RSS-Feed abonnieren

DOI: 10.1055/a-2719-5058
Imaging in Neuro-oncology
Autor*innen
Funding Information This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748 and the K12 CA184746 grant.
Abstract
Brain tumors are a diverse group of neoplasms that vary widely in treatment and prognosis. Imaging serves as the cornerstone of diagnosis, monitoring response to treatment and identifying progression of disease in neuro-oncologic care. This review outlines current and emerging imaging modalities with a focus on clinical application in glioma, meningioma, and brain metastasis. We cover standard imaging modalities, advanced magnetic resonance techniques such as perfusion and spectroscopic imaging, and nuclear imaging with positron emission tomography (PET), including amino acid PET. We summarize the standardized Response Assessment in Neuro-Oncology (RANO) criteria, and explore innovations in radiomics, artificial intelligence, and targeted imaging biomarkers. Finally, we address challenges related to equitable access to advanced imaging. This review provides a practical, clinically focused guide to support neurologists in the imaging-based care of patients with primary or metastatic brain tumors.
Publikationsverlauf
Eingereicht: 07. August 2025
Angenommen: 24. September 2025
Accepted Manuscript online:
13. Oktober 2025
Artikel online veröffentlicht:
30. Oktober 2025
© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA
-
References
- 1 Price M, Ballard C, Benedetti J. et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2017-2021. Neuro-oncol 2024; 26 (Suppl. 06) vi1-vi85
- 2 Nayak L, Lee EQ, Wen PY. Epidemiology of brain metastases. Curr Oncol Rep 2012; 14 (01) 48-54
- 3 Ostrom QT, Wright CH, Barnholtz-Sloan JS. Brain metastases: epidemiology. Handb Clin Neurol 2018; 149: 27-42
- 4 Langen KJ, Galldiks N, Hattingen E, Shah NJ. Advances in neuro-oncology imaging. Nat Rev Neurol 2017; 13 (05) 279-289
- 5 Carl B, Bopp M, Saß B. et al. Reliable navigation registration in cranial and spine surgery based on intraoperative computed tomography. Neurosurg Focus 2019; 47 (06) E11
- 6 Wang M, Song Z. Guidelines for the placement of fiducial points in image-guided neurosurgery. Int J Med Robot 2010; 6 (02) 142-149
- 7 Ellingson BM, Bendszus M, Boxerman J. et al; Jumpstarting Brain Tumor Drug Development Coalition Imaging Standardization Steering Committee. Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials. Neuro-oncol 2015; 17 (09) 1188-1198
- 8 Ellingson BM, Wen PY, Cloughesy TF. Evidence and context of use for contrast enhancement as a surrogate of disease burden and treatment response in malignant glioma. Neuro-oncol 2018; 20 (04) 457-471
- 9 Meier R, Knecht U, Loosli T. et al. Clinical evaluation of a fully-automatic segmentation method for longitudinal brain tumor volumetry. Sci Rep 2016; 6: 23376
- 10 Peiris H, Hayat M, Chen Z, Egan G, Harandi M. A robust volumetric transformer for accurate 3D tumor segmentation. In: Wang L, Dou Q, Fletcher PT, Speidel S, Li S. eds. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. Springer Nature Switzerland; 2022: 162-172
- 11 Rajput S, Kapdi R, Roy M, Raval MS. A triplanar ensemble model for brain tumor segmentation with volumetric multiparametric magnetic resonance images. Healthc Anal (N Y) 2024; 5: 100307
- 12 van den Bent MJ, Cloughesy TF, Ellingson BM. et al. The use of minor response, volumetric assessment, and growth rate kinetics as endpoints in grade 1–3 glioma clinical trials: a RANO perspective. Neuro-oncol 2025; noaf173. Epub ahead of print
- 13 Wen PY, Macdonald DR, Reardon DA. et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 2010; 28 (11) 1963-1972
- 14 Hattingen E, Jurcoane A, Daneshvar K. et al. Quantitative T2 mapping of recurrent glioblastoma under bevacizumab improves monitoring for non-enhancing tumor progression and predicts overall survival. Neuro-oncol 2013; 15 (10) 1395-1404
- 15 Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224 (01) 177-183
- 16 Zulfiqar M, Yousem DM, Lai H. ADC values and prognosis of malignant astrocytomas: does lower ADC predict a worse prognosis independent of grade of tumor?—a meta-analysis. AJR Am J Roentgenol 2013; 200 (03) 624-629
- 17 van Dijken BRJ, van Laar PJ, Holtman GA, van der Hoorn A. Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis. Eur Radiol 2017; 27 (10) 4129-4144
- 18 Yu Y, Ma Y, Sun M, Jiang W, Yuan T, Tong D. Meta-analysis of the diagnostic performance of diffusion magnetic resonance imaging with apparent diffusion coefficient measurements for differentiating glioma recurrence from pseudoprogression. Medicine (Baltimore) 2020; 99 (23) e20270
- 19 Padhani AR, Liu G, Koh DM. et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11 (02) 102-125
- 20 Suh CH, Kim HS, Jung SC, Park JE, Choi CG, Kim SJ. MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis. J Magn Reson Imaging 2019; 50 (02) 560-572
- 21 Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ. Perfusion MRI as a diagnostic biomarker for differentiating glioma from brain metastasis: a systematic review and meta-analysis. Eur Radiol 2018; 28 (09) 3819-3831
- 22 Xu W, Wang Q, Shao A, Xu B, Zhang J. The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: a systematic review and meta-analysis. PLoS One 2017; 12 (03) e0173430
- 23 Okuchi S, Rojas-Garcia A, Ulyte A. et al. Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: a systematic review and meta-analysis. Cancer Med 2019; 8 (12) 5564-5573
- 24 Falk Delgado A, De Luca F, van Westen D, Falk Delgado A. Arterial spin labeling MR imaging for differentiation between high- and low-grade glioma-a meta-analysis. Neuro-oncol 2018; 20 (11) 1450-1461
- 25 Patel P, Baradaran H, Delgado D. et al. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro-oncol 2017; 19 (01) 118-127
- 26 Wan B, Wang S, Tu M, Wu B, Han P, Xu H. The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: a meta-analysis. Medicine (Baltimore) 2017; 96 (11) e6333
- 27 Zhang J, Wang Y, Wang Y. et al. Perfusion magnetic resonance imaging in the differentiation between glioma recurrence and pseudoprogression: a systematic review, meta-analysis and meta-regression. Quant Imaging Med Surg 2022; 12 (10) 4805-4822
- 28 Galldiks N, Kaufmann TJ, Vollmuth P. et al. Challenges, limitations, and pitfalls of PET and advanced MRI in patients with brain tumors: a report of the PET/RANO group. Neuro-oncol 2024; 26 (07) 1181-1194
- 29 Mittal S, Wu Z, Neelavalli J, Haacke EM. Susceptibility-weighted imaging: technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009; 30 (02) 232-252
- 30 Li X, Zhu Y, Kang H. et al. Glioma grading by microvascular permeability parameters derived from dynamic contrast-enhanced MRI and intratumoral susceptibility signal on susceptibility weighted imaging. Cancer Imaging 2015; 15 (01) 4
- 31 Schwarz D, Bendszus M, Breckwoldt MO. Clinical value of susceptibility weighted imaging of brain metastases. Front Neurol 2020; 11: 55
- 32 Kushnirsky M, Nguyen V, Katz JS. et al. Time-delayed contrast-enhanced MRI improves detection of brain metastases and apparent treatment volumes. J Neurosurg 2016; 124 (02) 489-495
- 33 Satvat N, Korczynski O, Müller-Eschner M. et al. A rapid late enhancement MRI protocol improves differentiation between brain tumor recurrence and treatment-related contrast enhancement of brain parenchyma. Cancers (Basel) 2022; 14 (22) 5523
- 34 Jiang R, Du FZ, He C, Gu M, Ke ZW, Li JH. The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis. PLoS One 2014; 9 (11) e112550
- 35 Miloushev VZ, Chow DS, Filippi CG. Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas. AJNR Am J Neuroradiol 2015; 36 (02) 302-308
- 36 Manan AA, Yahya N, Idris Z, Manan HA. The utilization of diffusion tensor imaging as an image-guided tool in brain tumor resection surgery: a systematic review. Cancers (Basel) 2022; 14 (10) 2466
- 37 Bogomolny DL, Petrovich NM, Hou BL, Peck KK, Kim MJJ, Holodny AI. Functional MRI in the brain tumor patient. Top Magn Reson Imaging 2004; 15 (05) 325-335
- 38 Stopa BM, Senders JT, Broekman MLD, Vangel M, Golby AJ. Preoperative functional MRI use in neurooncology patients: a clinician survey. Neurosurg Focus 2020; 48 (02) E11
- 39 Zhu H, Barker PB. MR spectroscopy and spectroscopic imaging of the brain. Methods Mol Biol 2011; 711: 203-226
- 40 Dhermain FG, Hau P, Lanfermann H, Jacobs AH, van den Bent MJ. Advanced MRI and PET imaging for assessment of treatment response in patients with gliomas. Lancet Neurol 2010; 9 (09) 906-920
- 41 Bulik M, Jancalek R, Vanicek J, Skoch A, Mechl M. Potential of MR spectroscopy for assessment of glioma grading. Clin Neurol Neurosurg 2013; 115 (02) 146-153
- 42 Ekici S, Nye JA, Neill SG, Allen JW, Shu H-K, Fleischer CC. Glutamine imaging: a new avenue for glioma management. AJNR Am J Neuroradiol 2022; 43 (01) 11-18
- 43 Rafique Z, Awan MW, Iqbal S. et al. Diagnostic accuracy of magnetic resonance spectroscopy in predicting the grade of glioma keeping histopathology as the gold standard. Cureus 2022; 14 (02) e22056
- 44 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 (02) 189-201
- 45 El-Abtah ME, Talati P, Fu M. et al. Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma. Neurooncol Adv 2022; 4 (01) vdac128
- 46 Choi C, Ganji SK, DeBerardinis RJ. et al. 2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas. Nat Med 2012; 18 (04) 624-629
- 47 Jørgensen SH, Bøgh N, Hansen E, Væggemose M, Wiggers H, Laustsen C. Hyperpolarized MRI—an update and future perspectives. Semin Nucl Med 2022; 52 (03) 374-381
- 48 Deh K, Zhang G, Park AH. et al. First in-human evaluation of [1-13C]pyruvate in D2O for hyperpolarized MRI of the brain: a safety and feasibility study. Magn Reson Med 2024; 91 (06) 2559-2567
- 49 Miloushev VZ, Granlund KL, Boltyanskiy R. et al. Metabolic imaging of the human brain with hyperpolarized 13C pyruvate demonstrates 13C lactate production in brain tumor patients. Cancer Res 2018; 78 (14) 3755-3760
- 50 Berger A. How does it work? Positron emission tomography. BMJ 2003; 326 (7404) 1449
- 51 Liberti MV, Locasale JW. The Warburg effect: how does it benefit cancer cells?. Trends Biochem Sci 2016; 41 (03) 211-218
- 52 Verger A, Langen KJ. PET imaging in glioblastoma: use in clinical practice. In: De Vleeschouwer S. ed. Glioblastoma. Codon Publications; 2017. . Accessed August 1, 2025 at: http://www.ncbi.nlm.nih.gov/books/NBK469986/
- 53 Ninatti G, Pini C, Gelardi F, Sollini M, Chiti A. The role of PET imaging in the differential diagnosis between radiation necrosis and recurrent disease in irradiated adult-type diffuse gliomas: a systematic review. Cancers (Basel) 2023; 15 (02) 364
- 54 Spence AM, Muzi M, Graham MM. et al. 2-[(18)F]Fluoro-2-deoxyglucose and glucose uptake in malignant gliomas before and after radiotherapy: correlation with outcome. Clin Cancer Res 2002; 8 (04) 971-979
- 55 De Witte O, Lefranc F, Levivier M, Salmon I, Brotchi J, Goldman S. FDG-PET as a prognostic factor in high-grade astrocytoma. J Neurooncol 2000; 49 (02) 157-163
- 56 Colavolpe C, Metellus P, Mancini J. et al. Independent prognostic value of pre-treatment 18-FDG-PET in high-grade gliomas. J Neurooncol 2012; 107 (03) 527-535
- 57 Bai JW, Qiu SQ, Zhang GJ. Molecular and functional imaging in cancer-targeted therapy: current applications and future directions. Signal Transduct Target Ther 2023; 8 (01) 89
- 58 Omuro A, Beal K, Gutin P. et al. Phase II study of bevacizumab, temozolomide, and hypofractionated stereotactic radiotherapy for newly diagnosed glioblastoma. Clin Cancer Res 2014; 20 (19) 5023-5031
- 59 Zou Y, Tong J, Leng H, Jiang J, Pan M, Chen Z. Diagnostic value of using 18F-FDG PET and PET/CT in immunocompetent patients with primary central nervous system lymphoma: a systematic review and meta-analysis. Oncotarget 2017; 8 (25) 41518-41528
- 60 Krebs S, Mauguen A, Yildirim O. et al. Prognostic value of [18F]FDG PET/CT in patients with CNS lymphoma receiving ibrutinib-based therapies. Eur J Nucl Med Mol Imaging 2021; 48 (12) 3940-3950
- 61 Albano D, Bertoli M, Battistotti M. et al. Prognostic role of pretreatment 18F-FDG PET/CT in primary brain lymphoma. Ann Nucl Med 2018; 32 (08) 532-541
- 62 Kosaka N, Tsuchida T, Uematsu H, Kimura H, Okazawa H, Itoh H. 18F-FDG PET of common enhancing malignant brain tumors. AJR Am J Roentgenol 2008; 190 (06) W365-9
- 63 Galldiks N, Langen KJ, Albert NL. et al. PET imaging in patients with brain metastasis-report of the RANO/PET group. Neuro-oncol 2019; 21 (05) 585-595
- 64 Omuro AM, Leite CC, Mokhtari K, Delattre JY. Pitfalls in the diagnosis of brain tumours. Lancet Neurol 2006; 5 (11) 937-948
- 65 Albert NL, Weller M, Suchorska B. et al. Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro-oncol 2016; 18 (09) 1199-1208
- 66 Albert NL, Galldiks N, Ellingson BM. et al. PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group. Lancet Oncol 2024; 25 (01) e29-e41
- 67 Wiriyasermkul P, Nagamori S, Tominaga H. et al. Transport of 3-fluoro-L-α-methyl-tyrosine by tumor-upregulated L-type amino acid transporter 1: a cause of the tumor uptake in PET. J Nucl Med 2012; 53 (08) 1253-1261
- 68 Papin-Michault C, Bonnetaud C, Dufour M. et al. Study of LAT1 expression in brain metastases: towards a better understanding of the results of positron emission tomography using amino acid tracers. PLoS One 2016; 11 (06) e0157139
- 69 Ono M, Oka S, Okudaira H. et al. Comparative evaluation of transport mechanisms of trans-1-amino-3-[18F]fluorocyclobutanecarboxylic acid and L-[methyl-11C]methionine in human glioma cell lines. Brain Res 2013; 1535: 24-37
- 70 Dunet V, Rossier C, Buck A, Stupp R, Prior JO. Performance of 18F-fluoro-ethyl-tyrosine (18F-FET) PET for the differential diagnosis of primary brain tumor: a systematic review and Metaanalysis. J Nucl Med 2012; 53 (02) 207-214
- 71 Floeth FW, Pauleit D, Sabel M. et al. 18F-FET PET differentiation of ring-enhancing brain lesions. J Nucl Med 2006; 47 (05) 776-782
- 72 Kang SY, Jang Y, Cho MS. et al. 18F-FET PET/CT as a diagnostic tool for brain abscess. Clin Nucl Med 2021; 46 (10) e503-e506
- 73 Karunanithi S, Sharma P, Kumar A. et al. Comparative diagnostic accuracy of contrast-enhanced MRI and (18)F-FDOPA PET-CT in recurrent glioma. Eur Radiol 2013; 23 (09) 2628-2635
- 74 Fueger BJ, Czernin J, Cloughesy T. et al. Correlation of 6-18F-fluoro-L-dopa PET uptake with proliferation and tumor grade in newly diagnosed and recurrent gliomas. J Nucl Med 2010; 51 (10) 1532-1538
- 75 Kracht LW, Miletic H, Busch S. et al. Delineation of brain tumor extent with [11C]L-methionine positron emission tomography: local comparison with stereotactic histopathology. Clin Cancer Res 2004; 10 (21) 7163-7170
- 76 Tripathi M, Sharma R, D'Souza M. et al. Comparative evaluation of F-18 FDOPA, F-18 FDG, and F-18 FLT-PET/CT for metabolic imaging of low grade gliomas. Clin Nucl Med 2009; 34 (12) 878-883
- 77 Pauleit D, Floeth F, Hamacher K. et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 2005; 128 (Pt 3): 678-687
- 78 Becherer A, Karanikas G, Szabó M. et al. Brain tumour imaging with PET: a comparison between [18F]fluorodopa and [11C]methionine. Eur J Nucl Med Mol Imaging 2003; 30 (11) 1561-1567
- 79 Chen W, Silverman DHS, Delaloye S. et al. 18F-FDOPA PET imaging of brain tumors: comparison study with 18F-FDG PET and evaluation of diagnostic accuracy. J Nucl Med 2006; 47 (06) 904-911
- 80 Ledezma CJ, Chen W, Sai V. et al. 18F-FDOPA PET/MRI fusion in patients with primary/recurrent gliomas: initial experience. Eur J Radiol 2009; 71 (02) 242-248
- 81 Pafundi DH, Laack NN, Youland RS. et al. Biopsy validation of 18F-DOPA PET and biodistribution in gliomas for neurosurgical planning and radiotherapy target delineation: results of a prospective pilot study. Neuro-oncol 2013; 15 (08) 1058-1067
- 82 Kunz M, Thon N, Eigenbrod S. et al. Hot spots in dynamic (18)FET-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro-oncol 2011; 13 (03) 307-316
- 83 Pirotte B, Goldman S, Massager N. et al. Comparison of 18F-FDG and 11C-methionine for PET-guided stereotactic brain biopsy of gliomas. J Nucl Med 2004; 45 (08) 1293-1298
- 84 Horsley PJ, Bailey DL, Schembri G, Hsiao E, Drummond J, Back MF. The role of amino acid PET in radiotherapy target volume delineation for adult-type diffuse gliomas: a review of the literature. Crit Rev Oncol Hematol 2025; 205: 104552
- 85 Galldiks N, Stoffels G, Ruge MI. et al. Role of O-(2-18F-fluoroethyl)-L-tyrosine PET as a diagnostic tool for detection of malignant progression in patients with low-grade glioma. J Nucl Med 2013; 54 (12) 2046-2054
- 86 Jansen NL, Suchorska B, Wenter V. et al. Dynamic 18F-FET PET in newly diagnosed astrocytic low-grade glioma identifies high-risk patients. J Nucl Med 2014; 55 (02) 198-203
- 87 Jansen NL, Suchorska B, Wenter V. et al. Prognostic significance of dynamic 18F-FET PET in newly diagnosed astrocytic high-grade glioma. J Nucl Med 2015; 56 (01) 9-15
- 88 Suchorska B, Jansen NL, Linn J. et al; German Glioma Network. Biological tumor volume in 18FET-PET before radiochemotherapy correlates with survival in GBM. Neurology 2015; 84 (07) 710-719
- 89 Galldiks N, Langen KJ, Holy R. et al. Assessment of treatment response in patients with glioblastoma using O-(2-18F-fluoroethyl)-L-tyrosine PET in comparison to MRI. J Nucl Med 2012; 53 (07) 1048-1057
- 90 Galldiks N, Kracht LW, Burghaus L. et al. Use of 11C-methionine PET to monitor the effects of temozolomide chemotherapy in malignant gliomas. Eur J Nucl Med Mol Imaging 2006; 33 (05) 516-524
- 91 Jansen NL, Suchorska B, Schwarz SB. et al. [18F]fluoroethyltyrosine-positron emission tomography-based therapy monitoring after stereotactic iodine-125 brachytherapy in patients with recurrent high-grade glioma. Mol Imaging 2013; 12 (03) 137-147
- 92 Pöpperl G, Goldbrunner R, Gildehaus FJ. et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET for monitoring the effects of convection-enhanced delivery of paclitaxel in patients with recurrent glioblastoma. Eur J Nucl Med Mol Imaging 2005; 32 (09) 1018-1025
- 93 Pöpperl G, Götz C, Rachinger W. et al. Serial O-(2-[(18)F]fluoroethyl)-L: -tyrosine PET for monitoring the effects of intracavitary radioimmunotherapy in patients with malignant glioma. Eur J Nucl Med Mol Imaging 2006; 33 (07) 792-800
- 94 Harris RJ, Cloughesy TF, Pope WB. et al. 18F-FDOPA and 18F-FLT positron emission tomography parametric response maps predict response in recurrent malignant gliomas treated with bevacizumab. Neuro-oncol 2012; 14 (08) 1079-1089
- 95 Schwarzenberg J, Czernin J, Cloughesy TF. et al. Treatment response evaluation using 18F-FDOPA PET in patients with recurrent malignant glioma on bevacizumab therapy. Clin Cancer Res 2014; 20 (13) 3550-3559
- 96 Galldiks N, Rapp M, Stoffels G. et al. Response assessment of bevacizumab in patients with recurrent malignant glioma using [18F]Fluoroethyl-L-tyrosine PET in comparison to MRI. Eur J Nucl Med Mol Imaging 2013; 40 (01) 22-33
- 97 Hutterer M, Nowosielski M, Putzer D. et al. O-(2-18F-fluoroethyl)-L-tyrosine PET predicts failure of antiangiogenic treatment in patients with recurrent high-grade glioma. J Nucl Med 2011; 52 (06) 856-864
- 98 Herrmann K, Czernin J, Cloughesy T. et al. Comparison of visual and semiquantitative analysis of 18F-FDOPA-PET/CT for recurrence detection in glioblastoma patients. Neuro-oncol 2014; 16 (04) 603-609
- 99 Walter F, Cloughesy T, Walter MA. et al. Impact of 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine PET/CT on managing patients with brain tumors: the referring physician's perspective. J Nucl Med 2012; 53 (03) 393-398
- 100 Kebir S, Fimmers R, Galldiks N. et al. Late pseudoprogression in glioblastoma: diagnostic value of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine PET. Clin Cancer Res 2016; 22 (09) 2190-2196
- 101 Palmisciano P, Watanabe G, Conching A. et al. The role of [68Ga]Ga-DOTA-SSTR PET radiotracers in brain tumors: a systematic review of the literature and ongoing clinical trials. Cancers (Basel) 2022; 14 (12) 2925
- 102 Valotassiou V, Leondi A, Angelidis G, Psimadas D, Georgoulias P. SPECT and PET imaging of meningiomas. ScientificWorldJournal 2012; 2012: 412580
- 103 Graf R, Plotkin M, Steffen IG. et al. Magnetic resonance imaging, computed tomography, and 68Ga-DOTATOC positron emission tomography for imaging skull base meningiomas with infracranial extension treated with stereotactic radiotherapy—a case series. Head Face Med 2012; 8: 1
- 104 Law WP, Fiumara F, Fong W, Macfarlane DJ. The “double pituitary hot spot” sign of skull base meningioma on gallium-68-labelled somatostatin analogue PET. J Med Imaging Radiat Oncol 2013; 57 (06) 680-683
- 105 Purandare NC, Puranik A, Shah S. et al. Differentiating dural metastases from meningioma: role of 68Ga DOTA-NOC PET/CT. Nucl Med Commun 2020; 41 (04) 356-362
- 106 Unterrainer M, Ruf V, Ilhan H. et al. 68Ga-DOTATOC PET/CT differentiates meningioma from dural metastases. Clin Nucl Med 2019; 44 (05) 412-413
- 107 Gehler B, Paulsen F, Oksüz MO. et al. [68Ga]-DOTATOC-PET/CT for meningioma IMRT treatment planning. Radiat Oncol 2009; 4: 56
- 108 Nyuyki F, Plotkin M, Graf R. et al. Potential impact of (68)Ga-DOTATOC PET/CT on stereotactic radiotherapy planning of meningiomas. Eur J Nucl Med Mol Imaging 2010; 37 (02) 310-318
- 109 d'Amico A, Stąpór-Fudzińska M, Tarnawski R. CyberKnife radiosurgery planning of a secreting pituitary adenoma performed with 68Ga DOTATATE PET and MRI. Clin Nucl Med 2014; 39 (12) 1043-1044
- 110 Zhao X, Xiao J, Xing B, Wang R, Zhu Z, Li F. Comparison of (68)Ga DOTATATE to 18F-FDG uptake is useful in the differentiation of residual or recurrent pituitary adenoma from the remaining pituitary tissue after transsphenoidal adenomectomy. Clin Nucl Med 2014; 39 (07) 605-608
- 111 Xiao J, Zhu Z, Zhong D, Ma W, Wang R. Improvement in diagnosis of metastatic pituitary carcinoma by 68Ga DOTATATE PET/CT. Clin Nucl Med 2015; 40 (02) e129-e131
- 112 Kaya G, Soydas Turan B, Dagdelen S, Berker M, Tuncel M. 68Ga-DOTATATE PET/CT in pituitary carcinoma. Clin Nucl Med 2021; 46 (12) 996-998
- 113 van den Bent MJ, Vogelbaum MA, Cloughesy T. et al. Response assessment in neuro-oncology (RANO) 2009-2025: broad scope and implementation—a progress report. Neuro-oncol 2025; 27 (09) 2209-2224
- 114 Wen PY, Macdonald DR, Reardon DA. et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 2010; 28 (11) 1963-1972
- 115 Macdonald DR, Cascino TL, Schold Jr SC, Cairncross JG. Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 1990; 8 (07) 1277-1280
- 116 Lin NU, Lee EQ, Aoyama H. et al; Response Assessment in Neuro-Oncology (RANO) group. Response assessment criteria for brain metastases: proposal from the RANO group. Lancet Oncol 2015; 16 (06) e270-e278
- 117 Chamberlain M, Junck L, Brandsma D. et al. Leptomeningeal metastases: a RANO proposal for response criteria. Neuro-oncol 2017; 19 (04) 484-492
- 118 Okada H, Weller M, Huang R. et al. Immunotherapy response assessment in neuro-oncology: a report of the RANO working group. Lancet Oncol 2015; 16 (15) e534-e542
- 119 Kim SH, Roytman M, Madera G. et al. Evaluating diagnostic accuracy and determining optimal diagnostic thresholds of different approaches to [68Ga]-DOTATATE PET/MRI analysis in patients with meningioma. Sci Rep 2022; 12 (01) 9256
- 120 Wen PY, van den Bent M, Youssef G. et al. RANO 2.0: update to the response assessment in neuro-oncology criteria for high- and low-grade gliomas in adults. J Clin Oncol 2023; 41 (33) 5187-5199
- 121 Lohmann P, Galldiks N, Kocher M. et al. Radiomics in neuro-oncology: basics, workflow, and applications. Methods 2021; 188: 112-121
- 122 Kickingereder P, Bonekamp D, Nowosielski M. et al. Radiogenomics of glioblastoma: machine learning-based classification of molecular characteristics by using multiparametric and multiregional MR imaging features. Radiology 2016; 281 (03) 907-918
- 123 Lohmann P, Lerche C, Bauer EK. et al. Predicting IDH genotype in gliomas using FET PET radiomics. Sci Rep 2018; 8 (01) 13328
- 124 Franco P, Würtemberger U, Dacca K. et al. SPectroscOpic prediction of bRain Tumours (SPORT): study protocol of a prospective imaging trial. BMC Med Imaging 2020; 20 (01) 123
- 125 Zhou H, Chang K, Bai HX. et al. Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas. J Neurooncol 2019; 142 (02) 299-307
- 126 Peng L, Parekh V, Huang P. et al. Distinguishing true progression from radionecrosis after stereotactic radiation therapy for brain metastases with machine learning and radiomics. Int J Radiat Oncol Biol Phys 2018; 102 (04) 1236-1243
- 127 Kocak B, Mese I, Ates Kus E. Radiomics for differentiating radiation-induced brain injury from recurrence in gliomas: systematic review, meta-analysis, and methodological quality evaluation using METRICS and RQS. Eur Radiol 2025; 35 (08) 4490-4505
- 128 Hollon TC, Pandian B, Adapa AR. et al. Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nat Med 2020; 26 (01) 52-58
- 129 Lohmann P, Franceschi E, Vollmuth P. et al. Radiomics in neuro-oncological clinical trials. Lancet Digit Health 2022; 4 (11) e841-e849
- 130 Galldiks N, Langen KJ, Albert NL. et al. Investigational PET tracers in neuro-oncology—What's on the horizon? A report of the PET/RANO group. Neuro-oncol 2022; 24 (11) 1815-1826
- 131 Chung BT, Chen HY, Gordon J. et al. First hyperpolarized [2-13C]pyruvate MR studies of human brain metabolism. J Magn Reson 2019; 309: 106617
- 132 Izquierdo-Garcia JL, Cai LM, Chaumeil MM. et al. Glioma cells with the IDH1 mutation modulate metabolic fractional flux through pyruvate carboxylase. PLoS One 2014; 9 (09) e108289
- 133 Kim Y, Chen HY, Nickles T. et al. Translation of hyperpolarized [13C,15N2]urea MRI for novel human brain perfusion studies. Npj Imaging 2025; 3 (01) 11
- 134 Eskandari R, Kim N, Mamakhanyan A. et al. Hyperpolarized [5-13C,4,4-2H2,5-15N]-L-glutamine provides a means of annotating in vivo metabolic utilization of glutamine. Proc Natl Acad Sci U S A 2022; 119 (19) e2120595119
- 135 Patel S, Porcari P, Coffee E. et al. Simultaneous noninvasive quantification of redox and downstream glycolytic fluxes reveals compartmentalized brain metabolism. Sci Adv 2024; 10 (51) eadr2058
- 136 Michaelson NM, Watsula A, Bakare-Okpala A, Mohamadpour M, Chukwueke UN, Budhu JA. Disparities in neuro-oncology. Curr Neurol Neurosci Rep 2023; 23 (12) 815-825
- 137 Mukherjee D, Zaidi HA, Kosztowski T. et al. Disparities in access to neuro-oncologic care in the United States. Arch Surg 2010; 145 (03) 247-253
- 138 Kim Y, Armstrong TS, Gilbert MR, Celiku O. Disparities in the availability of and access to neuro-oncology trial-supporting infrastructure in the United States. J Natl Cancer Inst 2025; 117 (03) 511-516
- 139 Budhu JA, Chukwueke UN, Jackson S. et al. Defining interventions and metrics to improve diversity in CNS clinical trial participation: A SNO and RANO effort. Neuro-oncol 2024; 26 (04) 596-608
- 140 Wen PY, van den Bent M, Youssef G. et al. RANO 2.0: update to the response assessment in neuro-oncology criteria for high- and low-grade gliomas in adults. J Clin Oncol 2023 41. 33 . Accessed August 1, 2025 at: https://ascopubs.org/doi/10.1200/JCO.23.01059