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Bae J, Li C, Masurkar A, Ge Y, Kim SG. Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function. Neuroimage 2023; 278:120284. [PMID: 37507078 PMCID: PMC10475161 DOI: 10.1016/j.neuroimage.2023.120284] [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: 05/02/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
PURPOSE In Dynamic contrast-enhanced MRI (DCE-MRI), Arterial Input Function (AIF) has been shown to be a significant contributor to uncertainty in the estimation of kinetic parameters. This study is to assess the feasibility of using a deep learning network to estimate local Capillary Input Function (CIF) to estimate blood-brain barrier (BBB) permeability, while reducing the required scan time. MATERIALS AND METHOD A total of 13 healthy subjects (younger (<40 y/o): 8, older (> 67 y/o): 5) were recruited and underwent 25-min DCE-MRI scans. The 25 min data were retrospectively truncated to 10 min to simulate a reduced scan time of 10 min. A deep learning network was trained to predict the CIF using simulated tissue contrast dynamics with two vascular transport models. The BBB permeability (PS) was measured using 3 methods: (i) Ca-25min, using DCE-MRI data of 25 min with individually sampled AIF (Ca); (ii) Ca-10min, using truncated 10min data with AIF (Ca); and (iii) Cp-10min, using truncated 10 min data with CIF (Cp). The PS estimates from the Ca-25min method were used as reference standard values to assess the accuracy of the Ca-10min and Cp-10min methods in estimating the PS values. RESULTS When compared to the reference method(Ca-25min), the Ca-10min and Cp-10min methods resulted in an overestimation of PS by 217 ± 241 % and 48.0 ± 30.2 %, respectively. The Bland Altman analysis showed that the mean difference from the reference was 8.85 ± 1.78 (x10-4 min-1) with the Ca-10min, while it was reduced to 1.63 ± 2.25 (x10-4 min-1) with the Cp-10min, resulting in an average reduction of 81%. The limits of agreement also reduced by up to 39.2% with the Cp-10min. We found a 75% increase of BBB permeability in the gray matter and a 35% increase in the white matter, when comparing the older group to the younger group. CONCLUSIONS We demonstrated the feasibility of estimating the capillary-level input functions using a deep learning network. We also showed that this method can be used to estimate subtle age-related changes in BBB permeability with reduced scan time, without compromising accuracy. Moreover, the trained deep learning network can automatically select CIF, reducing the potential uncertainty resulting from manual user-intervention.
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Affiliation(s)
- Jonghyun Bae
- Vilcek Institute of Graduate Biomedical Science, New York University School of Medicine; Center for Biomedical Imaging, Radiology, New York University School of Medicine; Center for Advanced Imaging Innovation and Research, Radiology, New York University School of Medicine; Department of Radiology, Weill Cornell Medical College.
| | - Chenyang Li
- Vilcek Institute of Graduate Biomedical Science, New York University School of Medicine; Center for Biomedical Imaging, Radiology, New York University School of Medicine; Center for Advanced Imaging Innovation and Research, Radiology, New York University School of Medicine.
| | - Arjun Masurkar
- Center for Cognitive Neurology, Department of Neurology, New York University School of Medicine; Department of Neuroscience & Physiology, New York University School of Medicine; Neuroscience Institute, New York University School of Medicine.
| | - Yulin Ge
- Center for Biomedical Imaging, Radiology, New York University School of Medicine; Center for Advanced Imaging Innovation and Research, Radiology, New York University School of Medicine.
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Cao J, Pickup S, Rosen M, Zhou R. Impact of Arterial Input Function and Pharmacokinetic Models on DCE-MRI Biomarkers for Detection of Vascular Effect Induced by Stroma-Directed Drug in an Orthotopic Mouse Model of Pancreatic Cancer. Mol Imaging Biol 2023:10.1007/s11307-023-01824-7. [PMID: 37166575 DOI: 10.1007/s11307-023-01824-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 04/28/2023] [Accepted: 05/01/2023] [Indexed: 05/12/2023]
Abstract
PURPOSE We demonstrated earlier in mouse models of pancreatic ductal adenocarcinoma (PDA) that Ktrans derived from dynamic contrast-enhanced (DCE) MRI detected microvascular effect induced by PEGPH20, a hyaluronidase which removes stromal hyaluronan, leading to reduced interstitial fluid pressure in the tumor (Clinical Cancer Res (2019) 25: 2314-2322). How the choice of pharmacokinetic (PK) model and arterial input function (AIF) may impact DCE-derived markers for detecting such an effect is not known. PROCEDURES Retrospective analyses of the DCE-MRI of the orthotopic PDA model are performed to examine the impact of individual versus group AIF combined with Tofts model (TM), extended-Tofts model (ETM), or shutter-speed model (SSM) on the ability to detect the microvascular changes induced by PEGPH20 treatment. RESULTS Individual AIF exhibit a marked difference in peak gadolinium concentration. However, across all three PK models, kep values show a significant correlation between individual versus group-AIF (p < 0.01). Regardless individual or group AIF, when kep is obtained from fitting the DCE-MRI data using the SSM, kep shows a significant increase after PEGPH20 treatment (p < 0.05 compared to the baseline); %change of kep from baseline to post-treatment is also significantly different between PEGPH20 versus vehicle group (p < 0.05). In comparison, when kep is derived from the TM, only the use of individual AIF leads to a significant increase of kep after PEGPH20 treatment, whereas the %change of kep is not different between PEGPH20 versus vehicle group. Group AIF but not individual AIF allows detection of a significant increase of Vp (derived from the ETM) in PEGPH20 versus vehicle group (p < 0.05). Increase of Vp is consistent with a large increase of mean capillary lumen area estimated from immunostaining. CONCLUSION Our results suggest that kep derived from SSM and Vp from ETM, both using group AIF, are optimal for the detection of microvascular changes induced by stroma-directed drug PEGPH20. These analyses provide insights in the choice of PK model and AIF for optimal DCE protocol design in mouse pancreatic cancer models.
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Affiliation(s)
- Jianbo Cao
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Current address: Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
| | - Stephen Pickup
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Pancreatic Cancer Research Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rong Zhou
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Pancreatic Cancer Research Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Abstract
Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.
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Martens J, Panzer S, den Wijngaard J, Siebes M, Schreiber LM. Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study. Magn Reson Med 2019; 84:467-483. [DOI: 10.1002/mrm.28125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 11/19/2019] [Accepted: 11/20/2019] [Indexed: 12/22/2022]
Affiliation(s)
- Johannes Martens
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
| | - Sabine Panzer
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
| | - Jeroen den Wijngaard
- Department of Biomedical Engineering & Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Cardiovascular Sciences Amsterdam Netherlands
- Department of Clinical Chemistry and Hematology Diakonessenhuis Utrecht Netherlands
| | - Maria Siebes
- Department of Biomedical Engineering & Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Cardiovascular Sciences Amsterdam Netherlands
| | - Laura M. Schreiber
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
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Quarles CC, Bell LC, Stokes AM. Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI. Neuroimage 2018; 187:32-55. [PMID: 29729392 DOI: 10.1016/j.neuroimage.2018.04.069] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Revised: 04/27/2018] [Accepted: 04/29/2018] [Indexed: 12/22/2022] Open
Abstract
In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T1, T2 and T2∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T1, T2 and T2∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.
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Affiliation(s)
- C Chad Quarles
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA.
| | - Laura C Bell
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA
| | - Ashley M Stokes
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA
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Taxt T, Reed RK, Pavlin T, Rygh CB, Andersen E, Jiřík R. Semi-parametric arterial input functions for quantitative dynamic contrast enhanced magnetic resonance imaging in mice. Magn Reson Imaging 2017; 46:10-20. [PMID: 29066294 DOI: 10.1016/j.mri.2017.10.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 09/15/2017] [Accepted: 10/17/2017] [Indexed: 01/23/2023]
Abstract
OBJECTIVE An extension of single- and multi-channel blind deconvolution is presented to improve the estimation of the arterial input function (AIF) in quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). METHODS The Lucy-Richardson expectation-maximization algorithm is used to obtain estimates of the AIF and the tissue residue function (TRF). In the first part of the algorithm, nonparametric estimates of the AIF and TRF are obtained. In the second part, the decaying part of the AIF is approximated by three decaying exponential functions with the same delay, giving an almost noise free semi-parametric AIF. Simultaneously, the TRF is approximated using the adiabatic approximation of the Johnson-Wilson (aaJW) pharmacokinetic model. RESULTS In simulations and tests on real data, use of this AIF gave perfusion values close to those obtained with the corresponding previously published nonparametric AIF, and are more noise robust. CONCLUSION When used subsequently in voxelwise perfusion analysis, these semi-parametric AIFs should give more correct perfusion analysis maps less affected by recording noise than the corresponding nonparametric AIFs, and AIFs obtained from arteries. SIGNIFICANCE This paper presents a method to increase the noise robustness in the estimation of the perfusion parameter values in DCE-MRI.
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Affiliation(s)
- Torfinn Taxt
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Dept. of Radiology, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Rolf K Reed
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Centre for Cancer Biomarkers (CCBIO), University of Bergen, Jonas Lies vei 87, Bergen N-5021, Norway
| | - Tina Pavlin
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Dept. of Radiology, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Cecilie Brekke Rygh
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway
| | - Erling Andersen
- Dept. of Clinical Engineering, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Radovan Jiřík
- Czech Academy of Sciences, Inst. of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic.
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Nejad-Davarani SP, Bagher-Ebadian H, Ewing JR, Noll DC, Mikkelsen T, Chopp M, Jiang Q. An extended vascular model for less biased estimation of permeability parameters in DCE-T1 images. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3698. [PMID: 28211961 PMCID: PMC5489235 DOI: 10.1002/nbm.3698] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2014] [Revised: 12/20/2016] [Accepted: 12/29/2016] [Indexed: 06/06/2023]
Abstract
One of the key elements in dynamic contrast enhanced (DCE) image analysis is the arterial input function (AIF). Traditionally, in DCE studies a global AIF sampled from a major artery or vein is used to estimate the vascular permeability parameters; however, not addressing dispersion and delay of the AIF at the tissue level can lead to biased estimates of these parameters. To find less biased estimates of vascular permeability parameters, a vascular model of the cerebral vascular system is proposed that considers effects of dispersion of the AIF in the vessel branches, as well as extravasation of the contrast agent (CA) to the extravascular-extracellular space. Profiles of the CA concentration were simulated for different branching levels of the vascular structure, combined with the effects of vascular leakage. To estimate the permeability parameters, the extended model was applied to these simulated signals and also to DCE-T1 (dynamic contrast enhanced T1 ) images of patients with glioblastoma multiforme tumors. The simulation study showed that, compared with the case of solving the pharmacokinetic equation with a global AIF, using the local AIF that is corrected by the vascular model can give less biased estimates of the permeability parameters (Ktrans , vp and Kb ). Applying the extended model to signals sampled from different areas of the DCE-T1 image showed that it is able to explain the CA concentration profile in both the normal areas and the tumor area, where effects of vascular leakage exist. Differences in the values of the permeability parameters estimated in these images using the local and global AIFs followed the same trend as the simulation study. These results demonstrate that the vascular model can be a useful tool for obtaining more accurate estimation of parameters in DCE studies.
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Affiliation(s)
- Siamak P. Nejad-Davarani
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Department of Neurology, Henry Ford Health System, Detroit, MI, USA
| | - Hassan Bagher-Ebadian
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
| | - James R. Ewing
- Department of Neurology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
| | - Douglas C. Noll
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Tom Mikkelsen
- Department of Neurosurgery, Henry Ford Health System, Detroit, MI, USA
| | - Michael Chopp
- Department of Neurology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
| | - Quan Jiang
- Department of Neurology, Henry Ford Health System, Detroit, MI, USA
- Department of Physics, Oakland University, Rochester, MI, USA
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8
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Duan C, Kallehauge JF, Pérez-Torres CJ, Bretthorst GL, Beeman SC, Tanderup K, Ackerman JJH, Garbow JR. Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF. Mol Imaging Biol 2017; 20:150-159. [PMID: 28536804 DOI: 10.1007/s11307-017-1090-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
PURPOSE This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. PROCEDURES Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. RESULTS When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. CONCLUSIONS The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.
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Affiliation(s)
- Chong Duan
- Department of Chemistry, Washington University, Saint Louis, MO, USA
| | - Jesper F Kallehauge
- Department of Medical Physics, Aarhus University, Aarhus, Denmark.,Department of Oncology, Aarhus University, Aarhus, Denmark
| | - Carlos J Pérez-Torres
- Department of Radiology, Washington University, Saint Louis, MO, USA.,School of Health Sciences, Purdue University, West Lafayette, IN, 47907, USA
| | - G Larry Bretthorst
- Department of Radiation Oncology, Washington University, Saint Louis, MO, USA
| | - Scott C Beeman
- Department of Radiology, Washington University, Saint Louis, MO, USA
| | - Kari Tanderup
- Department of Oncology, Aarhus University, Aarhus, Denmark.,Department of Radiation Oncology, Washington University, Saint Louis, MO, USA.,Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joseph J H Ackerman
- Department of Chemistry, Washington University, Saint Louis, MO, USA.,Department of Radiology, Washington University, Saint Louis, MO, USA.,Department of Medicine, Washington University, Saint Louis, MO, USA.,Alvin J Siteman Cancer Center, Washington University, Saint Louis, MO, USA
| | - Joel R Garbow
- Department of Radiology, Washington University, Saint Louis, MO, USA. .,Alvin J Siteman Cancer Center, Washington University, Saint Louis, MO, USA.
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9
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Farsani ZA, Schmid VJ. Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Methods Inf Med 2017; 56:461-468. [PMID: 29582918 DOI: 10.3414/me17-01-0027] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. OBJECTIVES This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. METHODS In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. RESULTS The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. CONCLUSIONS The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI.
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Li X, Cai Y, Moloney B, Chen Y, Huang W, Woods M, Coakley FV, Rooney WD, Garzotto MG, Springer CS. Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 269:104-112. [PMID: 27288764 PMCID: PMC4958517 DOI: 10.1016/j.jmr.2016.05.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 05/26/2016] [Accepted: 05/27/2016] [Indexed: 05/25/2023]
Abstract
Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (K(trans)) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging biomarkers for cross-platform, multicenter applications. Data from our limited study cohort show that kio correlates with Gleason scores, suggesting that it may be a useful biomarker for prostate cancer disease progression monitoring.
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Affiliation(s)
- Xin Li
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States.
| | - Yu Cai
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States
| | - Brendan Moloney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States
| | - Yiyi Chen
- Division of Biostatistics, Dept. of Public Health and Preventive Medicine, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, United States
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States
| | - Mark Woods
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States; Department of Chemistry, Portland State University, Portland, OR 97207, United States
| | - Fergus V Coakley
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR 97239, United States
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States
| | - Mark G Garzotto
- Department of Urology, Oregon Health & Science University, Portland, OR 97239, United States; Portland VA Medical Center, Portland, OR 97239, United States
| | - Charles S Springer
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States
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Nadav G, Liberman G, Artzi M, Kiryati N, Bashat DB. Optimization of two-compartment-exchange-model analysis for dynamic contrast-enhanced mri incorporating bolus arrival time. J Magn Reson Imaging 2016; 45:237-249. [PMID: 27383624 DOI: 10.1002/jmri.25362] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2015] [Accepted: 06/10/2016] [Indexed: 01/19/2023] Open
Abstract
PURPOSE To optimize the analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) under the two-compartment-exchange-model (2CXM) and to incorporate voxelwise bolus-arrival-time (BAT). MATERIALS AND METHODS The accuracy of the pharmacokinetic (PK) parameters, extracted from 3T DCE-MRI using 2CXM, was tested under several conditions: eight algorithms for data estimation; correction for BAT; using model selection; different temporal resolution and scan duration. Comparisons were performed on simulated data. The best algorithm was applied to seven patients with brain tumors or following stroke. The extracted perfusion parameters were compared to those of dynamic susceptibility contrast MRI (DSC-MRI). RESULTS ACoPeD (AIF-corrected-perfusion-DCE-MRI), an analysis using a 2nd derivative regularized-spline and incorporating BAT, achieved the most accurate estimation in simulated data, mean-relative-error: Fp , F, vp , ve : 24.8%, 41.7%, 26.4%, 27.2% vs. 76.5%, 190.8%, 78.8%, 82.39% of the direct four parameters estimation (one-sided two-sample t-test, P < 0.001). Correction for BAT increased the estimation accuracy of the PK parameters by more than 30% and provided a supertemporal resolution estimation of the BAT (higher than the acquired resolution, mean-absolute-error 0.2 sec). High temporal resolution (∼2 sec) is required to avoid biased estimation of PK parameters, and long scan duration (∼20 min) is important for reliable permeability but not for perfusion estimations, mean-error-reduction: E: ∼12%, ve : ∼6%. Using ACoPeD, PK values from normal-appearing white matter, gray matter, and lesion were extracted from patients. Preliminary results showed significant voxelwise correlations to DSC-MRI, between flow values in a patient following stroke (r = 0.49, P < 0.001), and blood volume in a patient with a brain tumor (r = 0.62, P < 0.001). CONCLUSION This study proposes an optimized analysis method, ACoPeD, for tissue perfusion and permeability estimation using DCE-MRI, to be used in clinical settings. LEVEL OF EVIDENCE 1 J. Magn. Reson. Imaging 2017;45:237-249.
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Affiliation(s)
- Guy Nadav
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Gilad Liberman
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Department of Chemical Physics, Weizmann Institute, Rehovot, Israel
| | - Moran Artzi
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Nahum Kiryati
- School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Dafna Ben Bashat
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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Huang W, Chen Y, Fedorov A, Li X, Jajamovich GH, Malyarenko DI, Aryal MP, LaViolette PS, Oborski MJ, O'Sullivan F, Abramson RG, Jafari-Khouzani K, Afzal A, Tudorica A, Moloney B, Gupta SN, Besa C, Kalpathy-Cramer J, Mountz JM, Laymon CM, Muzi M, Schmainda K, Cao Y, Chenevert TL, Taouli B, Yankeelov TE, Fennessy F, Li X. The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge. ACTA ACUST UNITED AC 2016; 2:56-66. [PMID: 27200418 PMCID: PMC4869732 DOI: 10.18383/j.tom.2015.00184] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kepvs. 0.74 for Ktrans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than Ktrans.
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Affiliation(s)
- Wei Huang
- Oregon Health and Science University, Portland, OR
| | - Yiyi Chen
- Oregon Health and Science University, Portland, OR
| | - Andriy Fedorov
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Xia Li
- General ElectricGlobal Research, Niskayuna, NY
| | | | | | | | | | | | | | | | | | - Aneela Afzal
- Oregon Health and Science University, Portland, OR
| | | | | | | | - Cecilia Besa
- Icahn School ofMedicine at Mount Sinai, New York, NY
| | | | | | | | - Mark Muzi
- University of Washington, Seattle, WA
| | | | - Yue Cao
- University of Michigan, Ann Arbor, MI
| | | | - Bachir Taouli
- Icahn School ofMedicine at Mount Sinai, New York, NY
| | | | - Fiona Fennessy
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Xin Li
- Oregon Health and Science University, Portland, OR
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13
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Sommer K, Bernat D, Schmidt R, Breit HC, Schreiber LM. Resting myocardial blood flow quantification using contrast-enhanced magnetic resonance imaging in the presence of stenosis: A computational fluid dynamics study. Med Phys 2015; 42:4375-84. [PMID: 26133634 DOI: 10.1118/1.4922708] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE The extent to which atherosclerotic plaques affect contrast agent (CA) transport in the coronary arteries and, hence, quantification of myocardial blood flow (MBF) using magnetic resonance imaging (MRI) is unclear. The purpose of this work was to evaluate the influence of plaque induced stenosis both on CA transport and on the accuracy of MBF quantification. METHODS Computational fluid dynamics simulations in a high-detailed realistic vascular model were employed to investigate CA bolus transport in the coronary arteries. The impact of atherosclerosis was analyzed by inserting various medium- to high-grade stenoses in the vascular model. The influence of stenosis morphology was examined by varying the stenosis shapes but keeping the area reduction constant. Errors due to CA bolus transport were analyzed using the tracer-kinetic model MMID4. RESULTS Dispersion of the CA bolus was found in all models and for all outlets, but with a varying magnitude. The impact of stenosis was complex: while high-grade stenoses amplified dispersion, mild stenoses reduced the effect. Morphology was found to have a marked influence on dispersion for a small number of outlets in the post-stenotic region. Despite this marked influence on the concentration-time curves, MBF errors were less affected by stenosis. In total, MBF was underestimated by -7.9% to -44.9%. CONCLUSIONS The presented results reveal that local hemodynamics in the coronary vasculature appears to have a direct impact on CA bolus dispersion. Inclusion of atherosclerotic plaques resulted in a complex alteration of this effect, with both degree of area reduction and stenosis morphology affecting the amount of dispersion. This strong influence of vascular transport effects impairs the accuracy of MRI-based MBF quantification techniques and, potentially, other bolus-based perfusion measurement techniques like computed tomography perfusion imaging.
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Affiliation(s)
- Karsten Sommer
- Section of Medical Physics, Department of Radiology, Johannes Gutenberg University Medical Center, Mainz 55131, Germany and Max Planck Graduate Center with the Johannes Gutenberg University Mainz, Mainz 55128, Germany
| | - Dominik Bernat
- Section of Medical Physics, Department of Radiology, Johannes Gutenberg University Medical Center, Mainz 55131, Germany
| | - Regine Schmidt
- Section of Medical Physics, Department of Radiology, Johannes Gutenberg University Medical Center, Mainz 55131, Germany
| | - Hanns-Christian Breit
- Section of Medical Physics, Department of Radiology, Johannes Gutenberg University Medical Center, Mainz 55131, Germany
| | - Laura M Schreiber
- Comprehensive Heart Failure Center, Department of Cardiovascular Imaging, Würzburg University Hospital, Würzburg 97078, Germany
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14
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Filice S, Crisi G. Dynamic Contrast-Enhanced Perfusion MRI of High Grade Brain Gliomas Obtained with Arterial or Venous Waveform Input Function. J Neuroimaging 2015; 26:124-9. [PMID: 25923172 DOI: 10.1111/jon.12254] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 03/26/2015] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE The aim of this study was to evaluate the differences in dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) perfusion estimates of high-grade brain gliomas (HGG) due to the use of an input function (IF) obtained respectively from arterial (AIF) and venous (VIF) approaches by two different commercially available software applications. METHODS This prospective study includes 20 patients with pathologically confirmed diagnosis of high-grade gliomas. The data source was processed by using two DCE dedicated commercial packages, both based on the extended Toft model, but the first customized to obtain input function from arterial measurement and the second from sagittal sinus sampling. The quantitative parametric perfusion maps estimated from the two software packages were compared by means of a region of interest (ROI) analysis. The resulting input functions from venous and arterial data were also compared. RESULTS No significant difference has been found between the perfusion parameters obtained with the two different software packages (P-value < .05). The comparison of the VIFs and AIFs obtained by the two packages showed no statistical differences. CONCLUSIONS Direct comparison of DCE-MRI measurements with IF generated by means of arterial or venous waveform led to no statistical difference in quantitative metrics for evaluating HGG. However, additional research involving DCE-MRI acquisition protocols and post-processing would be beneficial to further substantiate the effectiveness of venous approach as the IF method compared with arterial-based IF measurement.
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Affiliation(s)
- Silvano Filice
- Department of Medical Physics and the Department of Neuroradiology, University Hospital of Parma, Parma, Italy
| | - Girolamo Crisi
- Department of Medical Physics and the Department of Neuroradiology, University Hospital of Parma, Parma, Italy
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15
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Chassidim Y, Vazana U, Prager O, Veksler R, Bar-Klein G, Schoknecht K, Fassler M, Lublinsky S, Shelef I. Analyzing the blood-brain barrier: the benefits of medical imaging in research and clinical practice. Semin Cell Dev Biol 2014; 38:43-52. [PMID: 25455024 DOI: 10.1016/j.semcdb.2014.11.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Revised: 11/23/2014] [Accepted: 11/24/2014] [Indexed: 01/03/2023]
Abstract
A dysfunctional BBB is a common feature in a variety of brain disorders, a fact stressing the need for diagnostic tools designed to assess brain vessels' permeability in space and time. Biological research has benefited over the years various means to analyze BBB integrity. The use of biomarkers for improper BBB functionality is abundant. Systemic administration of BBB impermeable tracers can both visualize brain regions characterized by BBB impairment, as well as lead to its quantification. Additionally, locating molecular, physiological content in regions from which it is restricted under normal BBB functionality undoubtedly indicates brain pathology-related BBB disruption. However, in-depth research into the BBB's phenotype demands higher analytical complexity than functional vs. pathological BBB; criteria which biomarker based BBB permeability analyses do not meet. The involvement of accurate and engineering sciences in recent brain research, has led to improvements in the field, in the form of more accurate, sensitive imaging-based methods. Improvements in the spatiotemporal resolution of many imaging modalities and in image processing techniques, make up for the inadequacies of biomarker based analyses. In pre-clinical research, imaging approaches involving invasive procedures, enable microscopic evaluation of BBB integrity, and benefit high levels of sensitivity and accuracy. However, invasive techniques may alter normal physiological function, thus generating a modality-based impact on vessel's permeability, which needs to be corrected for. Non-invasive approaches do not affect proper functionality of the inspected system, but lack in spatiotemporal resolution. Nevertheless, the benefit of medical imaging, even in pre-clinical phases, outweighs its disadvantages. The innovations in pre-clinical imaging and the development of novel processing techniques, have led to their implementation in clinical use as well. Specialized analyses of vessels' permeability add valuable information to standard anatomical inspections which do not take the latter into consideration.
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Affiliation(s)
- Yoash Chassidim
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Udi Vazana
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ofer Prager
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ronel Veksler
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Guy Bar-Klein
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Karl Schoknecht
- Department of Neurophysiology, Charite University of Medicine, Berlin, Germany
| | - Michael Fassler
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Svetlana Lublinsky
- Departments of Physiology & Cell Biology, Cognitive and Brain Sciences, The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ilan Shelef
- Medical Imaging Institute, Soroka Medical Center, Beer-Sheva, Israel
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Veksler R, Shelef I, Friedman A. Blood-brain barrier imaging in human neuropathologies. Arch Med Res 2014; 45:646-52. [PMID: 25453223 DOI: 10.1016/j.arcmed.2014.11.016] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 11/20/2014] [Indexed: 01/22/2023]
Abstract
The blood-brain barrier (BBB) is essential for normal function of the brain, and its role in many brain pathologies has been the focus of numerous studies during the last decades. Dysfunction of the BBB is not only being shown in numerous brain diseases, but animal studies have indicated that it plays a direct key role in the genesis of neurovascular dysfunction and associated neurodegeneration. As such evidence accumulates, the need for robust and clinically applicable methods for minimally invasive assessment of BBB integrity is becoming urgent. This review provides an introduction to BBB imaging methods in the clinical scenario. First, imaging modalities are reviewed, with a focus on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We then proceed to review image analysis methods, including quantitative and semi-quantitative methods. The advantages and limitations of each approach are discussed, and future directions and questions are highlighted.
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Affiliation(s)
- Ronel Veksler
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ilan Shelef
- Department of Medical Imaging, Soroka University Medical Center and the Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alon Friedman
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel; Department of Medical Neuroscience, Faculty of Medicine, Dalhousie University, Halifax, Canada.
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17
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Poulin É, Lebel R, Croteau É, Blanchette M, Tremblay L, Lecomte R, Bentourkia M, Lepage M. Optimization of the reference region method for dual pharmacokinetic modeling using Gd-DTPA/MRI and (18) F-FDG/PET. Magn Reson Med 2014; 73:740-8. [PMID: 24604379 DOI: 10.1002/mrm.25151] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Revised: 01/07/2014] [Accepted: 01/08/2014] [Indexed: 11/06/2022]
Abstract
PURPOSE The combination of MRI and positron emission tomography (PET) offers new possibilities for the development of novel methodologies. In pharmacokinetic image analysis, the blood concentration of the imaging compound as a function of time, [i.e., the arterial input function (AIF)] is required for MRI and PET. In this study, we tested whether an AIF extracted from a reference region (RR) in MRI can be used as a surrogate for the manually sampled (18) F-FDG AIF for pharmacokinetic modeling. METHODS An MRI contrast agent, gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA) and a radiotracer, (18) F-fluorodeoxyglucose ((18) F-FDG), were simultaneously injected in a F98 glioblastoma rat model. A correction to the RR AIF for Gd-DTPA is proposed to adequately represent the manually sampled AIF. A previously published conversion method was applied to convert this AIF into a (18) F-FDG AIF. RESULTS The tumor metabolic rate of glucose (TMRGlc) calculated with the manually sampled (18) F-FDG AIF, the (18) F-FDG AIF converted from the RR AIF and the (18) F-FDG AIF converted from the corrected RR AIF were found not statistically different (P>0.05). CONCLUSION An AIF derived from an RR in MRI can be accurately converted into a (18) F-FDG AIF and used in PET pharmacokinetic modeling.
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Affiliation(s)
- Éric Poulin
- Centre d'imagerie moléculaire de Sherbrooke, Département de médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, Canada
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Using dynamic contrast-enhanced magnetic resonance imaging data to constrain a positron emission tomography kinetic model: theory and simulations. Int J Biomed Imaging 2013; 2013:576470. [PMID: 24222761 PMCID: PMC3814089 DOI: 10.1155/2013/576470] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2013] [Accepted: 08/29/2013] [Indexed: 01/08/2023] Open
Abstract
We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.
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Fluckiger JU, Benefield BC, Harris KR, Lee DC. Absolute quantification of myocardial blood flow with constrained estimation of the arterial input function. J Magn Reson Imaging 2013; 38:603-9. [PMID: 23371884 DOI: 10.1002/jmri.24025] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2012] [Accepted: 12/07/2012] [Indexed: 12/22/2022] Open
Abstract
PURPOSE To evaluate the performance of the constrained alternating minimization with model (CAMM) method for estimating the input function from the myocardial tissue curves. MATERIALS AND METHODS Myocardial perfusion imaging was performed on seven canine models of coronary artery disease in 15 imaging sessions. In each session, stress was induced with intravenous infusion of adenosine and a variable occluder created coronary artery stenosis. A dual bolus protocol was used for each acquisition, and input functions were then estimated using the CAMM method with data acquired from the high dose scan following each imaging session. For each acquisition, myocardial blood flow was measured by injected microspheres. RESULTS The dual bolus and CAMM-derived flows were not significantly different (P = 0.18), and the correlation between the two methods was high (r = 0.97). The correlation between the dual bolus and CAMM methods and microsphere measurements was lower than that for the two MR methods (r = 0.53; r = 0.43, respectively). CONCLUSION The CAMM method presented here shows promise in estimating myocardial blood flow in patients with coronary artery disease at stress with a single injection and without any specialized acquisitions. Further work is needed to validate the approach in a clinical setting.
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Affiliation(s)
- Jacob U Fluckiger
- Department of Radiology, Northwestern University, Chicago, Illinois, USA.
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Fluckiger JU, Schabel MC, Dibella EVR. The effect of temporal sampling on quantitative pharmacokinetic and three-time-point analysis of breast DCE-MRI. Magn Reson Imaging 2012; 30:934-43. [PMID: 22513074 DOI: 10.1016/j.mri.2012.02.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2011] [Revised: 02/15/2012] [Accepted: 02/17/2012] [Indexed: 01/28/2023]
Abstract
The effects of temporal sampling on the previously published three-time-point (3TP) method are compared with those of a Tofts-Kety model using an arterial input function from the alternating minimization with model (AMM) method. Computer simulations are done to estimate the expected error in both the 3TP and Tofts-Kety models as a function of the temporal sampling rate of the data. The error in the 3TP model parameters remained essentially constant with respect to temporal sampling. The Tofts-Kety model showed a linear increase in parameter error with respect to temporal sampling. Both analysis methods were also applied to 87 clinically acquired breast scans. These scans were downsampled in time by a factor of 2 and 4, and the methods were reapplied. The spatial resolution was held constant throughout this study. At temporal resolutions less than 19.4 s, the Tofts-Kety model outperformed the 3TP model using receiver operating characteristic curve analysis (area under the ROC curve [AUC] of 0.94 compared to 0.91). As the temporal sampling rate decreased, the 3TP model outperformed the Tofts-Kety model (AUC of 0.89 versus 0.85). When the temporal sampling rate of the data was less than 20 s, the Tofts-Kety model with the AMM method had lower parameter error than the 3TP method.
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Affiliation(s)
- Jacob U Fluckiger
- Department of Radiology, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT 84108, USA
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Fluckiger JU, Schabel MC, DiBella EVR. Constrained estimation of the arterial input function for myocardial perfusion cardiovascular magnetic resonance. Magn Reson Med 2011; 66:419-27. [PMID: 21446030 DOI: 10.1002/mrm.22809] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2010] [Revised: 12/02/2010] [Accepted: 12/10/2010] [Indexed: 12/21/2022]
Abstract
Accurate quantification of myocardial perfusion remains challenging due to saturation of the arterial input function at high contrast concentrations. A method for estimating the arterial input function directly from tissue curves in the myocardium that avoids these difficulties is presented. In this constrained alternating minimization with model (CAMM) algorithm, a portion of the left ventricular blood pool signal is also used to constrain the estimation process. Extensive computer simulations assessing the accuracy of kinetic parameter estimation were performed. In 5000 noise realizations, the use of the AIF given by the estimation method returned kinetic parameters with mean Ktrans error of -2% and mean kep error of 0.4%. Twenty in vivo resting perfusion datasets were also processed with this method, and pharmacokinetic parameter values derived from the blind AIF were compared with those derived from a dual-bolus measured AIF. For 17 of the 20 datasets, there were no statistically significant differences in Ktrans estimates, and in aggregate the kinetic parameters were not significantly different from the dual-bolus method. The cardiac constrained alternating minimization with model method presented here provides a promising approach to quantifying perfusion of myocardial tissue with a single injection of contrast agent and without a special pulse sequence though further work is needed to validate the approach in a clinical setting.
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Affiliation(s)
- Jacob U Fluckiger
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah 84108, USA
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