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Wang D, Smith DS, Yang X. Dynamic MR image reconstruction based on total generalized variation and low-rank decomposition. Magn Reson Med 2020; 83:2064-2076. [PMID: 31697864 PMCID: PMC7047634 DOI: 10.1002/mrm.28064] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 10/09/2019] [Accepted: 10/14/2019] [Indexed: 02/05/2023]
Abstract
PURPOSE Propose a novel decomposition-based model employing the total generalized variation (TGV) and the nuclear norm, which can be used in compressed sensing-based dynamic MR reconstructions. THEORY AND METHODS We employ the nuclear norm to represent the time-coherent background and the spatiotemporal TGV functional for the sparse dynamic component above. We first design an algorithm using the classical first-order primal-dual method for solving the proposed model and then give the norm estimation for the convergence condition. The proposed model is compared with the state-of-the-art methods on different data sets under different sampling schemes and acceleration factors. RESULTS The proposed model achieves higher SERs and SSIMs than kt-SLR, kt-RPCA, L+S, and ICTGV on cardiac perfusion and breast DCE-MRI data sets under both the pseudoradial and the Cartesian sampling schemes. In addition, the proposed model better suppresses the spatial artifacts and preserves the edges. CONCLUSIONS The proposed model outperforms the state-of-the-art methods and generates high-quality reconstructions under different sampling schemes and different acceleration factors.
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Affiliation(s)
- Dong Wang
- Department of Mathematics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China
| | - David S. Smith
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Xiaoping Yang
- Department of Mathematics, Nanjing University, Nanjing, Jiangsu 210093, China,Correspondence to: Xiaoping Yang, Department of Mathematics, Nanjing University, Nanjing, Jiangsu 210093, China.
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Lingala SG, Guo Y, Bliesener Y, Zhu Y, Lebel RM, Law M, Nayak KS. Tracer kinetic models as temporal constraints during brain tumor DCE-MRI reconstruction. Med Phys 2019; 47:37-51. [PMID: 31663134 PMCID: PMC6980286 DOI: 10.1002/mp.13885] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 10/17/2019] [Accepted: 10/17/2019] [Indexed: 12/11/2022] Open
Abstract
Purpose To apply tracer kinetic models as temporal constraints during reconstruction of under‐sampled brain tumor dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI). Methods A library of concentration vs time profiles is simulated for a range of physiological kinetic parameters. The library is reduced to a dictionary of temporal bases, where each profile is approximated by a sparse linear combination of the bases. Image reconstruction is formulated as estimation of concentration profiles and sparse model coefficients with a fixed sparsity level. Simulations are performed to evaluate modeling error, and error statistics in kinetic parameter estimation in presence of noise. Retrospective under‐sampling experiments are performed on a brain tumor DCE digital reference object (DRO), and 12 brain tumor in‐vivo 3T datasets. The performances of the proposed under‐sampled reconstruction scheme and an existing compressed sensing‐based temporal finite‐difference (tFD) under‐sampled reconstruction were compared against the fully sampled inverse Fourier Transform‐based reconstruction. Results Simulations demonstrate that sparsity levels of 2 and 3 model the library profiles from the Patlak and extended Tofts‐Kety (ETK) models, respectively. Noise sensitivity analysis showed equivalent kinetic parameter estimation error statistics from noisy concentration profiles, and model approximated profiles. DRO‐based experiments showed good fidelity in recovery of kinetic maps from 20‐fold under‐sampled data. In‐vivo experiments demonstrated reduced bias and uncertainty in kinetic mapping with the proposed approach compared to tFD at under‐sampled reduction factors >= 20. Conclusions Tracer kinetic models can be applied as temporal constraints during brain tumor DCE‐MRI reconstruction. The proposed under‐sampled scheme resulted in model parameter estimates less biased with respect to conventional fully sampled DCE MRI reconstructions and parameter estimation. The approach is flexible, can use nonlinear kinetic models, and does not require tuning of regularization parameters.
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Affiliation(s)
- Sajan Goud Lingala
- Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Yi Guo
- Snap Inc., San Francisco, CA, USA
| | - Yannick Bliesener
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | | | - R Marc Lebel
- GE Healthcare Applied Sciences Laboratory, Calgary, Canada
| | - Meng Law
- Department of Neuroscience, Monash University, Melbourne, Australia
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
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Abstract
Dynamic contrast-enhanced MRI in pre-clinical imaging allows the in-vivo monitoring of vascular, physiological properties in normal and diseased tissue. There is considerable variation in the methods employed owing to the different questions that can be asked and answered about the physiologic alterations as well as morphologic changes in tissue. Here we review the typical decisions in the design and execution of a dynamic contrast-enhanced MRI study in mice although the findings can easily be transferred to other species. Emphasis is placed on highlighting the many pitfalls that wait for the unaware pre-clinical MRI practitioner and that go often unmentioned in the abundant literature dealing with dynamic contrast-enhanced MRI in animal models.
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Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast. Int J Biomed Imaging 2017; 2017:7835749. [PMID: 28932236 PMCID: PMC5592397 DOI: 10.1155/2017/7835749] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Accepted: 07/20/2017] [Indexed: 11/17/2022] Open
Abstract
PURPOSE Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. METHODS We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGV α2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes. RESULTS NN produced the lowest image error (SER: 29.1), while TV/TGV α2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799). CONCLUSION TV/TGV α2 should be used as temporal constraints for CS DCE-MRI of the breast.
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Liu RW, Shi L, Yu SCH, Xiong N, Wang D. Reconstruction of Undersampled Big Dynamic MRI Data Using Non-Convex Low-Rank and Sparsity Constraints. SENSORS (BASEL, SWITZERLAND) 2017; 17:E509. [PMID: 28273827 PMCID: PMC5375795 DOI: 10.3390/s17030509] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 02/16/2017] [Accepted: 02/20/2017] [Indexed: 11/17/2022]
Abstract
Dynamic magnetic resonance imaging (MRI) has been extensively utilized for enhancing medical living environment visualization, however, in clinical practice it often suffers from long data acquisition times. Dynamic imaging essentially reconstructs the visual image from raw (k,t)-space measurements, commonly referred to as big data. The purpose of this work is to accelerate big medical data acquisition in dynamic MRI by developing a non-convex minimization framework. In particular, to overcome the inherent speed limitation, both non-convex low-rank and sparsity constraints were combined to accelerate the dynamic imaging. However, the non-convex constraints make the dynamic reconstruction problem difficult to directly solve through the commonly-used numerical methods. To guarantee solution efficiency and stability, a numerical algorithm based on Alternating Direction Method of Multipliers (ADMM) is proposed to solve the resulting non-convex optimization problem. ADMM decomposes the original complex optimization problem into several simple sub-problems. Each sub-problem has a closed-form solution or could be efficiently solved using existing numerical methods. It has been proven that the quality of images reconstructed from fewer measurements can be significantly improved using non-convex minimization. Numerous experiments have been conducted on two in vivo cardiac datasets to compare the proposed method with several state-of-the-art imaging methods. Experimental results illustrated that the proposed method could guarantee the superior imaging performance in terms of quantitative and visual image quality assessments.
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Affiliation(s)
- Ryan Wen Liu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
| | - Lin Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
- Chow Yuk Ho Technology Center for Innovative Medicine, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
| | - Simon Chun Ho Yu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
| | - Naixue Xiong
- Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK 74464, USA.
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
- Research Center for Medical Image Computing, The Chinese University of Hong Kong, Shatin 999077, N.T., Hong Kong, China.
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China.
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Lee D, Han S, Cho H. Optimization of sparse phase encodings for variable repetition-delay turbo-spin echo (TSE) T 1 measurements for preclinical applications. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2017; 274:57-64. [PMID: 27886558 DOI: 10.1016/j.jmr.2016.11.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 11/07/2016] [Accepted: 11/09/2016] [Indexed: 06/06/2023]
Abstract
A variable repetition-delay (TR) spin echo sequence with repeated refocusing pulses, i.e., a variable TR turbo-spin echo (TSE), provides an attractive means of acquiring an accurate T1 map information that is free from gradient echo based artifacts such as magnetic field inhomogeneities particularly for ultra-high field (at 7T and above) preclinical applications. However, the applicability of multi-slice TSE sequences is often limited by signal distortion from T2 relaxation due to echo-train acquisitions for short T2 tissues, inter-slice cross talks and magnetization transfer (MT) from repetitive slice-selective 180° pulse, and extended scan times with multiple TR excitations. These TSE shortcomings are difficult to remedy for preclinical applications, where small sizes of target organs usually limit the slice-gap control with restricted parallel imaging capabilities. In this study, compressed-sensing-assisted turbo-spin echo (CS-TSE) acquisitions for variable TR T1 measurements at 7T preclinical scanner were implemented to reduce the echo-trains by sparse phase encodings. Following the sparse signal simulation and sampling scheme optimization, the measured T1 values from CS-TSE and TSE were compared for phantoms, ex vivo, and in vivo subjects. The phantom T1 values from CS-TSE and TSE were identical to those from the inversion recovery spin echo. For both ex vivo and in vivo multi-slice T1 mapping, the shortened echo-trains of CS-TSE relieved the T2 relaxation, reduced the inter-slice interferences of multi-slice acquisition, and made room for additional slice encodings while maintaining a shorter scan time than the conventional TSE at the expense of local image smoothness from CS regularizations.
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Affiliation(s)
- DongKyu Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Sohyun Han
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - HyungJoon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
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Pineda FD, Medved M, Wang S, Fan X, Schacht DV, Sennett C, Oto A, Newstead GM, Abe H, Karczmar GS. Ultrafast Bilateral DCE-MRI of the Breast with Conventional Fourier Sampling: Preliminary Evaluation of Semi-quantitative Analysis. Acad Radiol 2016; 23:1137-44. [PMID: 27283068 PMCID: PMC4987200 DOI: 10.1016/j.acra.2016.04.008] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 01/27/2016] [Accepted: 04/12/2016] [Indexed: 12/25/2022]
Abstract
RATIONALE AND OBJECTIVES The study aimed to evaluate the feasibility and advantages of a combined high temporal and high spatial resolution protocol for dynamic contrast-enhanced magnetic resonance imaging of the breast. MATERIALS AND METHODS Twenty-three patients with enhancing lesions were imaged at 3T. The acquisition protocol consisted of a series of bilateral, fat-suppressed "ultrafast" acquisitions, with 6.9- to 9.9-second temporal resolution for the first minute following contrast injection, followed by four high spatial resolution acquisitions with 60- to 79.5-second temporal resolution. All images were acquired with standard uniform Fourier sampling. A filtering method was developed to reduce noise and detect significant enhancement in the high temporal resolution images. Time of arrival (TOA) was defined as the time at which each voxel first satisfied all the filter conditions, relative to the time of initial arterial enhancement. RESULTS Ultrafast images improved visualization of the vasculature feeding and draining lesions. A small percentage of the entire field of view (<6%) enhanced significantly in the 30 seconds following contrast injection. Lesion conspicuity was highest in early ultrafast images, especially in cases with marked parenchymal enhancement. Although the sample size was relatively small, the average TOA for malignant lesions was significantly shorter than the TOA for benign lesions. Significant differences were also measured in other parameters descriptive of early contrast media uptake kinetics (P < 0.05). CONCLUSIONS Ultrafast imaging in the first minute of dynamic contrast-enhanced magnetic resonance imaging of the breast has the potential to add valuable information on early contrast dynamics. Ultrafast imaging could allow radiologists to confidently identify lesions in the presence of marked background parenchymal enhancement.
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Affiliation(s)
- Federico D Pineda
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Milica Medved
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Shiyang Wang
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Xiaobing Fan
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - David V Schacht
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Charlene Sennett
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Aytekin Oto
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Gillian M Newstead
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Hiroyuki Abe
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637
| | - Gregory S Karczmar
- Department of Radiology, University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637.
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Yang ACY, Kretzler M, Sudarski S, Gulani V, Seiberlich N. Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption. Invest Radiol 2016; 51:349-64. [PMID: 27003227 PMCID: PMC4948115 DOI: 10.1097/rli.0000000000000274] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
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Affiliation(s)
- Alice Chieh-Yu Yang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
| | - Madison Kretzler
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, USA
| | - Sonja Sudarski
- Institute for Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim - Heidelberg University, Heidelberg, Germany
| | - Vikas Gulani
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, USA
- Department of Radiology, University Hospitals of Cleveland, Cleveland, USA
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Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study. Technol Cancer Res Treat 2016; 16:446-460. [PMID: 27215931 DOI: 10.1177/1533034616649294] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. METHODS Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant Ktrans in the extended Tofts model and blood flow FB and blood volume VB from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. RESULTS The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. CONCLUSION With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.
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Lebel RM, Jones J, Ferre JC, Law M, Nayak KS. Highly accelerated dynamic contrast enhanced imaging. Magn Reson Med 2016; 71:635-44. [PMID: 23504992 DOI: 10.1002/mrm.24710] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
PURPOSE Dynamic contrast-enhanced imaging provides unique physiological information, notably the endothelial permeability (K(trans)), and may improve the diagnosis and management of multiple pathologies. Current acquisition methods provide limited spatial-temporal resolution and field-of-view, often preventing characterization of the entire pathology and precluding measurement of the arterial input function. We present a method for highly accelerated dynamic imaging and demonstrate its utility for dynamic contrast-enhanced modeling. METHODS We propose a novel Poisson ellipsoid sampling scheme and enforce multiple spatial and temporal l1-norm constraints during image reconstruction. Retrospective and prospective analyses were performed to validate the approach. RESULTS Retrospectively, no mean bias or diverging trend was observed as the acceleration rate was increased from 3× to 18×; less than 10% error was measured in K(trans) at any individual rates in this range. Prospectively accelerated images at a rate of 36× enabled full brain coverage with 0.94 × 0.94 × 1.9 mm(3) spatial and 4.1 s temporal resolutions. Images showed no visible degradation and provided accurate K(trans) values when compared to a clinical population. CONCLUSION Highly accelerated dynamic MRI using compressed sensing and parallel imaging provides accurate permeability modeling and enables full brain, high resolution acquisitions.
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Affiliation(s)
- Robert Marc Lebel
- Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
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11
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Han S, Cho H. Temporal resolution improvement of calibration-free dynamic contrast-enhanced MRI with compressed sensing optimized turbo spin echo: The effects of replacing turbo factor with compressed sensing accelerations. J Magn Reson Imaging 2015; 44:138-47. [DOI: 10.1002/jmri.25136] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Accepted: 12/03/2015] [Indexed: 11/09/2022] Open
Affiliation(s)
- SoHyun Han
- Department of Biomedical Engineering; Ulsan National Institute of Science and Technology; Ulsan South Korea
| | - HyungJoon Cho
- Department of Biomedical Engineering; Ulsan National Institute of Science and Technology; Ulsan South Korea
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Haeck J, Bol K, Bison S, van Tiel S, Koelewijn S, de Jong M, Veenland J, Bernsen M. Optimized time-resolved imaging of contrast kinetics (TRICKS) in dynamic contrast-enhanced MRI after peptide receptor radionuclide therapy in small animal tumor models. CONTRAST MEDIA & MOLECULAR IMAGING 2015; 10:413-20. [PMID: 25995102 DOI: 10.1002/cmmi.1643] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2014] [Revised: 03/03/2015] [Accepted: 03/25/2015] [Indexed: 01/15/2023]
Abstract
Anti-tumor efficacy of targeted peptide-receptor radionuclide therapy (PRRT) relies on several factors, including functional tumor vasculature. Little is known about the effect of PRRT on tumor vasculature. With dynamic contrast-enhanced (DCE-) MRI, functional vasculature is imaged and quantified using contrast agents. In small animals DCE-MRI is a challenging application. We optimized a clinical sequence for fast hemodynamic acquisitions, time-resolved imaging of contrast kinetics (TRICKS), to obtain DCE-MRI images at both high spatial and high temporal resolution in mice and rats. Using TRICKS, functional vasculature was measured prior to PRRT and longitudinally to investigate the effect of treatment on tumor vascular characteristics. Nude mice bearing H69 tumor xenografts and rats bearing syngeneic CA20948 tumors were used to study perfusion following PRRT administration with (177) lutetium octreotate. Both semi-quantitative and quantitative parameters were calculated. Treatment efficacy was measured by tumor-size reduction. Optimized TRICKS enabled MRI at 0.032 mm(3) voxel size with a temporal resolution of less than 5 s and large volume coverage, a substantial improvement over routine pre-clinical DCE-MRI studies. Tumor response to therapy was reflected in changes in tumor perfusion/permeability parameters. The H69 tumor model showed pronounced changes in DCE-derived parameters following PRRT. The rat CA20948 tumor model showed more heterogeneity in both treatment outcome and perfusion parameters. TRICKS enabled the acquisition of DCE-MRI at both high temporal resolution (Tres ) and spatial resolutions relevant for small animal tumor models. With the high Tres enabled by TRICKS, accurate pharmacokinetic data modeling was feasible. DCE-MRI parameters revealed changes over time and showed a clear relationship between tumor size and Ktrans .
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Affiliation(s)
- Joost Haeck
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Karin Bol
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Sander Bison
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Sandra van Tiel
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Stuart Koelewijn
- Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Marion de Jong
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Jifke Veenland
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Monique Bernsen
- Department of Radiology, Erasmus Medical Centre, Rotterdam, The Netherlands.,Department of Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
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Chen B, Zhao K, Li B, Cai W, Wang X, Zhang J, Fang J. High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement. Magn Reson Imaging 2015; 33:962-9. [PMID: 25967586 DOI: 10.1016/j.mri.2015.05.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Accepted: 05/06/2015] [Indexed: 10/23/2022]
Abstract
PURPOSE To demonstrate the feasibility of the improved temporal resolution by using compressed sensing (CS) combined imaging sequence in dynamic contrast-enhanced MRI (DCE-MRI) of kidney, and investigate its quantitative effects on renal perfusion measurements. MATERIALS AND METHODS Ten rabbits were included in the accelerated scans with a CS-combined 3D pulse sequence. To evaluate the image quality, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the proposed CS strategy and the conventional full sampling method. Moreover, renal perfusion was estimated by using the separable compartmental model in both CS simulation and realistic CS acquisitions. RESULTS The CS method showed DCE-MRI images with improved temporal resolution and acceptable image contrast, while presenting significantly higher SNR than the fully sampled images (p<.01) at 2-, 3- and 4-X acceleration. In quantitative measurements, renal perfusion results were in good agreement with the fully sampled one (concordance correlation coefficient=0.95, 0.91, 0.88) at 2-, 3- and 4-X acceleration in CS simulation. Moreover, in realistic acquisitions, the estimated perfusion by the separable compartmental model exhibited no significant differences (p>.05) between each CS-accelerated acquisition and the full sampling method. CONCLUSION The CS-combined 3D sequence could improve the temporal resolution for DCE-MRI in kidney while yielding diagnostically acceptable image quality, and it could provide effective measurements of renal perfusion.
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Affiliation(s)
- Bin Chen
- Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China
| | - Kai Zhao
- Dept. of Radiology, Peking University First Hospital, 100034, Beijing, China
| | - Bo Li
- College of Engineering, Peking University, 100871, Beijing, China
| | - Wenchao Cai
- Dept. of Radiology, Peking University First Hospital, 100034, Beijing, China
| | - Xiaoying Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China; Dept. of Radiology, Peking University First Hospital, 100034, Beijing, China
| | - Jue Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China; College of Engineering, Peking University, 100871, Beijing, China.
| | - Jing Fang
- Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China; College of Engineering, Peking University, 100871, Beijing, China
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Han SH, Cho FH, Song YK, Paulsen J, Song YQ, Kim YR, Kim JK, Cho G, Cho H. Ultrafast 3D spin-echo acquisition improves Gadolinium-enhanced MRI signal contrast enhancement. Sci Rep 2014; 4:5061. [PMID: 24863102 PMCID: PMC4034007 DOI: 10.1038/srep05061] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 05/07/2014] [Indexed: 11/27/2022] Open
Abstract
Long scan times of 3D volumetric MR acquisitions usually necessitate ultrafast in vivo gradient-echo acquisitions, which are intrinsically susceptible to magnetic field inhomogeneities. This is especially problematic for contrast-enhanced (CE)-MRI applications, where non-negligible T2* effect of contrast agent deteriorates the positive signal contrast and limits the available range of MR acquisition parameters and injection doses. To overcome these shortcomings without degrading temporal resolution, ultrafast spin-echo acquisitions were implemented. Specifically, a multiplicative acceleration factor from multiple spin echoes (×32) and compressed sensing (CS) sampling (×8) allowed highly-accelerated 3D Multiple-Modulation-Multiple-Echo (MMME) acquisition. At the same time, the CE-MRI of kidney with Gd-DOTA showed significantly improved signal enhancement for CS-MMME acquisitions (×7) over that of corresponding FLASH acquisitions (×2). Increased positive contrast enhancement and highly accelerated acquisition of extended volume with reduced RF irradiations will be beneficial for oncological and nephrological applications, in which the accurate in vivo 3D quantification of contrast agent concentration is necessary with high temporal resolution.
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Affiliation(s)
- S H Han
- Department of Biomedical Engineering, UNIST, Ulsan, South Korea
| | - F H Cho
- Department of Biomedical Engineering, UNIST, Ulsan, South Korea
| | - Y K Song
- Department of Biomedical Engineering, UNIST, Ulsan, South Korea
| | - J Paulsen
- Schlumberger Doll Research Center, Cambridge, MA, USA
| | - Y Q Song
- Schlumberger Doll Research Center, Cambridge, MA, USA
| | - Y R Kim
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - J K Kim
- Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - G Cho
- Korea Basic Science Institute, Ochang, South Korea
| | - H Cho
- Department of Biomedical Engineering, UNIST, Ulsan, South Korea
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Chen H, Wu T, Kerwin WS, Yuan C. Atherosclerotic plaque inflammation quantification using dynamic contrast-enhanced (DCE) MRI. Quant Imaging Med Surg 2014; 3:298-301. [PMID: 24404443 DOI: 10.3978/j.issn.2223-4292.2013.12.01] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2013] [Accepted: 12/05/2013] [Indexed: 01/12/2023]
Abstract
Inflammation plays an important role in atherosclerosis. Given the increasing interest in using in-vivo imaging methods to study the physiology and treatment effects in atherosclerosis, noninvasive intraplaque inflammation quantitative method is needed. Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) has been proposed and validated to quantitatively characterize atherosclerotic plaque inflammation. Recent studies have optimized the imaging protocol, pharmacokinetic modeling techniques. All of these technical advances further promoted DCE-MRI to clinical investigations in plaque risk assessment and therapeutic response monitor. Although larger clinical studies are still needed, DCE-MRI has been proven to be a promising tool to reveal more about intraplaque inflammation by in vivo quantitative inflammation imaging.
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Affiliation(s)
- Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Tingting Wu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - William S Kerwin
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Chun Yuan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China; ; Department of Radiology, University of Washington, Seattle, Washington, USA
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Rapacchi S, Han F, Natsuaki Y, Kroeker R, Plotnik A, Lehrman E, Sayre J, Laub G, Finn JP, Hu P. High spatial and temporal resolution dynamic contrast-enhanced magnetic resonance angiography using compressed sensing with magnitude image subtraction. Magn Reson Med 2013; 71:1771-83. [PMID: 23801456 DOI: 10.1002/mrm.24842] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2012] [Revised: 04/29/2013] [Accepted: 05/21/2013] [Indexed: 11/06/2022]
Abstract
PURPOSE We propose a compressed-sensing (CS) technique based on magnitude image subtraction for high spatial and temporal resolution dynamic contrast-enhanced MR angiography (CE-MRA). METHODS Our technique integrates the magnitude difference image into the CS reconstruction to promote subtraction sparsity. Fully sampled Cartesian 3D CE-MRA datasets from 6 volunteers were retrospectively under-sampled and three reconstruction strategies were evaluated: k-space subtraction CS, independent CS, and magnitude subtraction CS. The techniques were compared in image quality (vessel delineation, image artifacts, and noise) and image reconstruction error. Our CS technique was further tested on seven volunteers using a prospectively under-sampled CE-MRA sequence. RESULTS Compared with k-space subtraction and independent CS, our magnitude subtraction CS provides significantly better vessel delineation and less noise at 4× acceleration, and significantly less reconstruction error at 4× and 8× (P < 0.05 for all). On a 1-4 point image quality scale in vessel delineation, our technique scored 3.8 ± 0.4 at 4×, 2.8 ± 0.4 at 8×, and 2.3 ± 0.6 at 12× acceleration. Using our CS sequence at 12× acceleration, we were able to acquire dynamic CE-MRA with higher spatial and temporal resolution than current clinical TWIST protocol while maintaining comparable image quality (2.8 ± 0.5 vs. 3.0 ± 0.4, P = NS). CONCLUSION Our technique is promising for dynamic CE-MRA.
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Affiliation(s)
- Stanislas Rapacchi
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA
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Abstract
OBJECTIVE This and its companion article address the 10 most frequently asked questions that radiologists face when planning, performing, processing, and interpreting different MR perfusion studies in CNS imaging. CONCLUSION Perfusion MRI is a promising tool in assessing stroke, brain tumors, and patients with neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.
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