Skip to main content

Advertisement

SpringerLink
Log in

The landscape of brain tumor mimics in neuro-oncology practice

  • Research
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Background and objective

Differentiating neoplastic and non-neoplastic brain lesions is essential to make management recommendations and convey prognosis, but the distinction between brain tumors and their mimics in practice may prove challenging. The aim of this study is to provide the incidence of brain tumor mimics in the neuro-oncology setting and describe this patient subset.

Methods

Retrospective study of adult patients referred to the Division of Neuro-oncology for a presumed diagnosis of brain tumor from January 1, 2005 through December 31, 2017, who later satisfied the diagnosis of a non-neoplastic entity based on neuroimaging, clinical course, and/or histopathology evaluation. We classified tumor mimic entities according to clinical, radiologic, and laboratory characteristics that correlated with the diagnosis.

Results

The incidence of brain tumor mimics was 3.4% (132/3897). The etiologies of the non-neoplastic entities were vascular (35%), inflammatory non-demyelinating (26%), demyelinating (15%), cysts (10%), infectious (9%), and miscellaneous (5%). In our study, 38% of patients underwent biopsy to determine diagnosis, but in 26%, the biopsy was inconclusive.

Discussion

Brain tumor mimics represent a small but important subset of the neuro-oncology referrals. Vascular, inflammatory, and demyelinating etiologies represent two-thirds of cases. Recognizing the clinical, radiologic and laboratory characteristics of such entities may improve resource utilization and prevent unnecessary as well as potentially harmful diagnostic and therapeutic interventions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Anderson MD, Colen RR, Tremont-Lukats IW (2014) Imaging mimics of primary malignant tumors of the central nervous system (CNS). Curr Oncol Rep 16(8):399

    Article  PubMed  CAS  Google Scholar 

  2. Bradley D, Ress J (2013) Brain tumour mimics and chameleons. Pract Neurol 13(6):359–371

    Article  PubMed  Google Scholar 

  3. Cha S, Pierce S, Knopp EA, Johnson G, Yang C, Ton A et al (2001) Dynamic contrast-enhanced T2*-weighted MR imaging of tumefactive demyelinating lesions. AJNR Am J Neuroradiol 22(6):1109–1116

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Chiang IC, Hsieh TJ, Chiu ML, Liu GC, Kuo YT, Lin WC (2009) Distinction between pyogenic brain abscess and necrotic brain tumour using 3-tesla MR spectroscopy, diffusion and perfusion imaging. Br J Radiol 82(982):813–820

    Article  PubMed  Google Scholar 

  5. Dibble EH, Boxerman JL, Baird GL, Donahue JE, Rogg JM (2017) Toxoplasmosis versus lymphoma: cerebral lesion characterization using DSC-MRI revisited. Clin Neurol Neurosurg 152:84–89

    Article  PubMed  Google Scholar 

  6. Peterson K, Rosenblum MK, Powers JM, Alvord E, Walker RW, Posner JB (1993) Effect of brain irradiation on demyelinating lesions. Neurology 43(10):2105–2112

    Article  CAS  PubMed  Google Scholar 

  7. Fakhran S, Escott EJ (2008) Pineocytoma mimicking a pineal cyst on imaging: true diagnosis or dilemma or a case of incomplete imaging? AJNR Am J Neuroradiol 29(1):159–163

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Llufriu S, Pujol T, Blanco Y et al (2010) T2 hypointense rims and ring-enhancing lesions in MS. Mult Scler 16(11):1317–1325

    Article  PubMed  Google Scholar 

  9. Pastel DA, Mamourian AC, Duhaime AC (2009) Internal structure in pineal cysts on high-resolution magnetic resonance imaging: not a sign of malignancy. J Neurosurg Pediatr. 4(1):81–4. https://doi.org/10.3171/2008.5.17681

    Article  PubMed  Google Scholar 

  10. Osborn AG, Preece MT (2006) Intracranial cysts: radiologic-pathologic correlation and imaging approach. Radiology 239(3):650–664

    Article  PubMed  Google Scholar 

  11. Goldring S, Gregorie EM (1986) Experience with lesions that mimic gliomas in patients presenting with a chronic seizure disorder. Clin Neurosurg 33:43–70

    CAS  PubMed  Google Scholar 

  12. Michael AS, Levy JM, Paige ML (1990) Cysticercosis mimicking brain neoplasm: MR and CT appearance. J Comput Assist Tomogr 14(5):708–711

    Article  CAS  PubMed  Google Scholar 

  13. Okamoto K, Furusawa T, Ishikawa K, Quadery FA, Sasai K, Tokiguchi S (2004) Mimics of brain tumor on neuroimaging: part I. Radiat Med 22(2):63–76

    PubMed  Google Scholar 

  14. Okamoto K, Furusawa T, Ishikawa K, Quadery FA, Sasai K, Tokiguchi S (2004) Mimics of brain tumor on neuroimaging: part II. Radiat Med 22(3):135–142

    PubMed  Google Scholar 

  15. Go JL, Acharya J, Rajamohan AG (2018) Is it or is it not? Brain Tumor Mimics Semin Roentgenol 53(1):62–76

    Article  PubMed  Google Scholar 

  16. Nakayama M, Naganawa S, Ouyang M, Jones KA, Kim J, Capizzano AA et al (2021) A review of clinical and imaging findings in tumefactive demyelination. AJR Am J Roentgenol. 217:186–197

    Article  Google Scholar 

  17. Cunliffe CH, Fischer I, Monoky D, Law M, Revercomb C, Elrich S et al (2009) Intracranial lesions mimicking neoplasms. Arch Pathol Lab Med 133(1):101–123

    Article  PubMed  Google Scholar 

  18. Hatzoglou V, Omuro AM, Haque S, Khakoo Y, Ganly I, Oh JH et al (2016) Second-opinion interpretations of neuroimaging studies by oncologic neuroradiologists can help reduce errors in cancer care. Cancer 122(17):2708–2714

    Article  PubMed  Google Scholar 

  19. Mohammad HR, Boardman J, Howell L, Mills RJ, Emsley HC (2016) Urgent referral for suspected CNS cancer: which clinical features are associated with a positive predictive value of 3 % or more? BMC Neurol 16(1):152

    Article  PubMed  PubMed Central  Google Scholar 

  20. Barboriak DP, Lee L, Provenzale JM (2001) Serial MR imaging of pineal cysts: implications for natural history and follow-up. AJR Am J Roentgenol 176(3):737–743

    Article  CAS  PubMed  Google Scholar 

  21. Mamourian AC, Yarnell T (1991) Enhancement of pineal cysts on MR images. AJNR Am J Neuroradiol 12(4):773–774

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ (2018) MRI findings in tumefactive demyelinating lesions: a systematic review and meta-analysis. AJNR Am J Neuroradiol 39(9):1643–1649

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang KY, Idowu OR, Lin DDM (2017) Radiology and imaging for cavernous malformations. Handb Clin Neurol 143:249–266

    Article  PubMed  Google Scholar 

  24. de Souza JM, Domingues RC, Cruz LC Jr, Domingues FS, Iasbeck T, Gasparetto EL (2008) Susceptibility-weighted imaging for the evaluation of patients with familial cerebral cavernous malformations: a comparison with t2-weighted fast spin-echo and gradient-echo sequences. AJNR Am J Neuroradiol 29(1):154–158

    Article  PubMed  PubMed Central  Google Scholar 

  25. Karonen JO, Partanen PL, Vanninen RL, Vainio PA, Aronen HJ (2001) Evolution of MR contrast enhancement patterns during the first week after acute ischemic stroke. AJNR Am J Neuroradiol 22(1):103–111

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Siskas N, Lefkopoulos A, Ioannidis I, Charitandi A, Dimitriadis AS (2003) Cortical laminar necrosis in brain infarcts: serial MRI. Neuroradiology 45(5):283–288

    Article  CAS  PubMed  Google Scholar 

  27. Rawal S, Croul SE, Willinsky RA, Tymianski M, Krings T (2014) Subcortical cystic lesions within the anterior superior temporal gyrus: a newly recognized characteristic location for dilated perivascular spaces. AJNR Am J Neuroradiol 35(2):317–322

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Sung J, Jang J, Choi HS, Jung SL, Ahn KJ, Kim BS (2017) Linear sign in cystic brain lesions ≥5 mm: a suggestive feature of perivascular space. Eur Radiol 27(11):4747–4755

    Article  PubMed  Google Scholar 

  29. Donkol RH, Moghazy KM, Abolenin A (2012) Assessment of gray matter heterotopia by magnetic resonance imaging. World J Radiol. 4(3):90–96

    Article  PubMed  PubMed Central  Google Scholar 

  30. Huang YC, Weng HH, Tsai YT, Huang YC, Hsiao MC, Wu CY, Lin YH, Hsu HL, Lee JD (2009) Periictal magnetic resonance imaging in status epilepticus. Epilepsy Res 86(1):72–81

    Article  PubMed  Google Scholar 

  31. Kim JE, Kim DG, Paek SH, Jung HW (2003) Stereotactic biopsy for intracranial lesions: reliability and its impact on the planning of treatment. Acta Neurochir (Wien). 145(7):547–54

    Article  CAS  PubMed  Google Scholar 

  32. Williams JA, Bede P, Doherty CP (2017) An exploration of the spectrum of peri-ictal MRI change; a comprehensive literature review. Seizure 50:19–32

    Article  PubMed  Google Scholar 

  33. Noujaim SE, Rossi MD, Rao SK, Cacciarelli AA, Mendonca RA, Wang AM, Coelho FH (1999) CT and MR imaging of neurocysticercosis. AJR Am J Roentgenol 173(6):1485–1490

    Article  CAS  PubMed  Google Scholar 

  34. Martinez HR, Rangel-Guerra R, Elizondo G, Gonzalez J, Todd LE, Ancer J, Prakash SS (1989) MR imaging in neurocysticercosis: a study of 56 cases. AJNR Am J Neuroradiol 10(5):1011–1019

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Starkey J, Kobayashi N, Numaguchi Y, Moritani T (2017) Cytotoxic lesions of the corpus callosum that show restricted diffusion: mechanisms, causes, and manifestations. Radiographics 37(2):562–576

    Article  PubMed  Google Scholar 

  36. Schaefer PW, Grant PE, Gonzalez RG (2000) Diffusion-weighted MR imaging of the brain. Radiology 217(2):331–345

    Article  CAS  PubMed  Google Scholar 

  37. Feraco P, Donner D, Gagliardo C, Leonardi I, Piccinini S, Del Poggio A, Franciosi R, Petralia B, van den Hauwe L (2020) Cerebral abscesses imaging: a practical approach. J Popul Ther Clin Pharmacol 27(3):e11–e24

    Article  PubMed  Google Scholar 

  38. Toh CH, Wei KC, Chang CN, Hsu PW, Wong HF, Ng SH et al (2012) Differentiation of pyogenic brain abscesses from necrotic glioblastomas with use of susceptibility-weighted imaging. AJNR Am J Neuroradiol 33(8):1534–1538

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Sasagawa A, Mikami T, Kimura Y, Akiyama Y, Sugita S, Hasegawa T et al (2021) Stroke mimics and chameleons from the radiological viewpoint of glioma diagnosis. Neurol Med Chir (Tokyo) 61(2):134–143

    Article  Google Scholar 

  40. Marangoni S, Argentiero V, Tavolato B (2006) Neurosarcoidosis. Clinical description of 7 cases with a proposal for a new diagnostic strategy. J Neurol 253(4):488–495

    Article  PubMed  Google Scholar 

  41. Abdoli M, Freedman MS (2015) Neuro-oncology dilemma: tumour or tumefactive demyelinating lesion. Mult Scler Relat Disord 4(6):555–566

    Article  PubMed  Google Scholar 

  42. Dagher AP, Smirniotopoulos J (1996) Tumefactive demyelinating lesions. Neuroradiology 38(6):560–565

    Article  CAS  PubMed  Google Scholar 

  43. Omuro AM, Leite CC, Mokhtari K, Delattre JY (2006) Pitfalls in the diagnosis of brain tumours. The Lancet Neurology 5(11):937–948

    Article  PubMed  Google Scholar 

  44. Altintas A, Petek B, Isik N, Terzi M, Bolukbasi F, Tavsanli M et al (2012) Clinical and radiological characteristics of tumefactive demyelinating lesions: follow-up study. Mult Scler 18(10):1448–1453

    Article  CAS  PubMed  Google Scholar 

  45. Lapointe E, Li DKB, Traboulsee AL, Rauscher A (2018) What have we learned from perfusion MRI in multiple sclerosis? AJNR Am J Neuroradiol 39(6):994–1000

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Mistry N, Dixon J, Tallantyre E, Tench C, Abdel-Fahim R, Jaspan T et al (2013) Central veins in brain lesions visualized with high-field magnetic resonance imaging: a pathologically specific diagnostic biomarker for inflammatory demyelination in the brain. JAMA Neurol 70(5):623–628

    Article  PubMed  Google Scholar 

  47. Ontaneda D, Sati P, Raza P, Kilbane M, Gombos E, Alvarez E, Azevedo C et al (2021) North American imaging in MS cooperative. Central vein sign: a diagnostic biomarker in multiple sclerosis (CAVS-MS) study protocol for a prospective multicenter trial. Neuroimage Clin. 32:102834

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kim SH, Chang KH, Song IC, Han MH, Kim HC, Kang HS, Han MC (1997) Brain abscess and brain tumor: discrimination with in vivo H-1 MR spectroscopy. Radiology 204(1):239–245

    Article  CAS  PubMed  Google Scholar 

  49. Fritz D, van de Beek D, Brouwer MC (2016) Clinical features, treatment and outcome in neurosarcoidosis: systematic review and meta-analysis. BMC Neurol 16(1):220

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Division of Neuro-Oncology, Department of Neurology, University of Virginia, P.O. Box 800394, Charlottesville, VA, 22908, USA

    Lalanthica V. Yogendran, Nicole M. Calautti, Benjamin Purow, David Schiff & Camilo E. Fadul

  2. Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA, USA

    Tuba Kalelioglu, Joseph H. Donahue & Sohil H. Patel

  3. Department of Neurology, University of Maryland, Baltimore, MD, USA

    Haroon Ahmad

  4. Department of Neurology, The Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment at Swedish Neuroscience Institute, Seattle, WA, USA

    Kester A. Phillips

  5. Department of Pathology, Divisions of Neuropathology and Molecular Diagnostics, University of Virginia, Charlottesville, VA, USA

    Maria-Beatriz Lopes

  6. Department of Neurosurgery, University of Virginia, Charlottesville, VA, USA

    Ashok R. Asthagiri

Authors
  1. Lalanthica V. Yogendran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tuba Kalelioglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joseph H. Donahue
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haroon Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kester A. Phillips
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Nicole M. Calautti
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Maria-Beatriz Lopes
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ashok R. Asthagiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Benjamin Purow
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. David Schiff
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Sohil H. Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Camilo E. Fadul
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LVY: design and conceptualization of the study; acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. TK: acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. JD: design and conceptualization of the study; acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. HA: acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. KAP: acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. NMC: acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content. MBL: analysis and interpretation, acquisition of data; revising the manuscript for intellectual content. ARA: revising the manuscript for intellectual content. BP: revising the manuscript for intellectual content. DS: provision of data, revising the manuscript for intellectual content. SHP: acquisition of data; analysis and interpretation of data; revising the manuscript for intellectual content. CEF: design and conceptualization of the study; acquisition of data; analysis and interpretation of data; drafting and revising the manuscript for intellectual content.

Corresponding author

Correspondence to Camilo E. Fadul.

Ethics declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

This retrospective study was Health Insurance Portability and Accountability Act compliant and approved by the University of Virginia (UVA) Institutional Review Board, and confirmed that no ethical approval is required.

Informed consent

This is a retrospective study, and we reviewed our IRB-approved database, therefore informed consent was not required from all individual participants included in the study.

Consent for publication

The authors affirm we have a retrospective IRB-approved study in neuroradiology at the University of Virginia for evaluating MRI and associated clinical findings. The IRB at the University of Virginia has waived requirement for consent for these purposes.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 270 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yogendran, L.V., Kalelioglu, T., Donahue, J.H. et al. The landscape of brain tumor mimics in neuro-oncology practice. J Neurooncol 159, 499–508 (2022). https://doi.org/10.1007/s11060-022-04087-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-022-04087-4

Keywords

Search

Navigation