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Shalom ES, Kim H, van der Heijden RA, Ahmed Z, Patel R, Hormuth DA, DiCarlo JC, Yankeelov TE, Sisco NJ, Dortch RD, Stokes AM, Inglese M, Grech-Sollars M, Toschi N, Sahoo P, Singh A, Verma SK, Rathore DK, Kazerouni AS, Partridge SC, LoCastro E, Paudyal R, Wolansky IA, Shukla-Dave A, Schouten P, Gurney-Champion OJ, Jiřík R, Macíček O, Bartoš M, Vitouš J, Das AB, Kim SG, Bokacheva L, Mikheev A, Rusinek H, Berks M, Hubbard Cristinacce PL, Little RA, Cheung S, O'Connor JPB, Parker GJM, Moloney B, LaViolette PS, Bobholz S, Duenweg S, Virostko J, Laue HO, Sung K, Nabavizadeh A, Saligheh Rad H, Hu LS, Sourbron S, Bell LC, Fathi Kazerooni A. The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge. Magn Reson Med 2024; 91:1803-1821. [PMID: 38115695 DOI: 10.1002/mrm.29909] [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: 04/14/2023] [Revised: 08/22/2023] [Accepted: 10/16/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools forK trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardizeK trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS A framework was created to evaluateK trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines forK trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants'K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposedOSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS Across the 10 received submissions, theOSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability inK trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability withinK trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.
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Affiliation(s)
- Eve S Shalom
- School of Physics and Astronomy, University of Leeds, Leeds, UK
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Harrison Kim
- Department of Radiology, University of Alabama, Birmingham, Alabama, USA
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Reyna Patel
- Department of Radiology, Neuroradiology Division, Mayo Clinic, Scottsdale, Arizona, USA
| | - David A Hormuth
- Oden Institute for Computational Engineering and Sciences, The University of Texas, Austin, Texas, USA
| | - Julie C DiCarlo
- Biomedical Imaging Center, Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, Oncology, Livestrong Cancer Institutes, Oden Institute for Computational Engineering and Sciences, The University of Texas, Austin, Texas, USA
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas J Sisco
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Richard D Dortch
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Ashley M Stokes
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Marianna Inglese
- Department of Biomedicine and Prevention, University of Rome, Tor Vergata, Italy
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Matthew Grech-Sollars
- Department of Surgery and Cancer, Imperial College, London, UK
- Department of Computer Science, University College London, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome, Tor Vergata, Italy
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts, USA
| | - Prativa Sahoo
- University Medical Center Göttingen, Göttingen, Germany
| | - Anup Singh
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Sanjay K Verma
- Institute of Bioengineering and Bioimaging, Singapore, Singapore
| | - Divya K Rathore
- Institute of Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Anum S Kazerouni
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | | | - Eve LoCastro
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ivan A Wolansky
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Pepijn Schouten
- Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, The Netherlands
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Radovan Jiřík
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Ondřej Macíček
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Michal Bartoš
- Czech Academy of Sciences, Institute of Information Theory and Automation, Praha, Czech Republic
| | - Jiří Vitouš
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | | | - S Gene Kim
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Louisa Bokacheva
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Artem Mikheev
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Henry Rusinek
- Department of Radiology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Michael Berks
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | | | - Ross A Little
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Susan Cheung
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - James P B O'Connor
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- Department of Radiology, The Christie Hospital NHS Trust, Manchester, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Geoff J M Parker
- Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Bioxydyn Ltd, Manchester, UK
| | - Brendan Moloney
- Advanced Imaging Research Center, Oregon Health & Science Institute, Portland, Oregon, USA
| | - Peter S LaViolette
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Samuel Bobholz
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Savannah Duenweg
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - John Virostko
- Department of Diagnostic Medicine, University of Texas, Austin, Texas, USA
| | - Hendrik O Laue
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Kyunghyun Sung
- Department of Radiological Sciences, University of California, Los Angeles, California, USA
| | - Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Center for Data-Driven Discovery, Division of Neurosurgery, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Center for Computational Imaging & Simulation Technologies in Biomedicine, School of Computing/School of Medicine, University of Leeds, Leeds, UK
| | - Leland S Hu
- Neuroradiology Division, Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA
| | - Steven Sourbron
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Laura C Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | - Anahita Fathi Kazerooni
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, USA
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Maziero D, Azzam GA, de La Fuente M, Stoyanova R, Ford JC, Mellon EA. Implementation and evaluation of a dynamic contrast-enhanced MR perfusion protocol for glioblastoma using a 0.35 T MRI-Linac system. Phys Med 2024; 119:103316. [PMID: 38340693 DOI: 10.1016/j.ejmp.2024.103316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 11/29/2023] [Accepted: 02/05/2024] [Indexed: 02/12/2024] Open
Abstract
PURPOSE MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35 T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3D-T1w) and dynamic contrast-enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35 T MRI-Linac. METHODS AND MATERIALS The protocol implemented was used to acquire 3D-T1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0.35 T MRI-Linac. The detection of post-contrast-enhanced volumes was evaluated by comparing the 3DT1w images from the 0.35 T MRI-Linac to images obtained using a 3 T scanner. The DCE data were tested temporally and spatially using data from a flow phantom and patients. Ktrans maps were derived from DCE at three time points (a week before treatment-Pre RT, four weeks through treatment-Mid RT, and three weeks after treatment-Post RT) and were validated with patients' treatment outcomes. RESULTS The 3D-T1w contrast-enhancement volumes were visually and volumetrically similar between 0.35 T MRI-Linac and 3 T. DCE images showed temporal stability, and associated Ktrans maps were consistent with patient response to treatment. On average, Ktrans values showed a 54 % decrease and 8.6 % increase for a responder and non-responder respectively when Pre RT and Mid RT images were compared. CONCLUSION Our findings support the feasibility of obtaining post-contrast 3D-T1w and DCE data from patients with glioblastoma using a 0.35 T MRI-Linac system.
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Affiliation(s)
- Danilo Maziero
- Department of Radiation Medicine & Applied Sciences, UC San Diego Health, La Jolla, CA 92093, United States; Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States.
| | - Gregory Albert Azzam
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
| | - Macarena de La Fuente
- Department of Neurology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
| | - Radka Stoyanova
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
| | - John Chetley Ford
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
| | - Eric Albert Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
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Sayin ES, Duffin J, Stumpo V, Bellomo J, Piccirelli M, Poublanc J, Wijeya V, Para A, Pangalu A, Bink A, Nemeth B, Kulcsar Z, Mikulis DJ, Fisher JA, Sobczyk O, Fierstra J. Assessing Perfusion in Steno-Occlusive Cerebrovascular Disease Using Transient Hypoxia-Induced Deoxyhemoglobin as a Dynamic Susceptibility Contrast Agent. AJNR Am J Neuroradiol 2023; 45:37-43. [PMID: 38164571 PMCID: PMC10756578 DOI: 10.3174/ajnr.a8068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 11/01/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND PURPOSE Resting brain tissue perfusion in cerebral steno-occlusive vascular disease can be assessed by MR imaging using gadolinium-based susceptibility contrast agents. Recently, transient hypoxia-induced deoxyhemoglobin has been investigated as a noninvasive MR imaging contrast agent. Here we present a comparison of resting perfusion metrics using transient hypoxia-induced deoxyhemoglobin and gadolinium-based contrast agents in patients with known cerebrovascular steno-occlusive disease. MATERIALS AND METHODS Twelve patients with steno-occlusive disease underwent DSC MR imaging using a standard bolus of gadolinium-based contrast agent compared with transient hypoxia-induced deoxyhemoglobin generated in the lungs using an automated gas blender. A conventional multi-slice 2D gradient echo sequence was used to acquire the perfusion data and analyzed using a standard tracer kinetic model. MTT, relative CBF, and relative CBV maps were generated and compared between contrast agents. RESULTS The spatial distributions of the perfusion metrics generated with both contrast agents were consistent. Perfusion metrics in GM and WM were not statistically different except for WM MTT. CONCLUSIONS Cerebral perfusion metrics generated with noninvasive transient hypoxia-induced changes in deoxyhemoglobin are very similar to those generated using a gadolinium-based contrast agent in patients with cerebrovascular steno-occlusive disease.
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Affiliation(s)
- Ece Su Sayin
- From the Department of Physiology (E.S.S., J.D., J.A.F.), University of Toronto, Toronto, Ontario, Canada
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - James Duffin
- From the Department of Physiology (E.S.S., J.D., J.A.F.), University of Toronto, Toronto, Ontario, Canada
- Department of Anesthesia and Pain Management (J.D., J.A.F.), University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Vittorio Stumpo
- Department of Neurosurgery (V.S., J.B. J.F.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jacopo Bellomo
- Department of Neurosurgery (V.S., J.B. J.F.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Marco Piccirelli
- Department of Neuroradiology and Clinical Neuroscience Center (M.P., A. Pangalu, A.B., B.N., Z.K.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Julien Poublanc
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - Vepeson Wijeya
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - Andrea Para
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - Athina Pangalu
- Department of Neuroradiology and Clinical Neuroscience Center (M.P., A. Pangalu, A.B., B.N., Z.K.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology and Clinical Neuroscience Center (M.P., A. Pangalu, A.B., B.N., Z.K.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Bence Nemeth
- Department of Neuroradiology and Clinical Neuroscience Center (M.P., A. Pangalu, A.B., B.N., Z.K.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology and Clinical Neuroscience Center (M.P., A. Pangalu, A.B., B.N., Z.K.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - David J Mikulis
- Department of Medical Biophysics (D.J.M.), University of Toronto, Toronto, Ontario, Canada
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - Joseph A Fisher
- From the Department of Physiology (E.S.S., J.D., J.A.F.), University of Toronto, Toronto, Ontario, Canada
- Department of Anesthesia and Pain Management (J.D., J.A.F.), University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Olivia Sobczyk
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab (E.S.S., J.P., V.W., A. Para, D.J.M., O.S.), University Health Network, Toronto, Ontario, Canada
| | - Jorn Fierstra
- Department of Neurosurgery (V.S., J.B. J.F.), University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Seidemo A, Wirestam R, Helms G, Markenroth Bloch K, Xu X, Bengzon J, Sundgren PC, van Zijl PCM, Knutsson L. Tissue response curve-shape analysis of dynamic glucose-enhanced and dynamic contrast-enhanced magnetic resonance imaging in patients with brain tumor. NMR IN BIOMEDICINE 2023; 36:e4863. [PMID: 36310022 DOI: 10.1002/nbm.4863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/10/2022] [Accepted: 10/28/2022] [Indexed: 05/23/2023]
Abstract
Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p < 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.
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Affiliation(s)
- Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Gunther Helms
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | | | - Xiang Xu
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute, New York, New York, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Johan Bengzon
- Division of Neurosurgery, Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Lund Stem Cell Center, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Pia C Sundgren
- Lund University Bioimaging Center, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund and Malmö, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Mazaheri Y, Kim N, Lakhman Y, Jafari R, Vargas A, Otazo R. Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters. NMR IN BIOMEDICINE 2022; 35:e4718. [PMID: 35226774 PMCID: PMC9203940 DOI: 10.1002/nbm.4718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/17/2022] [Accepted: 02/22/2022] [Indexed: 06/14/2023]
Abstract
The aim of this work is to develop a data-driven quantitative dynamic contrast-enhanced (DCE) MRI technique using Golden-angle RAdial Sparse Parallel (GRASP) MRI with high spatial resolution and high flexible temporal resolution and pharmacokinetic (PK) analysis with an arterial input function (AIF) estimated directly from the data obtained from each patient. DCE-MRI was performed on 13 patients with gynecological malignancy using a 3-T MRI scanner with a single continuous golden-angle stack-of-stars acquisition and image reconstruction with two temporal resolutions, by exploiting a unique feature in GRASP that reconstructs acquired data with user-defined temporal resolution. Joint estimation of the AIF (both AIF shape and delay) and PK parameters was performed with an iterative algorithm that alternates between AIF and PK estimation. Computer simulations were performed to determine the accuracy (expressed as percentage error [PE]) and precision of the estimated parameters. PK parameters (volume transfer constant [Ktrans ], fractional volume of the extravascular extracellular space [ve ], and blood plasma volume fraction [vp ]) and normalized root-mean-square error [nRMSE] (%) of the fitting errors for the tumor contrast kinetic data were measured both with population-averaged and data-driven AIFs. On patient data, the Wilcoxon signed-rank test was performed to compare nRMSE. Simulations demonstrated that GRASP image reconstruction with a temporal resolution of 1 s/frame for AIF estimation and 5 s/frame for PK analysis resulted in an absolute PE of less than 5% in the estimation of Ktrans and ve , and less than 11% in the estimation of vp . The nRMSE (mean ± SD) for the dual temporal resolution image reconstruction and data-driven AIF was 0.16 ± 0.04 compared with 0.27 ± 0.10 (p < 0.001) with 1 s/frame using population-averaged AIF, and 0.23 ± 0.07 with 5 s/frame using population-averaged AIF (p < 0.001). We conclude that DCE-MRI data acquired and reconstructed with the GRASP technique at dual temporal resolution can successfully be applied to jointly estimate the AIF and PK parameters from a single acquisition resulting in data-driven AIFs and voxelwise PK parametric maps.
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Affiliation(s)
- Yousef Mazaheri
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Nathanael Kim
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Yulia Lakhman
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ramin Jafari
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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Amini Farsani Z, Schmid VJ. Maximum Entropy Technique and Regularization Functional for Determining the Pharmacokinetic Parameters in DCE-MRI. J Digit Imaging 2022; 35:1176-1188. [PMID: 35618849 PMCID: PMC9582183 DOI: 10.1007/s10278-022-00646-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/15/2022] [Accepted: 04/21/2022] [Indexed: 10/31/2022] Open
Abstract
This paper aims to solve the arterial input function (AIF) determination in dynamic contrast-enhanced MRI (DCE-MRI), an important linear ill-posed inverse problem, using the maximum entropy technique (MET) and regularization functionals. In addition, estimating the pharmacokinetic parameters from a DCE-MR image investigations is an urgent need to obtain the precise information about the AIF-the concentration of the contrast agent on the left ventricular blood pool measured over time. For this reason, the main idea is to show how to find a unique solution of linear system of equations generally in the form of [Formula: see text] named an ill-conditioned linear system of equations after discretization of the integral equations, which appear in different tomographic image restoration and reconstruction issues. Here, a new algorithm is described to estimate an appropriate probability distribution function for AIF according to the MET and regularization functionals for the contrast agent concentration when applying Bayesian estimation approach to estimate two different pharmacokinetic parameters. Moreover, by using the proposed approach when analyzing simulated and real datasets of the breast tumors according to pharmacokinetic factors, it indicates that using Bayesian inference-that infer the uncertainties of the computed solutions, and specific knowledge of the noise and errors-combined with the regularization functional of the maximum entropy problem, improved the convergence behavior and led to more consistent morphological and functional statistics and results. Finally, in comparison to the proposed exponential distribution based on MET and Newton's method, or Weibull distribution via the MET and teaching-learning-based optimization (MET/TLBO) in the previous studies, the family of Gamma and Erlang distributions estimated by the new algorithm are more appropriate and robust AIFs.
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Affiliation(s)
- Zahra Amini Farsani
- Bayesian Imaging and Spatial Statistics Group, Institute of Statistics, Ludwig-Maximilian-Universität München, Ludwigstraße 33, 80539, Munich, Germany. .,Statistics Department, School of Science, Lorestan University, 68151-44316, Khorramabad, Iran.
| | - Volker J Schmid
- Bayesian Imaging and Spatial Statistics Group, Institute of Statistics, Ludwig-Maximilian-Universität München, Ludwigstraße 33, 80539, Munich, Germany
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Sun B, Ge X, Li X, Zhang J, Zhao Z, Liu X, Zhou Y, Xu J, Zhao H, Sun J. Elevated Hemoglobin A1c Is Associated With Leaky Plaque Neovasculature as Detected by Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Arterioscler Thromb Vasc Biol 2022; 42:504-513. [PMID: 35236109 DOI: 10.1161/atvbaha.121.317190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 02/14/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Patients with diabetes have accelerated atherosclerosis progression, but the underlying mechanisms are not fully understood. Dynamic contrast-enhanced magnetic resonance imaging has allowed in vivo characterization of plaque neovasculature, which plays a critical role in plaque progression. We aimed to evaluate the impact of diabetes on carotid plaque neovasculature as assessed by dynamic contrast-enhanced magnetic resonance imaging. METHODS Patients with recent ischemic stroke and ipsilateral carotid plaque underwent multicontrast magnetic resonance imaging for characterizing plaque morphology and dynamic contrast-enhanced magnetic resonance imaging for pharmacokinetic parameters of plaque neovasculature, including transfer constant (Ktrans, reflecting flow, endothelial surface area, and permeability) and fractional plasma volume (νp). RESULTS Sixty-five patients were enrolled, including 30 patients with diabetes (years since diagnosis: median 5.0 [interquartile range, [3.0-12.0]) and 35 patients without diabetes. Subjects with diabetes had a greater plaque burden and a higher prevalence of high-risk characteristics. Additionally, carotid plaques in the subjects with diabetes showed higher Ktrans than those in the subjects without diabetes (0.100±0.048 min-1 versus 0.067±0.042 min-1, P=0.005) but νp was numerically lower in the subjects with diabetes (5.2±3.7% versus 6.2±4.3%, P=0.31). The association of diabetes with high Ktrans (β=0.033, P=0.005) was independent of patient and plaque characteristics and remained largely intact after adjusting for serum lipids, glucose, or hs-CRP (high-sensitivity C-reactive protein). However, it became nonexistent after adjusting for hemoglobin A1c (β=-0.010, P=0.49). CONCLUSIONS Dynamic contrast-enhanced magnetic resonance imaging of carotid plaques suggested that plaque neovasculature in patients with diabetes is leaky, indicating enhanced capability of bringing blood constituents and facilitating extravasation of inflammatory cells, erythrocytes, and plasma proteins. Leaky plaque neovasculature correlated with hemoglobin A1c and may play a role in accelerated atherosclerosis progression in diabetes.
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Affiliation(s)
- Beibei Sun
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Xiaoqian Ge
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
- Department of Radiology, Shandong Second Provincial General Hospital, Jinan, China (X.G.)
| | - Xiao Li
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
- Department of Radiology, Shandong Second Provincial General Hospital, Jinan, China (X.G.)
| | - Jianjian Zhang
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Zizhou Zhao
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Xiaosheng Liu
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Huilin Zhao
- Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, China (B.S., X.G., X.L., J.Z., Z.Z., X.L., Y.Z., J.X., H.Z.)
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle (J.S.)
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8
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Bhaduri S, Lesbats C, Sharkey J, Kelly CL, Mukherjee S, Taylor A, Delikatny EJ, Kim SG, Poptani H. Assessing Tumour Haemodynamic Heterogeneity and Response to Choline Kinase Inhibition Using Clustered Dynamic Contrast Enhanced MRI Parameters in Rodent Models of Glioblastoma. Cancers (Basel) 2022; 14:cancers14051223. [PMID: 35267531 PMCID: PMC8909848 DOI: 10.3390/cancers14051223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/16/2022] [Accepted: 02/23/2022] [Indexed: 12/04/2022] Open
Abstract
To investigate the utility of DCE-MRI derived pharmacokinetic parameters in evaluating tumour haemodynamic heterogeneity and treatment response in rodent models of glioblastoma, imaging was performed on intracranial F98 and GL261 glioblastoma bearing rodents. Clustering of the DCE-MRI-based parametric maps (using Tofts, extended Tofts, shutter speed, two-compartment, and the second generation shutter speed models) was performed using a hierarchical clustering algorithm, resulting in areas with poor fit (reflecting necrosis), low, medium, and high valued pixels representing parameters Ktrans, ve, Kep, vp, τi and Fp. There was a significant increase in the number of necrotic pixels with increasing tumour volume and a significant correlation between ve and tumour volume suggesting increased extracellular volume in larger tumours. In terms of therapeutic response in F98 rat GBMs, a sustained decrease in permeability and perfusion and a reduced cell density was observed during treatment with JAS239 based on Ktrans, Fp and ve as compared to control animals. No significant differences in these parameters were found for the GL261 tumour, indicating that this model may be less sensitive to JAS239 treatment regarding changes in vascular parameters. This study demonstrates that region-based clustered pharmacokinetic parameters derived from DCE-MRI may be useful in assessing tumour haemodynamic heterogeneity with the potential for assessing therapeutic response.
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Affiliation(s)
- Sourav Bhaduri
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Clémentine Lesbats
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK
| | - Jack Sharkey
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Claire Louise Kelly
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Soham Mukherjee
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Arthur Taylor
- Department of Molecular Physiology & Cell Signalling, University of Liverpool, Liverpool L69 3BX, UK;
| | - Edward J. Delikatny
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Sungheon G. Kim
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA;
| | - Harish Poptani
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Correspondence:
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9
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Modified Maximum Entropy Method and Estimating the AIF via DCE-MRI Data Analysis. ENTROPY 2022; 24:e24020155. [PMID: 35205451 PMCID: PMC8871336 DOI: 10.3390/e24020155] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/16/2022] [Accepted: 01/17/2022] [Indexed: 02/06/2023]
Abstract
Background: For the kinetic models used in contrast-based medical imaging, the assignment of the arterial input function named AIF is essential for the estimation of the physiological parameters of the tissue via solving an optimization problem. Objective: In the current study, we estimate the AIF relayed on the modified maximum entropy method. The effectiveness of several numerical methods to determine kinetic parameters and the AIF is evaluated—in situations where enough information about the AIF is not available. The purpose of this study is to identify an appropriate method for estimating this function. Materials and Methods: The modified algorithm is a mixture of the maximum entropy approach with an optimization method, named the teaching-learning method. In here, we applied this algorithm in a Bayesian framework to estimate the kinetic parameters when specifying the unique form of the AIF by the maximum entropy method. We assessed the proficiency of the proposed method for assigning the kinetic parameters in the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), when determining AIF with some other parameter-estimation methods and a standard fixed AIF method. A previously analyzed dataset consisting of contrast agent concentrations in tissue and plasma was used. Results and Conclusions: We compared the accuracy of the results for the estimated parameters obtained from the MMEM with those of the empirical method, maximum likelihood method, moment matching (“method of moments”), the least-square method, the modified maximum likelihood approach, and our previous work. Since the current algorithm does not have the problem of starting point in the parameter estimation phase, it could find the best and nearest model to the empirical model of data, and therefore, the results indicated the Weibull distribution as an appropriate and robust AIF and also illustrated the power and effectiveness of the proposed method to estimate the kinetic parameters.
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10
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Bülbül HM, Bülbül O, Sarıoğlu S, Özdoğan Ö, Doğan E, Karabay N. Relationships Between DCE-MRI, DWI, and 18F-FDG PET/CT Parameters with Tumor Grade and Stage in Patients with Head and Neck Squamous Cell Carcinoma. Mol Imaging Radionucl Ther 2021; 30:177-186. [PMID: 34658826 PMCID: PMC8522517 DOI: 10.4274/mirt.galenos.2021.25633] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Objectives Properties of head and neck squamous cell carcinoma (HNSCC) such as cellularity, vascularity, and glucose metabolism interact with each other. This study aimed to investigate the associations between diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and positron emission tomography/computed tomography (PET/CT) in patients with HNSCC. Methods Fourteen patients who were diagnosed with HNSCC were investigated using DCE-MRI, DCE, and 18fluoride-fluorodeoxyglucose PET/CT and evaluated retrospectively. Ktrans, Kep, Ve, and initial area under the curve (iAUC) parameters from DCE-MRI, ADCmax, ADCmean, and ADCmin parameters from DWI, and maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) parameters from PET were obtained. Spearman's correlation coefficient was used to analyze associations between these parameters. In addition, these parameters were grouped according to tumor grade and T and N stages, and the difference between the groups was evaluated using the Mann-Whitney U test. Results Correlations at varying degrees were observed in the parameters investigated. ADCmean moderately correlated with Ve (p=0.035; r=0.566). Ktrans inversely correlated with SUVmax (p=0.017; r=-0.626). iAUC inversely correlated with SUVmax, SUVmean, TLG, and MTV (p<0.05, r≤-0.700). MTV (40% threshold) was significantly higher in T4 tumors than in T1-3 tumors (p=0.020). No significant difference was found in the grouping made according to tumor grade and N stage in terms of these parameters. Conclusion Tumor cellularity, vascular permeability, and glucose metabolism had significant correlations at different degrees. Furthermore, MTV may be useful in predicting T4 tumors.
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Affiliation(s)
- Hande Melike Bülbül
- Recep Tayyip Erdoğan Training and Research Hospital, Clinic of Radiology, Rize, Turkey
| | - Ogün Bülbül
- Recep Tayyip Erdoğan Training and Research Hospital, Clinic of Nuclear Medicine, Rize, Turkey
| | - Sülen Sarıoğlu
- Dokuz Eylül University Faculty of Medicine, Department of Medical Pathology, İzmir, Turkey
| | - Özhan Özdoğan
- Dokuz Eylül University Faculty of Medicine, Department of Nuclear Medicine, İzmir, Turkey
| | - Ersoy Doğan
- Dokuz Eylül University Faculty of Medicine, Department of Otorhinolaryngology, İzmir, Turkey
| | - Nuri Karabay
- Dokuz Eylül University Faculty of Medicine, Department of Radiology, İzmir, Turkey
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11
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Bourassa-Moreau B, Lebel R, Gilbert G, Mathieu D, Lepage M. Robust arterial input function surrogate measurement from the superior sagittal sinus complex signal for fast dynamic contrast-enhanced MRI in the brain. Magn Reson Med 2021; 86:3052-3066. [PMID: 34268824 DOI: 10.1002/mrm.28922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/15/2021] [Accepted: 06/22/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE Accurately estimating the arterial input function for dynamic contrast-enhanced MRI is challenging. An arterial input function is typically determined from signal magnitude changes related to a contrast agent, often leading to underestimation of peak concentrations. Alternatively, signal phase recovers the accurate peak concentration for straight vessels but suffers from high noise. A recent method proposed to fit the signal in the complex plane by combining the advantages of the previous 2 methods. The purpose of this work is to refine this complex-based method to determine the venous output function (VOF), an arterial input function surrogate, from the superior sagittal sinus. METHODS We propose a state-of-the-art complex-based method that includes direct compensation for blood inflow and signal phase correction accounting for the curvature of the superior sagittal sinus, generally assumed collinear with B0 . We compared the magnitude-, phase-, and complex-based VOF determination methods against various simulated biases as well as for 29 brain metastases patients. RESULTS Angulation of the superior sagittal sinus relative to B0 varied widely within patients, and its effect on the signal phase caused an underestimation of peak concentrations of up to 65%. Correction significantly increased the VOF peak concentration for the phase- and complex-based VOFs in the cohort. The phase-based method recovered accurate peak concentrations but lacked precision in the tail of the VOF. Our complex-based VOF completely recovered the effect of inflow and resulted in a high-peak concentration with limited noise. CONCLUSION The new complex-based method resulted in high-quality VOF robust against superior sagittal sinus curvature and variations in patient positioning.
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Affiliation(s)
- Benoît Bourassa-Moreau
- Centre d'imagerie moléculaire de Sherbrooke, Département de médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Réjean Lebel
- Centre d'imagerie moléculaire de Sherbrooke, Département de médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Markham, Ontario, Canada
| | - David Mathieu
- Service de neurochirurgie, Département de chirurgie, Université de Sherbrooke, Sherbrooke, Québec, Canada.,Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Centre intégré de santé et de services sociaux de l'Estrie, Sherbrooke, Québec, Canada
| | - Martin Lepage
- Centre d'imagerie moléculaire de Sherbrooke, Département de médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.,Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Centre intégré de santé et de services sociaux de l'Estrie, Sherbrooke, Québec, Canada
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12
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MRI Dynamic Contrast Imaging of Oral Cavity and Oropharyngeal Tumors. Top Magn Reson Imaging 2021; 30:97-104. [PMID: 33828061 DOI: 10.1097/rmr.0000000000000283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
ABSTRACT In the past decade, dynamic contrast-enhanced magnetic resonance imaging has had an increasing role in assessing the microvascular characteristics of various tumors, including head and neck cancer. Dynamic contrast-enhanced magnetic resonance imaging allows noninvasive assessment of permeability and blood flow, both important parametric features of tumor hypoxia, which is in turn a marker for treatment resistance for head and neck cancer.In this article we will provide a comprehensive review technique in evaluating tumor proliferation and application of its parameters in differentiating between various tumor types of the oral cavity and how its parameters can correlate between epidermal growth factor receptor and human papillomavirus which can have an implication in patient's overall survival rates.We will also review how the parameters of this method can predict local tumor control after treatment and compare its efficacy with other imaging modalities. Lastly, we will review how its parameters can be used prospectively to identify early complications from treatment.
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13
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Shin DJ, Choi SH, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH, Jo SW, Lee EJ. Application of T1 Map Information Based on Synthetic MRI for Dynamic Contrast-Enhanced Imaging: A Comparison Study with the Fixed Baseline T1 Value Method. Korean J Radiol 2021; 22:1352-1368. [PMID: 33987992 PMCID: PMC8316777 DOI: 10.3348/kjr.2020.1201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/13/2020] [Accepted: 12/31/2020] [Indexed: 11/17/2022] Open
Abstract
Objective For an accurate dynamic contrast-enhanced (DCE) MRI analysis, exact baseline T1 mapping is critical. The purpose of this study was to compare the pharmacokinetic parameters of DCE MRI using synthetic MRI with those using fixed baseline T1 values. Materials and Methods This retrospective study included 102 patients who underwent both DCE and synthetic brain MRI. Two methods were set for the baseline T1: one using the fixed value and the other using the T1 map from synthetic MRI. The volume transfer constant (Ktrans), volume of the vascular plasma space (vp), and the volume of the extravascular extracellular space (ve) were compared between the two methods. The interclass correlation coefficients and the Bland-Altman method were used to assess the reliability. Results In normal-appearing frontal white matter (WM), the mean values of Ktrans, ve, and vp were significantly higher in the fixed value method than in the T1 map method. In the normal-appearing occipital WM, the mean values of ve and vp were significantly higher in the fixed value method. In the putamen and head of the caudate nucleus, the mean values of Ktrans, ve, and vp were significantly lower in the fixed value method. In addition, the T1 map method showed comparable interobserver agreements with the fixed baseline T1 value method. Conclusion The T1 map method using synthetic MRI may be useful for reflecting individual differences and reliable measurements in clinical applications of DCE MRI.
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Affiliation(s)
- Dong Jae Shin
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.,Center for Nanoparticle Research, Institute for Basic Science, Seoul, Korea.,School of Chemical and Biological Engineering, Seoul National University, Seoul, Korea.
| | - Roh Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Ji Hoon Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Chul Ho Sohn
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Sang Won Jo
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea
| | - Eun Jung Lee
- Department of Radiology, Human Medical Imaging & Intervention Center, Seoul, Korea
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14
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Crombé A, Fadli D, Buy X, Italiano A, Saut O, Kind M. High-Grade Soft-Tissue Sarcomas: Can Optimizing Dynamic Contrast-Enhanced MRI Postprocessing Improve Prognostic Radiomics Models? J Magn Reson Imaging 2020; 52:282-297. [PMID: 31922323 DOI: 10.1002/jmri.27040] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 12/07/2019] [Accepted: 12/11/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Heterogeneity on pretreatment dynamic contrast-enhanced (DCE)-MRI of sarcomas may be prognostic, but the best technique to capture this characteristic remains unknown. PURPOSE To investigate the best method to extract prognostic data from baseline DCE-MRI. STUDY TYPE Retrospective, single-center. POPULATION Fifty consecutive uniformly-treated adults with nonmetastatic high-grade sarcomas. FIELD STRENGTH/SEQUENCE 1.5T; T2 -weighted-imaging, fat-suppressed fast spoiled gradient echo DCE-MRI. ASSESSMENT Ninety-two radiomics features (RFs) were extracted at each DCE-MRI phase (11, from t = 0-88 sec). Relative changes in RFs (rRFs) since the acquisition baseline were calculated (11 × 92 rRFs). Curves of rRF as function of time postinjection were integrated (92 integrated-rRFs [irRFs]). Ktrans and area under the time-intensity curve at 88-sec parametric maps were computed and 2 × 92 parametric-RFs (pRFs) were extracted. Five DCE-MRI-based radiomics models were built on: an RFs subset (32 sec, 64 sec, 88 sec); all rRFs; all irRFs; and all pRFs. Two models were elaborated as reference, on: conventional radiological features; and T2 -WI RFs. STATISTICAL TESTS A common machine-learning approach was applied to radiomics models. Features with P < 0.05 at univariate analysis were entered in a LASSO-penalized Cox regression including bootstrapped 10-fold cross-validation. The resulting radiomics scores (RScores) were dichotomized per their median and entered in multivariate Cox models for predicting metastatic relapse-free survival. Models were compared with integrative area under the curve (AUC) and concordance index. RESULTS Only dichotomized RScores from models based on rRFs subset, all rRFS and irRFS correlated with prognostic (P = 0.0107-0.0377). The models including all rRFs and irRFs had the highest c-index (0.83), followed by the radiological model. The radiological model had the highest integrative AUC (0.87), followed by models including all rRFs and irRFs. The radiological and full rRFs models were significantly better than the T2 -based radiomics model (P = 0.02). DATA CONCLUSION The initial DCE-MRI of STS contains prognostic information. It seems more relevant to make predictions on rRFs instead of pRFs. Evidence Level: 3 Technical Efficacy: 3 J. Magn. Reson. Imaging 2020;52:282-297.
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Affiliation(s)
- Amandine Crombé
- Department of Radiology, Institut Bergonie, Bordeaux, France.,Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251 & Université de Bordeaux, Talence, France.,University of Bordeaux, Bordeaux, France
| | - David Fadli
- Department of Radiology, Institut Bergonie, Bordeaux, France
| | - Xavier Buy
- Department of Radiology, Institut Bergonie, Bordeaux, France
| | - Antoine Italiano
- University of Bordeaux, Bordeaux, France.,Department of Medical Oncology, Institut Bergonie, Bordeaux, France
| | - Olivier Saut
- Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251 & Université de Bordeaux, Talence, France.,University of Bordeaux, Bordeaux, France
| | - Michèle Kind
- Department of Radiology, Institut Bergonie, Bordeaux, France
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15
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Ahmed Z, Levesque IR. Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail. Magn Reson Med 2019; 83:286-298. [PMID: 31393033 DOI: 10.1002/mrm.27913] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/18/2019] [Accepted: 06/18/2019] [Indexed: 12/20/2022]
Abstract
PURPOSE Quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) requires an arterial input function (AIF) which is difficult to measure. We propose the reference region and input function tail (RRIFT) approach which uses a reference tissue and the washout portion of the AIF. METHODS RRIFT was evaluated in simulations with 100 parameter combinations at various temporal resolutions (5-30 s) and noise levels (σ = 0.01-0.05 mM). RRIFT was compared against the extended Tofts model (ETM) in 8 studies from patients with glioblastoma multiforme. Two versions of RRIFT were evaluated: one using measured patient-specific AIF tails, and another assuming a literature-based AIF tail. RESULTS RRIFT estimated the transfer constant K trans and interstitial volume v e with median errors within 20% across all simulations. RRIFT was more accurate and precise than the ETM at temporal resolutions slower than 10 s. The percentage error of K trans had a median and interquartile range of -9 ± 45% with the ETM and -2 ± 17% with RRIFT at a temporal resolution of 30 s under noiseless conditions. RRIFT was in excellent agreement with the ETM in vivo, with concordance correlation coefficients (CCC) of 0.95 for K trans , 0.96 for v e , and 0.73 for the plasma volume v p using a measured AIF tail. With the literature-based AIF tail, the CCC was 0.89 for K trans , 0.93 for v e and 0.78 for v p . CONCLUSIONS Quantitative DCE-MRI analysis using the input function tail and a reference tissue yields absolute kinetic parameters with the RRIFT method. This approach was viable in simulation and in vivo for temporal resolutions as low as 30 s.
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Affiliation(s)
- Zaki Ahmed
- Medical Physics Unit, McGill University, Montreal, Canada.,Department of Physics, McGill University, Montreal, Canada
| | - Ives R Levesque
- Medical Physics Unit, McGill University, Montreal, Canada.,Department of Physics, McGill University, Montreal, Canada.,Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada.,Cancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Canada
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16
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Knight SP, Meaney JF, Fagan AJ. DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits. Med Phys 2019; 46:3592-3602. [DOI: 10.1002/mp.13635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 04/30/2019] [Accepted: 05/21/2019] [Indexed: 01/01/2023] Open
Affiliation(s)
- Silvin P. Knight
- School of Medicine Trinity College University of Dublin Dublin Ireland
- National Centre for Advanced Medical Imaging (CAMI) St James's Hospital Dublin Ireland
| | - James F. Meaney
- School of Medicine Trinity College University of Dublin Dublin Ireland
- National Centre for Advanced Medical Imaging (CAMI) St James's Hospital Dublin Ireland
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17
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Artzi M, Liberman G, Blumenthal DT, Bokstein F, Aizenstein O, Ben Bashat D. Repeatability of dynamic contrast enhanced v p parameter in healthy subjects and patients with brain tumors. J Neurooncol 2018; 140:727-737. [PMID: 30392091 DOI: 10.1007/s11060-018-03006-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Accepted: 09/20/2018] [Indexed: 12/12/2022]
Abstract
PURPOSE To study the repeatability of plasma volume (vp) extracted from dynamic-contrast-enhanced (DCE) MRI in order to define threshold values for significant longitudinal changes, and to assess changes in patients with high-grade-glioma (HGG). METHODS Twenty eight healthy subjects, of which eleven scanned twice, were used to assess the repeatability of vp within the normal-appearing brain tissue and to define threshold values for significant changes based on least-detected-differences (LDD) of mean vp values and histogram comparisons using earth-mover's-distance (EMD). Sixteen patients with HGG were scanned longitudinally with eight patients scanned before and following bevacizumab therapy. Longitudinal changes were assessed based on defined threshold values in comparison to RANO criteria. RESULTS The threshold values for significant changes were: LDD = 0.0024 (ml/100 ml, 21%) for mean vp and EMD = 4.14. In patients, in 20/24 comparisons, no significant longitudinal changes were detected for vp within the normal-appearing brain tissue. Concurring results were obtained between changes in lesion volume (RANO criteria) and LDD or EMD values in cases diagnosed with progressive-disease, yet in about 50% of cases diagnosed with partial-response preliminary results demonstrated significant increase in vp despite significant reductions in lesion volume. In two patients, these changes preceded progression detected at follow-up scans. In general, a good concordance was obtained between LDD and EMD. CONCLUSION This study shows high repeatability of vp and provides threshold values for significant changes in longitudinal assessment of patients with brain tumors. Preliminary results suggest the use of vp-DCE parameter to improve assessment of therapy response in patients with high-grade-glioma.
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Affiliation(s)
- Moran Artzi
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gilad Liberman
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel
| | - Deborah T Blumenthal
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Felix Bokstein
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Orna Aizenstein
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Dafna Ben Bashat
- Sagol Brain Institute, 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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18
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Kim C, Suh JY, Heo C, Lee CK, Shim WH, Park BW, Cho G, Lee DW, Woo DC, Kim SY, Kim YJ, Bae DJ, Kim JK. Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters. Cancer Med 2018; 7:3921-3934. [PMID: 29983002 PMCID: PMC6089152 DOI: 10.1002/cam4.1624] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 05/28/2018] [Accepted: 05/29/2018] [Indexed: 12/15/2022] Open
Abstract
Tumor heterogeneity is an important concept when assessing intratumoral variety in vascular phenotypes and responses to antiangiogenic treatment. This study explored spatiotemporal heterogeneity of vascular alterations in C6 glioma mice during tumor growth and antiangiogenic treatment on serial MR examinations (days 0, 4, and 7 from initiation of vehicle or multireceptor tyrosine kinase inhibitor administration). Transvascular permeability (TP) was quantified on dynamic‐contrast‐enhanced MRI (DCE‐MRI) using extravascular extracellular agent (Gd‐DOTA); blood volume (BV) was estimated using intravascular T2 agent (SPION). With regard to region‐dependent variability in vascular phenotypes, the control group demonstrated higher TP in the tumor center than in the periphery, and greater BV in the tumor periphery than in the center. This distribution pattern became more apparent with tumor growth. Antiangiogenic treatment effect was regionally heterogeneous: in the tumor center, treatment significantly suppressed the increase in TP and decrease in BV (ie, typical temporal change in the control group); in the tumor periphery, treatment‐induced vascular alterations were insignificant and BV remained high. On histopathological examination, the control group showed greater CD31, VEGFR2, Ki67, and NG2 expression in the tumor periphery than in the center. After treatment, CD31 and Ki67 expression was significantly suppressed only in the tumor center, whereas VEGFR2 and α‐caspase 3 expression was decreased and NG2 expression was increased in the entire tumor. These results demonstrate that MRI can reliably depict spatial heterogeneity in tumor vascular phenotypes and antiangiogenic treatment effects. Preserved angiogenic activity (high BV on MRI and high CD31) and proliferation (high Ki67) in the tumor periphery after treatment may provide insights into the mechanism of tumor resistance to antiangiogenic treatment.
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Affiliation(s)
- Cherry Kim
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Ji-Yeon Suh
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Changhoe Heo
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Chang Kyung Lee
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Woo Hyun Shim
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.,Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Bum Woo Park
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Gyunggoo Cho
- Bio-imaging Research Team, Korea Basic Science Institute, Chungbuk, South Korea
| | - Do-Wan Lee
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Dong-Cheol Woo
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | - Sang-Yeob Kim
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea.,Department of Convergence Medicine, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Korea
| | - Yun Jae Kim
- Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
| | | | - Jeong Kon Kim
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.,Asan Institute for Life Sciences, University of Ulsan College of Medicine, Seoul, South Korea
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19
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Lecler A, Fournier L, Diard-Detoeuf C, Balvay D. Blood-Brain Barrier Leakage in Early Alzheimer Disease. Radiology 2018; 282:923-925. [PMID: 28218884 DOI: 10.1148/radiol.2017162578] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Augustin Lecler
- Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019 Paris, France
| | - Laure Fournier
- Cardiovascular Research Center-PARCC, Université Paris Descartes Sorbonne Paris Cité, UMR-S970, Paris, France †.,Department of Radiology, Université Paris Descartes Sorbonne Paris Cité, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Paris, France ‡
| | | | - Daniel Balvay
- Cardiovascular Research Center-PARCC, Université Paris Descartes Sorbonne Paris Cité, UMR-S970, Paris, France †
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20
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Kabadi SJ, Fatterpekar GM, Anzai Y, Mogen J, Hagiwara M, Patel SH. Dynamic Contrast-Enhanced MR Imaging in Head and Neck Cancer. Magn Reson Imaging Clin N Am 2018; 26:135-149. [DOI: 10.1016/j.mric.2017.08.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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21
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Fan WX, Chen XF, Cheng FY, Cheng YB, Xu T, Zhu WB, Zhu XL, Li GJ, Li S. Retrospective analysis of the utility of multiparametric MRI for differentiating between benign and malignant breast lesions in women in China. Medicine (Baltimore) 2018; 97:e9666. [PMID: 29369183 PMCID: PMC5794367 DOI: 10.1097/md.0000000000009666] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
We explored the utility of time-resolved angiography with interleaved stochastic trajectories dynamic contrast-enhanced magnetic resonance imaging (TWIST DCE-MRI), readout segmentation of long variable echo-trains diffusion-weighted magnetic resonance imaging- diffusion-weighted magnetic resonance imaging (RESOLVE-DWI), and echo-planar imaging- diffusion-weighted magnetic resonance imaging (EPI-DWI) for distinguishing between malignant and benign breast lesions.This retrospective analysis included female patients with breast lesions seen at a single center in China between January 2016 and April 2016. Patients were allocated to a benign or malignant group based on pathologic diagnosis. All patients received routine MRI, RESOLVE-DWI, EPI-DWI, and TWIST DCE-T1WI. Variables measured included quantitative parameters (K, Kep, and Ve), semiquantitative parameters (rate of contrast enhancement for contrast agent inflow [W-in], rate of contrast decay for contrast agent outflow [W-out], and time-to-peak enhancement after contrast agent injection [TTP]) and apparent diffusion coefficient (ADC) values for RESOLVE-DWI (ADCr) and EPI-DWI (ADCe). Receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic utility of each parameter for differentiating malignant from benign breast lesions.A total of 87 patients were included (benign, n = 20; malignant, n = 67). Compared with the benign group, the malignant group had significantly higher K, Kep and W-in and significantly lower W-out, TTP, ADCe, and ADCr (all P < .05); Ve was not significantly different between groups. RESOLVE-DWI was superior to conventional EPI-DWI at illustrating lesion boundary and morphology, while ADCr was significantly lower than ADCe in all patients. Kep, W-out, ADCr, and ADCe showed the highest diagnostic efficiency (based on AUC value) for differentiating between benign and malignant lesions. Combining 3 parameters (Kep, W-out, and ADCr) had a higher diagnostic efficiency (AUC, 0.965) than any individual parameter and distinguished between benign and malignant lesions with high sensitivity (91.0%), specificity (95.0%), and accuracy (91.9%).An index combining Kep, W-out, and ADCr could potentially be used for the differential diagnosis of breast lesions.
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Affiliation(s)
| | | | | | | | - Tai Xu
- Department of Breast Surgery
| | - Wen Biao Zhu
- Department of Pathology, Meizhou People's Hospital, Guangdong Province
| | - Xiao Lei Zhu
- Siemens Healthcare NEA DI MR Application, Guangzhou, China
| | - Gui Jin Li
- Siemens Healthcare NEA DI MR Application, Guangzhou, China
| | - Shuai Li
- Siemens Healthcare NEA DI MR Application, Guangzhou, China
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22
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Sun CY, Walker CM, Michel KA, Venkatesan AM, Lai SY, Bankson JA. Influence of parameter accuracy on pharmacokinetic analysis of hyperpolarized pyruvate. Magn Reson Med 2017; 79:3239-3248. [PMID: 29090487 DOI: 10.1002/mrm.26992] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2017] [Revised: 09/22/2017] [Accepted: 10/10/2017] [Indexed: 01/15/2023]
Abstract
PURPOSE To explore the effects of noise and error on kinetic analyses of tumor metabolism using hyperpolarized [1-13 C] pyruvate. METHODS Numerical simulations were performed to systematically investigate the effects of noise, the number of unknowns, and error in kinetic parameter estimates on kinetic analysis of the apparent rate of chemical conversion from hyperpolarized pyruvate to lactate (kPL ). A pharmacokinetic model with two physical and two chemical pools of hyperpolarized spins was used to generate and analyze the synthetic data. RESULTS The reproducibility of kPL estimates worsened quickly when peak signal-to-noise ratio for hyperpolarized pyruvate was below approximately 20. The accuracy of kPL estimates was most sensitive to errors in high excitation angles, the vascular blood volume fraction (vb ), and the rate of pyruvate extravasation (kve ), and was least sensitive to errors in the T1 of pyruvate. When vb and/or kve were fit as additional unknowns, the accuracy of kPL estimates suffered, and when the vascular input function of pyruvate was also fit, the reproducibility of kPL estimates worsened. CONCLUSIONS The accuracy and precision of kPL estimates improve substantially for peak signal-to-noise ratio above approximately 20. Accurate estimates of perfusion parameters (combinations of vb , kve , and the pyruvate vascular input function) and transmit calibration at high excitation angles have the greatest effect on the accuracy of kinetic analyses. Magn Reson Med 79:3239-3248, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Chang-Yu Sun
- Department of Imaging Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Christopher M Walker
- Department of Imaging Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Keith A Michel
- Department of Imaging Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Aradhana M Venkatesan
- Department of Diagnostic Radiology, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Stephen Y Lai
- Department of Head & Neck Surgery, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - James A Bankson
- Department of Imaging Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
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23
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Zhang J, Winters K, Reynaud O, Kim SG. Simultaneous measurement of T 1 /B 1 and pharmacokinetic model parameters using active contrast encoding (ACE)-MRI. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3737. [PMID: 28544159 PMCID: PMC5557664 DOI: 10.1002/nbm.3737] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 03/27/2017] [Accepted: 03/28/2017] [Indexed: 05/06/2023]
Abstract
The aim of this study was to assess the feasibility of combining dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) with the measurement of the radiofrequency (RF) transmit field B1 and pre-contrast longitudinal relaxation time T10 . A novel approach has been proposed to simultaneously estimate B1 and T10 from a modified DCE-MRI scan that actively encodes the washout phase of the curve with different amounts of T1 and B1 weighting using multiple flip angles and repetition times, hence referred to as active contrast encoding (ACE)-MRI. ACE-MRI aims to simultaneously measure B1 and T10 , together with contrast kinetic parameters, such as the transfer constant Ktrans , interstitial space volume fraction ve and vascular space volume fraction vp . The proposed method was tested using numerical simulations and in vivo studies with mouse models of breast cancer implanted in the flank and mammary fat pad, and glioma in the brain. In the numerical simulation study with a signal-to-noise ratio of 10, both B1 and T10 were estimated accurately with errors of 5.1 ± 3.5% and 12.3 ± 8.8% and coefficients of variation (CV) of 14.9 ± 8.6% and 15.0 ± 5.0%, respectively. Using the same ACE-MRI data, the kinetic parameters Ktrans , ve and vp were also estimated with errors of 14.2 ± 8.3% (CV = 13.5 ± 4.6%), 14.7 ± 9.9% (CV = 13.3 ± 4.5%) and 14.0 ± 9.3% (CV = 14.0 ± 4.5%), respectively. For the in vivo tumor data from 11 mice, voxel-wise comparisons between ACE-MRI and DCE-MRI methods showed that the mean differences for the five parameters were as follows: ΔKtrans = 0.006 (/min), Δve = 0.016, Δvp = 0.000, ΔB1 = -0.014 and ΔT1 = -0.085 (s), which suggests a good agreement between the two methods. When compared with separately measured B1 and T10 , and DCE-MRI estimated kinetic parameters as a reference, the mean relative errors of ACE-MRI estimation were B1 = -0.3%, T10 = -8.5%, Ktrans = 11.4%, ve = 14.5% and vp = 4.5%. This proof-of-concept study demonstrates that the proposed ACE-MRI method can be used to estimate B1 and T10 , together with contrast kinetic model parameters.
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Affiliation(s)
- Jin Zhang
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Kerryanne Winters
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Olivier Reynaud
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Sungheon Gene Kim
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
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24
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Wang J, Chen H, Sun J, Hippe DS, Zhang H, Yu S, Cai J, Xie L, Cui B, Yuan C, Zhao X, Yuan W, Liu H. Dynamic contrast-enhanced MR imaging of carotid vasa vasorum in relation to coronary and cerebrovascular events. Atherosclerosis 2017. [DOI: 10.1016/j.atherosclerosis.2017.06.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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25
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Lang N, Yuan H, Yu HJ, Su MY. Diagnosis of Spinal Lesions Using Heuristic and Pharmacokinetic Parameters Measured by Dynamic Contrast-Enhanced MRI. Acad Radiol 2017; 24:867-875. [PMID: 28162875 DOI: 10.1016/j.acra.2016.12.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Revised: 12/17/2016] [Accepted: 12/17/2016] [Indexed: 02/03/2023]
Abstract
RATIONALE AND OBJECTIVES This study aimed to evaluate the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiation of four spinal lesions by using heuristic and pharmacokinetic parameters analyzed from DCE signal intensity time course. MATERIALS AND METHODS DCE-MRI of 62 subjects with confirmed myeloma (n = 9), metastatic cancer (n = 22), lymphoma (n = 7), and inflammatory tuberculosis (TB) (n = 24) in the spine were analyzed retrospectively. The region of interest was placed on strongly enhanced tissues. The DCE time course was categorized as the "wash-out," "plateau," or "persistent enhancement" pattern. The maximum enhancement, steepest wash-in enhancement, and wash-out slope using the signal intensity at 67 seconds after contrast injection as reference were measured. The Tofts 2-compartmental pharmacokinetic model was applied to obtain Ktrans and kep. Pearson correlation between heuristic and pharmacokinetic parameters was evaluated, and receiver operating characteristic curve analysis was performed for pairwise group differentiation. RESULTS The mean wash-out slope was -22% ± 10% for myeloma, 1% ± 0.4% for metastatic cancer, 3% ± 3% for lymphoma, and 7% ± 10% for TB, and it could significantly distinguish myeloma from metastasis (area under the curve [AUC] = 0.884), lymphoma (AUC = 1.0), and TB (AUC = 1.0) with P = .001, and distinguish metastasis from TB (AUC = 0.741) with P = .005. The kep and wash-out slope were highly correlated (r = 0.92), and they showed a similar diagnostic performance. The Ktrans was significantly correlated with the maximum enhancement (r = 0.71) and the steepest wash-in enhancement (r = 0.85), but they had inferior diagnostic performance compared to the wash-out slope. CONCLUSIONS DCE-MRI may provide additional diagnostic information, and a simple wash-out slope had the best diagnostic performance. The heuristic and pharmacokinetic parameters were highly correlated.
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Affiliation(s)
- Ning Lang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China.
| | - Hon J Yu
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine Hall 164, Irvine, CA 92697-5020
| | - Min-Ying Su
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine Hall 164, Irvine, CA 92697-5020.
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26
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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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27
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Kim JH, Suh JY, Woo DC, Sung YS, Son WC, Choi YS, Pae SJ, Kim JK. Difference in the intratumoral distributions of extracellular-fluid and intravascular MR contrast agents in glioblastoma growth. NMR IN BIOMEDICINE 2016; 29:1688-1699. [PMID: 27723161 DOI: 10.1002/nbm.3591] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Revised: 07/05/2016] [Accepted: 07/06/2016] [Indexed: 06/06/2023]
Abstract
Contrast enhancement by an extracellular-fluid contrast agent (CA) (Gd-DOTA) depends primarily on the blood-brain-barrier permeability (bp), and transverse-relaxation change caused by intravascular T2 CA (superparamagnetic iron oxide nanoparticles, SPIONs) is closely associated with the blood volume (BV). Pharmacokinetic (PK) vascular characterization based on single-CA-using dynamic contrast-enhanced MRI (DCE-MRI) has shown significant measurement variation according to the molecular size of the CA. Based on this recognition, this study used a dual injection of Gd-DOTA and SPIONs for tracing the changes of bp and BV in C6 glioma growth (Days 1 and 7 after the tumor volume reached 2 mL). bp was quantified according to the non-PK parameters of Gd-DOTA-using DCE-MRI (wash-in rate, maximum enhancement ratio and initial area under the enhancement curve (IAUC)). BV was estimated by SPION-induced ΔR2 * and ΔR2 . With validated measurement reliability of all the parameters (coefficients of variation ≤10%), dual-contrast MRI demonstrated a different region-oriented distribution between Gd-DOTA and SPIONs within a tumor as follows: (a) the BV increased stepwise from the tumor center to the periphery; (b) the tumor periphery maintained the augmented BV to support continuous tumor expansion from Day 1 to Day 7; (c) the internal tumor area underwent significant vascular shrinkage (i.e. decreased ΔR2 and ΔR2 ) as the tumor increased in size; (d) the tumor center showed greater bp-indicating parameters, i.e. wash-in rate, maximum enhancement ratio and IAUC, than the periphery on both Days 1 and 7 and (e) the tumor center showed a greater increase of bp than the tumor periphery in tumor growth, as suggested to support tumor viability when there is insufficient blood supply. In the MRI-histologic correlation, a prominent BV increase in the tumor periphery seen in MRI was verified with increased fluorescein isothiocyanate-dextran signals and up-regulated immunoreactivity of CD31-VEGFR. In conclusion, the spatiotemporal alterations of BV and bp in glioblastoma growth, i.e. augmented BV in the tumor periphery and increased bp in the center, can be sufficiently evaluated by MRI with dual injection of extracellular-fluid Gd chelates and intravascular SPION.
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Affiliation(s)
- Jin Hee Kim
- Department of Radiology, Research Institute of Radiology, Bioimaging Infrastructure, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Ji-Yeon Suh
- Department of Radiology, Research Institute of Radiology, Bioimaging Infrastructure, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Dong-Cheol Woo
- Department of Radiology, Research Institute of Radiology, Bioimaging Infrastructure, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Yu Sub Sung
- Department of Radiology, Research Institute of Radiology, Bioimaging Infrastructure, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Woo-Chan Son
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Yoon Seok Choi
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Sang Joon Pae
- Department of Surgery, National Health Insurance Service, Ilsan, South Korea
| | - Jeong Kon Kim
- Department of Radiology, Research Institute of Radiology, Bioimaging Infrastructure, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
- Center for Bioimaging of New Drug Development, Asan Institute for life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
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28
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Spanakis M, Kontopodis E, Van Cauter S, Sakkalis V, Marias K. Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA. J Pharmacokinet Pharmacodyn 2016; 43:529-47. [PMID: 27647272 DOI: 10.1007/s10928-016-9493-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 09/07/2016] [Indexed: 12/16/2022]
Abstract
Dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) is used for detailed characterization of pathology of lesions sites, such as brain tumors, by quantitative analysis of tracer's data through the use of pharmacokinetic (PK) models. A key component for PK models in DCE-MRI is the estimation of the concentration-time profile of the tracer in a nearby vessel, referred as Arterial Input Function (AIF). The aim of this work was to assess through full body physiologically-based pharmacokinetic (PBPK) model approaches the PK profile of gadoteric acid (Gd-DOTA) and explore potential application for parameter estimation in DCE-MRI based on PBPK-derived AIFs. The PBPK simulations were generated through Simcyp(®) platform and the predicted PK parameters for Gd-DOTA were compared with available clinical data regarding healthy volunteers and renal impairment patients. The assessment of DCE-MRI parameters was implemented by utilizing similar virtual profiles based on gender, age and weight to clinical profiles of patients diagnosed with glioblastoma multiforme. The PBPK-derived AIFs were then used to compute DCE-MRI parameters through the Extended Tofts Model and compared with the corresponding ones derived from image-based AIF computation. The comparison involved: (i) image measured AIF of patients vs AIF of in silico profile, and, (ii) population average AIF vs in silico mean AIFs. The results indicate that PBPK-derived AIFs allowed the estimation of comparable imaging biomarkers with those calculated from typical DCE-MRI image analysis. The incorporation of PBPK models and potential utilization of in silico profiles to real patient data, can provide new perspectives in DCE-MRI parameter estimation and data analysis.
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Affiliation(s)
- Marios Spanakis
- Institute of Computer Science, Computational BioMedicine Lab, Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece.
| | - Eleftherios Kontopodis
- Institute of Computer Science, Computational BioMedicine Lab, Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece
| | - Sophie Van Cauter
- Department of Radiology, University Hospitals Leuven, Louvain, Belgium
| | - Vangelis Sakkalis
- Institute of Computer Science, Computational BioMedicine Lab, Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece
| | - Kostas Marias
- Institute of Computer Science, Computational BioMedicine Lab, Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece
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Response to characterization of orbital masses by multiparametric MRI. Eur J Radiol 2016; 85:1686-7. [PMID: 27397419 DOI: 10.1016/j.ejrad.2016.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Accepted: 06/22/2016] [Indexed: 11/24/2022]
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Turco S, Wijkstra H, Mischi M. Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review. IEEE Rev Biomed Eng 2016; 9:121-47. [PMID: 27337725 DOI: 10.1109/rbme.2016.2583541] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.
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Mills SJ, du Plessis D, Pal P, Thompson G, Buonacorrsi G, Soh C, Parker GJM, Jackson A. Mitotic Activity in Glioblastoma Correlates with Estimated Extravascular Extracellular Space Derived from Dynamic Contrast-Enhanced MR Imaging. AJNR Am J Neuroradiol 2016; 37:811-7. [PMID: 26705318 PMCID: PMC4817231 DOI: 10.3174/ajnr.a4623] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 10/06/2015] [Indexed: 01/02/2023]
Abstract
BACKGROUND AND PURPOSE A number of parameters derived from dynamic contrast-enhanced MR imaging and separate histologic features have been identified as potential prognosticators in high-grade glioma. This study evaluated the relationships between dynamic contrast-enhanced MRI-derived parameters and histologic features in glioblastoma multiforme. MATERIALS AND METHODS Twenty-eight patients with newly presenting glioblastoma multiforme underwent preoperative imaging (conventional imaging and T1 dynamic contrast-enhanced MRI). Parametric maps of the initial area under the contrast agent concentration curve, contrast transfer coefficient, estimate of volume of the extravascular extracellular space, and estimate of blood plasma volume were generated, and the enhancing fraction was calculated. Surgical specimens were used to assess subtype and were graded (World Health Organization classification system) and were assessed for necrosis, cell density, cellular atypia, mitotic activity, and overall vascularity scores. Quantitative assessment of endothelial surface area, vascular surface area, and a vascular profile count were made by using CD34 immunostaining. The relationships between MR imaging parameters and histopathologic features were examined. RESULTS High values of contrast transfer coefficient were associated with the presence of frank necrosis (P = .005). High values of the estimate of volume of the extravascular extracellular space were associated with a fibrillary histologic pattern (P < .01) and with increased mitotic activity (P < .05). No relationship was found between mitotic activity and histologic pattern, suggesting that the correlation between the estimate of volume of the extravascular extracellular space and mitotic activity was independent of the histologic pattern. CONCLUSIONS A correlation between the estimate of volume of the extravascular extracellular space and mitotic activity is reported. Further work is warranted to establish how dynamic contrast-enhanced MRI parameters relate to more quantitative histologic measurements, including markers of proliferation and measures of vascular endothelial growth factor expression.
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Affiliation(s)
- S J Mills
- From the Departments of Neuroradiology (S.J.M., G.T., C.S., A.J.) Imaging Science and Biomedical Engineering (S.J.M., G.T., G.B., G.J.M.P., A.J.), University of Manchester, Manchester, UK.
| | - D du Plessis
- Neuropathology (D.d.P., P.P.), Salford National Health Service Foundation Trust, Salford, UK
| | - P Pal
- Neuropathology (D.d.P., P.P.), Salford National Health Service Foundation Trust, Salford, UK
| | - G Thompson
- From the Departments of Neuroradiology (S.J.M., G.T., C.S., A.J.) Imaging Science and Biomedical Engineering (S.J.M., G.T., G.B., G.J.M.P., A.J.), University of Manchester, Manchester, UK
| | - G Buonacorrsi
- Imaging Science and Biomedical Engineering (S.J.M., G.T., G.B., G.J.M.P., A.J.), University of Manchester, Manchester, UK
| | - C Soh
- From the Departments of Neuroradiology (S.J.M., G.T., C.S., A.J.)
| | - G J M Parker
- Imaging Science and Biomedical Engineering (S.J.M., G.T., G.B., G.J.M.P., A.J.), University of Manchester, Manchester, UK
| | - A Jackson
- From the Departments of Neuroradiology (S.J.M., G.T., C.S., A.J.) Imaging Science and Biomedical Engineering (S.J.M., G.T., G.B., G.J.M.P., A.J.), University of Manchester, Manchester, UK
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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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Simonis FF, Sbrizzi A, Beld E, Lagendijk JJ, van den Berg CA. Improving the arterial input function in dynamic contrast enhanced MRI by fitting the signal in the complex plane. Magn Reson Med 2015; 76:1236-45. [DOI: 10.1002/mrm.26023] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 09/29/2015] [Accepted: 09/30/2015] [Indexed: 01/14/2023]
Affiliation(s)
- Frank F.J. Simonis
- Department of Radiotherapy; Imaging Division, University Medical Center Utrecht; Utrecht the Netherlands
| | - Alessandro Sbrizzi
- Department of Radiology; University Medical Center Utrecht; Utrecht the Netherlands
| | - Ellis Beld
- Department of Radiotherapy; Imaging Division, University Medical Center Utrecht; Utrecht the Netherlands
| | - Jan J.W. Lagendijk
- Department of Radiotherapy; Imaging Division, University Medical Center Utrecht; Utrecht the Netherlands
| | - Cornelis A.T. van den Berg
- Department of Radiotherapy; Imaging Division, University Medical Center Utrecht; Utrecht the Netherlands
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Gaddikeri S, Gaddikeri RS, Tailor T, Anzai Y. Dynamic Contrast-Enhanced MR Imaging in Head and Neck Cancer: Techniques and Clinical Applications. AJNR Am J Neuroradiol 2015; 37:588-95. [PMID: 26427839 DOI: 10.3174/ajnr.a4458] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
In the past decade, dynamic contrast-enhanced MR imaging has had an increasing role in assessing the microvascular characteristics of various tumors, including head and neck cancer. Dynamic contrast-enhanced MR imaging allows noninvasive assessment of permeability and blood flow, both important features of tumor hypoxia, which is a marker for treatment resistance for head and neck cancer. Dynamic contrast-enhanced MR imaging has the potential to identify early locoregional recurrence, differentiate metastatic lymph nodes from normal nodes, and predict tumor response to treatment and treatment monitoring in patients with head and neck cancer. Quantitative analysis is in its early stage and standardization and refinement of technique are essential. In this article, we review the techniques of dynamic contrast-enhanced MR imaging data acquisition, analytic methods, current limitations, and clinical applications in head and neck cancer.
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Affiliation(s)
- S Gaddikeri
- From the Department of Radiology (S.G., T.T., Y.A.), University of Washington Medical Center, Seattle, Washington
| | - R S Gaddikeri
- Department of Neuroradiology (R.S.G.), Rush University, Chicago, Illinois
| | - T Tailor
- From the Department of Radiology (S.G., T.T., Y.A.), University of Washington Medical Center, Seattle, Washington
| | - Y Anzai
- From the Department of Radiology (S.G., T.T., Y.A.), University of Washington Medical Center, Seattle, Washington Department of Radiology (Y.A.), University of Utah Health Care, Salt Lake City, Utah.
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Fennessy FM, Fedorov A, Penzkofer T, Kim KW, Hirsch MS, Vangel MG, Masry P, Flood TA, Chang MC, Tempany CM, Mulkern RV, Gupta SN. Quantitative pharmacokinetic analysis of prostate cancer DCE-MRI at 3T: comparison of two arterial input functions on cancer detection with digitized whole mount histopathological validation. Magn Reson Imaging 2015; 33:886-94. [PMID: 25683515 PMCID: PMC4465997 DOI: 10.1016/j.mri.2015.02.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Revised: 02/04/2015] [Accepted: 02/08/2015] [Indexed: 12/28/2022]
Abstract
Accurate pharmacokinetic (PK) modeling of dynamic contrast enhanced MRI (DCE-MRI) in prostate cancer (PCa) requires knowledge of the concentration time course of the contrast agent in the feeding vasculature, the so-called arterial input function (AIF). The purpose of this study was to compare AIF choice in differentiating peripheral zone PCa from non-neoplastic prostatic tissue (NNPT), using PK analysis of high temporal resolution prostate DCE-MRI data and whole-mount pathology (WMP) validation. This prospective study was performed in 30 patients who underwent multiparametric endorectal prostate MRI at 3.0T and WMP validation. PCa foci were annotated on WMP slides and MR images using 3D Slicer. Foci ≥0.5cm(3) were contoured as tumor regions of interest (TROIs) on subtraction DCE (early-arterial - pre-contrast) images. PK analyses of TROI and NNPT data were performed using automatic AIF (aAIF) and model AIF (mAIF) methods. A paired t-test compared mean and 90th percentile (p90) PK parameters obtained with the two AIF approaches. Receiver operating characteristic (ROC) analysis determined diagnostic accuracy (DA) of PK parameters. Logistic regression determined correlation between PK parameters and histopathology. Mean TROI and NNPT PK parameters were higher using aAIF vs. mAIF (p<0.05). There was no significant difference in DA between AIF methods: highest for p90 volume transfer constant (K(trans)) (aAIF differences in the area under the ROC curve (Az) = 0.827; mAIF Az=0.93). Tumor cell density correlated with aAIF K(trans) (p=0.03). Our results indicate that DCE-MRI using both AIF methods is excellent in discriminating PCa from NNPT. If quantitative DCE-MRI is to be used as a biomarker in PCa, the same AIF method should be used consistently throughout the study.
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Affiliation(s)
- Fiona M Fennessy
- Department of Radiology, Brigham and Women's Hospital, Boston MA 02115; Department of Radiology, Dana Farber Cancer Institute, Boston MA 02115.
| | - Andriy Fedorov
- Department of Radiology, Brigham and Women's Hospital, Boston MA 02115
| | - Tobias Penzkofer
- Department of Radiology, Brigham and Women's Hospital, Boston MA 02115; Department of Radiology, RWTH Aachen University Hospital, Aachen, Germany
| | - Kyung Won Kim
- Department of Radiology, Dana Farber Cancer Institute, Boston MA 02115
| | - Michelle S Hirsch
- Department of Pathology, Brigham and Women's Hospital, Boston MA, 02115
| | - Mark G Vangel
- Department of Radiology, Massachusetts General Hospital, Boston MA 02114
| | - Paul Masry
- Department of Pathology, Brigham and Women's Hospital, Boston MA, 02115
| | - Trevor A Flood
- Department of Pathology, Brigham and Women's Hospital, Boston MA, 02115
| | | | - Clare M Tempany
- Department of Radiology, Brigham and Women's Hospital, Boston MA 02115
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Azahaf M, Haberley M, Betrouni N, Ernst O, Behal H, Duhamel A, Ouzzane A, Puech P. Impact of arterial input function selection on the accuracy of dynamic contrast-enhanced MRI quantitative analysis for the diagnosis of clinically significant prostate cancer. J Magn Reson Imaging 2015; 43:737-49. [DOI: 10.1002/jmri.25034] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 08/06/2015] [Indexed: 01/06/2023] Open
Affiliation(s)
- Mustapha Azahaf
- Department of Gastrointestinal Imaging; CHU Lille, Université de Lille; Lille France
- INSERM, U1189, CHU Lille, Université de Lille; Lille France
| | - Marc Haberley
- Department of Gastrointestinal Imaging; CHU Lille, Université de Lille; Lille France
| | - Nacim Betrouni
- INSERM, U1189, CHU Lille, Université de Lille; Lille France
| | - Olivier Ernst
- Department of Gastrointestinal Imaging; CHU Lille, Université de Lille; Lille France
- INSERM, U1189, CHU Lille, Université de Lille; Lille France
| | - Hélène Behal
- Methodolgy and Biostatistics Units, EA2964, UDSL2, CHU Lille, Université de Lille; Lille France
| | - Alain Duhamel
- Methodolgy and Biostatistics Units, EA2964, UDSL2, CHU Lille, Université de Lille; Lille France
| | - Adil Ouzzane
- INSERM, U1189, CHU Lille, Université de Lille; Lille France
- Department of Urology; CHU Lille, Université de Lille; Lille France
| | - Philippe Puech
- INSERM, U1189, CHU Lille, Université de Lille; Lille France
- Department of Genitourinary Imaging; CHU Lille, Université de Lille; Lille France
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Rukat T, Walker-Samuel S, Reinsberg SA. Dynamic contrast-enhanced MRI in mice: an investigation of model parameter uncertainties. Magn Reson Med 2015; 73:1979-87. [PMID: 25052296 DOI: 10.1002/mrm.25319] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2014] [Revised: 05/13/2014] [Accepted: 05/23/2014] [Indexed: 11/08/2022]
Abstract
PURPOSE To establish the experimental factors that dominate the uncertainty of hemodynamic parameters in commonly used pharmacokinetic models. METHODS By fitting simulation results from a multiregion tissue exchange model (Multiple path, Multiple tracer, Indicator Dilution, 4 region), the precision and accuracy of hemodynamic parameters in dynamic contrast-enhanced MRI with four tracer kinetic models is investigated. The impact of various injection rates as well as imprecise knowledge of the arterial input functions is examined. RESULTS Fast injections are beneficial for K(trans) precision within the extended Tofts model and within the two-compartment exchange model but do not affect the other models under investigation. Biases from errors in the arterial input functions are mostly consistent in size and direction for the simple and the extended Tofts model, while they are hardly predictable for the other models. Errors in the hematocrit introduce the greatest loss in parameter accuracy, amounting to an average K(trans) bias of 40% for a 30% overestimation throughout all models. CONCLUSION This simulation study allows the detailed inspection of the isolated impact from various experimental conditions on parameter uncertainty. Because parameter uncertainty comparable to human studies was found, this study represents a validation of preclinical dynamic contrast-enhanced MRI for modeling human tumor physiology.
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Affiliation(s)
- Tammo Rukat
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada; Department of Physics, Humboldt University, Berlin, Germany
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DCE-MRI of the liver: reconstruction of the arterial input function using a low dose pre-bolus contrast injection. PLoS One 2014; 9:e115667. [PMID: 25546176 PMCID: PMC4278725 DOI: 10.1371/journal.pone.0115667] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Accepted: 11/26/2014] [Indexed: 11/26/2022] Open
Abstract
Purpose To assess the quality of the arterial input function (AIF) reconstructed using a dedicated pre-bolus low-dose contrast material injection imaged with a high temporal resolution and the resulting estimated liver perfusion parameters. Materials and Methods In this IRB–approved prospective study, 24 DCE-MRI examinations were performed in 21 patients with liver disease (M/F 17/4, mean age 56 y). The examination consisted of 1.3 mL and 0.05 mmol/kg of gadobenate dimeglumine for pre-bolus and main bolus acquisitions, respectively. The concentration-curve of the abdominal aorta in the pre-bolus acquisition was used to reconstruct the AIF. AIF quality and shape parameters obtained with pre-bolus and main bolus acquisitions and the resulting estimated hepatic perfusion parameters obtained with a dual-input single compartment model were compared between the 2 methods. Test–retest reproducibility of perfusion parameters were assessed in three patients. Results The quality of the pre-bolus AIF curve was significantly better than that of main bolus AIF. Shape parameters peak concentration, area under the time activity curve of gadolinium contrast at 60 s and upslope of pre-bolus AIF were all significantly higher, while full width at half maximum was significantly lower than shape parameters of main bolus AIF. Improved liver perfusion parameter reproducibility was observed using pre-bolus acquisition [coefficient of variation (CV) of 4.2%–38.7% for pre-bolus vs. 12.1–71.4% for main bolus] with the exception of distribution volume (CV of 23.6% for pre-bolus vs. 15.8% for main bolus). The CVs between pre-bolus and main bolus for the perfusion parameters were lower than 14%. Conclusion The AIF reconstructed with pre-bolus low dose contrast injection displays better quality and shape parameters and enables improved liver perfusion parameter reproducibility, although the resulting liver perfusion parameters demonstrated no clinically significant differences between pre-bolus and main bolus acquisitions.
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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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Onxley JD, Yoo DS, Muradyan N, MacFall JR, Brizel DM, Craciunescu OI. Comprehensive population-averaged arterial input function for dynamic contrast-enhanced vmagnetic resonance imaging of head and neck cancer. Int J Radiat Oncol Biol Phys 2014; 89:658-65. [PMID: 24929169 DOI: 10.1016/j.ijrobp.2014.03.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2013] [Revised: 02/13/2014] [Accepted: 03/06/2014] [Indexed: 11/19/2022]
Abstract
PURPOSE To generate a population-averaged arterial input function (PA-AIF) for quantitative analysis of dynamic contrast-enhanced MRI data in head and neck cancer patients. METHODS AND MATERIALS Twenty patients underwent dynamic contrast-enhanced MRI during concurrent chemoradiation therapy. Imaging consisted of 2 baseline scans 1 week apart (B1/B2) and 1 scan after 1 week of chemoradiation therapy (Wk1). Regions of interest (ROIs) in the right and left carotid arteries were drawn on coronal images. Plasma concentration curves of all ROIs were averaged and fit to a biexponential decay function to obtain the final PA-AIF (AvgAll). Right-sided and left-sided ROI plasma concentration curves were averaged separately to obtain side-specific AIFs (AvgRight/AvgLeft). Regions of interest were divided by time point to obtain time-point-specific AIFs (AvgB1/AvgB2/AvgWk1). The vascular transfer constant (Ktrans) and the fractional extravascular, extracellular space volume (Ve) for primaries and nodes were calculated using the AvgAll AIF, the appropriate side-specific AIF, and the appropriate time-point-specific AIF. Median Ktrans and Ve values derived from AvgAll were compared with those obtained from the side-specific and time-point-specific AIFs. The effect of using individual AIFs was also investigated. RESULTS The plasma parameters for AvgAll were a1,2 = 27.11/17.65 kg/L, m1,2 = 11.75/0.21 min(-1). The coefficients of repeatability (CRs) for AvgAll versus AvgLeft were 0.04 min(-1) for Ktrans and 0.02 for Ve. For AvgAll versus AvgRight, the CRs were 0.08 min(-1) for Ktrans and 0.02 for Ve. When AvgAll was compared with AvgB1/AvgB2/AvgWk1, the CRs were slightly higher: 0.32/0.19/0.78 min(-1), respectively, for Ktrans; and 0.07/0.08/0.09 for Ve. Use of a PA-AIF was not significantly different from use of individual AIFs. CONCLUSION A PA-AIF for head and neck cancer was generated that accounts for differences in right carotid artery versus left carotid artery, day-to-day fluctuations, and early treatment-induced changes. The small CRs obtained for Ktrans and Ve indicate that side-specific AIFs are not necessary. However, a time-point-specific AIF may improve pharmacokinetic accuracy.
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Affiliation(s)
- Jennifer D Onxley
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - David S Yoo
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | | | - James R MacFall
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
| | - David M Brizel
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina; Department of Surgery, Duke University Medical Center, Durham, North Carolina
| | - Oana I Craciunescu
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina.
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Gill AB, Black RT, Bowden DJ, Priest AN, Graves MJ, Lomas DJ. An investigation into the effects of temporal resolution on hepatic dynamic contrast-enhanced MRI in volunteers and in patients with hepatocellular carcinoma. Phys Med Biol 2014; 59:3187-200. [PMID: 24862216 DOI: 10.1088/0031-9155/59/12/3187] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This study investigated the effect of temporal resolution on the dual-input pharmacokinetic (PK) modelling of dynamic contrast-enhanced MRI (DCE-MRI) data from normal volunteer livers and from patients with hepatocellular carcinoma. Eleven volunteers and five patients were examined at 3 T. Two sections, one optimized for the vascular input functions (VIF) and one for the tissue, were imaged within a single heart-beat (HB) using a saturation-recovery fast gradient echo sequence. The data was analysed using a dual-input single-compartment PK model. The VIFs and/or uptake curves were then temporally sub-sampled (at interval ▵t = [2-20] s) before being subject to the same PK analysis. Statistical comparisons of tumour and normal tissue PK parameter values using a 5% significance level gave rise to the same study results when temporally sub-sampling the VIFs to HB < ▵t <4 s. However, sub-sampling to ▵t > 4 s did adversely affect the statistical comparisons. Temporal sub-sampling of just the liver/tumour tissue uptake curves at ▵t ≤ 20 s, whilst using high temporal resolution VIFs, did not substantially affect PK parameter statistical comparisons. In conclusion, there is no practical advantage to be gained from acquiring very high temporal resolution hepatic DCE-MRI data. Instead the high temporal resolution could be usefully traded for increased spatial resolution or SNR.
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Affiliation(s)
- Andrew B Gill
- Department of Radiology, University of Cambridge, Cambridge, UK. Department of Medical Physics, Cambridge University Hospitals, Cambridge, UK
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Nofiele JT, Cheng HLM. Establishment of a lung metastatic breast tumor xenograft model in nude rats. PLoS One 2014; 9:e97950. [PMID: 24835641 PMCID: PMC4024026 DOI: 10.1371/journal.pone.0097950] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 04/26/2014] [Indexed: 12/12/2022] Open
Abstract
Objective Larger animal models provide relevant tumor burden in the development of advanced clinical imaging methods for non-invasive cancer detection and diagnosis, and are especially valuable for studying metastatic disease. Most available experimental models, however, are based on immune-compromised mice. To lay the foundation for studying spontaneous metastasis using non-invasive magnetic resonance imaging (MRI), this study aims to establish a highly metastatic breast cancer xenograft model in nude rats. Materials and Methods A highly metastatic variant of human adenocarcinoma MDA-MB-231 known as LM2 was inoculated into nude rats. Orthotopic and subcutaneous (flank) sites were compared, with half of the orthotopic injections guided by ultrasound imaging. MRI with gadolinium contrast administration was performed weekly beginning on Day 6 and ending on Day 104. Excised tumors were assessed on histology using hematoxylin and eosin and CD34. Fisher's exact test was used to compare successful tumor induction amongst different inoculation methods. Results Primary LM2 tumors were established orthotopically in all cases under ultrasound-guided injection, and none otherwise (p = 0.0028). Contrast-enhanced MRI revealed rapidly progressing tumors that reached critical size (15 mm diameter) in 2 to 3 weeks after inoculation. MRI and histology findings were consistent: LM2 tumors were characterized by low vascularity confined to the tumor rim and large necrotic cores with increasing interstitial fluid pressure. Conclusions The metastatic LM2 breast tumor model was successfully established in the mammary fat pads of nude rats, using ultrasound needle guidance as a non-invasive alternative to surgery. This platform lays the foundation for future development and application of MRI to study spontaneous metastasis and different stages throughout the metastatic cascade.
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Affiliation(s)
- Joris Tchouala Nofiele
- The Research Institute and Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Hai-Ling Margaret Cheng
- The Research Institute and Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
- The Institute of Biomaterials & Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
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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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Orton MR, Collins DJ, Koh DM, Leach MO. Improved intravoxel incoherent motion analysis of diffusion weighted imaging by data driven Bayesian modeling. Magn Reson Med 2014; 71:411-20. [PMID: 23408505 DOI: 10.1002/mrm.24649] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2012] [Revised: 12/03/2012] [Accepted: 12/27/2012] [Indexed: 11/09/2022]
Abstract
In addition to the diffusion coefficient, fitting the intravoxel incoherent motion model to multiple b-value diffusion-weighted MR data gives pseudo-diffusion measures associated with rapid signal attenuation at low b-values that are of use in the assessment of a number of pathologies. When summary measures are required, such as the average parameter for a region of interest, least-squares based methods give adequate estimation accuracy. However, using least-squares methods for pixel-wise fitting typically gives noisy estimates, especially for the pseudo-diffusion parameters, which limits the applicability of the approach for assessing spatial features and heterogeneity. In this article, a Bayesian approach using a shrinkage prior model is proposed and is shown to substantially reduce estimation uncertainty so that spatial features in the parameters maps are more clearly apparent. The Bayesian approach has no user-defined parameters, so measures of parameter variation (heterogeneity) over regions of interest are determined by the data alone, whereas it is shown that for the least-squares estimates, measures of variation are essentially determined by user-defined constraints on the parameters. Use of a Bayesian shrinkage prior approach is, therefore, recommended for intravoxel incoherent motion modeling.
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Affiliation(s)
- Matthew R Orton
- CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research, Sutton, Surrey, UK
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Mendes J, Parker DL, McNally S, DiBella E, Bolster BD, Treiman GS. Three-dimensional dynamic contrast enhanced imaging of the carotid artery with direct arterial input function measurement. Magn Reson Med 2013; 72:816-22. [PMID: 24375566 DOI: 10.1002/mrm.24993] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2013] [Revised: 09/17/2013] [Accepted: 09/18/2013] [Indexed: 12/26/2022]
Abstract
PURPOSE Kinetic analysis using dynamic contrast enhanced MRI to assess neovascularization of carotid plaque requires images with high spatial and temporal resolution. This work demonstrates a new three-dimensional (3D) dynamic contrast enhanced imaging sequence, which directly measures the arterial input function with high temporal resolution yet maintains the high spatial resolution required to identify areas of increased adventitial neovascularity. THEORY AND METHODS The sequence consists of multiple rapid acquisitions of a saturation prepared dynamic 3D gradient recalled echo (GRE) sequence temporally interleaved with multiple acquisitions of a 2D slice. The saturation recovery time was adjusted to maintain signal linearity with the very different contrast agent concentrations in the 2D slice and 3D volume. The K(trans) maps were obtained from the 3D dynamic contrast measurements while the 2D slice was used to obtain the arterial input function. Calibration and dynamic studies are presented. RESULTS For contrast agent concentrations up to 5 mM, a saturation recovery time for the 2D slice of 20 ms resulted in less than a 10% deviation from the desired linear response of signal intensity with contrast agent concentration. The corresponding saturation recovery time of 83 ms for the 3D volume maintained less than a 10% deviation from the linear response up to contrast agent concentrations of 2 mM while a contrast agent concentration of 5 mM had almost a 30% deviation. There was a significant improvement in signal attenuation (9 ± 3% versus 23 ± 5% at 40 cm/s) when flow compensation was added to the slice select gradients. For patient studies, volume transfer and plasma fraction maps were calculated with data from the proposed sequence. CONCLUSION This work demonstrated a novel sequence for 3D dynamic contrast enhanced imaging with a simultaneously acquired 2D slice that directly measures the arterial input function with high temporal resolution. Acquisition parameters can be adjusted to accommodate the full range of contrast agent concentration values to be encountered and the kinetic parameters obtained were consistent with expected values.
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Affiliation(s)
- Jason Mendes
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah, USA
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Cuenod C, Balvay D. Perfusion and vascular permeability: Basic concepts and measurement in DCE-CT and DCE-MRI. Diagn Interv Imaging 2013; 94:1187-204. [DOI: 10.1016/j.diii.2013.10.010] [Citation(s) in RCA: 138] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Zöllner FG, Schock-Kusch D, Bäcker S, Neudecker S, Gretz N, Schad LR. Simultaneous measurement of kidney function by dynamic contrast enhanced MRI and FITC-sinistrin clearance in rats at 3 tesla: initial results. PLoS One 2013; 8:e79992. [PMID: 24260332 PMCID: PMC3832374 DOI: 10.1371/journal.pone.0079992] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2013] [Accepted: 10/02/2013] [Indexed: 11/19/2022] Open
Abstract
Glomerular filtration rate (GFR) is an essential parameter of kidney function which can be measured by dynamic contrast enhanced magnetic resonance imaging (MRI-GFR) and transcutaneous approaches based on fluorescent tracer molecules (optical-GFR). In an initial study comparing both techniques in separate measurements on the same animal, the correlation of the obtained GFR was poor. The goal of this study was to investigate if a simultaneous measurement was feasible and if thereby, the discrepancies in MRI-GFR and optical-GFR could be reduced. For the experiments healthy and unilateral nephrectomised (UNX) Sprague Dawley (SD) rats were used. The miniaturized fluorescent sensor was fixed on the depilated back of an anesthetized rat. A bolus of 5 mg/100 g b.w. of FITC-sinistrin was intravenously injected. For dynamic contrast enhanced perfusion imaging (DCE-MRI) a 3D time-resolved angiography with stochastic trajectories (TWIST) sequence was used. By means of a one compartment model the excretion half-life (t1/2) of FITC-sinistrin was calculated and converted into GFR. GFR from DCE-MRI was calculated by fitting pixel-wise a two compartment renal filtration model. Mean cortical GFR and GFR by FITC-sinistrin were compared by Bland-Altman plots and pair-wise t-test. Results show that a simultaneous GFR measurement using both techniques is feasible. Mean optical-GFR was 4.34 ± 2.22 ml/min (healthy SD rats) and 2.34 ± 0.90 ml/min (UNX rats) whereas MRI-GFR was 2.10 ± 0.64 ml/min (SD rats) and 1.17 ± 0.38 ml/min (UNX rats). Differences between healthy and UNX rats were significant (p<0.05) and almost equal percentage difference (46.1% and 44.3%) in mean GFR were assessed with both techniques. Overall mean optical-GFR values were approximately twice as high compared to MRI-GFR values. However, compared to a previous study, our results showed a higher agreement. In conclusion, the possibility to use the transcutaneous method in MRI may have a huge impact in improving and validating MRI methods for GFR assessment in animal models.
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Affiliation(s)
- Frank G. Zöllner
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- * E-mail:
| | - Daniel Schock-Kusch
- Medical Research Center, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sandra Bäcker
- Medical Research Center, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabine Neudecker
- Medical Research Center, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Norbert Gretz
- Medical Research Center, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lothar R. Schad
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Skinner JT, Yankeelov TE, Peterson TE, Does MD. Comparison of dynamic contrast-enhanced MRI and quantitative SPECT in a rat glioma model. CONTRAST MEDIA & MOLECULAR IMAGING 2013; 7:494-500. [PMID: 22991315 DOI: 10.1002/cmmi.1479] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacokinetic modeling of dynamic contrast-enhanced (DCE) MRI data provides measures of the extracellular-extravascular volume fraction (v(e) ) and the volume transfer constant (K(trans) ) in a given tissue. These parameter estimates may be biased, however, by confounding issues such as contrast agent and tissue water dynamics, or assumptions of vascularization and perfusion made by the commonly used model. In contrast to MRI, radiotracer imaging with SPECT is insensitive to water dynamics. A quantitative dual-isotope SPECT technique was developed to obtain an estimate of v(e) in a rat glioma model for comparison with the corresponding estimates obtained using DCE-MRI with a vascular input function and reference region model. Both DCE-MRI methods produced consistently larger estimates of v(e) in comparison to the SPECT estimates, and several experimental sources were postulated to contribute to these differences.
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Affiliation(s)
- Jack T Skinner
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232-2310, USA
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Eilaghi A, Kassner A, Sitartchouk I, Francis PL, Jakubovic R, Feinstein A, Aviv RI. Normal-appearing white matter permeability distinguishes poor cognitive performance in processing speed and working memory. AJNR Am J Neuroradiol 2013; 34:2119-24. [PMID: 23721894 DOI: 10.3174/ajnr.a3539] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Secondary-progressive MS is characterized by reduced acute inflammation and contrast enhancement but with increased axonal degeneration and cognitive/clinical disability that worsens with advanced disease. Relative recirculation, extracted from DSC is a surrogate measure of BBB integrity. We hypothesized that normal-appearing white matter relative recirculation is reduced in cognitively impaired compared with nonimpaired secondary-progressive MS, reflecting more advanced disease. MATERIALS AND METHODS Cognitive performance was classified as impaired or nonimpaired by use of Minimal Assessment of Cognitive Function In MS test components. Demographic data, brain parenchymal fraction, WM lesion fraction, and weighted mean normal-appearing white matter relative recirculation were compared in cognitively dichotomized groups. Univariate and multivariate logistic regressions were used to study the association between cognitive test results and normal-appearing white matter relative recirculation. RESULTS The mean (SD) age of 36 patients with secondary-progressive MS studied was 55.9 ± 9.3 years; 13 of 36 (36%) patients were male. A highly significant difference between normal-appearing white matter relative recirculation and WM lesion relative recirculation was present for all patients (P < .001). Normal-appearing white matter relative recirculation in impaired patients was significantly lower than in nonimpaired subjects for the Symbol Digit Modalities Test (P = .007), Controlled Word Association Test (P = .008), and Paced Auditory Serial Addition Test (P = .024). The Expanded Disability Status Scale demonstrated an inverse correlation with normal-appearing white matter relative recirculation (r = -0.319, P = .075). After adjustment for confounders, significant normal-appearing white matter relative recirculation reduction persisted for the Symbol Digit Modalities Test (P = .023) and the Paced Auditory Serial Addition Test (P = .047) but not for the Controlled Word Association Test (P = .13) in impaired patients. CONCLUSIONS Significant normal-appearing white matter relative recirculation reduction exists in cognitively impaired patients with secondary-progressive MS, localizing to the domains of processing speed and working memory.
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Mehrabian H, Chopra R, Martel AL. Calculation of intravascular signal in dynamic contrast enhanced-MRI using adaptive complex independent component analysis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2013; 32:699-710. [PMID: 23247848 DOI: 10.1109/tmi.2012.2233747] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Assessing tumor response to therapy is a crucial step in personalized treatments. Pharmacokinetic (PK) modeling provides quantitative information about tumor perfusion and vascular permeability that are associated with prognostic factors. A fundamental step in most PK analyses is calculating the signal that is generated in the tumor vasculature. This signal is usually inseparable from the extravascular extracellular signal. It was shown previously using in vivo and phantom experiments that independent component analysis (ICA) is capable of calculating the intravascular time-intensity curve in dynamic contrast enhanced (DCE)-MRI. A novel adaptive complex independent component analysis (AC-ICA) technique is developed in this study to calculate the intravascular time-intensity curve and separate this signal from the DCE-MR images of tumors. The use of the complex-valued DCE-MRI images rather than the commonly used magnitude images satisfied the fundamental assumption of ICA, i.e., linear mixing of the sources. Using an adaptive cost function in ICA through estimating the probability distribution of the tumor vasculature at each iteration resulted in a more robust and accurate separation algorithm. The AC-ICA algorithm provided a better estimate for the intravascular time-intensity curve than the previous ICA-based method. A simulation study was also developed in this study to realistically simulate DCE-MRI data of a leaky tissue mimicking phantom. The passage of the MR contrast agent through the leaky phantom was modeled with finite element analysis using a diffusion model. Once the distribution of the contrast agent in the imaging field of view was calculated, DCE-MRI data was generated by solving the Bloch equation for each voxel at each time point. The intravascular time-intensity curve calculation results were compared to the previously proposed ICA-based intravascular time-intensity curve calculation method that applied ICA to the magnitude of the DCE-MRI data (Mag-ICA) using both simulated and experimental tissue mimicking phantoms. The AC-ICA demonstrated superior performance compared to the Mag-ICA method. AC-ICA provided more accurate estimate of intravascular time-intensity curve, having smaller error between the calculated and actual intravascular time-intensity curves compared to the Mag-ICA. Furthermore, it showed higher robustness in dealing with datasets with different resolution by providing smaller variation between the results of each datasets and having smaller difference between the intravascular time-intensity curves of various resolutions. Thus, AC-ICA has the potential to be used as the intravascular time-intensity curve calculation method in PK analysis and could lead to more accurate PK analysis for tumors.
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Affiliation(s)
- Hatef Mehrabian
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 2M9 Canada.
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