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Śledzińska-Bebyn P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024; 112:63-81. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska-Bebyn
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Internal Diseases, 10th Military Clinical Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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Ungan G, Pons-Escoda A, Ulinic D, Arús C, Ortega-Martorell S, Olier I, Vellido A, Majós C, Julià-Sapé M. Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous. NMR IN BIOMEDICINE 2024; 37:e5095. [PMID: 38213096 DOI: 10.1002/nbm.5095] [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: 06/15/2023] [Revised: 11/06/2023] [Accepted: 12/01/2023] [Indexed: 01/13/2024]
Abstract
The standard treatment in glioblastoma includes maximal safe resection followed by concomitant radiotherapy plus chemotherapy and adjuvant temozolomide. The first follow-up study to evaluate treatment response is performed 1 month after concomitant treatment, when contrast-enhancing regions may appear that can correspond to true progression or pseudoprogression. We retrospectively evaluated 31 consecutive patients at the first follow-up after concomitant treatment to check whether the metabolic pattern assessed with multivoxel MRS was predictive of treatment response 2 months later. We extracted the underlying metabolic patterns of the contrast-enhancing regions with a blind-source separation method and mapped them over the reference images. Pattern heterogeneity was calculated using entropy, and association between patterns and outcomes was measured with Cramér's V. We identified three distinct metabolic patterns-proliferative, necrotic, and responsive, which were associated with status 2 months later. Individually, 70% of the patients showed metabolically heterogeneous patterns in the contrast-enhancing regions. Metabolic heterogeneity was not related to the regions' size and only stable patients were less heterogeneous than the rest. Contrast-enhancing regions are also metabolically heterogeneous 1 month after concomitant treatment. This could explain the reported difficulty in finding robust pseudoprogression biomarkers.
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Affiliation(s)
- Gülnur Ungan
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Albert Pons-Escoda
- Grup de Neuro-oncologia, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Daniel Ulinic
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | | | - Ivan Olier
- Data Science Research Centre, Liverpool John Moores University (LJMU), Liverpool, UK
| | - Alfredo Vellido
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- IDEAI-UPC Research Center, UPC BarcelonaTech, Barcelona, Spain
| | - Carles Majós
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Grup de Neuro-oncologia, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
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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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Mangalore S, Pradeep GVN, Murthy VKS, Bairwa P, Kumar P, Saini J, Prasad C, Sadashiva N, Beniwal M, Santosh V. Prospective Study to Evaluate the Role of Dual Point Contrast-enhanced Magnetic Resonance Imaging in Differentiation of Brain Tumoral from Nontumoral Tissue: A Magnetic Resonance/PET Study. Indian J Nucl Med 2024; 39:87-97. [PMID: 38989312 PMCID: PMC11232725 DOI: 10.4103/ijnm.ijnm_103_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 07/12/2024] Open
Abstract
Background and Purpose Follow-up imaging of gliomas is crucial to look for residual or recurrence and to differentiate them from nontumoral tissue. Positron emission tomography (PET)-magnetic resonance imaging (MRI) is the problem-solving tool in such cases. We investigated the role of dual point contrast (DPC)-enhanced MRI to discriminate tumoral from the nontumoral tissue compared to PET-MRI taken as the gold standard. Materials and Methods The institutional ethics committee approved the study, and consent was obtained from all the patients included in the study. We prospectively did immediate and 75-min delayed contrast MRI in glioma cases who came for follow-up as a part of PET-MRI study in our institute. Subtracted images were obtained using immediate and 75-min delayed contrast images. Color-coded subtracted images were compared with PET-MRI images. 75-min delayed contrast MRI and diffusion-weighted imaging (DWI) images with Gray Scale inversion were compared with PET attenuation-corrected images. Results We included 23 PET MRI cases done with different radiotracers in our study. Overall, we found PET-DPC correlation in (20/20 ~ 100%) cases of enhancing tumors. In two cases (DOPA and fluorodeoxyglucose), since they were nonenhancing low-grade gliomas and the other one was melanoma with intrinsic T1 hyperintensity and the DPC technique could not be used. DWI-PET correlated in 17/19 (~89.4%) cases, and perfusion-weighted imaging (PWI)-PET dynamic susceptibility contrast (DSC)/ASL correlated in 14/18 (~77.7%) cases after cases with hemorrhage were excluded. Conclusion DPC MRI showed a good correlation with PET MRI in discriminating tumoral from the nontumoral tissue. DPC MRI can act as a potential alternative to PET MRI in peripheral hospitals where PET is not available. However, the DPC technique is limited in low-grade nonenhancing gliomas.
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Affiliation(s)
- Sandhya Mangalore
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Guddanti Venkata Naga Pradeep
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Venkatesh K. S. Murthy
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Pawan Bairwa
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Pardeep Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Chandrajit Prasad
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Nishanth Sadashiva
- Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Manish Beniwal
- Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Vani Santosh
- Department of Neuropathology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
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Ortiz de Mendivil A, Martín-Medina P, García-Cañamaque L, Jiménez-Munarriz B, Ciérvide R, Diamantopoulos J. Challenges in radiological evaluation of brain metastases, beyond progression. RADIOLOGIA 2024; 66:166-180. [PMID: 38614532 DOI: 10.1016/j.rxeng.2024.03.003] [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: 11/15/2022] [Accepted: 04/02/2023] [Indexed: 04/15/2024]
Abstract
MRI is the cornerstone in the evaluation of brain metastases. The clinical challenges lie in discriminating metastases from mimickers such as infections or primary tumors and in evaluating the response to treatment. The latter sometimes leads to growth, which must be framed as pseudo-progression or radionecrosis, both inflammatory phenomena attributable to treatment, or be considered as recurrence. To meet these needs, imaging techniques are the subject of constant research. However, an exponential growth after radiotherapy must be interpreted with caution, even in the presence of results suspicious of tumor progression by advanced techniques, because it may be due to inflammatory changes. The aim of this paper is to familiarize the reader with inflammatory phenomena of brain metastases treated with radiotherapy and to describe two related radiological signs: "the inflammatory cloud" and "incomplete ring enhancement", in order to adopt a conservative management with close follow-up.
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Affiliation(s)
- A Ortiz de Mendivil
- Servicio de Radiodiagnóstico, Sección de Neurorradiología, Hospital Universitario HM Sanchinarro, Madrid, Spain.
| | - P Martín-Medina
- Servicio de Radiodiagnóstico, Sección de Neurorradiología, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | | | - B Jiménez-Munarriz
- Servicio de Oncología Médica, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | - R Ciérvide
- Servicio de Oncología Radioterápica, Hospital Universitario HM Sanchinarro, Madrid, Spain
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Dagher R, Gad M, da Silva de Santana P, Sadeghi MA, Yewedalsew SF, Gujar SK, Yedavalli V, Köhler CA, Khan M, Tavora DGF, Kamson DO, Sair HI, Luna LP. Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis. J Neurooncol 2024; 166:1-15. [PMID: 38212574 DOI: 10.1007/s11060-023-04528-8] [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: 11/05/2023] [Accepted: 12/01/2023] [Indexed: 01/13/2024]
Abstract
PURPOSE In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects. METHODS We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves. RESULTS We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however. CONCLUSION The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.
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Affiliation(s)
- Richard Dagher
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Mona Gad
- Diagnostic Radiology Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | | | - Mohammad Amin Sadeghi
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | | | - Sachin K Gujar
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Vivek Yedavalli
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Cristiano André Köhler
- Medical Sciences Post-Graduation Program, Department of Internal Medicine, School of Medicine, Federal University of Ceará, Fortaleza, Brazil
| | - Majid Khan
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | | | - David Olayinka Kamson
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, MD, USA
| | - Haris I Sair
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA.
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Snyder EJ, Sarma A, Poussaint TY, Krishnasarma R, Pruthi S. Complications of Cancer Therapy in Children: A Comprehensive Review of Neuroimaging Findings. J Comput Assist Tomogr 2023; 47:820-832. [PMID: 37707414 DOI: 10.1097/rct.0000000000001481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
ABSTRACT Complications of cancer therapy in children can result in a spectrum of neurologic toxicities that may occur at the initiation of therapy or months to years after treatment. Although childhood cancer remains rare, increasing survival rates mean that more children will be living longer after cancer treatment. Therefore, complications of cancer therapy will most likely occur with increasing frequency.At times, it is very difficult to differentiate between therapeutic complications and other entities such as tumor recurrence, development of secondary malignancy, and infection (among other conditions). Radiologists often play a key role in the diagnosis and evaluation of pediatric patients with malignancies, and thus, awareness of imaging findings of cancer complications and alternative diagnoses is essential in guiding management and avoiding misdiagnosis. The aim of this review article is to illustrate the typical neuroimaging findings of cancer therapy-related toxicities, including both early and late treatment effects, highlighting pearls that may aid in making the appropriate diagnosis.
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Affiliation(s)
- Elizabeth J Snyder
- From the Department of Radiology, Vanderbilt University Medical Center, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN
| | - Asha Sarma
- From the Department of Radiology, Vanderbilt University Medical Center, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN
| | | | - Rekha Krishnasarma
- From the Department of Radiology, Vanderbilt University Medical Center, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN
| | - Sumit Pruthi
- From the Department of Radiology, Vanderbilt University Medical Center, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN
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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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9
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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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Nogami Y, Banno K, Kobayashi Y, Tominaga E, Okuda S, Aoki D. Clinical utility of MR spectroscopy for gynecological pelvic abscesses using next-generation sequencing technology for the detection of causative bacteria. Exp Ther Med 2023; 25:96. [PMID: 36761007 PMCID: PMC9905653 DOI: 10.3892/etm.2023.11796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 11/30/2022] [Indexed: 01/14/2023] Open
Abstract
Due to the invasiveness of sample collection, treatment for an abscess in the pelvis, such as a gynecological abscess, is often started without a culture test. A test that could predict the appropriate antibiotic and clinical course without invasiveness prior to treatment initiation would be useful. Magnetic resonance spectroscopy (MRS) can be used to detect metabolites in an abscess and has the potential for evaluation of gynecological abscesses. The present study investigated the use of MRS for the evaluation of gynecological abscesses, using next-generation sequencing (NGS) for detection of true pathogenic bacteria. A total of 16 patients with a gynecological abscess who were treated at Keio University Hospital (Tokyo, Japan) from July 2015 to September 2016 and underwent MRS were recruited to the present study. If available, samples from drainage or surgery were used for detection of true pathogenic bacteria based on analyses of bacterial flora using NGS of 16S ribosomal DNA. MRS signals, NGS results and clinical course were then compared. All patients gave written informed consent after receiving an oral explanation of the study and the study was approved by the institutional research ethics committee. Of the 16 patients, six had MRS signals with a specific peak at 1.33 ppm, which suggested the presence of lipid or lactic acid. However, there was no significant association between metabolism, MRS signals, pathogenesis and clinical course. Only in cases of infectious lymphocele were there cases with a lactic acid peak that seemed to improve without drainage. In conclusion, the present study was not able to show marked usefulness of MRS for the identification of pathogenic bacteria and prediction of the clinical course; however, MRS may be useful for predicting the need for drainage in patients with infectious lymphocele. This study was registered as a clinical trial in the UMIN Clinical Trials Registry (registration no. UMIN000016705) on March 11, 2015.
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Affiliation(s)
- Yuya Nogami
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Kouji Banno
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan,Correspondence to: Dr Kouji Banno, Department of Obstetrics and Gynecology, Keio University School of Medicine, 35 Shinanomachi, Shinjyuku-ku, Tokyo 160-8582, Japan
| | - Yusuke Kobayashi
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Eiichiro Tominaga
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Shigeo Okuda
- Department of Radiology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Daisuke Aoki
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
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Castello A, Castellani M, Florimonte L, Ciccariello G, Mansi L, Lopci E. PET radiotracers in glioma: a review of clinical indications and evidence. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00523-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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13
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Diagnostic Performance of Dynamic Susceptibility Contrast-Enhanced Perfusion-Weighted Imaging in Differentiating Recurrence From Radiation Injury in Postoperative Glioma: A Meta-analysis. J Comput Assist Tomogr 2022; 46:938-944. [PMID: 35969866 DOI: 10.1097/rct.0000000000001356] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE It is important to differentiate between radiation injury (RI) and tumor recurrence (TR) in patients with glioma after surgery and radiotherapy. Our objective was to evaluate the use of dynamic susceptibility contrast-enhanced perfusion-weighted imaging to distinguish between TR and RI in patients with glioma. METHODS Relevant studies published until October 2021 were identified in the PubMed, Embase, and Cochrane Library databases. Stata v12.0 and RevMan 5.3 were used for meta-analysis. RESULTS In total, the meta-analysis incorporated 13 retrospective studies that included 513 patients with 522 lesions. Among the 522 lesions, 329 lesions were TRs and 193 lesions were RIs. The pooled relative cerebral blood volume value was significantly greater in the TR group (P < 0.00001) with significant heterogeneity (I2 = 88%). The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 83% (95 confidence interval [CI], 77%-88%), 85% (95 CI, 77%-91%), 5.60 (95 CI, 3.61-8.70), and 0.20 (95% CI, 0.14-0.27), respectively. The heterogeneity of sensitivity (I2 = 33.18%), specificity (I2 = 24.01%), PLR (I2 = 0.00%), and NLR (I2 = 6.68%) is not significant. The area under the receiver operating characteristic curve was 0.91 (95% CI, 0.88-0.93). The 3.0 T magnetic resonance imaging, high-grade glioma, and Europe/America patient subgroups showed PLR greater than 5 and NLR less than 0.2. There was no significant indication of publication bias in the analysis (P = 0.496). CONCLUSIONS It is concluded that dynamic susceptibility contrast-enhanced perfusion-weighted imaging is effective for the diagnostic differentiation between TR and RI in patients with glioma.
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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15
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Johnson DR, Glenn CA, Javan R, Olson JJ. Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults. J Neurooncol 2022; 158:139-165. [PMID: 34694565 DOI: 10.1007/s11060-021-03853-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 09/21/2021] [Indexed: 12/27/2022]
Abstract
TARGET POPULATION These recommendations apply to adults with glioblastoma who have been previously treated with first-line radiation or chemoradiotherapy and who are suspected of experiencing tumor progression. QUESTION In patients with previously treated glioblastoma, is standard contrast-enhanced magnetic resonance imaging including diffusion weighted imaging useful for diagnosing tumor progression and differentiating progression from treatment-related changes? LEVEL II Magnetic resonance imaging with and without gadolinium enhancement including diffusion weighted imaging is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance spectroscopy add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL II Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance perfusion add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Magnetic resonance perfusion is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does the addition of single-photon emission computed tomography (SPECT) provide additional useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Single-photon emission computed tomography imaging is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does 18F-fluorodeoxyglucose positron emission tomography add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III The routine use of 18F-fluorodeoxyglucose positron emission tomography to identify progression of glioblastoma is not recommended. QUESTION In patients with previously treated glioblastoma, does positron emission tomography with amino acid agents add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III It is suggested that amino acid positron emission tomography be considered to assist in the differentiation of progressive glioblastoma from treatment related changes.
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Affiliation(s)
- Derek Richard Johnson
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Chad Allan Glenn
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ramin Javan
- Department of Neuroradiology, George Washington University Hospital, Washington, DC, USA
| | - Jeffrey James Olson
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
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Bodensohn R, Forbrig R, Quach S, Reis J, Boulesteix AL, Mansmann U, Hadi I, Fleischmann D, Mücke J, Holzgreve A, Albert N, Ruf V, Dorostkar M, Corradini S, Herms J, Belka C, Thon N, Niyazi M. MRI-based contrast clearance analysis shows high differentiation accuracy between radiation-induced reactions and progressive disease after cranial radiotherapy. ESMO Open 2022; 7:100424. [PMID: 35248822 PMCID: PMC9058918 DOI: 10.1016/j.esmoop.2022.100424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 11/26/2022] Open
Abstract
Background Pseudoprogression (PsP) or radiation necrosis (RN) may frequently occur after cranial radiotherapy and show a similar imaging pattern compared with progressive disease (PD). We aimed to evaluate the diagnostic accuracy of magnetic resonance imaging-based contrast clearance analysis (CCA) in this clinical setting. Patients and methods Patients with equivocal imaging findings after cranial radiotherapy were consecutively included into this monocentric prospective study. CCA was carried out by software-based automated subtraction of imaging features in late versus early T1-weighted sequences after contrast agent application. Two experienced neuroradiologists evaluated CCA with respect to PsP/RN and PD being blinded for histological findings. The radiological assessment was compared with the histopathological results, and its accuracy was calculated statistically. Results A total of 33 patients were included; 16 (48.5%) were treated because of a primary brain tumor (BT), and 17 (51.1%) because of a secondary BT. In one patient, CCA was technically infeasible. The accuracy of CCA in predicting the histological result was 0.84 [95% confidence interval (CI) 0.67-0.95; one-sided P = 0.051; n = 32]. Sensitivity and specificity of CCA were 0.93 (95% CI 0.66-1.00) and 0.78 (95% CI 0.52-0.94), respectively. The accuracy in patients with secondary BTs was 0.94 (95% CI 0.71-1.00) and nonsignificantly higher compared with patients with primary BT with an accuracy of 0.73 (95% CI 0.45-0.92), P = 0.16. Conclusions In this study, CCA was a highly accurate, easy, and helpful method for distinguishing PsP or RN from PD after cranial radiotherapy, especially in patients with secondary tumors after radiosurgical treatment. CCA is accurate in distinguishing treatment reactions from true PD. CCA was more accurate for irradiated metastases than primary BTs. CCA is not feasible for lesions with no contrast media uptake.
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Jajodia A, Goel V, Goyal J, Patnaik N, Khoda J, Pasricha S, Gairola M. Combined Diagnostic Accuracy of Diffusion and Perfusion MR Imaging to Differentiate Radiation-Induced Necrosis from Recurrence in Glioblastoma. Diagnostics (Basel) 2022; 12:diagnostics12030718. [PMID: 35328270 PMCID: PMC8947286 DOI: 10.3390/diagnostics12030718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/12/2022] [Accepted: 03/11/2022] [Indexed: 11/26/2022] Open
Abstract
We aimed to use quantitative values derived from perfusion and diffusion-weighted MR imaging (PWI and DWI) to differentiate radiation-induced necrosis (RIN) from tumor recurrence in Glioblastoma (GBM) and investigate the best parameters for improved diagnostic accuracy and clinical decision-making. Methods: A retrospective analysis of follow-up MRI with new enhancing observations was performed in histopathologically confirmed subjects of post-treated GBM, who underwent re-surgical exploration. Quantitative estimation of rCBV (relative cerebral blood volume) from PWI and three methods of apparent diffusion coefficient (ADC) estimation were performed, namely ADC R1 (whole cross-sectional area of tumor), ADC R2 (only solid enhancing lesion), and ADC R3 (central necrosis). ROC curve and logistic regression analysis was completed. A confusion matrix table created using Excel provided the best combination parameters to ameliorate false-positive and false-negative results. Results: Forty-four subjects with a mean age of 46 years (range, 19−70 years) underwent re-surgical exploration with RIN in 28 (67%) and recurrent tumor in 16 (33%) on histopathology. rCBV threshold of >3.4 had the best diagnostic accuracy (AUC = 0.93, 81% sensitivity and 89% specificity). A multiple logistic regression model showed significant contributions from rCBV (p < 0.001) and ADC R3 (p = 0.001). After analysis of confusion matrix ADC R3 > 2032 × 10−6 mm2 achieved 100% specificity with gain in sensitivity (94% vs. 56%). Conclusions: A combination of parameters had better diagnostic performance, and a stepwise combination of rCBV and ADC R3 obviated unnecessary biopsies in 10% (3/28), leading to improved clinical decision-making.
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Affiliation(s)
- Ankush Jajodia
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, ON L8V 5C2, Canada
- Correspondence: (A.J.); (V.G.); Tel.: +91-97-6510-7872 (V.G.)
| | - Varun Goel
- Department of Medical Oncology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India
- Correspondence: (A.J.); (V.G.); Tel.: +91-97-6510-7872 (V.G.)
| | - Jitin Goyal
- Department of Radiology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India; (J.G.); (J.K.)
| | - Nivedita Patnaik
- Department of Laboratory & Histopathology, Rajiv Gandhi Cancer Institute, Delhi 110085, India; (N.P.); (S.P.)
| | - Jeevitesh Khoda
- Department of Radiology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India; (J.G.); (J.K.)
| | - Sunil Pasricha
- Department of Laboratory & Histopathology, Rajiv Gandhi Cancer Institute, Delhi 110085, India; (N.P.); (S.P.)
| | - Munish Gairola
- Department of Radiation Oncology, Rajiv Gandhi Cancer Institute, Delhi 110085, India;
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18
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Booth TC, Wiegers EC, Warnert EAH, Schmainda KM, Riemer F, Nechifor RE, Keil VC, Hangel G, Figueiredo P, Álvarez-Torres MDM, Henriksen OM. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Front Oncol 2022; 11:811425. [PMID: 35340697 PMCID: PMC8948428 DOI: 10.3389/fonc.2021.811425] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/28/2021] [Indexed: 01/16/2023] Open
Abstract
Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
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Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ruben E. Nechifor
- Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, Netherlands
| | - Gilbert Hangel
- Department of Neurosurgery & High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Patrícia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Otto M. Henriksen
- Department of Clinical Physiology, Nuclear medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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El-Abtah ME, Talati P, Fu M, Chun B, Clark P, Peters A, Ranasinghe A, He J, Rapalino O, Batchelor TT, Gilberto Gonzalez R, Curry WT, Dietrich J, Gerstner ER, Ratai EM. Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma. Neurooncol Adv 2022; 4:vdac128. [PMID: 36071927 PMCID: PMC9446677 DOI: 10.1093/noajnl/vdac128] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.
Methods
We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.
Results
28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.
Conclusions
Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.
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Affiliation(s)
- Mohamed E El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
| | - Melanie Fu
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Benjamin Chun
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Patrick Clark
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anna Peters
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anthony Ranasinghe
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Julian He
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Tracy T Batchelor
- Harvard Medical School , Boston, Massachusetts , USA
- Brigham and Women’s Hospital, Neurosciences Center , Boston, Massachusetts , USA
| | - R Gilberto Gonzalez
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - William T Curry
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Jorg Dietrich
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Elizabeth R Gerstner
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
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Li H, Duan Y, Liu N, Dong J, Liang Y, Ju R. Value of DWI Combined with Magnetic Resonance Spectroscopy in the Differential Diagnosis between Recurrent Glioma and Radiation Injury: A Meta-Analysis. Int J Clin Pract 2022; 2022:1629570. [PMID: 36380750 PMCID: PMC9626199 DOI: 10.1155/2022/1629570] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 10/16/2022] [Accepted: 10/19/2022] [Indexed: 11/23/2022] Open
Abstract
To analyse the value of the apparent diffusion coefficient (ADC) in diffusion-weighted imaging (DWI) and the choline (Cho)/creatine (Cr) ratio and Cho/N-acetyl-aspartate (NAA) ratio in magnetic resonance spectroscopy (MRS) in the differential diagnosis between recurrent glioma and radiation injury. Chinese and English studies related to the diagnosis of recurrent glioma and radiation injury using DWI and MRS and published before 15 October 2022 were retrieved from PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure, China Biomedical Literature Database, VIP Journal Database, and Wanfang Database for a meta-analysis. A total of 11 articles were included in this study. ADC was lower in the recurrent glioma group than in the radiation injury group (standardized mean difference = -1.29, 95% confidence interval (CI) (-1.87, -0.71), P < 0.001). The Cho/Cr ratio was higher in the recurrent glioma group than in the radiation injury group (weighted mean difference = 0.65, 95% CI (0.40, 0.90), and P < 0.001). The Cho/NAA ratio was higher in the recurrent glioma group than in the radiation injury group, as evidenced by the sensitivity analysis. The sensitivity and specificity of the Cho/Cr ratio were 0.85 (0.73-0.92) and 0.82 (0.67-0.91), respectively, and the area under the curve was 0.86. The sensitivity and specificity of the Cho/NAA ratio were 0.82 (0.66-0.91) and 0.94 (0.69-0.99), respectively, and the area under the curve was 0.93. This meta-analysis showed that ADC, Cho/Cr, and Cho/NAA ratios all had high sensitivity and specificity. Therefore, DWI combined with MRS can effectively improve the diagnosis of recurrent glioma and radiation injury.
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Affiliation(s)
- Hongyi Li
- Department of Radiology, The People's Hospital of Liaoning Province, Shenyang 110016, China
- Department of Radiology, The People's Hospital of China Medical University, Shenyang 110016, China
| | - Yang Duan
- Department of Radiology, The General Hospital of Northern Theater Command, Shenyang 110016, China
| | - Na Liu
- Department of Radiology, The People's Hospital of Liaoning Province, Shenyang 110016, China
- Department of Radiology, The People's Hospital of China Medical University, Shenyang 110016, China
| | - Junyi Dong
- Department of Radiology, The People's Hospital of Liaoning Province, Shenyang 110016, China
- Department of Radiology, The People's Hospital of China Medical University, Shenyang 110016, China
| | - Yuanzi Liang
- Department of Radiology, The People's Hospital of Liaoning Province, Shenyang 110016, China
- Department of Radiology, The People's Hospital of China Medical University, Shenyang 110016, China
| | - Ronghui Ju
- Department of Radiology, The People's Hospital of Liaoning Province, Shenyang 110016, China
- Department of Radiology, The People's Hospital of China Medical University, Shenyang 110016, China
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Abstract
PURPOSE OF REVIEW This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions. RECENT FINDINGS Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings. SUMMARY Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.
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Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière-Charles Foix
- Sorbonne Université, INSERM, CNRS, Assistance Publique-Hôpitaux de Paris, Institut du Cerveau et de la Moelle épinière, boulevard de l’Hôpital, Paris
| | - Stefano Casagranda
- Department of Research & Innovation, Olea Medical, avenue des Sorbiers, La Ciotat, France
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22
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Kumar A, ArunRaj ST, Bhullar K, Haresh KP, Gupta S, Ballal S, Yadav M, Singh M, Damle NA, Garg A, Tripathi M, Bal C. Ga-68 PSMA PET/CT in recurrent high-grade gliomas: evaluating PSMA expression in vivo. Neuroradiology 2021; 64:969-979. [PMID: 34648046 DOI: 10.1007/s00234-021-02828-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 10/09/2021] [Indexed: 01/24/2023]
Abstract
PURPOSE We planned this prospective study to evaluate PSMA expression in recurrent high-grade gliomas (rHGG), including anaplastic astrocytoma and glioblastoma using Glu-NH-CO-NH-Lys-(Ahx)-[Ga-68 (HBED-CC)]- (Ga-68 PSMA) positron emission tomography (PET), with its theranostic potential in mind. METHODS This was a prospective study enrolling patients with clinical and MRI evidence of rHGG on follow-up. Three treated cases of HGG with RN on MRI were also included as negative controls. Abnormal tracer accumulation in the brain parenchyma, more than the contralateral hemisphere was interpreted as positive study. For semiquantitative analysis, a 3D spherical region of interest (ROI) was drawn around the site of the abnormal Ga-68 PSMA uptake, and the ratio of SUVmax of tumor (T) to SUVmax of the contralateral corresponding area (TBR) was calculated. Each patients' PSMA brain PET was fused to the corresponding MRI and reviewed for concordance. RESULTS Thirty patients were included in the study, a total of 49 lesions were detected on MRI, and fused PET/MR images showed increased Ga-68 PSMA uptake in all these lesions. Multifocal lesions were better appreciated on fused PET-MR images, and concordance between MRI and PET was 100 % for patient and lesion-wise detection. Recurrent glioma lesions showed SUVmax and SUVmean values (median and IQR) 6.0 (4.4-8.2) and 3.3 (2.8-3.7), respectively. Lesions labeled as radiation necrosis on MRI did not show tracer accumulation. CONCLUSION Ga-68 PSMA has potential utility for evaluating recurrence in HGG and its potential for theranostics would encourage its use in the evaluation of these patients.
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Affiliation(s)
- Arunav Kumar
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India
| | | | - Khush Bhullar
- Department of Neuroimaging & Interventional Neuroradiology, All India Institute of Medical Sciences, New Delhi, India
| | - K P Haresh
- Department of Radiation Oncology, All India Institute of Medical Sciences, New Delhi, India
| | - Subhash Gupta
- Department of Radiation Oncology, All India Institute of Medical Sciences, New Delhi, India
| | - Sanjana Ballal
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India
| | - Madhav Yadav
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India
| | | | - Nishikant Avinash Damle
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India
| | - Ajay Garg
- Department of Neuroimaging & Interventional Neuroradiology, All India Institute of Medical Sciences, New Delhi, India
| | - Madhavi Tripathi
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India.
| | - Chandrasekhar Bal
- Department of Nuclear Medicine and PET/CT, All India Institute of Medical Sciences, New Delhi, India
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23
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Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas. Cancer J 2021; 27:344-352. [PMID: 34570448 DOI: 10.1097/ppo.0000000000000545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
ABSTRACT Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.
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24
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Zaccagna F, Grist JT, Quartuccio N, Riemer F, Fraioli F, Caracò C, Halsey R, Aldalilah Y, Cunningham CH, Massoud TF, Aloj L, Gallagher FA. Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances. Eur J Radiol 2021; 142:109842. [PMID: 34274843 DOI: 10.1016/j.ejrad.2021.109842] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.
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Affiliation(s)
- Fulvio Zaccagna
- Division of Neuroimaging, Department of Medical Imaging, University of Toronto, Toronto, Canada.
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom; Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, United Kingdom; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Palermo, Italy
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, University of Bergen, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Corradina Caracò
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Richard Halsey
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Yazeed Aldalilah
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom; Department of Radiology, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Tarik F Massoud
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, USA
| | - Luigi Aloj
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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Jafari SH, Rabiei N, Taghizadieh M, Mirazimi SMA, Kowsari H, Farzin MA, Razaghi Bahabadi Z, Rezaei S, Mohammadi AH, Alirezaei Z, Dashti F, Nejati M. Joint application of biochemical markers and imaging techniques in the accurate and early detection of glioblastoma. Pathol Res Pract 2021; 224:153528. [PMID: 34171601 DOI: 10.1016/j.prp.2021.153528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 06/09/2021] [Accepted: 06/14/2021] [Indexed: 11/28/2022]
Abstract
Glioblastoma is a primary brain tumor with the most metastatic effect in adults. Despite the wide range of multidimensional treatments, tumor heterogeneity is one of the main causes of tumor spread and gives great complexity to diagnostic and therapeutic methods. Therefore, featuring noble noninvasive prognostic methods that are focused on glioblastoma heterogeneity is perceived as an urgent need. Imaging neuro-oncological biomarkers including MGMT (O6-methylguanine-DNA methyltransferase) promoter methylation status, tumor grade along with other tumor characteristics and demographic features (e.g., age) are commonly referred to during diagnostic, therapeutic and prognostic processes. Therefore, the use of new noninvasive prognostic methods focused on glioblastoma heterogeneity is considered an urgent need. Some neuronal biomarkers, including the promoter methylation status of the promoter MGMT, the characteristics and grade of the tumor, along with the patient's demographics (such as age and sex) are involved in diagnosis, treatment, and prognosis. Among the wide array of imaging techniques, magnetic resonance imaging combined with the more physiologically detailed technique of H-magnetic resonance spectroscopy can be useful in diagnosing neurological cancer patients. In addition, intracranial tumor qualitative analysis and sometimes tumor biopsies help in accurate diagnosis. This review summarizes the evidence for biochemical biomarkers being a reliable biomarker in the early detection and disease management in GBM. Moreover, we highlight the correlation between Imaging techniques and biochemical biomarkers and ask whether they can be combined.
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Affiliation(s)
- Seyed Hamed Jafari
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Nikta Rabiei
- School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Taghizadieh
- Department of Pathology, School of Medicine, Center for Women's Health Research Zahra, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sayad Mohammad Ali Mirazimi
- School of Medicine, Kashan University of Medical Sciences, Kashan, Iran; Student Research Committee, Kashan University of Medical Sciences, Kashan, Iran
| | - Hamed Kowsari
- School of Medicine, Kashan University of Medical Sciences, Kashan, Iran; Student Research Committee, Kashan University of Medical Sciences, Kashan, Iran
| | - Mohammad Amin Farzin
- Department of Laboratory Medicine, School of Allied Medical Sciences, Kashan University of Medical Sciences, Kashan, Iran
| | - Zahra Razaghi Bahabadi
- School of Medicine, Kashan University of Medical Sciences, Kashan, Iran; Student Research Committee, Kashan University of Medical Sciences, Kashan, Iran
| | - Samaneh Rezaei
- Department of Medical Biotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amir Hossein Mohammadi
- Research Center for Biochemistry and Nutrition in Metabolic Diseases, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran
| | - Zahra Alirezaei
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran; Paramedical School, Bushehr University of Medical Sciences, Bushehr, Iran.
| | - Fatemeh Dashti
- School of Medicine, Kashan University of Medical Sciences, Kashan, Iran; Student Research Committee, Kashan University of Medical Sciences, Kashan, Iran.
| | - Majid Nejati
- Anatomical Sciences Research Center, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran.
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Radiation Necrosis Following Stereotactic Radiosurgery for Trigeminal Neuralgia. Can J Neurol Sci 2021; 47:425-427. [PMID: 32036796 DOI: 10.1017/cjn.2020.24] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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27
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Moon HH, Kim HS, Park JE, Kim YH, Kim JH. Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas. BMC Cancer 2021; 21:654. [PMID: 34074252 PMCID: PMC8170938 DOI: 10.1186/s12885-021-08414-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 05/24/2021] [Indexed: 11/24/2022] Open
Abstract
Background Updated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma. Methods This retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan–Meier method. Results Pseudoprogression rate was significantly lower (chi-square test, P = .047) and TTP was significantly shorter (hazard ratio [HR] = 2.03, P = .005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio = 0.26, P = .046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR = 4.33, P < 0.001 and HR = 3.71, P = .009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P = .001), whereas it was not in tumor-dominant NEL. Conclusions NEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08414-2.
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Affiliation(s)
- Hye Hyeon Moon
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea.
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
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Reliability of Magnetic Resonance Spectroscopy and Positron Emission Tomography Computed Tomography in Differentiating Metastatic Brain Tumor Recurrence from Radiation Necrosis. World Neurosurg 2021; 151:e1059-e1068. [PMID: 34052453 DOI: 10.1016/j.wneu.2021.05.064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Clinical and/or neuroimaging changes after whole-brain radiation therapy (WBRT) or stereotactic radiosurgery (SRS) for metastatic brain tumor(s) present the clinical dilemma of differentiating tumor recurrence from radiation necrosis. Several imaging modalities attempt to answer this clinical question, including magnetic resonance spectroscopy (MRS) and positron emission tomography (PET) computed tomography (CT). We evaluated our experience regarding the ability of MRS and PET CT to differentiate tumor recurrence from radiation necrosis in patients who have received WBRT or SRS. METHODS We retrospectively reviewed records of 242 patients with previous WBRT or SRS to identify those who had MRS and/or PET CT to differentiate tumor recurrence from radiation necrosis. Patients were sorted into true-positive, false-positive, false-negative, and true-negative groups on the basis of imaging interpretation and clinical course combined with surgical pathology results or reaction to nonsurgical treatments including SRS, dexamethasone, or observation. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were then calculated. RESULTS Of 25 patients presenting such diagnostic questions, 19 were evaluated with MRS and 13 with PET CT. MRS sensitivity was 100%, specificity was 50%, and accuracy was 81.8%, whereas PET CT sensitivity was 36.4%, specificity was 66.7%, and accuracy was 42.9%. CONCLUSIONS MRS has better accuracy than PET CT and a high negative predictive value, therefore making it more useful in distinguishing recurrent tumor from radiation necrosis. We encourage correlation with symptoms at imaging to aid in clinical decision making.
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Cui M, Zorrilla-Veloz RI, Hu J, Guan B, Ma X. Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis. Front Neurol 2021; 12:671867. [PMID: 34093419 PMCID: PMC8173157 DOI: 10.3389/fneur.2021.671867] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 03/24/2021] [Indexed: 11/24/2022] Open
Abstract
Purpose: To evaluate the diagnostic accuracy of PET with different radiotracers and parameters in differentiating between true glioma progression (TPR) and post treatment-related change (PTRC). Methods: Studies on using PET to differentiate between TPR and PTRC were screened from the PubMed and Embase databases. By following the PRISMA checklist, the quality assessment of included studies was performed, the true positive and negative values (TP and TN), false positive and negative values (FP and FN), and general characteristics of all the included studies were extracted. Results of PET consistent with reference standard were defined as TP or TN. The pooled sensitivity (Sen), specificity (Spe), and hierarchical summary receiver operating characteristic curves (HSROC) were generated to evaluate the diagnostic accuracy. Results: The 33 included studies had 1,734 patients with 1,811 lesions suspected of glioma recurrence. Fifteen studies tested the accuracy of 18F-FET PET, 12 tested 18F-FDG PET, seven tested 11C-MET PET, and three tested 18F-DOPA PET. 18F-FET PET showed a pooled Sen and Spe of 0.88 (95% CI: 0.80, 0.93) and 0.78 (0.69, 0.85), respectively. In the subgroup analysis of FET-PET, diagnostic accuracy of high-grade gliomas (HGGs) was higher than that of mixed-grade gliomas (P interaction = 0.04). 18F-FDG PET showed a pooled Sen and Spe of 0.78 (95% CI: 0.71, 0.83) and 0.87 (0.80, 0.92), the Spe of the HGGs group was lower than that of the low-grade gliomas group (0.82 vs. 0.90, P = 0.02). 11C-MET PET had a pooled Sen and Spe of 0.92 (95% CI: 0.83, 0.96) and 0.78 (0.69, 0.86). 18F-DOPA PET had a pooled Sen and Spe of 0.85 (95% CI: 0.80, 0.89) and 0.70 (0.60, 0.79). FET-PET combined with MRI had a pooled Sen and Spe of 0.88 (95% CI: 0.78, 0.94) and 0.76 (0.57, 0.88). Multi-parameters analysis of FET-PET had pooled Sen and Spe values of 0.88 (95% CI: 0.81, 0.92) and 0.79 (0.63, 0.89). Conclusion: PET has a moderate diagnostic accuracy in differentiating between TPR and PTRC. The high Sen of amino acid PET and high Spe of FDG-PET suggest that the combination of commonly used FET-PET and FDG-PET may be more accurate and promising, especially for low-grade glioma.
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Affiliation(s)
- Meng Cui
- Medical School of Chinese People's Liberation Army, Beijing, China
- Department of Neurosurgery, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Rocío Isabel Zorrilla-Veloz
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- The University of Texas MD Anderson Cancer Centre UT Health Graduate School of Biomedical Sciences, Houston, TX, United States
| | - Jian Hu
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- The University of Texas MD Anderson Cancer Centre UT Health Graduate School of Biomedical Sciences, Houston, TX, United States
| | - Bing Guan
- Department of Health Economics, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Xiaodong Ma
- Medical School of Chinese People's Liberation Army, Beijing, China
- Department of Neurosurgery, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
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30
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Weinberg BD, Kuruva M, Shim H, Mullins ME. Clinical Applications of Magnetic Resonance Spectroscopy in Brain Tumors: From Diagnosis to Treatment. Radiol Clin North Am 2021; 59:349-362. [PMID: 33926682 PMCID: PMC8272438 DOI: 10.1016/j.rcl.2021.01.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Magnetic resonance spectroscopy (MRS) is a valuable tool for imaging brain tumors, primarily as an adjunct to conventional imaging and clinical presentation. MRS is useful in initial diagnosis of brain tumors, helping differentiate tumors from possible mimics such as metastatic disease, lymphoma, demyelination, and infection, as well as in the subsequent follow-up of patients after resection and chemoradiation. Unfortunately, the spectroscopic appearance of many pathologies can overlap, and ultimately follow-up or biopsy may be required to make a definitive diagnosis. Future developments may continue to increase the value of MRS for initial diagnosis, treatment planning, and early detection of recurrence.
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Affiliation(s)
- Brent D Weinberg
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA.
| | - Manohar Kuruva
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Radiation Oncology, Emory University, 1365 Clifton Road Northeast, Atlanta, GA 30322, USA
| | - Mark E Mullins
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA
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Distinct Cerebrovascular Reactivity Patterns for Brain Radiation Necrosis. Cancers (Basel) 2021; 13:cancers13081840. [PMID: 33924308 PMCID: PMC8069508 DOI: 10.3390/cancers13081840] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/31/2021] [Accepted: 04/09/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Current imaging-based discrimination between radiation necrosis versus recurrent glioblastoma contrast-enhancing lesions remains imprecise but is paramount for prognostic and therapeutic evaluation. We examined whether patients with radiation necrosis exhibit distinct patterns of blood oxygenation-level dependent fMRI cerebrovascular reactivity (BOLD-CVR) as the first step to better distinguishing patients with radiation necrosis from recurrent glioblastoma compared with patients with newly diagnosed glioblastoma before surgery and radiotherapy. Methods: Eight consecutive patients with primary and secondary brain tumors and a multidisciplinary clinical and radiological diagnosis of radiation necrosis, and fourteen patients with a first diagnosis of glioblastoma underwent BOLD-CVR mapping. For all these patients, the contrast-enhancing lesion was derived from high-resolution T1-weighted MRI and rendered the volume-of-interest (VOI). From this primary VOI, additional 3 mm concentric expanding VOIs up to 30 mm were created for a detailed perilesional BOLD-CVR tissue analysis between the two groups. Receiver operating characteristic curves assessed the discriminative properties of BOLD-CVR for both groups. Results: Mean intralesional BOLD-CVR values were markedly lower in radiation necrosis than in glioblastoma contrast-enhancing lesions (0.001 ± 0.06 vs. 0.057 ± 0.05; p = 0.04). Perilesionally, a characteristic BOLD-CVR pattern was observed for radiation necrosis and glioblastoma patients, with an improvement of BOLD-CVR values in the radiation necrosis group and persisting lower perilesional BOLD-CVR values in glioblastoma patients. The ROC analysis discriminated against both groups when these two parameters were analyzed together (area under the curve: 0.85, 95% CI: 0.65-1.00). Conclusions: In this preliminary analysis, distinctive intralesional and perilesional BOLD-cerebrovascular reactivity patterns are found for radiation necrosis.
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Abstract
Magnetic resonance spectroscopy (MRS), being able to identify and measure some brain components (metabolites) in pathologic lesions and in normal-appearing tissue, offers a valuable additional diagnostic tool to assess several pediatric neurological diseases. In this review we will illustrate the basic principles and clinical applications of brain proton (H1; hydrogen) MRS (H1MRS), by now the only MRS method widely available in clinical practice. Performing H1MRS in the brain is inherently less complicated than in other tissues (e.g., liver, muscle), in which spectra are heavily affected by magnetic field inhomogeneities, respiration artifacts, and dominating signals from the surrounding adipose tissues. H1MRS in pediatric neuroradiology has some advantages over acquisitions in adults (lack of motion due to children sedation and lack of brain iron deposition allow optimal results), but it requires a deep knowledge of pediatric pathologies and familiarity with the developmental changes in spectral patterns, particularly occurring in the first two years of life. Examples from our database, obtained mainly from a 1.5 Tesla clinical scanner in a time span of 15 years, will demonstrate the efficacy of H1MRS in the diagnosis of a wide range of selected pediatric pathologies, like brain tumors, infections, neonatal hypoxic-ischemic encephalopathy, metabolic and white matter disorders.
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Affiliation(s)
- Roberto Liserre
- Department of Radiology, Neuroradiology Unit, ASST Spedali Civili University Hospital, Brescia, Italy
| | - Lorenzo Pinelli
- Department of Radiology, Neuroradiology Unit, ASST Spedali Civili University Hospital, Brescia, Italy
| | - Roberto Gasparotti
- Neuroradiology Unit, Department of Medical-Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
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Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
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Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
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Role of Dynamic Susceptibility Contrast Perfusion MRI in Glioma Progression Evaluation. JOURNAL OF ONCOLOGY 2021; 2021:1696387. [PMID: 33628239 PMCID: PMC7886570 DOI: 10.1155/2021/1696387] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 01/23/2021] [Accepted: 01/28/2021] [Indexed: 11/18/2022]
Abstract
Accurately and quickly differentiating true progression from pseudoprogression in glioma patients is still a challenge. This study aims to explore if dynamic susceptibility contrast- (DSC-) MRI can improve the evaluation of glioma progression. We enrolled 65 glioma patients with suspected gadolinium-enhancing lesion. Longitudinal MRI follow-up (mean 590 days, range: 210-2670 days) or re-operation (n = 3) was used to confirm true progression (n = 51) and pseudoprogression (n = 14). We assessed the diagnostic performance of each MRI variable and the different combinations. Our results showed that the relative cerebral blood volume (rCBV) in the true progression group (1.094, 95%CI: 1.135-1.636) was significantly higher than that of the pseudoprogression group (0.541 ± 0.154) (p < 0.001). Among the 18 patients who had serial DSC-MRI, the rCBV of the progression group (0.480, 95%CI: 0.173-0.810) differed significantly from pseudoprogression (-0.083, 95%CI: -1.138-0.620) group (p=0.015). With an rCBV threshold of 0.743, the sensitivity and specificity for discriminating true progression from pseudoprogression were 76.5% and 92.9%, respectively. The Cho/Cr and Cho/NAA ratios of the true progression group (2.520, 95%CI: 2.331-2.773; 2.414 ± 0.665, respectively) were higher than those of the pseudoprogression group (1.719 ± 0.664; 1.499 ± 0.500, respectively) ((p=0.001), (p < 0.001), respectively). The areas under ROC curve (AUCs) of enhancement pattern, MRS, and DSC-MRI for the differentiation were 0.782, 0.881, and 0.912, respectively. Interestingly, when combined enhancement pattern, MRS, and DSC-MRI variables, the AUC was 0.965 and achieved sensitivity 90.2% and specificity 100.0%. Our results suggest that DSC-MRI can significantly improve the diagnostic performance for identifying glioma progression. DSC-MRI combined with conventional MRI may promptly distinguish true gliomas progression from pseudoprogression when the suspected gadolinium-enhancing lesion was found, without the need for a long-term follow-up.
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35
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Park YW, Choi D, Park JE, Ahn SS, Kim H, Chang JH, Kim SH, Kim HS, Lee SK. Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation. Sci Rep 2021; 11:2913. [PMID: 33536499 PMCID: PMC7858615 DOI: 10.1038/s41598-021-82467-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 01/05/2021] [Indexed: 12/19/2022] Open
Abstract
The purpose of this study was to establish a high-performing radiomics strategy with machine learning from conventional and diffusion MRI to differentiate recurrent glioblastoma (GBM) from radiation necrosis (RN) after concurrent chemoradiotherapy (CCRT) or radiotherapy. Eighty-six patients with GBM were enrolled in the training set after they underwent CCRT or radiotherapy and presented with new or enlarging contrast enhancement within the radiation field on follow-up MRI. A diagnosis was established either pathologically or clinicoradiologically (63 recurrent GBM and 23 RN). Another 41 patients (23 recurrent GBM and 18 RN) from a different institution were enrolled in the test set. Conventional MRI sequences (T2-weighted and postcontrast T1-weighted images) and ADC were analyzed to extract 263 radiomic features. After feature selection, various machine learning models with oversampling methods were trained with combinations of MRI sequences and subsequently validated in the test set. In the independent test set, the model using ADC sequence showed the best diagnostic performance, with an AUC, accuracy, sensitivity, specificity of 0.80, 78%, 66.7%, and 87%, respectively. In conclusion, the radiomics models models using other MRI sequences showed AUCs ranging from 0.65 to 0.66 in the test set. The diffusion radiomics may be helpful in differentiating recurrent GBM from RN..
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Affiliation(s)
- Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea
| | - Dongmin Choi
- Department of Computer Science, Yonsei University, Seoul, South Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, South Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.
| | - Hwiyoung Kim
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, South Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea
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36
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Strauss SB, Meng A, Ebani EJ, Chiang GC. Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis. Neuroimaging Clin N Am 2021; 31:103-120. [PMID: 33220823 DOI: 10.1016/j.nic.2020.09.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.
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Affiliation(s)
- Sara B Strauss
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Alicia Meng
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Edward J Ebani
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Gloria C Chiang
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA.
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37
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Le Fèvre C, Constans JM, Chambrelant I, Antoni D, Bund C, Leroy-Freschini B, Schott R, Cebula H, Noël G. Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review. Part 2 - Radiological features and metric markers. Crit Rev Oncol Hematol 2021; 159:103230. [PMID: 33515701 DOI: 10.1016/j.critrevonc.2021.103230] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/10/2021] [Accepted: 01/16/2021] [Indexed: 12/28/2022] Open
Abstract
After chemoradiotherapy for glioblastoma, pseudoprogression can occur and must be distinguished from true progression to correctly manage glioblastoma treatment and follow-up. Conventional treatment response assessment is evaluated via conventional MRI (contrast-enhanced T1-weighted and T2/FLAIR), which is unreliable. The emergence of advanced MRI techniques, MR spectroscopy, and PET tracers has improved pseudoprogression diagnostic accuracy. This review presents a literature review of the different imaging techniques and potential imaging biomarkers to differentiate pseudoprogression from true progression.
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Affiliation(s)
- Clara Le Fèvre
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Jean-Marc Constans
- Department of Radiology, Amiens-Picardie University Hospital, 1 rond-point du Professeur Christian Cabrol, 80054, Amiens Cedex 1, France.
| | - Isabelle Chambrelant
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Delphine Antoni
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Caroline Bund
- Department of Nuclear Medicine, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Benjamin Leroy-Freschini
- Department of Nuclear Medicine, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Roland Schott
- Departement of Medical Oncology, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Hélène Cebula
- Departement of Neurosurgery, Hautepierre University Hospital, 1, avenue Molière, 67200, Strasbourg, France.
| | - Georges Noël
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
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38
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Cui Y, Zeng W, Jiang H, Ren X, Lin S, Fan Y, Liu Y, Zhao J. Higher Cho/NAA Ratio in Postoperative Peritumoral Edema Zone Is Associated With Earlier Recurrence of Glioblastoma. Front Neurol 2020; 11:592155. [PMID: 33343496 PMCID: PMC7747764 DOI: 10.3389/fneur.2020.592155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 11/17/2020] [Indexed: 12/13/2022] Open
Abstract
Objective: To explore the prognostic significance of metabolic parameters in postoperative peritumoral edema zone (PEZ) of patients with glioblastoma (GBM) based on proton magnetic resonance spectroscopy (MRS). Methods: The postoperative MRS data of 67 patients with GBM from Beijing Tiantan Hospital were retrospectively reviewed. Metabolite ratios including Cho/NAA, Cho/Cr, and NAA/Cr in both postoperative PEZ and contralateral normal brain region were recorded. Log-rank analysis and Cox regression model were used to identify parameters correlated with progression-free survival (PFS) and overall survival (OS). Results: Compared with the contralateral normal brain region, postoperative PEZ showed a lower ratio of NAA/Cr (1.20 ± 0.42 vs. 1.81 ± 0.48, P < 0.001), and higher ratios of Cho/Cr and Cho/NAA (1.36 ± 0.44 vs. 1.02 ± 0.27, P < 0.001 and 1.32 ± 0.59 vs. 0.57 ± 0.14, P < 0.001). Both the ratios of Cho/NAA and NAA/Cr were identified as prognostic factors in univariate analysis (P < 0.05), while only Cho/NAA ≥ 1.31 was further confirmed as an independent risk factor for early recurrence in the Cox regression model (P < 0.01). According to the factors of MGMT promoter unmethylation, without radiotherapy and Cho/NAA ≥ 1.31, a prognostic scoring scale for GBM was established, which could divide patients into low-risk, moderate-risk, and high-risk groups. There was a significant difference of survival rate between the three groups (P < 0.001). Conclusions: Higher Cho/NAA ratio in the postoperative PEZ of GBM predicts earlier recurrence and is associated with poor prognosis. The prognostic scoring scale based on clinical, molecular and metabolic parameters of patients with GBM can help doctors to make more precise prediction of survival time and to adjust therapeutic regimens.
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Affiliation(s)
- Yong Cui
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Wei Zeng
- Department of Neurosurgery, Beijing Electric Power Hospital, Beijing, China
| | - Haihui Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Song Lin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Yanzhu Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Yapeng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases, Center of Brain Tumor, Beijing Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China
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39
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Katsura M, Sato J, Akahane M, Furuta T, Mori H, Abe O. Recognizing Radiation-induced Changes in the Central Nervous System: Where to Look and What to Look For. Radiographics 2020; 41:224-248. [PMID: 33216673 DOI: 10.1148/rg.2021200064] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Radiation therapy (RT) continues to play a central role as an effective therapeutic modality for a variety of tumors and vascular malformations in the central nervous system. Although the planning and delivery techniques of RT have evolved substantially during the past few decades, the structures surrounding the target lesion are inevitably exposed to radiation. A wide variety of radiation-induced changes may be observed at posttreatment imaging, which may be confusing when interpreting images. Histopathologically, radiation can have deleterious effects on the vascular endothelial cells as well as on neuroglial cells and their precursors. In addition, radiation induces oxidative stress and inflammation, leading to a cycle of further cellular toxic effects and tissue damage. On the basis of the time of expression, radiation-induced injury can be divided into three phases: acute, early delayed, and late delayed. Acute and early delayed injuries are usually transient and reversible, whereas late delayed injuries are generally irreversible. The authors provide a comprehensive review of the timeline and expected imaging appearances after RT, including the characteristic imaging features after RT with concomitant chemotherapy. Specific topics discussed are imaging features that help distinguish expected posttreatment changes from recurrent disease, followed by a discussion on the role of advanced imaging techniques. Knowledge of the RT plan, the amount of normal structures included, the location of the target lesion, and the amount of time elapsed since RT is highly important at follow-up imaging, and the reporting radiologist should be able to recognize the characteristic imaging features after RT and differentiate these findings from tumor recurrence. ©RSNA, 2020.
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Affiliation(s)
- Masaki Katsura
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
| | - Jiro Sato
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
| | - Masaaki Akahane
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
| | - Toshihiro Furuta
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
| | - Harushi Mori
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
| | - Osamu Abe
- From the Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan (M.K., J.S., T.F., H.M., O.A.); and Department of Radiology, School of Medicine, International University of Health and Welfare, Chiba, Japan (M.A.)
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40
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Gao Y, Xiao X, Han B, Li G, Ning X, Wang D, Cai W, Kikinis R, Berkovsky S, Di Ieva A, Zhang L, Ji N, Liu S. Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation. JMIR Med Inform 2020; 8:e19805. [PMID: 33200991 PMCID: PMC7708085 DOI: 10.2196/19805] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 08/31/2020] [Accepted: 09/27/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients. OBJECTIVE This research aims to develop a deep learning methodology for automated differentiation of tumor recurrence from radiation necrosis based on routine magnetic resonance imaging (MRI) scans. METHODS In this retrospective study, 146 patients who underwent radiation therapy after glioma resection and presented with suspected recurrent lesions at the follow-up MRI examination were selected for analysis. Routine MRI scans were acquired from each patient, including T1, T2, and gadolinium-contrast-enhanced T1 sequences. Of those cases, 96 (65.8%) were confirmed as glioma recurrence on postsurgical pathological examination, while 50 (34.2%) were diagnosed as necrosis. A light-weighted deep neural network (DNN) (ie, efficient radionecrosis neural network [ERN-Net]) was proposed to learn radiological features of gliomas and necrosis from MRI scans. Sensitivity, specificity, accuracy, and area under the curve (AUC) were used to evaluate performance of the model in both image-wise and subject-wise classifications. Preoperative diagnostic performance of the model was also compared to that of the state-of-the-art DNN models and five experienced neurosurgeons. RESULTS DNN models based on multimodal MRI outperformed single-modal models. ERN-Net achieved the highest AUC in both image-wise (0.915) and subject-wise (0.958) classification tasks. The evaluated DNN models achieved an average sensitivity of 0.947 (SD 0.033), specificity of 0.817 (SD 0.075), and accuracy of 0.903 (SD 0.026), which were significantly better than the tested neurosurgeons (P=.02 in sensitivity and P<.001 in specificity and accuracy). CONCLUSIONS Deep learning offers a useful computational tool for the differential diagnosis between recurrent gliomas and necrosis. The proposed ERN-Net model, a simple and effective DNN model, achieved excellent performance on routine MRI scans and showed a high clinical applicability.
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Affiliation(s)
- Yang Gao
- Beijing Academy of Quantum Information Sciences, Beijing, China
| | - Xiong Xiao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bangcheng Han
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China
| | - Guilin Li
- Department of Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaolin Ning
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China
| | - Defeng Wang
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China
| | - Weidong Cai
- School of Computer Science, The University of Sydney, Sydney, Australia
| | - Ron Kikinis
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
- Department of Computer Science, University of Bremen, Bremen, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Shlomo Berkovsky
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
| | - Antonio Di Ieva
- Computational NeuroSurgery Lab, Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia
| | - Liwei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Nan Ji
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Sidong Liu
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
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Booth TC, Luis A, Brazil L, Thompson G, Daniel RA, Shuaib H, Ashkan K, Pandey A. Glioblastoma post-operative imaging in neuro-oncology: current UK practice (GIN CUP study). Eur Radiol 2020; 31:2933-2943. [PMID: 33151394 PMCID: PMC8043861 DOI: 10.1007/s00330-020-07387-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/13/2020] [Accepted: 10/07/2020] [Indexed: 12/14/2022]
Abstract
OBJECTIVES MRI remains the preferred imaging investigation for glioblastoma. Appropriate and timely neuroimaging in the follow-up period is considered to be important in making management decisions. There is a paucity of evidence-based information in current UK, European and international guidelines regarding the optimal timing and type of neuroimaging following initial neurosurgical treatment. This study assessed the current imaging practices amongst UK neuro-oncology centres, thus providing baseline data and informing future practice. METHODS The lead neuro-oncologist, neuroradiologist and neurosurgeon from every UK neuro-oncology centre were invited to complete an online survey. Participants were asked about current and ideal imaging practices following initial treatment. RESULTS Ninety-two participants from all 31 neuro-oncology centres completed the survey (100% response rate). Most centres routinely performed an early post-operative MRI (87%, 27/31), whereas only a third performed a pre-radiotherapy MRI (32%, 10/31). The number and timing of scans routinely performed during adjuvant TMZ treatment varied widely between centres. At the end of the adjuvant period, most centres performed an MRI (71%, 22/31), followed by monitoring scans at 3 monthly intervals (81%, 25/31). Additional short-interval imaging was carried out in cases of possible pseudoprogression in most centres (71%, 22/31). Routine use of advanced imaging was infrequent; however, the addition of advanced sequences was the most popular suggestion for ideal imaging practice, followed by changes in the timing of EPMRI. CONCLUSION Variations in neuroimaging practices exist after initial glioblastoma treatment within the UK. Multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment. KEY POINTS • Variations in imaging practices exist in the frequency, timing and type of interval neuroimaging after initial treatment of glioblastoma within the UK. • Large, multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment.
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Affiliation(s)
- Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK. .,Department of Neuroradiology Ruskin Wing, King's College Hospital NHS Foundation Trust, London, SE5 9RS, UK.
| | - Aysha Luis
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK.,Department of Neuroradiology, National Hospital For Neurology and Neurosrgery, London, WC1N 3BG, UK
| | - Lucy Brazil
- Department of Oncology, Guy's and St Thomas' NHS Foundation Trust, London, SE1 7EH, UK
| | - Gerry Thompson
- Centre for Clinical Brain Sciences, Edinburgh, EH16 4SB, UK
| | - Rachel A Daniel
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Haris Shuaib
- Department of Medical Physics, Guy's & St. Thomas' NHS Foundation Trust, London, SE1 7EH, UK.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, SE5 9RS, UK
| | - Anmol Pandey
- Faculty of Life Sciences and Medicine, King's College London Strand, London, WC2R 2LS, UK
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42
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Somme F, Bender L, Namer IJ, Noël G, Bund C. Usefulness of 18F-FDOPA PET for the management of primary brain tumors: a systematic review of the literature. Cancer Imaging 2020; 20:70. [PMID: 33023662 PMCID: PMC7541204 DOI: 10.1186/s40644-020-00348-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 09/21/2020] [Indexed: 11/30/2022] Open
Abstract
Contrast-enhanced magnetic resonance imaging is currently the standard of care in the management of primary brain tumors, although certain limitations remain. Metabolic imaging has proven useful for an increasing number of indications in oncology over the past few years, most particularly 18F-FDG PET/CT. In neuro-oncology, 18F-FDG was insufficient to clearly evaluate brain tumors. Amino-acid radiotracers such as 18F-FDOPA were then evaluated in the management of brain diseases, notably tumoral diseases. Even though European guidelines on the use of amino-acid PET in gliomas have been published, it is crucial that future studies standardize acquisition and interpretation parameters. The aim of this article was to systematically review the potential effect of this metabolic imaging technique in numerous steps of the disease: primary and recurrence diagnosis, grading, local and systemic treatment assessment, and prognosis. A total of 41 articles were included and analyzed in this review. It appears that 18F-FDOPA PET holds promise as an effective additional tool in the management of gliomas. More consistent prospective studies are still needed.
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Affiliation(s)
- François Somme
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France.
| | - Laura Bender
- Oncology Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
| | - Izzie Jacques Namer
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
- Strasbourg University, Unistra/CNRS UMR 7237, Strasbourg, France
| | - Georges Noël
- Radiotherapy Department, Paul Strauss Comprehensive Cancer Center, 3, rue de la porte de l'hôpital, F-67065, Strasbourg, France
- Strasbourg University, CNRS, IPHC UMR 7178, Centre Paul Strauss, UNICANCER, F-67000, Strasbourg, France
| | - Caroline Bund
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
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43
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Raza IJ, Tingate CA, Gkolia P, Romero L, Tee JW, Hunn MK. Blood Biomarkers of Glioma in Response Assessment Including Pseudoprogression and Other Treatment Effects: A Systematic Review. Front Oncol 2020; 10:1191. [PMID: 32923382 PMCID: PMC7456864 DOI: 10.3389/fonc.2020.01191] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 06/12/2020] [Indexed: 12/21/2022] Open
Abstract
Imaging-based monitoring of disease burden in glioma patients is frequently confounded by treatment effects. Circulating biomarkers could theoretically augment imaging-based response monitoring. This systematic review aimed to present and evaluate evidence for differential expression and diagnostic accuracy of circulating biomarkers with respect to outcomes of tumor response, progression, stable disease, and treatment effects (pseudoprogression, radionecrosis, pseudoresponse, and pseudolesions) in patients undergoing treatment for World Health Organization grades II-IV diffuse astrocytic and oligodendroglial tumors. MEDLINE, EMBASE, Web Of Science, and SCOPUS databases were searched until August 18, 2019, for observational or diagnostic studies on multiple circulating biomarker types: extracellular vesicles, circulating nucleic acids, circulating tumor cells, circulating proteins, and metabolites, angiogenesis related cells, immune cells, and other cell lines. Methodological quality of included studies was assessed using an adapted Quality Assessment of Diagnostic Accuracy Studies-2 tool, and level of evidence (IA-IVD) for individual biomarkers was evaluated using an adapted framework from the National Comprehensive Cancer Network guidelines on evaluating tumor marker utility. Of 13,202 unique records, 58 studies met the inclusion criteria. One hundred thirty-three distinct biomarkers were identified in a total of 1,853 patients across various treatment modalities. Fifteen markers for response, progression, or stable disease and five markers for pseudoprogression or radionecrosis reached level IB. No biomarkers reached level IA. Only five studies contained data for diagnostic accuracy measures. Overall methodological quality of included studies was low. While extensive data on biomarker dysregulation in varying response categories were reported, no biomarkers ready for clinical application were identified. Further assay refinement and evaluation in larger cohorts with diagnostic accuracy study designs are required. PROSPERO Registration: CRD42018110658.
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Affiliation(s)
- Istafa J Raza
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC, Australia
| | - Campbell A Tingate
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC, Australia
| | - Panagiota Gkolia
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC, Australia
| | - Lorena Romero
- The Ian Potter Library, The Alfred Hospital, Melbourne, VIC, Australia
| | - Jin W Tee
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC, Australia.,Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Martin K Hunn
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC, Australia.,Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
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Abdalla G, Hammam A, Anjari M, D'Arco DF, Bisdas DS. Glioma surveillance imaging: current strategies, shortcomings, challenges and outlook. BJR Open 2020; 2:20200009. [PMID: 33178973 PMCID: PMC7594888 DOI: 10.1259/bjro.20200009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 05/29/2020] [Accepted: 06/01/2020] [Indexed: 01/11/2023] Open
Abstract
Inaccurate assessment of surveillance imaging to assess response to glioma therapy may have life-changing consequences. Varied management plans including chemotherapy, radiotherapy or immunotherapy may all contribute to heterogeneous post-treatment appearances and the overlap between the morphological features of pseudoprogression, pseudoresponse and radiation necrosis can make their discrimination very challenging. Therefore, there has been a drive to develop objective strategies for post-treatment assessment of brain gliomas. This review discusses the most important of these approaches such as the RANO "Response Assessment in Neuro-Oncology", iRANO "Immunotherapy Response Assessment in Neuro-Oncology" and RAPNO "Response Assessment in Paediatric Neuro-Oncology" models. In addition to these systematic approaches for glioma surveillance, the relatively limited information provided by conventional imaging modalities alone has motivated the development of novel advanced magnetic resonance (MR) and metabolic imaging methods for further discrimination between viable tumour and treatment induced changes. Multiple clinical trials and meta-analyses have investigated the diagnostic performance of these novel techniques in the follow up of brain gliomas, including both single modality descriptive studies and comparative imaging assessment. In this manuscript, we review the literature and discuss the promises and pitfalls of frequently studied modalities in glioma surveillance imaging, including MR perfusion, MR diffusion and MR spectroscopy. In addition, we evaluate other promising MR techniques such as chemical exchange saturation transfer as well as fludeoxyglucose and non-FDG positron emission tomography techniques.
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Affiliation(s)
- Gehad Abdalla
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Ahmed Hammam
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Mustafa Anjari
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust, London, UK
| | - Dr. Felice D'Arco
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
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Advanced multimodal imaging in differentiating glioma recurrence from post-radiotherapy changes. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2020; 151:281-297. [PMID: 32448612 DOI: 10.1016/bs.irn.2020.03.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Gliomas are the most common malignant primary brain tumor, and their prognosis is extremely poor. Radiotherapy is an important treatment for glioma patients, but the changes caused by radiotherapy have brought difficulties in clinical image evaluation because differentiating glioma recurrence from post-radiotherapy changes including pseudo-progression (PD) and radiation necrosis (RN) remains a challenge. Therefore, accurate and reliable imaging evaluation is very important for making clinical decisions. In recent years, advanced multimodal imaging techniques have been applied to achieve the goal of better differentiating glioma recurrence from post-radiotherapy changes for minimizing errors associated with interpretation of treatment effects. In this review, we discuss the recent applications of advanced multimodal imaging such as diffusion MRI sequences, amide proton transfer MRI sequences, perfusion MRI sequences, MR spectroscopy and multinuclides PET/CT in the evaluation of post-radiotherapy treatment response in glioma patients and highlight their potential role in differentiating post-radiotherapy changes from glioma recurrence.
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Gonçalves FG, Chawla S, Mohan S. Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma. J Magn Reson Imaging 2020; 52:978-997. [PMID: 32190946 DOI: 10.1002/jmri.27105] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/28/2020] [Accepted: 01/30/2020] [Indexed: 12/14/2022] Open
Abstract
Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.
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Affiliation(s)
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Lv Y, Zhou J, Lv X, Tian L, He H, Liu Z, Wu Y, Han L, Sun M, Yang Y, Guo C, Li C, Zhang R, Xie C, Chen Y, Chen Z. Dual-energy spectral CT quantitative parameters for the differentiation of Glioma recurrence from treatment-related changes: a preliminary study. BMC Med Imaging 2020; 20:5. [PMID: 31948400 PMCID: PMC6966828 DOI: 10.1186/s12880-019-0406-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 12/24/2019] [Indexed: 11/18/2022] Open
Abstract
Background Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation. Methods Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Zeff and Zeff-N, respectively); spectral Hounsfield unit curve (λHU) slope; and iodine and normalized iodine concentration (IC and ICN, respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value. Results Examination of pre-contrast λHU, Zeff, Zeff-N, IC, ICN, and venous phase ICN showed no significant differences in quantitative parameters (P > 0.05). Venous phase λHU, Zeff, Zeff-N, and IC in glioma recurrence were higher than in treatment-related changes (P < 0.001). The optimal venous phase threshold was 1.03, 7.75, 1.04, and 2.85 mg/cm3, achieving 66.7, 91.7, 83.3, and 91.7% sensitivity; 100.0, 77.8, 88.9, and 77.8% specificity; 100.0, 73.3, 83.3, and 73.3% PPV; 81.8, 93.3, 88.9, and 93.3% NPV; and 86.7, 83.3, 86.7, and 83.3% accuracy, respectively. The respective areas under the curve (AUCs) were 0.912, 0.912, 0.931, and 0.910 in glioma recurrence and treatment-related changes. Conclusions Glioma recurrence could be potentially differentiated from treatment-related changes based on quantitative values measured by dual-energy spectral CT imaging.
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Affiliation(s)
- Yanchun Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Jian Zhou
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Xiaofei Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Li Tian
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Haoqiang He
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Zhigang Liu
- Department of head and neck oncology, Phase 1 clinical trial ward, The cancer center of the fifth affiliated hospital of Sun Yat-sen University, Zhuhai, 519001, China
| | - Yi Wu
- Department of Radiology, Shantou Central Hospital, No.114 Waima Road, Shantou, 515041, Guangdong, China
| | - Lujun Han
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Meili Sun
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Yadi Yang
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Chengcheng Guo
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Cong Li
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Rong Zhang
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Chuanmiao Xie
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Yinsheng Chen
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China.
| | - Zhongping Chen
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China.
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Leao DJ, Craig PG, Godoy LF, Leite CC, Policeni B. Response Assessment in Neuro-Oncology Criteria for Gliomas: Practical Approach Using Conventional and Advanced Techniques. AJNR Am J Neuroradiol 2020; 41:10-20. [PMID: 31857322 PMCID: PMC6975322 DOI: 10.3174/ajnr.a6358] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 10/29/2019] [Indexed: 01/08/2023]
Abstract
The Response Assessment in Neuro-Oncology criteria were developed as an objective tool for radiologic assessment of treatment response in high-grade gliomas. Imaging plays a critical role in the management of the patient with glioma, from initial diagnosis to posttreatment follow-up, which can be particularly challenging for radiologists. Interpreting findings after surgery, radiation, and chemotherapy requires profound knowledge about the tumor biology, as well as the peculiar changes expected to ensue as a consequence of each treatment technique. In this article, we discuss the imaging findings associated with tumor progression, tumor response, pseudoprogression, and pseudoresponse according to the Response Assessment in Neuro-Oncology criteria for high-grade and lower-grade gliomas. We describe relevant practical issues when evaluating patients with glioma, such as the need for imaging in the first 48 hours, the radiation therapy planning and isodose curves, the significance of T2/FLAIR hyperintense lesions, the impact of the timing for the evaluation after radiation therapy, and the definition of progressive disease on the histologic specimen. We also illustrate the correlation among the findings on conventional MR imaging with advanced techniques, such as perfusion, diffusion-weighted imaging, spectroscopy, and amino acid PET. Because many of the new lesions represent a mixture of tumor cells and tissue with radiation injury, the radiologist aims to identify the predominant component of the lesion and categorize the findings according to Response Assessment in Neuro-Oncology criteria so that the patient can receive the best treatment.
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Affiliation(s)
- D J Leao
- From the Cancer Hospital of Federal University of Uberlandia (D.J.L.), Uberlandia, Brazil
| | - P G Craig
- Department of Radiology, (P.G.C., B.P.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - L F Godoy
- Department of Diagnostic Radiology (L.F.G.), Hospital Sirio-Libanes, Sao Paulo, Brazil
- Department of Neuroradiology (L.F.G., C.C.L.), Faculdade de Medicina Instituto de Radiologia, Universidade de Sao Paulo Neuroradiology, Sao Paulo, Brazil
| | - C C Leite
- Department of Neuroradiology (L.F.G., C.C.L.), Faculdade de Medicina Instituto de Radiologia, Universidade de Sao Paulo Neuroradiology, Sao Paulo, Brazil
| | - B Policeni
- Department of Radiology, (P.G.C., B.P.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Zhang L. Glioma characterization based on magnetic resonance imaging: Challenge overview and future perspective. GLIOMA 2020. [DOI: 10.4103/glioma.glioma_9_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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50
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Okuchi S, Hammam A, Golay X, Kim M, Thust S. Endogenous Chemical Exchange Saturation Transfer MRI for the Diagnosis and Therapy Response Assessment of Brain Tumors: A Systematic Review. Radiol Imaging Cancer 2020; 2:e190036. [PMID: 33778693 PMCID: PMC7983695 DOI: 10.1148/rycan.2020190036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 09/13/2019] [Accepted: 10/21/2019] [Indexed: 01/09/2023]
Abstract
Purpose To generate a narrative synthesis of published data on the use of endogenous chemical exchange saturation transfer (CEST) MRI in brain tumors. Materials and Methods A systematic database search (PubMed, Ovid Embase, Cochrane Library) was used to collate eligible studies. Two researchers independently screened publications according to predefined exclusion and inclusion criteria, followed by comprehensive data extraction. All included studies were subjected to a bias risk assessment using the Quality Assessment of Diagnostic Accuracy Studies tool. Results The electronic database search identified 430 studies, of which 36 fulfilled the inclusion criteria. The final selection of included studies was categorized into five groups as follows: grading gliomas, 19 studies (area under the receiver operating characteristic curve [AUC], 0.500-1.000); predicting molecular subtypes of gliomas, five studies (AUC, 0.610-0.920); distinction of different brain tumor types, seven studies (AUC, 0.707-0.905); therapy response assessment, three studies (AUC not given); and differentiating recurrence from treatment-related changes, five studies (AUC, 0.880-0.980). A high bias risk was observed in a substantial proportion of studies. Conclusion Endogenous CEST MRI offers valuable, potentially unique information in brain tumors, but its diagnostic accuracy remains incompletely known. Further research is required to assess the method's role in support of molecular genetic diagnosis, to investigate its use in the posttreatment phase, and to compare techniques with a view to standardization.Keywords: Brain/Brain Stem, MR-Imaging, Neuro-OncologySupplemental material is available for this article.© RSNA, 2020.
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Affiliation(s)
- Sachi Okuchi
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Ahmed Hammam
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Xavier Golay
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Mina Kim
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Stefanie Thust
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
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