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Zhang Y, Wang F, Huang Y. PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma. Clinics (Sao Paulo) 2024; 79:100367. [PMID: 38692010 PMCID: PMC11070665 DOI: 10.1016/j.clinsp.2024.100367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/11/2024] [Accepted: 04/11/2024] [Indexed: 05/03/2024] Open
Abstract
OBJECTIVE This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG). METHODS Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value. RESULTS PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90. CONCLUSION PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.
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Affiliation(s)
- Yi Zhang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China.
| | - Feng Wang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
| | - YongLi Huang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
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2
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Fatania K, Frood R, Tyyger M, McDermott G, Fernandez S, Shaw GC, Boissinot M, Salvatore D, Ottobrini L, Teh I, Wright J, Bailey MA, Koch-Paszkowski J, Schneider JE, Buckley DL, Murray L, Scarsbrook A, Short SC, Currie S. Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma. Cancers (Basel) 2022; 14:3485. [PMID: 35884545 PMCID: PMC9315674 DOI: 10.3390/cancers14143485] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/11/2022] [Accepted: 07/15/2022] [Indexed: 12/03/2022] Open
Abstract
Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.
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Affiliation(s)
- Kavi Fatania
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Russell Frood
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
| | - Marcus Tyyger
- Department of Medical Physics, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK; (M.T.); (G.M.)
| | - Garry McDermott
- Department of Medical Physics, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK; (M.T.); (G.M.)
| | - Sharon Fernandez
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Gary C. Shaw
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Marjorie Boissinot
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Daniela Salvatore
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Segrate, Italy; (D.S.); (L.O.)
| | - Luisa Ottobrini
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Segrate, Italy; (D.S.); (L.O.)
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 20054 Segrate, Italy
| | - Irvin Teh
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - John Wright
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Marc A. Bailey
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
- Leeds Vascular Institute, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK
| | - Joanna Koch-Paszkowski
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Jurgen E. Schneider
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - David L. Buckley
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Louise Murray
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Andrew Scarsbrook
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Susan C. Short
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Stuart Currie
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
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Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:1342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
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Zhou Q, Xue C, Ke X, Zhou J. Treatment Response and Prognosis Evaluation in High-Grade Glioma: An Imaging Review Based on MRI. J Magn Reson Imaging 2022; 56:325-340. [PMID: 35129845 DOI: 10.1002/jmri.28103] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/25/2022] [Accepted: 01/25/2022] [Indexed: 12/19/2022] Open
Abstract
In recent years, the development of advanced magnetic resonance imaging (MRI) technology and machine learning (ML) have created new tools for evaluating treatment response and prognosis of patients with high-grade gliomas (HGG); however, patient prognosis has not improved significantly. This is mainly due to the heterogeneity between and within HGG tumors, resulting in standard treatment methods not benefitting all patients. Moreover, the survival of patients with HGG is not only related to tumor cells, but also to noncancer cells in the tumor microenvironment (TME). Therefore, during preoperative diagnosis and follow-up treatment of patients with HGG, noninvasive imaging markers are needed to characterize intratumoral heterogeneity, and then to evaluate treatment response and predict prognosis, timeously adjust treatment strategies, and achieve individualized diagnosis and treatment. In this review, we summarize the research progress of conventional MRI, advanced MRI technology, and ML in evaluation of treatment response and prognosis of patients with HGG. We further discuss the significance of the TME in the prognosis of HGG patients, associate imaging features with the TME, indirectly reflecting the heterogeneity within the tumor, and shifting treatment strategies from tumor cells alone to systemic therapy of the TME, which may be a major development direction in the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 4.
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Affiliation(s)
- Qing Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.,Second Clinical School, Lanzhou University, Lanzhou, Gansu, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, Gansu, China
| | - Caiqiang Xue
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.,Second Clinical School, Lanzhou University, Lanzhou, Gansu, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, Gansu, China
| | - Xiaoai Ke
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, Gansu, China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, Gansu, China
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5
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Mohan S, Wang S, Chawla S, Abdullah K, Desai A, Maloney E, Brem S. Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma. Surg Neurol Int 2021; 12:337. [PMID: 34345478 PMCID: PMC8326072 DOI: 10.25259/sni_353_2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 06/09/2021] [Indexed: 11/04/2022] Open
Abstract
Background Glioblastoma (GBM) is the most common malignant brain tumor and carries a dismal prognosis. Attempts to develop biologically targeted therapies are challenging as the blood-brain barrier can limit drugs from reaching their target when administered through conventional (intravenous or oral) routes. Furthermore, systemic toxicity of drugs often limits their therapeutic potential. To circumvent these problems, convection-enhanced delivery (CED) provides direct, targeted, intralesional therapy with a secondary objective to alter the tumor microenvironment from an immunologically "cold" (nonresponsive) to an "inflamed" (immunoresponsive) tumor. Case Description We report a patient with right occipital recurrent GBM harboring poor prognostic genotypes who was treated with MRI-guided CED of a fusion protein MDNA55 (a targeted toxin directed toward the interleukin-4 receptor). The patient underwent serial anatomical, diffusion, and perfusion MRI scans before initiation of targeted therapy and at 1, 3-month posttherapy. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume was noted at follow-up periods relative to baseline. Conclusion Our findings suggest that diffusion and perfusion MRI techniques may be useful in evaluating early response to CED of MDNA55 in recurrent GBM patients.
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Affiliation(s)
- Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sanjeev Chawla
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Kalil Abdullah
- Department of Neurosurgery, University of Texas-Southwestern Medical Center, Dallas, Texas, United States
| | - Arati Desai
- Department of Medicine Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Eileen Maloney
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
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6
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Kim MM, Aryal MP, Sun Y, Parmar HA, Li P, Schipper M, Wahl DR, Lawrence TS, Cao Y. Response assessment during chemoradiation using a hypercellular/hyperperfused imaging phenotype predicts survival in patients with newly diagnosed glioblastoma. Neuro Oncol 2021; 23:1537-1546. [PMID: 33599755 DOI: 10.1093/neuonc/noab038] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Adversely prognostic hypercellular and hyperperfused regions of glioblastoma (GBM) predict progression-free survival, and are a novel target for dose-intensified chemoradiation (chemoRT) recently implemented in a phase II clinical trial. As a secondary aim, we hypothesized that dose-intensified chemoRT would induce greater mid-treatment response of hypercellular/hyperperfused tumor regions vs standard chemoradiation, and that early response would improve overall survival (OS). METHODS Forty-nine patients with newly diagnosed GBM underwent prospective, multiparametric high b value diffusion-weighted MRI (DW-MRI) and perfusion dynamic contrast-enhanced MRI (DCE-MRI) pre-RT and 3-4 weeks into RT. The hypercellular tumor volume (TVHCV, mean contralateral normal brain + 2SD) and hyperperfused tumor volume (TVCBV, contralateral normal frontal gray matter + 1SD) were generated using automated thresholding. Twenty-six patients were enrolled on a dose-escalation trial targeting TVHCV/TVCBV with 75 Gy in 30 fractions, and 23 non-trial patients comprised the control group. OS was estimated using the Kaplan-Meier method and compared using the log-rank test. The effect of TVHCV/TVCBV and Gd-enhanced tumor volume on OS was assessed using multivariable Cox proportional-hazard regression. RESULTS Most patients had gross total (47%) or subtotal resection (37%), 25% were MGMT-methylated. Patients treated on the dose-escalation trial had significantly greater reduction in TVHCV/TVCBV (41% reduction, IQR 17%-75%) vs non-trial patients (6% reduction, IQR 6%-22%, P = .002). An increase in TVHCV/TVCBV during chemoRT was associated with worse OS (adjusted hazard ratio [aHR] 1.2, 95%CI 1.0-1.4, P = .02), while pre-treatment tumor volumes (P > .5) and changes in Gd-enhanced volume (P = .9) were not. CONCLUSIONS Multiparametric MRI permits identification of therapeutic resistance during chemoRT and supports adaptive strategies in future trials.
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Affiliation(s)
- Michelle M Kim
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Madhava P Aryal
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Yilun Sun
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Hemant A Parmar
- Department of Radiology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Pin Li
- Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew Schipper
- Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel R Wahl
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Yue Cao
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, The University of Michigan, Ann Arbor, Michigan, USA
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7
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Advanced magnetic resonance imaging to support clinical drug development for malignant glioma. Drug Discov Today 2020; 26:429-441. [PMID: 33249294 DOI: 10.1016/j.drudis.2020.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/18/2020] [Indexed: 11/22/2022]
Abstract
Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.
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8
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Kang Y, Hong EK, Rhim JH, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH, Park SW, Choi SH. Prognostic Value of Dynamic Contrast-Enhanced MRI-Derived Pharmacokinetic Variables in Glioblastoma Patients: Analysis of Contrast-Enhancing Lesions and Non-Enhancing T2 High-Signal Intensity Lesions. Korean J Radiol 2020; 21:707-716. [PMID: 32410409 PMCID: PMC7231611 DOI: 10.3348/kjr.2019.0629] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/31/2019] [Accepted: 02/09/2020] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE To evaluate pharmacokinetic variables from contrast-enhancing lesions (CELs) and non-enhancing T2 high signal intensity lesions (NE-T2HSILs) on dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for predicting progression-free survival (PFS) in glioblastoma (GBM) patients. MATERIALS AND METHODS Sixty-four GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. We analyzed the pharmacokinetic variables of the volume transfer constant (Ktrans) and volume fraction of extravascular extracellular space within the CEL and NE-T2HSIL of the entire tumor. Univariate and multivariate Cox regression analyses were performed using preoperative clinical characteristics, pharmacokinetic variables of DCE MR imaging, and postoperative molecular biomarkers to predict PFS. RESULTS The increased mean Ktrans of the CEL, increased 95th percentile Ktrans of the CELs, and absence of methylated O⁶-methylguanine-DNA methyltransferase promoter were relevant adverse variables for PFS in the univariate analysis (p = 0.041, p = 0.032, and p = 0.083, respectively). The Kaplan-Meier survival curves demonstrated that PFS was significantly shorter in patients with a mean Ktrans of the CEL > 0.068 and 95th percentile Ktrans of the CEL>0.223 (log-rank p = 0.038 and p = 0.041, respectively). However, only mean Ktrans of the CEL was significantly associated with PFS (p = 0.024; hazard ratio, 553.08; 95% confidence interval, 2.27-134756.74) in the multivariate Cox proportional hazard analysis. None of the pharmacokinetic variables from NE-T2HSILs were significantly related to PFS. CONCLUSION Among the pharmacokinetic variables extracted from CELs and NE-T2HSILs on preoperative DCE MR imaging, the mean Ktrans of CELs exhibits potential as a useful imaging predictor of PFS in GBM patients.
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Affiliation(s)
- Yeonah Kang
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea.,Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea
| | - Eun Kyoung Hong
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Jung Hyo Rhim
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Roh Eul Yoo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Ji Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Chul Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Sun Won Park
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
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9
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Xu L, Ge X, Sun N, Liu X. Dynamic contrast-enhanced MRI histogram parameters predict progression-free survival in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiotherapy. Acta Radiol 2020; 61:1316-1325. [PMID: 32053003 DOI: 10.1177/0284185120903139] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND There is increased interest in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting the outcomes of patients with advanced esophageal cancer. PURPOSE To explore whether DCE-MRI histogram parameters can predict 12-month progression-free survival (PFS) in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiation therapy (CRT). MATERIAL AND METHODS This retrospective study enrolled 134 patients with advanced esophageal squamous carcinoma who were receiving CRT. The pre-CRT DCE-MRI histogram parameters (median, mean, SD, skewness, kurtosis, and 10th and 90th percentiles) of Ktrans, Kep, and Ve were collected. PFS analyses were performed using the Kaplan-Meier method and log-rank tests to compute the survival curves. The significant prognostic predictors among the data characteristics and DCE-MRI parameters were determined using multivariate Cox proportional hazards regression analyses. RESULTS There were 65 good responders (PFS ≥ 12 months) and 69 poor responders (PFS < 12 months). The median and mean values of Ktrans were higher, and the kurtosis value of Ktrans was lower in good responders. The median, mean, and 10th and 90th percentile values of Ktrans were higher, and the kurtosis values of Ktrans and Ve were lower in good responders. The PFS of patients aged ≥60 years, a CR effect, or a 10th percentile value of Ktrans ≥0.13 was increased (P < 0.001, <0.001, and 0.014, respectively). CONCLUSION DCE-MRI histogram parameters can be used to evaluate the response to CRT in patients with advanced esophageal squamous carcinoma. The 10th percentile value of Ktrans has significant prognostic value for 12-month PFS.
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Affiliation(s)
- Lulu Xu
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xiaolin Ge
- Department of Radiotherapy, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Nana Sun
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xisheng Liu
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
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10
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Hou W, Li X, Pan H, Xu M, Bi S, Shen Y, Yu Y. Dynamic contrast-enhanced magnetic resonance imaging for monitoring the anti-angiogenesis efficacy in a C6 glioma rat model. Acta Radiol 2020; 61:973-982. [PMID: 31739674 DOI: 10.1177/0284185119887598] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful in predicting responses to angiogenic therapy of malignant tumors. PURPOSE To observe the dynamics of DCE-MRI parameters in evaluating early effects of antiangiogenic therapy in a C6 glioma rat model. MATERIAL AND METHODS The Bevacizumab or vehicle treatment was started from the 14th day after glioma model was established. The treated and control groups (n = 13 per group) underwent DCE-MRI scans on days 0, 1, 3, 5, and 7 after treatment. Tumor volume was calculated according to T2-weighted images. Hematoxylin and eosin, microvessel density (MVD), and proliferating cell nuclear antigen (PCNA) examination were performed on day 7. The MRI parameters between the two groups were compared and correlations with immunohistochemical scores were analyzed. RESULTS The average tumor volume of treated group was significantly lower than that of control group on day 7 (81.764 ± 1.043 vs. 103.634 ± 3.868 mm3, P = 0.002). Ktrans and Kep decreased in the treated group while they increased in the control group. The differences were observed on day 5 (Ktrans: 0.045 ± 0.018 vs. 0.093 ± 0.014 min-1, P < 0.001; Kep: 0.062 ± 0.018 vs. 0.134 ± 0.047 min-1, P = 0.005) and day 7 (Ktrans: 0.032 ± 0.010 vs. 0.115 ± 0.025 min-1, P < 0.001; Kep: 0.045 ± 0.016 vs. 0.144 ± 0.042 min-1, P < 0.001). The difference of Ve was observed on day 5 (0.847 ± 0.248 vs. 0.397 ± 0.151, P = 0.009) and 7 (0.920 ± 0.154 vs. 0.364 ± 0.105, P = 0.006). Ktrans and Kep showed positive correlations with MVD and Ve showed negative correlation with PCNA. CONCLUSION DCE-MRI can assess the changes of early effects of anti-angiogenic therapy in preclinical practice.
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Affiliation(s)
- Weishu Hou
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
| | - Xiaohu Li
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
| | - Hongli Pan
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
| | - Man Xu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
| | - Sixing Bi
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
| | - Yujun Shen
- Biopharmaceutical Research Institute, School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, PR China
| | - Yongqiang Yu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, PR China
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11
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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: 1.8] [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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12
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Hall WA, Paulson ES, van der Heide UA, Fuller CD, Raaymakers BW, Lagendijk JJW, Li XA, Jaffray DA, Dawson LA, Erickson B, Verheij M, Harrington KJ, Sahgal A, Lee P, Parikh PJ, Bassetti MF, Robinson CG, Minsky BD, Choudhury A, Tersteeg RJHA, Schultz CJ. The transformation of radiation oncology using real-time magnetic resonance guidance: A review. Eur J Cancer 2019; 122:42-52. [PMID: 31614288 PMCID: PMC8447225 DOI: 10.1016/j.ejca.2019.07.021] [Citation(s) in RCA: 140] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 07/11/2019] [Accepted: 07/16/2019] [Indexed: 12/11/2022]
Abstract
Radiation therapy (RT) is an essential component of effective cancer care and is used across nearly all cancer types. The delivery of RT is becoming more precise through rapid advances in both computing and imaging. The direct integration of magnetic resonance imaging (MRI) with linear accelerators represents an exciting development with the potential to dramatically impact cancer research and treatment. These impacts extend beyond improved imaging and dose deposition. Real-time MRI-guided RT is actively transforming the work flows and capabilities of virtually every aspect of RT. It has the opportunity to change entirely the delivery methods and response assessments of numerous malignancies. This review intends to approach the topic of MRI-based RT guidance from a vendor neutral and international perspective. It also aims to provide an introduction to this topic targeted towards oncologists without a speciality focus in RT. Speciality implications, areas for physician education and research opportunities are identified as they are associated with MRI-guided RT. The uniquely disruptive implications of MRI-guided RT are discussed and placed in context. We further aim to describe and outline important future changes to the speciality of radiation oncology that will occur with MRI-guided RT. The impacts on RT caused by MRI guidance include target identification, RT planning, quality assurance, treatment delivery, training, clinical workflow, tumour response assessment and treatment scheduling. In addition, entirely novel research areas that may be enabled by MRI guidance are identified for future investigation.
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Affiliation(s)
- William A Hall
- Medical College of Wisconsin, Department of Radiation Oncology, USA.
| | - Eric S Paulson
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | | | - Clifton D Fuller
- University of Texas, MD Anderson Cancer Center, USA; Netherlands Cancer Institute, the Netherlands
| | - B W Raaymakers
- UMC Utrecht, Department of Radiotherapy, the Netherlands
| | | | - X Allen Li
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | - David A Jaffray
- Princess Margaret Cancer Centre, University of Toronto, Canada
| | - Laura A Dawson
- Princess Margaret Cancer Centre, University of Toronto, Canada
| | - Beth Erickson
- Medical College of Wisconsin, Department of Radiation Oncology, USA
| | - Marcel Verheij
- Radbound University Medical Center, Nijmegen, the Netherlands
| | - Kevin J Harrington
- The Institute of Cancer Research, The Royal Marsden NHS Foundation Trust, UK
| | - Arjun Sahgal
- Sunnybrook Health Sciences Centre, University of Toronto, Canada
| | - Percy Lee
- University of California, Los Angeles, USA
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13
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Qin Y, Yu X, Hou J, Hu Y, Li F, Wen L, Lu Q, Liu S. Prognostic Value of the Pretreatment Primary Lesion Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma. Acad Radiol 2019; 26:1473-1482. [PMID: 30772137 DOI: 10.1016/j.acra.2019.01.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 01/22/2019] [Accepted: 01/22/2019] [Indexed: 12/19/2022]
Abstract
RATIONALE AND OBJECTIVES Early identifying the long-term outcome of chemoradiotherapy is helpful for personalized treatment in nasopharyngeal carcinoma (NPC). This study aimed to investigate the prognostic significance of pretreatment quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for NPC. MATERIALS AND METHODS The relationships between the prognosis and pretreatment quantitative DCE-MRI (Ktrans, Kep, Ve, and fpv) values of the primary tumors were analyzed in 134 NPC patients who received chemoradiotherapy. Kaplan-Meier analysis was performed to calculate the local-regional relapse-free survival (LRRFS), local relapse-free survival (LRFS), regional relapse-free survival, distant metastasis-free survival (DMFS), progression-free survival, and overall survival rates. Cox proportional hazards model was used to explore the independent predictors for prognosis. RESULTS The local-failure group had significantly higher Ve (p = 0.033) and fpv values (p = 0.005) than the non-local-failure group. The Ve-high group showed significantly lower LRRFS (p = 0.015) , LRFS (p = 0.013) , DMFS (p = 0.027) and progression-free survival (p = 0.035) rates than the Ve-low group. The fpv-high group exhibited significantly lower LRRFS (p = 0.004) and LRFS (p = 0.005) rates than the fpv-low group. Ve was the independent predictor for LRRFS (p = 0.008), LRFS (p = 0.007), DMFS (p = 0.041), and overall survival (p = 0.022). fpv was the independent indicator for LRRFS (p = 0.003) and LRFS (p = 0.001). CONCLUSION Baseline quantitative DCE-MRI may be valuable in predicting the prognosis for NPC.
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Affiliation(s)
- Yuhui Qin
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Xiaoping Yu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China.
| | - Jing Hou
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Ying Hu
- Department of Radiotherapy, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, PR China
| | - Feiping Li
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Lu Wen
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Qiang Lu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
| | - Siye Liu
- Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University and Hunan Cancer Hospital, 283 Tongzipo Road, Changsha 410013, Hunan, PR China
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14
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Meissner J, Korzowski A, Regnery S, Goerke S, Breitling J, Floca RO, Debus J, Schlemmer H, Ladd ME, Bachert P, Adeberg S, Paech D. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T. J Magn Reson Imaging 2019; 50:1268-1277. [DOI: 10.1002/jmri.26702] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/15/2019] [Accepted: 02/15/2019] [Indexed: 12/17/2022] Open
Affiliation(s)
- Jan‐Eric Meissner
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Andreas Korzowski
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Sebastian Regnery
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | - Steffen Goerke
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Johannes Breitling
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- MPI for Nuclear PhysicsMax‐Planck‐Society Heidelberg Germany
| | - Ralf Omar Floca
- Division of Medical Image ComputingGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Jürgen Debus
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | | | - Mark Edward Ladd
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- Faculty of MedicineUniversity of Heidelberg Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
| | - Sebastian Adeberg
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Daniel Paech
- Division of RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
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15
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Dynamic contrast-enhanced MRI of malignant pleural mesothelioma: a comparative study of pharmacokinetic models and correlation with mRECIST criteria. Cancer Imaging 2019; 19:10. [PMID: 30813957 PMCID: PMC6391827 DOI: 10.1186/s40644-019-0189-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 01/16/2019] [Indexed: 12/29/2022] Open
Abstract
Background Malignant pleural mesothelioma (MPM) is a rare and aggressive thoracic malignancy that is difficult to cure. Dynamic contrast-enhanced (DCE) MRI is a functional imaging technique used to analyze tumor microvascular properties and to monitor therapy response. Purpose of this study was to compare two tracer kinetic models, the extended Tofts (ET) and the adiabatic approximation tissue homogeneity model (AATH) for analysis of DCE-MRI and examine the value of the DCE parameters to predict response to chemotherapy in patients with MPM. Method This prospective, longitudinal, single tertiary radiology center study was conducted between October 2013 and July 2015. Patient underwent DCE-MRI studies at three time points: prior to therapy, during and after cisplatin-based chemotherapy. The images were analyzed using ET and AATH models. In short-term follow-up, the patients were classified as having disease control or progressive disease according to modified response evaluation criteria in solid tumors (mRECIST) criteria. Receiver operating characteristic curve analysis was used to examine specificity and sensitivity of DCE parameters for predicting response to therapy. Comparison tests were used to analyze whether derived parameters are interchangeable between the two models. Results Nineteen patients form the study population. The results indicate that the derived parameters are not interchangeable between the models. Significant correlation with response to therapy was found for AATH-calculated median pre-treatment efflux rate (kep) showing sensitivity of 83% and specificity of 100% (AUC 0.9). ET-calculated maximal pre-treatment kep showed 100% sensitivity and specificity for predicting treatment response during the early phase of the therapy and reached a favorable trend to significant prognostic value post-therapy. Conclusion Both models show potential in predicting response to therapy in MPM. High pre-treatment kep values suggest MPM disease control post-chemotherapy. Electronic supplementary material The online version of this article (10.1186/s40644-019-0189-5) contains supplementary material, which is available to authorized users.
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16
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Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 2018; 8:17062. [PMID: 30459364 PMCID: PMC6244161 DOI: 10.1038/s41598-018-34820-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 10/24/2018] [Indexed: 12/18/2022] Open
Abstract
Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1–6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (Ktrans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 Ktrans within the tumor region (week 5 Ktrans: HR = 1.038, p = 0.003; pre-C1 Ktrans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and Ktrans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.
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17
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Margiewicz S, Cordova C, Chi AS, Jain R. State of the Art Treatment and Surveillance Imaging of Glioblastomas. Semin Roentgenol 2017; 53:23-36. [PMID: 29405952 DOI: 10.1053/j.ro.2017.11.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
| | - Christine Cordova
- Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY
| | - Andrew S Chi
- Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY
| | - Rajan Jain
- Department of Radiology, NYU School of Medicine, New York, NY; Department of Neurosurgery, NYU School of Medicine, New York, NY.
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18
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Dehkordi ANV, Kamali-Asl A, Wen N, Mikkelsen T, Chetty IJ, Bagher-Ebadian H. DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique. NMR IN BIOMEDICINE 2017; 30:e3739. [PMID: 28543885 DOI: 10.1002/nbm.3739] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 03/28/2017] [Accepted: 03/30/2017] [Indexed: 06/07/2023]
Abstract
This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimated by the model selection (MS) technique in dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data analysis, and patient age. DCE-MRI investigations of 33 treatment-naïve patients with GBM were studied. Using the modified Tofts model and MS technique, the following physiologically nested models were constructed: Model 1, no vascular leakage (normal tissue); Model 2, leakage without efflux; Model 3, leakage with bidirectional exchange (influx and efflux). For each patient, the PK parameters of the three models were estimated as follows: blood plasma volume (vp ) for Model 1; vp and volume transfer constant (Ktrans ) for Model 2; vp , Ktrans and rate constant (kep ) for Model 3. Using Cox regression analysis, the best combination of the estimated PK parameters, together with patient age, was identified for the design and training of ANFIS. A K-fold cross-validation (K = 33) technique was employed for training, testing and optimization of ANFIS. Given the survival time distribution, three classes of survival were determined and a confusion matrix for the correct classification fraction (CCF) of the trained ANFIS was estimated as an accuracy index of ANFIS's performance. Patient age, kep and ve (Ktrans /kep ) of Model 3, and Ktrans of Model 2, were found to be the most effective parameters for training ANFIS. The CCF of the trained ANFIS was 84.8%. High diagonal elements of the confusion matrix (81.8%, 90.1% and 81.8% for Class 1, Class 2 and Class 3, respectively), with low off-diagonal elements, strongly confirmed the robustness and high performance of the trained ANFIS for predicting the three survival classes. This study confirms that DCE-MRI PK analysis, combined with the MS technique and ANFIS, allows the construction of a DCE-MRI-based fuzzy integrated predictor for the prediction of the survival of patients with GBM.
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Affiliation(s)
- Azimeh N V Dehkordi
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Alireza Kamali-Asl
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Tom Mikkelsen
- Department of Neurosurgery, Henry Ford Hospital, Detroit, Michigan, USA
- Ontario Brain Institute, Toronto, Ontario, Canada
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Hassan Bagher-Ebadian
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
- Department of Physics, Oakland University, Rochester, Michigan, USA
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Ulyte A, Katsaros VK, Liouta E, Stranjalis G, Boskos C, Papanikolaou N, Usinskiene J, Bisdas S. Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients. Neuroradiology 2016; 58:1197-1208. [PMID: 27796446 PMCID: PMC5153415 DOI: 10.1007/s00234-016-1741-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 08/16/2016] [Indexed: 12/22/2022]
Abstract
Introduction The prognostic value of the dynamic contrast-enhanced (DCE) MRI perfusion and its histogram analysis-derived metrics is not well established for high-grade glioma (HGG) patients. The aim of this prospective study was to investigate DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), reverse transfer constant (kep), and initial area under gadolinium concentration time curve (IAUGC) as predictors of progression-free (PFS) and overall survival (OS) in HGG patients. Methods Sixty-nine patients with suspected anaplastic astrocytoma or glioblastoma underwent preoperative DCE-MRI scans. DCE perfusion whole tumor region histogram parameters, clinical details, and PFS and OS data were obtained. Univariate, multivariate, and Kaplan–Meier survival analyses were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify perfusion parameters with the best differentiation performance. Results On univariate analysis, ve and skewness of vp had significant negative impacts, while kep had significant positive impact on OS (P < 0.05). ve was also a negative predictor of PFS (P < 0.05). Patients with lower ve and IAUGC had longer median PFS and OS on Kaplan–Meier analysis (P < 0.05). Ktrans and ve could also differentiate grade III from IV gliomas (area under the curve 0.819 and 0.791, respectively). Conclusions High ve is a consistent predictor of worse PFS and OS in HGG glioma patients. vp skewness and kep are also predictive for OS. Ktrans and ve demonstrated the best diagnostic performance for differentiating grade III from IV gliomas.
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Affiliation(s)
- Agne Ulyte
- Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | - Vasileios K Katsaros
- Department of Advanced Imaging Modalities - CT and MRI, General Anticancer and Oncological Hospital "St. Savvas", Athens, Greece.,Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Evangelia Liouta
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Georgios Stranjalis
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Christos Boskos
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece.,Department of Radiation Oncology, General Anticancer and Oncological Hospital "St. Savvas", Athens, Greece
| | - Nickolas Papanikolaou
- Department of Radiology, Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Jurgita Usinskiene
- National Cancer Institute, Vilnius, Lithuania.,Affidea Lietuva, Vilnius, Lithuania
| | - Sotirios Bisdas
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals, Box 65, Queen Square 8-11, London, WC1N 3BG, UK.
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