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Sone JY, Koskimäki J, Girard R. Editorial for "The Consistence of Dynamic-Contrast-Enhanced MRI and Filter-Exchange Imaging in Measuring Water Exchange Across the Blood-Brain Barrier in High-Grade Glioma". J Magn Reson Imaging 2023; 58:1861-1862. [PMID: 37052208 DOI: 10.1002/jmri.28726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 03/09/2023] [Indexed: 04/14/2023] Open
Affiliation(s)
- Je Yeong Sone
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago Medicine and Biological Sciences, Chicago, Illinois, USA
| | - Janne Koskimäki
- Department of Neurosurgery, Division of Clinical Neurosciences, Turku University Hospital and University of Turku, Turku, Finland
- Department of Neurosurgery, Oulu University Hospital, Neurocenter, Oulu, Finland
| | - Romuald Girard
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago Medicine and Biological Sciences, Chicago, Illinois, USA
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Hirschler L, Sollmann N, Schmitz‐Abecassis B, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda K, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Emblem KE, Smits M, Petr J, Hangel G. Advanced MR Techniques for Preoperative Glioma Characterization: Part 1. J Magn Reson Imaging 2023; 57:1655-1675. [PMID: 36866773 PMCID: PMC10946498 DOI: 10.1002/jmri.28662] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/04/2023] Open
Abstract
Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.
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Affiliation(s)
- Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
- Medical Delta FoundationDelftThe Netherlands
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityKrems an der DonauAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - Nazmiye Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Cancer Center AmsterdamAmsterdamThe Netherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenThe Netherlands
- Department of NeurologyHaaglanden Medical CenterThe HagueThe Netherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchLondonUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and PsychotherapyInternational Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes‐Bolyai UniversityCluj‐NapocaRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | - Kathleen Schmainda
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftThe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University Hospital, BrnoBrnoCzech Republic
- Faculty of Medicine, Masaryk UniversityBrnoCzech Republic
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
| | - Marion Smits
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
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Uchida Y, Kan H, Sakurai K, Oishi K, Matsukawa N. Contributions of blood-brain barrier imaging to neurovascular unit pathophysiology of Alzheimer's disease and related dementias. Front Aging Neurosci 2023; 15:1111448. [PMID: 36861122 PMCID: PMC9969807 DOI: 10.3389/fnagi.2023.1111448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
The blood-brain barrier (BBB) plays important roles in the maintenance of brain homeostasis. Its main role includes three kinds of functions: (1) to protect the central nervous system from blood-borne toxins and pathogens; (2) to regulate the exchange of substances between the brain parenchyma and capillaries; and (3) to clear metabolic waste and other neurotoxic compounds from the central nervous system into meningeal lymphatics and systemic circulation. Physiologically, the BBB belongs to the glymphatic system and the intramural periarterial drainage pathway, both of which are involved in clearing interstitial solutes such as β-amyloid proteins. Thus, the BBB is believed to contribute to preventing the onset and progression for Alzheimer's disease. Measurements of BBB function are essential toward a better understanding of Alzheimer's pathophysiology to establish novel imaging biomarkers and open new avenues of interventions for Alzheimer's disease and related dementias. The visualization techniques for capillary, cerebrospinal, and interstitial fluid dynamics around the neurovascular unit in living human brains have been enthusiastically developed. The purpose of this review is to summarize recent BBB imaging developments using advanced magnetic resonance imaging technologies in relation to Alzheimer's disease and related dementias. First, we give an overview of the relationship between Alzheimer's pathophysiology and BBB dysfunction. Second, we provide a brief description about the principles of non-contrast agent-based and contrast agent-based BBB imaging methodologies. Third, we summarize previous studies that have reported the findings of each BBB imaging method in individuals with the Alzheimer's disease continuum. Fourth, we introduce a wide range of Alzheimer's pathophysiology in relation to BBB imaging technologies to advance our understanding of the fluid dynamics around the BBB in both clinical and preclinical settings. Finally, we discuss the challenges of BBB imaging techniques and suggest future directions toward clinically useful imaging biomarkers for Alzheimer's disease and related dementias.
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Affiliation(s)
- Yuto Uchida
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States,*Correspondence: Yuto Uchida, ; Noriyuki Matsukawa,
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Ōbu, Aichi, Japan
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan,*Correspondence: Yuto Uchida, ; Noriyuki Matsukawa,
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Kang KM, Choi SH, Chul-Kee P, Kim TM, Park SH, Lee JH, Lee ST, Hwang I, Yoo RE, Yun TJ, Kim JH, Sohn CH. Differentiation between glioblastoma and primary CNS lymphoma: application of DCE-MRI parameters based on arterial input function obtained from DSC-MRI. Eur Radiol 2021; 31:9098-9109. [PMID: 34003350 DOI: 10.1007/s00330-021-08044-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 04/06/2021] [Accepted: 05/04/2021] [Indexed: 11/24/2022]
Abstract
OBJECTIVE This study aimed to evaluate whether arterial input functions (AIFs) obtained from dynamic susceptibility contrast (DSC)-MRI (AIFDSC) improve the reliability and diagnostic accuracy of dynamic contrast-enhanced (DCE)-derived pharmacokinetic (PK) parameters for differentiating glioblastoma from primary CNS lymphoma (PCNSL) compared with AIFs derived from DCE-MRI (AIFDCE). METHODS This retrospective study included 172 patients with glioblastoma (n = 147) and PCNSL (n = 25). All patients had undergone preoperative DSC- and DCE-MRI. The volume transfer constant (Ktrans), volume of the vascular plasma space (vp), and volume of the extravascular extracellular space (ve) were acquired using AIFDSC and AIFDCE. The relative cerebral blood volume (rCBV) was obtained from DSC-MRI. Intraclass correlation coefficients (ICC) and ROC curves were used to assess the reliability and diagnostic accuracy of individual parameters. RESULTS The mean Ktrans, vp, and ve values revealed better ICCs with AIFDSC than with AIFDCE (Ktrans, 0.911 vs 0.355; vp, 0.766 vs 0.503; ve, 0.758 vs 0.657, respectively). For differentiating all glioblastomas from PCNSL, the mean rCBV (AUC = 0.856) was more accurate than the AIFDSC-driven mean Ktrans, which had the largest AUC (0.711) among the DCE-derived parameters (p = 0.02). However, for glioblastomas with low rCBV (≤ 75th percentile of PCNSL; n = 30), the AIFDSC-driven mean Ktrans and vp were more accurate than rCBV (AUC: Ktrans, 0.807 vs rCBV, 0.515, p = 0.004; vp, 0.715 vs rCBV, p = 0.045). CONCLUSION DCE-derived PK parameters using the AIFDSC showed improved reliability and diagnostic accuracy for differentiating glioblastoma with low rCBV from PCNSL. KEY POINTS • An accurate differential diagnosis of glioblastoma and PCNSL is crucial because of different therapeutic strategies. • In contrast to the rCBV from DSC-MRI, another perfusion imaging technique, the DCE parameters for the differential diagnosis have been limited because of the low reliability of AIFs from DCE-MRI. • When we analyzed DCE-MRI data using AIFs from DSC-MRI (AIFDSC), AIFDSC-driven DCE parameters showed improved reliability and better diagnostic accuracy than rCBV for differentiating glioblastoma with low rCBV from PCNSL.
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Affiliation(s)
- Koung Mi Kang
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea. .,Center for Nanoparticle Research, Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
| | - Park Chul-Kee
- Department of Neurosurgery and Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Min Kim
- Department of Internal Medicine and Cancer Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Joo Ho Lee
- Department of Radiation Oncology and Cancer Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Soon-Tae Lee
- Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
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Kim HS, Kwon SL, Choi SH, Hwang I, Kim TM, Park CK, Park SH, Won JK, Kim IH, Lee ST. Prognostication of anaplastic astrocytoma patients: application of contrast leakage information of dynamic susceptibility contrast-enhanced MRI and dynamic contrast-enhanced MRI. Eur Radiol 2020; 30:2171-2181. [PMID: 31953664 DOI: 10.1007/s00330-019-06598-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 10/13/2019] [Accepted: 11/19/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE To examine the applicability of contrast leakage information from dynamic susceptibility contrast-enhanced (DSC) MRI and dynamic contrast-enhanced (DCE) MRI to determine which one is the most valuable surrogate imaging biomarker for predicting disease progression in anaplastic astrocytoma (AA) patients. MATERIALS AND METHODS This study was approved by the institutional review board (IRB), which waived informed consent. A total of seventy-three AA patients who had undergone preoperative DCE and DSC MRI and received standard treatment, including partial resection or biopsy followed by radiation therapy, were included in this retrospective study. Based on Response Assessment in Neuro-Oncology (RANO), patients were sorted into progression (n = 21) and non-progression (n = 52) groups. Tumor boundaries were defined as high-signal intensity (SI) lesions on fluid-attenuated inversion recovery (FLAIR) imaging, where we analyzed mean pharmacokinetic parameters (Ktrans, Vp, and Ve) from DCE MRI and contrast leakage information (mean extraction fraction (EF)) from DSC MRI. RESULTS Mean Ve and mean EF were significantly higher in patients with progression-free survival (PFS) < 18 months than in those with PFS ≥ 18 months. For distinguishing the group with PFS < 18 months, AUC values were calculated using the mean Ve value (AUC = 0.716). The Kaplan-Meier survival analysis revealed that mean Ve value was significantly correlated with PFS. In Cox proportional-hazards regression, only the mean Ve value was found to be significantly associated with PFS. CONCLUSION We found that the mean Ve value based on high-SI tumor lesions on FLAIR imaging was capable of predicting outcomes of AA patients as a potential surrogate imaging biomarker. KEY POINTS • Mean Ve(2.152 ± 1.857 vs. 1.173 ± 1.408) was significantly higher in anaplastic astrocytoma patients with PFS < 18 months that in those with PFS ≥ 18 months (p = 0.02). • Cox proportional-hazards regression showed that only mean Ve(p = 0.034) was significantly associated with PFS, regardless of IDH mutation status, in anaplastic astrocytoma patients.
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Affiliation(s)
- Hee Soo Kim
- College of Medicine, Seoul National University, Seoul, South Korea
| | - Se Lee Kwon
- College of Medicine, Seoul National University, Seoul, South Korea
| | - Seung Hong Choi
- Department of Radiology, College of Medicine, Seoul National University, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, South Korea.
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, South Korea.
- School of Chemical and Biological Engineering, Seoul National University, Seoul, 151-742, South Korea.
| | - Inpyeong Hwang
- Department of Radiology, College of Medicine, Seoul National University, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, South Korea
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, South Korea
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Biomedical Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Sung-Hye Park
- Department of Pathology, College of Medicine, Seoul National University, Seoul, South Korea
| | - Jae-Kyung Won
- Department of Pathology, College of Medicine, Seoul National University, Seoul, South Korea
| | - Il Han Kim
- Department of Radiation Oncology, Cancer Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Soon Tae Lee
- Department of Neurology, College of Medicine, Seoul National University, Seoul, South Korea
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Hwang I, Choi SH, Park CK, Kim TM, Park SH, Won JK, Kim IH, Lee ST, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH. Dynamic Contrast-Enhanced MR Imaging of Nonenhancing T2 High-Signal-Intensity Lesions in Baseline and Posttreatment Glioblastoma: Temporal Change and Prognostic Value. AJNR Am J Neuroradiol 2019; 41:49-56. [PMID: 31806595 DOI: 10.3174/ajnr.a6323] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 10/02/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The prognostic value of dynamic contrast-enhanced MR imaging on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma has not been thoroughly elucidated to date. We evaluated the temporal change and prognostic value for progression-free survival of dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma before and after standard treatment, including gross total surgical resection. MATERIALS AND METHODS This retrospective study included 33 patients who were newly diagnosed with glioblastoma and treated with gross total surgical resection followed by concurrent chemoradiation therapy and adjuvant chemotherapy with temozolomide in a single institution. All patients underwent dynamic contrast-enhanced MR imaging before surgery as a baseline and after completion of maximal surgical resection and concurrent chemoradiation therapy. On the whole nonenhancing T2 high-signal-intensity lesion, dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters (volume transfer constant [K trans], volume of extravascular extracellular space [v e], and blood plasma volume [vp ]) were calculated. The Cox proportional hazards regression model analysis was performed to determine the histogram features or percentage changes of pharmacokinetic parameters related to progression-free survival. RESULTS Baseline median K trans, baseline first quartile K trans, and posttreatment median K trans were significant independent variables, as determined by univariate analysis (P < .05). By multivariate Cox regression analysis including methylation status of O6-methylguanine-DNA methyltransferase, baseline median K trans was determined to be the significant independent variable and was negatively related to progression-free survival (hazard ratio = 1.48, P = .003). CONCLUSIONS Baseline median K trans from nonenhancing T2 high-signal-intensity lesions could be a potential prognostic imaging biomarker in patients undergoing gross total surgical resection followed by standard therapy for glioblastoma.
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Affiliation(s)
- I Hwang
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - S H Choi
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research .,Institute for Basic Science, and School of Chemical and Biological Engineering (S.H.C.)
| | - C-K Park
- Department of Neurosurgery and Biomedical Research Institute (P.C.-K.)
| | - T M Kim
- Department of Internal Medicine and Cancer Research Institute (T.M.K.)
| | - S-H Park
- Department of Pathology (S.-H.P., J.K.W.)
| | - J K Won
- Department of Pathology (S.-H.P., J.K.W.)
| | - I H Kim
- Department of Radiation Oncology and Cancer Research Institute (I.H.K.)
| | - S-T Lee
- Department of Neurology (S.-T.L.), Seoul National University Hospital, Seoul, Korea
| | - R-E Yoo
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - K M Kang
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - T J Yun
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - J-H Kim
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - C-H Sohn
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
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Yoo RE, Choi SH, Oh BM, Do Shin S, Lee EJ, Shin DJ, Jo SW, Kang KM, Yun TJ, Kim JH, Sohn CH. Quantitative dynamic contrast-enhanced MR imaging shows widespread blood-brain barrier disruption in mild traumatic brain injury patients with post-concussion syndrome. Eur Radiol 2018; 29:1308-1317. [DOI: 10.1007/s00330-018-5656-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 07/01/2018] [Accepted: 07/04/2018] [Indexed: 12/27/2022]
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8
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Ahmed Z, Levesque IR. An extended reference region model for DCE-MRI that accounts for plasma volume. NMR IN BIOMEDICINE 2018; 31:e3924. [PMID: 29745982 DOI: 10.1002/nbm.3924] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 02/20/2018] [Accepted: 02/27/2018] [Indexed: 06/08/2023]
Abstract
The reference region model (RRM) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides pharmacokinetic parameters without requiring the arterial input function. A limitation of the RRM is that it assumes that the blood plasma volume in the tissue of interest is zero, but this is often not true in highly vascularized tissues, such as some tumours. This study proposes an extended reference region model (ERRM) to account for tissue plasma volume. Furthermore, ERRM was combined with a two-fit approach to reduce the number of fitting parameters, and this was named the constrained ERRM (CERRM). The accuracy and precision of RRM, ERRM and CERRM were evaluated in simulations covering a range of parameters, noise and temporal resolutions. These models were also compared with the extended Tofts model (ETM) on in vivo glioblastoma multiforme data. In simulations, RRM overestimated Ktrans by over 10% at vp = 0.01 under noiseless conditions. In comparison, ERRM and CERRM were both accurate, with CERRM showing better precision when noise was included. On in vivo data, CERRM provided maps that had the highest agreement with ETM, whilst also being robust at temporal resolutions as poor as 30 s. ERRM can provide pharmacokinetic parameters without an arterial input function in tissues with non-negligible vp where RRM provides inaccurate estimates. The two-fit approach, named CERRM, further improves on the accuracy and precision of ERRM.
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Affiliation(s)
- Zaki Ahmed
- Medical Physics Unit, McGill University, Montreal, QC, Canada
- Department of Physics, McGill University, Montreal, QC, Canada
| | - Ives R Levesque
- Medical Physics Unit, McGill University, Montreal, QC, Canada
- Department of Physics, McGill University, Montreal, QC, Canada
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
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Liang J, Liu D, Gao P, Zhang D, Chen H, Shi C, Luo L. Diagnostic Values of DCE-MRI and DSC-MRI for Differentiation Between High-grade and Low-grade Gliomas: A Comprehensive Meta-analysis. Acad Radiol 2018; 25:338-348. [PMID: 29223713 DOI: 10.1016/j.acra.2017.10.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 10/15/2017] [Accepted: 10/16/2017] [Indexed: 12/14/2022]
Abstract
RATIONALE AND OBJECTIVES This study aimed to collect the studies on the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI) in differentiating the grades of gliomas, and evaluate the diagnostic performances of relevant quantitative parameters in glioma grading. MATERIALS AND METHODS We systematically searched studies on the diagnosis of gliomas with DCE-MRI or DSC-MRI in Medline, PubMed, China National Knowledge Infrastructure database, Cochrane Library, and Embase published between January 2005 and December 2016. Standardized mean differences and 95% confidence intervals were calculated for volume transfer coefficient (Ktrans), volume fraction of extravascular extracellular space (Ve), rate constant of backflux (Kep), relative cerebral blood volume (rCBV), and relative cerebral blood flow (rCBF) using Review Manager 5.2 software. Sensitivity, specificity, area under the curve (AUC), and Begg test were calculated by Stata 12.0. RESULTS Twenty-two studies with available outcome data were included in the analysis. The standardized mean difference of Ktrans values between high-grade glioma and low-grade glioma were 1.18 (0.91, 1.45); Ve values were 1.43 (1.06, 1.80); Kep values were 0.65 (-0.05, 1.36); rCBV values were 1.44 (1.08, 1.81); and rCBF values were 1.17 (0.68, 1.67), respectively. The results were all significant statistically (P < .05) except Kep values (P = .07), and high-grade glioma had higher Ktrans, Ve, rCBV, and rCBF values than low-grade glioma. AUC values of Ktrans, Ve, rCBV, and rCBF were 0.90, 0.88, 0.93, and 0.73, respectively; rCBV had the largest AUC among the four parameters (P < .05). CONCLUSION Both DCE-MRI and DSC-MRI are reliable techniques in differentiating the grades of gliomas, and rCBV was found to be the most sensitive one.
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Affiliation(s)
- Jianye Liang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West Tianhe District, Guangzhou, 510630, China
| | - Dexiang Liu
- Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China
| | - Peng Gao
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West Tianhe District, Guangzhou, 510630, China
| | - Dong Zhang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West Tianhe District, Guangzhou, 510630, China
| | - Hanwei Chen
- Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China
| | - Changzheng Shi
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West Tianhe District, Guangzhou, 510630, China.
| | - Liangping Luo
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613, Huangpu Road West Tianhe District, Guangzhou, 510630, China.
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Hindel S, Söhner A, Maaß M, Sauerwein W, Möllmann D, Baba HA, Kramer M, Lüdemann L. Validation of Blood Volume Fraction Quantification with 3D Gradient Echo Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Porcine Skeletal Muscle. PLoS One 2017; 12:e0170841. [PMID: 28141810 PMCID: PMC5283669 DOI: 10.1371/journal.pone.0170841] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 01/11/2017] [Indexed: 12/16/2022] Open
Abstract
The purpose of this study was to assess the accuracy of fractional blood volume (vb) estimates in low-perfused and low-vascularized tissue using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The results of different MRI methods were compared with histology to evaluate the accuracy of these methods under clinical conditions. vb was estimated by DCE-MRI using a 3D gradient echo sequence with k-space undersampling in five muscle groups in the hind leg of 9 female pigs. Two gadolinium-based contrast agents (CA) were used: a rapidly extravasating, extracellular, gadolinium-based, low-molecular-weight contrast agent (LMCA, gadoterate meglumine) and an extracellular, gadolinium-based, albumin-binding, slowly extravasating blood pool contrast agent (BPCA, gadofosveset trisodium). LMCA data were evaluated using the extended Tofts model (ETM) and the two-compartment exchange model (2CXM). The images acquired with administration of the BPCA were used to evaluate the accuracy of vb estimation with a bolus deconvolution technique (BD) and a method we call equilibrium MRI (EqMRI). The latter calculates the ratio of the magnitude of the relaxation rate change in the tissue curve at an approximate equilibrium state to the height of the same area of the arterial input function (AIF). Immunohistochemical staining with isolectin was used to label endothelium. A light microscope was used to estimate the fractional vascular area by relating the vascular region to the total tissue region (immunohistochemical vessel staining, IHVS). In addition, the percentage fraction of vascular volume was determined by multiplying the microvascular density (MVD) with the average estimated capillary lumen, π(d2)2, where d = 8μm is the assumed capillary diameter (microvascular density estimation, MVDE). Except for ETM values, highly significant correlations were found between most of the MRI methods investigated. In the cranial thigh, for example, the vb medians (interquartile range, IQRs) of IHVS, MVDE, BD, EqMRI, 2CXM and ETM were vb = 0.7(0.3)%, 1.1(0.4)%, 1.1(0.4)%, 1.4(0.3)%, 1.2(1.8)% and 0.1(0.2)%, respectively. Variances, expressed by the difference between third and first quartiles (IQR) were highest for the 2CXM for all muscle groups. High correlations between the values in four muscle groups—medial, cranial, lateral thigh and lower leg - estimated with MRI and histology were found between BD and EqMRI, MVDE and 2CXM and IHVS and ETM. Except for the ETM, no significant differences between the vb medians of all MRI methods were revealed with the Wilcoxon rank sum test. The same holds for all muscle regions using the 2CXM and MVDE. Except for cranial thigh muscle, no significant difference was found between EqMRI and MVDE. And except for the cranial thigh and the lower leg muscle, there was also no significant difference between the vb medians of BD and MVDE. Overall, there was good vb agreement between histology and the BPCA MRI methods and the 2CXM LMCA approach with the exception of the ETM method. Although LMCA models have the advantage of providing excellent curve fits and can in principle determine more physiological parameters than BPCA methods, they yield more inaccurate results.
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Affiliation(s)
- Stefan Hindel
- Department of Radiotherapy, Medical Physics, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
- * E-mail:
| | - Anika Söhner
- Department of Radiotherapy, Medical Physics, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
| | - Marc Maaß
- Department of General and Visceral Surgery at Evangelical Hospital Wesel, Wesel, North Rhine-Westphalia, Germany
| | - Wolfgang Sauerwein
- Department of Radiotherapy, Medical Physics, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
| | - Dorothe Möllmann
- Department of Pathology, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
| | - Hideo Andreas Baba
- Department of Pathology, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
| | - Martin Kramer
- Hospital of Veterinary Medicine, Department of Small Animal Surgery, Justus Liebig University Giessen, Giessen, Hesse, Germany
| | - Lutz Lüdemann
- Department of Radiotherapy, Medical Physics, University Hospital Essen, Essen, North Rhine-Westphalia, Germany
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Dynamic contrast-enhanced MR imaging in predicting progression of enhancing lesions persisting after standard treatment in glioblastoma patients: a prospective study. Eur Radiol 2016; 27:3156-3166. [PMID: 27975145 DOI: 10.1007/s00330-016-4692-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 11/02/2016] [Accepted: 11/29/2016] [Indexed: 12/19/2022]
Abstract
OBJECTIVES To prospectively explore the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the progression of enhancing lesions persisting after standard treatment in patients with surgically resected glioblastoma (GBM). METHODS Forty-seven GBM patients, who underwent near-total tumorectomy followed by concurrent chemoradiation therapy (CCRT) with temozolomide (TMZ) between May 2014 and February 2016, were enrolled. Twenty-four patients were finally analyzed for measurable enhancing lesions persisting after standard treatment. DCE-MRI parameters were calculated at enhancing lesions. Mann-Whitney U tests and multivariable stepwise logistic regression were used to compare parameters between progression (n = 16) and non-progression (n = 8) groups. RESULTS Mean Ktrans and ve were significantly lower in progression than in non-progression (P = 0.037 and P = 0.037, respectively). The 5th percentile of the cumulative Ktrans histogram was also significantly lower in the progression than in non-progression group (P = 0.017). Mean ve was the only independent predictor of progression (P = 0.007), with a sensitivity of 100%, specificity of 63%, and an overall accuracy of 88% at a cut-off value of 0.873. CONCLUSIONS DCE-MRI may help predict the progression of enhancing lesions persisting after the completion of standard treatment in patients with surgically resected GBM, with mean ve serving as an independent predictor of progression. KEY POINTS • Enhancing lesions may persist after standard treatment in GBM patients. • DCE-MRI may help predict the progression of the enhancing lesions. • Mean K trans and v e were lower in progression than in non-progression group. • DCE-MRI may help identify patients requiring close follow-up after standard treatment. • DCE-MRI may help plan treatment strategies for GBM patients.
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12
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Ryu JK, Rhee SJ, Song JY, Cho SH, Jahng GH. Characteristics of quantitative perfusion parameters on dynamic contrast-enhanced MRI in mammographically occult breast cancer. J Appl Clin Med Phys 2016; 17:377-390. [PMID: 27685105 PMCID: PMC5874120 DOI: 10.1120/jacmp.v17i5.6091] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 04/27/2016] [Accepted: 04/25/2016] [Indexed: 12/12/2022] Open
Abstract
The purpose of this study was to compare the characteristics of quantitative per-fusion parameters obtained from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in patients with mammographically occult (MO) breast cancers and those with mammographically visible (MV) breast cancers. Quantitative parameters (AUC, Ktrans, kep, ve, vp, and wi) from 13 MO breast cancers and 16 MV breast cancers were mapped after the DCE-MRI data were acquired. Various prog-nostic factors, including axillary nodal status, estrogen receptor (ER), progesterone receptor (PR), Ki-67, p53, E-cadherin, and human epidermal growth factor receptor 2 (HER2) were obtained in each group. Fisher's exact test was used to compare any differences of the various prognostic factors between the two groups. The Mann- Whitney U test was applied to compare the quantitative parameters between these two groups. Finally, Spearman's correlation was used to investigate the relation-ships between perfusion indices and four factors - age, tumor size, Ki-67, and p53 - for each group. Although age, tumor size, and the prognostic factors were not statistically different between the two groups, the mean values of the quantitative parameters, except wi in the MV group, were higher than those in the MO group without statistical significance (p = 0.219). The kep value was significantly differ-ent between the two groups (p = 0.048), but the other parameters were not. In the MO group, vp with size, ve with p53, and Ktrans and vp with Ki-67 had significant correlations (p < 0.05). However, in the MV group, only kep showed significant correlation with age. The kep value was only the perfusion parameter of statistical significance between MO and MV breast cancers.
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Affiliation(s)
- Jung Kyu Ryu
- Kyung Hee University Hospital at Gandong, College of Medicine, Kyung Hee University.
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13
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Comparison of Cerebral Blood Volume and Plasma Volume in Untreated Intracranial Tumors. PLoS One 2016; 11:e0161807. [PMID: 27584684 PMCID: PMC5008702 DOI: 10.1371/journal.pone.0161807] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 08/14/2016] [Indexed: 02/06/2023] Open
Abstract
Purpose Plasma volume and blood volume are imaging-derived parameters that are often used to evaluation intracranial tumors. Physiologically, these parameters are directly related, but their two different methods of measurements, T1-dynamic contrast enhanced (DCE)- and T2-dynamic susceptibility contrast (DSC)-MR utilize different model assumptions and approaches. This poses the question of whether the interchangeable use of T1-DCE-MRI derived fractionated plasma volume (vp) and relative cerebral blood volume (rCBV) assessed using DSC-MRI, particularly in glioblastoma, is reliable, and if this relationship can be generalized to other types of brain tumors. Our goal was to examine the hypothetical correlation between these parameters in three most common intracranial tumor types. Methods Twenty-four newly diagnosed, treatment naïve brain tumor patients, who had undergone DCE- and DSC-MRI, were classified in three histologically proven groups: glioblastoma (n = 7), meningioma (n = 9), and intraparenchymal metastases (n = 8). The rCBV was obtained from DSC after normalization with the normal-appearing anatomically symmetrical contralateral white matter. Correlations between these parameters were evaluated using Pearson (r), Spearman's (ρ) and Kendall’s tau-b (τB) rank correlation coefficient. Results The Pearson, Spearman and Kendall’s correlation between vp with rCBV were r = 0.193, ρ = 0.253 and τB = 0.33 (p-Pearson = 0.326, p-Spearman= 0.814 and p-Kendall= 0.823) in glioblastoma, r = -0.007, ρ = 0.051 and τB = 0.135 (p-Pearson = 0.970, p-Spearman= 0.765 and p-Kendall= 0.358) in meningiomas, and r = 0.289, ρ = 0.228 and τB = 0.239 (p-Pearson = 0.109, p-Spearman= 0.210 and p-Kendall= 0.095) in metastasis. Conclusion Results indicate that no correlation exists between vp with rCBV in glioblastomas, meningiomas and intraparenchymal metastatic lesions. Consequently, these parameters, as calculated in this study, should not be used interchangeably in either research or clinical practice.
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Kim R, Choi SH, Yun TJ, Lee ST, Park CK, Kim TM, Kim JH, Park SW, Sohn CH, Park SH, Kim IH. Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging. Eur Radiol 2016; 27:1176-1185. [PMID: 27357131 DOI: 10.1007/s00330-016-4464-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2016] [Revised: 05/30/2016] [Accepted: 06/06/2016] [Indexed: 12/29/2022]
Abstract
OBJECTIVES To identify candidate imaging biomarkers for early disease progression in glioblastoma multiforme (GBM) patients by analysis of dynamic contrast-enhanced (DCE) MR parameters of non-enhancing T2 high signal intensity (SI) lesions. METHODS Forty-nine GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. According to the Response Assessment in Neuro-Oncology criteria, patients were classified into progression (n = 21) or non-progression (n = 28) groups. We analysed the pharmacokinetic parameters of Ktrans, Ve and Vp within non-enhancing T2 high SI lesions of each tumour. The best percentiles of each parameter from cumulative histograms were identified by the area under the receiver operating characteristic curve (AUC) and were compared using multivariate stepwise logistic regression. RESULTS For the differentiation of early disease progression, the highest AUC values were found in the 99th percentile of Ktrans (AUC 0.954), the 97th percentile of Ve (AUC 0.815) and the 94th percentile of Vp (AUC 0.786) (all p < 0.05). The 99th percentile of Ktrans was the only significant independent variable from the multivariate stepwise logistic regression (p = 0.002). CONCLUSIONS We found that the Ktrans of non-enhancing T2 high SI lesions in GBM patients holds potential as a candidate prognostic marker in future prospective studies. KEY POINTS • DCE MR imaging provides candidate prognostic marker of GBM after standard treatment. • Cumulative histogram was applied to include entire non-enhancing T2 high SI lesions. • The 99th percentile value of Ktrans was the most likely potential biomarker.
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Affiliation(s)
- Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea. .,Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 110-799, Republic of Korea. .,Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul National University, Daehak-dong, Gwanak-gu, Seoul, 151-742, Republic of Korea. .,School of Chemical and Biological Engineering, Seoul National University, Daehak-dong, Gwanak-gu, Seoul, 151-742, Republic of Korea.
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Soon-Tae Lee
- Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Min Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Sun-Won Park
- Department of Radiology, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Il Han Kim
- Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea
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15
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Santarosa C, Castellano A, Conte GM, Cadioli M, Iadanza A, Terreni MR, Franzin A, Bello L, Caulo M, Falini A, Anzalone N. Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis. Eur J Radiol 2016; 85:1147-56. [PMID: 27161065 DOI: 10.1016/j.ejrad.2016.03.020] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Revised: 03/10/2016] [Accepted: 03/20/2016] [Indexed: 12/01/2022]
Abstract
INTRODUCTION Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K(trans). METHODS Twenty-six newly diagnosed glioma patients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and K(trans) were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K(trans) values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis. RESULTS rCBV, Vp and K(trans) measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. K(trans) hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and K(trans)max. Combination of DCE-derived Vp and K(trans) parameters improved the diagnostic performance of the histogram method. CONCLUSION This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived K(trans) is equally useful for grading, providing different informations with respect to Vp.
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Affiliation(s)
- Corrado Santarosa
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Gian Marco Conte
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Marcello Cadioli
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy; Philips Healthcare, Monza, Italy
| | - Antonella Iadanza
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | | | - Alberto Franzin
- Department of Neurosurgery, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Lorenzo Bello
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; Unit of Surgical Neurooncology, Humanitas Research Hospital, Rozzano, MI, Italy
| | - Massimo Caulo
- Department of Neuroscience and Imaging and ITAB-Institute of Advanced Biomedical Technologies, University "G. d'Annunzio", Chieti, Italy
| | - Andrea Falini
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Nicoletta Anzalone
- Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy.
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Yoo RE, Choi SH. Recent Application of Advanced MR Imaging to Predict Pseudoprogression in High-grade Glioma Patients. Magn Reson Med Sci 2015; 15:165-77. [PMID: 26726012 PMCID: PMC5600053 DOI: 10.2463/mrms.rev.2015-0053] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Pseudoprogression is regarded as a subacute form of treatment-related change with a reported incidence of 20-30%, occurring predominantly within the first three months after the completion of concurrent chemoradiotherapy (CCRT) in glioblastoma multiforme (GBM) patients. Occurrence of progressive lesions on conventional contrast-enhanced MR imaging may also accompany clinical deterioration, posing considerable diagnostic challenges to clinicians and radiologists. False interpretation of treatment-related change as true progression may lead to the cessation of effective first-line therapy (i.e., adjuvant temozolomide) and unnecessary surgery. Increasing awareness of the diagnostic challenge of the phenomenon has underscored the need for better imaging techniques that may aid in differentiating the treatment-related change from true progression. In this review, we discuss the recent applications of advanced MR imaging such as diffusion-weighted and perfusion-weighted imaging in the evaluation of treatment response in high-grade glioma patients and highlight their potential role in differentiating pseudoprogression from true progression.
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Affiliation(s)
- Roh-Eul Yoo
- Department of Radiology, Seoul National University Hospital
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17
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Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel'farb G, Ouseph R, Dwyer AC. Models and methods for analyzing DCE-MRI: a review. Med Phys 2015; 41:124301. [PMID: 25471985 DOI: 10.1118/1.4898202] [Citation(s) in RCA: 195] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches. METHODS DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases. RESULTS Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors. CONCLUSIONS Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.
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Affiliation(s)
- Fahmi Khalifa
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292 and Electronics and Communication Engineering Department, Mansoura University, Mansoura 35516, Egypt
| | - Ahmed Soliman
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Ayman El-Baz
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Mohamed Abou El-Ghar
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Tarek El-Diasty
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Georgy Gimel'farb
- Department of Computer Science, University of Auckland, Auckland 1142, New Zealand
| | - Rosemary Ouseph
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
| | - Amy C Dwyer
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
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Roniotis A, Oraiopoulou ME, Tzamali E, Kontopodis E, Van Cauter S, Sakkalis V, Marias K. A Proposed Paradigm Shift in Initializing Cancer Predictive Models with DCE-MRI Based PK Parameters: A Feasibility Study. Cancer Inform 2015; 14:7-18. [PMID: 26085787 PMCID: PMC4463799 DOI: 10.4137/cin.s19339] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Revised: 03/02/2015] [Accepted: 03/06/2015] [Indexed: 01/12/2023] Open
Abstract
Glioblastoma multiforme is the most aggressive type of glioma and the most common malignant primary intra-axial brain tumor. In an effort to predict the evolution of the disease and optimize therapeutical decisions, several models have been proposed for simulating the growth pattern of glioma. One of the latest models incorporates cell proliferation and invasion, angiogenic net rates, oxygen consumption, and vasculature. These factors, particularly oxygenation levels, are considered fundamental factors of tumor heterogeneity and compartmentalization. This paper focuses on the initialization of the cancer cell populations and vasculature based on imaging examinations of the patient and presents a feasibility study on vasculature prediction over time. To this end, pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging using Toft’s model are used in order to feed the model. Ktrans is used as a metric of the density of endothelial cells (vasculature); at the same time, it also helps to discriminate distinct image areas of interest, under a set of assumptions. Feasibility results of applying the model to a real clinical case are presented, including a study on the effect of certain parameters on the pattern of the simulated tumor.
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Affiliation(s)
- Alexandros Roniotis
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece
| | - Mariam-Eleni Oraiopoulou
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece. ; Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Eleftheria Tzamali
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece
| | - Eleftherios Kontopodis
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece
| | - Sofie Van Cauter
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Vangelis Sakkalis
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece
| | - Kostas Marias
- Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece
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Dynamic Contrast-Enhanced MRI in the Study of Brain Tumors. Comparison Between the Extended Tofts-Kety Model and a Phenomenological Universalities (PUN) Algorithm. J Digit Imaging 2015; 28:748-54. [PMID: 25776769 DOI: 10.1007/s10278-015-9788-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a well-established technique for studying blood-brain barrier (BBB) permeability that allows measurements to be made for a wide range of brain pathologies, including multiple sclerosis and brain tumors (BT). This latter application is particularly interesting, because high-grade gliomas are characterized by increased microvascular permeability and a loss of BBB function due to the structural abnormalities of the endothelial layer. In this study, we compared the extended Tofts-Kety (ETK) model and an extended derivate class from phenomenological universalities called EU1 in 30 adult patients with different BT grades. A total of 75 regions of interest were manually drawn on the MRI and subsequently analyzed using the ETK and EU1 algorithms. Significant linear correlations were found among the parameters obtained by these two algorithms. The means of R (2) obtained using ETK and EU1 models for high-grade tumors were 0.81 and 0.91, while those for low-grade tumors were 0.82 and 0.85, respectively; therefore, these two models are equivalent. In conclusion, we can confirm that the application of the EU1 model to the DCE-MRI experimental data might be a useful alternative to pharmacokinetic models in the study of BT, because the analytic results can be generated more quickly and easily than with the ETK model.
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Kalpathy-Cramer J, Gerstner ER, Emblem KE, Andronesi O, Rosen B. Advanced magnetic resonance imaging of the physical processes in human glioblastoma. Cancer Res 2015; 74:4622-4637. [PMID: 25183787 DOI: 10.1158/0008-5472.can-14-0383] [Citation(s) in RCA: 98] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."
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Affiliation(s)
- Jayashree Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging, Departments of Radiology, Oslo University Hospital, Oslo, Norway
| | - Elizabeth R Gerstner
- Neurology, Massachusetts General Hospital and Harvard Medical School, Oslo University Hospital, Oslo, Norway
| | - Kyrre E Emblem
- Athinoula A. Martinos Center for Biomedical Imaging, Departments of Radiology, Oslo University Hospital, Oslo, Norway.,The Intervention Centre, Oslo University Hospital, Oslo, Norway
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Departments of Radiology, Oslo University Hospital, Oslo, Norway
| | - Bruce Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Departments of Radiology, Oslo University Hospital, Oslo, Norway
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Abe T, Mizobuchi Y, Nakajima K, Otomi Y, Irahara S, Obama Y, Majigsuren M, Khashbat D, Kageji T, Nagahiro S, Harada M. Diagnosis of brain tumors using dynamic contrast-enhanced perfusion imaging with a short acquisition time. SPRINGERPLUS 2015; 4:88. [PMID: 25793147 PMCID: PMC4359190 DOI: 10.1186/s40064-015-0861-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Accepted: 01/29/2015] [Indexed: 12/02/2022]
Abstract
This study sought to determine the diagnostic utility of perfusion parameters derived from dynamic contrast-enhanced (DCE) perfusion MRI with a short acquisition time (approximately 3.5 min) in patients with glioma, brain metastasis, and primary CNS lymphoma (PCNSL). Twenty-six patients with 29 lesions (4 low-grade glioma, 13 high-grade glioma, 7 metastasis, and 5 PCNSL) underwent DCE-MRI in a 3 T scanner. A ROI was placed on the hotspot of each tumor in maps for volume transfer contrast Ktrans, extravascular extracellular volume Ve, and fractional plasma volume Vp. We analyzed differences in parameters between tumors using the Mann–Whitney U test. We calculated sensitivity and specificity using receiver operating characteristics analysis. Mean Ktrans values of LGG, HGG, metastasis and PCNSL were 0.034, 0.31, 0.38, 0.44, respectively. Mean Ve values of each tumors was 0.036, 0.57, 0.47, 0.96, and mean Vp value of each tumors was 0.070, 0.086, 0.26, 0.17, respectively. Compared with other tumor types, low-grade glioma showed lower Ktrans (P < 0.01, sensitivity = 88%, specificity = 100%) and lower Ve (P < 0.01, sensitivity = 96%, specificity = 100%). PCNSL showed higher Ve (P < 0.01, sensitivity = 100%, specificity = 88%), but the other perfusion parameters overlapped with those of different histology. Kinetic parameters derived from DCE-MRI with short acquisition time provide useful information for the differential diagnosis of brain tumors.
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Affiliation(s)
- Takashi Abe
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Yoshifumi Mizobuchi
- Departments of Neurosurgery, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
| | - Kohei Nakajima
- Departments of Neurosurgery, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
| | - Yoichi Otomi
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Saho Irahara
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Yuki Obama
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Mungunkhuyag Majigsuren
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Delgerdalai Khashbat
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
| | - Teruyoshi Kageji
- Departments of Neurosurgery, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
| | - Shinji Nagahiro
- Departments of Neurosurgery, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
| | - Masafumi Harada
- Department of Radiology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-18-15, Kuramoto-cho, Tokushima City, Tokushima 770-8509 Japan
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22
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Kitamoto E, Chikui T, Kawano S, Ohga M, Kobayashi K, Matsuo Y, Yoshiura T, Obara M, Honda H, Yoshiura K. The application of dynamic contrast-enhanced MRI and diffusion-weighted MRI in patients with maxillofacial tumors. Acad Radiol 2015; 22:210-6. [PMID: 25442795 DOI: 10.1016/j.acra.2014.08.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2014] [Revised: 08/07/2014] [Accepted: 08/25/2014] [Indexed: 10/24/2022]
Abstract
RATIONALE AND OBJECTIVES To elucidate the characteristics of four types of tumors, including squamous cell carcinoma (SCC), malignant lymphoma (ML), malignant salivary gland tumors (MSGTs), and pleomorphic adenoma (Pleo), in the maxillofacial region using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI)data. MATERIALS AND METHODS A total of 59 tumors were included in this research. DCE-MRI and DW-MRI were performed. We applied the Tofts and Kermode model (TK model) for the DCE-MRI data and obtained three dependent parameters: the influx forward volume transfer constant into the extravascular extracellular space from the plasma (K(trans)), the fractional volume of extravascular extracellular space per unit volume of tissue (ve), and the fractional volume of plasma (vp). RESULTS Among the K(trans) values, there were no significant differences between the three types of malignant tumors; however, there was a significant difference between the SCC and Pleo (P = .0099). The ve values of the Pleo were highest, with significant differences compared to the other categories (SCC, P = .0012; ML, P = .0017; and MSGT, P = .041). The ML had the lowest ve values, and there were significant differences between ML and the other two types of malignant tumors (SCC, P = .0278 and MSGT, P = .0062). In 14 (24%) cases, apparent diffusion coefficient (ADC) could not be measured because of poor image quality. The ADC values of the ML were lowest, whereas those of Pleo were highest, similar to that observed for ve. CONCLUSIONS The Pleo tumors had lower K(trans) values and higher ve values, which are useful for differentiating them from the malignant tumors. Moreover, the ve was also useful for establishing a diagnosis of ML.
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Evaluation of IAUGC indices and two DCE-MRI pharmacokinetic parameters assessed by two different theoretical algorithms in patients with brain tumors. Clin Imaging 2014; 38:808-14. [DOI: 10.1016/j.clinimag.2014.07.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2013] [Revised: 06/09/2014] [Accepted: 07/10/2014] [Indexed: 11/20/2022]
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Simulating the effect of input errors on the accuracy of Tofts' pharmacokinetic model parameters. Magn Reson Imaging 2014; 33:222-35. [PMID: 25308097 DOI: 10.1016/j.mri.2014.10.004] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2013] [Revised: 09/26/2014] [Accepted: 10/05/2014] [Indexed: 01/19/2023]
Abstract
Pharmacokinetic modeling in Dynamic Contrast Enhanced (DCE)-MRI is an elegant and useful method that provides valuable insight into angiogenesis in cancer and inflammatory diseases. Despite its widespread use, the reliability of the model results is still questioned, as many factors hamper the calculation of the model's parameters, resulting in the poor reproducibility and accuracy of the method. Pharmacokinetic modeling relies on the knowledge of inputs such as the Arterial Input Function (AIF) and of the tissue contrast agent concentration, both of which are difficult to accurately measure. Any errors in the measurement of either of the inputs propagate into the calculated pharmacokinetic model parameters (PMPs), and the significance of the effect depends on the source of the measurement error. In this work we systematically investigate the effect of the incorrect estimation of the parameters describing the inputs of the model on the calculated PMPs when using Tofts' model. Furthermore, we analyze the dependence of these errors on the native values of the PMPs. We show that errors on the measurement of the native T1 as well as errors on the parameters describing the initial peak of the AIF have the largest impact on the calculated PMPs. The parameter whose error has the least effect is the one describing the slow decay of the AIF. The effect of input parameter (IP) errors on the calculated PMPs is found to be dependent on the native set of PMPs: this is particularly true for the errors in the flip angle, and for the errors in parameters describing the initial AIF peak. Conversely the effect of T1 and AIF scaling errors on the calculated PMPs is only slightly dependent on the native PMPs.
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25
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Heye AK, Culling RD, Valdés Hernández MDC, Thrippleton MJ, Wardlaw JM. Assessment of blood-brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review. NEUROIMAGE-CLINICAL 2014; 6:262-74. [PMID: 25379439 PMCID: PMC4215461 DOI: 10.1016/j.nicl.2014.09.002] [Citation(s) in RCA: 256] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Revised: 09/04/2014] [Accepted: 09/05/2014] [Indexed: 01/31/2023]
Abstract
There is increasing recognition of the importance of blood-brain barrier (BBB) disruption in aging, dementia, stroke and multiple sclerosis in addition to more commonly-studied pathologies such as tumors. Dynamic contrast-enhanced MRI (DCE-MRI) is a method for studying BBB disruption in vivo. We review pathologies studied, scanning protocols and data analysis procedures to determine the range of available methods and their suitability to different pathologies. We systematically review the existing literature up to February 2014, seeking studies that assessed BBB integrity using T1-weighted DCE-MRI techniques in animals and humans in normal or abnormal brain tissues. The literature search provided 70 studies that were eligible for inclusion, involving 417 animals and 1564 human subjects in total. The pathologies most studied are intracranial neoplasms and acute ischemic strokes. There are large variations in the type of DCE-MRI sequence, the imaging protocols and the contrast agents used. Moreover, studies use a variety of different methods for data analysis, mainly based on model-free measurements and on the Patlak and Tofts models. Consequently, estimated K (Trans) values varied widely. In conclusion, DCE-MRI is shown to provide valuable information in a large variety of applications, ranging from common applications, such as grading of primary brain tumors, to more recent applications, such as assessment of subtle BBB dysfunction in Alzheimer's disease. Further research is required in order to establish consensus-based recommendations for data acquisition and analysis and, hence, improve inter-study comparability and promote wider use of DCE-MRI.
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Affiliation(s)
- Anna K Heye
- Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Ross D Culling
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
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Abstract
Neuroimaging plays a crucial role in diagnosis of brain tumors and in the decision-making process for therapy. Functional imaging techniques can reflect cellular density (diffusion imaging), capillary density (perfusion techniques), and tissue biochemistry (magnetic resonance [MR] spectroscopy). In addition, cortical activation imaging (functional MR imaging) can identify various loci of eloquent cerebral cortical function. Combining these new tools can increase diagnostic specificity and confidence. Familiarity with conventional and advanced imaging findings facilitates accurate diagnosis, differentiation from other processes, and optimal patient treatment. This article is a practical synopsis of pathologic, clinical, and imaging spectra of most common brain tumors.
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Affiliation(s)
- Danai Chourmouzi
- Diagnostic Radiology Department, Interbalcan Medical Centre, Asklipiou 10, Thessaloniki 57001, Greece.
| | - Elissabet Papadopoulou
- Diagnostic Radiology Department, Interbalcan Medical Centre, Asklipiou 10, Thessaloniki 57001, Greece
| | - Kostantinos Marias
- Computational Medicine Laboratory, Institute of Computer Science, Plastira 100 Vasilika Vouton, FORTH, Heraklion, Greece
| | - Antonios Drevelegas
- Diagnostic Radiology Department, Interbalcan Medical Centre, Asklipiou 10, Thessaloniki 57001, Greece
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27
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Revert Ventura A, Sanz Requena R, Martí-Bonmatí L, Pallardó Y, Jornet J, Gaspar C. The heterogeneity of blood flow on magnetic resonance imaging: A biomarker for grading cerebral astrocytomas. RADIOLOGIA 2014. [DOI: 10.1016/j.rxeng.2012.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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28
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Bergamino M, Bonzano L, Levrero F, Mancardi GL, Roccatagliata L. A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors. Phys Med 2014; 30:635-43. [PMID: 24793824 DOI: 10.1016/j.ejmp.2014.04.005] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Revised: 03/18/2014] [Accepted: 04/08/2014] [Indexed: 12/11/2022] Open
Abstract
In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated.
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Affiliation(s)
- M Bergamino
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy; Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Genoa, Italy.
| | - L Bonzano
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy; Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Genoa, Italy
| | - F Levrero
- Department of Medical Physics, San Martino Hospital, Genoa, Italy
| | - G L Mancardi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy; Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Genoa, Italy
| | - L Roccatagliata
- Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Genoa, Italy; Department of Health Sciences, University of Genoa, Genoa, Italy
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29
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Jung SC, Yeom JA, Kim JH, Ryoo I, Kim SC, Shin H, Lee AL, Yun TJ, Park CK, Sohn CH, Park SH, Choi SH. Glioma: Application of histogram analysis of pharmacokinetic parameters from T1-weighted dynamic contrast-enhanced MR imaging to tumor grading. AJNR Am J Neuroradiol 2014; 35:1103-10. [PMID: 24384119 DOI: 10.3174/ajnr.a3825] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging. MATERIALS AND METHODS Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas. RESULTS All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis. CONCLUSIONS Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.
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Affiliation(s)
- S C Jung
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - J A Yeom
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - J-H Kim
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - I Ryoo
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - S C Kim
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - H Shin
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - A L Lee
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - T J Yun
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | | | - C-H Sohn
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)
| | - S-H Park
- Pathology (S.-H.P.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - S H Choi
- From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)Center for Nanoparticle Research (S.H.C.), Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
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30
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Inhibition of SUR1 decreases the vascular permeability of cerebral metastases. Neoplasia 2013; 15:535-43. [PMID: 23633925 DOI: 10.1593/neo.13164] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Revised: 03/04/2013] [Accepted: 03/11/2013] [Indexed: 01/13/2023] Open
Abstract
Inhibition of sulfonylurea receptor 1 (SUR1) by glyburide has been shown to decrease edema after subarachnoid hemorrhage. We investigated if inhibiting SUR1 reduces cerebral edema due to metastases, the most common brain tumor, and explored the putative association of SUR1 and the endothelial tight junction protein, zona occludens-1 (ZO-1). Nude rats were intracerebrally implanted with small cell lung carcinoma (SCLC) LX1 or A2058 melanoma cells (n = 36). Rats were administered vehicle, glyburide (4.8 µg twice, orally), or dexamethasone (0.35 mg, intravenous). Blood-tumor barrier (BTB) permeability (K (trans)) was evaluated before and after treatment using dynamic contrast-enhanced magnetic resonance imaging. SUR1 and ZO-1 expression was evaluated using immunofluorescence and Western blots. In both models, SUR1 expression was significantly increased (P < .05) in tumors. In animals with SCLC, control mean K (trans) (percent change ± standard error) was 101.8 ± 36.6%, and both glyburide (-21.4 ± 14.2%, P < .01) and dexamethasone (-14.2 ± 13.1%, P < .01) decreased BTB permeability. In animals with melanoma, compared to controls (117.1 ± 43.4%), glyburide lowered BTB permeability increase (3.2 ± 15.4%, P < .05), while dexamethasone modestly lowered BTB permeability increase (63.1 ± 22.1%, P > .05). Both glyburide (P < .001) and dexamethasone (P < .01) decreased ZO-1 gap formation. By decreasing ZO-1 gaps, glyburide was at least as effective as dexamethasone at halting increased BTB permeability caused by SCLC and melanoma. Glyburide is a safe, inexpensive, and efficacious alternative to dexamethasone for the treatment of cerebral metastasis-related vasogenic edema.
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31
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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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32
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Ewing JR, Bagher-Ebadian H. Model selection in measures of vascular parameters using dynamic contrast-enhanced MRI: experimental and clinical applications. NMR IN BIOMEDICINE 2013; 26:1028-41. [PMID: 23881857 PMCID: PMC3752406 DOI: 10.1002/nbm.2996] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2012] [Revised: 05/15/2013] [Accepted: 06/11/2013] [Indexed: 05/22/2023]
Abstract
A review of the selection of models in dynamic contrast-enhanced MRI (DCE-MRI) is conducted, with emphasis on the balance between the bias and variance required to produce stable and accurate estimates of vascular parameters. The vascular parameters considered as a first-order model are the forward volume transfer constant K(trans) , the plasma volume fraction vp and the interstitial volume fraction ve . To illustrate the critical issues in model selection, a data-driven selection of models in an animal model of cerebral glioma is followed. Systematic errors and extended models are considered. Studies with nested and non-nested pharmacokinetic models are reviewed; models considering water exchange are considered.
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Affiliation(s)
- James R Ewing
- Department of Neurology, Henry Ford Health System, Detroit, MI, USA.
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Choi HS, Kim AH, Ahn SS, Shin NY, Kim J, Lee SK. Glioma grading capability: comparisons among parameters from dynamic contrast-enhanced MRI and ADC value on DWI. Korean J Radiol 2013; 14:487-92. [PMID: 23690718 PMCID: PMC3655305 DOI: 10.3348/kjr.2013.14.3.487] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2012] [Accepted: 11/15/2012] [Indexed: 11/29/2022] Open
Abstract
Objective Permeability parameters from dynamic contrast-enhanced MRI (DCE-MRI) and apparent diffusion coefficient (ADC) value on diffusion-weighted imaging (DWI) can be quantitative physiologic metrics for gliomas. The transfer constant (Ktrans) has shown efficacy in grading gliomas. Volume fraction of extravascular extracellular space (ve) has been underutilized to grade gliomas. The purpose of this study was to evaluate ve in its ability to grade gliomas and to assess the correlation with other permeability parameters and ADC values. Materials and Methods A total of 33 patients diagnosed with pathologically-confirmed gliomas were examined by 3 T MRI including DCE-MRI and ADC map. A region of interest analyses for permeability parameters from DCE-MRI and ADC were performed on the enhancing solid portion of the tumors. Permeability parameters form DCE-MRI and ADC between low- and high-grade gliomas; the diagnostic performances of presumptive metrics and correlation among those metrics were statistically analyzed. Results High-grade gliomas showed higher Ktrans (0.050 vs. 0.010 in median value, p = 0.002) and higher ve (0.170 vs. 0.015 in median value, p = 0.001) than low-grade gliomas. Receiver operating characteristic curve analysis showed significance in both Ktrans and ve for glioma grading. However, there was no significant difference in diagnostic performance between Ktrans and ve. ADC value did not correlate with any of the permeability parameters from DCE-MRI. Conclusion Extravascular extracellular space (ve) appears to be comparable with transfer constant (Ktrans) in differentiating high-grade gliomas from low-grade gliomas. ADC value does not show correlation with any permeability parameters from DCE-MRI.
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Affiliation(s)
- Hyun Seok Choi
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul 120-752, Korea
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Measurement of blood-brain barrier permeability with t1-weighted dynamic contrast-enhanced MRI in brain tumors: a comparative study with two different algorithms. ISRN NEUROSCIENCE 2013; 2013:905279. [PMID: 24959569 PMCID: PMC4045531 DOI: 10.1155/2013/905279] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2012] [Accepted: 01/16/2013] [Indexed: 12/01/2022]
Abstract
The purpose of this study was to assess the feasibility of measuring different permeability parameters with T1-weighted dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in order to investigate the blood brain-barrier permeability associated with different brain tumors. The Patlak algorithm and the extended Tofts-Kety model were used to this aim. Twenty-five adult patients with tumors of different histological grades were enrolled in this study. MRI examinations were performed at 1.5 T. Multiflip angle, fast low-angle shot, and axial 3D T1-weighted images were acquired to calculate T1 maps, followed by a DCE acquisition. A region of interest was placed within the tumor of each patient to calculate the mean value of different permeability parameters. Differences in permeability measurements were found between different tumor grades, with higher histological grades characterized by higher permeability values. A significant difference in transfer constant (Ktrans) values was found between the two methods on high-grade tumors; however, both techniques revealed a significant correlation between the histological grade of tumors and their Ktrans values. Our results suggest that DCE acquisition is feasible in patients with brain tumors and that Ktrans maps can be easily obtained by these two algorithms, even if the theoretical model adopted could affect the final results.
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Larsson C, Kleppestø M, Rasmussen I, Salo R, Vardal J, Brandal P, Bjørnerud A. Sampling requirements in DCE-MRI based analysis of high grade gliomas: simulations and clinical results. J Magn Reson Imaging 2012; 37:818-29. [PMID: 23086710 DOI: 10.1002/jmri.23866] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2011] [Accepted: 09/06/2012] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To investigate the effect of variations in temporal resolution and total measurement times on the estimations of kinetic parameters derived from dynamic contrast-enhanced (DCE) MRI in patients with high-grade gliomas (HGGs). MATERIALS AND METHODS DCE-MRI with high temporal resolution (dynamic sampling time (T(s)) = 2.1 s and 3.4 s) and total sampling time (T(acq)) of 5.2 min was acquired in 101 examinations from 15 patients. Using the modified Tofts model K(trans), k(ep) v(e) and v(p) were estimated. The effects of increasing T(s) and reducing T(acq) on the estimated kinetic parameters were estimated through down-sampling and data truncation, and the results were compared with numerical simulations. RESULTS There was an overall dependence of all four kinetic parameters on T(s) and T(acq). Increasing T(s) resulted in under-estimation of K(trans) and over-estimation of V(p), whereas k(ep) and V(e) varied in a less predictable manner. Reducing T(acq) resulted in over-estimation of K(trans) and k(ep) and under-estimation of v(p) and v(e). Increasing T(s) and reducing T(acq) resulted in increased relative error for all four parameters. CONCLUSION Estimated K(trans), K(ep), and V(e) in HGGs were within 15% of the high sampling rate reference values for T(s) <20 s. Increasing T(s) and reducing T(acq) leads to reduced precision of the estimated values.
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Revert Ventura AJ, Sanz Requena R, Martí-Bonmatí L, Pallardó Y, Jornet J, Gaspar C. [The heterogeneity of blood flow on magnetic resonance imaging: a biomarker for grading cerebral astrocytomas]. RADIOLOGIA 2012; 56:328-38. [PMID: 22738943 DOI: 10.1016/j.rx.2012.01.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2011] [Revised: 01/04/2012] [Accepted: 01/05/2012] [Indexed: 11/16/2022]
Abstract
OBJECTIVES To study whether the histograms of quantitative parameters of perfusion in MRI obtained from tumor volume and peritumor volume make it possible to grade astrocytomas in vivo. MATERIAL AND METHODS We included 61 patients with histological diagnoses of grade II, III, or IV astrocytomas who underwent T2*-weighted perfusion MRI after intravenous contrast agent injection. We manually selected the tumor volume and peritumor volume and quantified the following perfusion parameters on a voxel-by-voxel basis: blood volume (BV), blood flow (BF), mean transit time (TTM), transfer constant (K(trans)), washout coefficient, interstitial volume, and vascular volume. For each volume, we obtained the corresponding histogram with its mean, standard deviation, and kurtosis (using the standard deviation and kurtosis as measures of heterogeneity) and we compared the differences in each parameter between different grades of tumor. We also calculated the mean and standard deviation of the highest 10% of values. Finally, we performed a multiparametric discriminant analysis to improve the classification. RESULTS For tumor volume, we found statistically significant differences among the three grades of tumor for the means and standard deviations of BV, BF, and K(trans), both for the entire distribution and for the highest 10% of values. For the peritumor volume, we found no significant differences for any parameters. The discriminant analysis improved the classification slightly. CONCLUSIONS The quantification of the volume parameters of the entire region of the tumor with BV, BF, and K(trans) is useful for grading astrocytomas. The heterogeneity represented by the standard deviation of BF is the most reliable diagnostic parameter for distinguishing between low grade and high grade lesions.
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Affiliation(s)
| | - R Sanz Requena
- Servicio de Radiología, Hospital Quirón Valencia, Valencia, España
| | - L Martí-Bonmatí
- Servicio de Radiología, Hospital Quirón Valencia, Valencia, España; Servicio de Radiología, Hospital Universitario y Politécnico La Fe, Valencia, España
| | - Y Pallardó
- Servicio de Radiología, Hospital de Manises, Manises, Valencia, España
| | - J Jornet
- Servicio de Radiología, Hospital de la Ribera, Alzira, Valencia, España
| | - C Gaspar
- Servicio de Oncología, Hospital de la Ribera, Alzira, Valencia, España
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Thompson EM, Guillaume DJ, Dósa E, Li X, Nazemi KJ, Gahramanov S, Hamilton BE, Neuwelt EA. Dual contrast perfusion MRI in a single imaging session for assessment of pediatric brain tumors. J Neurooncol 2012; 109:105-14. [PMID: 22528798 DOI: 10.1007/s11060-012-0872-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2011] [Accepted: 03/31/2012] [Indexed: 10/28/2022]
Abstract
Ferumoxytol, an iron nanoparticle used as an intravascular contrast agent for perfusion magnetic resonance imaging (MRI), has never been explored in the pediatric population. The purpose of this prospective study is to characterize the vascular and permeability properties of pediatric brain tumors using two contrast agents during a single imaging session: ferumoxytol for dynamic susceptibility weighted contrast (DSC) MRI and gadoteridol for dynamic contrast-enhanced (DCE) MRI. In a single imaging session, patients received intravenous ferumoxytol for DSC MRI followed by gadoteridol for DCE MRI. Relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), transfer coefficient (K(trans)), and extravascular extracellular space volume fraction (v(e)) of the brain lesions were calculated. Patients underwent serial imaging sessions over the course of 2 years. Of the 7 patients enrolled thus far, none has experienced an adverse event. Two patients with medulloblastoma were enrolled preoperatively. In the first, rCBV(max), rCBF, K(trans) max, and v(e) max values were 3.74, 3.12, 0.47 min (-1), and 0.08, respectively, while in the second patient, rCBV(max), rCBF, K(trans) max, and v(e) max values were 4.72, 3.47, 0.60 min(-1), and 0.05, respectively. Four patients were enrolled after new gadolinium enhancement was noted in the tumor resection cavity. In 80 % of these lesions, rCBV was <1 suggestive of pseudoprogression secondary to radiochemotherapy. These preliminary results demonstrate that use of ferumoxytol and gadoteridol contrast agents during a single imaging session is feasible, safe, and appears useful for assessing tumor perfusion and permeability characteristics in children.
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Affiliation(s)
- Eric M Thompson
- Department of Neurological Surgery, Oregon Health & Science University, 3303 SW Bond Avenue, CH8N, Portland, OR, 97239, USA
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Nelson SJ. Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI. NMR IN BIOMEDICINE 2011; 24:734-49. [PMID: 21538632 PMCID: PMC3772179 DOI: 10.1002/nbm.1669] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2010] [Revised: 11/14/2010] [Accepted: 12/10/2010] [Indexed: 05/26/2023]
Abstract
MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T(1) -weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T(2) lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.
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Affiliation(s)
- Sarah J Nelson
- University of California at San Francisco - Mission Bay, San Francisco, CA, USA.
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Lavini C, Verhoeff JJC. Reproducibility of the gadolinium concentration measurements and of the fitting parameters of the vascular input function in the superior sagittal sinus in a patient population. Magn Reson Imaging 2011; 28:1420-30. [PMID: 20817379 DOI: 10.1016/j.mri.2010.06.017] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2009] [Revised: 04/29/2010] [Accepted: 06/25/2010] [Indexed: 01/22/2023]
Abstract
It is widely recognised that the measurement of the arterial input function (AIF) is a key issue and a major source of errors in the pharmacokinetic modelling of dynamic, contrast-enhanced magnetic resonance imaging (DCE-MRI) data, and the modality of the AIF determination is still a matter of debate. In this study we addressed the problem of the intrinsic variability of the AIF within the imaged volume of a DCE-MRI scan by systematically investigating the change in the concentration of contrast agent over time and the fit parameters of the derived vascular input function (VIF) obtained from the superior sagittal sinus (SSS) of a patient population that was scanned longitudinally during treatment for high grade glioma. From a total of 82 scanning sessions, we compared the results obtained with three different DCE-MRI protocols and between two different fitting functions. We applied a correction algorithm to the measured concentration-time curves to minimize the effect of the low temporal resolution on the VIF, and investigated the effect of this algorithm on the reproducibility. Finally, where possible, we compared the signal obtained in the SSS to the signal obtained in the middle cerebral artery. We found a good intrapatient reproducibility of both the measured gadolinium concentrations and VIF parameters, and that the variation of the parameters due to slice location within a patient was significantly lower than the intra patient variation. Intrapatient, interscan differences were significantly less marked than inter-patient differences showing a good intraclass correlation coefficient. We did encounter a MRI protocol dependence of the VIF fitting parameters. The correction algorithm significantly improved the reproducibility of the fitting parameters. These results support the idea that the use of a patient specific measured AIF, not necessarily averaged over a large volume, offers a significant benefit with respect to an external AIF or a measured cohort average AIF.
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Affiliation(s)
- Cristina Lavini
- Department of Radiology, Academic Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
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Janssen MHM, Aerts HJWL, Buijsen J, Lambin P, Lammering G, Öllers MC. Repeated positron emission tomography-computed tomography and perfusion-computed tomography imaging in rectal cancer: fluorodeoxyglucose uptake corresponds with tumor perfusion. Int J Radiat Oncol Biol Phys 2011; 82:849-55. [PMID: 21392896 DOI: 10.1016/j.ijrobp.2010.10.029] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2010] [Revised: 09/08/2010] [Accepted: 10/06/2010] [Indexed: 12/16/2022]
Abstract
PURPOSE The purpose of this study was to analyze both the intratumoral fluorodeoxyglucose (FDG) uptake and perfusion within rectal tumors before and after hypofractionated radiotherapy. METHODS AND MATERIALS Rectal cancer patients, referred for preoperative hypofractionated radiotherapy (RT), underwent FDG-positron emission tomography (PET)-computed tomography (CT) and perfusion-CT (pCT) imaging before the start of hypofractionated RT and at the day of the last RT fraction. The pCT-images were analyzed using the extended Kety model, quantifying tumor perfusion with the pharmacokinetic parameters K(trans), v(e), and v(p). The mean and maximum FDG uptake based on the standardized uptake value (SUV) and transfer constant (K(trans)) within the tumor were correlated. Also, the tumor was subdivided into eight subregions and for each subregion the mean and maximum SUVs and K(trans) values were assessed and correlated. Furthermore, the mean FDG uptake in voxels presenting with the lowest 25% of perfusion was compared with the FDG uptake in the voxels with the 25% highest perfusion. RESULTS The mean and maximum K(trans) values were positively correlated with the corresponding SUVs (ρ = 0.596, p = 0.001 and ρ = 0.779, p < 0.001). Also, positive correlations were found for K(trans) values and SUVs within the subregions (mean, ρ = 0.413, p < 0.001; and max, ρ = 0.540, p < 0.001). The mean FDG uptake in the 25% highest-perfused tumor regions was significantly higher compared with the 25% lowest-perfused regions (10.6% ± 5.1%, p = 0.017). During hypofractionated radiotherapy, stable mean (p = 0.379) and maximum (p = 0.280) FDG uptake levels were found, whereas the mean (p = 0.040) and maximum (p = 0.003) K(trans) values were found to significantly increase. CONCLUSION Highly perfused rectal tumors presented with higher FDG-uptake levels compared with relatively low perfused tumors. Also, intratumor regions with a high FDG uptake demonstrated with higher levels of perfusion than regions with a relatively low FDG-uptake. Early after hypofractionated RT, stable FDG uptake levels were found, whereas tumor perfusion was found to significantly increase.
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Affiliation(s)
- Marco H M Janssen
- Department of Radiation Oncology, Maastricht University Medical Center, Maastricht, The Netherlands.
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Li W, Griswold M, Yu X. Rapid T1 mapping of mouse myocardium with saturation recovery Look-Locker method. Magn Reson Med 2011; 64:1296-303. [PMID: 20632410 DOI: 10.1002/mrm.22544] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Dynamic contrast-enhanced MRI using gadolinium or manganese provides unique characterization of myocardium and its pathology. In this study, an electrocardiography (ECG) triggered saturation recovery Look-Locker method was developed and validated for fast cardiac T(1) mapping in small animal models. By sampling the initial portion of the longitudinal magnetization recovery curve, high temporal resolution (∼ 3 min) can be achieved at a high spatial resolution (195 × 390 μm2) in mouse heart without the aid of parallel imaging or echo-planar imaging. Validation studies were performed both in vitro on a phantom and in vivo on C57BL/6 mice (n = 6). Our results showed a strong agreement between T(1) measured by saturation recovery Look-Locker and by the standard saturation recovery method in vitro or inversion recovery Look-Locker in vivo. The utility of saturation recovery Look-Locker in dynamic contrast-enhanced MRI studies was demonstrated in manganese-enhanced MRI experiments in mice. Our results suggest that saturation recovery Look-Locker can provide rapid and accurate cardiac T(1) mapping for studies using small animal models.
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Affiliation(s)
- Wen Li
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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Effects of inflow and radiofrequency spoiling on the arterial input function in dynamic contrast-enhanced MRI: A combined phantom and simulation study. Magn Reson Med 2011; 65:1670-9. [DOI: 10.1002/mrm.22760] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2010] [Revised: 11/04/2010] [Accepted: 11/24/2010] [Indexed: 02/04/2023]
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Liu HL, Wu YY, Yang WS, Chen CF, Lim KE, Hsu YY. Is Weisskoff model valid for the correction of contrast agent extravasation with combined T1 and T2∗ effects in dynamic susceptibility contrast MRI? Med Phys 2011; 38:802-9. [DOI: 10.1118/1.3534197] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Use of dynamic contrast-enhanced MRI to measure subtle blood-brain barrier abnormalities. Magn Reson Imaging 2010; 29:305-14. [PMID: 21030178 PMCID: PMC4025605 DOI: 10.1016/j.mri.2010.09.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2009] [Revised: 07/16/2010] [Accepted: 09/04/2010] [Indexed: 11/22/2022]
Abstract
There is growing interest in investigating the role of subtle changes in blood–brain barrier (BBB) function in common neurological disorders and the possible use of imaging techniques to assess these abnormalities. Some studies have used dynamic contrast-enhanced MR imaging (DCE-MRI) and these have demonstrated much smaller signal changes than obtained from more traditional applications of the technique, such as in intracranial tumors and multiple sclerosis. In this work, preliminary results are presented from a DCE-MRI study of patients with mild stroke classified according to the extent of visible underlying white matter abnormalities. These data are used to estimate typical signal enhancement profiles in different tissue types and by degrees of white matter abnormality. The effect of scanner noise, drift and different intrinsic tissue properties on signal enhancement data is also investigated and the likely implications for interpreting the enhancement profiles are discussed. No significant differences in average signal enhancement or contrast agent concentration were observed between patients with different degrees of white matter abnormality, although there was a trend towards greater signal enhancement with more abnormal white matter. Furthermore, the results suggest that many of the factors considered introduce uncertainty of a similar magnitude to expected effect sizes, making it unclear whether differences in signal enhancement are truly reflective of an underlying BBB abnormality or due to an unrelated effect. As the ultimate aim is to achieve a reliable quantification of BBB function in subtle disorders, this study highlights the factors which may influence signal enhancement and suggests that further work is required to address the challenging problems of quantifying contrast agent concentration in healthy and diseased living human tissue and of establishing a suitable model to enable quantification of relevant physiological parameters. Meanwhile, it is essential that future studies use an appropriate control group to minimize these influences.
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Schabel MC, Morrell GR, Oh KY, Walczak CA, Barlow RB, Neumayer LA. Pharmacokinetic mapping for lesion classification in dynamic breast MRI. J Magn Reson Imaging 2010; 31:1371-8. [PMID: 20512889 DOI: 10.1002/jmri.22179] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
PURPOSE To prospectively investigate whether a rapid dynamic MRI protocol, in conjunction with pharmacokinetic modeling, could provide diagnostically useful information for discriminating biopsy-proven benign lesions from malignancies. MATERIALS AND METHODS Patients referred to breast biopsy based on suspicious screening findings were eligible. After anatomic imaging, patients were scanned using a dynamic protocol with complete bilateral breast coverage. Maps of pharmacokinetic parameters representing transfer constant (K(trans)), efflux rate constant (k(ep)), blood plasma volume fraction (v(p)), and extracellular extravascular volume fraction (v(e)) were averaged over lesions and used, with biopsy results, to generate receiver operating characteristic curves for linear classifiers using one, two, or three parameters. RESULTS Biopsy and imaging results were obtained from 93 lesions in 74 of 78 study patients. Classification based on K(trans) and k(ep) gave the greatest accuracy, with an area under the receiver operating characteristic curve of 0.915, sensitivity of 91%, and specificity of 85%, compared with values of 88% and 68%, respectively, obtained in a recent study of clinical breast MRI in a similar patient population. CONCLUSION Pharmacokinetic classification of breast lesions is practical on modern MRI hardware and provides significant accuracy for identification of malignancies. Sensitivity of a two-parameter linear classifier is comparable to that reported in a recent multicenter study of clinical breast MRI, while specificity is significantly higher.
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Affiliation(s)
- Matthias C Schabel
- University of Utah Department of Radiology, Salt Lake City, Utah 84132, USA.
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Revert Ventura A, Sanz-Requena R, Martí-Bonmatí L, Jornet J, Piquer J, Cremades A, Carot J. Análisis nosológico con parámetros de perfusión tisular de RM obtenidos mediante los modelos monocompartimental y farmacocinético en los glioblastomas cerebrales. RADIOLOGIA 2010; 52:432-41. [DOI: 10.1016/j.rx.2010.03.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2009] [Revised: 03/17/2010] [Accepted: 03/25/2010] [Indexed: 10/19/2022]
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Schabel MC, Fluckiger JU, DiBella EVR. A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: I. Simulations. Phys Med Biol 2010; 55:4783-806. [PMID: 20679691 DOI: 10.1088/0031-9155/55/16/011] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Widespread adoption of quantitative pharmacokinetic modeling methods in conjunction with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has led to increased recognition of the importance of obtaining accurate patient-specific arterial input function (AIF) measurements. Ideally, DCE-MRI studies use an AIF directly measured in an artery local to the tissue of interest, along with measured tissue concentration curves, to quantitatively determine pharmacokinetic parameters. However, the numerous technical and practical difficulties associated with AIF measurement have made the use of population-averaged AIF data a popular, if sub-optimal, alternative to AIF measurement. In this work, we present and characterize a new algorithm for determining the AIF solely from the measured tissue concentration curves. This Monte Carlo blind estimation (MCBE) algorithm estimates the AIF from the subsets of D concentration-time curves drawn from a larger pool of M candidate curves via nonlinear optimization, doing so for multiple (Q) subsets and statistically averaging these repeated estimates. The MCBE algorithm can be viewed as a generalization of previously published methods that employ clustering of concentration-time curves and only estimate the AIF once. Extensive computer simulations were performed over physiologically and experimentally realistic ranges of imaging and tissue parameters, and the impact of choosing different values of D and Q was investigated. We found the algorithm to be robust, computationally efficient and capable of accurately estimating the AIF even for relatively high noise levels, long sampling intervals and low diversity of tissue curves. With the incorporation of bootstrapping initialization, we further demonstrated the ability to blindly estimate AIFs that deviate substantially in shape from the population-averaged initial guess. Pharmacokinetic parameter estimates for K(trans), k(ep), v(p) and v(e) all showed relative biases and uncertainties of less than 10% for measurements having a temporal sampling rate of 4 s and a concentration measurement noise level of sigma = 0.04 mM. A companion paper discusses the application of the MCBE algorithm to DCE-MRI data acquired in eight patients with malignant brain tumors.
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Affiliation(s)
- Matthias C Schabel
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah Health Sciences Center, 729 Arapeen Drive, Salt Lake City, UT 84108-1218, USA.
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Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response. Br J Cancer 2010; 103:486-97. [PMID: 20628390 PMCID: PMC2939778 DOI: 10.1038/sj.bjc.6605773] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) contains crucial information about tumour heterogeneity and the transport limitations that reduce drug efficacy. Mathematical modelling of drug delivery and cellular responsiveness based on underutilised DCE-MRI data has the unique potential to predict therapeutic responsiveness for individual patients. Methods: To interpret DCE-MRI data, we created a modelling framework that operates over multiple time and length scales and incorporates intracellular metabolism, nutrient and drug diffusion, trans-vascular permeability, and angiogenesis. The computational methodology was used to analyse DCE-MR images collected from eight breast cancer patients at Baystate Medical Center in Springfield, MA. Results: Computer simulations showed that trans-vascular transport was correlated with tumour aggressiveness because increased vessel growth and permeability provided more nutrients for cell proliferation. Model simulations also indicate that vessel density minimally affects tissue growth and drug response, and nutrient availability promotes growth. Finally, the simulations indicate that increased transport heterogeneity is coupled with increased tumour growth and poor drug response. Conclusion: Mathematical modelling based on DCE-MRI has the potential to aid treatment decisions and improve overall cancer care. This model is the critical first step in the creation of a comprehensive and predictive computational method.
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Kierkels RG, Backes WH, Janssen MH, Buijsen J, Beets-Tan RG, Lambin P, Lammering G, Oellers MC, Aerts HJ. Comparison Between Perfusion Computed Tomography and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Rectal Cancer. Int J Radiat Oncol Biol Phys 2010; 77:400-8. [DOI: 10.1016/j.ijrobp.2009.05.015] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2009] [Revised: 05/19/2009] [Accepted: 05/19/2009] [Indexed: 11/24/2022]
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Heisen M, Fan X, Buurman J, van Riel NAW, Karczmar GS, ter Haar Romeny BM. The influence of temporal resolution in determining pharmacokinetic parameters from DCE-MRI data. Magn Reson Med 2010; 63:811-6. [PMID: 20187187 PMCID: PMC3076555 DOI: 10.1002/mrm.22171] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
We investigated the influence of the temporal resolution of dynamic contrast-enhanced MRI data on pharmacokinetic parameter estimation. Dynamic Gd-DTPA (Gadolinium-diethylene triamine pentaacetic acid) enhanced MRI data of implanted prostate tumors on rat hind limb were acquired at 4.7 T, with a temporal resolution of approximately 5 sec. The data were subsequently downsampled to temporal resolutions in the range of 15 sec to 85 sec, using a strategy that involves a recombination of k-space data. A basic two-compartment model was fit to the contrast agent uptake curves. The results demonstrated that as temporal resolution decreases, the volume transfer constant (K(trans)) is progressively underestimated (approximately 4% to approximately 25%), and the fractional extravascular extracellular space (v(e)) is progressively overestimated (approximately 1% to approximately 10%). The proposed downsampling strategy simulates the influence of temporal resolution more realistically than simply downsampling by removing samples.
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Affiliation(s)
- Marieke Heisen
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
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