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Filss CP, Cramer J, Löher S, Lohmann P, Stoffels G, Stegmayr C, Kocher M, Heinzel A, Galldiks N, Wittsack HJ, Sabel M, Neumaier B, Scheins J, Shah NJ, Meyer PT, Mottaghy FM, Langen KJ. Assessment of Brain Tumour Perfusion Using Early-Phase 18F-FET PET: Comparison with Perfusion-Weighted MRI. Mol Imaging Biol 2024; 26:36-44. [PMID: 37848641 PMCID: PMC10827807 DOI: 10.1007/s11307-023-01861-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/10/2023] [Accepted: 09/19/2023] [Indexed: 10/19/2023]
Abstract
PURPOSE Morphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET). PROCEDURE Using a hybrid brain PET/MRI scanner, PWI and dynamic 18F-FET PET were performed in 33 patients with cerebral glioma and four patients with highly vascularized meningioma. The time interval from 0 to 2 min p.i. was selected to best reflect the blood pool phase in 18F-FET PET. For each patient, maps of MR-rCBV, early 18F-FET PET (0-2 min p.i.) and late 18F-FET PET (20-40 min p.i.) were generated and coregistered. Volumes of interest were placed on the tumour (VOI-TU) and normal-appearing brain (VOI-REF). The correlation between tumour-to-brain ratios (TBR) of the different parameters was analysed. In addition, three independent observers evaluated MR-rCBV and early 18F-FET maps (18F-FET-rCBV) for concordance in signal intensity, tumour extent and intratumoural distribution. RESULTS TBRs calculated from MR-rCBV and 18F-FET-rCBV showed a significant correlation (r = 0.89, p < 0.001), while there was no correlation between late 18F-FET PET and MR-rCBV (r = 0.24, p = 0.16) and 18F-FET-rCBV (r = 0.27, p = 0.11). Visual rating yielded widely agreeing findings or only minor differences between MR-rCBV maps and 18F-FET-rCBV maps in 93 % of the tumours (range of three independent raters 91-94%, kappa among raters 0.78-1.0). CONCLUSION Early 18F-FET maps (0-2 min p.i.) in gliomas provide similar information to MR-rCBV maps and may be helpful when PWI is not possible or available. Further studies in gliomas are needed to evaluate whether 18F-FET-rCBV provides the same clinical information as MR-rCBV.
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Affiliation(s)
- Christian P Filss
- Department of Nuclear Medicine, RWTH University Hospital, Aachen, Germany.
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany.
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany.
| | - Julian Cramer
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Faculty of Medical Engineering and Technomathematics, FH Aachen University of Applied Sciences, Campus Juelich, Jülich, Germany
| | - Saskia Löher
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Faculty of Medical Engineering and Technomathematics, FH Aachen University of Applied Sciences, Campus Juelich, Jülich, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
| | - Carina Stegmayr
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
| | - Martin Kocher
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- Department of Stereotactic and Functional Neurosurgery, Center for Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Alexander Heinzel
- Department of Nuclear Medicine, RWTH University Hospital, Aachen, Germany
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- Department of Nuclear Medicine, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Hans J Wittsack
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Michael Sabel
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- Department of Neurosurgery, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Bernd Neumaier
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Institute of Radiochemistry and Experimental Molecular Imaging, University Hospital Cologne, Cologne, Germany
| | - Jürgen Scheins
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- JARA - BRAIN - Translational Medicine, RWTH Aachen University, Aachen, Germany
- Department of Neurology, RWTH Aachen University Hospital, Aachen, Germany
| | - Philipp T Meyer
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Felix M Mottaghy
- Department of Nuclear Medicine, RWTH University Hospital, Aachen, Germany
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, Netherlands
| | - Karl-Josef Langen
- Department of Nuclear Medicine, RWTH University Hospital, Aachen, Germany
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-5, INM-11), Forschungszentrum Jülich, Jülich, Germany
- Center of Integrated Oncology (CIO), University of Aachen, Bonn, Cologne and Düsseldorf, Germany
- JARA - BRAIN - Translational Medicine, RWTH Aachen University, Aachen, Germany
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2
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Chen Q, Wang K, Ren X, Zhao X, Chen Q, Fan D, Zhang S, Li X, Ai L. Individualized discrimination of tumor progression from treatment-related changes in different types of adult-type diffuse gliomas using [ 11C]methionine PET. J Neurooncol 2023; 165:547-559. [PMID: 38095773 DOI: 10.1007/s11060-023-04529-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/04/2023] [Indexed: 12/29/2023]
Abstract
PURPOSE This study aimed to assess the ability of [11C]methionine (MET) PET in distinguishing between tumor progression (TP) and treatment-related changes (TRCs) among different types of adult-type diffuse gliomas according to the 2021 World Health Organization classification and predict overall survival (OS). METHODS We retrospectively selected 113 patients with adult-type diffuse gliomas with suspected TP who underwent MET PET imaging. Maximum and mean tumor-to-background ratios (TBRmax, TBRmean) and metabolic tumor volume (MTV) were calculated. Diagnoses were verified by histopathology (n = 50) or by clinical/radiological follow-up (n = 63). The diagnostic performance of MET PET parameters was evaluated through receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculation. Survival analysis employed the Kaplan-Meier method and Cox proportional-hazards regression. RESULTS TP and TRCs were diagnosed in 76 (67%) and 37 (33%) patients, respectively. ROC analysis revealed TBRmax had the best performance in differentiating TP from TRCs with a cut-off of 1.96 in IDH-mutant astrocytoma (AUC, 0.87; sensitivity, 93%; specificity 69%), 1.80 in IDH-mutant and 1p/19q-codeleted oligodendroglioma (AUC, 0.96; sensitivity, 100%; specificity, 89%), and 2.13 in IDH wild-type glioblastoma (AUC, 0.89; sensitivity, 89%; specificity, 78%), respectively. On multivariate analysis, higher TBRmean and MTV were significantly correlated with shorter OS in all IDH-mutant gliomas, as well as in IDH-mutant astrocytoma subgroup. CONCLUSION This work confirms that MET PET has varying diagnostic performances in distinguishing TP from TRCs within three types of adult-type diffuse gliomas, and highlights its high diagnostic accuracy in IDH-mutant and 1p/19q-codeleted oligodendroglioma and potential prognostic value for IDH-mutant gliomas, particularly IDH-mutant astrocytoma.
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Affiliation(s)
- Qiang Chen
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Kai Wang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaobin Zhao
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Qian Chen
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Di Fan
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Shu Zhang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Xiaotong Li
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Lin Ai
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China.
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3
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Karschnia P, Smits M, Reifenberger G, Le Rhun E, Ellingson BM, Galldiks N, Kim MM, Huse JT, Schnell O, Harter PN, Mohme M, von Baumgarten L, Albert NL, Huang RY, Mehta MP, van den Bent M, Weller M, Vogelbaum MA, Chang SM, Berger MS, Tonn JC. A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups. Lancet Oncol 2023; 24:e438-e450. [PMID: 37922934 PMCID: PMC10849105 DOI: 10.1016/s1470-2045(23)00453-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 08/23/2023] [Accepted: 09/07/2023] [Indexed: 11/07/2023]
Abstract
Surgical resection represents the standard of care for people with newly diagnosed diffuse gliomas, and the neuropathological and molecular profile of the resected tissue guides clinical management and forms the basis for research. The Response Assessment in Neuro-Oncology (RANO) consortium is an international, multidisciplinary effort that aims to standardise research practice in neuro-oncology. These recommendations represent a multidisciplinary consensus from the four RANO groups: RANO resect, RANO recurrent glioblastoma, RANO radiotherapy, and RANO/PET for a standardised workflow to achieve a representative tumour evaluation in a disease characterised by intratumoural heterogeneity, including recommendations on which tumour regions should be surgically sampled, how to define those regions on the basis of preoperative imaging, and the optimal sample volume. Practical recommendations for tissue sampling are given for people with low-grade and high-grade gliomas, as well as for people with newly diagnosed and recurrent disease. Sampling of liquid biopsies is also addressed. A standardised workflow for subsequent handling of the resected tissue is proposed to avoid information loss due to decreasing tissue quality or insufficient clinical information. The recommendations offer a framework for prospective biobanking studies.
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Affiliation(s)
- Philipp Karschnia
- Department of Neurosurgery, Ludwig-Maximilians-University of Munich, Munich, Germany; German Cancer Consortium, Partner Site Munich, Munich, Germany
| | - Marion Smits
- Department of Neuroradiology and Nuclear Medicine, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Guido Reifenberger
- Institute of Neuropathology, Heinrich Heine University Medical Faculty and University Hospital Düsseldorf, Düsseldorf, Germany
| | - Emilie Le Rhun
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Department of Neurology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine, University of Cologne and University Hospital Cologne, Cologne, Germany; Research Center Juelich, Institute of Neuroscience and Medicine, Juelich, Germany
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan Hospital, Ann Arbor, MI, USA
| | - Jason T Huse
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Oliver Schnell
- Department of Neurosurgery, University of Freiburg, Freiburg, Germany
| | - Patrick N Harter
- German Cancer Consortium, Partner Site Munich, Munich, Germany; Center for Neuropathology and Prion Research, Faculty of Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Malte Mohme
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Louisa von Baumgarten
- Department of Neurosurgery, Ludwig-Maximilians-University of Munich, Munich, Germany; German Cancer Consortium, Partner Site Munich, Munich, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Raymond Y Huang
- Division of Neuroradiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Minesh P Mehta
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL, USA
| | - Martin van den Bent
- Department of Neurology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Michael Weller
- Department of Neurology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | | | - Susan M Chang
- Department of Neurosurgery and Division of Neuro-Oncology, University of California, San Francisco, CA, USA
| | - Mitchel S Berger
- Department of Neurosurgery and Division of Neuro-Oncology, University of California, San Francisco, CA, USA
| | - Joerg-Christian Tonn
- Department of Neurosurgery, Ludwig-Maximilians-University of Munich, Munich, Germany; German Cancer Consortium, Partner Site Munich, Munich, Germany.
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4
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Langen KJ, Galldiks N, Mauler J, Kocher M, Filß CP, Stoffels G, Régio Brambilla C, Stegmayr C, Willuweit A, Worthoff WA, Shah NJ, Lerche C, Mottaghy FM, Lohmann P. Hybrid PET/MRI in Cerebral Glioma: Current Status and Perspectives. Cancers (Basel) 2023; 15:3577. [PMID: 37509252 PMCID: PMC10377176 DOI: 10.3390/cancers15143577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Advanced MRI methods and PET using radiolabelled amino acids provide valuable information, in addition to conventional MR imaging, for brain tumour diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumour progression from treatment-related changes, and the early assessment of responses to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing, and has been addressed in numerous studies. Currently, most radiology and nuclear medicine departments perform these examinations independently of each other, leading to multiple examinations for the patient. The advent of hybrid PET/MRI allowed a convergence of the methods, but to date simultaneous imaging has reached little relevance in clinical neuro-oncology. This is partly due to the limited availability of hybrid PET/MRI scanners, but is also due to the fact that PET is a second-line examination in brain tumours. PET is only required in equivocal situations, and the spatial co-registration of PET examinations of the brain to previous MRI is possible without disadvantage. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumours compared with a single modality. This review focuses on studies investigating the diagnostic value of combined amino acid PET and 'advanced' MRI in patients with cerebral gliomas. Available studies suggest that the combination of amino acid PET and advanced MRI improves grading and the histomolecular characterisation of newly diagnosed tumours. Few data are available concerning the delineation of tumour extent. A clear additive diagnostic value of amino acid PET and advanced MRI can be achieved regarding the differentiation of tumour recurrence from treatment-related changes. Here, the PET-guided evaluation of advanced MR methods seems to be helpful. In summary, there is growing evidence that a multimodal approach can achieve decisive improvements in the diagnostics of cerebral gliomas, for which hybrid PET/MRI offers optimal conditions.
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Affiliation(s)
- Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
- Department of Nuclear Medicine, RWTH Aachen University Hospital, 52074 Aachen, Germany
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, 53127 Bonn, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, 53127 Bonn, Germany
- Department of Neurology, Faculty of Medicine, University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
| | - Jörg Mauler
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Martin Kocher
- Department of Stereotaxy and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine, University Hospital Cologne, 50931 Cologne, Germany
| | - Christian Peter Filß
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
- Department of Nuclear Medicine, RWTH Aachen University Hospital, 52074 Aachen, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Cláudia Régio Brambilla
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Carina Stegmayr
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Antje Willuweit
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Wieland Alexander Worthoff
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Nadim Jon Shah
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
- Department of Neurology, RWTH Aachen University Hospital, 52074 Aachen, Germany
| | - Christoph Lerche
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
| | - Felix Manuel Mottaghy
- Department of Nuclear Medicine, RWTH Aachen University Hospital, 52074 Aachen, Germany
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, 53127 Bonn, Germany
- Department of Neurology, Faculty of Medicine, University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), 6229 HX Maastricht, The Netherlands
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, INM-4, INM-11), Forschungszentrum Juelich, 52425 Juelich, Germany
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5
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Khalili N, Kazerooni AF, Familiar A, Haldar D, Kraya A, Foster J, Koptyra M, Storm PB, Resnick AC, Nabavizadeh A. Radiomics for characterization of the glioma immune microenvironment. NPJ Precis Oncol 2023; 7:59. [PMID: 37337080 DOI: 10.1038/s41698-023-00413-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/02/2023] [Indexed: 06/21/2023] Open
Abstract
Increasing evidence suggests that besides mutational and molecular alterations, the immune component of the tumor microenvironment also substantially impacts tumor behavior and complicates treatment response, particularly to immunotherapies. Although the standard method for characterizing tumor immune profile is through performing integrated genomic analysis on tissue biopsies, the dynamic change in the immune composition of the tumor microenvironment makes this approach not feasible, especially for brain tumors. Radiomics is a rapidly growing field that uses advanced imaging techniques and computational algorithms to extract numerous quantitative features from medical images. Recent advances in machine learning methods are facilitating biological validation of radiomic signatures and allowing them to "mine" for a variety of significant correlates, including genetic, immunologic, and histologic data. Radiomics has the potential to be used as a non-invasive approach to predict the presence and density of immune cells within the microenvironment, as well as to assess the expression of immune-related genes and pathways. This information can be essential for patient stratification, informing treatment decisions and predicting patients' response to immunotherapies. This is particularly important for tumors with difficult surgical access such as gliomas. In this review, we provide an overview of the glioma microenvironment, describe novel approaches for clustering patients based on their tumor immune profile, and discuss the latest progress on utilization of radiomics for immune profiling of glioma based on current literature.
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Affiliation(s)
- Nastaran Khalili
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
- AI2D Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurosurgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ariana Familiar
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Debanjan Haldar
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam Kraya
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jessica Foster
- Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mateusz Koptyra
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Phillip B Storm
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Adam C Resnick
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ali Nabavizadeh
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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6
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Galldiks N, Lohmann P, Fink GR, Langen KJ. Amino Acid PET in Neurooncology. J Nucl Med 2023; 64:693-700. [PMID: 37055222 DOI: 10.2967/jnumed.122.264859] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/10/2023] [Indexed: 04/15/2023] Open
Abstract
For decades, several amino acid PET tracers have been used to optimize diagnostics in patients with brain tumors. In clinical routine, the most important clinical indications for amino acid PET in brain tumor patients are differentiation of neoplasm from nonneoplastic etiologies, delineation of tumor extent for further diagnostic and treatment planning (i.e., diagnostic biopsy, resection, or radiotherapy), differentiation of treatment-related changes such as pseudoprogression or radiation necrosis after radiation or chemoradiation from tumor progression at follow-up, and assessment of response to anticancer therapy, including prediction of patient outcome. This continuing education article addresses the diagnostic value of amino acid PET for patients with either glioblastoma or metastatic brain cancer.
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Affiliation(s)
- Norbert Galldiks
- Department of Neurology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany;
- Institute of Neuroscience and Medicine, Research Center Juelich, Juelich, Germany
- Center for Integrated Oncology, Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany; and
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine, Research Center Juelich, Juelich, Germany
| | - Gereon R Fink
- Department of Neurology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine, Research Center Juelich, Juelich, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine, Research Center Juelich, Juelich, Germany
- Center for Integrated Oncology, Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany; and
- Department of Nuclear Medicine, RWTH University Hospital Aachen, Aachen, Germany
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7
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Familiar AM, Mahtabfar A, Fathi Kazerooni A, Kiani M, Vossough A, Viaene A, Storm PB, Resnick AC, Nabavizadeh A. Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges. Neurooncol Adv 2023; 5:vdad119. [PMID: 37841693 PMCID: PMC10576517 DOI: 10.1093/noajnl/vdad119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023] Open
Abstract
With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new modality for precision medicine. At the same time, the ability to harness multi-modal data is met with challenges in aggregating data across medical departments and institutions, as well as significant complexity in modeling the phenotypic and genotypic heterogeneity of pediatric brain tumors. In this paper, we review recent pathomic and integrated pathomic, radiomic, and genomic studies with clinical applications. We discuss current challenges limiting translational research on pediatric brain tumors and outline technical and analytical solutions. Overall, we propose that to empower the potential residing in radio-pathomics, systemic changes in cross-discipline data management and end-to-end software platforms to handle multi-modal data sets are needed, in addition to embracing modern AI-powered approaches. These changes can improve the performance of predictive models, and ultimately the ability to advance brain cancer treatments and patient outcomes through the development of such models.
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Affiliation(s)
- Ariana M Familiar
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Aria Mahtabfar
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mahsa Kiani
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arastoo Vossough
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Angela Viaene
- Department of Pathology and Laboratory Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Phillip B Storm
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam C Resnick
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ali Nabavizadeh
- Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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8
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Wollring MM, Werner JM, Ceccon G, Lohmann P, Filss CP, Fink GR, Langen KJ, Galldiks N. Clinical applications and prospects of PET imaging in patients with IDH-mutant gliomas. J Neurooncol 2022; 162:481-488. [PMID: 36577872 DOI: 10.1007/s11060-022-04218-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/14/2022] [Indexed: 12/29/2022]
Abstract
PET imaging using radiolabeled amino acids in addition to MRI has become a valuable diagnostic tool in the clinical management of patients with brain tumors. This review provides a comprehensive overview of PET studies in glioma patients with a mutation in the isocitrate dehydrogenase gene (IDH). A considerable fraction of these tumors typically show no contrast enhancement on MRI, especially when classified as grade 2 according to the World Health Organization classification of Central Nervous System tumors. Major diagnostic challenges in this situation are differential diagnosis, target definition for diagnostic biopsies, delineation of glioma extent for treatment planning, differentiation of treatment-related changes from tumor progression, and the evaluation of response to alkylating agents. The main focus of this review is the role of amino acid PET in this setting. Furthermore, in light of clinical trials using IDH inhibitors targeting the mutated IDH enzyme for treating patients with IDH-mutant gliomas, we also aim to give an outlook on PET probes specifically targeting the IDH mutation, which appear potentially helpful for response assessment.
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Affiliation(s)
- Michael M Wollring
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany.
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937, Cologne, Germany.
| | - Jan-Michael Werner
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937, Cologne, Germany
| | - Garry Ceccon
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany
| | - Christian P Filss
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany
- Department of Nuclear Medicine, University Hospital Aachen, Aachen, Germany
| | - Gereon R Fink
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937, Cologne, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany
- Department of Nuclear Medicine, University Hospital Aachen, Aachen, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Leo-Brandt-St., 52425, Juelich, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937, Cologne, Germany
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
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9
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Duffau H. A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead. J Pers Med 2022; 12:jpm12101621. [PMID: 36294760 PMCID: PMC9604939 DOI: 10.3390/jpm12101621] [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: 08/28/2022] [Revised: 09/15/2022] [Accepted: 09/22/2022] [Indexed: 11/09/2022] Open
Abstract
Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.
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Affiliation(s)
- Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, 80 Av. Augustin Fliche, 34295 Montpellier, France; ; Tel.: +33-4-67-33-66-12; Fax: +33-4-67-33-69-12
- Team “Plasticity of Central Nervous System, Stem Cells and Glial Tumors”, National Institute for Health and Medical Research (INSERM), U1191 Laboratory, Institute of Functional Genomics, University of Montpellier, 34091 Montpellier, France
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10
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Silva M, Vivancos C, Duffau H. The Concept of «Peritumoral Zone» in Diffuse Low-Grade Gliomas: Oncological and Functional Implications for a Connectome-Guided Therapeutic Attitude. Brain Sci 2022; 12:brainsci12040504. [PMID: 35448035 PMCID: PMC9032126 DOI: 10.3390/brainsci12040504] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/10/2022] [Accepted: 04/12/2022] [Indexed: 12/22/2022] Open
Abstract
Diffuse low-grade gliomas (DLGGs) are heterogeneous and poorly circumscribed neoplasms with isolated tumor cells that extend beyond the margins of the lesion depicted on MRI. Efforts to demarcate the glioma core from the surrounding healthy brain led us to define an intermediate region, the so-called peritumoral zone (PTZ). Although most studies about PTZ have been conducted on high-grade gliomas, the purpose here is to review the cellular, metabolic, and radiological characteristics of PTZ in the specific context of DLGG. A better delineation of PTZ, in which glioma cells and neural tissue strongly interact, may open new therapeutic avenues to optimize both functional and oncological results. First, a connectome-based “supratotal” surgical resection (i.e., with the removal of PTZ in addition to the tumor core) resulted in prolonged survival by limiting the risk of malignant transformation, while improving the quality of life, thanks to a better control of seizures. Second, the timing and order of (neo)adjuvant medical treatments can be modulated according to the pattern of peritumoral infiltration. Third, the development of new drugs specifically targeting the PTZ could be considered from an oncological (such as immunotherapy) and epileptological perspective. Further multimodal investigations of PTZ are needed to maximize long-term outcomes in DLGG patients.
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Affiliation(s)
- Melissa Silva
- Department of Neurosurgery, Hospital Garcia de Orta, 2805-267 Almada, Portugal;
| | - Catalina Vivancos
- Department of Neurosurgery, Hospital Universitario La Paz, 28046 Madrid, Spain;
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, 34295 Montpellier, France
- Team “Plasticity of Central Nervous System, Stem Cells and Glial Tumors”, Institute of Functional Genomics, National Institute for Health and Medical Research (INSERM) U1191, University of Montpellier, 34295 Montpellier, France
- Correspondence:
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11
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Ninatti G, Sollini M, Bono B, Gozzi N, Fedorov D, Antunovic L, Gelardi F, Navarria P, Politi LS, Pessina F, Chiti A. Preoperative [11C]methionine PET to personalize treatment decisions in patients with lower-grade gliomas. Neuro Oncol 2022; 24:1546-1556. [PMID: 35171292 PMCID: PMC9435504 DOI: 10.1093/neuonc/noac040] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND PET with radiolabelled amino acids is used in the preoperative evaluation of patients with glial neoplasms. This study aimed to assess the role of [ 11C]methionine (MET) PET in assessing molecular features, tumour extent, and prognosis in newly-diagnosed lower-grade gliomas (LGGs) surgically treated. METHODS 153 patients with a new diagnosis of grade 2/3 glioma who underwent surgery at our Institution and were imaged preoperatively using [ 11C]MET PET/CT were retrospectively included. [ 11C]MET PET images were qualitatively and semiquantitatively analyzed using tumour-to-background ratio (TBR). Progression-free survival (PFS) rates were estimated using the Kaplan-Meier method and Cox proportional-hazards regression was used to test the association of clinicopathological and imaging data to PFS. RESULTS Overall, 111 lesions (73%) were positive, while thirty-two (21%) and ten (6%) were isometabolic and hypometabolic at [ 11C]MET PET, respectively. [ 11C]MET uptake was more common in oligodendrogliomas than IDH-mutant astrocytomas (87% vs 50% of cases, respectively). Among [ 11C]MET-positive gliomas, grade 3 oligodendrogliomas had the highest median TBRmax (3.22). In 25% of patients, PET helped to better delineate tumour margins compared to MRI only. In IDH-mutant astrocytomas, higher TBRmax values at [ 11C]MET PET were independent predictors of shorter PFS. CONCLUSIONS This work highlights the role of preoperative [ 11C]MET PET in estimating the type, assessing tumour extent, and predicting biological behaviour and prognosis of LGGs. Our findings support the implementation of [ 11C]MET PET in routine clinical practice to better manage these neoplasms.
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Affiliation(s)
- Gaia Ninatti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy
| | - Martina Sollini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Beatrice Bono
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Noemi Gozzi
- Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Daniil Fedorov
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy
| | - Lidija Antunovic
- Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Fabrizia Gelardi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Pierina Navarria
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Letterio S Politi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Federico Pessina
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Arturo Chiti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
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12
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Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations. PLoS Comput Biol 2021; 17:e1009206. [PMID: 34310608 PMCID: PMC8341701 DOI: 10.1371/journal.pcbi.1009206] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 08/05/2021] [Accepted: 06/22/2021] [Indexed: 11/19/2022] Open
Abstract
Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells’ behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level. Low levels of oxygen, called hypoxia, are observable in many solid tumors. They are associated with more aggressive malignant cells that are resistant to chemo-, radio-, and immunotherapies. Recently developed imaging techniques provide a way to measure the magnitude of frequent short-term oxygen fluctuations, but they operate on a macro-scale voxel level. To examine the possible causes of rapid oxygen fluctuations at the cell level, we developed a hybrid agent-based mathematical model. We tested two different mechanisms that may be responsible for these cyclic effects on tissue oxygenation: temporal variations in vascular influx of oxygen and modulations in cellular oxygen absorption. Additionally, we developed a procedure to identify plausible tissue morphologies from data collected from radiological images. This can provide a bridge between the micro-scale simulations with individual cells and the longitudinal medical images containing average values. In future applications, this approach can be used to generate a set of tissues compatible with radiology images and to simulate tumor responses to various anticancer treatments at the cell-scale level.
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13
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Strahlenther Onkol 2021; 197:1-23. [PMID: 34259912 DOI: 10.1007/s00066-021-01812-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca-L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Christoph Henkenberens
- Department of Radiotherapy and Special Oncology, Medical School Hannover, Hannover, Germany
| | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiotherapy and Oncology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany.
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14
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Nuklearmedizin 2021; 60:326-343. [PMID: 34261141 DOI: 10.1055/a-1525-7029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany.,Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | | | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiotherapy and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
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15
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Galldiks N, Niyazi M, Grosu AL, Kocher M, Langen KJ, Law I, Minniti G, Kim MM, Tsien C, Dhermain F, Soffietti R, Mehta MP, Weller M, Tonn JC. Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients - a report of the PET/RANO group. Neuro Oncol 2021; 23:881-893. [PMID: 33538838 DOI: 10.1093/neuonc/noab013] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The management of patients with glioma usually requires multimodality treatment including surgery, radiotherapy, and systemic therapy. Accurate neuroimaging plays a central role for radiotherapy planning and follow-up after radiotherapy completion. In order to maximize the radiation dose to the tumor and to minimize toxic effects on the surrounding brain parenchyma, reliable identification of tumor extent and target volume delineation is crucial. The use of positron emission tomography (PET) for radiotherapy planning and monitoring in gliomas has gained considerable interest over the last several years, but Class I data are not yet available. Furthermore, PET has been used after radiotherapy for response assessment and to distinguish tumor progression from pseudoprogression or radiation necrosis. Here, the Response Assessment in Neuro-Oncology (RANO) working group provides a summary of the literature and recommendations for the use of PET imaging for radiotherapy of patients with glioma based on published studies, constituting levels 1-3 evidence according to the Oxford Centre for Evidence-based Medicine.
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Affiliation(s)
- Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3,-4), Research Center Juelich, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Düsseldorf, Cologne and Aachen, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, University Hospital Freiburg, Freiburg, Germany
| | - Martin Kocher
- Institute of Neuroscience and Medicine (INM-3,-4), Research Center Juelich, Juelich, Germany.,Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3,-4), Research Center Juelich, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Düsseldorf, Cologne and Aachen, Germany.,Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, University Hospital Copenhagen, Copenhagen, Denmark
| | - Giuseppe Minniti
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.,IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Christina Tsien
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, Baltimore, Maryland, USA
| | - Frederic Dhermain
- Department of Radiation Therapy, Institut de Cancerologie Gustave Roussy, Villejuif, France
| | - Riccardo Soffietti
- Department of Neuro-Oncology, University and City of Health and Science Hospital, Turin, Italy
| | - Minesh P Mehta
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, Florida, USA.,Herbert Wertheim College of Medicine, Florida International University, Miami, Florida, USA
| | - Michael Weller
- Department of Neurology & Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Jörg-Christian Tonn
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
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16
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Stadlbauer A, Heinz G, Oberndorfer S, Zimmermann M, Kinfe TM, Buchfelder M, Dörfler A, Kremenevski N, Marhold F. Physiological MRI of microvascular architecture, neovascularization activity, and oxygen metabolism facilitate early recurrence detection in patients with IDH-mutant WHO grade 3 glioma. Neuroradiology 2021; 64:265-277. [PMID: 34115146 PMCID: PMC8789727 DOI: 10.1007/s00234-021-02740-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 05/27/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE This study aimed to determine the diagnostic performance of physiological MRI biomarkers including microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension for recurrence detection of IDH-mutant WHO grade 3 glioma. METHODS Sixty patients with IDH-mutant WHO grade 3 glioma who received overall 288 follow-up MRI examinations at 3 Tesla after standard treatment were retrospectively evaluated. A conventional MRI protocol was extended with a physiological MRI approach including vascular architecture mapping and quantitative blood-oxygen-level-dependent imaging which required 7 min extra data acquisition time. Custom-made MATLAB software was used for the calculation of MRI biomarker maps of microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension. Statistical procedures included receiver operating characteristic analysis. RESULTS Overall, 34 patients showed recurrence of the WHO grade 3 glioma; of these, in 15 patients, recurrence was detected one follow-up examination (averaged 160 days) earlier by physiological MRI data than by conventional MRI. During this time period, the tumor volume increased significantly (P = 0.001) on average 7.4-fold from 1.5 to 11.1 cm3. Quantitative analysis of MRI biomarkers demonstrated microvascular but no macrovascular hyperperfusion in early recurrence. Neovascularization activity (AUC = 0.833), microvascular perfusion (0.682), and oxygen metabolism (0.661) showed higher diagnostic performance for early recurrence detection of WHO grade 3 glioma compared to conventional MRI including cerebral blood volume (0.649). CONCLUSION This study demonstrated that the targeted assessment of microvascular features and tissue oxygen tension as an early sign of neovascularization activity provided valuable information for recurrence diagnostic of WHO grade 3 glioma.
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Affiliation(s)
- Andreas Stadlbauer
- Institute of Medical Radiology, University Clinic St. Pölten, Karl Landsteiner University of Health Sciences, Dunant Platz 1, A-3100, St. Pölten, Austria.
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
| | - Gertraud Heinz
- Institute of Medical Radiology, University Clinic St. Pölten, Karl Landsteiner University of Health Sciences, Dunant Platz 1, A-3100, St. Pölten, Austria
| | - Stefan Oberndorfer
- Department of Neurology, University Clinic of St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
| | - Max Zimmermann
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
- Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Thomas M Kinfe
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
- Division of Functional Neurosurgery and Stereotaxy, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Michael Buchfelder
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Dörfler
- Department of Neuroradiology, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Natalia Kremenevski
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Franz Marhold
- Department of Neurosurgery, University Clinic of St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
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17
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Furtak J, Rakowska J, Szylberg T, Harat M, Małkowski B, Harat M. Glioma Biopsy Based on Hybrid Dual Time-Point FET-PET/MRI-A Proof of Concept Study. Front Neurol 2021; 12:634609. [PMID: 34046002 PMCID: PMC8144440 DOI: 10.3389/fneur.2021.634609] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 03/15/2021] [Indexed: 11/13/2022] Open
Abstract
Neuroimaging based on O-[2-(18F)fluoroethyl]-l-tyrosine (FET)-PET provides additional information on tumor grade and extent compared with MRI. Dynamic PET for biopsy target selection further improves results but is often clinically impractical. Static FET-PET performed at two time-points may be a good compromise, but data on this approach are limited. The aim of this study was to compare the histology of lesions obtained from two challenging glioma patients with targets selected based on hybrid dual time-point FET-PET/MRI. Five neuronavigated tumor biopsies were performed in two difficult cases of suspected glioma. Lesions with (T1-CE) and without contrast enhancement (T1 and T2-FLAIR) on MRI were selected. Dual time-point FET-PET imaging was performed 5–15 min (PET10) and 45–60 min (PET60) after radionuclide injection. The most informative FET-PET/MRI images were coregistered with MRI in time of biopsy planning. Five biopsy targets (three from high uptake and two from moderate uptake FET areas) thought to represent the most malignant sites and tumor extent were selected. Histopathological findings were compared with FET-PET and MRI images. Increased FET uptake in the area of non-CE locations on MRI correlated well with high-grade gliomas localized as far as 3 cm from T1-CE foci. Selecting a target in the motor cortex based on FET kinetics defined by dual time-point PET resulted in a grade IV diagnosis after previous negative biopsies based on MRI. An additional grade III diagnosis was obtained from an area of glioma infiltration with moderate FET uptake (between 1 and 1.25 SUV). These findings seem to show that dual time-point FET-PET-based biopsies can provide additional and clinically useful information for glioma diagnosis. Selection of targets based on dual time-point images may be useful for determining the most malignant tumor areas and may therefore be useful for resection and radiotherapy planning.
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Affiliation(s)
- Jacek Furtak
- Department of Neurosurgery, 10th Military Research Hospital, Bydgoszcz, Poland
| | - Józefina Rakowska
- Department of Neurosurgery, 10th Military Research Hospital, Bydgoszcz, Poland
| | - Tadeusz Szylberg
- Department of Pathomorphology, 10th Military Research Hospital, Bydgoszcz, Poland
| | - Marek Harat
- Department of Neurosurgery, 10th Military Research Hospital, Bydgoszcz, Poland.,Department of Neurosurgery and Neurology, Faculty of Health Sciences, Ludwik Rydygier Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland
| | - Bogdan Małkowski
- Department of Positron Emission Tomography and Molecular Imaging, Ludwik Rydygier Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland.,Department of Nuclear Medicine, Franciszek Lukaszczyk Oncology Center, Bydgoszcz, Poland
| | - Maciej Harat
- Department of Oncology and Brachytherapy, Faculty of Medicine, Ludwik Rydygier Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland.,Department of Neurooncology and Radiosurgery, Franciszek Lukaszczyk Oncology Center, Bydgoszcz, Poland
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18
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Blocker SJ, Cook J, Mowery YM, Everitt JI, Qi Y, Hornburg KJ, Cofer GP, Zapata F, Bassil AM, Badea CT, Kirsch DG, Johnson GA. Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas. Radiol Imaging Cancer 2021; 3:e200103. [PMID: 34018846 DOI: 10.1148/rycan.2021200103] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Purpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R2 values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R2 = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R2 = 0.99, P < .001) and variance in nuclear circularity (best line fit: R2 = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.
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Affiliation(s)
- Stephanie J Blocker
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - James Cook
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Yvonne M Mowery
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Jeffrey I Everitt
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Yi Qi
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Kathryn J Hornburg
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Gary P Cofer
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Fernando Zapata
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Alex M Bassil
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - Cristian T Badea
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - David G Kirsch
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
| | - G Allan Johnson
- From the Departments of Radiology (S.J.B., J.C., Y.Q., K.H., G.P.C., F.Z., C.T.B., G.A.J.), Radiation Oncology (Y.M.M., A.M.B., D.G.K.), and Pathology (J.I.E.), Duke University Medical Center, Center for In Vivo Microscopy, Bryan Research Building, 311 Research Dr, Durham, NC 27710
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19
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Ma H, Zhao J, Liu S, Xie D, Zhang Z, Nie D, Wen F, Yang Z, Tang G. 18F-Trifluoromethylated D-Cysteine as a Promising New PET Tracer for Glioma Imaging: Comparative Analysis With MRI and Histopathology in Orthotopic C6 Models. Front Oncol 2021; 11:645162. [PMID: 33996562 PMCID: PMC8117348 DOI: 10.3389/fonc.2021.645162] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/15/2021] [Indexed: 11/13/2022] Open
Abstract
Comparing MRI and histopathology, this study aims to comprehensively explore the potential application of 18F-trifluoromethylated D-cysteine (S-[18F]CF3-D-CYS) in evaluating glioma by using orthotopic C6 glioma models. Sprague-Dawley (SD) rats (n = 9) were implanted with C6 glioma cells. Tumor growth was monitored every week by multiparameter MRI [including dynamic contrast-enhanced MRI (DCE-MRI)], [18F]FDG, S-[18F]CF3-D-CYS, and [18F]FDOPA PET imaging. Repeated scans of the same rat with the two or three [18F]-labeled radiotracers were investigated. Initial regions of interest were manually delineated on T2WI and set on the same level of PET images, and tumor-to-normal brain uptake ratios (TNRs) were calculated to semiquantitatively assess the tracer accumulation in the tumor. The tumor volume in PET and histopathology was calculated. HE and Ki67 immunohistochemical staining were further performed. The correlations between the uptake of S-[18F]CF3-D-CYS and Ki67 were analyzed. Dynamic S-[18F]CF3-D-CYS PET imaging showed tumor uptake rapidly reached a peak, maintained plateau during 10-30 min after injection, then decreased slowly. Compared with [18F]FDG and [18F]FDOPA PET imaging, S-[18F]CF3-D-CYS PET demonstrated the highest TNRs (P < 0.05). There were no significant differences in the tumor volume measured on S-[18F]CF3-D-CYS PET or HE specimen. Furthermore, our results showed that the uptake of S-[18F]CF3-D-CYS was significantly positively correlated with tumor Ki67, and the poor accumulated S-[18F]CF3-D-CYS was consistent with tumor hemorrhage. There was no significant correlation between the S-[18F]CF3-D-CYS uptakes and the Ktrans values derived from DCE-MRI. In comparison with MRI and histopathology, S-[18F]CF3-D-CYS PET performs well in the diagnosis and evaluation of glioma. S-[18F]CF3-D-CYS PET may serve as a valuable tool in the clinical management of gliomas.
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Affiliation(s)
- Hui Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jing Zhao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shaoyu Liu
- Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Dingxiang Xie
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhanwen Zhang
- Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Nuclear Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dahong Nie
- Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Radiation Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Fuhua Wen
- Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhiyun Yang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ganghua Tang
- Department of Nuclear Medicine, Guangdong Engineering Research Center for Translational Application of Medical Radiopharmaceuticals, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Nanfang PET Center, Department of Nuclear Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
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20
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Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies. Mol Imaging 2021; 2021:8874078. [PMID: 34194287 PMCID: PMC8205602 DOI: 10.1155/2021/8874078] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/23/2020] [Accepted: 11/17/2020] [Indexed: 12/16/2022] Open
Abstract
Introduction Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging. Methods A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020. Results A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive. Conclusions aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.
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21
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Tatekawa H, Hagiwara A, Yao J, Oughourlian TC, Ueda I, Uetani H, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Pope WB, Salamon N, Ellingson BM. Voxelwise and Patientwise Correlation of 18F-FDOPA PET, Relative Cerebral Blood Volume, and Apparent Diffusion Coefficient in Treatment-Naïve Diffuse Gliomas with Different Molecular Subtypes. J Nucl Med 2020; 62:319-325. [PMID: 32646876 DOI: 10.2967/jnumed.120.247411] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/11/2020] [Indexed: 11/16/2022] Open
Abstract
Our purpose was to identify correlations between 18F-fluorodihydroxyphenylalanine (18F-FDOPA) uptake and physiologic MRI, including relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC), in gliomas with different molecular subtypes and to evaluate their prognostic values. Methods: Sixty-eight treatment-naïve glioma patients who underwent 18F-FDOPA PET and physiologic MRI were retrospectively selected (36 with isocitrate dehydrogenase wild-type [IDHwt], 16 with mutant 1p/19q noncodeleted [IDHm-noncodel], and 16 with mutant codeleted [IDHm-codel]). Fluid-attenuated inversion recovery hyperintense areas were segmented and used as regions of interest. For voxelwise and patientwise analyses, Pearson correlation coefficients (r voxelwise and r patientwise) between the normalized SUV (nSUV), rCBV, and ADC were evaluated. Cox regression analysis was performed to investigate the associations between overall survival and r voxelwise, maximum or median nSUV, median rCBV, or median ADC. Results: For IDHwt and IDHm-noncodel gliomas, nSUV demonstrated significant positive correlations with rCBV (r voxelwise = 0.25 and 0.31, respectively; r patientwise = 0.50 and 0.70, respectively) and negative correlations with ADC (r voxelwise = -0.19 and -0.19, respectively; r patientwise = -0.58 and -0.61, respectively) in both voxelwise and patientwise analyses. IDHm-codel gliomas demonstrated a significant positive correlation between nSUV and ADC only in voxelwise analysis (r voxelwise = 0.18). In Cox regression analysis, r voxelwise between nSUV and rCBV (hazard ratio, 28.82) or ADC (hazard ratio, 0.085) had significant associations with overall survival for only IDHwt gliomas. Conclusion: IDHm-codel gliomas showed distinctive patterns of correlations between amino acid PET and physiologic MRI. Stronger correlations between nSUV and rCBV or ADC may result in a worse prognosis for IDHwt gliomas.
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Affiliation(s)
- Hiroyuki Tatekawa
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering, UCLA, Los Angeles, California
| | - Talia C Oughourlian
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Issei Ueda
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurosurgery, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California .,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering, UCLA, Los Angeles, California.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California
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22
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Langen KJ, Galldiks N, Lohmann P. Combined FET PET/ADC mapping: improved imaging of glioma infiltration? Neuro Oncol 2020; 22:313-314. [PMID: 31859354 DOI: 10.1093/neuonc/noz236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Karl-Josef Langen
- Institute of Neuroscience and Medicine, Research Center Juelich,Juelich, Germany
- Department of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany
- Center of Integrated Oncology, Universities Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine, Research Center Juelich,Juelich, Germany
- Center of Integrated Oncology, Universities Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine, Research Center Juelich,Juelich, Germany
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23
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Lohmann P, Werner JM, Shah NJ, Fink GR, Langen KJ, Galldiks N. Combined Amino Acid Positron Emission Tomography and Advanced Magnetic Resonance Imaging in Glioma Patients. Cancers (Basel) 2019; 11:cancers11020153. [PMID: 30699942 PMCID: PMC6406895 DOI: 10.3390/cancers11020153] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 01/24/2019] [Accepted: 01/25/2019] [Indexed: 02/07/2023] Open
Abstract
Imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) provide valuable information about brain tumor patients. Particularly amino acid PET, advanced MRI techniques, and combinations thereof are of great interest for the non-invasive assessment of biological characteristics in patients with primary or secondary brain cancer. A methodological innovation that potentially advances research in patients with brain tumors is the increasing availability of hybrid PET/MRI systems, which enables the simultaneous acquisition of both imaging modalities. Furthermore, the advent of ultra-high field MRI scanners operating at magnetic field strengths of 7 T or more will allow further development of metabolic MR imaging at higher resolution. This review focuses on the combination of amino acid PET with MR spectroscopic imaging, perfusion- and diffusion-weighted imaging, as well as chemical exchange saturation transfer in patients with high-grade gliomas, especially glioblastomas.
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Affiliation(s)
- Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, -4, -5, -11), Forschungszentrum Juelich, 52425 Juelich, Germany.
| | - Jan-Michael Werner
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany.
| | - N Jon Shah
- Institute of Neuroscience and Medicine (INM-3, -4, -5, -11), Forschungszentrum Juelich, 52425 Juelich, Germany.
- JARA-BRAIN-Translational Medicine, 52074 Aachen, Germany.
- Department of Neurology, RWTH Aachen University, 52074 Aachen, Germany.
| | - Gereon R Fink
- Institute of Neuroscience and Medicine (INM-3, -4, -5, -11), Forschungszentrum Juelich, 52425 Juelich, Germany.
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany.
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4, -5, -11), Forschungszentrum Juelich, 52425 Juelich, Germany.
- Department of Nuclear Medicine, RWTH Aachen University, 52074 Aachen, Germany.
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, -4, -5, -11), Forschungszentrum Juelich, 52425 Juelich, Germany.
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany.
- Center of Integrated Oncology (CIO), Universities of Cologne and Bonn, 50937 Cologne, Germany.
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