CC BY 4.0 · Indian J Med Paediatr Oncol 2023; 44(01): 026-038
DOI: 10.1055/s-0042-1759712
Review Article

Imaging Recommendations for the Diagnosis, Staging, and Management of Adult Brain Tumors

HariKishore Kamepalli
1   Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, India
,
1   Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, India
,
Chandrasekharan Kesavadas
1   Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, India
› Author Affiliations

Abstract

Neuroimaging plays a pivotal role in the clinical practice of brain tumors aiding in the diagnosis, genotype prediction, preoperative planning, and prognostication. The brain tumors most commonly seen in adults are extra-axial lesions like meningioma, intra-axial lesions like gliomas and lesions of the pituitary gland. Clinical features may be localizing like partial seizures, weakness, and sensory disturbances or nonspecific like a headache. On clinical suspicion of a brain tumor, the primary investigative workup should focus on imaging. Other investigations like fundoscopy and electroencephalography may be performed depending on the clinical presentation. Obtaining a tissue sample after identifying a brain tumor on imaging is crucial for confirming the diagnosis and planning further treatment. Tissue sample may be obtained by techniques such as stereotactic biopsy or upfront surgery. The magnetic resonance (MR) imaging protocol needs to be standardized and includes conventional sequences like T1-weighted (T1W) imaging with and without contrast, T2w imaging, fluid-attenuated axial inversion recovery, diffusion-weighted imaging (DWI), susceptibility-weighted imaging, and advanced imaging sequences like MR perfusion and MR spectroscopy. Various tumor characteristics in each of these sequences can help us narrow down the differential diagnosis and also predict the grade of the tumor. Multidisciplinary co-ordination is needed for proper management and care of brain tumor patients. Treatment protocols need to be adapted and individualized for each patient depending on the age, general condition of the patient, histopathological characteristics, and genotype of the tumor. Treatment options include surgery, radiotherapy, and chemotherapy. Imaging also plays a vital role in post-treatment follow-up. Sequences like DWI, MR perfusion, and MR spectroscopy are useful to distinguish post-treatment effects like radiation necrosis and pseudoprogression from true recurrence. Radiological reporting of brain tumor images should follow a structured format to include all the elements that could have an impact on the treatment decisions in patients.



Publication History

Article published online:
06 March 2023

© 2023. 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 and Scientific Publishers Pvt. Ltd.
A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

 
  • References

  • 1 Castillo M. History and evolution of brain tumor imaging: insights through radiology. Radiology 2014; 273 (2, Suppl) S111-S125
  • 2 Geva T. Magnetic resonance imaging: historical perspective. J Cardiovasc Magn Reson 2006; 8 (04) 573-580
  • 3 McNeill KA. Epidemiology of brain tumors. Neurol Clin 2016; 34 (04) 981-998
  • 4 de Robles P, Fiest KM, Frolkis AD. et al. The worldwide incidence and prevalence of primary brain tumors: a systematic review and meta-analysis. Neuro-oncol 2015; 17 (06) 776-783
  • 5 Porter KR, McCarthy BJ, Freels S, Kim Y, Davis FG. Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology. Neuro-oncol 2010; 12 (06) 520-527
  • 6 Dasgupta A, Gupta T, Jalali R. Indian data on central nervous tumors: a summary of published work. South Asian J Cancer 2016; 5 (03) 147-153
  • 7 Alther B, Mylius V, Weller M, Gantenbein A. From first symptoms to diagnosis: Initial clinical presentation of primary brain tumors. Clinical and Translational Neuroscience. 2020; 4 (02) DOI: 10.1177/2514183 × 20968368.
  • 8 Weller M, van den Bent M, Preusser M. et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat Rev Clin Oncol 2021; 18 (03) 170-186 DOI: 10.1038/s41571-020-00447-z. Erratum in: Nat Rev Clin Oncol. 2022 May;19(5):357–358. PMID: 33293629; PMCID: PMC7904519
  • 9 Xiao F, Lv S, Zong Z. et al. Cerebrospinal fluid biomarkers for brain tumor detection: clinical roles and current progress. Am J Transl Res 2020; 12 (04) 1379-1396
  • 10 Merve A, Millner TO, Marino S. Integrated phenotype-genotype approach in diagnosis and classification of common central nervous system tumours. Histopathology 2019; 75 (03) 299-311
  • 11 Akshulakov SK, Kerimbayev TT, Biryuchkov MY, Urunbayev YA, Farhadi DS, Byvaltsev VA. Current trends for improving safety of stereotactic brain biopsies: advanced optical methods for vessel avoidance and tumor detection. Front Oncol 2019; 9: 947 DOI: 10.3389/fonc.2019.00947.
  • 12 Tanboon J, Williams EA, Louis DN. The diagnostic use of immunohistochemical surrogates for signature molecular genetic alterations in gliomas. J Neuropathol Exp Neurol 2016; 75 (01) 4-18
  • 13 Louis DN, Perry A, Wesseling P. et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro-oncol 2021; 23 (08) 1231-1251
  • 14 Barresi V, Eccher A, Simbolo M. et al. Diffuse gliomas in patients aged 55 years or over: a suggestion for IDH mutation testing. Neuropathology 2020; 40 (01) 68-74
  • 15 Whitfield BT, Huse JT. Classification of adult-type diffuse gliomas: impact of the World Health Organization 2021 update. Brain Pathol 2022; 32 (04) e13062 DOI: 10.1111/bpa.13062.
  • 16 Iv M, Yoon BC, Heit JJ, Fischbein N, Wintermark M. Current clinical state of advanced magnetic resonance imaging for brain tumor diagnosis and follow up. Semin Roentgenol 2018; 53 (01) 45-61
  • 17 Blumenthal DT, Aisenstein O, Ben-Horin I. et al. Calcification in high grade gliomas treated with bevacizumab. J Neurooncol 2015; 123 (02) 283-288
  • 18 Lyndon D, Lansley JA, Evanson J, Krishnan AS. Dural masses: meningiomas and their mimics. Insights Imaging 2019; 10 (01) 11
  • 19 Haldorsen IS, Espeland A, Larsson EM. Central nervous system lymphoma: characteristic findings on traditional and advanced imaging. AJNR Am J Neuroradiol 2011; 32 (06) 984-992
  • 20 Zhang D, Hu LB, Henning TD. et al. MRI findings of primary CNS lymphoma in 26 immunocompetent patients. Korean J Radiol 2010; 11 (03) 269-277
  • 21 Yamasaki F, Kurisu K, Satoh K. et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology 2005; 235 (03) 985-991
  • 22 Ellingson BM, Malkin MG, Rand SD. et al. Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity. J Magn Reson Imaging 2010; 31 (03) 538-548
  • 23 Kono K, Inoue Y, Nakayama K. et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol 2001; 22 (06) 1081-1088
  • 24 Park SI, Suh CH, Guenette JP, Huang RY, Kim HS. The T2-FLAIR mismatch sign as a predictor of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas: a systematic review and diagnostic meta-analysis. Eur Radiol 2021; 31 (07) 5289-5299
  • 25 Kitis O, Altay H, Calli C, Yunten N, Akalin T, Yurtseven T. Minimum apparent diffusion coefficients in the evaluation of brain tumors. Eur J Radiol 2005; 55 (03) 393-400
  • 26 Bozdağ M, Er A, Ekmekçi S. Association of apparent diffusion coefficient with Ki-67 proliferation index, progesterone-receptor status and various histopathological parameters, and its utility in predicting the high grade in meningiomas. Acta Radiol 2021; 62 (03) 401-413
  • 27 Makino K, Hirai T, Nakamura H. et al. Differentiating between primary central nervous system lymphomas and glioblastomas: combined use of perfusion-weighted and diffusion-weighted magnetic resonance imaging. World Neurosurg 2018; 112: e1-e6
  • 28 Law M, Yang S, Wang H. et al. Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 2003; 24 (10) 1989-1998
  • 29 Law M, Young RJ, Babb JS. et al. Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 2008; 247 (02) 490-498
  • 30 Kong L, Chen H, Yang Y, Chen L. A meta-analysis of arterial spin labelling perfusion values for the prediction of glioma grade. Clin Radiol 2017; 72 (03) 255-261
  • 31 Danchaivijitr N, Waldman AD, Tozer DJ. et al. Low-grade gliomas: do changes in rCBV measurements at longitudinal perfusion-weighted MR imaging predict malignant transformation?. Radiology 2008; 247 (01) 170-178
  • 32 Winter RC, Antunes ACM, de Oliveira FH. The relationship between vascular endothelial growth factor and histological grade in intracranial meningioma. Surg Neurol Int 2020; 11: 328
  • 33 Xing Z, You RX, Li J, Liu Y, Cao DR. Differentiation of primary central nervous system lymphomas from high-grade gliomas by rCBV and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Clin Neuroradiol 2014; 24 (04) 329-336
  • 34 Lee MD, Baird GL, Bell LC, Quarles CC, Boxerman JL. Utility of percentage signal recovery and baseline signal in DSC-MRI optimized for relative CBV measurement for differentiating glioblastoma, lymphoma, metastasis, and meningioma. AJNR Am J Neuroradiol 2019; 40 (09) 1445-1450
  • 35 Jiang S, Eberhart CG, Lim M. et al. Identifying recurrent malignant glioma after treatment using amide proton transfer-weighted MR imaging: a validation study with image-guided stereotactic biopsy. Clin Cancer Res 2019; 25 (02) 552-561
  • 36 Cha S, Lupo JM, Chen MH. et al. Differentiation of glioblastoma multiforme and single brain metastasis by peak height and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. AJNR Am J Neuroradiol 2007; 28 (06) 1078-1084
  • 37 Mangla R, Kolar B, Zhu T, Zhong J, Almast J, Ekholm S. Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain. AJNR Am J Neuroradiol 2011; 32 (06) 1004-1010
  • 38 Roberts HC, Roberts TP, Bollen AW, Ley S, Brasch RC, Dillon WP. Correlation of microvascular permeability derived from dynamic contrast-enhanced MR imaging with histologic grade and tumor labeling index: a study in human brain tumors. Acad Radiol 2001; 8 (05) 384-391
  • 39 Fudaba H, Shimomura T, Abe T. et al. Comparison of multiple parameters obtained on 3T pulsed arterial spin-labeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma grading. AJNR Am J Neuroradiol 2014; 35 (11) 2091-2098
  • 40 Byrnes TJD, Barrick TR, Bell BA, Clark CA. Diffusion tensor imaging discriminates between glioblastoma and cerebral metastases in vivo. NMR Biomed 2011; 24 (01) 54-60
  • 41 Lu S, Ahn D, Johnson G, Law M, Zagzag D, Grossman RI. Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 2004; 232 (01) 221-228
  • 42 Farquharson S, Tournier JD, Calamante F. et al. White matter fiber tractography: why we need to move beyond DTI. J Neurosurg 2013; 118 (06) 1367-1377
  • 43 Mandelli ML, Berger MS, Bucci M, Berman JI, Amirbekian B, Henry RG. Quantifying accuracy and precision of diffusion MR tractography of the corticospinal tract in brain tumors. J Neurosurg 2014; 121 (02) 349-358
  • 44 Dahnert, Wolfgang. (2011). Radiology Review Manual (7th ed.). Philadelphia: Wolter Kluwer Health
  • 45 Al-Okaili RN, Krejza J, Woo JH. et al. Intraaxial brain masses: MR imaging-based diagnostic strategy–initial experience. Radiology 2007; 243 (02) 539-550 [PubMed: 17456876]
  • 46 Iv M, Bisdas S. Neuroimaging in the era of the evolving WHO classification of brain tumors, from the AJR special series on cancer staging. AJR Am J Roentgenol 2021; 217 (01) 3-15
  • 47 Zikou A, Sioka C, Alexiou GA, Fotopoulos A, Voulgaris S, Argyropoulou MI. Radiation necrosis, pseudoprogression, pseudoresponse, and tumor recurrence: imaging challenges for the evaluation of treated gliomas. Contrast Media Mol Imaging 2018; 2018: 6828396 DOI: 10.1155/2018/6828396.
  • 48 Sagiyama K, Mashimo T, Togao O. et al. In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma. Proc Natl Acad Sci U S A 2014; 111 (12) 4542-4547
  • 49 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
  • 50 Ellingson BM, Wen PY, Cloughesy TF. Modified criteria for radiographic response assessment in glioblastoma clinical trials. Neurotherapeutics 2017; 14 (02) 307-320
  • 51 Kim S, Hoch MJ, Cooper ME, Gore A, Weinberg BD. Using a website to teach a structured reporting system, the brain tumor reporting and data system. Curr Probl Diagn Radiol 2020 [published online]
  • 52 BT-RADS website. Brain tumor reporting and data system (BT-RADS). Accessed November 18, 2022, at: www.btrads.com
  • 53 Singhal V. Clinical approach to acute decline in sensorium. Indian J Crit Care Med 2019; 23 (Suppl 2): S120-S123
  • 54 Shorvon S. The management of status epilepticus. J Neurol Neurosurg Psychiatry 2001; 70 (Suppl 2): II22-II27
  • 55 Maschio M, Aguglia U, Avanzini G. et al; Brain Tumor-related Epilepsy study group of Italian League Against Epilepsy (LICE). Management of epilepsy in brain tumors. Neurol Sci 2019; 40 (10) 2217-2234
  • 56 Dietrich J, Rao K, Pastorino S, Kesari S. Corticosteroids in brain cancer patients: benefits and pitfalls. Expert Rev Clin Pharmacol 2011; 4 (02) 233-242
  • 57 Jiang T, Nam DH, Ram Z. et al; Chinese Glioma Cooperative Group (CGCG), Society for Neuro-Oncology of China (SNO-China), Chinese Brain Cancer Association (CBCA), Chinese Glioma Genome Atlas (CGGA), Asian Glioma Genome Atlas (AGGA) network. Clinical practice guidelines for the management of adult diffuse gliomas. Cancer Lett 2021; 499: 60-72
  • 58 , Ed. (2020). Management of Gliomas: Individualized Treatment Options, Journal of the National Comprehensive Cancer Network J Natl Compr Canc Netw, 18(7.5), 985–988. Accessed November 18, 2022, at: https://jnccn.org/view/journals/jnccn/18/7.5/article-p985.xml
  • 59 McFaline-Figueroa JR, Lee EQ. Brain tumors. Am J Med 2018; 131 (08) 874-882
  • 60 Goldbrunner R, Stavrinou P, Jenkinson MD. et al. EANO guideline on the diagnosis and management of meningiomas. Neuro-oncol 2021; 23 (11) 1821-1834
  • 61 Molitch ME. Diagnosis and treatment of pituitary adenomas: a review. JAMA 2017; 317 (05) 516-524
  • 62 von Baumgarten L, Illerhaus G, Korfel A, Schlegel U, Deckert M, Dreyling M. The diagnosis and treatment of primary CNS lymphoma. Dtsch Arztebl Int 2018; 115 (25) 419-426
  • 63 Hoang-Xuan K, Deckert M, Ferreri AJM. et al. European Association of Neuro-Oncology (EANO) guidelines for treatment of primary central nervous system lymphoma (PCNSL). Neuro-oncol 2022; •••: noac196 ; Epub ahead of print DOI: 10.1093/neuonc/noac196.
  • 64 Le Rhun E, Guckenberger M, Smits M. et al; EANO Executive Board and ESMO Guidelines Committee. Electronic address: clinicalguidelines@esmo.org. EANO-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up of patients with brain metastasis from solid tumours. Ann Oncol 2021; 32 (11) 1332-1347
  • 65 Bette S, Gempt J, Huber T. et al. Patterns and time dependence of unspecific enhancement in postoperative magnetic resonance imaging after glioblastoma resection. World Neurosurg 2016; 90: 440-447
  • 66 Raverot G, Burman P, McCormack A. et al; European Society of Endocrinology. European Society of Endocrinology Clinical Practice Guidelines for the management of aggressive pituitary tumours and carcinomas. Eur J Endocrinol 2018; 178 (01) G1-G24
  • 67 Bink A, Benner J, Reinhardt J. et al. Structured reporting in neuroradiology: intracranial tumors. Front Neurol 2018; 9: 32 DOI: 10.3389/fneur.2018.00032.