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Rejimon AC, Ramesh KK, Trivedi AG, Huang V, Schreibmann E, Weinberg BD, Kleinberg LR, Shu HKG, Shim H, Olson JJ. The Utility of Spectroscopic MRI in Stereotactic Biopsy and Radiotherapy Guidance in Newly Diagnosed Glioblastoma. Tomography 2024; 10:428-443. [PMID: 38535775 PMCID: PMC10975697 DOI: 10.3390/tomography10030033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/01/2024] Open
Abstract
Current diagnostic and therapeutic approaches for gliomas have limitations hindering survival outcomes. We propose spectroscopic magnetic resonance imaging as an adjunct to standard MRI to bridge these gaps. Spectroscopic MRI is a volumetric MRI technique capable of identifying tumor infiltration based on its elevated choline (Cho) and decreased N-acetylaspartate (NAA). We present the clinical translatability of spectroscopic imaging with a Cho/NAA ≥ 5x threshold for delineating a biopsy target in a patient diagnosed with non-enhancing glioma. Then, we describe the relationship between the undertreated tumor detected with metabolite imaging and overall survival (OS) from a pilot study of newly diagnosed GBM patients treated with belinostat and chemoradiation. Each cohort (control and belinostat) were split into subgroups using the median difference between pre-radiotherapy Cho/NAA ≥ 2x and the treated T1-weighted contrast-enhanced (T1w-CE) volume. We used the Kaplan-Meier estimator to calculate median OS for each subgroup. The median OS was 14.4 months when the difference between Cho/NAA ≥ 2x and T1w-CE volumes was higher than the median compared with 34.3 months when this difference was lower than the median. The T1w-CE volumes were similar in both subgroups. We find that patients who had lower volumes of undertreated tumors detected via spectroscopy had better survival outcomes.
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Affiliation(s)
- Abinand C. Rejimon
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA;
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Jeffrey J. Olson
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
- Department of Neurosurgery, Emory University, Atlanta, GA 30322, USA
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Laprie A, Noel G, Chaltiel L, Truc G, Sunyach MP, Charissoux M, Magne N, Auberdiac P, Biau J, Ken S, Tensaouti F, Khalifa J, Sidibe I, Roux FE, Vieillevigne L, Catalaa I, Boetto S, Uro-Coste E, Supiot S, Bernier V, Filleron T, Mounier M, Poublanc M, Olivier P, Delord JP, Cohen-Jonathan-Moyal E. Randomized phase III trial of metabolic imaging-guided dose escalation of radio-chemotherapy in patients with newly diagnosed glioblastoma (SPECTRO GLIO trial). Neuro Oncol 2024; 26:153-163. [PMID: 37417948 PMCID: PMC10768994 DOI: 10.1093/neuonc/noad119] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) systematically recurs after a standard 60 Gy radio-chemotherapy regimen. Since magnetic resonance spectroscopic imaging (MRSI) has been shown to predict the site of relapse, we analyzed the effect of MRSI-guided dose escalation on overall survival (OS) of patients with newly diagnosed GBM. METHODS In this multicentric prospective phase III trial, patients who had undergone biopsy or surgery for a GBM were randomly assigned to a standard dose (SD) of 60 Gy or a high dose (HD) of 60 Gy with an additional simultaneous integrated boost totaling 72 Gy to MRSI metabolic abnormalities, the tumor bed and residual contrast enhancements. Temozolomide was administered concomitantly and maintained for 6 months thereafter. RESULTS One hundred and eighty patients were included in the study between March 2011 and March 2018. After a median follow-up of 43.9 months (95% CI [42.5; 45.5]), median OS was 22.6 months (95% CI [18.9; 25.4]) versus 22.2 months (95% CI [18.3; 27.8]) for HD, and median progression-free survival was 8.6 (95% CI [6.8; 10.8]) versus 7.8 months (95% CI [6.3; 8.6]), in SD versus HD, respectively. No increase in toxicity rate was observed in the study arm. The pseudoprogression rate was similar across the SD (14.4%) and HD (16.7%) groups. For O(6)-methylguanine-DNA methyltransferase (MGMT) methylated patients, the median OS was 38 months (95% CI [23.2; NR]) for HD patients versus 28.5 months (95% CI [21.1; 35.7]) for SD patients. CONCLUSION The additional MRSI-guided irradiation dose totaling 72 Gy was well tolerated but did not improve OS in newly diagnosed GBM. TRIAL REGISTRATION NCT01507506; registration date: December 20, 2011. https://clinicaltrials.gov/ct2/show/NCT01507506?cond=NCT01507506&rank=1.
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Affiliation(s)
- Anne Laprie
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | | | - Leonor Chaltiel
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Gilles Truc
- Centre Georges-François Leclerc, Dijon, France
| | | | | | - Nicolas Magne
- Institut de Cancérologie de la Loire, Saint-Priest en Jarez, France
| | | | - Julian Biau
- Centre Jean-Perrin, Clermont-Ferrand, France
| | - Soléakhéna Ken
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, RadOpt-CRCT-INSERM, Toulouse, France
| | - Fatima Tensaouti
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole & ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Jonathan Khalifa
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | | | - Franck-Emmanuel Roux
- Centre Hospitalier Universitaire de Toulouse, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Laure Vieillevigne
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | | | - Sergio Boetto
- Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Emmanuelle Uro-Coste
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse-Oncopole, RadOpt-CRCT-INSERM, Toulouse, France
| | - Stéphane Supiot
- Institut de Cancerologie de l’Ouest, Nantes st Herblain, France
| | - Valérie Bernier
- Institut de Cancérologie de Lorraine Centre Alexis Vautrin, Nancy, France
| | - Thomas Filleron
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Muriel Mounier
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Muriel Poublanc
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Pascale Olivier
- Service de Pharmacologie Médicale et Clinique, Centre Régional de Pharmacovigilance, de Pharmacoépidémiologie et d’Information sur le Médicament CHU de Toulouse, Toulouse, France
| | - Jean-Pierre Delord
- Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
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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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Hasanzadeh A, Moghaddam HS, Shakiba M, Jalali AH, Firouznia K. The Role of Multimodal Imaging in Differentiating Vasogenic from Infiltrative Edema: A Systematic Review. Indian J Radiol Imaging 2023; 33:514-521. [PMID: 37811185 PMCID: PMC10556327 DOI: 10.1055/s-0043-1772466] [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] [Indexed: 10/10/2023] Open
Abstract
Background High-grade gliomas (HGGs) are the most prevalent primary malignancy of the central nervous system. The tumor results in vasogenic and infiltrative edema . Exact anatomical differentiation of these edemas is so important for surgical planning. Multimodal imaging could be used to differentiate the edema type. Purpose The aim of this study was to investigate the role of multimodal imaging in the differentiation of vasogenic edema from infiltrative edema in patients with HGG (grade III and grade IV). Data Sources A search on PubMed, EMBASE, Scopus, and ISI Web of Science Core Collection up to June 2022 using terms related to (a) multimodal imaging AND (b) HGG AND (c) edema. (PROSPERO registration number: CRD42022336131) Study Selection Two reviewers screened the articles and independently extracted the data. We included original articles assessing the role of multimodal imaging in differentiating vasogenic from infiltrative edema in patients with HGG. Six high-quality articles remained for the narrative synthesis. Data Synthesis Dynamic susceptibility contrast imaging showed that relative cerebral blood volume and relative cerebral blood flow were higher in the infiltrative edema component than in the vasogenic edema component. Diffusion tensor imaging revealed a dispute on fractional anisotropy. The apparent diffusion coefficient was comparable between the two edematous components. Magnetic resonance spectroscopy exhibited an increment in choline/creatinine ratio and choline/N-acetyl aspartate ratio in the infiltrative edema component. Limitations Strict study selection, low sample size of relevant published studies, and heterogeneity in endpoint variables were the major drawbacks. Conclusions Multimodal imaging, including dynamic susceptibility contrast and magnetic resonance spectroscopy, might help differentiate between vasogenic and infiltrative edema.
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Affiliation(s)
- Alireza Hasanzadeh
- Medical School, Tehran University of Medical Sciences, Tehran, Iran
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Sanjari Moghaddam
- Medical School, Tehran University of Medical Sciences, Tehran, Iran
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Madjid Shakiba
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Amir Hossein Jalali
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kavous Firouznia
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Aldawsari AM, Al-Qaisieh B, Broadbent DA, Bird D, Murray L, Speight R. The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review. Phys Imaging Radiat Oncol 2023; 27:100476. [PMID: 37565088 PMCID: PMC10410581 DOI: 10.1016/j.phro.2023.100476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 07/15/2023] [Accepted: 07/19/2023] [Indexed: 08/12/2023] Open
Abstract
Background and purpose Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning. Materials and methods PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution. Results Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps. Conclusions Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.
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Affiliation(s)
- Abeer M. Aldawsari
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh 12371, Saudi Arabia
| | - Bashar Al-Qaisieh
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David A. Broadbent
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David Bird
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - Louise Murray
- Department of Clinical Oncology, Leeds Teaching Hospitals NHS Trust, St James’s University Hospital, Leeds LS9 7LP, United Kingdom
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Richard Speight
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
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Zakharova NE, Batalov AI, Pogosbekian EL, Chekhonin IV, Goryaynov SA, Bykanov AE, Tyurina AN, Galstyan SA, Nikitin PV, Fadeeva LM, Usachev DY, Pronin IN. Perifocal Zone of Brain Gliomas: Application of Diffusion Kurtosis and Perfusion MRI Values for Tumor Invasion Border Determination. Cancers (Basel) 2023; 15:2760. [PMID: 37345097 DOI: 10.3390/cancers15102760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/28/2023] [Accepted: 05/09/2023] [Indexed: 06/23/2023] Open
Abstract
(1) Purpose: To determine the borders of malignant gliomas with diffusion kurtosis and perfusion MRI biomarkers. (2) Methods: In 50 high-grade glioma patients, diffusion kurtosis and pseudo-continuous arterial spin labeling (pCASL) cerebral blood flow (CBF) values were determined in contrast-enhancing area, in perifocal infiltrative edema zone, in the normal-appearing peritumoral white matter of the affected cerebral hemisphere, and in the unaffected contralateral hemisphere. Neuronavigation-guided biopsy was performed from all affected hemisphere regions. (3) Results: We showed significant differences between the DKI values in normal-appearing peritumoral white matter and unaffected contralateral hemisphere white matter. We also established significant (p < 0.05) correlations of DKI with Ki-67 labeling index and Bcl-2 expression activity in highly perfused enhancing tumor core and in perifocal infiltrative edema zone. CBF correlated with Ki-67 LI in highly perfused enhancing tumor core. One hundred percent of perifocal infiltrative edema tissue samples contained tumor cells. All glioblastoma samples expressed CD133. In the glioblastoma group, several normal-appearing white matter specimens were infiltrated by tumor cells and expressed CD133. (4) Conclusions: DKI parameters reveal changes in brain microstructure invisible on conventional MRI, e.g., possible infiltration of normal-appearing peritumoral white matter by glioma cells. Our results may be useful for plotting individual tumor invasion maps for brain glioma surgery or radiotherapy planning.
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Affiliation(s)
- Natalia E Zakharova
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Artem I Batalov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Eduard L Pogosbekian
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Ivan V Chekhonin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Sergey A Goryaynov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Andrey E Bykanov
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Anastasia N Tyurina
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Suzanna A Galstyan
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Pavel V Nikitin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Lyudmila M Fadeeva
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Dmitry Yu Usachev
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
| | - Igor N Pronin
- Federal State Autonomous Institution "N.N. Burdenko National Medical Research Center of Neurosurgery" of the Ministry of Health of the Russian, 4th Tverskaya-Yamskaya Str. 16, Moscow 125047, Russia
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7
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Tensaouti F, Desmoulin F, Gilhodes J, Roques M, Ken S, Lotterie JA, Noël G, Truc G, Sunyach MP, Charissoux M, Magné N, Lubrano V, Péran P, Cohen-Jonathan Moyal E, Laprie A. Is pre-radiotherapy metabolic heterogeneity of glioblastoma predictive of progression-free survival? Radiother Oncol 2023; 183:109665. [PMID: 37024057 DOI: 10.1016/j.radonc.2023.109665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 03/25/2023] [Accepted: 03/28/2023] [Indexed: 04/08/2023]
Abstract
BACKGROUND AND PURPOSE All glioblastoma subtypes share the hallmark of aggressive invasion, meaning that it is crucial to identify their different components if we are to ensure effective treatment and improve survival. Proton MR spectroscopic imaging (MRSI) is a noninvasive technique that yields metabolic information and is able to identify pathological tissue with high accuracy. The aim of the present study was to identify clusters of metabolic heterogeneity, using a large MRSI dataset, and determine which of these clusters are predictive of progression-free survival (PFS). MATERIALS AND METHODS MRSI data of 180 patients acquired in a pre-radiotherapy examination were included in the prospective SPECTRO-GLIO trial. Eight features were extracted for each spectrum: Cho/NAA, NAA/Cr, Cho/Cr, Lac/NAA, and the ratio of each metabolite to the sum of all the metabolites. Clustering of data was performed using a mini-batch k-means algorithm. The Cox model and logrank test were used for PFS analysis. RESULTS Five clusters were identified as sharing similar metabolic information and being predictive of PFS. Two clusters revealed metabolic abnormalities. PFS was lower when Cluster 2 was the dominant cluster in patients' MRSI data. Among the metabolites, lactate (present in this cluster and in Cluster 5) was the most statistically significant predictor of poor outcome. CONCLUSION Results showed that pre-radiotherapy MRSI can be used to reveal tumor heterogeneity. Groups of spectra, which have the same metabolic information, reflect the different tissue components representative of tumor burden proliferation and hypoxia. Clusters with metabolic abnormalities and high lactate are predictive of PFS.
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Affiliation(s)
- Fatima Tensaouti
- Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, Radiation oncology, Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France.
| | - Franck Desmoulin
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Julia Gilhodes
- Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, Biostatistics, Toulouse, France
| | - Margaux Roques
- CHU Toulouse, Neuroradiology, Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Soleakhena Ken
- Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, Engineering and Medical Physics, Toulouse, France; Inserm U1037- Centre de Recherches contre le Cancer de Toulouse, Radiation oncology, Toulouse, France
| | - Jean-Albert Lotterie
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France; CHU Toulouse, Nuclear Medicine, Toulouse, France
| | | | - Gilles Truc
- Centre Georges-François Leclerc, Radiation Oncology, Dijon, France
| | | | - Marie Charissoux
- Institut du Cancer de Montpellier, Radiation Oncology, Montpellier, France
| | - Nicolas Magné
- Institut de Cancérologie de la Loire Lucien Neuwirth, Radiation Oncology, Saint-Priest-en-Jarez, France
| | - Vincent Lubrano
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Patrice Péran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Elizabeth Cohen-Jonathan Moyal
- Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, Radiation oncology, Toulouse, France; Inserm U1037- Centre de Recherches contre le Cancer de Toulouse, Radiation oncology, Toulouse, France
| | - Anne Laprie
- Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse - Oncopôle, Radiation oncology, Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
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8
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Ramesh KK, Huang V, Rosenthal J, Mellon EA, Goryawala M, Barker PB, Gurbani SS, Trivedi AG, Giuffrida AS, Schreibmann E, Han H, de le Fuente M, Dunbar EM, Holdhoff M, Kleinberg LR, Shu HKG, Shim H, Weinberg BD. A Novel Approach to Determining Tumor Progression Using a Three-Site Pilot Clinical Trial of Spectroscopic MRI-Guided Radiation Dose Escalation in Glioblastoma. Tomography 2023; 9:362-374. [PMID: 36828381 PMCID: PMC9964256 DOI: 10.3390/tomography9010029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60-70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211).
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Affiliation(s)
- Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Jeffrey Rosenthal
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Eric A. Mellon
- Department of Radiation Oncology, University of Miami, Miami, FL 45056, USA
| | | | - Peter B. Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Saumya S. Gurbani
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Alexander S. Giuffrida
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Erin M. Dunbar
- Department of Neuro-Oncology and Neurosurgery, Piedmont Atlanta Hospital, Atlanta, GA 30309, USA
| | - Matthias Holdhoff
- Department of Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
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9
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Laprie A, Tensaouti F, Cohen-Jonathan Moyal E. [Radiation dose intensification for glioblastoma]. Cancer Radiother 2022; 26:894-898. [PMID: 36085279 DOI: 10.1016/j.canrad.2022.07.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/07/2022] [Accepted: 07/07/2022] [Indexed: 10/14/2022]
Abstract
Glioblastoma is the most common brain tumor in adults; its treatment includes surgical excision or biopsy followed by radio-chemotherapy. Even if radiotherapy increases the survival of all patients regardless of their age or their general condition, there are always sources of radioresistance, where relapses occur and therefore treatment fails. Indeed, these foci result in a local relapse, which is observed in 95% of cases in the irradiation fields. We will describe here the current approaches to overcome this radioresistance by dose escalation, without or with guidance by metabolic and functional imaging (dose-painting). We will detail several prospective trials including the French phase III trial, SPECTRO-GLIO, randomizing the use of an integrated boost guided by spectrometric magnetic resonance imaging and similar trials developed across the Atlantic. We will also discuss approaches using different PET markers as well as diffusion or perfusion magnetic resonance imaging.
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Affiliation(s)
- A Laprie
- Département d'oncologie radiothérapie, institut universitaire du cancer de Toulouse-Oncopole, 1, avenue Irène-Joliot-Curie, 31059 Toulouse cedex, France; Inserm Toulouse neuroimaging center (Tonic), place Baylac, 31000 Toulouse, France.
| | - F Tensaouti
- Département d'oncologie radiothérapie, institut universitaire du cancer de Toulouse-Oncopole, 1, avenue Irène-Joliot-Curie, 31059 Toulouse cedex, France; Inserm Toulouse neuroimaging center (Tonic), place Baylac, 31000 Toulouse, France
| | - E Cohen-Jonathan Moyal
- Département d'oncologie radiothérapie, institut universitaire du cancer de Toulouse-Oncopole, 1, avenue Irène-Joliot-Curie, 31059 Toulouse cedex, France; Inserm Radopt, CRCT, Centre de recherche en cancérologie de Toulouse, 2, avenue Hubert-Curien, 31100 Toulouse, France
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10
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Ramesh K, Mellon EA, Gurbani SS, Weinberg BD, Schreibmann E, Sheriff SA, Goryawala M, de le Fuente M, Eaton BR, Zhong J, Voloschin AD, Sengupta S, Dunbar EM, Holdhoff M, Barker PB, Maudsley AA, Kleinberg LR, Shim H, Shu HKG. A multi-institutional pilot clinical trial of spectroscopic MRI-guided radiation dose escalation for newly diagnosed glioblastoma. Neurooncol Adv 2022; 4:vdac006. [PMID: 35382436 PMCID: PMC8976280 DOI: 10.1093/noajnl/vdac006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Background Glioblastomas (GBMs) are aggressive brain tumors despite radiation therapy (RT) to 60 Gy and temozolomide (TMZ). Spectroscopic magnetic resonance imaging (sMRI), which measures levels of specific brain metabolites, can delineate regions at high risk for GBM recurrence not visualized on contrast-enhanced (CE) MRI. We conducted a clinical trial to assess the feasibility, safety, and efficacy of sMRI-guided RT dose escalation to 75 Gy for newly diagnosed GBMs. Methods Our pilot trial (NCT03137888) enrolled patients at 3 institutions (Emory University, University of Miami, Johns Hopkins University) from September 2017 to June 2019. For RT, standard tumor volumes based on T2-FLAIR and T1w-CE MRIs with margins were treated in 30 fractions to 50.1 and 60 Gy, respectively. An additional high-risk volume based on residual CE tumor and Cho/NAA (on sMRI) ≥2× normal was treated to 75 Gy. Survival curves were generated by the Kaplan-Meier method. Toxicities were assessed according to CTCAE v4.0. Results Thirty patients were treated in the study. The median age was 59 years. 30% were MGMT promoter hypermethylated; 7% harbored IDH1 mutation. With a median follow-up of 21.4 months for censored patients, median overall survival (OS) and progression-free survival were 23.0 and 16.6 months, respectively. This regimen appeared well-tolerated with 70% of grade 3 or greater toxicity ascribed to TMZ and 23% occurring at least 1 year after RT. Conclusion Dose-escalated RT to 75 Gy guided by sMRI appears feasible and safe for patients with newly diagnosed GBMs. OS outcome is promising and warrants additional testing. Based on these results, a randomized phase II trial is in development.
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Affiliation(s)
- Karthik Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Eric A Mellon
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Saumya S Gurbani
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | | | | | | | - Bree R Eaton
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Jim Zhong
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Alfredo D Voloschin
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Soma Sengupta
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Present affiliation: Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, Ohio, USA
| | | | - Matthias Holdhoff
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Peter B Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Lawrence R Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA,Corresponding Authors: Hyunsuk Shim, PhD and Hui-Kuo G. Shu, MD, PhD, Department of Radiation Oncology, Winship Cancer Institute of Emory University, 1701 Uppergate Drive, Atlanta, GA 30322, USA (. )
| | - Hui-Kuo G Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA
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11
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Zhong J, Huang V, Gurbani SS, Ramesh K, Scott Cordova J, Schreibmann E, Shu HKG, Olson J, Han H, Giuffrida A, Shim H, Weinberg BD. 3D whole-brain metabolite imaging to improve characterization of low-to-intermediate grade gliomas. J Neurooncol 2021; 153:303-311. [PMID: 33983570 PMCID: PMC8237861 DOI: 10.1007/s11060-021-03770-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 05/03/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE MRI is the standard imaging modality used for diagnosis, treatment planning, and post-treatment management of gliomas. Contrast-enhanced T1-weighted (CE-T1w) MRI is used to plan biopsy and radiation for grade IV gliomas but is less effective for grade II and III gliomas (i.e., low-to-intermediate grade gliomas) which may have minimal or no enhancement. Magnetic resonance spectroscopic imaging (MRSI) is an advanced MRI technique that has been shown, to improve diagnostic yield of biopsy and target delineation for grade IV glioma. The purpose of this study is to determine if MRSI can improve characterization and tissue sampling of low-to-intermediate grade gliomas. METHODS Prospective grade II and grade III glioma patients were enrolled to undergo whole brain high-resolution MRSI prior to tissue sampling. Choline/N-acetyl-aspartate (Cho/NAA) maps were overlaid on anatomic imaging and imported into stereotactic biopsy software. Patients were treated with standard-of-care surgery and radiation. Volumes of spectroscopically abnormal tissue were generated and compared with anatomic imaging and areas of enhancing recurrence on follow-up imaging. RESULTS Ten patients had pathologic diagnosis of grade II (n = 4) or grade III (n = 6) with a median follow-up of 27.3 months. Five patients had recurrence, and regions of recurrence were found to overlap with metabolically abnormal regions on MRSI at the time of diagnosis. CONCLUSION MRSI in low-to-intermediate grade glioma patients is predictive of areas of subsequent recurrence. Larger studies are needed to determine if MRSI can be used to guide surgical and radiation treatment planning in these patients.
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Affiliation(s)
- Jim Zhong
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Vicki Huang
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Saumya S Gurbani
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Karthik Ramesh
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - J Scott Cordova
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Hui-Kuo G Shu
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Jeffrey Olson
- Department of Neurosurgery, Winship Cancer Institute of Emory University, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Hui Han
- Biomedical Sciences and Biomedical Imaging Research Institute, Cedars Sinai, Los Angeles, CA, 90048, USA
| | - Alexander Giuffrida
- Department of Biomedical Engineering, Winship Cancer Institute of Emory University, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA.
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA.
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12
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Tal A, Zhao T, Schirda C, Hetherington HP, Pan JW, Gonen O. Fast, regional three-dimensional hybrid (1D-Hadamard 2D-rosette) proton MR spectroscopic imaging in the human temporal lobes. NMR IN BIOMEDICINE 2021; 34:e4507. [PMID: 33754420 PMCID: PMC8122085 DOI: 10.1002/nbm.4507] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 02/03/2021] [Accepted: 02/25/2021] [Indexed: 05/05/2023]
Abstract
1 H-MRSI is commonly performed with gradient phase encoding, due to its simplicity and minimal radio frequency (RF) heating (specific absorption rate). Its two well-known main problems-(i) "voxel bleed" due to the intrinsic point-spread function, and (ii) chemical shift displacement error (CSDE) when slice-selective RF pulses are used, which worsens with increasing volume of interest (VOI) size-have long become accepted as unavoidable. Both problems can be mitigated with Hadamard multislice RF encoding. This is demonstrated and quantified with numerical simulations, in a multislice phantom and in five healthy young adult volunteers at 3 T, targeting a 2-cm thick temporal lobe VOI through the bilateral hippocampus. This frequently targeted region (e.g. in epilepsy and Alzheimer's disease) is subject to strong, 1-2 ppm.cm-1 regional B0, susceptibility gradients that can dramatically reduce the signal-to-noise ratio (SNR) and water suppression effectiveness. The chemical shift imaging (CSI) sequence used a 3-ms Shinnar-Le Roux (SLR) 90° RF pulse, acquiring eight steps in the slice direction. The Hadamard sequence acquired two overlapping slices using the same SLR 90° pulses, under twofold stronger gradients that proportionally halved the CSDE. Both sequences used 2D 20 × 20 rosette spectroscopic imaging (RSI) for in-plane spatial localization and both used RF and gradient performance characteristics that are easily met by all modern MRI instruments. The results show that Hadamard spectroscopic imaging (HSI) suffered dramatically less signal bleed within the VOI compared with CSI (<1% vs. approximately 26% in simulations; and 5%-8% vs. >50%) in a phantom specifically designed to test these effects. The voxels' SNR per unit volume per unit time was also 40% higher for HSI. In a group of five healthy volunteers, we show that HSI with in-plane 2D-RSI facilitates fast, 3D multivoxel encoding at submilliliter spatial resolution, over the bilateral human hippocampus, in under 10 min, with negligible CSDE, spectral and spatial contamination and more than 6% improved SNR per unit time per unit volume.
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Affiliation(s)
- Assaf Tal
- Department of Chemical and Biological Physics, The Weizmann Institute of Science, Rehovot, Israel
| | - Tiejun Zhao
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | - Claudiu Schirda
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Hoby P. Hetherington
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jullie W. Pan
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Oded Gonen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
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13
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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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14
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Kamson D, Tsien C. Novel Magnetic Resonance Imaging and Positron Emission Tomography in the RT Planning and Assessment of Response of Malignant Gliomas. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00078-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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15
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Tyurina AN, Pronin IN, Fadeeva LM, Batalov AI, Zakharova NE, Podoprigora AE, Shults EI, Kornienko VN. Proton 3D MR spectroscopy in the diagnosis of glial brain tumors. ACTA ACUST UNITED AC 2019. [DOI: 10.24835/1607-0763-2019-3-8-18] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The purpose of this study was an assessment of the proton 3D MR spectroscopy efficacy in diagnosis of primary glial brain tumors.Material and methods. Sixty three patients aged from 20 to 60 years with primary glial brain tumors of varying degrees of malignancy were examined. The ratios of main metabolites indices were evaluated with following comparison with the metabolites obtained in gray and white matter of the opposite hemisphere.The ratios of main metabolites: Cho/Cr, NAA/Cr, Cho/NAA showed significant (p <0.005) differences in the groups of patients with low and high grade gliomas.Results. The obtained data proved the efficacy of the proton 3D MR-spectroscopy in predicting of the glial brain tumors malignancy.
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Affiliation(s)
- A. N. Tyurina
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - I. N. Pronin
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - L. M. Fadeeva
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - A. I. Batalov
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - N. E. Zakharova
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - A. E. Podoprigora
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - E. I. Shults
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - V. N. Kornienko
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
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16
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Laprie A, Ken S, Filleron T, Lubrano V, Vieillevigne L, Tensaouti F, Catalaa I, Boetto S, Khalifa J, Attal J, Peyraga G, Gomez-Roca C, Uro-Coste E, Noel G, Truc G, Sunyach MP, Magné N, Charissoux M, Supiot S, Bernier V, Mounier M, Poublanc M, Fabre A, Delord JP, Cohen-Jonathan Moyal E. Dose-painting multicenter phase III trial in newly diagnosed glioblastoma: the SPECTRO-GLIO trial comparing arm A standard radiochemotherapy to arm B radiochemotherapy with simultaneous integrated boost guided by MR spectroscopic imaging. BMC Cancer 2019; 19:167. [PMID: 30791889 PMCID: PMC6385401 DOI: 10.1186/s12885-019-5317-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Accepted: 01/24/2019] [Indexed: 02/05/2023] Open
Abstract
Background Glioblastoma, a high-grade glial infiltrating tumor, is the most frequent malignant brain tumor in adults and carries a dismal prognosis. External beam radiotherapy (EBRT) increases overall survival but this is still low due to local relapses, mostly occurring in the irradiation field. As the ratio of spectra of choline/N acetyl aspartate> 2 (CNR2) on MR spectroscopic imaging has been described as predictive for the site of local relapse, we hypothesized that dose escalation on these regions would increase local control and hence global survival. Methods/design In this multicenter prospective phase III trial for newly diagnosed glioblastoma, 220 patients having undergone biopsy or surgery are planned for randomization to two arms. Arm A is the Stupp protocol (EBRT 60 Gy on contrast enhancement + 2 cm margin with concomitant temozolomide (TMZ) and 6 months of TMZ maintenance); Arm B is the same treatment with an additional simultaneous integrated boost of intensity-modulated radiotherapy (IMRT) of 72Gy/2.4Gy delivered on the MR spectroscopic imaging metabolic volumes of CHO/NAA > 2 and contrast-enhancing lesions or resection cavity. Stratification is performed on surgical and MGMT status. Discussion This is a dose-painting trial, i.e. delivery of heterogeneous dose guided by metabolic imaging. The principal endpoint is overall survival. An online prospective quality control of volumes and dose is performed in the experimental arm. The study will yield a large amount of longitudinal multimodal MR imaging data including planning CT, radiotherapy dosimetry, MR spectroscopic, diffusion and perfusion imaging. Trial registration NCT01507506, registration date December 20, 2011.
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Affiliation(s)
- Anne Laprie
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France. .,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France.
| | - Soléakhéna Ken
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France.,Department of Engineering and Medical Physics, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-OncopoleCancer de Toulouse-Oncopole, Toulouse, France
| | - Thomas Filleron
- Biostatistics Unit, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Vincent Lubrano
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France.,Neurosurgery Department, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Laure Vieillevigne
- Department of Engineering and Medical Physics, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-OncopoleCancer de Toulouse-Oncopole, Toulouse, France
| | - Fatima Tensaouti
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France
| | - Isabelle Catalaa
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France.,Neuroimaging Department, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Sergio Boetto
- Neurosurgery Department, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Jonathan Khalifa
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Justine Attal
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Guillaume Peyraga
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Carlos Gomez-Roca
- Medical Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Emmanuelle Uro-Coste
- Pathology department, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Georges Noel
- Radiation Oncology Department, Centre Paul Strauss, Strasbourg, France
| | - Gilles Truc
- Radiation Oncology Department Centre Georges-François Leclerc, Dijon, France
| | | | - Nicolas Magné
- Radiation Oncology Department, Institut de Cancérologie de la Loire, Saint-Priest en Jarez, France
| | - Marie Charissoux
- Radiation Oncology Department - Centre Val d'aurelle, Montpellier, France
| | - Stéphane Supiot
- Radiation Oncology Department, Institut de Cancerologie de l'Ouest, Nantes st Herblain, France
| | - Valérie Bernier
- Radiation Oncology Department, Institut de cancérologie de Lorraine centre Alexis Vautrin, Nancy, France
| | - Muriel Mounier
- Clinical Research Department, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Muriel Poublanc
- Clinical Research Department, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Amandine Fabre
- Clinical Research Department, Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Jean-Pierre Delord
- Medical Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- Radiation Oncology Department, Institut Claudius Regaud- Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France.,INSERM UMR1037, Cancer Research Center of Toulouse, Oncopole, Toulouse, France
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17
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Assessment of Residual Tumor After Resection of Glioma: A Magnetic Resonance Spectroscopic Study. ARCHIVES OF NEUROSCIENCE 2019. [DOI: 10.5812/ans.88159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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18
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Peyraga G, Robaine N, Khalifa J, Cohen-Jonathan-Moyal E, Payoux P, Laprie A. Molecular PET imaging in adaptive radiotherapy: brain. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2018; 62:337-348. [PMID: 30497232 DOI: 10.23736/s1824-4785.18.03116-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
INTRODUCTION Owing to their heterogeneity and radioresistance, the prognosis of primitive brain tumors, which are mainly glial tumors, remains poor. Dose escalation in radioresistant areas is a potential issue for improving local control and overall survival. This review focuses on advances in biological and metabolic imaging of brain tumors that are proving to be essential for defining tumor target volumes in radiation therapy (RT) and for increasing the use of DPRT (dose painting RT) and ART (adaptative RT), to optimize dose in radio-resistant areas. EVIDENCE ACQUISITION Various biological imaging modalities such as PET (hypoxia, glucidic metabolism, protidic metabolism, cellular proliferation, inflammation, cellular membrane synthesis) and MRI (spectroscopy) may be used to identify these areas of radioresistance. The integration of these biological imaging modalities improves the diagnosis, prognosis and treatment of brain tumors. EVIDENCE SYNTHESIS Technological improvements (PET and MRI), the development of research, and intensive cooperation between different departments are necessary before using daily metabolic imaging (PET and MRI) to treat patients with brain tumors. CONCLUSIONS The adaptation of treatment volumes during RT (ART) seems promising, but its development requires improvements in several areas and an interdisciplinary approach involving radiology, nuclear medicine and radiotherapy. We review the literature on biological imaging to outline the perspectives for using DPRT and ART in brain tumors.
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Affiliation(s)
- Guillaume Peyraga
- Department of Radiation Therapy, Claudius Regaud Institute, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France
| | - Nesrine Robaine
- Department of Nuclear Medicine, Claudius Regaud Institute, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France
| | - Jonathan Khalifa
- Department of Radiation Therapy, Claudius Regaud Institute, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France.,Paul Sabatier University, Toulouse III, Toulouse, France
| | - Elizabeth Cohen-Jonathan-Moyal
- Department of Radiation Therapy, Claudius Regaud Institute, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France.,Paul Sabatier University, Toulouse III, Toulouse, France
| | - Pierre Payoux
- Department of Nuclear Medicine, Purpan University Hospital Center, Toulouse, France
| | - Anne Laprie
- Department of Radiation Therapy, Claudius Regaud Institute, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France - .,Paul Sabatier University, Toulouse III, Toulouse, France
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19
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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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20
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de Graaf RA, Brown PB, De Feyter HM, McIntyre S, Nixon TW. Elliptical localization with pulsed second-order fields (ECLIPSE) for robust lipid suppression in proton MRSI. NMR IN BIOMEDICINE 2018; 31:e3949. [PMID: 29985532 PMCID: PMC6108906 DOI: 10.1002/nbm.3949] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 04/02/2018] [Accepted: 04/27/2018] [Indexed: 05/21/2023]
Abstract
Proton MRSI has great clinical potential for metabolic mapping of the healthy and pathological human brain. Unfortunately, the promise has not yet been fully achieved due to numerous technical challenges related to insufficient spectral quality caused by magnetic field inhomogeneity, insufficient RF transmit power and incomplete lipid suppression. Here a robust, novel method for lipid suppression in 1 H MRSI is presented. The method is based on 2D spatial localization of an elliptical region of interest using pulsed second-order spherical harmonic (SH) magnetic fields. A dedicated, high-amplitude second-order SH gradient setup was designed and constructed, containing coils to generate Z2, X2Y2 and XY magnetic fields. Simulations and phantom MRI results are used to demonstrate the principles of the method and illustrate the manifestation of chemical shift displacement. 1 H MRSI on human brain in vivo demonstrates high quality, robust suppression of extracranial lipids. The method allows a wide range of inner or outer volume selection or suppression and should find application in MRSI, reduced-field-of-view MRI and single-volume MRS.
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Affiliation(s)
- Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Peter B. Brown
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Henk M. De Feyter
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Scott McIntyre
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Terence W. Nixon
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
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21
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Pedrosa de Barros N, Meier R, Pletscher M, Stettler S, Knecht U, Herrmann E, Schucht P, Reyes M, Gralla J, Wiest R, Slotboom J. On the relation between MR spectroscopy features and the distance to MRI-visible solid tumor in GBM patients. Magn Reson Med 2018; 80:2339-2355. [DOI: 10.1002/mrm.27359] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 04/23/2018] [Accepted: 04/23/2018] [Indexed: 11/12/2022]
Affiliation(s)
- Nuno Pedrosa de Barros
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Raphael Meier
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Martin Pletscher
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Samuel Stettler
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Urspeter Knecht
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Evelyn Herrmann
- Department of Radiation Oncology; University of Bern; Bern Switzerland
| | - Philippe Schucht
- Department of Neurosurgery; University of Bern; Bern Switzerland
| | - Mauricio Reyes
- Institute for Surgical Technology and Biomechanics, University of Bern; Bern Switzerland
| | - Jan Gralla
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Roland Wiest
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
| | - Johannes Slotboom
- University Institute for Diagnostic and Interventional Neuroradiology, University of Bern; Bern Switzerland
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22
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Beigi M, Ghasemi K, Mirzaghavami P, Khanmohammadi M, SalighehRad H. Malignancy probability map as a novel imaging biomarker to predict malignancy distribution: employing MRS in GBM patients. J Neurooncol 2018. [PMID: 29542059 DOI: 10.1007/s11060-018-2829-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The main aim of this study was to propose a new statistical method for evaluation of spatial malignancy distribution within Magnetic Resonance Spectroscopy (MRS) grid in Glioblastoma Multiforme patients. Voxels with different malignancy probabilities were presented as a novel MRS-based Malignancy Probability Map (MPM). For this purpose, a predictive probability-based clustering approach was developed, including the two following steps: (1) Gaussian Mixture Model, (2) Quadratic Discriminate Analysis coupled with Genetic Algorithm. Clustered probability values from two methods were then integrated to exploit the MPM. Results show that the suggested method is able to estimate the malignancy distribution with over 90% sensitivity and specificity. The proposed MRS-based MPM has an acceptable accuracy for providing useful complementary information about regional diffuse glioma malignancy, with the potential to lead to better detection of tumoral regions with high probability of malignancy. So, it also may encourage the use of additional information of this map as a tool for dose painting.
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Affiliation(s)
- Manijeh Beigi
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Kevan Ghasemi
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Parvin Mirzaghavami
- Medical Physics Department, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | | | - Hamidreza SalighehRad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Imaging, Tehran University of Medical Sciences, Tehran, Iran.
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.
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23
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Valentini MC, Mellai M, Annovazzi L, Melcarne A, Denysenko T, Cassoni P, Casalone C, Maurella C, Grifoni S, Fania P, Cistaro A, Schiffer D. Comparison among conventional and advanced MRI, 18F-FDG PET/CT, phenotype and genotype in glioblastoma. Oncotarget 2017; 8:91636-91653. [PMID: 29207673 PMCID: PMC5710953 DOI: 10.18632/oncotarget.21482] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 07/30/2017] [Indexed: 12/20/2022] Open
Abstract
Glioblastoma (GB) is a highly heterogeneous tumor. In order to identify in vivo the most malignant tumor areas, the extent of tumor infiltration and the sites giving origin to GB stem cells (GSCs), we combined positron emission tomography/computed tomography (PET/CT) and conventional and advanced magnetic resonance imaging (MRI) with histology, immunohistochemistry and molecular genetics. Prior to dura opening and tumor resection, forty-eight biopsy specimens [23 of contrast-enhancing (CE) and 25 of non-contrast enhancing (NE) regions] from 12 GB patients were obtained by a frameless image-guided stereotactic biopsy technique. The highest values of 2-[18F]-fluoro-2-deoxy-D-glucose maximum standardized uptake value (18F-FDG SUVmax), relative cerebral blood volume (rCBV), Choline/Creatine (Cho/Cr), Choline/N-acetylaspartate (Cho/NAA) and Lipids/Lactate (LL) ratio have been observed in the CE region. They corresponded to the most malignant tumor phenotype, to the greatest molecular spectrum and stem cell potential. On the contrary, apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in the CE region were very variable. 18F-FDG SUVmax, Cho/Cr and Cho/NAA ratio resulted the most suitable parameters to detect tumor infiltration. In edematous areas, reactive astrocytes and microglia/macrophages were influencing variables. Combined MRI and 18F-FDG PET/CT allowed to recognize the specific biological significance of the different identified areas of GB.
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Affiliation(s)
| | - Marta Mellai
- Research Center/Policlinico di Monza Foundation, 13100 Vercelli, Italy
| | - Laura Annovazzi
- Research Center/Policlinico di Monza Foundation, 13100 Vercelli, Italy
| | - Antonio Melcarne
- Department of Neurosurgery, A.O.U. Città della Salute e della Scienza, 10126 Turin, Italy
| | - Tetyana Denysenko
- Research Center/Policlinico di Monza Foundation, 13100 Vercelli, Italy
| | - Paola Cassoni
- Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Cristina Casalone
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, 10154 Turin, Italy
| | - Cristiana Maurella
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, 10154 Turin, Italy
| | - Silvia Grifoni
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, 10154 Turin, Italy
| | - Piercarlo Fania
- Positron Emission Tomography Center IRMET S.p.A, Euromedic Inc., 10136 Turin, Italy
| | - Angelina Cistaro
- Positron Emission Tomography Center IRMET S.p.A, Euromedic Inc., 10136 Turin, Italy
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Davide Schiffer
- Research Center/Policlinico di Monza Foundation, 13100 Vercelli, Italy
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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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Anwar M, Molinaro AM, Morin O, Chang SM, Haas-Kogan DA, Nelson SJ, Lupo JM. Identifying Voxels at Risk for Progression in Glioblastoma Based on Dosimetry, Physiologic and Metabolic MRI. Radiat Res 2017; 188:303-313. [PMID: 28723274 PMCID: PMC5628052 DOI: 10.1667/rr14662.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Despite the longstanding role of radiation in cancer treatment and the presence of advanced, high-resolution imaging techniques, delineation of voxels at-risk for progression remains purely a geometric expansion of anatomic images, missing subclinical disease at risk for recurrence while treating potentially uninvolved tissue and increasing toxicity. This remains despite the modern ability to precisely shape radiation fields. A striking example of this is the treatment of glioblastoma, a highly infiltrative tumor that may benefit from accurate identification of subclinical disease. In this study, we hypothesize that parameters from physiologic and metabolic magnetic resonance imaging (MRI) at diagnosis could predict the likelihood of voxel progression at radiographic recurrence in glioblastoma by identifying voxel characteristics that indicate subclinical disease. Integrating dosimetry can reveal its effect on voxel outcome, enabling risk-adapted voxel dosing. As a system example, 24 patients with glioblastoma treated with radiotherapy, temozolomide and an anti-angiogenic agent were analyzed. Pretreatment median apparent diffusion coefficient (ADC), fractional anisotropy (FA), relative cerebral blood volume (rCBV), vessel leakage (percentage recovery), choline-to-NAA index (CNI) and dose of voxels in the T2 nonenhancing lesion (NEL), T1 post-contrast enhancing lesion (CEL) or normal-appearing volume (NAV) of brain, were calculated for voxels that progressed [NAV→NEL, CEL (N = 8,765)] and compared against those that remained stable [NAV→NAV (N = 98,665)]. Voxels that progressed (NAV→NEL) had significantly different (P < 0.01) ADC (860), FA (0.36) and CNI (0.67) versus stable voxels (804, 0.43 and 0.05, respectively), indicating increased cell turnover, edema and decreased directionality, consistent with subclinical disease. NAV→CEL voxels were more abnormal (1,014, 0.28, 2.67, respectively) and leakier (percentage recovery = 70). A predictive model identified areas of recurrence, demonstrating that elevated CNI potentiates abnormal diffusion, even far (>2 cm) from the tumor and dose escalation >45 Gy has diminishing benefits. Integrating advanced MRI with dosimetry can identify at voxels at risk for progression and may allow voxel-level risk-adapted dose escalation to subclinical disease while sparing normal tissue. When combined with modern planning software, this technique may enable risk-adapted radiotherapy in any disease site with multimodal imaging.
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Affiliation(s)
- Mekhail Anwar
- Department of Radiation Oncology, University of California, San Francisco, California
| | - Annette M. Molinaro
- Department of Neurosurgery, Division of Epidemiology and Biostatistics, University of California, San Francisco, California
| | - Olivier Morin
- Department of Radiation Oncology, University of California, San Francisco, California
| | - Susan M. Chang
- Department of Neurosurgery, Division of Neuro-oncology, University of California, San Francisco, California
| | - Daphne A. Haas-Kogan
- Department of Radiation Oncology, University of California, San Francisco, California
| | - Sarah J. Nelson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Janine M. Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
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26
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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: 47] [Impact Index Per Article: 6.7] [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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Cordova JS, Kandula S, Gurbani S, Zhong J, Tejani M, Kayode O, Patel K, Prabhu R, Schreibmann E, Crocker I, Holder CA, Shim H, Shu HK. Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma. ACTA ACUST UNITED AC 2016; 2:366-373. [PMID: 28105468 PMCID: PMC5241103 DOI: 10.18383/j.tom.2016.00187] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Due to glioblastoma's infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter. Maps depicting choline to N-Acetylaspartate (Cho/NAA) ratios were registered to contrast-enhanced T1-weighted RT planning MRI for each patient. Volumes depicting metabolic abnormalities (1.5-, 1.75-, and 2.0-fold increases in Cho/NAA ratios) were compared with conventional target volumes and contrast-enhancing tumor at recurrence. sMRI-modified RT plans were generated to evaluate target volume coverage and organ-at-risk dose constraints. Conventional clinical target volumes and Cho/NAA abnormalities identified significantly different regions of microscopic infiltration with substantial Cho/NAA abnormalities falling outside of the conventional 60 Gy isodose line (41.1, 22.2, and 12.7 cm3, respectively). Clinical target volumes using Cho/NAA thresholds exhibited significantly higher coverage of contrast enhancement at recurrence on average (92.4%, 90.5%, and 88.6%, respectively) than conventional plans (82.5%). sMRI-based plans targeting tumor infiltration met planning objectives in all cases with no significant change in target coverage. In 2 cases, the sMRI-modified plan exhibited better coverage of contrast-enhancing tumor at recurrence than the original plan. Integration of the high-resolution, whole-brain sMRI into RT planning is feasible, resulting in RT target volumes that can effectively target tumor infiltration while adhering to conventional constraints.
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Affiliation(s)
- J Scott Cordova
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Shravan Kandula
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia; Florida Hospital Medical Group, Radiation Oncology Associates, Orlando, Florida
| | - Saumya Gurbani
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia; Department of Biomedical Engineering, GA Institute of Technology, Atlanta, Georgia
| | - Jim Zhong
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | - Mital Tejani
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | - Oluwatosin Kayode
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | - Kirtesh Patel
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | - Roshan Prabhu
- SE Radiation Oncology Group, Levine Cancer Institute, Charlotte, North Carolina
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia
| | - Ian Crocker
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia; Winship Cancer Institute, Atlanta, Georgia
| | - Chad A Holder
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Hyunsuk Shim
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia; Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia; Winship Cancer Institute, Atlanta, Georgia; Department of Biomedical Engineering, GA Institute of Technology, Atlanta, Georgia
| | - Hui-Kuo Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia; Winship Cancer Institute, Atlanta, Georgia
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Müller A, Jurcoane A, Kebir S, Ditter P, Schrader F, Herrlinger U, Tzaridis T, Mädler B, Schild HH, Glas M, Hattingen E. Quantitative T1-mapping detects cloudy-enhancing tumor compartments predicting outcome of patients with glioblastoma. Cancer Med 2016; 6:89-99. [PMID: 27891815 PMCID: PMC5269700 DOI: 10.1002/cam4.966] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 10/11/2016] [Accepted: 10/25/2016] [Indexed: 12/13/2022] Open
Abstract
Contrast enhancement of glioblastomas (GBM) is caused by the decrease in relaxation time, T1. Here, we demonstrate that the quantitative measurement of T1 (qT1) discovers a subtle enhancement in GBM patients that is invisible in standard MRI. We assessed the volume change of this “cloudy” enhancement during radio‐chemotherapy and its impact on patients’ progression‐free survival (PFS). We enrolled 18 GBM patients in this observational, prospective cohort study and measured 3T‐MRI pre‐ and post contrast agent with standard T1‐weighted (T1w) and with sequences to quantify T1 before radiation, and at 6‐week intervals during radio‐chemotherapy. We measured contrast enhancement by subtracting pre from post contrast contrast images, yielding relative signal increase ∆T1w and relative T1 shortening ∆qT1. On ∆qT1, we identified a solid and a cloudy‐enhancing compartment and evaluated the impact of their therapy‐related volume change upon PFS. In ∆qT1 maps cloudy‐enhancing compartments were found in all but two patients at baseline and in all patients during therapy. The qT1 decrease in the cloudy‐enhancing compartment post contrast was 21.64% versus 1.96% in the contralateral control tissue (P < 0.001). It was located at the margin of solid enhancement which was also seen on T1w. In contrast, the cloudy‐enhancing compartment was visually undetectable on ∆T1w. A volume decrease of more than 21.4% of the cloudy‐enhancing compartment at first follow‐up predicted longer PFS (P = 0.038). Cloudy‐enhancing compartment outside the solid contrast‐enhancing area of GBM is a new observation which is only visually detectable with qT1‐mapping and may represent tumor infiltration. Its early volume decrease predicts a longer PFS in GBM patients during standard radio‐chemotherapy.
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Affiliation(s)
- Andreas Müller
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Alina Jurcoane
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Sied Kebir
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Philip Ditter
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Felix Schrader
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Theophilos Tzaridis
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Burkhard Mädler
- Philips GmbH, UB Healthcare, Lübeckertordamm 5, Hamburg, 20099, Germany
| | - Hans H Schild
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Martin Glas
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany.,Division of Experimental and Translational Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany.,Clinical Cooperation Unit Neurooncology, MediClin Robert Janker Clinic & University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
| | - Elke Hattingen
- Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund Freud Str. 25, Bonn, 53127, Germany
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Lopez CJ, Nagornaya N, Parra NA, Kwon D, Ishkanian F, Markoe AM, Maudsley A, Stoyanova R. Association of Radiomics and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme. Int J Radiat Oncol Biol Phys 2016; 97:586-595. [PMID: 28011044 DOI: 10.1016/j.ijrobp.2016.11.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 11/03/2016] [Accepted: 11/08/2016] [Indexed: 01/05/2023]
Abstract
PURPOSE To build a framework for investigation of the associations between imaging, clinical target volumes (CTVs), and metabolic tumor volumes (MTVs) features for better understanding of the underlying information in the CTVs and dependencies between these volumes. High-throughput extraction of imaging and metabolomic quantitative features from magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging of glioblastoma multiforme (GBM) results in tens of variables per patient. In radiation therapy of GBM the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl aspartate (NAA) and choline (Cho). The corresponding clinical target volumes (CTVs) for radiation therapy are based on contrast-enhanced T1-weighted (CE-T1w) and T2-weighted (T2w)/fluid-attenuated inversion recovery MRI. METHODS AND MATERIALS Necrotic portions, enhancing lesion, and edema were manually contoured on CE-T1w/T2w images for 17 GBM patients. Clinical target volumes and MTVs for NAA (MTVNAA) and Cho (MTVCho) were constructed. Imaging and metabolic features related to size, shape, and signal intensities of the volumes were extracted. Tumors were also scored categorically for 10 semantic imaging traits by a neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and CTVs/MTVs features were visualized as heatmaps. Associations between MTVNAA and MTVCho and imaging features were studied using Spearman correlation. RESULTS Forty-eight imaging features were extracted per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. Twenty features were extracted from CTVs and MTVs. A series of semantic imaging traits were replaced with automatically extracted continuous variables. There were multiple (22) significant correlations of imaging measures with CTVs/MTVNAA, whereas there were only 6 with CTVs/MTVCho. CONCLUSIONS A framework for investigation of codependencies between MRI and magnetic resonance spectroscopic imaging radiomic features and CTVs/MTVs has been established. The MTV for NAA was found to be closely associated with MRI volumes, whereas very few imaging features were related to MTVCho, indicating that Cho provides additional information to imaging.
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Affiliation(s)
- Christopher J Lopez
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Natalya Nagornaya
- Department of Radiology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Nestor A Parra
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Deukwoo Kwon
- Biostatistics and Bioinformatics Core Resource, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Fazilat Ishkanian
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Arnold M Markoe
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Andrew Maudsley
- Department of Radiology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Radka Stoyanova
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida.
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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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31
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Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation? J Neurooncol 2016; 130:181-192. [DOI: 10.1007/s11060-016-2232-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 07/31/2016] [Indexed: 01/18/2023]
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32
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Price SJ, Young AMH, Scotton WJ, Ching J, Mohsen LA, Boonzaier NR, Lupson VC, Griffiths JR, McLean MA, Larkin TJ. Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas. J Magn Reson Imaging 2016; 43:487-94. [PMID: 26140696 PMCID: PMC5008200 DOI: 10.1002/jmri.24996] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Accepted: 06/23/2015] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To use perfusion and magnetic resonance (MR) spectroscopy to compare the diffusion tensor imaging (DTI)-defined invasive and noninvasive regions. Invasion of normal brain is a cardinal feature of glioblastomas (GBM) and a major cause of treatment failure. DTI can identify invasive regions. MATERIALS AND METHODS In all, 50 GBM patients were imaged preoperatively at 3T with anatomic sequences, DTI, dynamic susceptibility perfusion MR (DSCI), and multivoxel spectroscopy. The DTI and DSCI data were coregistered to the spectroscopy data and regions of interest (ROIs) were made in the invasive (determined by DTI), noninvasive regions, and normal brain. Values of relative cerebral blood volume (rCBV), N-acetyl aspartate (NAA), myoinositol (mI), total choline (Cho), and glutamate + glutamine (Glx) normalized to creatine (Cr) and Cho/NAA were measured at each ROI. RESULTS Invasive regions showed significant increases in rCBV, suggesting angiogenesis (invasive rCBV 1.64 [95% confidence interval, CI: 1.5-1.76] vs. noninvasive 1.14 [1.09-1.18]; P < 0.001), Cho/Cr (invasive 0.42 [0.38-0.46] vs. noninvasive 0.35 [0.31-0.38]; P = 0.02) and Cho/NAA (invasive 0.54 [0.41-0.68] vs. noninvasive 0.37 [0.29-0.45]; P = < 0.03), suggesting proliferation, and Glx/Cr (invasive 1.54 [1.27-1.82] vs. noninvasive 1.3 [1.13-1.47]; P = 0.028), suggesting glutamate release; and a significantly reduced NAA/Cr (invasive 0.95 [0.85-1.05] vs. noninvasive 1.19 [1.06-1.31]; P = 0.008). The mI/Cr was not different between the three ROIs (invasive 1.2 [0.99-1.41] vs. noninvasive 1.3 [1.14-1.46]; P = 0.68). In the noninvasive regions, the values were not different from normal brain. CONCLUSION Combining DTI to identify the invasive region with perfusion and spectroscopy, we can identify changes in invasive regions not seen in noninvasive regions.
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Affiliation(s)
- Stephen J Price
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Adam M H Young
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - William J Scotton
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Jared Ching
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Laila A Mohsen
- University Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Natalie R Boonzaier
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Victoria C Lupson
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - John R Griffiths
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Mary A McLean
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Timothy J Larkin
- Neurosurgery Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
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Prognostic Value of MRS Metabolites in Postoperative Irradiated High Grade Gliomas. BIOMED RESEARCH INTERNATIONAL 2015; 2015:341042. [PMID: 26339606 PMCID: PMC4538329 DOI: 10.1155/2015/341042] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 02/09/2015] [Indexed: 11/17/2022]
Abstract
Purpose. We studied the prognostic significance of Magnetic Resonance Spectroscopy (MRS) in operated high grade gliomas. Materials and Methods. Twelve patients were treated with radiotherapy and Temozolomide. The MRS data were taken four weeks after operation (before radiotherapy) and every six months after the completion of RT. The N-acetyl aspartate, choline, creatine, and myo-inositol parameters were quantified, analyzed, and correlated to recurrence-free survival (RFS). Results. The median RFS was 26.06 months. RFS was significantly worse in elderly patients (P = 0.001) along with the higher choline/creatine ratios at either baseline (P = 0.003) or six months post Radiotherapy (P = 0.042). Median RFS was 23 months in high choline/creatine levels ≥2 at 6 months after radiotherapy and 11 months for those with <2 choline/creatine levels. There was a significant correlation of maximum difference of choline/creatine ratio with RFS (rho = 0.64, P = 0.045). Conclusion. Age and choline/creatine ratio are strong independent prognostic factors in high grade gliomas.
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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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Raschke F, Jones TL, Barrick TR, Howe FA. Delineation of gliomas using radial metabolite indexing. NMR IN BIOMEDICINE 2014; 27:1053-1062. [PMID: 25042619 DOI: 10.1002/nbm.3154] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2013] [Revised: 05/18/2014] [Accepted: 05/20/2014] [Indexed: 06/03/2023]
Abstract
(1) H MRSI has demonstrated the ability to characterise and delineate brain tumours, but robust data analysis methods are still needed. In this study, we present an objective analysis method for MRSI data to delineate tumour abnormality regions. The presented method is a development of the choline-to-N-acetylaspartate index (CNI), which uses perpendicular distances in a choline versus N-acetylaspartate plot as a measure of abnormality. We propose a radial CNI (rCNI) method that uses the choline to N-acetylaspartate ratio directly as an abnormality measure. To avoid problems with small or zero denominators, we perform an arctangent transformation. CNI abnormality contours were evaluated using a z-score threshold of 2 (CNI2) and 2.5 (CNI2.5) and compared with rCNI2. Simulations modelling low-grade (LGG) and high-grade (HGG) gliomas with different tissue compartments and partial volume effects suggest improved specificity of rCNI2 (LGG 92%/HGG 91%) over CNI2 (LGG 69%/HGG 69%) and CNI2.5 (LGG 74%/HGG 75%), whilst retaining a similar sensitivity to both CNI2 and CNI2.5. Our simulation results also confirm a previously reported increase in specificity of CNI2.5 over CNI2 with little penalty in sensitivity. The analysis of MRSI data acquired from 10 patients with low-grade glioma at 3 T suggests a more robust delineation of the lesions using rCNI with respect to conventional imaging compared with standard CNI. Further analysis of 29 glioma datasets acquired at 1.5 T, together with previously published estimated tumour proportions, suggests that rCNI has higher sensitivity and specificity for the identification of abnormal MRSI voxels.
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Affiliation(s)
- F Raschke
- Neurosciences Research Centre, Cardiovascular and Cell Sciences Institute, St George's, University of London, London, UK
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Guarnaschelli JN, Vagal AS, McKenzie JT, McPherson CM, Warnick RE, Batra V, Breneman JC, Lamba MA. Target definition for malignant gliomas: No difference in radiation treatment volumes between 1.5T and 3T magnetic resonance imaging. Pract Radiat Oncol 2014; 4:e195-e201. [DOI: 10.1016/j.prro.2013.11.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2013] [Revised: 10/08/2013] [Accepted: 11/06/2013] [Indexed: 11/15/2022]
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Deviers A, Ken S, Filleron T, Rowland B, Laruelo A, Catalaa I, Lubrano V, Celsis P, Berry I, Mogicato G, Cohen-Jonathan Moyal E, Laprie A. Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme. Int J Radiat Oncol Biol Phys 2014; 90:385-93. [PMID: 25104068 DOI: 10.1016/j.ijrobp.2014.06.009] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2014] [Revised: 05/28/2014] [Accepted: 06/02/2014] [Indexed: 12/16/2022]
Abstract
PURPOSE Because lactate accumulation is considered a surrogate for hypoxia and tumor radiation resistance, we studied the spatial distribution of the lactate-to-N-acetyl-aspartate ratio (LNR) before radiation therapy (RT) with 3D proton magnetic resonance spectroscopic imaging (3D-(1)H-MRSI) and assessed its impact on local tumor control in glioblastoma (GBM). METHODS AND MATERIALS Fourteen patients with newly diagnosed GBM included in a phase 2 chemoradiation therapy trial constituted our database. Magnetic resonance imaging (MRI) and MRSI data before RT were evaluated and correlated to MRI data at relapse. The optimal threshold for tumor-associated LNR was determined with receiver-operating-characteristic (ROC) curve analysis of the pre-RT LNR values and MRI characteristics of the tumor. This threshold was used to segment pre-RT normalized LNR maps. Two spatial analyses were performed: (1) a pre-RT volumetric comparison of abnormal LNR areas with regions of MRI-defined lesions and a choline (Cho)-to- N-acetyl-aspartate (NAA) ratio ≥ 2 (CNR2); and (2) a voxel-by-voxel spatial analysis of 4,186,185 voxels with the intention of evaluating whether pre-RT abnormal LNR areas were predictive of the site of local recurrence. RESULTS A LNR of ≥ 0.4 (LNR-0.4) discriminated between tumor-associated and normal LNR values with 88.8% sensitivity and 97.6% specificity. LNR-0.4 voxels were spatially different from those of MRI-defined lesions, representing 44% of contrast enhancement, 64% of central necrosis, and 26% of fluid-attenuated inversion recovery (FLAIR) abnormality volumes before RT. They extended beyond the overlap with CNR2 for most patients (median: 20 cm(3); range: 6-49 cm(3)). LNR-0.4 voxels were significantly predictive of local recurrence, regarded as contrast enhancement at relapse: 71% of voxels with a LNR-0.4 before RT were contrast enhanced at relapse versus 10% of voxels with a normal LNR (P<.01). CONCLUSIONS Pre-RT LNR-0.4 in GBM indicates tumor areas that are likely to relapse. Further investigations are needed to confirm lactate imaging as a tool to define additional biological target volumes for dose painting.
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Affiliation(s)
- Alexandra Deviers
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France; UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; INP (Institut National Polytechnique), ENVT (Ecole Nationale Vétérinaire de Toulouse), Unité d'Anatomie-Imagerie-Embryologie, Université de Toulouse, Toulouse, France
| | - Soléakhéna Ken
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France; UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France
| | - Thomas Filleron
- Bureau des Etudes Cliniques, Institut Claudius Regaud, Toulouse, France
| | - Benjamin Rowland
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France
| | - Andrea Laruelo
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France
| | - Isabelle Catalaa
- UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; Hôpital de Rangueil, CHU (Centre Hospitalier Universitaire) de Toulouse, Toulouse, France
| | - Vincent Lubrano
- UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; Hôpital de Rangueil, CHU (Centre Hospitalier Universitaire) de Toulouse, Toulouse, France
| | - Pierre Celsis
- UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France
| | - Isabelle Berry
- UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; Hôpital de Rangueil, CHU (Centre Hospitalier Universitaire) de Toulouse, Toulouse, France; Université Toulouse III Paul Sabatier, Toulouse, France
| | - Giovanni Mogicato
- UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; INP (Institut National Polytechnique), ENVT (Ecole Nationale Vétérinaire de Toulouse), Unité d'Anatomie-Imagerie-Embryologie, Université de Toulouse, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France; UMR1037, CRCT, Institut National de la Santé et de la Recherche Médicale, Toulouse, France; Université Toulouse III Paul Sabatier, Toulouse, France
| | - Anne Laprie
- Département de Radiothérapie, Institut Claudius Regaud, Toulouse, France; UMR (Unité Mixte de Recherche) 825, Institut National de la Santé et de la Recherche Médicale, Toulouse, France.
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Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma. Semin Radiat Oncol 2014; 24:248-58. [PMID: 25219809 DOI: 10.1016/j.semradonc.2014.06.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
This review explores how the integration of advanced imaging methods with high-quality anatomical images significantly improves the characterization, target definition, assessment of response to therapy, and overall management of patients with high-grade glioma. Metrics derived from diffusion-, perfusion-, and susceptibility-weighted magnetic resonance imaging in conjunction with magnetic resonance spectroscopic imaging, allows us to characterize regions of edema, hypoxia, increased cellularity, and necrosis within heterogeneous tumor and surrounding brain tissue. Quantification of such measures may provide a more reliable initial representation of tumor delineation and response to therapy than changes in the contrast-enhancing or T2 lesion alone and have a significant effect on targeting resection, planning radiation, and assessing treatment effectiveness. In the long term, implementation of these imaging methodologies can also aid in the identification of recurrent tumor and its differentiation from treatment-related confounds and facilitate the detection of radiationinduced vascular injury in otherwise normal-appearing brain tissue.
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Lo SS, Sahgal A, Slotman BJ, Mansur DB, Khouri A, Sloan AE, Machtay M, Chang EL. What is the most appropriate clinical target volume for glioblastoma? CNS Oncol 2014; 2:419-25. [PMID: 25054665 DOI: 10.2217/cns.13.38] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Glioblastoma is one of the most common primary brain tumors in adults and the prognosis is very poor. The standard treatment is gross total resection and postoperative radiotherapy with concurrent and adjuvant chemotherapy with temozolomide. Given its propensity to spread to areas of brain parenchyma surrounding the gross tumor volume (GTV), a generous margin is typically created around the GTV. Peritumoral edema is frequently included in the GTV, especially in the USA. The margin of expansion from GTV to clinical target volume also varies widely among different institutions. There is a lack of consensus as to what constitutes the most appropriate clinical target volume for glioblastoma.
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Affiliation(s)
- Simon S Lo
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Comprehensive Cancer Center, Cleveland, OH, USA
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Parra NA, Maudsley AA, Gupta RK, Ishkanian F, Huang K, Walker GR, Padgett K, Roy B, Panoff J, Markoe A, Stoyanova R. Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes. Int J Radiat Oncol Biol Phys 2014; 90:376-84. [PMID: 25066215 DOI: 10.1016/j.ijrobp.2014.03.049] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Revised: 02/27/2014] [Accepted: 03/28/2014] [Indexed: 11/19/2022]
Abstract
PURPOSE Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). METHODS AND MATERIALS Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. RESULTS The MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60. CONCLUSIONS This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information.
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Affiliation(s)
- N Andres Parra
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Andrew A Maudsley
- Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
| | - Rakesh K Gupta
- Department of Radiology & Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - Fazilat Ishkanian
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Kris Huang
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Gail R Walker
- Biostatistics and Bioinformatics Core Resource, Sylvester Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Kyle Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida; Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
| | - Bhaswati Roy
- Department of Radiology & Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - Joseph Panoff
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Arnold Markoe
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Radka Stoyanova
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida.
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Raschke F, Fellows GA, Wright AJ, Howe FA. (1) H 2D MRSI tissue type analysis of gliomas. Magn Reson Med 2014; 73:1381-9. [PMID: 24894747 DOI: 10.1002/mrm.25251] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2014] [Revised: 03/22/2014] [Accepted: 03/24/2014] [Indexed: 01/15/2023]
Abstract
PURPOSE To decompose 1H MR spectra of glioma patients into normal and abnormal tissue proportions for tumor classification and delineation. METHODS Anatomical imaging and 1H magnetic resonance spectroscopic imaging data have been acquired from 11 grade II and 13 grade IV glioma patients. LCModel was used to decompose the magnetic resonance spectroscopic imaging data into normal brain, grade II, and grade IV tissue proportions using a tissue type basis set. Simulations were conducted to evaluate the accuracy of the methodology. Results were visualized using colormaps and abnormality contours showing tumor grade and extent. RESULTS Simulations suggest that infiltrative tumor proportions as low as 20% can be identified at the typical 1H magnetic resonance spectroscopy signal-to-noise found in vivo. Tumor grading according to the highest estimated tumor grade within a lesion gave a classification accuracy of 86% discriminating between grade II and grade IV glioma. Voxels with significant proportions of tumor type spectra were found beyond the margins of contrast enhancement for most grade IV cases consistent with infiltration whereas the abnormality contours show that some tumors are confined within the hyperintensities shown by both post contrast T1 weighted and T2 weighted imaging. CONCLUSION LCModel can be used to decompose 1H MR spectra into proportions of normal and abnormal tissue to identify tumor extent, infiltration, and overall grade.
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Affiliation(s)
- Felix Raschke
- Neurosciences Research Centre, Cardiovascular and Cell Sciences Institute, St. George's University of London, London, UK
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Radiobiological framework for the evaluation of stereotactic radiosurgery plans for invasive brain tumours. ISRN ONCOLOGY 2014; 2013:527251. [PMID: 24490086 PMCID: PMC3893765 DOI: 10.1155/2013/527251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2013] [Accepted: 10/18/2013] [Indexed: 11/24/2022]
Abstract
This study presents a radiobiological formalism for the evaluation of the treatment plans with respect to the probability of controlling tumours treated with stereotactic radiosurgery accounting for possible infiltrations of malignant cells beyond the margins of the delineated target. Treatments plans devised for three anaplastic astrocytoma cases were assumed for this study representing cases with different difficulties for target coverage. Several scenarios were considered regarding the infiltration patterns. Tumour response was described in terms of tumour control probability (TCP) assuming a Poisson model taking into account the initial number of clonogenic cells and the cell survival. The results showed the strong impact of the pattern of infiltration of tumour clonogens outside the delineated target on the outcome of the treatment. The treatment plan has to take into account the existence of the possible microscopic disease around the visible lesion; otherwise the high gradients around the target effectively prevent the sterilisation of the microscopic spread leading to low probability of control, in spite of the high dose delivered to the target. From this perspective, the proposed framework offers a further criterion for the evaluation of stereotactic radiosurgery plans taking into account the possible infiltration of tumour cells around the visible target.
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Heikal AA, Wachowicz K, Fallone BG. MTF behavior of compressed sensing MR spectroscopic imaging. Med Phys 2013; 40:052302. [PMID: 23635289 DOI: 10.1118/1.4800642] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To investigate the modulation transfer function (MTF) behavior of compressed sensing (CS) MR spectroscopic imaging (MRSI) with regard to CS reconstruction weights and the acquired peak signal-to-noise ratio (SNR); which may have an effect on MTF due to the nonlinear nature of the CS reconstruction process. METHODS A specially designed phantom consisting of wedges arranged in a fan pattern was used to calculate the MTF of the MRSI scans. Arc profiles of the phantom yield a square wave with a spatial frequency inversely proportional to the radius of the profile. The MTF was derived by considering the amplitude ratio of the fundamental frequency between the ideal square wave and the reconstructed output. As compressed sensing relies on nonlinear reconstruction and a minimization algorithm that requires the definition of reconstruction weights, the behavior of the MTF with respect to the choice of reconstruction weights and peak SNR is not intuitive. As such, simulations were used to investigate the response of the MTF to CS reconstruction weights at varying peak SNRs. The resulting optimized reconstruction weight was used to reconstruct an experimental CS-MRSI scan of the phantom and compare the corresponding MTF to those of a fully sampled dataset, and a time-equivalent Nyquist-sampled low-resolution dataset. RESULTS Simulations showed that MTFs of CS-MRSI datasets varied widely with different reconstruction weights. Moreover, the response of the MTF to peak SNR was not consistent across the range of reconstruction weights. An optimized reconstruction weight was derived from the simulations and used in reconstructing the experimental dataset. The MTF of the experimental CS-MRSI dataset showed improvement over the equivalent Nyquist sampled dataset at the resolution limit of 0.1 MTF, while it suffered from reduced response at low resolutions between 0.4 and 0.8 lp/cm. CONCLUSIONS The authors have shown that in certain cases small variations in the reconstruction weights yield a measureable effect on the CS reconstructed images, particularly with regard to MTF. Furthermore, it was found that peak SNR affects CS-MRSI MTF especially at higher wavelet reconstruction weights. Accordingly, prior knowledge of the expected peak SNR is essential to optimize the CS reconstruction process. Their phantom-MTF technique provides a quantitative performance measure of MRSI sequences, through which they were able to quantify a loss of 32.4% in spatial resolution for CS-MRSI at 0.1 MTF compared to a loss of 48.6% for the time-equivalent Nyquist-sampled low-resolution scans. They also showed that CS-MRSI suffered decreased low-resolution response as opposed to the equivalent low-resolution datasets.
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Affiliation(s)
- A A Heikal
- Department of Medical Physics, Cross Cancer Institute 11560 University Avenue, Edmonton, Alberta T6G 1Z2, Canada.
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Hattingen E, Bähr O, Rieger J, Blasel S, Steinbach J, Pilatus U. Phospholipid metabolites in recurrent glioblastoma: in vivo markers detect different tumor phenotypes before and under antiangiogenic therapy. PLoS One 2013; 8:e56439. [PMID: 23520454 PMCID: PMC3592858 DOI: 10.1371/journal.pone.0056439] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2012] [Accepted: 01/09/2013] [Indexed: 11/18/2022] Open
Abstract
Purpose Metabolic changes upon antiangiogenic therapy of recurrent glioblastomas (rGBMs) may provide new biomarkers for treatment efficacy. Since in vitro models showed that phospholipid membrane metabolism provides specific information on tumor growth we employed in-vivo MR-spectroscopic imaging (MRSI) of human rGBMs before and under bevacizumab (BVZ) to measure concentrations of phosphocholine (PCho), phosphoethanolamine (PEth), glycerophosphocholine (GPC), and glyceroethanolamine (GPE). Methods 1H and 31P MRSI was prospectively performed in 32 patients with rGBMs before and under BVZ therapy at 8 weeks intervals until tumor progression. Patients were dichotomized into subjects with long overall survival (OS) (>median OS) and short OS (<median OS) survival time from BVZ-onset. Metabolite concentrations from tumor tissue and their ratios were compared to contralateral normal-appearing tissue (control). Results Before BVZ, 1H-detectable choline signals (total GPC and PCho) in rGBMs were elevated but significance failed after dichotomizing. For metabolite ratios obtained by 31P MRSI, the short-OS group showed higher PCho/GPC (p = 0.004) in rGBMs compared to control tissue before BVZ while PEth/GPE was elevated in rGBMs of both groups (long-OS p = 0.04; short-OS p = 0.003). Under BVZ, PCho/GPC and PEth/GPE in the tumor initially decreased (p = 0.04) but only PCho/GPC re-increased upon tumor progression (p = 0.02). Intriguingly, in normal-appearing tissue an initial PEth/GPE decrease (p = 0.047) was followed by an increase at the time of tumor progression (p = 0.031). Conclusion An elevated PCho/GPC ratio in the short-OS group suggests that it is a negative predictive marker for BVZ efficacy. These gliomas may represent a malignant phenotype even growing under anti-VEGF treatment. Elevated PEth/GPE may represent an in-vivo biomarker more sensitive to GBM infiltration than MRI.
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Affiliation(s)
- Elke Hattingen
- Institute of Neuroradiology, Goethe-University Hospital Frankfurt, Frankfurt, Germany.
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Integration method of 3D MR spectroscopy into treatment planning system for glioblastoma IMRT dose painting with integrated simultaneous boost. Radiat Oncol 2013; 8:1. [PMID: 23280007 PMCID: PMC3552736 DOI: 10.1186/1748-717x-8-1] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Accepted: 12/27/2012] [Indexed: 11/25/2022] Open
Abstract
Background To integrate 3D MR spectroscopy imaging (MRSI) in the treatment planning system (TPS) for glioblastoma dose painting to guide simultaneous integrated boost (SIB) in intensity-modulated radiation therapy (IMRT). Methods For sixteen glioblastoma patients, we have simulated three types of dosimetry plans, one conventional plan of 60-Gy in 3D conformational radiotherapy (3D-CRT), one 60-Gy plan in IMRT and one 72-Gy plan in SIB-IMRT. All sixteen MRSI metabolic maps were integrated into TPS, using normalization with color-space conversion and threshold-based segmentation. The fusion between the metabolic maps and the planning CT scans were assessed. Dosimetry comparisons were performed between the different plans of 60-Gy 3D-CRT, 60-Gy IMRT and 72-Gy SIB-IMRT, the last plan was targeted on MRSI abnormalities and contrast enhancement (CE). Results Fusion assessment was performed for 160 transformations. It resulted in maximum differences <1.00 mm for translation parameters and ≤1.15° for rotation. Dosimetry plans of 72-Gy SIB-IMRT and 60-Gy IMRT showed a significantly decreased maximum dose to the brainstem (44.00 and 44.30 vs. 57.01 Gy) and decreased high dose-volumes to normal brain (19 and 20 vs. 23% and 7 and 7 vs. 12%) compared to 60-Gy 3D-CRT (p < 0.05). Conclusions Delivering standard doses to conventional target and higher doses to new target volumes characterized by MRSI and CE is now possible and does not increase dose to organs at risk. MRSI and CE abnormalities are now integrated for glioblastoma SIB-IMRT, concomitant with temozolomide, in an ongoing multi-institutional phase-III clinical trial. Our method of MR spectroscopy maps integration to TPS is robust and reliable; integration to neuronavigation systems with this method could also improve glioblastoma resection or guide biopsies.
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Ortega-Martorell S, Lisboa PJG, Vellido A, Simões RV, Pumarola M, Julià-Sapé M, Arús C. Convex non-negative matrix factorization for brain tumor delimitation from MRSI data. PLoS One 2012; 7:e47824. [PMID: 23110107 PMCID: PMC3479143 DOI: 10.1371/journal.pone.0047824] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2012] [Accepted: 09/17/2012] [Indexed: 11/24/2022] Open
Abstract
Background Pattern Recognition techniques can provide invaluable insights in the field of neuro-oncology. This is because the clinical analysis of brain tumors requires the use of non-invasive methods that generate complex data in electronic format. Magnetic Resonance (MR), in the modalities of spectroscopy (MRS) and spectroscopic imaging (MRSI), has been widely applied to this purpose. The heterogeneity of the tissue in the brain volumes analyzed by MR remains a challenge in terms of pathological area delimitation. Methodology/Principal Findings A pre-clinical study was carried out using seven brain tumor-bearing mice. Imaging and spectroscopy information was acquired from the brain tissue. A methodology is proposed to extract tissue type-specific sources from these signals by applying Convex Non-negative Matrix Factorization (Convex-NMF). Its suitability for the delimitation of pathological brain area from MRSI is experimentally confirmed by comparing the images obtained with its application to selected target regions, and to the gold standard of registered histopathology data. The former showed good accuracy for the solid tumor region (proliferation index (PI)>30%). The latter yielded (i) high sensitivity and specificity in most cases, (ii) acquisition conditions for safe thresholds in tumor and non-tumor regions (PI>30% for solid tumoral region; ≤5% for non-tumor), and (iii) fairly good results when borderline pixels were considered. Conclusions/Significance The unsupervised nature of Convex-NMF, which does not use prior information regarding the tumor area for its delimitation, places this approach one step ahead of classical label-requiring supervised methods for discrimination between tissue types, minimizing the negative effect of using mislabeled voxels. Convex-NMF also relaxes the non-negativity constraints on the observed data, which allows for a natural representation of the MRSI signal. This should help radiologists to accurately tackle one of the main sources of uncertainty in the clinical management of brain tumors, which is the difficulty of appropriately delimiting the pathological area.
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Affiliation(s)
- Sandra Ortega-Martorell
- Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Paulo J. G. Lisboa
- Department of Mathematics and Statistics, Liverpool John Moores University (LJMU), Liverpool, United Kingdom
| | - Alfredo Vellido
- Department of Computer Languages and Systems, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - Rui V. Simões
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America
| | - Martí Pumarola
- Murine Pathology Unit, Centre de Biotecnologia Animal i Teràpia Gènica, Departament de Medicina i Cirurgia Animals, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Margarida Julià-Sapé
- Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Carles Arús
- Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- * E-mail:
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Yan Y, Guo Z, Zhang H, Wang N, Xu Y. Precision radiotherapy for brain tumors: A 10-year bibliometric analysis. Neural Regen Res 2012; 7:1752-9. [PMID: 25624798 PMCID: PMC4302458 DOI: 10.3969/j.issn.1673-5374.2012.22.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2012] [Accepted: 08/02/2012] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE: Precision radiotherapy plays an important role in the management of brain tumors. This study aimed to identify global research trends in precision radiotherapy for brain tumors using a bibliometric analysis of the Web of Science. DATA RETRIEVAL: We performed a bibliometric analysis of data retrievals for precision radiotherapy for brain tumors containing the key words cerebral tumor, brain tumor, intensity-modulated radiotherapy, stereotactic body radiation therapy, stereotactic ablative radiotherapy, imaging-guided radiotherapy, dose-guided radiotherapy, stereotactic brachytherapy, and stereotactic radiotherapy using the Web of Science. SELECTION CRITERIA: Inclusion criteria: (a) peer-reviewed articles on precision radiotherapy for brain tumors which were published and indexed in the Web of Science; (b) type of articles: original research articles and reviews; (c) year of publication: 2002-2011. Exclusion criteria: (a) articles that required manual searching or telephone access; (b) Corrected papers or book chapters. MAIN OUTCOME MEASURES: (1) Annual publication output; (2) distribution according to country; (3) distribution according to institution; (4) top cited publications; (5) distribution according to journals; and (6) comparison of study results on precision radiotherapy for brain tumors. RESULTS: The stereotactic radiotherapy, intensity-modulated radiotherapy, and imaging-guided radiotherapy are three major methods of precision radiotherapy for brain tumors. There were 260 research articles addressing precision radiotherapy for brain tumors found within the Web of Science. The USA published the most papers on precision radiotherapy for brain tumors, followed by Germany and France. European Synchrotron Radiation Facility, German Cancer Research Center and Heidelberg University were the most prolific research institutes for publications on precision radiotherapy for brain tumors. Among the top 13 research institutes publishing in this field, seven are in the USA, three are in Germany, two are in France, and there is one institute in India. Research interests including urology and nephrology, clinical neurology, as well as rehabilitation are involved in precision radiotherapy for brain tumors studies. CONCLUSION: Precision radiotherapy for brain tumors remains a highly active area of research and development.
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Affiliation(s)
- Ying Yan
- Department of Radiotherapy, Shenyang Northern Hospital, Shenyang 110016, Liaoning Province, China
| | - Zhanwen Guo
- Department of Radiotherapy, Shenyang Northern Hospital, Shenyang 110016, Liaoning Province, China
| | - Haibo Zhang
- Department of Radiotherapy, Shenyang Northern Hospital, Shenyang 110016, Liaoning Province, China
| | - Ning Wang
- Department of Radiotherapy, Shenyang Northern Hospital, Shenyang 110016, Liaoning Province, China
| | - Ying Xu
- Department of Radiotherapy, Shenyang Northern Hospital, Shenyang 110016, Liaoning Province, China
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Guo J, Yao C, Chen H, Zhuang D, Tang W, Ren G, Wang Y, Wu J, Huang F, Zhou L. The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas. Acta Neurochir (Wien) 2012; 154:1361-70; discussion 1370. [PMID: 22729482 PMCID: PMC3407558 DOI: 10.1007/s00701-012-1418-x] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2012] [Accepted: 06/05/2012] [Indexed: 11/28/2022]
Abstract
Background The marginal delineation of gliomas cannot be defined by conventional imaging due to their infiltrative growth pattern. Here we investigate the relationship between changes in glioma metabolism by proton magnetic resonance spectroscopic imaging (1H-MRSI) and histopathological findings in order to determine an optimal threshold value of choline/N-acetyl-aspartate (Cho/NAA) that can be used to define the extent of glioma spread. Method Eighteen patients with different grades of glioma were examined using 1H-MRSI. Needle biopsies were performed under the guidance of neuronavigation prior to craniotomy. Intraoperative magnetic resonance imaging (MRI) was performed to evaluate the accuracy of sampling. Haematoxylin and eosin, and immunohistochemical staining with IDH1, MIB-1, p53, CD34 and glial fibrillary acidic protein (GFAP) antibodies were performed on all samples. Logistic regression analysis was used to determine the relationship between Cho/NAA and MIB-1, p53, CD34, and the degree of tumour infiltration. The clinical threshold ratio distinguishing tumour tissue in high-grade (grades III and IV) glioma (HGG) and low-grade (grade II) glioma (LGG) was calculated. Results In HGG, higher Cho/NAA ratios were associated with a greater probability of higher MIB-1 counts, stronger CD34 expression, and tumour infiltration. Ratio threshold values of 0.5, 1.0, 1.5 and 2.0 appeared to predict the specimens containing the tumour with respective probabilities of 0.38, 0.60, 0.79, 0.90 in HGG and 0.16, 0.39, 0.67, 0.87 in LGG. Conclusions HGG and LGG exhibit different spectroscopic patterns. Using 1H-MRSI to guide the extent of resection has the potential to improve the clinical outcome of glioma surgery.
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Affiliation(s)
- Jun Guo
- Shanghai Medical College, Fudan University, Shanghai, 200040 China
| | - Chengjun Yao
- Glioma Surgery Division, Department of Neurologic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No.12 Central Wulumuqi Road, Jing’an District, Shanghai, 200040 China
| | - Hong Chen
- Department of Neuropathology, Fudan University, Shanghai, 200040 China
| | - Dongxiao Zhuang
- Glioma Surgery Division, Department of Neurologic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No.12 Central Wulumuqi Road, Jing’an District, Shanghai, 200040 China
| | - Weijun Tang
- Department of Radiology, Huashan Hospital, Shanghai, China
| | - Guang Ren
- Department of Radiology, Huashan Hospital, Shanghai, China
| | - Yin Wang
- Department of Neuropathology, Fudan University, Shanghai, 200040 China
| | - Jinsong Wu
- Glioma Surgery Division, Department of Neurologic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No.12 Central Wulumuqi Road, Jing’an District, Shanghai, 200040 China
| | - Fengping Huang
- Glioma Surgery Division, Department of Neurologic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No.12 Central Wulumuqi Road, Jing’an District, Shanghai, 200040 China
| | - Liangfu Zhou
- Glioma Surgery Division, Department of Neurologic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No.12 Central Wulumuqi Road, Jing’an District, Shanghai, 200040 China
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Geethanath S, Baek HM, Ganji SK, Ding Y, Maher EA, Sims RD, Choi C, Lewis MA, Kodibagkar VD. Compressive sensing could accelerate 1H MR metabolic imaging in the clinic. Radiology 2012; 262:985-94. [PMID: 22357898 DOI: 10.1148/radiol.11111098] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To retrospectively evaluate the fidelity of magnetic resonance (MR) spectroscopic imaging data preservation at a range of accelerations by using compressed sensing. MATERIALS AND METHODS The protocols were approved by the institutional review board of the university, and written informed consent to acquire and analyze MR spectroscopic imaging data was obtained from the subjects prior to the acquisitions. This study was HIPAA compliant. Retrospective application of compressed sensing was performed on 10 clinical MR spectroscopic imaging data sets, yielding 600 voxels from six normal brain data sets, 163 voxels from two brain tumor data sets, and 36 voxels from two prostate cancer data sets for analysis. The reconstructions were performed at acceleration factors of two, three, four, five, and 10 and were evaluated by using the root mean square error (RMSE) metric, metabolite maps (choline, creatine, N-acetylaspartate [NAA], and/or citrate), and statistical analysis involving a voxelwise paired t test and one-way analysis of variance for metabolite maps and ratios for comparison of the accelerated reconstruction with the original case. RESULTS The reconstructions showed high fidelity for accelerations up to 10 as determined by the low RMSE (< 0.05). Similar means of the metabolite intensities and hot-spot localization on metabolite maps were observed up to a factor of five, with lack of statistically significant differences compared with the original data. The metabolite ratios of choline to NAA and choline plus creatine to citrate did not show significant differences from the original data for up to an acceleration factor of five in all cases and up to that of 10 for some cases. CONCLUSION A reduction of acquisition time by up to 80%, with negligible loss of information as evaluated with clinically relevant metrics, has been successfully demonstrated for hydrogen 1 MR spectroscopic imaging.
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Affiliation(s)
- Sairam Geethanath
- Joint Graduate Program in Biomedical Engineering, UT Arlington and UT Southwestern Medical Center, Dallas, Tex, USA
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McIntyre DJO, Madhu B, Lee SH, Griffiths JR. Magnetic resonance spectroscopy of cancer metabolism and response to therapy. Radiat Res 2012; 177:398-435. [PMID: 22401303 DOI: 10.1667/rr2903.1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Magnetic resonance spectroscopy allows noninvasive in vivo measurements of biochemical information from living systems, ranging from cultured cells through experimental animals to humans. Studies of biopsies or extracts offer deeper insights by detecting more metabolites and resolving metabolites that cannot be distinguished in vivo. The pharmacokinetics of certain drugs, especially fluorinated drugs, can be directly measured in vivo. This review briefly describes these methods and their applications to cancer metabolism, including glycolysis, hypoxia, bioenergetics, tumor pH, and tumor responses to radiotherapy and chemotherapy.
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Affiliation(s)
- Dominick J O McIntyre
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
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