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Low JC, Cao J, Hesse F, Wright AJ, Tsyben A, Alshamleh I, Mair R, Brindle KM. Deuterium Metabolic Imaging Differentiates Glioblastoma Metabolic Subtypes and Detects Early Response to Chemoradiotherapy. Cancer Res 2024; 84:1996-2008. [PMID: 38635885 PMCID: PMC11176915 DOI: 10.1158/0008-5472.can-23-2552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 01/30/2024] [Accepted: 03/28/2024] [Indexed: 04/20/2024]
Abstract
Metabolic subtypes of glioblastoma (GBM) have different prognoses and responses to treatment. Deuterium metabolic imaging with 2H-labeled substrates is a potential approach to stratify patients into metabolic subtypes for targeted treatment. In this study, we used 2H magnetic resonance spectroscopy and magnetic resonance spectroscopic imaging (MRSI) measurements of [6,6'-2H2]glucose metabolism to identify metabolic subtypes and their responses to chemoradiotherapy in patient-derived GBM xenografts in vivo. The metabolism of patient-derived cells was first characterized in vitro by measuring the oxygen consumption rate, a marker of mitochondrial tricarboxylic acid cycle activity, as well as the extracellular acidification rate and 2H-labeled lactate production from [6,6'-2H2]glucose, which are markers of glycolytic activity. Two cell lines representative of a glycolytic subtype and two representative of a mitochondrial subtype were identified. 2H magnetic resonance spectroscopy and MRSI measurements showed similar concentrations of 2H-labeled glucose from [6,6'-2H2]glucose in all four tumor models when implanted orthotopically in mice. The glycolytic subtypes showed higher concentrations of 2H-labeled lactate than the mitochondrial subtypes and normal-appearing brain tissue, whereas the mitochondrial subtypes showed more glutamate/glutamine labeling, a surrogate for tricarboxylic acid cycle activity, than the glycolytic subtypes and normal-appearing brain tissue. The response of the tumors to chemoradiation could be detected within 24 hours of treatment completion, with the mitochondrial subtypes showing a decrease in both 2H-labeled glutamate/glutamine and lactate concentrations and glycolytic tumors showing a decrease in 2H-labeled lactate concentration. This technique has the potential to be used clinically for treatment selection and early detection of treatment response. SIGNIFICANCE Deuterium magnetic resonance spectroscopic imaging of glucose metabolism has the potential to differentiate between glycolytic and mitochondrial metabolic subtypes in glioblastoma and to evaluate early treatment responses, which could guide patient treatment.
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Affiliation(s)
- Jacob C.M. Low
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Jianbo Cao
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Friederike Hesse
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Alan J. Wright
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Anastasia Tsyben
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Islam Alshamleh
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Richard Mair
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Kevin M. Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom
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Cela I, Capone E, Trevisi G, Sala G. Extracellular vesicles in glioblastoma: Biomarkers and therapeutic tools. Semin Cancer Biol 2024; 101:25-43. [PMID: 38754752 DOI: 10.1016/j.semcancer.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/19/2024] [Accepted: 04/30/2024] [Indexed: 05/18/2024]
Abstract
Glioblastoma (GBM) is the most aggressive tumor among the gliomas and intracranial tumors and to date prognosis for GBM patients remains poor, with a median survival typically measured in months to a few years depending on various factors. Although standardized therapies are routinely employed, it is clear that these strategies are unable to cope with heterogeneity and invasiveness of GBM. Furthermore, diagnosis and monitoring of responses to therapies are directly dependent on tissue biopsies or magnetic resonance imaging (MRI) techniques. From this point of view, liquid biopsies are arising as key sources of a variety of biomarkers with the advantage of being easily accessible and monitorable. In this context, extracellular vesicles (EVs), physiologically shed into body fluids by virtually all cells, are gaining increasing interest both as natural carriers of biomarkers and as specific signatures even for GBM. What makes these vesicles particularly attractive is they are also emerging as therapeutical vehicles to treat GBM given their native ability to cross the blood-brain barrier (BBB). Here, we reviewed recent advances on the use of EVs as biomarker for liquid biopsy and nanocarriers for targeted delivery of anticancer drugs in glioblastoma.
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Affiliation(s)
- Ilaria Cela
- Department of Innovative Technologies in Medicine & Dentistry, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy; Center for Advanced Studies and Technology (CAST), University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Emily Capone
- Department of Innovative Technologies in Medicine & Dentistry, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy; Center for Advanced Studies and Technology (CAST), University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Gianluca Trevisi
- Department of Neurosciences, Imaging and Clinical Sciences, "G. D'Annunzio" University, Chieti, Italy; Neurosurgical Unit, Santo Spirito Hospital, Pescara 65121, Italy
| | - Gianluca Sala
- Department of Innovative Technologies in Medicine & Dentistry, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy; Center for Advanced Studies and Technology (CAST), University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy.
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3
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Ebaid NY, Ahmed RN, Assy MM, Amin MI, Alaa Eldin AM, Alsowey AM, Abdelhay RM. Diagnostic validity and reliability of BT-RADS in the management of recurrent high-grade glioma. J Neuroradiol 2024; 51:101190. [PMID: 38492800 DOI: 10.1016/j.neurad.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND AND PURPOSE BT-RADS is a new framework system for reporting the treatment response of brain tumors. The aim of the study was to assess the diagnostic performance and reliability of the BT-RADS in predicting the recurrence of high-grade glioma (HGG). MATERIALS AND METHODS This prospective single-center study recruited 81 cases with previously operated and pathologically proven HGG. The patients underwent baseline and follow-up contrast-enhanced MRI (CE-MRI). Two neuro-radiologists with ten years-experience in neuroimaging independently analyzed and interpreted the MRI images and assigned a BT-RADS category for each case. To assess the diagnostic accuracy of the BT-RADS for detecting recurrent HGG, the reference standard was the histopathology for BT-RADS categories 3 and 4, while neurological clinical examination and clinical follow up were used as a reference for BT-RADS categories 1 and 2. The inter-reader agreement was assessed using the Cohen's Kappa test. RESULTS The study included 81 cases of HGG, of which 42 were recurrent and 39 were non-recurrent HGG cases based on the reference test. BT-RADS 3B was the best cutoff for predicting recurrent HGG with a sensitivity of 90.5 % to 92.9 %, specificity of 76.9 % to 84.6 %, and accuracy of 83.9 % to 88.9 %, based on both readers. The BT-RADS showed a substantial inter-reader agreement with a K of 0.710 (P = 0.001). CONCLUSIONS The BT-RADS is a valid and reliable framework for predicting recurrent HGG. Moreover, BT-RADS can help neuro-oncologists make clinical decisions that can potentially improve the patient's outcome.
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Affiliation(s)
- Noha Yahia Ebaid
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt; Negida academy LLC, Arlington, MA, USA
| | - Rasha Nadeem Ahmed
- Department of Surgery, College of medicine, Ninevah University, Mosul, Iraq
| | - Mostafa Mohamad Assy
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt
| | - Mohamed Ibrahim Amin
- Department of Radiology, Faculty of medicine, Zagazig University, Zagazig, Egypt
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Cadrien C, Sharma S, Lazen P, Licandro R, Furtner J, Lipka A, Niess E, Hingerl L, Motyka S, Gruber S, Strasser B, Kiesel B, Mischkulnig M, Preusser M, Roetzer-Pejrimovsky T, Wöhrer A, Weber M, Dorfer C, Trattnig S, Rössler K, Bogner W, Widhalm G, Hangel G. 7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading. Cancer Imaging 2024; 24:67. [PMID: 38802883 PMCID: PMC11129458 DOI: 10.1186/s40644-024-00704-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 04/27/2024] [Indexed: 05/29/2024] Open
Abstract
INTRODUCTION With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients. METHODS We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status. RESULTS Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy. CONCLUSIONS We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.
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Affiliation(s)
- Cornelius Cadrien
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Sukrit Sharma
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Philipp Lazen
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Roxane Licandro
- A.A. Martinos Center for Biomedical Imaging, Laboratory for Computational Neuroimaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, USA
- Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab (CIR), Medical University of Vienna, Vienna, Austria
| | - Julia Furtner
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Danube Private University, Krems, Austria
| | - Alexandra Lipka
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Eva Niess
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Barbara Kiesel
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Mario Mischkulnig
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Matthias Preusser
- Division of Oncology, Department of Internal Medicine I, Medical University of Vienna, Vienna, Austria
| | - Thomas Roetzer-Pejrimovsky
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Adelheid Wöhrer
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab (CIR), Medical University of Vienna, Vienna, Austria
| | - Christian Dorfer
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Karl Rössler
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Georg Widhalm
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Gilbert Hangel
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria.
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria.
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria.
- Medical Imaging Cluster, Medical University of Vienna, Vienna, Austria.
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Indira Chandran V, Gopala S, Venkat EH, Kjolby M, Nejsum P. Extracellular vesicles in glioblastoma: a challenge and an opportunity. NPJ Precis Oncol 2024; 8:103. [PMID: 38760427 PMCID: PMC11101656 DOI: 10.1038/s41698-024-00600-2] [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: 12/08/2023] [Accepted: 05/03/2024] [Indexed: 05/19/2024] Open
Abstract
Glioblastoma is a highly heterogeneous tumor whose pathophysiological complexities dictate both the diagnosis of disease severity as well as response to therapy. Conventional diagnostic tools and standard treatment regimens have only managed to achieve limited success in the management of patients suspected of glioblastoma. Extracellular vesicles are an emerging liquid biopsy tool that has shown great promise in resolving the limitations presented by the heterogeneous nature of glioblastoma. Here we discuss the contrasting yet interdependent dual role of extracellular vesicles as communication agents that contribute to the progression of glioblastoma by creating a heterogeneous microenvironment and as a liquid biopsy tool providing an opportunity to accurately identify the disease severity and progression.
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Affiliation(s)
- Vineesh Indira Chandran
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
- Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark.
| | - Srinivas Gopala
- Department of Biochemistry, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Easwer Hariharan Venkat
- Department of Neurosurgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Mads Kjolby
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Pharmacology and Steno Diabetes Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Peter Nejsum
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark
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Herings SDA, van den Elshout R, de Wit R, Mannil M, Ravesloot C, Scheenen TWJ, Arens A, van der Kolk A, Meijer FJA, Henssen DJHA. How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods. Neuroradiology 2024:10.1007/s00234-024-03374-3. [PMID: 38714545 DOI: 10.1007/s00234-024-03374-3] [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: 11/16/2023] [Accepted: 05/01/2024] [Indexed: 05/10/2024]
Abstract
INTRODUCTION Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques. METHODS 50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC). RESULTS 29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment. CONCLUSIONS VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.
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Affiliation(s)
- Siem D A Herings
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands.
| | - Rik van den Elshout
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Rebecca de Wit
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Manoj Mannil
- University Clinic for Radiology, Westfälische Wilhelms-University Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, E48149, Muenster, Germany
| | - Cécile Ravesloot
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Anne Arens
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Anja van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Dylan J H A Henssen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
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Almalki YE, Basha MAA, Metwally MI, Zeed NA, Nada MG, Alduraibi SK, Morsy AA, Balata R, Al Attar AZ, Amer MM, Farag MAEAM, Aly SA, Basha AMA, Hamed EM. Validating Brain Tumor Reporting and Data System (BT-RADS) as a Diagnostic Tool for Glioma Follow-Up after Surgery. Biomedicines 2024; 12:887. [PMID: 38672241 PMCID: PMC11048183 DOI: 10.3390/biomedicines12040887] [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: 03/03/2024] [Revised: 04/03/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Gliomas are a type of brain tumor that requires accurate monitoring for progression following surgery. The Brain Tumor Reporting and Data System (BT-RADS) has emerged as a potential tool for improving diagnostic accuracy and reducing the need for repeated operations. This prospective multicenter study aimed to evaluate the diagnostic accuracy and reliability of BT-RADS in predicting tumor progression (TP) in postoperative glioma patients and evaluate its acceptance in clinical practice. The study enrolled patients with a history of partial or complete resection of high-grade glioma. All patients underwent two consecutive follow-up brain MRI examinations. Five neuroradiologists independently evaluated the MRI examinations using the BT-RADS. The diagnostic accuracy of the BT-RADS for predicting TP was calculated using histopathology after reoperation and clinical and imaging follow-up as reference standards. Reliability based on inter-reader agreement (IRA) was assessed using kappa statistics. Reader acceptance was evaluated using a short survey. The final analysis included 73 patients (male, 67.1%; female, 32.9%; mean age, 43.2 ± 12.9 years; age range, 31-67 years); 47.9% showed TP, and 52.1% showed no TP. According to readers, TP was observed in 25-41.7% of BT-3a, 61.5-88.9% of BT-3b, 75-90.9% of BT-3c, and 91.7-100% of BT-RADS-4. Considering >BT-RADS-3a as a cutoff value for TP, the sensitivity, specificity, and accuracy of the BT-RADS were 68.6-85.7%, 84.2-92.1%, and 78.1-86.3%, respectively, according to the reader. The overall IRA was good (κ = 0.75) for the final BT-RADS classification and very good for detecting new lesions (κ = 0.89). The readers completely agreed with the statement "the application of the BT-RADS should be encouraged" (score = 25). The BT-RADS has good diagnostic accuracy and reliability for predicting TP in postoperative glioma patients. However, BT-RADS 3 needs further improvements to increase its diagnostic accuracy.
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Affiliation(s)
- Yassir Edrees Almalki
- Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran 61441, Saudi Arabia;
| | - Mohammad Abd Alkhalik Basha
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Maha Ibrahim Metwally
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Nesma Adel Zeed
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Mohamad Gamal Nada
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | | | - Ahmed A. Morsy
- Department of Neurosurgery, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt;
| | - Rawda Balata
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (R.B.); (A.Z.A.A.)
| | - Ahmed Z. Al Attar
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (R.B.); (A.Z.A.A.)
| | - Mona M. Amer
- Department of Neurology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt;
| | | | - Sameh Abdelaziz Aly
- Department of Diagnostic Radiology, Faculty of Human Medicine, Benha University, Benha 13511, Egypt;
| | | | - Enas Mahmoud Hamed
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
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8
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Li K, Zhu Q, Yang J, Zheng Y, Du S, Song M, Peng Q, Yang R, Liu Y, Qi L. Imaging and Liquid Biopsy for Distinguishing True Progression From Pseudoprogression in Gliomas, Current Advances and Challenges. Acad Radiol 2024:S1076-6332(24)00162-4. [PMID: 38614827 DOI: 10.1016/j.acra.2024.03.019] [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: 12/10/2023] [Revised: 01/14/2024] [Accepted: 03/18/2024] [Indexed: 04/15/2024]
Abstract
RATIONALE AND OBJECTIVES Gliomas are aggressive brain tumors with a poor prognosis. Assessing treatment response is challenging because magnetic resonance imaging (MRI) may not distinguish true progression (TP) from pseudoprogression (PsP). This review aims to discuss imaging techniques and liquid biopsies used to distinguish TP from PsP. MATERIALS AND METHODS This review synthesizes existing literature to examine advances in imaging techniques, such as magnetic resonance diffusion imaging (MRDI), perfusion-weighted imaging (PWI) MRI, and liquid biopsies, for identifying TP or PsP through tumor markers and tissue characteristics. RESULTS Advanced imaging techniques, including MRDI and PWI MRI, have proven effective in delineating tumor tissue properties, offering valuable insights into glioma behavior. Similarly, liquid biopsy has emerged as a potent tool for identifying tumor-derived markers in biofluids, offering a non-invasive glimpse into tumor evolution. Despite their promise, these methodologies grapple with significant challenges. Their sensitivity remains inconsistent, complicating the accurate differentiation between TP and PSP. Furthermore, the absence of standardized protocols across platforms impedes the reliability of comparisons, while inherent biological variability adds complexity to data interpretation. CONCLUSION Their potential applications have been highlighted, but gaps remain before routine clinical use. Further research is needed to develop and validate these promising methods for distinguishing TP from PsP in gliomas.
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Affiliation(s)
- Kaishu Li
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China; Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China.; Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Qihui Zhu
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Junyi Yang
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Yin Zheng
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Siyuan Du
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Meihui Song
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Qian Peng
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Runwei Yang
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Yawei Liu
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Ling Qi
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China.
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9
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Hu LS, Smits M, Kaufmann TJ, Knutsson L, Rapalino O, Galldiks N, Sundgrene PC, Cha S. Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2024. [PMID: 38477525 DOI: 10.2214/ajr.23.30612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
This AJR Expert Panel Narrative explores the current status of advanced MRI and PET techniques for the post-therapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from post-treatment effects include DWI and diffusion tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced MRI, and arterial spin labeling; MR spectroscopy including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after HGG treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The article concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.
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Affiliation(s)
- Leland S Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ
- Department of Cancer Biology, Mayo Clinic, Phoenix, AZ
- Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | | | - Linda Knutsson
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Otto Rapalino
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Norbert Galldiks
- Dept. of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
- Inst. of Neuroscience and Medicine (INM-3), Research Center Juelich, Juelich, Germany
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
| | - Pia C Sundgrene
- Institution of Clinical Sciences Lund/Radiology, Lund University, Lund Sweden
- Lund BioImaging Center, Lund University, Lud, Sweden
- Department of Medical Imaging and Function Skane University hospital, Lund, Sweden
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
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10
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Hilario A, Salvador E, Cardenas A, Romero J, Lechuga C, Chen Z, Martinez de Aragon A, Perez-Nuñez A, Hernandez-Lain A, Sepulveda J, Lagares A, Toldos O, Rodriguez-Gonzalez V, Ramos A. Low rCBV values in glioblastoma tumor progression under chemoradiotherapy. Neuroradiology 2024; 66:317-323. [PMID: 38183424 DOI: 10.1007/s00234-023-03279-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/26/2023] [Indexed: 01/08/2024]
Abstract
PURPOSE After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence. METHODS Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software. RESULTS Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time. CONCLUSION Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.
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Affiliation(s)
- A Hilario
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain.
| | - E Salvador
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Cardenas
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - J Romero
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - C Lechuga
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - Z Chen
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Martinez de Aragon
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Perez-Nuñez
- Department of Neurosurgery, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Hernandez-Lain
- Department of Neuropathology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - J Sepulveda
- Department of Medical Oncology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Lagares
- Department of Neurosurgery, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - O Toldos
- Department of Neuropathology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - V Rodriguez-Gonzalez
- Department of Radiation Oncology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Ramos
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
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11
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Bhattacharya K, Rastogi S, Mahajan A. Post-treatment imaging of gliomas: challenging the existing dogmas. Clin Radiol 2024; 79:e376-e392. [PMID: 38123395 DOI: 10.1016/j.crad.2023.11.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 10/23/2023] [Accepted: 11/21/2023] [Indexed: 12/23/2023]
Abstract
Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.
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Affiliation(s)
- K Bhattacharya
- Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - S Rastogi
- Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
| | - A Mahajan
- Department of imaging, The Clatterbridge Cancer Centre, NHS Foundation Trust, Pembroke Place, Liverpool L7 8YA, UK; University of Liverpool, Liverpool L69 3BX, UK.
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12
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Otsuji R, Fujioka Y, Hata N, Kuga D, Hatae R, Sangatsuda Y, Nakamizo A, Mizoguchi M, Yoshimoto K. Liquid Biopsy for Glioma Using Cell-Free DNA in Cerebrospinal Fluid. Cancers (Basel) 2024; 16:1009. [PMID: 38473369 DOI: 10.3390/cancers16051009] [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: 12/25/2023] [Revised: 02/24/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Glioma is one of the most common primary central nervous system (CNS) tumors, and its molecular diagnosis is crucial. However, surgical resection or biopsy is risky when the tumor is located deep in the brain or brainstem. In such cases, a minimally invasive approach to liquid biopsy is beneficial. Cell-free DNA (cfDNA), which directly reflects tumor-specific genetic changes, has attracted attention as a target for liquid biopsy, and blood-based cfDNA monitoring has been demonstrated for other extra-cranial cancers. However, it is still challenging to fully detect CNS tumors derived from cfDNA in the blood, including gliomas, because of the unique structure of the blood-brain barrier. Alternatively, cerebrospinal fluid (CSF) is an ideal source of cfDNA and is expected to contribute significantly to the liquid biopsy of gliomas. Several successful studies have been conducted to detect tumor-specific genetic alterations in cfDNA from CSF using digital PCR and/or next-generation sequencing. This review summarizes the current status of CSF-based cfDNA-targeted liquid biopsy for gliomas. It highlights how the approaches differ from liquid biopsies of other extra-cranial cancers and discusses the current issues and prospects.
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Affiliation(s)
- Ryosuke Otsuji
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Yutaka Fujioka
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Nobuhiro Hata
- Department of Neurosurgery, Oita University Faculty of Medicine, Yufu 879-5593, Japan
| | - Daisuke Kuga
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Ryusuke Hatae
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Yuhei Sangatsuda
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Akira Nakamizo
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Masahiro Mizoguchi
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
- Department of Neurosurgery, National Hospital Organization Kyushu Medical Center, Clinical Research Institute, Fukuoka 810-8563, Japan
| | - Koji Yoshimoto
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
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13
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Blakstad H, Mendoza Mireles EE, Heggebø LC, Magelssen H, Sprauten M, Johannesen TB, Vik-Mo EO, Leske H, Niehusmann P, Skogen K, Helseth E, Emblem KE, Brandal P. Incidence and outcome of pseudoprogression after radiation therapy in glioblastoma patients: A cohort study. Neurooncol Pract 2024; 11:36-45. [PMID: 38222046 PMCID: PMC10785573 DOI: 10.1093/nop/npad063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024] Open
Abstract
Background Differentiating post-radiation MRI changes from progressive disease (PD) in glioblastoma (GBM) patients represents a major challenge. The clinical problem is two-sided; avoid termination of effective therapy in case of pseudoprogression (PsP) and continuation of ineffective therapy in case of PD. We retrospectively assessed the incidence, management, and prognostic impact of PsP and analyzed factors associated with PsP in a GBM patient cohort. Methods Consecutive GBM patients diagnosed in the South-Eastern Norway Health Region from 2015 to 2018 who had received RT and follow-up MRI were included. Tumor, patient, and treatment characteristics were analyzed in relationship to re-evaluated MRI examinations at 3 and 6 months post-radiation using Response Assessment in Neuro-Oncology criteria. Results A total of 284 patients were included in the study. PsP incidence 3 and 6 months post-radiation was 19.4% and 7.0%, respectively. In adjusted analyses, methylated O6-methylguanine-DNA methyltransferase (MGMT) promoter and the absence of neurological deterioration were associated with PsP at both 3 (p < .001 and p = .029, respectively) and 6 months (p = .045 and p = .034, respectively) post-radiation. For patients retrospectively assessed as PD 3 months post-radiation, there was no survival benefit of treatment change (p = .838). Conclusions PsP incidence was similar to previous reports. In addition to the previously described correlation of methylated MGMT promoter with PsP, we also found that absence of neurological deterioration significantly correlated with PsP. Continuation of temozolomide courses did not seem to compromise survival for patients with PD at 3 months post-radiation; therefore, we recommend continuing adjuvant temozolomide courses in case of inconclusive MRI findings.
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Affiliation(s)
- Hanne Blakstad
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Eduardo Erasmo Mendoza Mireles
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Vilhelm Magnus Laboratory, Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
| | - Liv Cathrine Heggebø
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Mette Sprauten
- Department of Oncology, Oslo University Hospital, Oslo, Norway
| | - Tom Børge Johannesen
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Cancer Registry of Norway, Oslo, Norway
| | - Einar Osland Vik-Mo
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Vilhelm Magnus Laboratory, Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
| | - Henning Leske
- Department of Pathology, Oslo University Hospital, Oslo
- University of Oslo, Oslo, Norway
| | - Pitt Niehusmann
- Department of Pathology, Oslo University Hospital, Oslo
- Division of Cancer Medicine, Oslo University Hospital, Oslo
| | - Karoline Skogen
- Department of Radiology, Oslo University Hospital, Oslo, Norway
| | - Eirik Helseth
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
| | - Kyrre Eeg Emblem
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Petter Brandal
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway
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14
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Lambrecht S, Liu D, Dzaye O, Kamson DO, Reis J, Liebig T, Holdhoff M, Van Zijl P, Qin Q, Lin DDM. Velocity-Selective Arterial Spin Labeling Perfusion in Monitoring High Grade Gliomas Following Therapy: Clinical Feasibility at 1.5T and Comparison with Dynamic Susceptibility Contrast Perfusion. Brain Sci 2024; 14:126. [PMID: 38391701 PMCID: PMC10886779 DOI: 10.3390/brainsci14020126] [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: 12/31/2023] [Revised: 01/19/2024] [Accepted: 01/20/2024] [Indexed: 02/24/2024] Open
Abstract
MR perfusion imaging is important in the clinical evaluation of primary brain tumors, particularly in differentiating between true progression and treatment-induced change. The utility of velocity-selective ASL (VSASL) compared to the more commonly utilized DSC perfusion technique was assessed in routine clinical surveillance MR exams of 28 patients with high-grade gliomas at 1.5T. Using RANO criteria, patients were assigned to two groups, one with detectable residual/recurrent tumor ("RT", n = 9), and the other with no detectable residual/recurrent tumor ("NRT", n = 19). An ROI was drawn to encompass the largest dimension of the lesion with measures normalized against normal gray matter to yield rCBF and tSNR from VSASL, as well as rCBF and leakage-corrected relative CBV (lc-rCBV) from DSC. VSASL (rCBF and tSNR) and DSC (rCBF and lc-rCBV) metrics were significantly higher in the RT group than the NRT group allowing adequate discrimination (p < 0.05, Mann-Whitney test). Lin's concordance analyses showed moderate to excellent concordance between the two methods, with a stronger, moderate correlation between VSASL rCBF and DSC lc-rCBV (r = 0.57, p = 0.002; Pearson's correlation). These results suggest that VSASL is clinically feasible at 1.5T and has the potential to offer a noninvasive alternative to DSC perfusion in monitoring high-grade gliomas following therapy.
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Affiliation(s)
- Sebastian Lambrecht
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Institute of Neuroradiology, University Hospital LMU Munich, 81377 Munich, Germany
| | - Dapeng Liu
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Omar Dzaye
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - David O Kamson
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Jonas Reis
- Institute of Neuroradiology, University Hospital LMU Munich, 81377 Munich, Germany
| | - Thomas Liebig
- Institute of Neuroradiology, University Hospital LMU Munich, 81377 Munich, Germany
| | - Matthias Holdhoff
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Peter Van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Qin Qin
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Doris D M Lin
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
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15
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Tunlayadechanont P, Panyaping T, Chansakul T, Hirunpat P, Kampaengtip A. Intravoxel incoherent motion for differentiating residual/recurrent tumor from post-treatment change in patients with high-grade glioma. Neuroradiol J 2023; 36:657-664. [PMID: 37105183 PMCID: PMC10649527 DOI: 10.1177/19714009231173108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023] Open
Abstract
PURPOSE To investigate the diagnostic value of f derived from IVIM technique and to correlate it with rCBV derived from DSC for the differentiation of residual/recurrent tumor from post-treatment change in patients with high-grade glioma. MATERIALS AND METHODS Patients who underwent MR imaging with IVIM and DSC studies for evaluation of high-grade glioma after standard treatment were enrolled in this retrospective study. For qualitative analysis, the f and rCBV maps were interpreted as hypoperfused or hyperperfused in each parameter. Quantitative analysis was performed using ROI analysis in f and rCBV parameters. The lesions were divided into residual/recurrent tumor and post-treatment change groups. RESULTS Nineteen patients with high-grade glioma were included. In qualitative analysis, the f-map shows higher sensitivity (100.0%) than rCBV map (92.3%), while the rCBV map shows higher specificity (100.0%) than the f-map (83.3%). In quantitative analysis, the optimal cutoff values of 1.19 for f and 1.06 for rCBV are shown to provide high diagnostic value with high sensitivity (91.7%) for both parameters but slightly higher specificity of rCBV (85.7%) than f (71.4%). The correlation between f and rCBV was good with ICC of 0.810. CONCLUSION The f value measured by IVIM technique, non-contrast perfusion technique, has high diagnostic performance and potential to be an alternative method to CBV measured by DSC for differentiation between residual/recurrent tumor and post-treatment change in patients with high-grade glioma.
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Affiliation(s)
- Padcha Tunlayadechanont
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Theeraphol Panyaping
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Thanissara Chansakul
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Pornrujee Hirunpat
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Adun Kampaengtip
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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Teunissen WHT, Lavrova A, van den Bent M, van der Hoorn A, Warnert EAH, Smits M. Arterial spin labelling MRI for brain tumour surveillance: do we really need cerebral blood flow maps? Eur Radiol 2023; 33:8005-8013. [PMID: 37566264 PMCID: PMC10598159 DOI: 10.1007/s00330-023-10099-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 06/09/2023] [Accepted: 07/01/2023] [Indexed: 08/12/2023]
Abstract
OBJECTIVES Arterial spin labelling (ASL) perfusion MRI is one of the available advanced MRI techniques for brain tumour surveillance. The first aim of this study was to investigate the correlation between quantitative cerebral blood flow (CBF) and non-quantitative perfusion weighted imaging (ASL-PWI) measurements. The second aim was to investigate the diagnostic accuracy of ASL-CBF and ASL-PWI measurements as well as visual assessment for identifying tumour progression. METHODS A consecutive cohort of patients who underwent 3-T MRI surveillance containing ASL for treated brain tumours was used. ROIs were drawn in representative parts of tumours in the ASL-CBF maps and copied to the ASL-PWI. ASL-CBF ratios and ASL-PWI ratios of the tumour ROI versus normal appearing white matter (NAWM) were correlated (Pearson correlation) and AUCs were calculated to assess diagnostic accuracy. Additionally, lesions were visually classified as hypointense, isointense, or hyperintense. We calculated accuracy at two thresholds: low threshold (between hypointense-isointense) and high threshold (between isointense-hyperintense). RESULTS A total of 173 lesions, both enhancing and non-enhancing, measured in 115 patients (93 glioma, 16 metastasis, and 6 lymphoma) showed a very high correlation of 0.96 (95% CI: 0.88-0.99) between ASL-CBF ratios and ASL-PWI ratios. AUC was 0.76 (95%CI: 0.65-0.88) for ASL-CBF ratios and 0.72 (95%CI: 0.58-0.85) for ASL-PWI ratios. Diagnostic accuracy of visual assessment for enhancing lesions was 0.72. CONCLUSION ASL-PWI ratios and ASL-CBF ratios showed a high correlation and comparable AUCs; therefore, quantification of ASL-CBF could be omitted in these patients. Visual classification had comparable diagnostic accuracy to the ASL-PWI or ASL-CBF ratios. CLINICAL RELEVANCE STATEMENT This study shows that CBF quantification of ASL perfusion MRI could be omitted for brain tumour surveillance and that visual assessment provides the same diagnostic accuracy. This greatly reduces the complexity of the use of ASL in routine clinical practice. KEY POINTS • Arterial spin labelling MRI for clinical brain tumour surveillance is undervalued and underinvestigated. • Non-quantitative and quantitative arterial spin labelling assessments show high correlation and comparable diagnostic accuracy. • Quantification of arterial spin labelling MRI could be omitted to improve daily clinical workflow.
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Affiliation(s)
- Wouter H T Teunissen
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
| | - Anna Lavrova
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, University of Michigan Hospital, Ann Arbor, MI, USA
| | - Martin van den Bent
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Anouk van der Hoorn
- Medical Imaging Center, Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
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17
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van den Bent MJ, Geurts M, French PJ, Smits M, Capper D, Bromberg JEC, Chang SM. Primary brain tumours in adults. Lancet 2023; 402:1564-1579. [PMID: 37738997 DOI: 10.1016/s0140-6736(23)01054-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 05/06/2023] [Accepted: 05/16/2023] [Indexed: 09/24/2023]
Abstract
The most frequent adult-type primary CNS tumours are diffuse gliomas, but a large variety of rarer CNS tumour types exists. The classification of these tumours is increasingly based on molecular diagnostics, which is reflected in the extensive molecular foundation of the recent WHO 2021 classification of CNS tumours. Resection as extensive as is safely possible is the cornerstone of treatment in most gliomas, and is now also recommended early in the treatment of patients with radiological evidence of histologically low-grade tumours. For the adult-type diffuse glioma, standard of care is a combination of radiotherapy and chemotherapy. Although treatment with curative intent is not available, combined modality treatment has resulted in long-term survival (>10-20 years) for some patients with isocitrate dehydrogenase (IDH) mutant tumours. Other rarer tumours require tailored approaches, best delivered in specialised centres. Targeted treatments based on molecular alterations still only play a minor role in the treatment landscape of adult-type diffuse glioma, and today are mainly limited to patients with tumours with BRAFV600E (ie, Val600Glu) mutations. Immunotherapy for CNS tumours is still in its infancy, and so far, trials with checkpoint inhibitors and vaccination studies have not shown improvement in patient outcomes in glioblastoma. Current research is focused on improving our understanding of the immunosuppressive tumour environment, the molecular heterogeneity of tumours, and the role of tumour microtube network connections between cells in the tumour microenvironment. These factors all appear to play a role in treatment resistance, and indicate that novel approaches are needed to further improve outcomes of patients with CNS tumours.
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Affiliation(s)
- Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Netherlands.
| | - Marjolein Geurts
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Netherlands; Medical Delta, Delft, Netherlands
| | - David Capper
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium, Berlin, Germany; German Cancer Research Center, Heidelberg, Germany
| | - Jacoline E C Bromberg
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Netherlands
| | - Susan M Chang
- Brain Tumor Center, University of California San Francisco, San Francisco, CA, USA
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18
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van Dijken BRJ, Doff AR, Enting RH, van Laar PJ, Jeltema HR, Dierckx RAJO, van der Hoorn A. Influence of MRI Follow-Up on Treatment Decisions during Standard Concomitant and Adjuvant Chemotherapy in Patients with Glioblastoma: Is Less More? Cancers (Basel) 2023; 15:4973. [PMID: 37894340 PMCID: PMC10605145 DOI: 10.3390/cancers15204973] [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: 09/15/2023] [Revised: 10/03/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
MRI is the gold standard for treatment response assessments for glioblastoma. However, there is no consensus regarding the optimal interval for MRI follow-up during standard treatment. Moreover, a reliable assessment of treatment response is hindered by the occurrence of pseudoprogression. It is unknown if a radiological follow-up strategy at 2-3 month intervals actually benefits patients and how it influences clinical decision making about the continuation or discontinuation of treatment. This study assessed the consequences of scheduled follow-up scans post-chemoradiotherapy (post-CCRT), after three cycles of adjuvant chemotherapy [TMZ3/6], and after the completion of treatment [TMZ6/6]), and of unscheduled scans on treatment decisions during standard concomitant and adjuvant treatment in glioblastoma patients. Additionally, we evaluated how often follow-up scans resulted in diagnostic uncertainty (tumor progression versus pseudoprogression), and whether perfusion MRI improved clinical decision making. Scheduled follow-up scans during standard treatment in glioblastoma patients rarely resulted in an early termination of treatment (2.3% post-CCRT, 3.2% TMZ3/6, and 7.8% TMZ6/6), but introduced diagnostic uncertainty in 27.7% of cases. Unscheduled scans resulted in more major treatment consequences (30%; p < 0.001). Perfusion MRI caused less diagnostic uncertainty (p = 0.021) but did not influence treatment consequences (p = 0.871). This study does not support the current pragmatic follow-up strategy and suggests a more tailored follow-up approach.
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Affiliation(s)
- Bart R. J. van Dijken
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Annerieke R. Doff
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Roelien H. Enting
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands;
| | - Peter Jan van Laar
- Department of Radiology, Hospital Group Twente, 7600 SZ Almelo, The Netherlands
| | - Hanne-Rinck Jeltema
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands;
| | - Rudi A. J. O. Dierckx
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
- Department of Nuclear Medicine, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Anouk van der Hoorn
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
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Huang Q, Wu J, Le N, Shen Y, Guo P, Schreck KC, Kamson D, Blair L, Heo HY, Li X, Li W, Sair HL, Blakeley JO, Laterra J, Holdhoff M, Grossman SA, Mukherjee D, Bettegowda C, van Zijl P, Zhou J, Jiang S. CEST2022: Amide proton transfer-weighted MRI improves the diagnostic performance of multiparametric non-contrast-enhanced MRI techniques in patients with post-treatment high-grade gliomas. Magn Reson Imaging 2023; 102:222-228. [PMID: 37321378 PMCID: PMC10528251 DOI: 10.1016/j.mri.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
New or enlarged lesions in malignant gliomas after surgery and chemoradiation can be associated with tumor recurrence or treatment effect. Due to similar radiographic characteristics, conventional-and even some advanced MRI techniques-are limited in distinguishing these two pathologies. Amide proton transfer-weighted (APTw) MRI, a protein-based molecular imaging technique that does not require the administration of any exogenous contrast agent, was recently introduced into the clinical setting. In this study, we evaluated and compared the diagnostic performances of APTw MRI with several non-contrast-enhanced MRI sequences, such as diffusion-weighted imaging, susceptibility-weighted imaging, and pseudo-continuous arterial spin labeling. Thirty-nine scans from 28 glioma patients were obtained on a 3 T MRI scanner. A histogram analysis approach was employed to extract parameters from each tumor area. Statistically significant parameters (P < 0.05) were selected to train multivariate logistic regression models to evaluate the performance of MRI sequences. Multiple histogram parameters, particularly from APTw and pseudo-continuous arterial spin labeling images, demonstrated significant differences between treatment effect and recurrent tumor. The regression model trained on the combination of all significant histogram parameters achieved the best result (area under the curve = 0.89). We found that APTw images added value to other advanced MR images for the differentiation of treatment effect and tumor recurrence.
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Affiliation(s)
- Qianqi Huang
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jingpu Wu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nhat Le
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yiqing Shen
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Pengfei Guo
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Karisa C Schreck
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - David Kamson
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Lindsay Blair
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Hye-Young Heo
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Wenbo Li
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Haris L Sair
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jaishri O Blakeley
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - John Laterra
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Holdhoff
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Stuart A Grossman
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Debraj Mukherjee
- Department of Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Chetan Bettegowda
- Department of Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Peter van Zijl
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jinyuan Zhou
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Shanshan Jiang
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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20
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Hazari PP, Yadav SK, Kumar PK, Dhingra V, Rani N, Kumar R, Singh B, Mishra AK. Preclinical and Clinical Use of Indigenously Developed 99mTc-Diethylenetriaminepentaacetic Acid-Bis-Methionine: l-Type Amino Acid Transporter 1-Targeted Single Photon Emission Computed Tomography Radiotracer for Glioma Management. ACS Pharmacol Transl Sci 2023; 6:1233-1247. [PMID: 37705592 PMCID: PMC10496141 DOI: 10.1021/acsptsci.3c00091] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Indexed: 09/15/2023]
Abstract
A new era in tumor classification, diagnosis, and prognostic evaluation has begun as a consequence of recent developments in the molecular and genetic characterization of central nervous system tumors. In this newly emerging era, molecular imaging modalities are essential for preoperative diagnosis, surgical planning, targeted treatment, and post-therapy evaluation of gliomas. The radiotracers are able to identify brain tumors, distinguish between low- and high-grade lesions, confirm a patient's eligibility for theranostics, and assess post-radiation alterations. We previously synthesized and reported the novel l-type amino acid transporter 1 (LAT-1)-targeted amino acid derivative in light of the use of amino acid derivatives in imaging technologies. Further, we have developed a single vial ready to label Tc-lyophilized kit preparations of diethylenetriaminepentaacetic acid-bis-methionine [DTPA-bis(Met)], also referred to as methionine-diethylenetriaminepentaacetic acid-methionine (MDM) and evaluated its imaging potential in numerous clinical studies. This review summarizes our previous publications on 99mTc-DTPA-bis(Met) in different clinical studies such as detection of breast cancer, as a prognostic marker, in detection of recurrent/residual gliomas, for differentiation of recurrent/residual gliomas from radiation necrosis, and for comparison of 99mTc-DTPA-bis(Met) with 11C-L-methionine (11C-MET), with relevant literature on imaging modalities in glioma management.
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Affiliation(s)
- Puja Panwar Hazari
- Division
of Cyclotron and Radiopharmaceutical Sciences, Institute of Nuclear Medicine and Allied Sciences, DRDO, Delhi- 110054, India
| | - Shiv Kumar Yadav
- Division
of Cyclotron and Radiopharmaceutical Sciences, Institute of Nuclear Medicine and Allied Sciences, DRDO, Delhi- 110054, India
| | - Pardeep Kumar Kumar
- Department
of Neuroimaging and Interventional Radiology, National Institute of Mental Health & Neurosciences, Bangalore-560029, India
| | - Vandana Dhingra
- All
India Institute of Medical Sciences, Rishikesh-249203, India
| | - Nisha Rani
- Division
of Psychiatric Neuroimaging, Department of Psychiatry and Behavioral
Sciences, Johns Hopkins University School
of Medicine 600 N. Wolfe Street, Phipps 300, Baltimore, Maryland 21287, United States
| | - Rakesh Kumar
- All
India Institute of Medical Sciences, Delhi-110029, India
| | - Baljinder Singh
- Department
of Nuclear Medicine, Postgraduate Institute
of Medical Education and Research, Chandigarh-160012, India
| | - Anil K. Mishra
- Division
of Cyclotron and Radiopharmaceutical Sciences, Institute of Nuclear Medicine and Allied Sciences, DRDO, Delhi- 110054, India
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21
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Alizadeh M, Broomand Lomer N, Azami M, Khalafi M, Shobeiri P, Arab Bafrani M, Sotoudeh H. Radiomics: The New Promise for Differentiating Progression, Recurrence, Pseudoprogression, and Radionecrosis in Glioma and Glioblastoma Multiforme. Cancers (Basel) 2023; 15:4429. [PMID: 37760399 PMCID: PMC10526457 DOI: 10.3390/cancers15184429] [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: 07/11/2023] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
Glioma and glioblastoma multiform (GBM) remain among the most debilitating and life-threatening brain tumors. Despite advances in diagnosing approaches, patient follow-up after treatment (surgery and chemoradiation) is still challenging for differentiation between tumor progression/recurrence, pseudoprogression, and radionecrosis. Radiomics emerges as a promising tool in initial diagnosis, grading, and survival prediction in patients with glioma and can help differentiate these post-treatment scenarios. Preliminary published studies are promising about the role of radiomics in post-treatment glioma/GBM. However, this field faces significant challenges, including a lack of evidence-based solid data, scattering publication, heterogeneity of studies, and small sample sizes. The present review explores radiomics's capabilities in following patients with glioma/GBM status post-treatment and to differentiate tumor progression, recurrence, pseudoprogression, and radionecrosis.
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Affiliation(s)
- Mohammadreza Alizadeh
- Physiology Research Center, Iran University of Medical Sciences, Tehran 14496-14535, Iran;
| | - Nima Broomand Lomer
- Faculty of Medicine, Guilan University of Medical Sciences, Rasht 41937-13111, Iran;
| | - Mobin Azami
- Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj 66186-34683, Iran;
| | - Mohammad Khalafi
- Radiology Department, Tabriz University of Medical Sciences, Tabriz 51656-65931, Iran;
| | - Parnian Shobeiri
- School of Medicine, Tehran University of Medical Sciences, Tehran 14167-53955, Iran; (P.S.); (M.A.B.)
| | - Melika Arab Bafrani
- School of Medicine, Tehran University of Medical Sciences, Tehran 14167-53955, Iran; (P.S.); (M.A.B.)
| | - Houman Sotoudeh
- Department of Radiology and Neurology, Heersink School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL 35294, USA
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22
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Mantica M, Drappatz J, Lieberman F, Hadjipanayis CG, Lunsford LD, Niranjan A. Phase II study of border zone stereotactic radiosurgery with bevacizumab in patients with recurrent or progressive glioblastoma multiforme. J Neurooncol 2023; 164:179-190. [PMID: 37515669 DOI: 10.1007/s11060-023-04398-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 07/14/2023] [Indexed: 07/31/2023]
Abstract
PURPOSE Recurrent glioblastoma is universally fatal with limited effective treatment options. The aim of this phase 2 study of Border Zone SRS plus bevacizumab was to evaluate OS in patients with recurrent GBM. METHODS Patients with histologically confirmed GBM with recurrent disease who had received prior first-line treatment with fractionated radiotherapy and chemotherapy and eligible for SRS were enrolled. Bevacizumab 10 mg/kg was given day -1, day 14, and then every 14 days until disease progression. 1-14 days before BZ-SRS procedure, patients underwent brain MRI /MRS. MRS with measurement of choline-to-N-acetyl aspartate index (CNI) area ≥ 3 was targeted for SRS. RESULTS From 2015-2017, sixteen of planned 40 patients were enrolled. The median age was 62 (range, 48-74Y). 3/16 (0.188) participants experienced grade 2 toxicity. No AREs were reported. The mOS was 11.73 months compared to 8.74 months (P = 0.324) from date of SRS for the BZ-SRS and institutional historical controls, respectively. PFS-6 and OS-6 were 31.2% (p = 0.00294) and 81.2%(p = 0.058), respectively. Of 13 evaluable for best response: 1 CR (p = 0.077), 4 PR (p = 0.308), 7 SD (p = 0.538), and 1 PD (p = 0.077). 11/16 participants had MRS scans with an estimated probability that MRS changes a treatment plan of 0 (0, 0.285). CONCLUSION BZ-SRS with bevacizumab was feasible and well tolerated. There is no significant survival benefit using BZ-SRS with bevacizumab compared to institutional historical controls. Secondary analysis revealed a trend toward improved PFS-6, but not OS-6 after BZ-SRS. MRS scans did not result in changes to SRS treatment plans.
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Affiliation(s)
- Megan Mantica
- University of Pittsburgh Medical Center, 5150 Centre Avenue, Pittsburgh, PA, 15232, USA.
| | - Jan Drappatz
- University of Pittsburgh Medical Center, 5150 Centre Avenue, Pittsburgh, PA, 15232, USA
| | - Frank Lieberman
- University of Pittsburgh Medical Center, 5150 Centre Avenue, Pittsburgh, PA, 15232, USA
| | | | - L Dade Lunsford
- University of Pittsburgh Medical Center, 200 Lothrop Street, Pittsburgh, PA, 15213, USA
| | - Ajay Niranjan
- University of Pittsburgh Medical Center, 200 Lothrop Street, Pittsburgh, PA, 15213, USA
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23
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Mannam SS, Nwagwu CD, Sumner C, Weinberg BD, Hoang KB. Perfusion-Weighted Imaging: The Use of a Novel Perfusion Scoring Criteria to Improve the Assessment of Brain Tumor Recurrence versus Treatment Effects. Tomography 2023; 9:1062-1070. [PMID: 37368539 DOI: 10.3390/tomography9030087] [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: 04/20/2023] [Revised: 05/16/2023] [Accepted: 05/19/2023] [Indexed: 06/29/2023] Open
Abstract
INTRODUCTION Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)-among other advanced brain tumor imaging modalities-is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI. METHODS Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen's Kappa. RESULTS Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects. CONCLUSIONS With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.
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Affiliation(s)
- Sneha Sai Mannam
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chibueze D Nwagwu
- Department of Neurosurgery, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Christina Sumner
- Department of Radiology and Imaging Sciences, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Kimberly B Hoang
- Department of Neurosurgery, School of Medicine, Emory University, Atlanta, GA 30322, USA
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24
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Filippi L, Frantellizzi V, Vincentis GD, Schillaci O, Evangelista L. Clinical Applications of TSPO PET for Glioma Imaging: Current Evidence and Future Perspective-A Systematic Review. Diagnostics (Basel) 2023; 13:diagnostics13101813. [PMID: 37238297 DOI: 10.3390/diagnostics13101813] [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: 03/05/2023] [Revised: 05/17/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023] Open
Abstract
Our aim was to provide a comprehensive overview of the existing literature concerning the clinical applications of positron emission computed tomography (PET) with radiopharmaceuticals targeting the translocator protein (TSPO) in gliomas. A literature search for studies about TSPO PET in the last 10 years (from 2013 to February 2023) was carried out on PubMed, Scopus, and Web of Science using the following keywords: "PET" AND "Gliomas" AND "TSPO". The Critical Appraisal Skills Program checklist for diagnostic test studies was used for testing the quality of selected papers. Ten articles were selected, encompassing 314 glioma patients submitted to PET/CT (9/10) or PET/MRI (1/10) with TSPO ligands. Among the various available TSPO tracers, the most frequently used was the third-generation ligand, [18F]-GE-180. TSPO PET results were useful to identify anaplastic transformation in gliomas and for the prognostic stratification of patients bearing homogeneous genetic alterations. When compared to amino-acid PET, TSPO PET with [18F]-GE-180 presented superior image quality and provided larger and only partially overlapping PET-based volumes. Although biased by some issues (i.e., small sample size, most of the studies coming from the same country), preliminary applications of TSPO PET were encouraging. Further studies are needed to define implications in clinical practice and shape the role of TSPO PET for patients' selection for potential TSPO-targeted molecular therapies.
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Affiliation(s)
- Luca Filippi
- Nuclear Medicine Unit, "Santa Maria Goretti" Hospital, Via Antonio Canova, 04100 Latina, Italy
| | - Viviana Frantellizzi
- Department of Radiological Sciences, Oncology and Anatomo-Pathology, Sapienza, University of Rome, 00185 Rome, Italy
| | - Giuseppe De Vincentis
- Department of Radiological Sciences, Oncology and Anatomo-Pathology, Sapienza, University of Rome, 00185 Rome, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University Tor Vergata, Viale Oxford 81, 00133 Rome, Italy
| | - Laura Evangelista
- Nuclear Medicine Unit, Department of Medicine (DIMED), University of Padua, Via Giustiniani, 35128 Padua, Italy
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25
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Henssen D, Leijten L, Meijer FJA, van der Kolk A, Arens AIJ, Ter Laan M, Smeenk RJ, Gijtenbeek A, van de Giessen EM, Tolboom N, Oprea-Lager DE, Smits M, Nagarajah J. Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma. Cancers (Basel) 2023; 15:cancers15092631. [PMID: 37174097 PMCID: PMC10177124 DOI: 10.3390/cancers15092631] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/01/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-11C]methionine, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) and 6-[18F]-fluoro-3,4-dihydroxy-L-phenylalanine ([18F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Lars Leijten
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Anja van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Anne I J Arens
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mark Ter Laan
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurosurgery, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Robert J Smeenk
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anja Gijtenbeek
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Elsmarieke M van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Daniela E Oprea-Lager
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
- Brain Tumor Center, Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands
- Medical Delta, 2629 JH Delft, The Netherlands
| | - James Nagarajah
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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de Godoy LL, Mohan S, Wang S, Nasrallah MP, Sakai Y, O'Rourke DM, Bagley S, Desai A, Loevner LA, Poptani H, Chawla S. Validation of multiparametric MRI based prediction model in identification of pseudoprogression in glioblastomas. J Transl Med 2023; 21:287. [PMID: 37118754 PMCID: PMC10142504 DOI: 10.1186/s12967-023-03941-x] [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: 11/19/2022] [Accepted: 01/30/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND Accurate differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastomas (GBMs) is essential for appropriate clinical management and prognostication of these patients. In the present study, we sought to validate the findings of our previously developed multiparametric MRI model in a new cohort of GBM patients treated with standard therapy in identifying PsP cases. METHODS Fifty-six GBM patients demonstrating enhancing lesions within 6 months after completion of concurrent chemo-radiotherapy (CCRT) underwent anatomical imaging, diffusion and perfusion MRI on a 3 T magnet. Subsequently, patients were classified as TP + mixed tumor (n = 37) and PsP (n = 19). When tumor specimens were available from repeat surgery, histopathologic findings were used to identify TP + mixed tumor (> 25% malignant features; n = 34) or PsP (< 25% malignant features; n = 16). In case of non-availability of tumor specimens, ≥ 2 consecutive conventional MRIs using mRANO criteria were used to determine TP + mixed tumor (n = 3) or PsP (n = 3). The multiparametric MRI-based prediction model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI derived parameters from contrast enhancing regions. In the next step, PP values were used to characterize each lesion as PsP or TP+ mixed tumor. The lesions were considered as PsP if the PP value was < 50% and TP+ mixed tumor if the PP value was ≥ 50%. Pearson test was used to determine the concordance correlation coefficient between PP values and histopathology/mRANO criteria. The area under ROC curve (AUC) was used as a quantitative measure for assessing the discriminatory accuracy of the prediction model in identifying PsP and TP+ mixed tumor. RESULTS Multiparametric MRI model correctly predicted PsP in 95% (18/19) and TP+ mixed tumor in 57% of cases (21/37) with an overall concordance rate of 70% (39/56) with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.56; p < 0.001). The ROC analyses revealed an accuracy of 75.7% in distinguishing PsP from TP+ mixed tumor. Leave-one-out cross-validation test revealed that 73.2% of cases were correctly classified as PsP and TP + mixed tumor. CONCLUSIONS Our multiparametric MRI based prediction model may be helpful in identifying PsP in GBM patients.
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Affiliation(s)
- Laiz Laura de Godoy
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - MacLean P Nasrallah
- Clinical Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Yu Sakai
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen Bagley
- Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arati Desai
- Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Laurie A Loevner
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Harish Poptani
- Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Sanjeev Chawla
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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Qi D, Li J, Quarles CC, Fonkem E, Wu E. Assessment and prediction of glioblastoma therapy response: challenges and opportunities. Brain 2023; 146:1281-1298. [PMID: 36445396 PMCID: PMC10319779 DOI: 10.1093/brain/awac450] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/03/2022] [Accepted: 11/10/2022] [Indexed: 11/30/2022] Open
Abstract
Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.
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Affiliation(s)
- Dan Qi
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
| | - Jing Li
- School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - C Chad Quarles
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Ekokobe Fonkem
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
| | - Erxi Wu
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX 77843, USA
- Department of Oncology and LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
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Aseel A, McCarthy P, Mohammed A. Brain magnetic resonance spectroscopy to differentiate recurrent neoplasm from radiation necrosis: A systematic review and meta-analysis. J Neuroimaging 2023; 33:189-201. [PMID: 36631883 DOI: 10.1111/jon.13080] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 12/21/2022] [Accepted: 12/21/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND AND PURPOSE Postradiation treatment necrosis is one of the most serious late sequelae and appears within 6 months. The magnetic resonance spectroscopy imaging (MRSI) has been used for the detection of brain tumors. The study aimed to determine the radiological accuracy and efficacy in distinguishing recurrent brain tumor from radiation-induced necrosis by identifying pseudoprogression. METHODS The research was performed in accordance with the preferred reporting items for systematic review and meta-analysis guidelines. International electronic databases including 15 English sources were investigated. A total of 4281 papers with 2159 citations from 15 databases from 2011 to 2021 met the search strategies of magnetic resonance (MR) spectroscopy in recurrent brain tumors and postradiation necrosis. RESULTS Nine studies were enrolled in the meta-analysis with a total of 354 patients (203 male and 151 female) whose average age ranged from 4 to 74 years. Anbarloui et al., Elias et al., Nemattalla et al., Smith et al., Zeng et al., and Weybright et al. showed strong evidence of heterogeneity regarding choline/N-acetylaspartate (Cho/NAA) ratio in the evaluation of the nine studies. Elias et al., Nemattalla et al., Bobek-Billewicz et al., and Smith et al. showed a high heterogeneity in Cho/creatine (Cr) ratio. Elias et al., Nemattalla et al., Smith et al., and Weybright et al. revealed high heterogeneity in NAA/Cr ratio estimates. CONCLUSION MR spectroscopy is effective in distinguishing recurrent brain tumors from necrosis. Our meta-analysis revealed that Cho/NAA, Cho/Cr, and NAA/Cr ratios were significantly better predictor of detected recurrent tumor. Therefore, the MRSI is an informative tool in the distinction of tumor recurrence versus necrosis.
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Affiliation(s)
- Almusaedi Aseel
- School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Galway, Ireland
| | - Peter McCarthy
- School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Galway, Ireland
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Smith EJ, Naik A, Shaffer A, Goel M, Krist DT, Liang E, Furey CG, Miller WK, Lawton MT, Barnett DH, Weis B, Rizk A, Smith RS, Hassaneen W. Differentiating radiation necrosis from tumor recurrence: a systematic review and diagnostic meta-analysis comparing imaging modalities. J Neurooncol 2023; 162:15-23. [PMID: 36853489 DOI: 10.1007/s11060-023-04262-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/07/2023] [Indexed: 03/01/2023]
Abstract
PURPSOSE Cerebral radiation necrosis (RN) is often a delayed phenomenon occurring several months to years after the completion of radiation treatment. Differentiating RN from tumor recurrence presents a diagnostic challenge on standard MRI. To date, no evidence-based guidelines exist regarding imaging modalities best suited for this purpose. We aim to review the current literature and perform a diagnostic meta-analysis comparing various imaging modalities that have been studied to differentiate tumor recurrence and RN. METHODS A systematic search adherent to PRISMA guidelines was performed using Scopus, PubMed/MEDLINE, and Embase. Pooled sensitivities and specificities were determined using a random-effects or fixed-effects proportional meta-analysis based on heterogeneity. Using diagnostic odds ratios, a diagnostic frequentist random-effects network meta-analysis was performed, and studies were ranked using P-score hierarchical ranking. RESULTS The analysis included 127 studies with a total of 220 imaging datasets, including the following imaging modalities: MRI (n = 10), MR Spectroscopy (MRS) (n = 28), dynamic contrast-enhanced MRI (n = 7), dynamic susceptibility contrast MRI (n = 36), MR arterial spin labeling (n = 5), diffusion-weighted imaging (n = 13), diffusion tensor imaging (DTI) (n = 2), PET (n = 89), and single photon emission computed tomography (SPECT) (n = 30). MRS had the highest pooled sensitivity (90.7%). DTI had the highest pooled specificity (90.5%). Our hierarchical ranking ranked SPECT and MRS as most preferable, and MRI was ranked as least preferable. CONCLUSION These findings suggest SPECT and MRS carry greater utility than standard MRI in distinguishing RN from tumor recurrence.
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Affiliation(s)
| | - Anant Naik
- Carle Illinois College of Medicine, Urbana, IL, USA
| | | | - Mahima Goel
- Carle Illinois College of Medicine, Urbana, IL, USA
| | | | - Edward Liang
- Carle Illinois College of Medicine, Urbana, IL, USA
| | - Charuta G Furey
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ, USA
| | - William K Miller
- Department of Neurosurgery, University of Illinois Peoria, Peoria, IL, USA
| | - Michael T Lawton
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Daniel H Barnett
- Department of Radiation Oncology, Carle Foundation Hospital, Urbana, IL, USA
| | - Blake Weis
- Department of Radiology, Carle Foundation Hospital, Urbana, IL, USA
| | - Ahmed Rizk
- Department of Neurosurgery, Hospital of the Merciful Brothers, Trier, Germany
| | - Ron S Smith
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Wael Hassaneen
- Department of Neurosurgery, Carle Foundation Hospital, 610 N Lincoln Ave, Urbana, IL, 61801, USA.
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Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response. Int J Mol Sci 2023; 24:ijms24043151. [PMID: 36834563 PMCID: PMC9959624 DOI: 10.3390/ijms24043151] [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: 01/07/2023] [Revised: 01/29/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.
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Nguyen TB, Zakhari N, Velasco Sandoval S, Guarnizo-Capera A, Alexios Gulak M, Woulfe J, Jansen G, Thornhill R, Majtenyi N, Cron GO. Diagnostic Accuracy of Arterial Spin-Labeling, Dynamic Contrast-Enhanced, and DSC Perfusion Imaging in the Diagnosis of Recurrent High-Grade Gliomas: A Prospective Study. AJNR Am J Neuroradiol 2023; 44:134-142. [PMID: 36702501 PMCID: PMC9891339 DOI: 10.3174/ajnr.a7771] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 12/30/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE For patients with high-grade gliomas, the appearance of a new, enhancing lesion after surgery and chemoradiation represents a diagnostic dilemma. We hypothesized that MR perfusion without and with contrast can differentiate tumor recurrence from radiation necrosis. MATERIALS AND METHODS In this prospective study, we performed 3 MR perfusion methods: arterial spin-labeling, DSC, and dynamic contrast enhancement. For each lesion, we measured CBF from arterial spin-labeling, uncorrected relative CBV, and leakage-corrected relative CBV from DSC imaging. The volume transfer constant and plasma volume were obtained from dynamic contrast-enhanced imaging without and with T1 mapping using modified Look-Locker inversion recovery (MOLLI). The diagnosis of tumor recurrence or radiation necrosis was determined by either histopathology for patients who underwent re-resection or radiologic follow-up for patients who did not have re-resection. RESULTS There were 26 patients with 32 lesions, 19 lesions with tumor recurrence and 13 lesions with radiation necrosis. Compared with radiation necrosis, lesions with tumor recurrence had higher CBF (P = .033), leakage-corrected relative CBV (P = .048), and plasma volume using MOLLI T1 mapping (P = .012). For differentiating tumor recurrence from radiation necrosis, the areas under the curve were 0.81 for CBF, 0.80 for plasma volume using MOLLI T1 mapping, and 0.71 for leakage-corrected relative CBV. A correlation was found between CBF and leakage-corrected relative CBV (r s = 0.54), volume transfer constant, and plasma volume (0.50 < r s< 0.77) but not with uncorrected relative CBV (r s = 0.20, P = .29). CONCLUSIONS In the differentiation of tumor recurrence from radiation necrosis in a newly enhancing lesion, the diagnostic value of arterial spin-labeling-derived CBF is similar to that of DSC and dynamic contrast-enhancement-derived blood volume.
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Affiliation(s)
- T B Nguyen
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - N Zakhari
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - S Velasco Sandoval
- Division of Neuroradiology (S.V.S., A.G.-C.), Department of Radiology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, D.C., Colombia
| | - A Guarnizo-Capera
- Division of Neuroradiology (S.V.S., A.G.-C.), Department of Radiology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, D.C., Colombia
| | - M Alexios Gulak
- Department of Anesthesiology and Pain Medicine (M.A.G.), University of Toronto, Toronto, Ontario, Canada
| | - J Woulfe
- Department of Pathology and Laboratory Medicine (J.W., G.J.), The Ottawa Hospital, Ottawa, Ontario, Canada
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - G Jansen
- Department of Pathology and Laboratory Medicine (J.W., G.J.), The Ottawa Hospital, Ottawa, Ontario, Canada
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - R Thornhill
- From the Department of Radiology (T.B.N., N.Z., R.T.), Radiation Oncology and Medical Physics
- University of Ottawa (T.B.N., N.Z., J.W., G.J., R.T.), Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute (T.B.N., J.W., G.J., R.T.), Ottawa, Ontario, Canada
| | - N Majtenyi
- Department of Medical Physics (N.M.), Grand River Regional Cancer Centre, Kitchener, Ontario, Canada
| | - G O Cron
- Stanford University (G.O.C.), Stanford, California
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Sidibe I, Tensaouti F, Gilhodes J, Cabarrou B, Filleron T, Desmoulin F, Ken S, Noël G, Truc G, Sunyach MP, Charissoux M, Magné N, Lotterie JA, Roques M, Péran P, Cohen-Jonathan Moyal E, Laprie A. Pseudoprogression in GBM versus true progression in patients with glioblastoma: A multiapproach analysis. Radiother Oncol 2023; 181:109486. [PMID: 36706959 DOI: 10.1016/j.radonc.2023.109486] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE To investigate the feasibility of using a multiapproach analysis combining clinical data, diffusion- and perfusion-weighted imaging, and 3D magnetic resonance spectroscopic imaging to distinguish true tumor progression (TP) from pseudoprogression (PSP) in patients with glioblastoma. MATERIALS AND METHODS Progression was suspected within 6 months of radiotherapy in 46 of the 180 patients included in the Phase-III SpectroGlio trial (NCT01507506). Choline/creatine (Cho/Cr), choline/N-acetyl aspartate (Cho/NAA) and lactate/N-acetyl aspartate (Lac/NAA) ratios were extracted. Apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were calculated. ADC, relative CBV values and tumor volume (TV) were collected at relapse. Differences between TP and PSP were evaluated using Mann-Whitney tests, and p values were adjusted with Bonferroni correction. RESULTS Patients with suspected progression underwent a new MRI scan 1 month after the first one. Of these, 28 were classified as PSP, and 18 as TP. After a median follow-up of 41 months, median overall survival was higher in PSP than in TP (25.2 vs 20.3 months; p = 0.0092). Lac/NAA and Cho/Cr ratios were higher in TP than in PSP (1.2 vs 0.5; p = 0.006; and 3 vs 2.2; p = 0.021). After multivariate regression analysis, TV was the most significant predictor of TP vs PSP, and the only one retained in the model (p = 0.028). CONCLUSION Three spectroscopic ratios could be used to differentiate PSP from TP. TV at relapse was the most predictive factor in the multivariate analysis, and overall survival was higher in PSP than in TP.
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Affiliation(s)
- Ingrid Sidibe
- Radiation Oncology Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France; Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Fatima Tensaouti
- Radiation Oncology Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France; Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Julia Gilhodes
- Biostatistics Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France
| | - Bastien Cabarrou
- Biostatistics Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France
| | - Thomas Filleron
- Biostatistics Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France
| | - Franck Desmoulin
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Soleakhena Ken
- Radiation Oncology Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France; Radiation Oncology Department, Toulouse Center for Cancer Research & INSERM, Toulouse, France
| | - Georges Noël
- Radiation Oncology Department, ICANS, Strasbourg, France
| | - Gilles Truc
- Radiation Oncology Department, Georges-François Leclerc Center, Dijon, France
| | | | | | - Nicolas Magné
- Radiation Oncology Department, Lucien Neuwirth Loire Cancer Institute, Saint-Priest-en-Jarez, France
| | - Jean-Albert Lotterie
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Margaux Roques
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Patrice Péran
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- Radiation Oncology Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France; Radiation Oncology Department, Toulouse Center for Cancer Research & INSERM, Toulouse, France
| | - Anne Laprie
- Radiation Oncology Department, Claudius Regaud Institute/Toulouse University Cancer Institute - Oncopôle, Toulouse, France; Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier & INSERM, Toulouse, France.
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Alsulami TA, Hyare H, Thomas DL, Golay X. The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis. Neurooncol Adv 2023; 5:vdad122. [PMID: 37841694 PMCID: PMC10576519 DOI: 10.1093/noajnl/vdad122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023] Open
Abstract
Background The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects. Methods Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed. Results This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95]. Conclusion These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.
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Affiliation(s)
- Tamadur A Alsulami
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia
| | - Harpreet Hyare
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK
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McKenney AS, Weg E, Bale TA, Wild AT, Um H, Fox MJ, Lin A, Yang JT, Yao P, Birger ML, Tixier F, Sellitti M, Moss NS, Young RJ, Veeraraghavan H. Radiomic Analysis to Predict Histopathologically Confirmed Pseudoprogression in Glioblastoma Patients. Adv Radiat Oncol 2023; 8:100916. [PMID: 36711062 PMCID: PMC9873493 DOI: 10.1016/j.adro.2022.100916] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/18/2022] [Indexed: 02/01/2023] Open
Abstract
Purpose Pseudoprogression mimicking recurrent glioblastoma remains a diagnostic challenge that may adversely confound or delay appropriate treatment or clinical trial enrollment. We sought to build a radiomic classifier to predict pseudoprogression in patients with primary isocitrate dehydrogenase wild type glioblastoma. Methods and Materials We retrospectively examined a training cohort of 74 patients with isocitrate dehydrogenase wild type glioblastomas with brain magnetic resonance imaging including dynamic contrast enhanced T1 perfusion before resection of an enhancing lesion indeterminate for recurrent tumor or pseudoprogression. A recursive feature elimination random forest classifier was built using nested cross-validation without and with O6-methylguanine-DNA methyltransferase status to predict pseudoprogression. Results A classifier constructed with cross-validation on the training cohort achieved an area under the receiver operating curve of 81% for predicting pseudoprogression. This was further improved to 89% with the addition of O6-methylguanine-DNA methyltransferase status into the classifier. Conclusions Our results suggest that radiomic analysis of contrast T1-weighted images and magnetic resonance imaging perfusion images can assist the prompt diagnosis of pseudoprogression. Validation on external and independent data sets is necessary to verify these advanced analyses, which can be performed on routinely acquired clinical images and may help inform clinical treatment decisions.
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Affiliation(s)
- Anna Sophia McKenney
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology, New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York
| | - Emily Weg
- Department of Radiation Oncology, University of Washington, Seattle, Washington
| | - Tejus A. Bale
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Aaron T. Wild
- Department Southeast Radiation Oncology, Levine Cancer Institute, Charlotte, North Carolina
| | - Hyemin Um
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael J. Fox
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrew Lin
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jonathan T. Yang
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Peter Yao
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Maxwell L. Birger
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Florent Tixier
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matthew Sellitti
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Nelson S. Moss
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Robert J. Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology, New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, New York
- Corresponding author: Robert J. Young, MD
| | - Harini Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
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Singnurkar A, Poon R, Detsky J. 18F-FET-PET imaging in high-grade gliomas and brain metastases: a systematic review and meta-analysis. J Neurooncol 2023; 161:1-12. [PMID: 36502457 DOI: 10.1007/s11060-022-04201-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022]
Abstract
PURPOSE To provide a summary of the diagnostic performance of 18F-FET-PET in the management of patients with high-grade brain gliomas or metastases from extracranial primary malignancies. METHODS MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews databases were searched for studies that reported on diagnostic test parameters in radiotherapy planning, response assessment, and tumour recurrence/treatment-related changes differentiation. Radiomic studies were excluded. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool and the GRADE approach. A bivariate, random-effects model was used to produce summary estimates of sensitivity and specificity. RESULTS Twenty-six studies with a total of 1206 patients/lesions were included in the analysis. For radiotherapy planning of glioma, the pooled proportion of patients from 3 studies with 18F-FET uptake extending beyond the 20 mm margin from the gadolinium enhancement on standard MRI was 39% (95% CI, 10-73%). In 3 studies, 18F-FET-PET was also shown to be predictive of early responders to treatment, whereas MRI failed to show any prognostic value. For the differentiation of glioma recurrence from treatment-related changes, the pooled sensitivity and specificity of TBRmax 1.9-2.3 from 6 studies were 91% (95% CI, 74-97%) and 84% (95% CI, 69-93%), respectively. The respective values for brain metastases from 4 studies were 82% (95% CI, 74-88%) and 82% (95% CI, 74-88%) using TBRmax 2.15-3.11. CONCLUSION While 18F-FET shows promise as a complementary modality to standard-of-care MRI for the management of primary and metastatic brain malignancies, further validation with standardized image interpretation methods in well-designed prospective studies are warranted.
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Affiliation(s)
- Amit Singnurkar
- Department of Medical Imaging, University of Toronto Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Raymond Poon
- Program in Evidence-Based Care, Ontario Health (Cancer Care Ontario), Department of Oncology, McMaster University McMaster University, Hamilton, ON, Canada. .,Program in Evidence-Based Care, Ontario Health (Cancer Care Ontario), Juravinski Hospital and Cancer Centre, G Wing, 2nd Floor, 711 Concession Street, Hamilton, ON, L8V 1C3, Canada.
| | - Jay Detsky
- Department of Radiation Oncology, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada
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Henssen D, Meijer F, Verburg FA, Smits M. Challenges and opportunities for advanced neuroimaging of glioblastoma. Br J Radiol 2023; 96:20211232. [PMID: 36062962 PMCID: PMC10997013 DOI: 10.1259/bjr.20211232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 08/10/2022] [Accepted: 08/25/2022] [Indexed: 11/05/2022] Open
Abstract
Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederik A. Verburg
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
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Jiang S, Guo P, Heo HY, Zhang Y, Wu J, Jin Y, Laterra J, Eberhart CG, Lim M, Blakeley JO. Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas. NMR IN BIOMEDICINE 2023; 36:e4824. [PMID: 36057449 PMCID: PMC10502874 DOI: 10.1002/nbm.4824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/25/2022] [Accepted: 08/28/2022] [Indexed: 06/15/2023]
Abstract
The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T1 w, T2 w, FLAIR, and Gd-T1 w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T1 w, T2 w, FLAIR, Gd-T1 w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.
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Affiliation(s)
- Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Pengfei Guo
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yi Zhang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jingpu Wu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuecen Jin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - John Laterra
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
- Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | | | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Neurosurgery, Stanford University, Palo Alto, California, USA
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Muthukumar S, Darden J, Crowley J, Witcher M, Kiser J. A Comparison of PET Tracers in Recurrent High-Grade Gliomas: A Systematic Review. Int J Mol Sci 2022; 24:ijms24010408. [PMID: 36613852 PMCID: PMC9820099 DOI: 10.3390/ijms24010408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 12/28/2022] Open
Abstract
Humans with high-grade gliomas have a poor prognosis, with a mean survival time of just 12-18 months for patients who undergo standard-of-care tumor resection and adjuvant therapy. Currently, surgery and chemoradiotherapy serve as standard treatments for this condition, yet these can be complicated by the tumor location, growth rate and recurrence. Currently, gadolinium-based, contrast-enhanced magnetic resonance imaging (CE-MRI) serves as the predominant imaging modality for recurrent high-grade gliomas, but it faces several drawbacks, including its inability to distinguish tumor recurrence from treatment-related changes and its failure to reveal the entirety of tumor burden (de novo or recurrent) due to limitations inherent to gadolinium contrast. As such, alternative imaging modalities that can address these limitations, including positron emission tomography (PET), are worth pursuing. To this end, the identification of PET-based markers for use in imaging of recurrent high-grade gliomas is paramount. This review will highlight several PET radiotracers that have been implemented in clinical practice and provide a comparison between them to assess the efficacy of these tracers.
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Affiliation(s)
| | - Jordan Darden
- Carilion Clinic Neurosurgery, Roanoke, VA 24016, USA
| | | | - Mark Witcher
- Carilion Clinic Neurosurgery, Roanoke, VA 24016, USA
| | - Jackson Kiser
- Carilion Clinic Radiology, Roanoke, VA 24016, USA
- Correspondence:
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Teunissen WHT, Govaerts CW, Kramer MCA, Labrecque JA, Smits M, Dirven L, van der Hoorn A. Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis. Radiother Oncol 2022; 177:121-133. [PMID: 36377093 DOI: 10.1016/j.radonc.2022.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 10/11/2022] [Accepted: 10/21/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response. METHODS A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy. RESULTS Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis. CONCLUSION A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.
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Affiliation(s)
- Wouter H T Teunissen
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Chris W Govaerts
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands
| | - Miranda C A Kramer
- University Medical Center Groningen, department of Radiotherapy, Groningen, the Netherlands
| | - Jeremy A Labrecque
- Erasmus MC, Netherlands Institute for Health Science (NIHES), Rotterdam, the Netherlands
| | - Marion Smits
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Linda Dirven
- Leiden University Medical Center, department of Neurology, Leiden, the Netherlands; Haaglanden Medical Center, department of Neurology, The Hague, the Netherlands
| | - Anouk van der Hoorn
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands.
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Hesse F, Wright AJ, Somai V, Bulat F, Kreis F, Brindle KM. Imaging Glioblastoma Response to Radiotherapy Using 2H Magnetic Resonance Spectroscopy Measurements of Fumarate Metabolism. Cancer Res 2022; 82:3622-3633. [PMID: 35972377 PMCID: PMC9530651 DOI: 10.1158/0008-5472.can-22-0101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/25/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022]
Abstract
Early detection of tumor cell death in glioblastoma following treatment with chemoradiation has the potential to distinguish between true disease progression and pseudoprogression. Tumor cell death can be detected noninvasively in vivo by imaging the production of [2,3-2H2]malate from [2,3-2H2]fumarate using 2H magnetic resonance (MR) spectroscopic imaging. We show here that 2H MR spectroscopy and spectroscopic imaging measurements of [2,3-2H2]fumarate metabolism can detect tumor cell death in orthotopically implanted glioblastoma models within 48 hours following the completion of chemoradiation. Following the injection of [2,3-2H2]fumarate into tumor-bearing mice, production of [2,3-2H2]malate was measured in a human cell line-derived model and in radiosensitive and radioresistant patient-derived models of glioblastoma that were treated with temozolomide followed by targeted fractionated irradiation. The increase in the [2,3-2H2]malate/[2,3-2H2]fumarate signal ratio posttreatment, which correlated with histologic assessment of cell death, was a more sensitive indicator of treatment response than diffusion-weighted and contrast agent-enhanced 1H MRI measurements, which have been used clinically to detect responses of glioblastoma to chemoradiation. Overall, early detection of glioblastoma cell death using 2H MRI of malate production from fumarate could help improve the clinical evaluation of response to chemoradiation. SIGNIFICANCE 2H magnetic resonance imaging of labeled fumarate metabolism can detect early evidence of tumor cell death following chemoradiation, meeting a clinical need to reliably detect treatment response in glioblastoma.
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Affiliation(s)
- Friederike Hesse
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Alan J. Wright
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Vencel Somai
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, School of Clinical Medicine, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Flaviu Bulat
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Felix Kreis
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Kevin M. Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
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McCarthy L, Verma G, Hangel G, Neal A, Moffat BA, Stockmann JP, Andronesi OC, Balchandani P, Hadjipanayis CG. Application of 7T MRS to High-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:1378-1395. [PMID: 35618424 PMCID: PMC9575545 DOI: 10.3174/ajnr.a7502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/11/2022] [Indexed: 01/26/2023]
Abstract
MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.
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Affiliation(s)
- L McCarthy
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
| | - G Verma
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - G Hangel
- Department of Neurosurgery (G.H.)
- High-field MR Center (G.H.), Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - A Neal
- Department of Medicine (A.N.), Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
- Department of Neurology (A.N.), Royal Melbourne Hospital, Melbourne, Australia
| | - B A Moffat
- The Melbourne Brain Centre Imaging Unit (B.A.M.), Department of Radiology, The University of Melbourne, Melbourne, Australia
| | - J P Stockmann
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - O C Andronesi
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - P Balchandani
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - C G Hadjipanayis
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
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Magnetic Resonance Neuroimaging Contrast Agents of Nanomaterials. BIOMED RESEARCH INTERNATIONAL 2022; 2022:6790665. [PMID: 36082155 PMCID: PMC9448598 DOI: 10.1155/2022/6790665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/25/2022] [Accepted: 08/03/2022] [Indexed: 11/17/2022]
Abstract
Since the early 1980s when MRI imaging technology was put into clinical use, the number of MRI clinical tests has steadily increased by more than 10% every year. At the same time, exogenous MRI contrast agents have also been developed with the development of MRI technology. However, there are still challenges in the preparation of contrast agents for magnetic resonance imaging, such as how to prepare high-efficiency contrast agents with high stability and low biological toxicity. In order to study the contrast agent with simple preparation method, low cost, and good imaging effect, a magnetic resonance contrast agent was prepared by magnetic nanoparticles. By acting on magnetic resonance imaging detection method, and using polymer ligands to synthesize magnetic nanoparticles, experiments and tests of P(MA-alt-VAc) polymer ligand-modified magnetic nanoparticles were carried out. The experimental results showed that when nanoparticles containing different iron ion concentrations were incubated with DC 2.4 normal cells for 48 hours, the cell viability was still higher than 80% at concentrations up to 200 μm. It shows that the nanoparticle has high cell activity and good biological adaptability. The transverse relaxation (r2) value of the nanoparticles in aqueous solution at 37°C and 1.5 T magnetic field is 231.1 m−1 s−1, which is much higher than that of PTMP-PMAA (r2 = 35.1 mM−1 s−1), which is also more than five times the relaxation of SHU-555C (r2 = 44 mM−1 s−1). It shows that the nanoparticles prepared in this paper have good effect and can be used as a contrast agent in human brain for magnetic resonance imaging.
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DEGRO practical guideline for central nervous system radiation necrosis part 1: classification and a multistep approach for diagnosis. Strahlenther Onkol 2022; 198:873-883. [PMID: 36038669 PMCID: PMC9515024 DOI: 10.1007/s00066-022-01994-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/19/2022] [Indexed: 10/31/2022]
Abstract
PURPOSE The Working Group for Neuro-Oncology of the German Society for Radiation Oncology in cooperation with members of the Neuro-Oncology Working Group of the German Cancer Society aimed to define a practical guideline for the diagnosis and treatment of radiation-induced necrosis (RN) of the central nervous system (CNS). METHODS Panel members of the DEGRO working group invited experts, participated in a series of conferences, supplemented their clinical experience, performed a literature review, and formulated recommendations for medical treatment of RN including bevacizumab in clinical routine. CONCLUSION Diagnosis and treatment of RN requires multidisciplinary structures of care and defined processes. Diagnosis has to be made on an interdisciplinary level with the joint knowledge of a neuroradiologist, radiation oncologist, neurosurgeon, neuropathologist, and neuro-oncologist. A multistep approach as an opportunity to review as many characteristics as possible to improve diagnostic confidence is recommended. Additional information about radiotherapy (RT) techniques is crucial for the diagnosis of RN. Misdiagnosis of untreated and progressive RN can lead to severe neurological deficits. In this practice guideline, we propose a detailed nomenclature of treatment-related changes and a multistep approach for their diagnosis.
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Qin D, Yang G, Jing H, Tan Y, Zhao B, Zhang H. Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma. Cancers (Basel) 2022; 14:cancers14153771. [PMID: 35954435 PMCID: PMC9367286 DOI: 10.3390/cancers14153771] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/25/2022] [Accepted: 07/27/2022] [Indexed: 12/30/2022] Open
Abstract
Simple Summary Glioma is the most common primary malignant tumor of the adult central nervous system. Despite aggressive multimodal treatment, its prognosis remains poor. During follow-up, it remains challenging to distinguish treatment-related changes from tumor progression in treated patients with gliomas due to both share clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions). The early effective identification of tumor progression and treatment-related changes is of great significance for the prognosis and treatment of gliomas. We believe that advanced neuroimaging techniques can provide additional information for distinguishing both at an early stage. In this article, we focus on the research of magnetic resonance imaging technology and artificial intelligence in tumor progression and treatment-related changes. Finally, it provides new ideas and insights for clinical diagnosis. Abstract As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.
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Affiliation(s)
- Danlei Qin
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
| | - Guoqiang Yang
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Hui Jing
- Department of MRI, The Six Hospital, Shanxi Medical University, Taiyuan 030008, China;
| | - Yan Tan
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Bin Zhao
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
| | - Hui Zhang
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
- Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
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Chen K, Jiang XW, Deng LJ, She HL. Differentiation between glioma recurrence and treatment effects using amide proton transfer imaging: A mini-Bayesian bivariate meta-analysis. Front Oncol 2022; 12:852076. [PMID: 35978813 PMCID: PMC9376615 DOI: 10.3389/fonc.2022.852076] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 06/29/2022] [Indexed: 11/24/2022] Open
Abstract
Background Amide proton transfer (APT) imaging as an emerging MRI approach has been used for distinguishing tumor recurrence (TR) and treatment effects (TEs) in glioma patients, but the initial results from recent studies are different. Aim The aim of this study is to systematically review and quantify the diagnostic performance of APT in assessing treatment response in patients with post-treatment gliomas. Methods A systematic search in PubMed, EMBASE, and the Web of Science was performed to retrieve related original studies. For the single and added value of APT imaging in distinguishing TR from TEs, we calculated pooled sensitivity and specificity by using Bayesian bivariate meta-analyses. Results Six studies were included, five of which reported on single APT imaging parameters and four of which reported on multiparametric MRI combined with APT imaging parameters. For single APT imaging parameters, the pooled sensitivity and specificity were 0.85 (95% CI: 0.75–0.92) and 0.88 (95% CI: 0.74–0.97). For multiparametric MRI including APT, the pooled sensitivity and specificity were 0.92 (95% CI: 0.85–0.97) and 0.83 (95% CI: 0.55–0.97), respectively. In addition, in the three studies reported on both single and added value of APT imaging parameters, the combined imaging parameters further improved diagnostic performance, yielding pooled sensitivity and specificity of 0.91 (95% CI: 0.80–0.97) and 0.92 (95% CI: 0.79–0.98), respectively, but the pooled sensitivity was 0.81 (95% CI: 0.65-0.93) and specificity was 0.82 (95% CI: 0.61–0.94) for single APT imaging parameters. Conclusion APT imaging showed high diagnostic performance in assessing treatment response in patients with post-treatment gliomas, and the addition of APT imaging to other advanced MRI techniques can improve the diagnostic accuracy for distinguishing TR from TE.
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Affiliation(s)
- Kai Chen
- Department of Medical Imaging, Shenzhen Samii Medical Center, Shenzhen, China
| | - Xi-Wen Jiang
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
| | - Li-jing Deng
- Department of Neonatology, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Hua-Long She
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
- *Correspondence: Hua-Long She,
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Hormuth DA, Farhat M, Christenson C, Curl B, Chad Quarles C, Chung C, Yankeelov TE. Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy. Adv Drug Deliv Rev 2022; 187:114367. [PMID: 35654212 PMCID: PMC11165420 DOI: 10.1016/j.addr.2022.114367] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/25/2022] [Accepted: 05/25/2022] [Indexed: 11/01/2022]
Abstract
Immunotherapy has become a fourth pillar in the treatment of brain tumors and, when combined with radiation therapy, may improve patient outcomes and reduce the neurotoxicity. As with other combination therapies, the identification of a treatment schedule that maximizes the synergistic effect of radiation- and immune-therapy is a fundamental challenge. Mechanism-based mathematical modeling is one promising approach to systematically investigate therapeutic combinations to maximize positive outcomes within a rigorous framework. However, successful clinical translation of model-generated combinations of treatment requires patient-specific data to allow the models to be meaningfully initialized and parameterized. Quantitative imaging techniques have emerged as a promising source of high quality, spatially and temporally resolved data for the development and validation of mathematical models. In this review, we will present approaches to personalize mechanism-based modeling frameworks with patient data, and then discuss how these techniques could be leveraged to improve brain cancer outcomes through patient-specific modeling and optimization of treatment strategies.
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Affiliation(s)
- David A Hormuth
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.
| | - Maguy Farhat
- Departments of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Chase Christenson
- Departments of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| | - Brandon Curl
- Departments of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77230, USA
| | - C Chad Quarles
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Caroline Chung
- Departments of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Thomas E Yankeelov
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Oncology, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA; Departments of Imaging Physics, MD Anderson Cancer Center, Houston, TX 77230, USA
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Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and [ 18F]FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma. Eur J Nucl Med Mol Imaging 2022; 49:4677-4691. [PMID: 35907033 PMCID: PMC9605929 DOI: 10.1007/s00259-022-05917-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/16/2022] [Indexed: 11/04/2022]
Abstract
Purpose Both amino acid positron emission tomography (PET) and magnetic resonance imaging (MRI) blood volume (BV) measurements are used in suspected recurrent high-grade gliomas. We compared the separate and combined diagnostic yield of simultaneously acquired dynamic contrast-enhanced (DCE) perfusion MRI and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET in patients with anaplastic astrocytoma and glioblastoma following standard therapy. Methods A total of 76 lesions in 60 hybrid [18F]FET PET/MRI scans with DCE MRI from patients with suspected recurrence of anaplastic astrocytoma and glioblastoma were included retrospectively. BV was measured from DCE MRI employing a 2-compartment exchange model (2CXM). Diagnostic performances of maximal tumour-to-background [18F]FET uptake (TBRmax), maximal BV (BVmax) and normalised BVmax (nBVmax) were determined by ROC analysis using 6-month histopathological (n = 28) or clinical/radiographical follow-up (n = 48) as reference. Sensitivity and specificity at optimal cut-offs were determined separately for enhancing and non-enhancing lesions. Results In progressive lesions, all BV and [18F]FET metrics were higher than in non-progressive lesions. ROC analyses showed higher overall ROC AUCs for TBRmax than both BVmax and nBVmax in both lesion-wise (all lesions, p = 0.04) and in patient-wise analysis (p < 0.01). Combining TBRmax with BV metrics did not increase ROC AUC. Lesion-wise positive fraction/sensitivity/specificity at optimal cut-offs were 55%/91%/84% for TBRmax, 45%/77%/84% for BVmax and 59%/84%/72% for nBVmax. Combining TBRmax and best-performing BV cut-offs yielded lesion-wise sensitivity/specificity of 75/97%. The fraction of progressive lesions was 11% in concordant negative lesions, 33% in lesions only BV positive, 64% in lesions only [18F]FET positive and 97% in concordant positive lesions. Conclusion The overall diagnostic accuracy of DCE BV imaging is good, but lower than that of [18F]FET PET. Adding DCE BV imaging did not improve the overall diagnostic accuracy of [18F]FET PET, but may improve specificity and allow better lesion-wise risk stratification than [18F]FET PET alone. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05917-3.
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The Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in the Differentiation of Pseudoprogression and Recurrence of Intracranial Gliomas. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:5680522. [PMID: 35935318 PMCID: PMC9337951 DOI: 10.1155/2022/5680522] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 06/22/2022] [Accepted: 07/01/2022] [Indexed: 11/25/2022]
Abstract
Objective The objective of this study was to determine the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing postoperative changes in intracranial gliomas. Method A total of fifty-one patients who had new enhanced lesions after surgical resection followed by standard radiotherapy and chemotherapy were collected retrospectively from October 2014 to June 2021. The patients were divided into a pseudoprogression group (15 cases) and a recurrence group (36 cases) according to the pathological results of the second operation or a follow-up of more than six months. The follow-up data of all patients were complete, and DCE-MRI was performed. The images were processed to obtain the quantitative parameters Ktrans, Ve, and Kep and the semiquantitative parameter iAUC, which were analysed with relevant statistical software. Results First, the difference in Ktrans and iAUC values between the two groups was statistically significant (P < 0.05), and the difference in Ve and Kep values was not statistically significant (P > 0.05). Second, by comparing the area under the curve, threshold, sensitivity and specificity of Ktrans, and iAUC, it was found that the iAUC threshold value was slightly higher than that of Ktrans, and the specificity of Ktrans was equal to that of iAUC, while the area under the curve and sensitivity of Ktrans were higher than those of iAUC. Third, Ktrans and iAUC had high accuracy in diagnosing recurrence and pseudoprogression, and Ktrans had higher accuracy than iAUC. Conclusion In this study, DCE-MRI has a certain diagnostic value in the early differentiation of recurrence and pseudoprogression, offering a new method for the diagnosis and assessment of gliomas after surgery.
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Liquid Biopsy in Glioblastoma. Cancers (Basel) 2022; 14:cancers14143394. [PMID: 35884454 PMCID: PMC9323318 DOI: 10.3390/cancers14143394] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/10/2022] [Accepted: 07/11/2022] [Indexed: 12/27/2022] Open
Abstract
Simple Summary Glioblastoma is the most common and malignant primary brain tumor. Despite intensive research for new treatments, the survival of patients has not significantly improved in recent decades. Currently, glioblastoma is mainly diagnosed by neuroimaging techniques followed by histopathological and molecular analysis of the resected or biopsied tissue. Both imaging and tissue-based methods have, despite their advantages, some important limitations highlighting the necessity for alternative techniques such as liquid biopsy. It appears as an attractive and non-invasive alternative to support the diagnosis and the follow-up of patients with glioblastoma and to identify early recurrence. Liquid biopsy, primarily through blood tests, involves the detection and quantification of tumoral content released by tumors into the biofluids. The aim of the present review is to discuss the biological bases, the advantages, and the disadvantages of the most important circulating biomarkers so far proposed for glioblastoma. Abstract Glioblastoma (GBM) is the most common and aggressive primary brain tumor. Despite recent advances in therapy modalities, the overall survival of GBM patients remains poor. GBM diagnosis relies on neuroimaging techniques. However, confirmation via histopathological and molecular analysis is necessary. Given the intrinsic limitations of such techniques, liquid biopsy (mainly via blood samples) emerged as a non-invasive and easy-to-implement alternative that could aid in both the diagnosis and the follow-up of GBM patients. Cancer cells release tumoral content into the bloodstream, such as circulating tumor DNA, circulating microRNAs, circulating tumor cells, extracellular vesicles, or circulating nucleosomes: all these could serve as a marker of GBM. In this narrative review, we discuss the current knowledge, the advantages, and the disadvantages of each circulating biomarker so far proposed.
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Withofs N, Kumar R, Alavi A, Hustinx R. Facts and Fictions About [ 18F]FDG versus Other Tracers in Managing Patients with Brain Tumors: It Is Time to Rectify the Ongoing Misconceptions. PET Clin 2022; 17:327-342. [PMID: 35717096 DOI: 10.1016/j.cpet.2022.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
MRI is the first-choice imaging technique for brain tumors. Positron emission tomography can be combined together with multiparametric MRI to increase diagnostic confidence. Radiolabeled amino acids have gained wide clinical acceptance. The reported pooled specificity of [18F]FDG positron emission tomography is high and [18F]FDG might still be the first-choice positron emission tomography tracer in cases of World Health Organization grade 3 to 4 gliomas or [18F]FDG-avid tumors, avoiding the use of more expensive and less available radiolabeled amino acids. The present review discusses the additional value of positron emission tomography with a focus on [18F]FDG and radiolabeled amino acids.
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Affiliation(s)
- Nadia Withofs
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hopital, Avenue de l'hopital, 1, Liege 1 4000, Belgium; GIGA-CRC in vivo imaging, University of Liege, GIGA CHU - B34 Quartier Hôpital Avenue de l'Hôpital,11, 4000 Liège, Belgium.
| | - Rakesh Kumar
- Diagnostic Nuclear Medicine Division, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Roland Hustinx
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hopital, Avenue de l'hopital, 1, Liege 1 4000, Belgium; GIGA-CRC in vivo imaging, University of Liege, GIGA CHU - B34 Quartier Hôpital Avenue de l'Hôpital,11, 4000 Liège, Belgium
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