly reduced the number of parameters to be determined from J-resolved 1 H-MRSI data. A semi-LASER-based (Localization by Adiabatic SElective Refocusing) echo-planar spectroscopic imaging (EPSI) sequence was used for data acquisition. The proposed data acquisition scheme sampled k , t 1 , t 2 -space in variable density, where t1 and t2 specify the J-coupling and chemical-shift encoding times, respectively. Selection of the J-coupling encoding times (or, echo time values) was based on a Cramer-Rao lower bound analysis, which were optimized for gamma-aminobutyric acid (GABA) detection. In image reconstruction, parameters of the subspace-based spatiospectral model were determined by solving a constrained optimization problem. RESULTS Feasibility of the proposed method was evaluated using both simulated and experimental data from a spectroscopic phantom. The phantom experimental results showed that the proposed method, with a factor of 12 acceleration in data acquisition, could determine the distribution of J-coupled molecules with expected accuracy. In vivo study with healthy human subjects also showed that 3D maps of brain metabolites and neurotransmitters can be obtained with a nominal spatial resolution of 3.0 × 3.0 × 4.8 mm3 from J-resolved 1 H-MRSI data acquired in 19.4 min. CONCLUSIONS This work demonstrated the feasibility of highly accelerated J-resolved 1 H-MRSI using limited and sparse sampling of k , t 1 , t 2 -space and subspace modeling. With further development, the proposed method may enable high-resolution mapping of brain metabolites and neurotransmitters in clinical applications.
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Affiliation(s)
- Lihong Tang
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yibo Zhao
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Yudu Li
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Rong Guo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Bryan Clifford
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Georges El Fakhri
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Chao Ma
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Zhi-Pei Liang
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jie Luo
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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14
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Landheer K, Schulte RF, Treacy MS, Swanberg KM, Juchem C. Theoretical description of modern1H in Vivo magnetic resonance spectroscopic pulse sequences. J Magn Reson Imaging 2019; 51:1008-1029. [DOI: 10.1002/jmri.26846] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 06/14/2019] [Accepted: 06/17/2019] [Indexed: 01/20/2023] Open
Affiliation(s)
- Karl Landheer
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | | | - Michael S. Treacy
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | - Kelley M. Swanberg
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | - Christoph Juchem
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
- Radiology, Columbia University College of Physicians and Surgeons New York New York USA
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15
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Abstract
Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.
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Affiliation(s)
- Geoffrey S Payne
- University Hospitals Southampton NHS Foundation Trust, Tremona Road, Southampton SO16 6YD, United Kingdom
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16
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Kumar V, Bora GS, Kumar R, Jagannathan NR. Multiparametric (mp) MRI of prostate cancer. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2018; 105:23-40. [PMID: 29548365 DOI: 10.1016/j.pnmrs.2018.01.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Revised: 01/17/2018] [Accepted: 01/28/2018] [Indexed: 06/08/2023]
Abstract
Prostate cancer (PCa) is one of the most prevalent cancers in men. A large number of men are detected with PCa; however, the clinical behavior ranges from low-grade indolent tumors that never develop into a clinically significant disease to aggressive, invasive tumors that may rapidly progress to metastatic disease. The challenges in clinical management of PCa are at levels of screening, diagnosis, treatment, and follow-up after treatment. Magnetic resonance imaging (MRI) methods have shown a potential role in detection, localization, staging, assessment of aggressiveness, targeting biopsies, etc. in PCa patients. Multiparametric MRI (mpMRI) is emerging as a better option compared to the individual imaging methods used in the evaluation of PCa. There are attempts to improve the reproducibility and reliability of mpMRI by using an objective scoring system proposed in the prostate imaging reporting and data system (PIRADS) for standardized reporting. Prebiopsy mpMRI may be used to detect PCa in men with elevated prostate-specific antigen or abnormal digital rectal examination and to enable targeted biopsies. mpMRI can also be used to decide on clinical management of patients, for example active surveillance, and may help in detecting only the pathology that requires detection. It can potentially not only guide patient selection for initial and repeat biopsy but also reduce false-negative biopsies. This review presents a description of the MR methods most commonly applied for investigations of prostate. The anatomical, functional and metabolic parameters obtained from these MR methods are discussed with regard to their physical basis and their contribution to mpMRI investigations of PCa.
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Affiliation(s)
- Virendra Kumar
- Department of NMR & MRI Facility, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
| | - Girdhar S Bora
- Department of Urology, Post-Graduate Institute of Medical Sciences, Chandigarh 160012, India
| | - Rajeev Kumar
- Department of Urology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
| | - Naranamangalam R Jagannathan
- Department of NMR & MRI Facility, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
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17
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Chan KL, Ouwerkerk R, Barker PB. Water suppression in the human brain with hypergeometric RF pulses for single-voxel and multi-voxel MR spectroscopy. Magn Reson Med 2018; 80:1298-1306. [PMID: 29446118 DOI: 10.1002/mrm.27133] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 01/23/2018] [Accepted: 01/24/2018] [Indexed: 12/23/2022]
Abstract
PURPOSE To develop and investigate a novel water suppression sequence with hypergeometric pulses at 3 T. METHODS Simulations were used to optimize the delays and amplitudes of 5 hypergeometric prepulses, to minimize the residual water over a range of T1 and B1 values. Single-voxel data with hypergeometric water suppression (HGWS) prepulses were acquired in the centrum semiovale, 2 parietal regions, and insula of 7 subjects, and compared with VAPOR water suppression. Magnetic resonance spectroscopic imaging (MRSI) data using both VAPOR and HGWS prepulses were also collected and compared. Water suppression performance was calculated as the residual water peak height relative to the unsuppressed water peak. MRSI voxel-by-voxel comparison was performed by calculating the ratio between HGWS and VAPOR residual water peaks. RESULTS In simulations, HGWS and VAPOR are insensitive to B1 and water T1 variations, but with no B1 variation, HGWS has a lower average residual water fraction (0.0033) than that of VAPOR (0.0091). In single-voxel acquisitions, HGWS performs better than VAPOR in all regions with a 2.3-fold to 5.7-fold lower residual water. In MRSI acquisitions, HGWS performs on average 2.3-fold better than VAPOR in 98.9% of the voxels. CONCLUSION HGWS provides better water suppression than VAPOR in both single-voxel and multivoxel acquisitions with a shorter sequence duration.
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Affiliation(s)
- Kimberly L Chan
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Ronald Ouwerkerk
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Biomedical and Metabolic Imaging Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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18
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Li Y, Bian W, Larson P, Crane JC, Parvathaneni P, Nagarajan S, Nelson SJ. Reliable and Reproducible GABA Measurements Using Automated Spectral Prescription at Ultra-High Field. Front Hum Neurosci 2017; 11:506. [PMID: 29118697 PMCID: PMC5661373 DOI: 10.3389/fnhum.2017.00506] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Accepted: 10/06/2017] [Indexed: 11/18/2022] Open
Abstract
Purpose: To evaluate spectral acquisition processes important for obtaining reliable and reproducible γ-aminobutyric acid (GABA) signals from volunteers in brain regions that are frequently used for neuroimaging studies [anterior cingulate cortex (ACC), superior temporal gyrus, and caudate] at ultra-high field. Methods: Ten healthy volunteers were studied using a single-voxel Point-RESolved Spectrosocpy (PRESS) sequence with band selective inversion with gradient dephasing pulses (BASING). The editing pulse was designed to be symmetrically placed at 2.0 and 1.4 ppm in the two cycles to reduce the co-editing of macro-molecules (MM). Spectral data were obtained with phase encoding matrix 8 × 8 × 1 and two editing cycles or 1 × 1 × 1 and 64 editing/64 non-editing. The total acquisition time was approximately 4.5 min for each acquisition. An automated MRS prescription method was utilized for the placement of the GABA scan location in 5/10 subjects. Three regions of interest were predefined in the MNI152 space and then registered and transformed to subject space. These volunteers also had repeat scans to examine between-session reproducibility. Results: The placement of editing pulses symmetrically at 1.7 ppm reduced the effect of MM contributions and provided more accurate GABA estimation. Chemical shift misregistration errors caused by classic PRESS localization sequence are more significant at ultra-high field strength. Therefore, a large over-excitation factor was needed to reduce this error. Furthermore, the inefficiency of saturation bands and unspoiled coherence could also interfere with the quality of the data. Reliable recovery of metabolite signals resulted from the implementation of 8 × 8 × 1 phase encoding that successfully removed artifacts and errors, without compromising the total acquisition time. Between successive scans on the same subject, dice overlap ratios of the excited spectral volume between the two scans were in the range of 92–95%. Within subject variability of metabolites between two repeat scans was smaller in the ACC and left superior temporal gyrus when compared to that in the right caudate, with averaged coefficients of variation being 3.6, 6.0, and 16.9%, respectively. Conclusion: This study demonstrated the feasibility of obtaining reliable and reproducible GABA measurements at ultra-high field.
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Affiliation(s)
- Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Wei Bian
- Department of Radiology, Stanford University, Palo Alto, CA, United States
| | - Peder Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Jason C Crane
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Prasanna Parvathaneni
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States.,Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
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19
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Mikkelsen M, Barker PB, Bhattacharyya PK, Brix MK, Buur PF, Cecil KM, Chan KL, Chen DYT, Craven AR, Cuypers K, Dacko M, Duncan NW, Dydak U, Edmondson DA, Ende G, Ersland L, Gao F, Greenhouse I, Harris AD, He N, Heba S, Hoggard N, Hsu TW, Jansen JFA, Kangarlu A, Lange T, Lebel RM, Li Y, Lin CYE, Liou JK, Lirng JF, Liu F, Ma R, Maes C, Moreno-Ortega M, Murray SO, Noah S, Noeske R, Noseworthy MD, Oeltzschner G, Prisciandaro JJ, Puts NAJ, Roberts TPL, Sack M, Sailasuta N, Saleh MG, Schallmo MP, Simard N, Swinnen SP, Tegenthoff M, Truong P, Wang G, Wilkinson ID, Wittsack HJ, Xu H, Yan F, Zhang C, Zipunnikov V, Zöllner HJ, Edden RAE. Big GABA: Edited MR spectroscopy at 24 research sites. Neuroimage 2017; 159:32-45. [PMID: 28716717 PMCID: PMC5700835 DOI: 10.1016/j.neuroimage.2017.07.021] [Citation(s) in RCA: 121] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Revised: 06/20/2017] [Accepted: 07/11/2017] [Indexed: 12/14/2022] Open
Abstract
Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.
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Affiliation(s)
- Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Pallab K Bhattacharyya
- Imaging Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Radiology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA
| | - Maiken K Brix
- Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Pieter F Buur
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
| | - Kim M Cecil
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kimberly L Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David Y-T Chen
- Department of Radiology, Taipei Medical University Shuang Ho Hospital, New Taipei City, Taiwan
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway
| | - Koen Cuypers
- Department of Kinesiology, KU Leuven, Leuven, Belgium; REVAL Rehabilitation Research Center, Hasselt University, Diepenbeek, Belgium
| | - Michael Dacko
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Niall W Duncan
- Brain and Consciousness Research Centre, Taipei Medical University, Taipei, Taiwan
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - David A Edmondson
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Gabriele Ende
- Department of Neuroimaging, Central Institute of Mental Health, Mannheim, Germany
| | - Lars Ersland
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Fei Gao
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Ian Greenhouse
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Stefanie Heba
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Nigel Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Tun-Wei Hsu
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Jacobus F A Jansen
- Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Alayar Kangarlu
- Department of Psychiatry, Columbia University, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | | | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Jy-Kang Liou
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Jiing-Feng Lirng
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Feng Liu
- New York State Psychiatric Institute, New York, NY, USA
| | - Ruoyun Ma
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Celine Maes
- Department of Kinesiology, KU Leuven, Leuven, Belgium
| | | | - Scott O Murray
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Sean Noah
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | | | - Michael D Noseworthy
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Nicolaas A J Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Markus Sack
- Department of Neuroimaging, Central Institute of Mental Health, Mannheim, Germany
| | - Napapon Sailasuta
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | | | - Nicholas Simard
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
| | - Stephan P Swinnen
- Department of Kinesiology, KU Leuven, Leuven, Belgium; Leuven Research Institute for Neuroscience & Disease (LIND), KU Leuven, Leuven, Belgium
| | - Martin Tegenthoff
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Peter Truong
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Guangbin Wang
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Iain D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany
| | - Hongmin Xu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chencheng Zhang
- Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Vadim Zipunnikov
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Helge J Zöllner
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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Bogner W, Hangel G, Esmaeili M, Andronesi OC. 1D-spectral editing and 2D multispectral in vivo 1H-MRS and 1H-MRSI - Methods and applications. Anal Biochem 2017; 529:48-64. [PMID: 28034791 DOI: 10.1016/j.ab.2016.12.020] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 12/16/2016] [Accepted: 12/23/2016] [Indexed: 12/27/2022]
Abstract
This article reviews the methodological aspects of detecting low-abundant J-coupled metabolites via 1D spectral editing techniques and 2D nuclear magnetic resonance (NMR) methods applied in vivo, in humans, with a focus on the brain. A brief explanation of the basics of J-evolution will be followed by an introduction to 1D spectral editing techniques (e.g., J-difference editing, multiple quantum coherence filtering) and 2D-NMR methods (e.g., correlation spectroscopy, J-resolved spectroscopy). Established and recently developed methods will be discussed and the most commonly edited J-coupled metabolites (e.g., neurotransmitters, antioxidants, onco-markers, and markers for metabolic processes) will be briefly summarized along with their most important applications in neuroscience and clinical diagnosis.
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Affiliation(s)
- Wolfgang Bogner
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria.
| | - Gilbert Hangel
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria.
| | - Morteza Esmaeili
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
| | - Ovidiu C Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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21
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Harris AD, Saleh MG, Edden RAE. Edited 1 H magnetic resonance spectroscopy in vivo: Methods and metabolites. Magn Reson Med 2017; 77:1377-1389. [PMID: 28150876 PMCID: PMC5352552 DOI: 10.1002/mrm.26619] [Citation(s) in RCA: 122] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Revised: 12/30/2016] [Accepted: 12/30/2016] [Indexed: 12/13/2022]
Abstract
The Proton magnetic resonance (1 H-MRS) spectrum contains information about the concentration of tissue metabolites within a predefined region of interest (a voxel). The conventional spectrum in some cases obscures information about less abundant metabolites due to limited separation and complex splitting of the metabolite peaks. One method to detect these metabolites is to reduce the complexity of the spectrum using editing. This review provides an overview of the one-dimensional editing methods available to interrogate these obscured metabolite peaks. These methods include sequence optimizations, echo-time averaging, J-difference editing methods (single BASING, dual BASING, and MEGA-PRESS), constant-time PRESS, and multiple quantum filtering. It then provides an overview of the brain metabolites whose detection can benefit from one or more of these editing approaches, including ascorbic acid, γ-aminobutyric acid, lactate, aspartate, N-acetyl aspartyl glutamate, 2-hydroxyglutarate, glutathione, glutamate, glycine, and serine. Magn Reson Med 77:1377-1389, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, AB T2N 1N4, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB T3B 6A9, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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22
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Ma J, Wismans C, Cao Z, Klomp DWJ, Wijnen JP, Grissom WA. Tailored spiral in-out spectral-spatial water suppression pulses for magnetic resonance spectroscopic imaging. Magn Reson Med 2017; 79:31-40. [PMID: 28370494 DOI: 10.1002/mrm.26683] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 02/02/2017] [Accepted: 02/28/2017] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop short water suppression sequences for 7 T magnetic resonance spectroscopic imaging, with mitigation of subject-specific transmit RF field ( B1+) inhomogeneity. METHODS Patient-tailored spiral in-out spectral-spatial saturation pulses were designed for a three-pulse WET water suppression sequence. The pulses' identical spatial subpulses were designed using patient-specific B1+ maps and a spiral in-out excitation k-space trajectory. The subpulse train was weighted by a spectral envelope that was root-flipped to minimize peak RF demand. The pulses were validated in in vivo experiments that acquired high resolution magnetic resonance spectroscopic imaging data, using a crusher coil for fast lipid suppression. Residual water signals and MR spectra were compared between the proposed tailored sequence and a conventional WET sequence. RESULTS Replacing conventional spectrally-selective pulses with tailored spiral in-out spectral-spatial pulses reduced mean water residual from 5.88 to 2.52% (57% improvement). Pulse design time was less then 0.4 s. The pulses' specific absorption rate were compatible with magnetic resonance spectroscopic imaging TRs under 300 ms, which enabled spectra of fine in plane spatial resolution (5 mm) with good quality to be measured in 7.5 min. CONCLUSION Tailored spiral in-out spectral-spatial water suppression enables efficient high resolution magnetic resonance spectroscopic imaging in the brain. Magn Reson Med 79:31-40, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Jun Ma
- Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Carrie Wismans
- Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Zhipeng Cao
- Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Dennis W J Klomp
- Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Jannie P Wijnen
- Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - William A Grissom
- Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
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23
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Bellomo G, Marcocci F, Bianchini D, Mezzenga E, D’Errico V, Menghi E, Zannoli R, Sarnelli A. MR Spectroscopy in Prostate Cancer: New Algorithms to Optimize Metabolite Quantification. PLoS One 2016; 11:e0165730. [PMID: 27832096 PMCID: PMC5104319 DOI: 10.1371/journal.pone.0165730] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Accepted: 10/17/2016] [Indexed: 11/18/2022] Open
Abstract
Prostate cancer (PCa) is the most common non-cutaneous cancer in male subjects and the second leading cause of cancer-related death in developed countries. The necessity of a non-invasive technique for the diagnosis of PCa in early stage has grown through years. Proton magnetic resonance spectroscopy (1H-MRS) and proton magnetic resonance spectroscopy imaging (1H-MRSI) are advanced magnetic resonance techniques that can mark the presence of metabolites such as citrate, choline, creatine and polyamines in a selected voxel, or in an array of voxels (in MRSI) inside prostatic tissue. Abundance or lack of these metabolites can discriminate between pathological and healthy tissue. Although the use of magnetic resonance spectroscopy (MRS) is well established in brain and liver with dedicated software for spectral analysis, quantification of metabolites in prostate can be very difficult to achieve, due to poor signal to noise ratio and strong J-coupling of the citrate. The aim of this work is to develop a software prototype for automatic quantification of citrate, choline and creatine in prostate. Its core is an original fitting routine that makes use of a fixed step gradient descent minimization algorithm (FSGD) and MRS simulations developed with the GAMMA libraries in C++. The accurate simulation of the citrate spin systems allows to predict the correct J-modulation under different NMR sequences and under different coupling parameters. The accuracy of the quantifications was tested on measurements performed on a Philips Ingenia 3T scanner using homemade phantoms. Some acquisitions in healthy volunteers have been also carried out to test the software performance in vivo.
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Affiliation(s)
- Giovanni Bellomo
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
| | - Francesco Marcocci
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
- * E-mail:
| | - David Bianchini
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
| | - Emilio Mezzenga
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
| | - Vincenzo D’Errico
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
| | - Enrico Menghi
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
| | - Romano Zannoli
- Experimental, Diagnostic and Specialty Medicine Department DIMES, University of Bologna, Bologna, Italy
| | - Anna Sarnelli
- Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy
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Landheer K, Sahgal A, Myrehaug S, Chen AP, Cunningham CH, Graham SJ. A rapid inversion technique for the measurement of longitudinal relaxation times of brain metabolites: application to lactate in high-grade gliomas at 3 T. NMR IN BIOMEDICINE 2016; 29:1381-1390. [PMID: 27455374 DOI: 10.1002/nbm.3580] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 05/30/2016] [Accepted: 06/13/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to develop a time-efficient inversion technique to measure the T1 relaxation time of the methyl group of lactate (Lac) in the presence of contaminating lipids and to measure T1 at 3 T in a cohort of primary high-grade gliomas. Three numerically optimized inversion times (TIs) were chosen to minimize the expected error in T1 estimates for a given input total scan duration (set to be 30 min). A two-cycle spectral editing scheme was used to suppress contaminating lipids. The T1 values were then estimated from least-squares fitting of signal measurements versus TI. Lac T1 was estimated as 2000 ± 280 ms. After correcting for T1 (and T2 from literature values), the mean absolute Lac concentration was estimated as 4.3 ± 2.6 mm. The technique developed agrees with the results obtained by standard inversion recovery and can be used to provide rapid T1 estimates of other spectral components as required. Lac T1 exhibits similar variations to other major metabolites observable by MRS in high-grade gliomas. The T1 estimate provided here will be useful for future MRS studies wishing to report relaxation-corrected estimates of Lac concentration as an objective tumor biomarker. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Karl Landheer
- Department of Medical Biophysics, University of Toronto, ON, Canada.
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Odette Cancer Center, University of Toronto, ON, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Odette Cancer Center, University of Toronto, ON, Canada
| | | | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Simon J Graham
- Department of Medical Biophysics, University of Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
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25
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Buonocore MH, Maddock RJ. Magnetic resonance spectroscopy of the brain: a review of physical principles and technical methods. Rev Neurosci 2016. [PMID: 26200810 DOI: 10.1515/revneuro-2015-0010] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Magnetic resonance spectroscopy (MRS) provides unique information about the neurobiological substrates of brain function in health and disease. However, many of the physical principles underlying MRS are distinct from those underlying magnetic resonance imaging, and they may not be widely understood by neuroscientists new to this methodology. This review describes these physical principles and many of the technical methods in current use for MRS experiments. A better understanding these principles and methods may help investigators select pulse sequences and quantification methods best suited to the aims of their research program and avoid pitfalls that can hamper new investigators in this field.
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26
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Weis J, von Below C, Tolf A, Ortiz-Nieto F, Wassberg C, Häggman M, Ladjevardi S, Ahlström H. Quantification of metabolite concentrations in benign and malignant prostate tissues using 3D proton MR spectroscopic imaging. J Magn Reson Imaging 2016; 45:1232-1240. [PMID: 27556571 DOI: 10.1002/jmri.25443] [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: 06/08/2016] [Revised: 08/09/2016] [Accepted: 08/09/2016] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To estimate concentrations of choline (Cho), spermine (Spm), and citrate (Cit) in prostate tissue using 3D proton magnetic resonance spectroscopic imaging (MRSI) with water as an internal concentration reference as well as to assess the relationships between the measured metabolites and also between the metabolites and apparent diffusion coefficient (ADC). MATERIALS AND METHODS Forty-six prostate cancer patients were scanned at 3T. Spectra were acquired with the point-resolved spectroscopy (PRESS) localization technique. Single-voxel spectra of four healthy volunteers were used to estimate T1 relaxation time of Spm. Spm, Cho concentrations, and ADC values of benign prostate tissues were correlated with Cit content. RESULTS The T1 value, 708 ± 132 msec, was estimated for Spm. Mean concentrations in the benign peripheral zone (PZ) were Cho, 4.5 ± 1 mM, Spm, 13.0 ± 4.4 mM, Cit, 64.4 ± 16.1 mM. Corresponding values in the benign central gland (CG) were Cho, 3.6 ± 1 mM, Spm, 13.3 ± 4.5 mM, Cit, 34.3 ± 12.9 mM. Concentrations of Cit and Spm were positively correlated in the benign PZ zone (r = 0.730) and CG (r = 0.664). Positive correlation was found between Cit and Cho in the benign CG (r = 0.705). Whereas Cit and ADC were positively correlated in the benign PZ (r = 0.673), only low correlation was found in CG (r = 0.265). CONCLUSION We have shown that it is possible to perform water-referenced quantitative 3D MRSI of the prostate at the cost of a relatively short prolongation of the acquisition time. The individual metabolite concentrations provide additional information compared to the previously used metabolite-to-citrate ratios. LEVEL OF EVIDENCE 1 J. Magn. Reson. Imaging 2017;45:1232-1240.
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Affiliation(s)
- Jan Weis
- Department of Radiology, Uppsala University Hospital, Uppsala, Sweden
| | - Catrin von Below
- Department of Radiology, Uppsala University Hospital, Uppsala, Sweden
| | - Anna Tolf
- Department of Pathology, Uppsala University Hospital, Uppsala, Sweden
| | | | - Cecilia Wassberg
- Department of Radiology, Uppsala University Hospital, Uppsala, Sweden
| | | | - Sam Ladjevardi
- Department of Urology, University Hospital, Uppsala, Sweden
| | - Håkan Ahlström
- Department of Radiology, Uppsala University Hospital, Uppsala, Sweden
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Starobinets O, Korn N, Iqbal S, Noworolski SM, Zagoria R, Kurhanewicz J, Westphalen AC. Practical aspects of prostate MRI: hardware and software considerations, protocols, and patient preparation. Abdom Radiol (NY) 2016; 41:817-30. [PMID: 27193785 DOI: 10.1007/s00261-015-0590-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The use of multiparametric MRI scans for the evaluation of men with prostate cancer has increased dramatically and is likely to continue expanding as new developments come to practice. However, it has not yet gained the same level of acceptance of other imaging tests. Partly, this is because of the use of suboptimal protocols, lack of standardization, and inadequate patient preparation. In this manuscript, we describe several practical aspects of prostate MRI that may facilitate the implementation of new prostate imaging programs or the expansion of existing ones.
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Affiliation(s)
- Olga Starobinets
- Graduate Group of Bioengineering, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Box 0946, San Francisco, CA, 94143, USA
| | - Natalie Korn
- Graduate Group of Bioengineering, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Box 0946, San Francisco, CA, 94143, USA
| | - Sonam Iqbal
- Graduate Group of Bioengineering, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Box 0946, San Francisco, CA, 94143, USA
| | - Susan M Noworolski
- Graduate Group of Bioengineering, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Box 0946, San Francisco, CA, 94143, USA
| | - Ronald Zagoria
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, M372, Box 0628, San Francisco, CA, 94143, USA
| | - John Kurhanewicz
- Graduate Group of Bioengineering, Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, Ste. 203, San Francisco, CA, 94158, USA
| | - Antonio C Westphalen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, M372, Box 0628, San Francisco, CA, 94143, USA.
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28
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Esmaeili M, Bathen TF, Rosen BR, Andronesi OC. Three-dimensional MR spectroscopic imaging using adiabatic spin echo and hypergeometric dual-band suppression for metabolic mapping over the entire brain. Magn Reson Med 2016; 77:490-497. [PMID: 26840906 DOI: 10.1002/mrm.26115] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Revised: 12/14/2015] [Accepted: 12/16/2015] [Indexed: 11/12/2022]
Abstract
PURPOSE Large lipid and water signals in MR spectroscopic imaging (MRSI) complicate brain metabolite quantification. In this study, we combined adiabatic hypergeometric dual-band (HGDB) lipid and water suppression with gradient offset independent adiabatic (GOIA) spin echo to improve three-dimensional (3D) MRSI of the entire brain. METHODS 3D MRSI was acquired at 3T with a 32-channel coil. HGDB pulses were used before excitation and during echo time. A brain slab was selected with GOIA-W(16,4) pulses, weighted phase encoded stack of spirals, and real-time motion/shim correction. HGDB alone or in combination with OVS and MEGA (MEscher-GArwood) was compared with OVS only and no suppression. RESULTS The combined HGDB pulses suppressed lipids to 2%-3% of their full unsuppressed signal. The HGDB lipid suppression was on average 5 times better than OVS suppression. HGDB+MEGA provided 30% more suppression compared with a previously described HGDB+OVS scheme. The number of voxels with good metabolic fits was significantly larger in the HGDB data (91%-94%) compared with the OVS data (59%-80%). CONCLUSION HGDB pulses provided efficient lipid and water suppression for full brain 3D MRSI. The HGDB suppression is superior to traditional OVS, and it can be combined with adiabatic spin echo to provide a sequence that is robust to B1 inhomogeneity. Magn Reson Med 77:490-497, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Morteza Esmaeili
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ovidiu C Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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29
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Feldman RE, Balchandani P. A semiadiabatic spectral-spatial spectroscopic imaging (SASSI) sequence for improved high-field MR spectroscopic imaging. Magn Reson Med 2015; 76:1071-82. [PMID: 26519948 DOI: 10.1002/mrm.26025] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Revised: 09/08/2015] [Accepted: 10/02/2015] [Indexed: 12/27/2022]
Abstract
PURPOSE MR spectroscopic imaging (MRSI) benefits from operation at 7T due to increased signal-to-noise ratio (SNR) and spectral separation. The 180° radiofrequency (RF) pulses used in the conventional MRSI sequences are particularly susceptible to the variation in the transmitted RF (B1 ) field and severe chemical shift localization errors at 7T. RF power deposition, as measured by specific absorption rate (SAR), also increases with field strength. Adiabatic 180° RF pulses may mitigate the effects of B1 variation. We designed and implemented a semiadiabatic spectral-spatial spectroscopic imaging (SASSI) pulse sequence to provide more uniform spectral data at 7T with reduced SAR. METHODS The adiabatic Shinnar-Le Roux algorithm was used to generate a high bandwidth 180° adiabatic spectral-spatial (SPSP) pulse that captured a spectral range containing the main metabolites of interest. A pair of 180° SPSP pulses was used to refocus the signal excited by a 90° SPSP pulse in order to select a 3D volume of interest in the SASSI sequence. RESULTS The SASSI pulse sequence produced spectra with more uniform brain metabolite SNR when compared with the conventional nonadiabatic MRSI sequence. CONCLUSION SASSI achieved comparable SNR to the current adiabatic alternative, semi-LASER, but with 1/3 of the SAR. Magn Reson Med 76:1071-1082, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Rebecca E Feldman
- Translational and Molecular Imaging Institution, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
| | - Priti Balchandani
- Translational and Molecular Imaging Institution, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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30
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Basharat M, Payne GS, Morgan VA, Parker C, Dearnaley D, deSouza NM. TE = 32 ms vs TE = 100 ms echo-time (1)H-magnetic resonance spectroscopy in prostate cancer: Tumor metabolite depiction and absolute concentrations in tumors and adjacent tissues. J Magn Reson Imaging 2015; 42:1086-93. [PMID: 26258905 PMCID: PMC4914942 DOI: 10.1002/jmri.24875] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 02/06/2015] [Indexed: 12/16/2022] Open
Abstract
PURPOSE To compare the depiction of metabolite signals in short and long echo time (TE) prostate cancer spectra at 3T, and to quantify their concentrations in tumors of different stage and grade, and tissues adjacent to tumor. MATERIALS AND METHODS First, single-voxel magnetic resonance imaging (MRI) spectra were acquired from voxels consisting entirely of tumor, as defined on T2-weighted and diffusion-weighted (DW)-MRI and from a biopsy-positive octant, at TEs of 32 msec and 100 msec in 26 prostate cancer patients. Then, in a separate cohort of 26 patients, single-voxel TE = 32 msec MR spectroscopy (MRS) was performed over a partial-tumor region and a matching, contralateral normal-appearing region, defined similarly. Metabolite depiction was compared between TEs using Cramér-Rao lower bounds (CRLB), and absolute metabolite concentrations were calculated from TE = 32 msec spectra referenced to unsuppressed water spectra. RESULTS Citrate and spermine resonances in tumor were better depicted (had significantly lower CRLB) at TE = 32 msec, while the choline resonance was better depicted at TE = 100 msec. Citrate and spermine concentrations were significantly lower in patients of more advanced stage, significantly lower in Gleason grade 3+4 than 3+3 tumors, and significantly lower than expected from the tumor fraction in partial-tumor voxels (by 14 mM and 4 mM, respectively, P < 0.05). CONCLUSION Citrate and spermine resonances are better depicted at short TE than long TE in tumors. Reduction in these concentrations is related to increasing tumor stage and grade in vivo, while reductions in the normal-appearing tissues immediately adjacent to tumor likely reflect tumor field effects.
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Affiliation(s)
- Meer Basharat
- CRUK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
| | - Geoffrey S Payne
- CRUK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
| | - Veronica A Morgan
- CRUK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
| | - Chris Parker
- Academic Urology Unit, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
| | - David Dearnaley
- Academic Urology Unit, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
| | - Nandita M deSouza
- CRUK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
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31
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Brix MK, Ersland L, Hugdahl K, Grüner R, Posserud MB, Hammar Å, Craven AR, Noeske R, Evans CJ, Walker HB, Midtvedt T, Beyer MK. "Brain MR spectroscopy in autism spectrum disorder-the GABA excitatory/inhibitory imbalance theory revisited". Front Hum Neurosci 2015; 9:365. [PMID: 26157380 PMCID: PMC4475903 DOI: 10.3389/fnhum.2015.00365] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Accepted: 06/08/2015] [Indexed: 12/27/2022] Open
Abstract
Magnetic resonance spectroscopy (MRS) from voxels placed in the left anterior cingulate cortex (ACC) was measured from 14 boys with Autism Spectrum Disorder (ASD) and 24 gender and age-matched typically developing (TD) control group. Our main aims were to compare the concentration of γ-aminobutyric acid (GABA) between the two groups, and to investigate the relationship between brain metabolites and autism symptom severity in the ASD group. We did find a significant negative correlation in the ASD group between Autism Spectrum Screening Questionnaire (ASSQ) and GABA+/Cr, which may imply that severity of symptoms in ASD is associated with differences in the level of GABA in the brain, supporting the excitatory/inhibitory (E/I) imbalance theory. However we did not find a significant difference between the two groups in GABA levels.
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Affiliation(s)
- Maiken K. Brix
- Department of Radiology, Haukeland University HospitalBergen, Norway
- Department of Clinical Medicine (K1), University of BergenBergen, Norway
| | - Lars Ersland
- Department of Clinical Engineering, Haukeland University HospitalBergen, Norway
- NORMENT – KG Jebsen Center for Mental Disorders Research, University of BergenBergen, Norway
| | - Kenneth Hugdahl
- Department of Radiology, Haukeland University HospitalBergen, Norway
- NORMENT – KG Jebsen Center for Mental Disorders Research, University of BergenBergen, Norway
- Department of Biological and Medical Psychology, University of BergenBergen, Norway
- Division of Psychiatry, Haukeland University HospitalBergen, Norway
| | - Renate Grüner
- Department of Radiology, Haukeland University HospitalBergen, Norway
- NORMENT – KG Jebsen Center for Mental Disorders Research, University of BergenBergen, Norway
- Department of Physics and Technology, University of BergenBergen, Norway
| | - Maj-Britt Posserud
- Department of Child and Adolescent Psychiatry, Haukeland University HospitalBergen, Norway
| | - Åsa Hammar
- Department of Biological and Medical Psychology, University of BergenBergen, Norway
| | - Alexander R. Craven
- NORMENT – KG Jebsen Center for Mental Disorders Research, University of BergenBergen, Norway
- Department of Biological and Medical Psychology, University of BergenBergen, Norway
| | - Ralph Noeske
- MR Applications and Workflow Development, GE HealthcareBerlin, Germany
| | - C. John Evans
- CUBRIC, School of Psychology/Ysgol Seicoleg, Cardiff University/Prifysgol Caerdydd WalesCardiff, UK
| | - Hanne B. Walker
- Faculty of Mathematics and Natural Sciences, University of OsloOslo, Norway
| | - Tore Midtvedt
- Department of Microbiology, Tumor and Cell Biology, Karolinska InstituteStockholm, Sweden
| | - Mona K. Beyer
- Department of Radiology and Nuclear Medicine, Oslo University HospitalOslo, Norway
- Faculty of Health Sciences, Department of Life Sciences and Health, Oslo and Akershus University College of Applied SciencesOslo, Norway
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Aydın H, Kızılgöz V, Tekin BO. Overview of current multiparametric magnetic resonance imaging approach in the diagnosis and staging of prostate cancer. Kaohsiung J Med Sci 2015; 31:167-78. [DOI: 10.1016/j.kjms.2015.01.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 10/07/2014] [Accepted: 02/19/2014] [Indexed: 01/08/2023] Open
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Zhang Y, Zhou J, Bottomley PA. Minimizing lipid signal bleed in brain (1) H chemical shift imaging by post-acquisition grid shifting. Magn Reson Med 2014; 74:320-9. [PMID: 25168657 DOI: 10.1002/mrm.25438] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 08/01/2014] [Accepted: 08/13/2014] [Indexed: 12/27/2022]
Abstract
PURPOSE Low spatial resolution in conventional 1H brain chemical shifting imaging (CSI) studies causes partial volume error (PVE) or signal "bleed" that is especially deleterious to voxels near the scalp. The standard spatial apodization approach adversely affects spatial resolution. Here, a novel automated post-processing strategy of partial volume correction employing grid shifting ("PANGS") is presented, which minimizes residual PVE without compromising spatial resolution. METHODS PANGS shifts the locations of the reconstruction coordinates in a designated region of image space-the scalp, to match the tissue "centers-of-mass" instead of the geometric centers of each voxel, by iteratively minimizing the PVE from the scalp into outside voxels. PANGS' performance was evaluated by numerical simulation, and in 3 Tesla 1H CSI human studies employing outer volume suppression and long echo times. RESULTS PANGS reduced lipid contamination of cortical spectra by up to 86% (54% on average). Metabolite maps exhibited significantly less lipid artifact than conventional and spatially-filtered CSI. All methods generated quantitatively identical spectral peak areas from central brain locations, but spatial filtering increased spectral linewidths and reduced spatial resolution. CONCLUSION PANGS significantly reduces lipid artifacts in 1H brain CSI spectra and metabolite maps, and improves metabolite detection in cortical regions without compromising resolution.
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Affiliation(s)
- Yi Zhang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Paul A Bottomley
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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Kobus T, Wright AJ, Weiland E, Heerschap A, Scheenen TWJ. Metabolite ratios in 1H MR spectroscopic imaging of the prostate. Magn Reson Med 2014; 73:1-12. [PMID: 24488656 DOI: 10.1002/mrm.25122] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Revised: 11/18/2013] [Accepted: 12/17/2013] [Indexed: 12/24/2022]
Abstract
In (1)H MR spectroscopic imaging ((1)H-MRSI) of the prostate the spatial distribution of the signal levels of the metabolites choline, creatine, polyamines, and citrate are assessed. The ratio of choline (plus spermine as the main polyamine) plus creatine over citrate [(Cho+(Spm+)Cr)/Cit] is derived from these metabolites and is used as a marker for the presence of prostate cancer. In this review, the factors that are of importance for the metabolite ratio are discussed. This is relevant, because the appearance of the metabolites in the spectrum depends not only on the underlying anatomy, metabolism, and physiology of the tissue, but also on acquisition parameters. These parameters influence especially the spectral shapes of citrate and spermine resonances, and consequently, the (Cho+(Spm+)Cr)/Cit ratio. Both qualitative and quantitative approaches can be used for the evaluation of (1)H-MRSI spectra of the prostate. For the quantitative approach, the (Cho+(Spm+)Cr)/Cit ratio can be determined by integration or by a fit based on model signals. Using the latter, the influence of the acquisition parameters on citrate can be taken into account. The strong overlap between the choline, creatine, and spermine resonances complicates fitting of the individual metabolites. This overlap and (unknown, possibly tissue-related) variations in T1, T2, and J-modulation hamper the application of corrections needed for a "normalized" (Cho+(Spm+)Cr)/Cit ratio that would enable comparison of spectra measured with different prostate MR spectroscopy protocols. Quantitative (Cho+(Spm+)Cr)/Cit thresholds for the evaluation of prostate cancer are therefore commonly established per institution or per protocol. However, if the same acquisition and postprocessing protocol were used, the ratio and the thresholds would be institution-independent, promoting the clinical usability of prostate (1)H-MRSI.
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Affiliation(s)
- Thiele Kobus
- Radboud University Medical Centre, Radiology Department, Nijmegen, The Netherlands
| | - Alan J Wright
- Radboud University Medical Centre, Radiology Department, Nijmegen, The Netherlands
| | | | - Arend Heerschap
- Radboud University Medical Centre, Radiology Department, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Radboud University Medical Centre, Radiology Department, Nijmegen, The Netherlands
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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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Nelson SJ, Ozhinsky E, Li Y, Park IW, Crane J. Strategies for rapid in vivo 1H and hyperpolarized 13C MR spectroscopic imaging. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 229:187-97. [PMID: 23453759 PMCID: PMC3808990 DOI: 10.1016/j.jmr.2013.02.003] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2012] [Revised: 02/01/2013] [Accepted: 02/01/2013] [Indexed: 05/13/2023]
Abstract
In vivo MRSI is an important imaging modality that has been shown in numerous research studies to give biologically relevant information for assessing the underlying mechanisms of disease and for monitoring response to therapy. The increasing availability of high field scanners and multichannel radiofrequency coils has provided the opportunity to acquire in vivo data with significant improvements in sensitivity and signal to noise ratio. These capabilities may be used to shorten acquisition time and provide increased coverage. The ability to acquire rapid, volumetric MRSI data is critical for examining heterogeneity in metabolic profiles and for relating serial changes in metabolism within the same individual during the course of the disease. In this review we discuss the implementation of strategies that use alternative k-space sampling trajectories and parallel imaging methods in order to speed up data acquisition. The impact of such methods is demonstrated using three recent examples of how these methods have been applied. These are to the acquisition of robust 3D (1)H MRSI data within 5-10 min at a field strength of 3 T, to obtaining higher sensitivity for (1)H MRSI at 7 T and to using ultrafast volumetric and dynamic (13)C MRSI for monitoring the changes in signals that occur following the injection of hyperpolarized (13)C agents.
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Affiliation(s)
- Sarah J Nelson
- Surbeck Laboratory for Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94158-2330, USA.
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WEIS J, ORTIZ-NIETO F, AHLSTR^|^Ouml;M H. MR Spectroscopy of the Prostate at 3T: Measurements of Relaxation Times and Quantification of Prostate Metabolites using Water as an Internal Reference. Magn Reson Med Sci 2013; 12:289-96. [DOI: 10.2463/mrms.2013-0017] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Razek NMA, Azab AO, Omar OS, Soliman HO. Role of proton MR spectroscopy in the high field magnet (3T) in diagnosis of indeterminate breast masses (BIRDS 3 & 4). THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2012. [DOI: 10.1016/j.ejrnm.2012.08.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Posse S, Otazo R, Dager SR, Alger J. MR spectroscopic imaging: Principles and recent advances. J Magn Reson Imaging 2012. [DOI: 10.1002/jmri.23945] [Citation(s) in RCA: 144] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
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40
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Caivano R, Cirillo P, Balestra A, Lotumolo A, Fortunato G, Macarini L, Zandolino A, Vita G, Cammarota A. Prostate cancer in magnetic resonance imaging: diagnostic utilities of spectroscopic sequences. J Med Imaging Radiat Oncol 2012; 56:606-16. [PMID: 23210579 DOI: 10.1111/j.1754-9485.2012.02449.x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2011] [Accepted: 05/24/2012] [Indexed: 11/28/2022]
Abstract
OBJECTIVE The aim of our work is to determine the efficacy of a combined study 3 Tesla Magnetic Resonance Imaging (3T MRI), with phased-array coil, for the detection of prostate cancer using magnetic resonance spectroscopy (MRS) and diffusion-weighted images (DWI) in identifying doubt nodules. SUBJECTS AND METHODS In this study, we prospectively studied 46 patients who consecutively underwent digital-rectal exploration for high doses of prostate specific antigen (PSA), as well as a MRI examination and a subsequent rectal biopsy. The study of magnetic resonance imaging was performed with a Philips Achieva 3T scanner and phased-array coil. The images were obtained with turbo spin-echo sequences T2-weighted images, T1-weighted before and after the administration of contrast medium, DWI sequences and 3D spectroscopic sequences. The ultrasound-guided prostate biopsy was performed approximately 15 days after the MRI. The data obtained from MR images and spectroscopy were correlated with histological data. RESULTS MRI revealed sensitivity and specificity of 88% and 61% respectively and positive predictive value (PPV) of 73%, negative predicted value (NPV) of 81% and accuracy of 76%. In identifying the location of prostate cancer, the sensitivity of 3T MRS was 92%, with a specificity of 89%, PPV of 87%, NPV of 88% and accuracy of 87%; DWI showed a sensitivity of 88%, specificity of 61%, PPV of 73%, NPV of 81% and accuracy of 76%. CONCLUSIONS The 3T MR study with phased-array coil and the use of DWI and spectroscopic sequences, in addition to T2-weighted sequences, revealed to be accurate in the diagnosis of prostate cancer and in the identification of nodules to be biopsied. It may be indicated as a resolute way before biopsy in patients with elevated PSA value and can be proposed in the staging and follow-up.
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Affiliation(s)
- Rocchina Caivano
- Department of Radiology, I.R.C.C.S. - C.R.O.B., Rionero in Vulture (Pz), Italy.
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Li B, Cai W, Lv D, Guo X, Zhang J, Wang X, Fang J. Comparison of MRS and DWI in the diagnosis of prostate cancer based on sextant analysis. J Magn Reson Imaging 2012; 37:194-200. [PMID: 23002033 DOI: 10.1002/jmri.23809] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2012] [Accepted: 08/08/2012] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To evaluate apparent diffusion coefficient (ADC) value, metabolic ratio ((Cho + Cr)/Cit) and the combination of the two in identifying prostate malignant regions. MATERIALS AND METHODS Fifty-six consecutive patients with prostate biopsy results were retrospectively recruited in this study. Transrectal ultrasound-guided (TRUS) systemic prostate biopsies were used as a standard of reference. Mean ADC value and mean metabolic ratio (MMR) were calculated within each benign sextant region or malignant region. The efficiency of these two indices in prostate cancer (PCa) diagnosis is estimated in Fisher linear discriminant analysis (FLDA). The area under the receiver operating characteristic (ROC) curve was used to evaluate the distinguishing capacity of mean ADC, MMR, and the combination of the two in differentiating between noncancerous and cancerous cases. RESULTS There were significant differences for mean ADC value and MMR between malignant and benign regions. Weights of mean ADC value obtained by FLDA were much higher than those of MMR. In differentiating malignant regions, both ADC alone and combined ADC and metabolic ratio performed significantly better than MMR alone. However, accuracy improvements were not significant by using combined ADC and MMR than ADC alone. CONCLUSION DWI is more efficient than MR spectroscopic (MRS) in the detection of PCa in this study. Combined ADC and MMR performed significantly better than MMR alone in distinguishing malignant from benign region in prostate peripheral zone.
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Affiliation(s)
- Bo Li
- College of Engineering, Peking University, Beijing, China, People's Republic of China
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Hugdahl K, Beyer MK, Brix M, Ersland L. Autism spectrum disorder, functional MRI and MR spectroscopy: possibilities and challenges. MICROBIAL ECOLOGY IN HEALTH AND DISEASE 2012; 23:18960. [PMID: 23990828 PMCID: PMC3747752 DOI: 10.3402/mehd.v23i0.18960] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Background In this article we provide an overview of the use of the functional magnetic resonance imaging (fMRI) and MR spectroscopy (MRS) in studies of autism spectrum disorders (ASD). We moreover provide preliminary data using these measures in cases of children with ASD and healthy controls. A hypothesis was that ASD children would show aberrant brain activation in the prefrontal and parietal cortex in an oddball stimulus situation, with predictable and unpredictable deviant tone stimuli, as an index of resistance to change in the ASD children. We also hypothesized that glutamate and GABA metabolite levels would differ between the two groups. Methods fMRI images were acquired from a GE Signa HDx 3T MR scanner, as were the MRS data. Behavioral data were acquired as response accuracy to the deviant tone stimulus. The tone stimuli were presented in a standard fMRI ON-OFF box-car paradigim. Results The fMRI results showed reduced brain activation in the ASD cases compared to the controls, preferably in the inferior and superior frontal gyrus, posterior temporal lobe, and superior and inferior parietal lobule. These areas make up an effort mode network (EMN), being activated in response to cognitive effort. The MRS results also showed differences between the groups. Discussion The results are discussed in a theoretical framework of resistance to unexpected changes in the environment in ASD children, and how this could have a neurobiological underpinning. The results are also discussed in relation to the brain-gut link, and the possibility that ASD may have a microbial link. A limitation with the study is the few cases reported and the preliminary quality of the results.
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Affiliation(s)
- Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway ; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway ; Department of Radiology, Haukeland University Hospital, Bergen, Norway
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Mizukoshi W, Kozawa E, Inoue K, Saito N, Nishi N, Saeki T, Kimura F. (1)H MR spectroscopy with external reference solution at 1.5 T for differentiating malignant and benign breast lesions: comparison using qualitative and quantitative approaches. Eur Radiol 2012; 23:75-83. [PMID: 22777619 DOI: 10.1007/s00330-012-2555-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2012] [Revised: 05/03/2012] [Accepted: 05/25/2012] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To compare the diagnostic capability of proton ((1)H) magnetic resonance spectroscopy (MRS) in differentiating benign from malignant breast lesions on the basis of qualitative and quantitative approaches. METHODS We performed single-voxel (1)H MRS for 208 breast lesions, identified a clear total composite choline compounds (tCho) peak of signal-to-noise of ≥2 to represent malignancy (qualitative approach), and regarded tCho concentration equal to or greater than the cut-off value to represent malignancy (quantitative approach). We compared the diagnostic ability of both approaches using the Akaike information criterion (AIC) and McFadden's R (2). RESULTS Histologically, 169 lesions were malignant; 39 were benign. The qualitative approach demonstrated 84.6 % sensitivity and 51.3 % specificity for differentiating malignant and benign lesions. The mean tCho concentration was 1.13 mmol/kg for malignancy, 0.43 mmol/kg for benignity. The optimal cut-off point was 0.61 mmol/kg, use of which achieved 68.1 % sensitivity and 79.4 % specificity. Calculated AIC and R (2) score suggested the superiority of the quantitative approach for differentiating malignancy. CONCLUSIONS Quantitative MRS provides higher specificity than qualitative MRS for differentiating malignant from benign lesions and could be more useful as an additional examination in routine breast MR imaging.
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Affiliation(s)
- Waka Mizukoshi
- Department of Diagnostic Radiology, International Medical Center of Saitama Medical University, 1397-1 Yamane, Hidaka City, Saitama, Japan.
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Venugopal N, McCurdy B, Hovdebo J, Al Mehairi S, Alamri A, Sandhu GS, Sivalingam S, Drachenberg D, Ryner L. Automatic conformal prescription of very selective saturation bands for in vivo 1H-MRSI of the prostate. NMR IN BIOMEDICINE 2012; 25:643-653. [PMID: 22162346 DOI: 10.1002/nbm.1780] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2010] [Revised: 07/11/2011] [Accepted: 07/13/2011] [Indexed: 05/31/2023]
Abstract
An important step in the implementation of three-dimensional in vivo proton magnetic resonance spectroscopic imaging ((1)H-MRSI) of the prostate is the placement of spatial saturation pulses around the region of interest (ROI) for the removal of unwanted contaminating signals from peripheral tissue. The present study demonstrates the use of a technique called conformal voxel magnetic resonance spectroscopy (CV-MRS). This method automates the placement, orientation, timing and flip angle of very selective saturation (VSS) pulses around an irregularly-shaped, user-defined ROI. The method employs a user adjustable number of automatically positioned VSS pulses (20 used in the present study) which null the signal from periprostatic lipids while closely conforming the shape of the excitation voxel to the shape of the prostate. A standard endorectal coil in combination with a torso-phased array coil was used for all in vivo prostate studies. Three-dimensional in vivo prostate (1)H-MRSI data were obtained using the proposed semi-automated CV-MRS technique, and compared with a standard point resolved spectroscopy (PRESS) technique at TE = 130 ms using manual placement of saturation pulses. The in vivo prostate (1)H-MRSI data collected from 12 healthy subjects using the CV-MRS method showed significantly reduced lipid contamination throughout the prostate, and reduced baseline distortions. On average there was a 50 ± 17% (range 12% - 68%) reduction in lipids throughout the prostate. A voxel-by-voxel benchmark test of over 850 voxels showed that there were 63% more peaks fitted using the LCModel when using a Cramer-Rao Lower Bound (CRLB) cut-off of 40% when using the optimized conformal voxel technique in comparison to the manual placement approach. The evaluation of this CV-MRS technique has demonstrated the potential for easy automation of the graphical prescription of saturation bands for use in (1)H-MRSI.
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Affiliation(s)
- N Venugopal
- Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada.
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Tiwari P, Kurhanewicz J, Viswanath S, Sridhar A, Madabhushi A. Multimodal wavelet embedding representation for data combination (MaWERiC): integrating magnetic resonance imaging and spectroscopy for prostate cancer detection. NMR IN BIOMEDICINE 2012; 25:607-619. [PMID: 21960175 PMCID: PMC3298634 DOI: 10.1002/nbm.1777] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2011] [Revised: 06/28/2011] [Accepted: 06/29/2011] [Indexed: 05/28/2023]
Abstract
Recently, both Magnetic Resonance (MR) Imaging (MRI) and Spectroscopy (MRS) have emerged as promising tools for detection of prostate cancer (CaP). However, due to the inherent dimensionality differences in MR imaging and spectral information, quantitative integration of T(2) weighted MRI (T(2)w MRI) and MRS for improved CaP detection has been a major challenge. In this paper, we present a novel computerized decision support system called multimodal wavelet embedding representation for data combination (MaWERiC) that employs, (i) wavelet theory to extract 171 Haar wavelet features from MRS and 54 Gabor features from T(2)w MRI, (ii) dimensionality reduction to individually project wavelet features from MRS and T(2)w MRI into a common reduced Eigen vector space, and (iii), a random forest classifier for automated prostate cancer detection on a per voxel basis from combined 1.5 T in vivo MRI and MRS. A total of 36 1.5 T endorectal in vivo T(2)w MRI and MRS patient studies were evaluated per voxel by MaWERiC using a three-fold cross validation approach over 25 iterations. Ground truth for evaluation of results was obtained by an expert radiologist annotations of prostate cancer on a per voxel basis who compared each MRI section with corresponding ex vivo wholemount histology sections with the disease extent mapped out on histology. Results suggest that MaWERiC based MRS T(2)w meta-classifier (mean AUC, μ = 0.89 ± 0.02) significantly outperformed (i) a T(2)w MRI (using wavelet texture features) classifier (μ = 0.55 ± 0.02), (ii) a MRS (using metabolite ratios) classifier (μ = 0.77 ± 0.03), (iii) a decision fusion classifier obtained by combining individual T(2)w MRI and MRS classifier outputs (μ = 0.85 ± 0.03), and (iv) a data combination method involving a combination of metabolic MRS and MR signal intensity features (μ = 0.66 ± 0.02).
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Affiliation(s)
- Pallavi Tiwari
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854
| | - John Kurhanewicz
- University of California, Department of Radiology, San Francisco, CA, 94143
| | - Satish Viswanath
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854
| | - Akshay Sridhar
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854
| | - Anant Madabhushi
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854
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High Field MR Spectroscopy: Investigating Human Metabolite Levels at High Spectral and Spatial Resolution. HIGH-FIELD MR IMAGING 2012. [DOI: 10.1007/174_2011_201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Hoeks CMA, Barentsz JO, Hambrock T, Yakar D, Somford DM, Heijmink SWTPJ, Scheenen TWJ, Vos PC, Huisman H, van Oort IM, Witjes JA, Heerschap A, Fütterer JJ. Prostate cancer: multiparametric MR imaging for detection, localization, and staging. Radiology 2011; 261:46-66. [PMID: 21931141 DOI: 10.1148/radiol.11091822] [Citation(s) in RCA: 544] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
This review presents the current state of the art regarding multiparametric magnetic resonance (MR) imaging of prostate cancer. Technical requirements and clinical indications for the use of multiparametric MR imaging in detection, localization, characterization, staging, biopsy guidance, and active surveillance of prostate cancer are discussed. Although reported accuracies of the separate and combined multiparametric MR imaging techniques vary for diverse clinical prostate cancer indications, multiparametric MR imaging of the prostate has shown promising results and may be of additional value in prostate cancer localization and local staging. Consensus on which technical approaches (field strengths, sequences, use of an endorectal coil) and combination of multiparametric MR imaging techniques should be used for specific clinical indications remains a challenge. Because guidelines are currently lacking, suggestions for a general minimal protocol for multiparametric MR imaging of the prostate based on the literature and the authors' experience are presented. Computer programs that allow evaluation of the various components of a multiparametric MR imaging examination in one view should be developed. In this way, an integrated interpretation of anatomic and functional MR imaging techniques in a multiparametric MR imaging examination is possible. Education and experience of specialist radiologists are essential for correct interpretation of multiparametric prostate MR imaging findings. Supportive techniques, such as computer-aided diagnosis are needed to obtain a fast, cost-effective, easy, and more reproducible prostate cancer diagnosis out of more and more complex multiparametric MR imaging data.
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Affiliation(s)
- Caroline M A Hoeks
- Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
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Weis J, Jorulf H, Bergman A, Ortiz-Nieto F, Häggman M, Ahlström H. MR spectroscopy of the human prostate using surface coil at 3 T: Metabolite ratios, age-dependent effects, and diagnostic possibilities. J Magn Reson Imaging 2011; 34:1277-84. [DOI: 10.1002/jmri.22746] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Accepted: 07/19/2011] [Indexed: 11/09/2022] Open
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Klomp DWJ, Renema WKJ. Spectroscopic imaging of the mouse brain. Methods Mol Biol 2011; 771:337-51. [PMID: 21874487 DOI: 10.1007/978-1-61779-219-9_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) of the mouse brain reveals a wealth of metabolic information, not only from a single region of interest (single voxel), but spatially mapped over potentially the entire brain. However, MRSI requires challenging methods before the data can be obtained accurately. When applied in vivo, MRSI is generally combined with volume-selective spin perturbation to exclude artifact originating from outside the volume of interest. To obtain good magnetic field (B (0)) uniformity at this volume, accurate B (0) shimming is required. Finally, the immensely large signals originating from water spins need to be suppressed to prevent sidebands that contaminate the spectra, or even saturate the dynamic range of the MR receiver. This chapter describes solutions for these challenges and ends with a rationale between single-voxel MRS versus MRSI.
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Affiliation(s)
- Dennis W J Klomp
- Department of Radiology, University Medical Center, 3584 CX, Utrecht, The Netherlands.
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Ozhinsky E, Vigneron DB, Nelson SJ. Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands. J Magn Reson Imaging 2011; 33:792-802. [PMID: 21448942 DOI: 10.1002/jmri.22507] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
PURPOSE To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands. MATERIALS AND METHODS The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality. RESULTS 3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality. CONCLUSION The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases.
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Affiliation(s)
- Eugene Ozhinsky
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
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