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Naji N, Gee M, Jickling GC, Emery DJ, Saad F, McCreary CR, Smith EE, Camicioli R, Wilman AH. Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo. NMR IN BIOMEDICINE 2024; 37:e5139. [PMID: 38465729 DOI: 10.1002/nbm.5139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 03/12/2024]
Abstract
T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2: 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0 of 3 T or higher with no additional time cost, when standard T2*-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.
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Affiliation(s)
- Nashwan Naji
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Myrlene Gee
- Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
| | - Glen C Jickling
- Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
| | - Derek J Emery
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada
| | - Feryal Saad
- Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Cheryl R McCreary
- Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Eric E Smith
- Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Richard Camicioli
- Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada
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Duan C, Bian X, Cheng K, Lyu J, Xiong Y, Xiao S, Wang X, Duan Q, Li C, Huang J, Hu J, Wang ZJ, Zhou X, Lou X. Synthesized 7T MPRAGE From 3T MPRAGE Using Generative Adversarial Network and Validation in Clinical Brain Imaging: A Feasibility Study. J Magn Reson Imaging 2024; 59:1620-1629. [PMID: 37559435 DOI: 10.1002/jmri.28944] [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: 11/27/2022] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND Ultra-high field 7T MRI can provide excellent tissue contrast and anatomical details, but is often cost prohibitive, and is not widely accessible in clinical practice. PURPOSE To generate synthetic 7T images from widely acquired 3T images with deep learning and to evaluate the feasibility of this approach for brain imaging. STUDY TYPE Prospective. POPULATION 33 healthy volunteers and 89 patients with brain diseases, divided into training, and evaluation datasets in the ratio 4:1. SEQUENCE AND FIELD STRENGTH T1-weighted nonenhanced or contrast-enhanced magnetization-prepared rapid acquisition gradient-echo sequence at both 3T and 7T. ASSESSMENT A generative adversarial network (SynGAN) was developed to produce synthetic 7T images from 3T images as input. SynGAN training and evaluation were performed separately for nonenhanced and contrast-enhanced paired acquisitions. Qualitative image quality of acquired 3T and 7T images and of synthesized 7T images was evaluated by three radiologists in terms of overall image quality, artifacts, sharpness, contrast, and visualization of vessel using 5-point Likert scales. STATISTICAL TESTS Wilcoxon signed rank tests to compare synthetic 7T images with acquired 7T and 3T images and intraclass correlation coefficients to evaluate interobserver variability. P < 0.05 was considered significant. RESULTS Of the 122 paired 3T and 7T MRI scans, 66 were acquired without contrast agent and 56 with contrast agent. The average time to generate synthetic images was ~11.4 msec per slice (2.95 sec per participant). The synthetic 7T images achieved significantly improved tissue contrast and sharpness in comparison to 3T images in both nonenhanced and contrast-enhanced subgroups. Meanwhile, there was no significant difference between acquired 7T and synthetic 7T images in terms of all the evaluation criteria for both nonenhanced and contrast-enhanced subgroups (P ≥ 0.180). DATA CONCLUSION The deep learning model has potential to generate synthetic 7T images with similar image quality to acquired 7T images. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Caohui Duan
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Xiangbing Bian
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Kun Cheng
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Jinhao Lyu
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Yongqin Xiong
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Sa Xiao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Xueyang Wang
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Qi Duan
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Chenxi Li
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Jiayu Huang
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Jianxing Hu
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Z Jane Wang
- Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Xin Lou
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
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Bian B, Hou L, Chai Y, Jiang Y, Pan X, Sun Y, Wang H, Qiu D, Yu Z, Zhao H, Zhang H, Meng F, Zhang L. Visualizing the Habenula Using 3T High-Resolution MP2RAGE and QSM: A Preliminary Study. AJNR Am J Neuroradiol 2024; 45:504-510. [PMID: 38453416 PMCID: PMC11288573 DOI: 10.3174/ajnr.a8156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 12/18/2023] [Indexed: 03/09/2024]
Abstract
BACKGROUND AND PURPOSE The habenula is a key node in the regulation of emotion-related behavior. Accurate visualization of the habenula and its reliable quantitative analysis is vital for the assessment of psychiatric disorders. To obtain high-contrast habenula images and allow them to be compatible with clinical applications, this preliminary study compared 3T MP2RAGE and quantitative susceptibility mapping with MPRAGE by evaluating the habenula segmentation performance. MATERIALS AND METHODS Ten healthy volunteers were scanned twice with 3T MPRAGE and MP2RAGE and once with quantitative susceptibility mapping. Image quality and visibility of habenula anatomic features were analyzed by 3 radiologists using a 5-point scale. Contrast assessments of the habenula and thalamus were also performed. The reproducibility of the habenula volume from MPRAGE and MP2RAGE was evaluated by manual segmentation and the Multiple Automatically Generated Template brain segmentation algorithm (MAGeTbrain). T1 values and susceptibility were measured in the whole habenula and habenula geometric subregion using MP2RAGE T1-mapping and quantitative susceptibility mapping. RESULTS The 3T MP2RAGE and quantitative susceptibility mapping demonstrated clear boundaries and anatomic features of the habenula compared with MPRAGE, with a higher SNR and contrast-to-noise ratio (all P < .05). Additionally, 3T MP2RAGE provided reliable habenula manual and MAGeTbrain segmentation volume estimates with greater reproducibility. T1-mapping derived from MP2RAGE was highly reliable, and susceptibility contrast was highly nonuniform within the habenula. CONCLUSIONS We identified an optimized sequence combination (3T MP2RAGE combined with quantitative susceptibility mapping) that may be useful for enhancing habenula visualization and yielding more reliable quantitative data.
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Affiliation(s)
- BingYang Bian
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Lin Hou
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - YaTing Chai
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - YueLuan Jiang
- MR Scientific Marketing, Diagnostic Imaging (Y.J.), Siemens Healthineers Ltd, Beijing, China
| | - XingChen Pan
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Yang Sun
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - HongChao Wang
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - DongDong Qiu
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - ZeChen Yu
- Siemens Healthineers Digital Technology (Shanghai) Co Ltd (Z.Y.), Shanghai, China
| | - Hua Zhao
- Department of Physiology (H. Zhao), College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - HuiMao Zhang
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - FanYang Meng
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Lei Zhang
- From the Department of Radiology (B.B., L.H., Y.C., X.P., Y.S., H.W., D.Q., H. Zhang, F.M., L.Z.), Jilin Provincial Key Laboratory of Medical Imaging and Big Data, Radiology and Technology Innovation Center of Jilin Province, Jilin Provincial International Joint Research Center of Medical Artificial Intelligence, The First Hospital of Jilin University, Changchun, Jilin, China
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Runderkamp BA, Roos T, van der Zwaag W, Strijkers GJ, Caan MWA, Nederveen AJ. Whole-liver flip-angle shimming at 7 T using parallel-transmit k T -point pulses and Fourier phase-encoded DREAM B 1 + mapping. Magn Reson Med 2024; 91:75-90. [PMID: 37799015 DOI: 10.1002/mrm.29819] [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: 03/16/2023] [Revised: 06/18/2023] [Accepted: 07/13/2023] [Indexed: 10/07/2023]
Abstract
PURPOSE To obtain homogeneous signal throughout the human liver at 7 T. Flip angle (FA) shimming in 7T whole-liver imaging was performed through parallel-transmit kT -point pulses based on subject-specific multichannel absoluteB 1 + $$ {\mathrm{B}}_1^{+} $$ maps from Fourier phase-encoded dual refocusing echo acquisition mode (PE-DREAM). METHODS The optimal number of Fourier phase-encoding steps for PE-DREAMB 1 + $$ {\mathrm{B}}_1^{+} $$ mapping was determined for a 7T eight-channel parallel-transmission system. FA shimming experiments were performed in the liver of 7 healthy subjects with varying body mass index. In these subjects, firstB 0 $$ {\mathrm{B}}_0 $$ shimming and Fourier PE-DREAMB 1 + $$ {\mathrm{B}}_1^{+} $$ mapping were performed. Subsequently, three small-flip-angle 3D gradient-echo scans were acquired, comparing a circularly polarized (CP) mode, a phase shim, and a kT -point pulse. Resulting homogeneity was assessed and compared with estimated FA maps and distributions. RESULTS Fourier PE-DREAM with 13 phase-encoding steps resulted in a good tradeoff betweenB 1 + $$ {\mathrm{B}}_1^{+} $$ accuracy and scan time. Lower coefficient of variation values (average [min-max] across subjects) of the estimated FA in the volume of interest were observed using kT -points (7.4 [6.6%-8.0%]), compared with phase shimming (18.8 [12.9%-23.4%], p < 0.001) and CP (43.2 [39.4%-47.1%], p < 0.001). kT -points delivered whole-liver images with the nominal FA and the highest degree of homogeneity. CP and phase shimming resulted in either inaccurate or imprecise FA distributions. Here, locations having suboptimal FA in the estimated FA maps corresponded to liver areas suffering from inconsistent signal intensity and T1 -weighting in the gradient-echo scans. CONCLUSION Homogeneous whole-liver 3D gradient-echo acquisitions at 7 T can be obtained with eight-channel kT -point pulses calculated based on subject-specific multichannel absolute Fourier PE-DREAMB 1 + $$ {\mathrm{B}}_1^{+} $$ maps.
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Affiliation(s)
- Bobby A Runderkamp
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Thomas Roos
- Spinoza Centre for Neuroimaging, Royal Netherlands Academy for Arts and Sciences (KNAW), Amsterdam, the Netherlands
- High-Field Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Wietske van der Zwaag
- Spinoza Centre for Neuroimaging, Royal Netherlands Academy for Arts and Sciences (KNAW), Amsterdam, the Netherlands
- Computational and Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
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Woodward OB, Driver I, Schwarz ST, Hart E, Wise R. Assessment of brainstem function and haemodynamics by MRI: challenges and clinical prospects. Br J Radiol 2023; 96:20220940. [PMID: 37721043 PMCID: PMC10607409 DOI: 10.1259/bjr.20220940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 04/25/2023] [Accepted: 05/24/2023] [Indexed: 09/19/2023] Open
Abstract
MRI offers techniques for non-invasively measuring a range of aspects of brain tissue function. Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to assess neural activity, based on the brain's haemodynamic response, while arterial spin labelling (ASL) MRI is a non-invasive method of quantitatively mapping cerebral perfusion. Both techniques can be applied to measure cerebrovascular reactivity (CVR), an important marker of the health of the cerebrovascular system. BOLD, ASL and CVR have been applied to study a variety of disease processes and are already used in certain clinical circumstances. The brainstem is a critical component of the central nervous system and is implicated in a variety of disease processes. However, its function is difficult to study using MRI because of its small size and susceptibility to physiological noise. In this article, we review the physical and biological underpinnings of BOLD and ASL and their application to measure CVR, discuss the challenges associated with applying them to the brainstem and the opportunities for brainstem MRI in the research and clinical settings. With further optimisation, functional MRI techniques could feasibly be used to assess brainstem haemodynamics and neural activity in the clinical setting.
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Affiliation(s)
- Owen Bleddyn Woodward
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Ian Driver
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | | | - Emma Hart
- University of Bristol, Bristol, United Kingdom
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van Horen T, Siero J, Bhogal A, Petridou N, Báez-Yáñez M. Microvascular Specificity of Spin Echo BOLD fMRI: Impact of EPI Echo Train Length. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.15.557938. [PMID: 37745507 PMCID: PMC10516014 DOI: 10.1101/2023.09.15.557938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
A spatially specific fMRI acquisition requires specificity to the microvasculature that serves active neuronal sites. Macrovascular contributions will reduce the microvascular specificity but can be reduced by using spin echo (SE) sequences that use a π pulse to refocus static field inhomogeneities near large veins. The microvascular specificity of a SE-echo planar imaging (SE-EPI) scan depends on the echo train length (ETL)-duration, but the dependence is not well-characterized in humans at 7T. To determine how microvascular-specific SE-EPI BOLD is in humans at 7T, we developed a Monte Carlo voxel model that computes the signal of a proton ensemble residing in a vasculature subjected to a SE-EPI pulse sequence. We characterized the ETL-duration dependence of the microvascular specificity by simulating the BOLD signal as a function of ETL, the range adhering to experimentally realistic readouts. We performed a validation experiment for our simulation observations, in which we acquired a set of SE-EPI BOLD time series with varying ETL during a hyperoxic gas challenge. Both our simulations and measurements show an increase in macrovascular contamination as a function of ETL, with an increase of 30% according to our simulation and 60% according to our validation experiment between the shortest and longest ETL durations (23.1 - 49.7 ms). We conclude that the microvascular specificity decreases heavily with increasing ETL-durations. We recommend reducing the ETL-duration as much as possible to minimize macrovascular contamination in SE-EPI BOLD experiments. We additionally recommend scanning at high resolutions to minimize partial volume effects with CSF. CSF voxels show a large BOLD response, which can be attributed to both the presence of large veins (high blood volume) and molecular oxygen-induced T1-shortening (significant in a hyperoxia experiment). The magnified BOLD signal in a GM-CSF partial volume voxel reduces the desired microvascular specificity and, therefore, will hinder the interpretation of functional MRI activation patterns.
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Affiliation(s)
- T.W.P. van Horen
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - J.C.W. Siero
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
- Spinoza Center for Neuroimaging, Amsterdam, The Netherlands
| | - A.A. Bhogal
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - N. Petridou
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - M.G. Báez-Yáñez
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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Tao S, Zhou X, Greco E, Gupta V, Freund BE, Westerhold EM, Feyissa AM, Tatum WO, Grewal S, Patel V, Middlebrooks EH. Edge-Enhancing Gradient-Echo MP2RAGE for Clinical Epilepsy Imaging at 7T. AJNR Am J Neuroradiol 2023; 44:268-270. [PMID: 36732031 PMCID: PMC10187818 DOI: 10.3174/ajnr.a7782] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 01/03/2023] [Indexed: 02/04/2023]
Abstract
The 3D edge-enhancing gradient-echo (EDGE) MR imaging sequence offers superior contrast-to-noise ratio in the detection of focal cortical dysplasia. EDGE could benefit from 7T MR imaging but also faces challenges such as image inhomogeneity and low acquisition efficiency. We propose an EDGE-MP2RAGE sequence that can provide both EDGE and T1-weighted contrast, simultaneously, improving data-acquisition efficiency. We demonstrate that with sequence optimization, EDGE images with sufficient uniformity and T1-weighted images with high gray-to-white matter contrast can be achieved.
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Affiliation(s)
- S Tao
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | - X Zhou
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | - E Greco
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | - V Gupta
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | | | - E M Westerhold
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | | | | | - S Grewal
- Neurosurgery (S.G., E.H.M.), Mayo Clinic, Jacksonville, Florida
| | - V Patel
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
| | - E H Middlebrooks
- From the Departments of Radiology (S.T., X.Z., E.G., V.G., E.M.W., V.P., E.H.M.)
- Neurosurgery (S.G., E.H.M.), Mayo Clinic, Jacksonville, Florida
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Jacobs SM, Versteeg E, van der Kolk AG, Visser LNC, Oliveira ÍAF, van Maren E, Klomp DWJ, Siero JCW. Image quality and subject experience of quiet T1-weighted 7-T brain imaging using a silent gradient coil. Eur Radiol Exp 2022; 6:36. [PMID: 36042139 PMCID: PMC9428090 DOI: 10.1186/s41747-022-00293-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/16/2022] [Indexed: 11/17/2022] Open
Abstract
Objectives Acoustic noise in magnetic resonance imaging (MRI) negatively impacts patients. We assessed a silent gradient coil switched at 20 kHz combined with a T1-weighted magnetisation prepared rapid gradient-echo (MPRAGE) sequence at 7 T. Methods Five healthy subjects (21–29 years; three females) without previous 7-T MRI experience underwent both a quiet MPRAGE (Q-MPRAGE) and conventional MPRAGE (C-MPRAGE) sequence twice. Image quality was assessed quantitatively, and qualitatively by two neuroradiologists. Sound level was measured objectively and rated subjectively on a 0 to 10 scale by all subjects immediately following each sequence and after the whole examination (delayed). All subjects also reported comfort level, overall experience and willingness to undergo the sequence again. Results Compared to C-MPRAGE, Q-MPRAGE showed higher signal-to-noise ratio (10%; p = 0.012) and lower contrast-to-noise ratio (20%; p < 0.001) as well as acceptable to good image quality. Q-MPRAGE produced 27 dB lower sound level (76 versus 103 dB). Subjects reported lower sound level for Q-MPRAGE both immediate (4.4 ± 1.4 versus 6.4 ± 1.3; p = 0.007) and delayed (4.6 ± 1.4 versus 6.3 ± 1.3; p = 0.005), while they rated comfort level (7.4 ± 1.0 versus 6.1 ± 1.7; p = 0.016) and overall experience (7.6 ± 1.0 versus 6.0 ± 0.9; p = 0.005) higher. Willingness to undergo the sequence again was also higher, however not significantly (8.1 ± 1.0 versus 7.2 ± 1.3; p = 0.066). Conclusion Q-MPRAGE using a silent gradient coil reduced sound level by 27 dB compared to C-MPRAGE at 7 T while featuring acceptable-to-good image quality and a quieter and more pleasant subject experience.
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Affiliation(s)
- Sarah M Jacobs
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - Edwin Versteeg
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - Anja G van der Kolk
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.,Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Leonie N C Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.,Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institute, Stockholm, Sweden
| | - Ícaro A F Oliveira
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands.,Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | - Emiel van Maren
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dennis W J Klomp
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeroen C W Siero
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.,Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
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Oliveira ÍAF, Cai Y, Hofstetter S, Siero JCW, van der Zwaag W, Dumoulin SO. Comparing BOLD and VASO-CBV population receptive field estimates in human visual cortex. Neuroimage 2021; 248:118868. [PMID: 34974115 DOI: 10.1016/j.neuroimage.2021.118868] [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: 10/28/2021] [Revised: 12/20/2021] [Accepted: 12/29/2021] [Indexed: 10/19/2022] Open
Abstract
Vascular Space Occupancy (VASO) is an alternative fMRI approach based on changes in Cerebral Blood Volume (CBV). VASO-CBV fMRI can provide higher spatial specificity than the blood oxygenation level-dependent (BOLD) method because the CBV response is thought to be limited to smaller vessels. To investigate how this technique compares to BOLD fMRI for cognitive neuroscience applications, we compared population receptive field (pRF) mapping estimates between BOLD and VASO-CBV. We hypothesized that VASO-CBV would elicit distinct pRF properties compared to BOLD. Specifically, since pRF size estimates also depend on vascular sources, we hypothesized that reduced vascular blurring might yield narrower pRFs for VASO-CBV measurements. We used a VASO sequence with a double readout 3D EPI sequence at 7T to simultaneously measure VASO-CBV and BOLD responses in the visual cortex while participants viewed conventional pRF mapping stimuli. Both VASO-CBV and BOLD images show similar eccentricity and polar angle maps across all participants. Compared to BOLD-based measurements, VASO-CBV yielded lower tSNR and variance explained. The pRF size changed with eccentricity similarly for VASO-CBV and BOLD, and the pRF size estimates were similar for VASO-CBV and BOLD, even when we equate variance explained between VASO-CBV and BOLD. This result suggests that the vascular component of the pRF size is not dominating in either VASO-CBV or BOLD.
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Affiliation(s)
- Ícaro A F Oliveira
- Spinoza Centre for Neuroimaging, Meibergdreef 75, Amsterdam 1105 BK, the Netherland; Experimental and Applied Psychology, VU University, Amsterdam, the Netherland.
| | - Yuxuan Cai
- Spinoza Centre for Neuroimaging, Meibergdreef 75, Amsterdam 1105 BK, the Netherland; Experimental and Applied Psychology, VU University, Amsterdam, the Netherland
| | - Shir Hofstetter
- Spinoza Centre for Neuroimaging, Meibergdreef 75, Amsterdam 1105 BK, the Netherland
| | - Jeroen C W Siero
- Spinoza Centre for Neuroimaging, Meibergdreef 75, Amsterdam 1105 BK, the Netherland; Radiology, Utrecht Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherland
| | | | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Meibergdreef 75, Amsterdam 1105 BK, the Netherland; Experimental and Applied Psychology, VU University, Amsterdam, the Netherland; Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherland
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Colizoli O, de Gee JW, van der Zwaag W, Donner TH. Functional magnetic resonance imaging responses during perceptual decision-making at 3 and 7 T in human cortex, striatum, and brainstem. Hum Brain Mapp 2021; 43:1265-1279. [PMID: 34816533 PMCID: PMC8837598 DOI: 10.1002/hbm.25719] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/03/2021] [Accepted: 11/07/2021] [Indexed: 11/29/2022] Open
Abstract
While functional magnetic resonance imaging (fMRI) at ultra‐high field (7 T) promises a general increase in sensitivity compared to lower field strengths, the benefits may be most pronounced for specific applications. The current study aimed to evaluate the relative benefit of 7 over 3 T fMRI for the assessment of responses evoked in different brain regions by a well‐controlled cognitive task. At 3 and 7 T, the same participants made challenging perceptual decisions about visual motion combined with monetary rewards for correct choices. Previous work on this task has extensively characterized the underlying cognitive computations and single‐cell responses in cortical and subcortical structures. We quantified the evoked fMRI responses in extrastriate visual cortical areas, the striatum, and the brainstem during the decision interval and the post‐feedback interval of the task. The dependence of response amplitudes on field strength during the decision interval differed between cortical, striatal, and brainstem regions, with a generally bigger 7 versus 3 T benefit in subcortical structures. We also found stronger responses during relatively easier than harder decisions at 7 T for dopaminergic midbrain nuclei, in line with reward expectation. Our results demonstrate the potential of 7 T fMRI for illuminating the contribution of small brainstem nuclei to the orchestration of cognitive computations in the human brain.
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Affiliation(s)
- Olympia Colizoli
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jan Willem de Gee
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Tobias H Donner
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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