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Lemarié A, Lubrano V, Delmas C, Lusque A, Cerapio JP, Perrier M, Siegfried A, Arnauduc F, Nicaise Y, Dahan P, Filleron T, Mounier M, Toulas C, Cohen-Jonathan Moyal E. The STEMRI trial: Magnetic resonance spectroscopy imaging can define tumor areas enriched in glioblastoma stem-like cells. SCIENCE ADVANCES 2023; 9:eadi0114. [PMID: 37922359 PMCID: PMC10624352 DOI: 10.1126/sciadv.adi0114] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/03/2023] [Indexed: 11/05/2023]
Abstract
Despite maximally safe resection of the magnetic resonance imaging (MRI)-defined contrast-enhanced (CE) central tumor area and chemoradiotherapy, most patients with glioblastoma (GBM) relapse within a year in peritumoral FLAIR regions. Magnetic resonance spectroscopy imaging (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (choline/N-acetyl-aspartate index >2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSCs), CNI+ areas might be GSC enriched. In this prospective trial, 16 patients with GBM underwent MRSI/MRI before surgery/chemoradiotherapy to investigate GSC content in CNI-/+ biopsies from CE/FLAIR. Biopsy and derived-GSC characterization revealed a FLAIR/CNI+ sample enrichment in GSC and in gene signatures related to stemness, DNA repair, adhesion/migration, and mitochondrial bioenergetics. FLAIR/CNI+ samples generate GSC-enriched neurospheres faster than FLAIR/CNI-. Parameters assessing biopsy GSC content and time-to-neurosphere formation in FLAIR/CNI+ were associated with worse patient outcome. Preoperative MRI/MRSI would certainly allow better resection and targeting of FLAIR/CNI+ areas, as their GSC enrichment can predict worse outcomes.
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Affiliation(s)
- Anthony Lemarié
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- UFR Santé, Université de Toulouse III–Paul Sabatier, Toulouse, France
| | - Vincent Lubrano
- TONIC, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Toulouse Neuro Imaging Center, Toulouse, France
- CHU de Toulouse, Neurosurgery Department, Toulouse, France
| | - Caroline Delmas
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- Institut Claudius Regaud, IUCT-Oncopole, Interface Department, Toulouse, France
| | - Amélie Lusque
- Institut Claudius Regaud, IUCT-Oncopole, Biostatistics and Health Data Science Unit, Toulouse, France
| | - Juan-Pablo Cerapio
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
| | - Marion Perrier
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
| | - Aurore Siegfried
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- CHU de Toulouse, Anatomopathology Department, Toulouse, France
| | - Florent Arnauduc
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- UFR Santé, Université de Toulouse III–Paul Sabatier, Toulouse, France
| | - Yvan Nicaise
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- UFR Santé, Université de Toulouse III–Paul Sabatier, Toulouse, France
| | - Perrine Dahan
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
| | - Thomas Filleron
- Institut Claudius Regaud, IUCT-Oncopole, Biostatistics and Health Data Science Unit, Toulouse, France
| | - Muriel Mounier
- Institut Claudius Regaud, IUCT-Oncopole, Clinical Trials Office, Toulouse, France
| | - Christine Toulas
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- Institut Claudius Regaud, IUCT-Oncopole, Cancer Biology Department, Molecular Oncology Division, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III–Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France
- UFR Santé, Université de Toulouse III–Paul Sabatier, Toulouse, France
- Institut Claudius Regaud, IUCT-Oncopole, Radiation Oncology Department, Toulouse, France
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2
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Guerini AE, Nici S, Magrini SM, Riga S, Toraci C, Pegurri L, Facheris G, Cozzaglio C, Farina D, Liserre R, Gasparotti R, Ravanelli M, Rondi P, Spiazzi L, Buglione M. Adoption of Hybrid MRI-Linac Systems for the Treatment of Brain Tumors: A Systematic Review of the Current Literature Regarding Clinical and Technical Features. Technol Cancer Res Treat 2023; 22:15330338231199286. [PMID: 37774771 PMCID: PMC10542234 DOI: 10.1177/15330338231199286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/24/2023] [Accepted: 08/08/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Possible advantages of magnetic resonance (MR)-guided radiation therapy (MRgRT) for the treatment of brain tumors include improved definition of treatment volumes and organs at risk (OARs) that could allow margin reductions, resulting in limited dose to the OARs and/or dose escalation to target volumes. Recently, hybrid systems integrating a linear accelerator and an magnetic resonance imaging (MRI) scan (MRI-linacs, MRL) have been introduced, that could potentially lead to a fully MRI-based treatment workflow. METHODS We performed a systematic review of the published literature regarding the adoption of MRL for the treatment of primary or secondary brain tumors (last update November 3, 2022), retrieving a total of 2487 records; after a selection based on title and abstracts, the full text of 74 articles was analyzed, finally resulting in the 52 papers included in this review. RESULTS AND DISCUSSION Several solutions have been implemented to achieve a paradigm shift from CT-based radiotherapy to MRgRT, such as the management of geometric integrity and the definition of synthetic CT models that estimate electron density. Multiple sequences have been optimized to acquire images with adequate quality with on-board MR scanner in limited times. Various sophisticated algorithms have been developed to compensate the impact of magnetic field on dose distribution and calculate daily adaptive plans in a few minutes with satisfactory dosimetric parameters for the treatment of primary brain tumors and cerebral metastases. Dosimetric studies and preliminary clinical experiences demonstrated the feasibility of treating brain lesions with MRL. CONCLUSIONS The adoption of an MRI-only workflow is feasible and could offer several advantages for the treatment of brain tumors, including superior image quality for lesions and OARs and the possibility to adapt the treatment plan on the basis of daily MRI. The growing body of clinical data will clarify the potential benefit in terms of toxicity and response to treatment.
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Affiliation(s)
- Andrea Emanuele Guerini
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
- Co-first authors
| | - Stefania Nici
- Medical Physics Department, ASST Spedali Civili Hospital, Brescia, Italy
- Co-first authors
| | - Stefano Maria Magrini
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
| | - Stefano Riga
- Medical Physics Department, ASST Spedali Civili Hospital, Brescia, Italy
| | - Cristian Toraci
- Medical Physics Department, ASST Spedali Civili Hospital, Brescia, Italy
| | - Ludovica Pegurri
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
| | - Giorgio Facheris
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
| | - Claudia Cozzaglio
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
- Medical Physics Department, ASST Spedali Civili Hospital, Brescia, Italy
| | - Davide Farina
- Radiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Roberto Liserre
- Department of Radiology, Neuroradiology Unit, ASST Spedali Civili University Hospital, Brescia, Italy
| | - Roberto Gasparotti
- Neuroradiology Unit, Department of Medical-Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Marco Ravanelli
- Radiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Paolo Rondi
- Radiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Luigi Spiazzi
- Medical Physics Department, ASST Spedali Civili Hospital, Brescia, Italy
- Co-last author
| | - Michela Buglione
- Department of Radiation Oncology, University and Spedali Civili Hospital, Brescia, Italy
- Co-last author
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Abstract
Abstract
Purpose
Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.
Methods
PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.
Results
We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.
Conclusions
Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.
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Candiota AP, Arús C. Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives. Metabolites 2022; 12:metabo12030243. [PMID: 35323686 PMCID: PMC8950145 DOI: 10.3390/metabo12030243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 11/16/2022] Open
Abstract
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.
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Affiliation(s)
- Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Correspondence:
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5
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Pang Y, Wang H, Li H. Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy. Front Oncol 2022; 11:764665. [PMID: 35111666 PMCID: PMC8801459 DOI: 10.3389/fonc.2021.764665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 11/29/2021] [Indexed: 12/22/2022] Open
Abstract
Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.
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Affiliation(s)
- Yaru Pang
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Hui Wang
- Department of Chemical Engineering, University College London, London, United Kingdom
| | - He Li
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
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6
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Connor M, Kim MM, Cao Y, Hattangadi-Gluth J. Precision Radiotherapy for Gliomas: Implementing Novel Imaging Biomarkers to Improve Outcomes With Patient-Specific Therapy. Cancer J 2021; 27:353-363. [PMID: 34570449 PMCID: PMC8480523 DOI: 10.1097/ppo.0000000000000546] [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] [Indexed: 11/27/2022]
Abstract
ABSTRACT Gliomas are the most common primary brain cancer, yet are extraordinarily challenging to treat because they can be aggressive and infiltrative, locally recurrent, and resistant to standard treatments. Furthermore, the treatments themselves, including radiation therapy, can affect patients' neurocognitive function and quality of life. Noninvasive imaging is the standard of care for primary brain tumors, including diagnosis, treatment planning, and monitoring for treatment response. This article explores the ways in which advanced imaging has and will continue to transform radiation treatment for patients with gliomas, with a focus on cognitive preservation and novel biomarkers, as well as precision radiotherapy and treatment adaptation. Advances in novel imaging techniques continue to push the field forward, to more precisely guided treatment planning, radiation dose escalation, measurement of therapeutic response, and understanding of radiation-associated injury.
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Affiliation(s)
- Michael Connor
- From the Department of Radiation Medicine and Applied Sciences, UC San Diego, Moores Cancer Center, La Jolla, CA
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Jona Hattangadi-Gluth
- From the Department of Radiation Medicine and Applied Sciences, UC San Diego, Moores Cancer Center, La Jolla, CA
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7
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Wang C, Padgett KR, Su MY, Mellon EA, Maziero D, Chang Z. Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy. Med Phys 2021; 49:2794-2819. [PMID: 34374098 DOI: 10.1002/mp.15130] [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] [Received: 03/03/2021] [Revised: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 11/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
| | - Kyle R Padgett
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA.,Department of Radiology, University of Miami, Miami, Florida, USA
| | - Min-Ying Su
- Department of Radiological Sciences, University of California, Irvine, California, USA.,Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Eric A Mellon
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Danilo Maziero
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Zheng Chang
- Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
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8
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Mohan S, Wang S, Chawla S, Abdullah K, Desai A, Maloney E, Brem S. Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma. Surg Neurol Int 2021; 12:337. [PMID: 34345478 PMCID: PMC8326072 DOI: 10.25259/sni_353_2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 06/09/2021] [Indexed: 11/04/2022] Open
Abstract
Background Glioblastoma (GBM) is the most common malignant brain tumor and carries a dismal prognosis. Attempts to develop biologically targeted therapies are challenging as the blood-brain barrier can limit drugs from reaching their target when administered through conventional (intravenous or oral) routes. Furthermore, systemic toxicity of drugs often limits their therapeutic potential. To circumvent these problems, convection-enhanced delivery (CED) provides direct, targeted, intralesional therapy with a secondary objective to alter the tumor microenvironment from an immunologically "cold" (nonresponsive) to an "inflamed" (immunoresponsive) tumor. Case Description We report a patient with right occipital recurrent GBM harboring poor prognostic genotypes who was treated with MRI-guided CED of a fusion protein MDNA55 (a targeted toxin directed toward the interleukin-4 receptor). The patient underwent serial anatomical, diffusion, and perfusion MRI scans before initiation of targeted therapy and at 1, 3-month posttherapy. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume was noted at follow-up periods relative to baseline. Conclusion Our findings suggest that diffusion and perfusion MRI techniques may be useful in evaluating early response to CED of MDNA55 in recurrent GBM patients.
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Affiliation(s)
- Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sanjeev Chawla
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Kalil Abdullah
- Department of Neurosurgery, University of Texas-Southwestern Medical Center, Dallas, Texas, United States
| | - Arati Desai
- Department of Medicine Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Eileen Maloney
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
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9
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Maudsley AA, Andronesi OC, Barker PB, Bizzi A, Bogner W, Henning A, Nelson SJ, Posse S, Shungu DC, Soher BJ. Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4309. [PMID: 32350978 PMCID: PMC7606742 DOI: 10.1002/nbm.4309] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 02/01/2020] [Accepted: 03/10/2020] [Indexed: 05/04/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.
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Affiliation(s)
- Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Ovidiu C Andronesi
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, and the Kennedy Krieger Institute, F.M. Kirby Center for Functional Brain Imaging, Baltimore, Maryland
| | - Alberto Bizzi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico
| | - Dikoma C Shungu
- Department of Neuroradiology, Weill Cornell Medical College, New York, New York
| | - Brian J Soher
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
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10
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Maziero D, Straza MW, Ford JC, Bovi JA, Diwanji T, Stoyanova R, Paulson ES, Mellon EA. MR-Guided Radiotherapy for Brain and Spine Tumors. Front Oncol 2021; 11:626100. [PMID: 33763361 PMCID: PMC7982530 DOI: 10.3389/fonc.2021.626100] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 02/12/2021] [Indexed: 12/19/2022] Open
Abstract
MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.
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Affiliation(s)
- Danilo Maziero
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Michael W Straza
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - John C Ford
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Joseph A Bovi
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Tejan Diwanji
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Radka Stoyanova
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Eric A Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
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11
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Castellano A, Bailo M, Cicone F, Carideo L, Quartuccio N, Mortini P, Falini A, Cascini GL, Minniti G. Advanced Imaging Techniques for Radiotherapy Planning of Gliomas. Cancers (Basel) 2021; 13:cancers13051063. [PMID: 33802292 PMCID: PMC7959155 DOI: 10.3390/cancers13051063] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 02/07/2023] Open
Abstract
The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Michele Bailo
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Francesco Cicone
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
- Correspondence: ; Tel.: +39-0-961-369-4155
| | - Luciano Carideo
- National Cancer Institute, G. Pascale Foundation, 80131 Naples, Italy;
| | - Natale Quartuccio
- A.R.N.A.S. Ospedale Civico Di Cristina Benfratelli, 90144 Palermo, Italy;
| | - Pietro Mortini
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Andrea Falini
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Giuseppe Lucio Cascini
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, 53100 Siena, Italy;
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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12
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Kim MM, Aryal MP, Sun Y, Parmar HA, Li P, Schipper M, Wahl DR, Lawrence TS, Cao Y. Response assessment during chemoradiation using a hypercellular/hyperperfused imaging phenotype predicts survival in patients with newly diagnosed glioblastoma. Neuro Oncol 2021; 23:1537-1546. [PMID: 33599755 DOI: 10.1093/neuonc/noab038] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Adversely prognostic hypercellular and hyperperfused regions of glioblastoma (GBM) predict progression-free survival, and are a novel target for dose-intensified chemoradiation (chemoRT) recently implemented in a phase II clinical trial. As a secondary aim, we hypothesized that dose-intensified chemoRT would induce greater mid-treatment response of hypercellular/hyperperfused tumor regions vs standard chemoradiation, and that early response would improve overall survival (OS). METHODS Forty-nine patients with newly diagnosed GBM underwent prospective, multiparametric high b value diffusion-weighted MRI (DW-MRI) and perfusion dynamic contrast-enhanced MRI (DCE-MRI) pre-RT and 3-4 weeks into RT. The hypercellular tumor volume (TVHCV, mean contralateral normal brain + 2SD) and hyperperfused tumor volume (TVCBV, contralateral normal frontal gray matter + 1SD) were generated using automated thresholding. Twenty-six patients were enrolled on a dose-escalation trial targeting TVHCV/TVCBV with 75 Gy in 30 fractions, and 23 non-trial patients comprised the control group. OS was estimated using the Kaplan-Meier method and compared using the log-rank test. The effect of TVHCV/TVCBV and Gd-enhanced tumor volume on OS was assessed using multivariable Cox proportional-hazard regression. RESULTS Most patients had gross total (47%) or subtotal resection (37%), 25% were MGMT-methylated. Patients treated on the dose-escalation trial had significantly greater reduction in TVHCV/TVCBV (41% reduction, IQR 17%-75%) vs non-trial patients (6% reduction, IQR 6%-22%, P = .002). An increase in TVHCV/TVCBV during chemoRT was associated with worse OS (adjusted hazard ratio [aHR] 1.2, 95%CI 1.0-1.4, P = .02), while pre-treatment tumor volumes (P > .5) and changes in Gd-enhanced volume (P = .9) were not. CONCLUSIONS Multiparametric MRI permits identification of therapeutic resistance during chemoRT and supports adaptive strategies in future trials.
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Affiliation(s)
- Michelle M Kim
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Madhava P Aryal
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Yilun Sun
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Hemant A Parmar
- Department of Radiology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Pin Li
- Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew Schipper
- Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel R Wahl
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Theodore S Lawrence
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA
| | - Yue Cao
- Department of Radiation Oncology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiology, The University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, The University of Michigan, Ann Arbor, Michigan, USA
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13
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van Houdt PJ, Yang Y, van der Heide UA. Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy. Front Oncol 2021; 10:615643. [PMID: 33585242 PMCID: PMC7878523 DOI: 10.3389/fonc.2020.615643] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, CA, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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14
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Laino ME, Young R, Beal K, Haque S, Mazaheri Y, Corrias G, Bitencourt AG, Karimi S, Thakur SB. Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning. BJR Open 2020; 2:20190026. [PMID: 33178960 PMCID: PMC7594883 DOI: 10.1259/bjro.20190026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 01/13/2020] [Accepted: 03/18/2020] [Indexed: 12/23/2022] Open
Abstract
The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications.
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Affiliation(s)
| | - Robert Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - Kathryn Beal
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - Sofia Haque
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | | | - Giuseppe Corrias
- Department of Radiology, University of Cagliari, 40 Via Università, 09124 Cagliari, Italy
| | | | - Sasan Karimi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
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15
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Bolan PJ, Branzoli F, Di Stefano AL, Nichelli L, Valabregue R, Saunders SL, Akçakaya M, Sanson M, Lehéricy S, Marjańska M. Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2020; 12267:730-739. [PMID: 35005744 PMCID: PMC8735854 DOI: 10.1007/978-3-030-59728-3_71] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In vivo magnetic resonance spectroscopy (MRS) can provide clinically valuable metabolic information from brain tumors that can be used for prognosis and monitoring response to treatment. Unfortunately, this technique has not been widely adopted in clinical practice or even clinical trials due to the difficulty in acquiring and analyzing the data. In this work we propose a computational approach to solve one of the most critical technical challenges: the problem of quickly and accurately positioning an MRS volume of interest (a cuboid voxel) inside a tumor using MR images for guidance. The proposed automated method comprises a convolutional neural network to segment the lesion, followed by a discrete optimization to position an MRS voxel optimally within the lesion. In a retrospective comparison, the novel automated method is shown to provide improved lesion coverage compared to manual voxel placement.
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Affiliation(s)
- Patrick J Bolan
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Francesca Branzoli
- Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Paris, France
- Sorbonne Université, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Anna Luisa Di Stefano
- Hôpital de la Pitié-Salpêtrière, Service de Neurologie 2, Paris, France
- Department of Neurology, Foch Hospital, Suresnes, Paris, France
| | - Lucia Nichelli
- Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Paris, France
- Sorbonne Université, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Romain Valabregue
- Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Paris, France
- Sorbonne Université, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Sara L Saunders
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Mehmet Akçakaya
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis MN, USA
| | - Marc Sanson
- Sorbonne Université, Inserm U 1127, CNRS UMR 7225, Paris, France
- Hôpital de la Pitié-Salpêtrière, Service de Neurologie 2, Paris, France
- Onconeurotek tumor bank, Institut du Cerveau et de la Moelle épinère - ICM, Paris, France
| | - Stéphane Lehéricy
- Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Paris, France
- Sorbonne Université, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
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16
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Wang Y, Liu C, Zhang X, Deng W. Synthetic CT Generation Based on T2 Weighted MRI of Nasopharyngeal Carcinoma (NPC) Using a Deep Convolutional Neural Network (DCNN). Front Oncol 2019; 9:1333. [PMID: 31850218 PMCID: PMC6901977 DOI: 10.3389/fonc.2019.01333] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 11/14/2019] [Indexed: 01/31/2023] Open
Abstract
Purpose: There is an emerging interest of applying magnetic resonance imaging (MRI) to radiotherapy (RT) due to its superior soft tissue contrast for accurate target delineation as well as functional information for evaluating treatment response. MRI-based RT planning has great potential to enable dose escalation to tumors while reducing toxicities to surrounding normal tissues in RT treatments of nasopharyngeal carcinoma (NPC). Our study aims to generate synthetic CT from T2-weighted MRI using a deep learning algorithm. Methods: Thirty-three NPC patients were retrospectively selected for this study with local IRB's approval. All patients underwent clinical CT simulation and 1.5T MRI within the same week in our hospital. Prior to CT/MRI image registration, we had to normalize two different modalities to a similar intensity scale using the histogram matching method. Then CT and T2 weighted MRI were rigidly and deformably registered using intensity-based registration toolbox elastix (version 4.9). A U-net deep learning algorithm with 23 convolutional layers was developed to generate synthetic CT (sCT) using 23 NPC patients' images as the training set. The rest 10 NPC patients were used as the test set (~1/3 of all datasets). Mean absolute error (MAE) and mean error (ME) were calculated to evaluate HU differences between true CT and sCT in bone, soft tissue and overall region. Results: The proposed U-net algorithm was able to create sCT based on T2-weighted MRI in NPC patients, which took 7 s per patient on average. Compared to true CT, MAE of sCT in all tested patients was 97 ± 13 Hounsfield Unit (HU) in soft tissue, 131 ± 24 HU in overall region, and 357 ± 44 HU in bone, respectively. ME was −48 ± 10 HU in soft tissue, −6 ± 13 HU in overall region, and 247 ± 44 HU in bone, respectively. The majority soft tissue and bone region was reconstructed accurately except the interface between soft tissue and bone and some delicate structures in nasal cavity, where the inaccuracy was induced by imperfect deformable registration. One patient example was shown with almost no difference in dose distribution using true CT vs. sCT in the PTV regions in the sinus area with fine bone structures. Conclusion: Our study indicates that it is feasible to generate high quality sCT images based on T2-weighted MRI using the deep learning algorithm in patients with nasopharyngeal carcinoma, which may have great clinical potential for MRI-only treatment planning in the future.
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Affiliation(s)
- Yuenan Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Chenbin Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Xiao Zhang
- Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Weiwei Deng
- Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen, China
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17
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Meissner J, Korzowski A, Regnery S, Goerke S, Breitling J, Floca RO, Debus J, Schlemmer H, Ladd ME, Bachert P, Adeberg S, Paech D. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T. J Magn Reson Imaging 2019; 50:1268-1277. [DOI: 10.1002/jmri.26702] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/15/2019] [Accepted: 02/15/2019] [Indexed: 12/17/2022] Open
Affiliation(s)
- Jan‐Eric Meissner
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Andreas Korzowski
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Sebastian Regnery
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | - Steffen Goerke
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Johannes Breitling
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- MPI for Nuclear PhysicsMax‐Planck‐Society Heidelberg Germany
| | - Ralf Omar Floca
- Division of Medical Image ComputingGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Jürgen Debus
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | | | - Mark Edward Ladd
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- Faculty of MedicineUniversity of Heidelberg Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
| | - Sebastian Adeberg
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Daniel Paech
- Division of RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
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18
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Press RH, Zhong J, Gurbani SS, Weinberg BD, Eaton BR, Shim H, Shu HKG. The Role of Standard and Advanced Imaging for the Management of Brain Malignancies From a Radiation Oncology Standpoint. Neurosurgery 2018; 85:165-179. [DOI: 10.1093/neuros/nyy461] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 08/30/2018] [Indexed: 01/20/2023] Open
Abstract
Abstract
Radiation therapy (RT) plays a critical role in the overall management of many central nervous system (CNS) tumors. Advances in RT treatment planning, with techniques such as intensity modulated radiation therapy, volumetric modulated arc therapy, and stereotactic radiosurgery, now allow the delivery of highly conformal dose with great precision. These techniques rely on high-resolution 3-dimensional anatomical imaging modalities such as computed tomography or magnetic resonance imaging (MRI) scans to accurately and reliably define CNS targets and normal tissue avoidance structures. The integration of cross-sectional imaging into radiation oncology has directly translated into improvements in the therapeutic window of RT, and the union between radiation oncology and imaging is only expected to grow stronger. In addition, advanced imaging modalities including diffusion, perfusion, and spectroscopic MRIs as well as positron emission tomography (PET) scans with novel tracers are being utilized to provide additional insight into tumor biology and behavior beyond anatomy. Together, these standard and advanced imaging modalities hold significant potential to improve future RT delivery and response assessment. In this review, we will discuss the current utilization of standard/advanced imaging for CNS tumors from a radiation oncology perspective as well as the implications of novel MRI and PET modalities currently under investigation.
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Affiliation(s)
- Robert H Press
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Jim Zhong
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Saumya S Gurbani
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia
| | - Bree R Eaton
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
| | - Hyunsuk Shim
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Hui-Kuo G Shu
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia
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19
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Press RH, Shu HKG, Shim H, Mountz JM, Kurland BF, Wahl RL, Jones EF, Hylton NM, Gerstner ER, Nordstrom RJ, Henderson L, Kurdziel KA, Vikram B, Jacobs MA, Holdhoff M, Taylor E, Jaffray DA, Schwartz LH, Mankoff DA, Kinahan PE, Linden HM, Lambin P, Dilling TJ, Rubin DL, Hadjiiski L, Buatti JM. The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective. Int J Radiat Oncol Biol Phys 2018; 102:1219-1235. [PMID: 29966725 PMCID: PMC6348006 DOI: 10.1016/j.ijrobp.2018.06.023] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2018] [Revised: 05/25/2018] [Accepted: 06/14/2018] [Indexed: 02/07/2023]
Abstract
Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.
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Affiliation(s)
- Robert H. Press
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - Hui-Kuo G. Shu
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - Hyunsuk Shim
- Dept. of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - James M. Mountz
- Dept. of Radiology, University of Pittsburgh, Pittsburgh, PA
| | | | | | - Ella F. Jones
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA
| | - Nola M. Hylton
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA
| | - Elizabeth R. Gerstner
- Dept. of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | | | - Lori Henderson
- Cancer Imaging Program, National Cancer Institute, Bethesda, MD
| | | | - Bhadrasain Vikram
- Radiation Research Program/Division of Cancer Treatment & Diagnosis, National Cancer Institute, Bethesda, MD
| | - Michael A. Jacobs
- Dept. of Radiology and Radiological Science, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore MD
| | - Matthias Holdhoff
- Brain Cancer Program, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore MD
| | - Edward Taylor
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - David A. Jaffray
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | | | - David A. Mankoff
- Dept. of Radiology, University of Pennsylvania, Philadelphia, PA
| | | | | | - Philippe Lambin
- Dept. of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Thomas J. Dilling
- Dept. of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | | | | | - John M. Buatti
- Dept. of Radiation Oncology, University of Iowa, Iowa City, IA
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20
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Vareth M, Lupo J, Larson P, Nelson S. A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors. NMR IN BIOMEDICINE 2018; 31:e3929. [PMID: 30168205 PMCID: PMC6290901 DOI: 10.1002/nbm.3929] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 03/01/2018] [Accepted: 03/07/2018] [Indexed: 05/12/2023]
Abstract
The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm3 ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.
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Affiliation(s)
- Maryam Vareth
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Janine Lupo
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Peder Larson
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sarah Nelson
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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21
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Vareth M, Lupo J, Larson P, Nelson S. A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors. NMR IN BIOMEDICINE 2018. [PMID: 30168205 DOI: 10.1002/nbm.3929e3929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm3 ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.
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Affiliation(s)
- Maryam Vareth
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Janine Lupo
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Peder Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sarah Nelson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
- Surbeck Laboratory of Advanced Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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22
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Abstract
Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.
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Affiliation(s)
- Geoffrey S Payne
- University Hospitals Southampton NHS Foundation Trust, Tremona Road, Southampton SO16 6YD, United Kingdom
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23
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Maudsley AA. Lesion segmentation for MR spectroscopic imaging using the convolution difference method. Magn Reson Med 2018; 81:1499-1510. [PMID: 30303564 DOI: 10.1002/mrm.27500] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 07/18/2018] [Accepted: 08/01/2018] [Indexed: 11/05/2022]
Abstract
PURPOSE Delineation of lesion boundaries from volumetric MRSI metabolite ratio maps using a method that accounts for the spatial response function of the acquisition and variable spectral quality and is robust to signal heterogeneity within the lesion. METHODS A novel method for lesion segmentation, termed convolution difference, has been developed that is robust to signal heterogeneity within the lesion and to differences in the spatial response function. Procedures are described for processing metabolite ratio maps and to exclude regions of inadequate spectral quality. This method was evaluated using computer simulations, and the results were compared with an iterative thresholding technique that determines an optimal amplitude threshold, and with the use of a fixed amplitude threshold. These methods were evaluated for segmentation of volumetric MRSI studies of gliomas using maps of the choline to N-acetylaspartate ratio, and a qualitative comparison of lesion volumes carried out. RESULTS Simulation studies indicated improved performance for the convolution difference method when applied to ratio maps. Variations in tumor volume were observed for the in vivo studies between the convolution difference and the iterative thresholding methods; however, visual analysis indicates that both showed improved accuracy in comparison to using a fixed amplitude threshold. CONCLUSION This study reinforces previous reports indicating that the use of fixed threshold values for segmentation of maps with broad spatial response functions can result in errors in lesion volume definition. A novel segmentation method, termed the convolution difference, has been introduced and demonstrated to be robust for segmentation of volumetric MRSI metabolite data.
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Affiliation(s)
- Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, Florida
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24
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Nelson SJ, Kadambi AK, Park I, Li Y, Crane J, Olson M, Molinaro A, Roy R, Butowski N, Cha S, Chang S. Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen. Neuro Oncol 2017; 19:430-439. [PMID: 27576874 DOI: 10.1093/neuonc/now159] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2016] [Accepted: 06/16/2016] [Indexed: 12/27/2022] Open
Abstract
Background The heterogeneous biology of glioblastoma (GBM) emphasizes the need for imaging methods to assess tumor burden and assist in evaluating individual patients. The purpose of this study was to investigate early changes in metrics from 3D 1H magnetic resonance spectroscopic imaging (MRSI) data, compare them with anatomic lesion volumes, and determine whether they were associated with survival for patients with newly diagnosed GBM receiving a multimodality treatment regimen. Methods Serial MRI and MRSI scans provided estimates of anatomic lesion volumes and levels of choline, creatine, N-acetylaspartate, lactate, and lipid. The association of metrics derived from these data with survival was assessed using Cox proportional hazards models with adjustments for age, Karnofsky performance score, and extent of resection. Temporal changes in parameters were evaluated using a Wilcoxon signed rank test. Results Anatomic lesion volumes at the post-radiotherapy (RT) scan, metabolic lesion volume at mid-RT and post-RT scans, as well as metrics describing levels of choline, lactate, and lipid were associated with overall survival. There was a significant reduction in the enhancing lesion volume, increase in T2 lesion volume from mid-RT to post-RT, and decrease in parameters describing metabolite levels during these early time points. Conclusion The MRSI data provided metrics that described the effects of treatment on the metabolic lesion burden and were associated with overall survival. This suggests that adding these parameters to standard assessments of changes in anatomic lesion volumes could contribute to making early decisions about the efficacy of such combination therapies.
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Affiliation(s)
- Sarah J Nelson
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California
| | - Achuta K Kadambi
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Ilwoo Park
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Yan Li
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Jason Crane
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Marram Olson
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Annette Molinaro
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.,Department of Neurological Surgery, University of California, San Francisco, California
| | - Ritu Roy
- Surbeck Laboratory of Advanced Imaging, University of California, San Francisco, California
| | - Nicholas Butowski
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.,Department of Neurological Surgery, University of California, San Francisco, California
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California.,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California.,Department of Neurological Surgery, University of California, San Francisco, California
| | - Susan Chang
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California
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25
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Cao Y, Tseng CL, Balter JM, Teng F, Parmar HA, Sahgal A. MR-guided radiation therapy: transformative technology and its role in the central nervous system. Neuro Oncol 2017; 19:ii16-ii29. [PMID: 28380637 DOI: 10.1093/neuonc/nox006] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.
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Affiliation(s)
- Yue Cao
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Radiology, University of Michigan, Ann Arbor, Michigan, USA
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - James M Balter
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Feifei Teng
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, China
| | | | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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26
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Andronesi OC, Esmaeili M, Borra RJH, Emblem K, Gerstner ER, Pinho MC, Plotkin SR, Chi AS, Eichler AF, Dietrich J, Ivy SP, Wen PY, Duda DG, Jain R, Rosen BR, Sorensen GA, Batchelor TT. Early changes in glioblastoma metabolism measured by MR spectroscopic imaging during combination of anti-angiogenic cediranib and chemoradiation therapy are associated with survival. NPJ Precis Oncol 2017; 1:20. [PMID: 29202103 PMCID: PMC5708878 DOI: 10.1038/s41698-017-0020-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/13/2022] Open
Abstract
Precise assessment of treatment response in glioblastoma during combined anti-angiogenic and chemoradiation remains a challenge. In particular, early detection of treatment response by standard anatomical imaging is confounded by pseudo-response or pseudo-progression. Metabolic changes may be more specific for tumor physiology and less confounded by changes in blood-brain barrier permeability. We hypothesize that metabolic changes probed by magnetic resonance spectroscopic imaging can stratify patient response early during combination therapy. We performed a prospective longitudinal imaging study in newly diagnosed glioblastoma patients enrolled in a phase II clinical trial of the pan-vascular endothelial growth factor receptor inhibitor cediranib in combination with standard fractionated radiation and temozolomide (chemoradiation). Forty patients were imaged weekly during therapy with an imaging protocol that included magnetic resonance spectroscopic imaging, perfusion magnetic resonance imaging, and anatomical magnetic resonance imaging. Data were analyzed using receiver operator characteristics, Cox proportional hazards model, and Kaplan-Meier survival plots. We observed that the ratio of total choline to healthy creatine after 1 month of treatment was significantly associated with overall survival, and provided as single parameter: (1) the largest area under curve (0.859) in receiver operator characteristics, (2) the highest hazard ratio (HR = 85.85, P = 0.006) in Cox proportional hazards model, (3) the largest separation (P = 0.004) in Kaplan-Meier survival plots. An inverse correlation was observed between total choline/healthy creatine and cerebral blood flow, but no significant relation to tumor volumetrics was identified. Our results suggest that in vivo metabolic biomarkers obtained by magnetic resonance spectroscopic imaging may be an early indicator of response to anti-angiogenic therapy combined with standard chemoradiation in newly diagnosed glioblastoma.
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Affiliation(s)
- Ovidiu C. Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Morteza Esmaeili
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Ronald J. H. Borra
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Medical Imaging Centre of Southwest Finland, Department of Diagnostic Radiology, Turku University Hospital, Turku, Finland
- Present Address: Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Kyrre Emblem
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: The Intervention Centre, Clinic for Diagnostics and Intervention, Oslo University Hospital, Oslo, Norway
| | - Elizabeth R. Gerstner
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Marco C. Pinho
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75235 USA
| | - Scott R. Plotkin
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Andrew S. Chi
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Brain Tumor Center, Laura and Isaac Perlmutter Cancer Center, New York University Langone Medical Center and School of Medicine, New York, NY 10016 USA
| | - April F. Eichler
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Neurology, Maine Medical Center, Portland, ME 04074 USA
| | - Jorg Dietrich
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - S. Percy Ivy
- Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD 20892 USA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02114 USA
| | - Dan G. Duda
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Rakesh Jain
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Bruce R. Rosen
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Gregory A. Sorensen
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: IMRIS, Deerfield Imaging, Minnetonka, MN 55343 USA
| | - Tracy T. Batchelor
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
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27
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Nelson SJ, Li Y, Lupo JM, Olson M, Crane JC, Molinaro A, Roy R, Clarke J, Butowski N, Prados M, Cha S, Chang SM. Serial analysis of 3D H-1 MRSI for patients with newly diagnosed GBM treated with combination therapy that includes bevacizumab. J Neurooncol 2016; 130:171-179. [PMID: 27535746 PMCID: PMC5069332 DOI: 10.1007/s11060-016-2229-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2016] [Accepted: 07/31/2016] [Indexed: 10/26/2022]
Abstract
Interpretation of changes in the T1- and T2-weighted MR images from patients with newly diagnosed glioblastoma (GBM) treated with standard of care in conjunction with anti-angiogenic agents is complicated by pseudoprogression and pseudoresponse. The hypothesis being tested in this study was that 3D H-1 magnetic resonance spectroscopic imaging (MRSI) provides estimates of levels of choline, creatine, N-acetylaspartate (NAA), lactate and lipid that change in response to treatment and that metrics describing these characteristics are associated with survival. Thirty-one patients with newly diagnosed GBM and being treated with radiation therapy (RT), temozolomide, erlotinib and bevacizumab were recruited to receive serial MR scans that included 3-D lactate edited MRSI at baseline, mid-RT, post-RT and at specific follow-up time points. The data were processed to provide estimates of metrics representing changes in metabolite levels relative to normal appearing brain. Cox proportional hazards analysis was applied to examine the relationship of these parameters with progression free survival (PFS) and overall survival (OS). There were significant reductions in parameters that describe relative levels of choline to NAA and creatine, indicating that the treatment caused a decrease in tumor cellularity. Changes in the levels of lactate and lipid relative to the NAA from contralateral brain were consistent with vascular normalization. Metabolic parameters from the first serial follow-up scan were associated with PFS and OS, when accounting for age and extent of resection. Integrating metabolic parameters into the assessment of patients with newly diagnosed GBM receiving therapies that include anti-angiogenic agents may be helpful for tracking changes in tumor burden, resolving ambiguities in anatomic images caused by non-specific treatment effects and for predicting outcome.
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Affiliation(s)
- Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, CA, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Marram Olson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Jason C Crane
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Annette Molinaro
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Ritu Roy
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Jennifer Clarke
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Nicholas Butowski
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Michael Prados
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
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28
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Rapalino O, Ratai EM. Multiparametric Imaging Analysis: Magnetic Resonance Spectroscopy. Magn Reson Imaging Clin N Am 2016; 24:671-686. [PMID: 27742109 DOI: 10.1016/j.mric.2016.06.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Magnetic resonance spectroscopy (MRS) is a magnetic resonance-based imaging modality that allows noninvasive sampling of metabolic changes in normal and abnormal brain parenchyma. MRS is particularly useful in the differentiation of developmental or non-neoplastic disorders from neoplastic processes. MRS is also useful during routine imaging follow-up after radiation treatment or during antiangiogenic treatment and for predicting outcomes and treatment response. The objective of this article is to provide a concise but thorough review of the basic physical principles, important applications of MRS in brain tumor imaging, and future directions.
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Affiliation(s)
- O Rapalino
- Neuroradiology Division, Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - E M Ratai
- Neuroradiology Division, Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Room 2301, Charlestown, MA 02129, USA.
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29
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Lai YL, Wu CY, Chao KSC. Biological imaging in clinical oncology: radiation therapy based on functional imaging. Int J Clin Oncol 2016; 21:626-632. [PMID: 27384183 DOI: 10.1007/s10147-016-1000-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 05/29/2016] [Indexed: 12/25/2022]
Abstract
Radiation therapy is one of the most effective tools for cancer treatment. In recent years, intensity-modulated radiation therapy has become increasingly popular in that target dose-escalation can be done while sparing adjacent normal tissues. For this reason, the development of measures to pave the way for accurate target delineation is of great interest. With the integration of functional information obtained by biological imaging with radiotherapy, strategies using advanced biological imaging to visualize metabolic pathways and to improve therapeutic index and predict treatment response are discussed in this article.
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Affiliation(s)
- Yo-Liang Lai
- Department of Radiation Oncology, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Chun-Yi Wu
- Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan
| | - K S Clifford Chao
- China Medical University, 91 Hsueh-Shih Road, Taichung, 40402, Taiwan.
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30
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Mohan S, Chawla S, Wang S, Verma G, Skolnik A, Brem S, Peters KB, Poptani H. Assessment of early response to tumor-treating fields in newly diagnosed glioblastoma using physiologic and metabolic MRI: initial experience. CNS Oncol 2016; 5:137-44. [PMID: 27076281 DOI: 10.2217/cns-2016-0003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Tumor-treating fields (TTFields) is a novel antimitotic treatment modality for patients with glioblastoma. To assess response to TTFields, a newly diagnosed patient with glioblastoma underwent diffusion, perfusion and 3D echo-planar spectroscopic imaging prior to initiation of TTFields plus temozolamide (baseline) and at 1- and 2-month follow-up periods. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume were noted at 2 months relative to baseline suggesting inhibition of tumor growth and angiogenesis. Additionally, a reduction in choline/creatine was also noted during this period. These preliminary data indicate the potential of physiologic and metabolic MRI in assessing early treatment response to TTFields in combination with temozolamide.
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Affiliation(s)
- Suyash Mohan
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Gaurav Verma
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron Skolnik
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Katherine B Peters
- The Preston Robert Tisch Brain Tumor Center, Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - Harish Poptani
- Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Cellular & Molecular Physiology, University of Liverpool, Liverpool, UK
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31
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Combs SE, Nüsslin F, Wilkens JJ. Individualized radiotherapy by combining high-end irradiation and magnetic resonance imaging. Strahlenther Onkol 2016; 192:209-15. [PMID: 26852244 DOI: 10.1007/s00066-016-0944-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Accepted: 01/14/2016] [Indexed: 01/22/2023]
Abstract
Image-guided radiotherapy (IGRT) has been integrated into daily clinical routine and can today be considered the standard especially with high-dose radiotherapy. Currently imaging is based on MV- or kV-CT, which has clear limitations especially in soft-tissue contrast. Thus, combination of magnetic resonance (MR) imaging and high-end radiotherapy opens a new horizon. The intricate technical properties of MR imagers pose a challenge to technology when combined with radiation technology. Several solutions that are almost ready for routine clinical application have been developed. The clinical questions include dose-escalation strategies, monitoring of changes during treatment as well as imaging without additional radiation exposure during treatment.
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Affiliation(s)
- Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, München, Germany. .,Institute of Innovative Radiotherapy (iRT), Department of Radiation Sciences (DRS), Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
| | - Fridtjof Nüsslin
- Department of Radiation Oncology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, München, Germany
| | - Jan J Wilkens
- Department of Radiation Oncology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, München, Germany.,Institute of Innovative Radiotherapy (iRT), Department of Radiation Sciences (DRS), Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
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32
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Chaumeil MM, Lupo JM, Ronen SM. Magnetic Resonance (MR) Metabolic Imaging in Glioma. Brain Pathol 2015; 25:769-80. [PMID: 26526945 PMCID: PMC8029127 DOI: 10.1111/bpa.12310] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Accepted: 08/25/2015] [Indexed: 12/25/2022] Open
Abstract
This review is focused on describing the use of magnetic resonance (MR) spectroscopy for metabolic imaging of brain tumors. We will first review the MR metabolic imaging findings generated from preclinical models, focusing primarily on in vivo studies, and will then describe the use of metabolic imaging in the clinical setting. We will address relatively well-established (1) H MRS approaches, as well as (31) P MRS, (13) C MRS and emerging hyperpolarized (13) C MRS methodologies, and will describe the use of metabolic imaging for understanding the basic biology of glioma as well as for improving the characterization and monitoring of brain tumors in the clinic.
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Affiliation(s)
| | - Janine M. Lupo
- Department of Radiology and Biomedical ImagingMission Bay Campus
| | - Sabrina M. Ronen
- Department of Radiology and Biomedical ImagingMission Bay Campus
- Brain Tumor Research CenterUniversity of CaliforniaSan FranciscoCA
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Prestwich R, Vaidyanathan S, Scarsbrook A. Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy. Clin Oncol (R Coll Radiol) 2015; 27:588-600. [DOI: 10.1016/j.clon.2015.06.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Revised: 06/02/2015] [Accepted: 06/08/2015] [Indexed: 02/03/2023]
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McGee KP, Hu Y, Tryggestad E, Brinkmann D, Witte B, Welker K, Panda A, Haddock M, Bernstein MA. MRI in radiation oncology: Underserved needs. Magn Reson Med 2015; 75:11-4. [PMID: 26173404 DOI: 10.1002/mrm.25826] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 06/09/2015] [Indexed: 12/12/2022]
Affiliation(s)
- Kiaran P McGee
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Erik Tryggestad
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Debra Brinkmann
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Bob Witte
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kirk Welker
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Anshuman Panda
- Department of Radiology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Michael Haddock
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
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von Neubeck C, Seidlitz A, Kitzler HH, Beuthien-Baumann B, Krause M. Glioblastoma multiforme: emerging treatments and stratification markers beyond new drugs. Br J Radiol 2015; 88:20150354. [PMID: 26159214 DOI: 10.1259/bjr.20150354] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Glioblastoma multiforme (GBM) is the most common primary brain tumour in adults. The standard therapy for GBM is maximal surgical resection followed by radiotherapy with concurrent and adjuvant temozolomide (TMZ). In spite of the extensive treatment, the disease is associated with poor clinical outcome. Further intensification of the standard treatment is limited by the infiltrating growth of the GBM in normal brain areas, the expected neurological toxicities with radiation doses >60 Gy and the dose-limiting toxicities induced by systemic therapy. To improve the outcome of patients with GBM, alternative treatment modalities which add low or no additional toxicities to the standard treatment are needed. Many Phase II trials on new chemotherapeutics or targeted drugs have indicated potential efficacy but failed to improve the overall or progression-free survival in Phase III clinical trials. In this review, we will discuss contemporary issues related to recent technical developments and new metabolic strategies for patients with GBM including MR (spectroscopy) imaging, (amino acid) positron emission tomography (PET), amino acid PET, surgery, radiogenomics, particle therapy, radioimmunotherapy and diets.
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Affiliation(s)
- C von Neubeck
- 1 German Cancer Consortium (DKTK), Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany.,2 OncoRay, National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - A Seidlitz
- 2 OncoRay, National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,3 Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - H H Kitzler
- 4 Department of Neuroradiology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - B Beuthien-Baumann
- 2 OncoRay, National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,5 Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,6 Helmholtz-Zentrum, Dresden-Rossendorf (HZDR), PET Centre, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - M Krause
- 1 German Cancer Consortium (DKTK), Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany.,2 OncoRay, National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,3 Department of Radiation Oncology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,7 Helmholtz-Zentrum, Dresden-Rossendorf (HZDR), Institute of Radiooncology, Dresden, Germany
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36
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Pun WK, Chow SP, Fang D, Cheng CL, Leong JC, Ng C. Post-traumatic oedema of the foot after tibial fracture. Expert Rev Mol Diagn 1990; 15:735-47. [PMID: 2592102 DOI: 10.1586/14737159.2015.1039515] [Citation(s) in RCA: 88] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
A total of 97 patients with diaphyseal tibial fractures treated with functional bracing were studied prospectively. Persistent ipsilateral foot swelling was present in 84.5 per cent of the patients. Most of the swellings subsided with time, but a small percentage of them persisted for a duration of 2 years or more after injury. The time for disappearance of the swelling in 50 per cent of the patients was 18.6 weeks. The development of oedema is not related to the age and sex of the patients, the configuration, type and level of the fractures, or the association of a fibular fracture. The bone healed quicker in those who did not have swelling of the foot. Once the swelling has developed, it seems to run its own course and its disappearance is not related to the age and sex, the configuration, type and level of fractures, the association of a fibular fracture, or the time for fracture healing. This complication does not have any adverse effect on the functional recovery of the patients.
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Affiliation(s)
- W K Pun
- Department of Orthopaedic Surgery, University of Hong Kong, Queen Mary Hospital
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