1
|
Arshad SM, Potter LC, Chen C, Liu Y, Chandrasekaran P, Crabtree C, Tong MS, Simonetti OP, Han Y, Ahmad R. Motion-robust free-running volumetric cardiovascular MRI. Magn Reson Med 2024; 92:1248-1262. [PMID: 38733066 PMCID: PMC11209797 DOI: 10.1002/mrm.30123] [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: 12/01/2023] [Revised: 03/31/2024] [Accepted: 04/01/2024] [Indexed: 05/13/2024]
Abstract
PURPOSE To present and assess an outlier mitigation method that makes free-running volumetric cardiovascular MRI (CMR) more robust to motion. METHODS The proposed method, called compressive recovery with outlier rejection (CORe), models outliers in the measured data as an additive auxiliary variable. We enforce MR physics-guided group sparsity on the auxiliary variable, and jointly estimate it along with the image using an iterative algorithm. For evaluation, CORe is first compared to traditional compressed sensing (CS), robust regression (RR), and an existing outlier rejection method using two simulation studies. Then, CORe is compared to CS using seven three-dimensional (3D) cine, 12 rest four-dimensional (4D) flow, and eight stress 4D flow imaging datasets. RESULTS Our simulation studies show that CORe outperforms CS, RR, and the existing outlier rejection method in terms of normalized mean square error and structural similarity index across 55 different realizations. The expert reader evaluation of 3D cine images demonstrates that CORe is more effective in suppressing artifacts while maintaining or improving image sharpness. Finally, 4D flow images show that CORe yields more reliable and consistent flow measurements, especially in the presence of involuntary subject motion or exercise stress. CONCLUSION An outlier rejection method is presented and tested using simulated and measured data. This method can help suppress motion artifacts in a wide range of free-running CMR applications.
Collapse
Affiliation(s)
- Syed M. Arshad
- Biomedical Engineering, The Ohio State University, Ohio,
USA
- Electrical & Computer Engineering, The Ohio State
University, Ohio, USA
| | - Lee C. Potter
- Electrical & Computer Engineering, The Ohio State
University, Ohio, USA
- Davis Heart and Lung Research Institute, The Ohio State
University Wexner Medical Center, Ohio, USA
| | - Chong Chen
- Biomedical Engineering, The Ohio State University, Ohio,
USA
- Electrical & Computer Engineering, The Ohio State
University, Ohio, USA
| | - Yingmin Liu
- Davis Heart and Lung Research Institute, The Ohio State
University Wexner Medical Center, Ohio, USA
| | - Preethi Chandrasekaran
- Davis Heart and Lung Research Institute, The Ohio State
University Wexner Medical Center, Ohio, USA
| | | | - Matthew S. Tong
- Internal Medicine, The Ohio State University Wexner Medical
Center, Ohio, USA
| | - Orlando P. Simonetti
- Davis Heart and Lung Research Institute, The Ohio State
University Wexner Medical Center, Ohio, USA
- Internal Medicine, The Ohio State University Wexner Medical
Center, Ohio, USA
| | - Yuchi Han
- Internal Medicine, The Ohio State University Wexner Medical
Center, Ohio, USA
| | - Rizwan Ahmad
- Biomedical Engineering, The Ohio State University, Ohio,
USA
- Electrical & Computer Engineering, The Ohio State
University, Ohio, USA
- Davis Heart and Lung Research Institute, The Ohio State
University Wexner Medical Center, Ohio, USA
| |
Collapse
|
2
|
Chen C, Liu Y, Simonetti OP, Tong M, Jin N, Bacher M, Speier P, Ahmad R. Cardiac and respiratory motion extraction for MRI using pilot tone-a patient study. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:93-105. [PMID: 37874445 PMCID: PMC10842141 DOI: 10.1007/s10554-023-02966-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 09/21/2023] [Indexed: 10/25/2023]
Abstract
This study aims to evaluate the accuracy and reliability of the cardiac and respiratory signals extracted from Pilot Tone (PT) in patients clinically referred for cardiovascular MRI. Twenty-three patients were scanned under free-breathing conditions using a balanced steady-state free-precession real-time (RT) cine sequence on a 1.5T scanner. The PT signal was generated by a built-in PT transmitter integrated within the body array coil, and retrospectively processed to extract respiratory and cardiac signals. For comparison, ECG and BioMatrix (BM) respiratory sensor signals were also synchronously recorded. To assess the performances of PT, ECG, and BM, cardiac and respiratory signals extracted from the RT cine images were used as the ground truth. The respiratory motion extracted from PT correlated positively with the image-derived respiratory signal in all cases and showed a stronger correlation (absolute coefficient: 0.95 ± 0.09) than BM (0.72 ± 0.24). For the cardiac signal, PT trigger jitter (standard deviation of PT trigger locations relative to ECG triggers) ranged from 6.6 to 83.3 ms, with a median of 21.8 ms. The mean absolute difference between the PT and corresponding ECG cardiac cycle duration was less than 5% of the average ECG RR interval for 21 out of 23 patients. We did not observe a significant linear dependence (p > 0.28) of PT delay and PT jitter on the patients' BMI or cardiac cycle duration. This study demonstrates the potential of PT to monitor both respiratory and cardiac motion in patients clinically referred for cardiovascular MRI.
Collapse
Affiliation(s)
- Chong Chen
- Department of Biomedical Engineering, The Ohio State University, Columbus, US.
| | - Yingmin Liu
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Orlando P Simonetti
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Matthew Tong
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, US
| | - Ning Jin
- Siemens Medical Solutions USA, Inc, Columbus, US
| | | | | | - Rizwan Ahmad
- Department of Biomedical Engineering, The Ohio State University, Columbus, US
| |
Collapse
|
3
|
Tucker D, Zhao S, Potter LC. Maximum Likelihood Estimation in Mixed Integer Linear Models. IEEE SIGNAL PROCESSING LETTERS 2023; 30:1557-1561. [PMID: 37981947 PMCID: PMC10655770 DOI: 10.1109/lsp.2023.3324833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
We consider the maximum likelihood (ML) parameter estimation problem for mixed integer linear models with arbitrary noise covariance. This problem appears in applications such as single frequency estimation, phase contrast imaging, and direction of arrival (DoA) estimation. Parameter estimates are found by solving a closest lattice point problem, which requires a lattice basis. In this letter, we present a lattice basis construction for ML parameter estimation and conclude with simulated results from DoA estimation and phase contrast imaging.
Collapse
Affiliation(s)
- David Tucker
- Department of Electrical & Computer Engineering, Ohio State University, Columbus, OH 43210
| | - Shen Zhao
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA 94304
| | - Lee C Potter
- Department of Electrical & Computer Engineering, Ohio State University, Columbus, OH 43210
| |
Collapse
|
4
|
Falcão MBL, Rossi GMC, Rutz T, Prša M, Tenisch E, Ma L, Weiss EK, Baraboo JJ, Yerly J, Markl M, Stuber M, Roy CW. Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI. Magn Reson Med 2023; 90:117-132. [PMID: 36877140 PMCID: PMC10149606 DOI: 10.1002/mrm.29634] [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: 08/25/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/07/2023]
Abstract
PURPOSE To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. METHODS Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. RESULTS For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04± $$ \pm $$ 0.32 mm and 0.31± $$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02± $$ \pm $$ 0.51 mm up to 5.85± $$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32± $$ \pm $$ 0.11 cm2 , 11.1± $$ \pm $$ 3.5 mL, and 22.3± $$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10± $$ \pm $$ 0.03 cm2 , 2.6± $$ \pm $$ 0.7 mL, and 5.1± 0 $$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92± $$ \pm $$ 2.95 cm2 , 5.06± $$ \pm $$ 2.64 cm2 , 4.87± $$ \pm $$ 2.57 cm2 , 4.87± $$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 = 0.92) and peak flow (r2 = 0.94), followed by navigator-gated 4D flow (r2 = 0.83 and r2 = 0.86, respectively), and uncorrected 4D flow (r2 = 0.69 and r2 = 0.86, respectively). CONCLUSION fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.
Collapse
Affiliation(s)
- Mariana B. L. Falcão
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Giulia M. C. Rossi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prša
- Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Elizabeth K. Weiss
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Justin J. Baraboo
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Christopher W. Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| |
Collapse
|
5
|
Kim D, Jen ML, Eisenmenger LB, Johnson KM. Accelerated 4D-flow MRI with 3-point encoding enabled by machine learning. Magn Reson Med 2023; 89:800-811. [PMID: 36198027 PMCID: PMC9712238 DOI: 10.1002/mrm.29469] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/22/2022] [Accepted: 09/06/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE To investigate the acceleration of 4D-flow MRI using a convolutional neural network (CNN) that produces three directional velocities from three flow encodings, without requiring a fourth reference scan measuring background phase. METHODS A fully 3D CNN using a U-net architecture was trained in a block-wise fashion to take complex images from three flow encodings and to produce three real-valued images for each velocity component. Using neurovascular 4D-flow scans (n = 144), the CNN was trained to predict velocities computed from four flow encodings by standard reconstruction including correction for residual background phase offsets. Methods to optimize loss functions were investigated, including magnitude, complex difference, and uniform velocity weightings. Subsequently, 3-point encoding was evaluated using cross validation of pixelwise correlation, flow measurements in major arteries, and in experiments with data at differing acceleration rates than the training data. RESULTS The CNN-produced 3-point velocities showed excellent agreements with the 4-point velocities, both qualitatively in velocity images, in flow rate measures, and quantitatively in regression analysis (slope = 0.96, R2 = 0.992). Optimizing the training to focus on vessel velocities rather than the global velocity error and improved the correlation of velocity within vessels themselves. The lowest error was observed when the loss function used uniform velocity weighting, in which the magnitude-weighted inverse of the velocity frequency uniformly distributed weighting across all velocity ranges. When applied to highly accelerated data, the 3-point network maintained a high correlation with ground truth data and demonstrated a denoising effect. CONCLUSION The 4D-flow MRI can be accelerated using machine learning requiring only three flow encodings to produce three-directional velocity maps with small errors.
Collapse
Affiliation(s)
- Dahan Kim
- Department of Physics, University of Wisconsin, Madison, Wisconsin, USA,Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Mu-Lan Jen
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Laura B. Eisenmenger
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Kevin M. Johnson
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA,Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| |
Collapse
|
6
|
Varga-Szemes A, Halfmann M, Schoepf UJ, Jin N, Kilburg A, Dargis DM, Düber C, Ese A, Aquino G, Xiong F, Kreitner KF, Markl M, Emrich T. Highly Accelerated Compressed-Sensing 4D Flow for Intracardiac Flow Assessment. J Magn Reson Imaging 2022. [PMID: 36264176 DOI: 10.1002/jmri.28484] [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: 08/02/2022] [Revised: 10/03/2022] [Accepted: 10/04/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Four-dimensional (4D) flow MRI allows for the quantification of complex flow patterns; however, its clinical use is limited by its inherently long acquisition time. Compressed sensing (CS) is an acceleration technique that provides substantial reduction in acquisition time. PURPOSE To compare intracardiac flow measurements between conventional and CS-based highly accelerated 4D flow acquisitions. STUDY TYPE Prospective. SUBJECTS Fifty healthy volunteers (28.0 ± 7.1 years, 24 males). FIELD STRENGTH/SEQUENCE Whole heart time-resolved 3D gradient echo with three-directional velocity encoding (4D flow) with conventional parallel imaging (factor 3) as well as CS (factor 7.7) acceleration at 3 T. ASSESSMENT 4D flow MRI data were postprocessed by applying a valve tracking algorithm. Acquisition times, flow volumes (mL/cycle) and diastolic function parameters (ratio of early to late diastolic left ventricular peak velocities [E/A] and ratio of early mitral inflow velocity to mitral annular early diastolic velocity [E/e']) were quantified by two readers. STATISTICAL TESTS Paired-samples t-test and Wilcoxon rank sum test to compare measurements. Pearson correlation coefficient (r), Bland-Altman-analysis (BA) and intraclass correlation coefficient (ICC) to evaluate agreement between techniques and readers. A P value < 0.05 was considered statistically significant. RESULTS A significant improvement in acquisition time was observed using CS vs. conventional accelerated acquisition (6.7 ± 1.3 vs. 12.0 ± 1.3 min). Net forward flow measurements for all valves showed good correlation (r > 0.81) and agreement (ICCs > 0.89) between conventional and CS acceleration, with 3.3%-8.3% underestimation by the CS technique. Evaluation of diastolic function showed 3.2%-17.6% error: E/A 2.2 [1.9-2.4] (conventional) vs. 2.3 [2.0-2.6] (CS), BA bias 0.08 [-0.81-0.96], ICC 0.82; and E/e' 4.6 [3.9-5.4] (conventional) vs. 3.8 [3.4-4.3] (CS), BA bias -0.90 [-2.31-0.50], ICC 0.89. DATA CONCLUSION Analysis of intracardiac flow patterns and evaluation of diastolic function using a highly accelerated 4D flow sequence prototype is feasible, but it shows underestimation of flow measurements by approximately 10%. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Moritz Halfmann
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany.,German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Ning Jin
- Siemens Medical Solutions USA Inc., Chicago, Illinois, USA
| | - Anton Kilburg
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Danielle M Dargis
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Christoph Düber
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Amir Ese
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Gilberto Aquino
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
| | - Fei Xiong
- Siemens Medical Solutions USA Inc., Chicago, Illinois, USA
| | - Karl-Friedrich Kreitner
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Michael Markl
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.,Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina.,Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany.,German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
| |
Collapse
|
7
|
Huang S, Lah JJ, Allen JW, Qiu D. A probabilistic Bayesian approach to recover R2*$$ {R}_{2\ast } $$ map and phase images for quantitative susceptibility mapping. Magn Reson Med 2022; 88:1624-1642. [PMID: 35672899 PMCID: PMC10627109 DOI: 10.1002/mrm.29303] [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: 02/28/2022] [Revised: 04/04/2022] [Accepted: 04/26/2022] [Indexed: 12/29/2022]
Abstract
PURPOSE Undersampling is used to reduce the scan time for high-resolution three-dimensional magnetic resonance imaging. In order to achieve better image quality and avoid manual parameter tuning, we propose a probabilistic Bayesian approach to recover R 2 ∗ $$ {R}_2^{\ast } $$ map and phase images for quantitative susceptibility mapping (QSM), while allowing automatic parameter estimation from undersampled data. THEORY Sparse prior on the wavelet coefficients of images is interpreted from a Bayesian perspective as sparsity-promoting distribution. A novel nonlinear approximate message passing (AMP) framework that incorporates a mono-exponential decay model is proposed. The parameters are treated as unknown variables and jointly estimated with image wavelet coefficients. METHODS Undersampling takes place in the y-z plane of k-space according to the Poisson-disk pattern. Retrospective undersampling is performed to evaluate the performances of different reconstruction approaches, prospective undersampling is performed to demonstrate the feasibility of undersampling in practice. RESULTS The proposed AMP with parameter estimation (AMP-PE) approach successfully recovers R 2 ∗ $$ {R}_2^{\ast } $$ maps and phase images for QSM across various undersampling rates. It is more computationally efficient, and performs better than the state-of-the-art l 1 $$ {l}_1 $$ -norm regularization (L1) approach in general, except a few cases where the L1 approach performs as well as AMP-PE. CONCLUSION AMP-PE achieves better performance by drawing information from both the sparse prior and the mono-exponential decay model. It does not require parameter tuning, and works with a clinical, prospective undersampling scheme where parameter tuning is often impossible or difficult due to the lack of ground-truth image.
Collapse
Affiliation(s)
- Shuai Huang
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, 30322, USA
| | - James J. Lah
- Department of Neurology, Emory University, Atlanta, GA, 30322, USA
| | - Jason W. Allen
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, 30322, USA
| | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, 30322, USA
| |
Collapse
|
8
|
Deux JF, Crowe LA, Genecand L, Hachulla AL, Glessgen CG, Noble S, Beghetti M, Ning J, Giese D, Lador F, Vallée JP. Correlation between Pulmonary Artery Pressure and Vortex Duration Determined by 4D Flow MRI in Main Pulmonary Artery in Patients with Suspicion of Chronic Thromboembolic Pulmonary Hypertension (CTEPH). J Clin Med 2022; 11:jcm11175237. [PMID: 36079178 PMCID: PMC9457422 DOI: 10.3390/jcm11175237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/23/2022] [Accepted: 09/01/2022] [Indexed: 11/16/2022] Open
Abstract
Chronic thromboembolic pulmonary hypertension (CTEPH) is one of the causes of pulmonary hypertension (PH) and requires invasive measurement of the mean pulmonary artery pressure (mPAP) during right heart catheterisation (RHC) for the diagnosis. 4D flow MRI could provide non-invasive parameters to estimate the mPAP. Twenty-five patients with suspected CTEPH underwent cardiac MRI. Mean vortex duration (%), pulmonary distensibility, right ventricular volumes and function were measured using 4D flow MRI and cine sequences, and compared with the mPAP measured by RHC. The mPAP measured during RHC was 33 ± 16 mmHg (10−66 mmHg). PH (defined as mPAP > 20 mmHg) was present in 19 of 25 patients (76%). A vortical flow was observed in all but two patients (92%) on 4D flow images, and vortex duration showed good correlation with the mPAP (r = 0.805; p < 0.0001). Youden index analysis showed that a vortex duration of 8.6% of the cardiac cycle provided a 95% sensitivity and an 83% specificity to detect PH. Reliability for the measurement of vortex duration was excellent for both intra-observer ICC = 0.823 and inter-observer ICC = 0.788. Vortex duration could be a useful parameter to non-invasively estimate mPAP in patients with suspected CTEPH.
Collapse
Affiliation(s)
- Jean-François Deux
- Division of Radiology, Diagnostic Department Geneva University Hospitals, 1205 Geneva, Switzerland
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
- Correspondence: ; Tel.: +41-66-145-41-73
| | - Lindsey A. Crowe
- Division of Radiology, Diagnostic Department Geneva University Hospitals, 1205 Geneva, Switzerland
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
| | - Léon Genecand
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
- Division of Pulmonary Medicine, Department of Medicine, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Anne-Lise Hachulla
- Division of Radiology, Diagnostic Department Geneva University Hospitals, 1205 Geneva, Switzerland
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Carl G. Glessgen
- Division of Radiology, Diagnostic Department Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Stéphane Noble
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
- Division of Cardiology, Department of Medicine, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Maurice Beghetti
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
- Paediatric Cardiology Unit, Geneva University Hospitals, 1205 Geneva, Switzerland
- Centre Universitaire Romand de Cardiologie et Chirurgie Cardiaque Pédiatrique, University of Geneva and Lausanne, 1205 Geneva, Switzerland
| | - Jin Ning
- Siemens Medical Solutions USA Inc., Cleveland, OH 44125, USA
| | - Daniel Giese
- Magnetic Resonance, Siemens Healthcare GmbH, 91052 Erlangen, Germany
| | - Frédéric Lador
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
- Division of Pulmonary Medicine, Department of Medicine, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Jean-Paul Vallée
- Division of Radiology, Diagnostic Department Geneva University Hospitals, 1205 Geneva, Switzerland
- Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
- Pulmonary Hypertension Program, Geneva University Hospitals, 1205 Geneva, Switzerland
| |
Collapse
|
9
|
Knapp J, Tavares de Sousa M, Schönnagel BP. Fetal Cardiovascular MRI - A Systemic Review of the Literature: Challenges, New Technical Developments, and Perspectives. ROFO-FORTSCHR RONTG 2022; 194:841-851. [PMID: 35905903 DOI: 10.1055/a-1761-3500] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
BACKGROUND Fetal magnetic resonance imaging (MRI) has become a valuable adjunct to ultrasound in the prenatal diagnosis of congenital pathologies of the central nervous system, thorax, and abdomen. Fetal cardiovascular magnetic resonance (CMR) was limited, mainly by the lack of cardiac gating, and has only recently evolved due to technical developments. METHOD A literature search was performed on PubMed, focusing on technical advancements to perform fetal CMR. In total, 20 publications on cardiac gating techniques in the human fetus were analyzed. RESULTS Fetal MRI is a safe imaging method with no developmental impairments found to be associated with in utero exposure to MRI. Fetal CMR is challenging due to general drawbacks (e. g., fetal motion) and specific limitations such as the difficulty to generate a cardiac gating signal to achieve high spatiotemporal resolution. Promising technical advancements include new methods for fetal cardiac gating, based on novel post-processing approaches and an external hardware device, as well as motion compensation and acceleration techniques. CONCLUSION Newly developed direct and indirect gating approaches were successfully applied to achieve high-quality morphologic and functional imaging as well as quantitative assessment of fetal hemodynamics in research settings. In cases when prenatal echocardiography is limited, e. g., by an unfavorable fetal position in utero, or when its results are inconclusive, fetal CMR could potentially serve as a valuable adjunct in the prenatal assessment of congenital cardiovascular malformations. However, sufficient data on the diagnostic performance and clinical benefit of new fetal CMR techniques is still lacking. KEY POINTS · New fetal cardiac gating methods allow high-quality fetal CMR.. · Motion compensation and acceleration techniques allow for improvement of image quality.. · Fetal CMR could potentially serve as an adjunct to fetal echocardiography in the future.. CITATION FORMAT · Knapp J, Tavares de Sousa M, Schönnagel BP. Fetal Cardiovascular MRI - A Systemic Review of the Literature: Challenges, New Technical Developments, and Perspectives. Fortschr Röntgenstr 2022; 194: 841 - 851.
Collapse
Affiliation(s)
- Janine Knapp
- Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Björn P Schönnagel
- Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| |
Collapse
|
10
|
Isoda H, Fukuyama A. Quality Control for 4D Flow MR Imaging. Magn Reson Med Sci 2022; 21:278-292. [PMID: 35197395 PMCID: PMC9680545 DOI: 10.2463/mrms.rev.2021-0165] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 01/08/2022] [Indexed: 01/06/2023] Open
Abstract
In recent years, 4D flow MRI has become increasingly important in clinical applications for the blood vessels in the whole body, heart, and cerebrospinal fluid. 4D flow MRI has advantages over 2D cine phase-contrast (PC) MRI in that any targeted area of interest can be analyzed post-hoc, but there are some factors to be considered, such as ensuring measurement accuracy, a long imaging time and post-processing complexity, and interobserver variability.Due to the partial volume phenomenon caused by low spatial and temporal resolutions, the accuracy of flow measurement in 4D flow MRI is reduced. For spatial resolution, it is recommended to include at least four voxels in the vessel of interest, and if possible, six voxels. In large vessels such as the aorta, large voxels can be secured and SNR can be maintained, but in small cerebral vessels, SNR is reduced, resulting in reduced accuracy. A temporal resolution of less than 40 ms is recommended. The velocity-to-noise ratio (VNR) of low-velocity blood flow is low, resulting in poor measurement accuracy. The use of dual velocity encoding (VENC) or multi-VENC is recommended to avoid velocity wrap around and to increase VNR. In order to maintain sufficient spatio-temporal resolution, a longer imaging time is required, leading to potential patient movement during examination and a corresponding decrease in measurement accuracy.For the clinical application of new technologies, including various acceleration techniques, in vitro and in vivo accuracy verification based on existing accuracy-validated 2D cine PC MRI and 4D flow MRI, as well as accuracy verification on the conservation of mass' principle, should be performed, and intraobserver repeatability, interobserver reproducibility, and test-retest reproducibility should be checked.
Collapse
Affiliation(s)
- Haruo Isoda
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
- Biomedical Imaging Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Atsushi Fukuyama
- Faculty of Health Sciences, Department of Radiological Sciences, Japan Healthcare University, Sapporo, Hokkaido, Japan
| |
Collapse
|
11
|
Yao X, Hu L, Peng Y, Feng F, Ouyang R, Xie W, Wang Q, Sun A, Zhong Y. Right and left ventricular function and flow quantification in pediatric patients with repaired tetralogy of Fallot using four-dimensional flow magnetic resonance imaging. BMC Med Imaging 2021; 21:161. [PMID: 34719378 PMCID: PMC8559379 DOI: 10.1186/s12880-021-00693-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 10/26/2021] [Indexed: 11/10/2022] Open
Abstract
Background To assess the accuracy and reproducibility of right ventricular (RV) and left ventricular (LV) function and flow measurements in children with repaired tetralogy of Fallot (rTOF) using four-dimensional (4D) flow, compared with conventional two-dimensional (2D) magnetic resonance imaging (MRI) sequences. Methods Thirty pediatric patients with rTOF were retrospectively enrolled to undergo 2D balanced steady-state free precession cine (2D b-SSFP cine), 2D phase contrast (PC), and 4D flow cardiac MRI. LV and RV volumes and flow in the ascending aorta (AAO) and main pulmonary artery (MPA) were quantified. Pearson’s or Spearman’s correlation tests, paired t-tests, the Wilcoxon signed-rank test, Bland–Altman analysis, and intraclass correlation coefficients (ICC) were performed. Results The 4D flow scan time was shorter compared with 2D sequences (P < 0.001). The biventricular volumes between 4D flow and 2D b-SSFP cine had no significant differences (P > 0.05), and showed strong correlations (r > 0.90, P < 0.001) and good consistency. The flow measurements of the AAO and MPA between 4D flow and 2D PC showed moderate to good correlations (r > 0.60, P < 0.001). There was good internal consistency in cardiac output. There was good intraobserver and interobserver biventricular function agreement (ICC > 0.85). Conclusions RV and LV function and flow quantification in pediatric patients with rTOF using 4D flow MRI can be measured accurately and reproducibly compared to those with conventional 2D sequences.
Collapse
Affiliation(s)
- Xiaofen Yao
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Liwei Hu
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Yafeng Peng
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Fei Feng
- AI Imaging, GE Healthcare, No. 1 Huatuo Road, Shanghai, 201203, China
| | - Rongzhen Ouyang
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Weihui Xie
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Qian Wang
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Aimin Sun
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China
| | - Yumin Zhong
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, No. 1678 Dongfang Road, Shanghai, 200127, China.
| |
Collapse
|
12
|
Falcão MBL, Di Sopra L, Ma L, Bacher M, Yerly J, Speier P, Rutz T, Prša M, Markl M, Stuber M, Roy CW. Pilot tone navigation for respiratory and cardiac motion-resolved free-running 5D flow MRI. Magn Reson Med 2021; 87:718-732. [PMID: 34611923 PMCID: PMC8627452 DOI: 10.1002/mrm.29023] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 08/17/2021] [Accepted: 09/03/2021] [Indexed: 11/07/2022]
Abstract
Purpose In this work, we integrated the pilot tone (PT) navigation system into a reconstruction framework for respiratory and cardiac motion‐resolved 5D flow. We tested the hypotheses that PT would provide equivalent respiratory curves, cardiac triggers, and corresponding flow measurements to a previously established self‐gating (SG) technique while being independent from changes to the acquisition parameters. Methods Fifteen volunteers and 9 patients were scanned with a free‐running 5D flow sequence, with PT integrated. Respiratory curves and cardiac triggers from PT and SG were compared across all subjects. Flow measurements from 5D flow reconstructions using both PT and SG were compared to each other and to a reference electrocardiogram‐gated and respiratory triggered 4D flow acquisition. Radial trajectories with variable readouts per interleave were also tested in 1 subject to compare cardiac trigger quality between PT and SG. Results The correlation between PT and SG respiratory curves were 0.95 ± 0.06 for volunteers and 0.95 ± 0.04 for patients. Heartbeat duration measurements in volunteers and patients showed a bias to electrocardiogram measurements of, respectively, 0.16 ± 64.94 ms and 0.01 ± 39.29 ms for PT versus electrocardiogram and of 0.24 ± 63.68 ms and 0.09 ± 32.79 ms for SG versus electrocardiogram. No significant differences were reported for the flow measurements between 5D flow PT and from 5D flow SG. A decrease in the cardiac triggering quality of SG was observed for increasing readouts per interleave, whereas PT quality remained constant. Conclusion PT has been successfully integrated in 5D flow MRI and has shown equivalent results to the previously described 5D flow SG technique, while being completely acquisition‐independent.
Collapse
Affiliation(s)
- Mariana B L Falcão
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, USA
| | - Mario Bacher
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Siemens Healthcare GmbH, Erlangen, Germany.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | | | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prša
- Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| |
Collapse
|
13
|
von Kleist H, Buehrer M, Kozerke S, Saengsin K, Harrington JK, Powell AJ, Moghari MH. Cardiac self-gating using blind source separation for 2D cine cardiovascular magnetic resonance imaging. Magn Reson Imaging 2021; 81:42-52. [PMID: 33905835 DOI: 10.1016/j.mri.2021.04.008] [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: 01/10/2021] [Revised: 04/11/2021] [Accepted: 04/21/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To develop and validate a new cardiac self-gating algorithm using blind source separation for 2D cine steady-state free precession (SSFP) imaging. METHODS A standard cine SSFP sequence was modified so that the center point of k-space was sampled with each excitation. The center points of k-space were processed by 4 blind source separation methods, and used to detect heartbeats and assign k-space data to appropriate time points in the cardiac cycle. The proposed self-gating technique was prospectively validated in 8 patients against the standard electrocardiogram (ECG)-gating method by comparing the cardiac cycle lengths, image quality metrics, and ventricular volume measurements. RESULTS There was close agreement between the cardiac cycle length using the ECG- and self-gating methods (bias 0.0 bpm, 95% limits of agreement ±2.1 bpm). The image quality metrics were not significantly different between the ECG- and self-gated images. The ventricular volumes, stroke volumes, and mass measured from self-gated images were all comparable with those from ECG-gated images (all biases <5%). CONCLUSION The self-gating method yielded comparable cardiac cycle length, image quality, and ventricular measurements compared with standard ECG-gated cine imaging. It may simplify patient preparation, be more robust when there is arrhythmia, and allow cardiac gating at higher field strengths.
Collapse
Affiliation(s)
- Henrik von Kleist
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Department of Informatics, Technical University of Munich, Garching, Germany.
| | - Martin Buehrer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Kwannapas Saengsin
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Jamie K Harrington
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Andrew J Powell
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Mehdi H Moghari
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| |
Collapse
|