Skip to main content

Advertisement

Log in

Analysis of the association between vestibular schwannoma and hearing status using a newly developed radiomics technique

  • Otology
  • Published:
European Archives of Oto-Rhino-Laryngology Aims and scope Submit manuscript

Abstract

Purpose

Vestibular schwannoma is a benign tumor originating from Schwann cells surrounding the eighth cranial nerve and can cause hearing loss, tinnitus, balance problems, and facial nerve disorders. Because of the slow growth of the tumor, predicting the hearing function of patients with vestibular schwannoma’s is important to obtain information that would be useful for deciding the treatment modality. This study aimed to analyze the association between magnetic resonance imaging features and hearing status using a new radiomics technique.

Methods

We retrospectively analyzed 115 magnetic resonance images and hearing results from 73 patients with vestibular schwannoma. A total of 70 radiomics features from each tumor volume were calculated using T1-weighted magnetic resonance imaging. Radiomics features were classified as histogram-based, shape-based, texture-based, and filter-based. The least absolute shrinkage and selection operator method was used to select the radiomics features among the 70 features that best predicted the hearing test. To ensure the stability of the selected features, the least absolute shrinkage and selection operator method was repeated 10 times. Finally, features set five or more times were selected as radiomics signatures.

Results

The radiomics signatures selected using the least absolute shrinkage and selection operator method were: minimum, variance, maximum 3D diameter, size zone variance, log skewness, skewness slope, and kurtosis slope. In random forest, the mean performance was 0.66 (0.63–0.77), and the most important feature was Log skewness.

Conclusions

Newly developed radiomics features are associated with hearing status in patients with vestibular schwannoma and could provide information when deciding the treatment modality.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Availability of data and materials

The data sets generated and/or analyzed during the current study are not publicly available due to the legal restrictions of South Korea. However, they are available from the corresponding author upon reasonable request.

References

  1. Halliday J, Rutherford SA, McCabe MG, Evans DG (2018) An update on the diagnosis and treatment of vestibular schwannoma. Expert Rev Neurother 18(1):29–39. https://doi.org/10.1080/14737175.2018.1399795

    Article  CAS  PubMed  Google Scholar 

  2. Gurewitz J, Schnurman Z, Nakamura A, Navarro RE, Patel DN, McMenomey SO, Roland JT, Golfinos JG, Kondziolka D (2022) Hearing loss and volumetric growth rate in untreated vestibular schwannoma. J Neurosurg 136(3):768–775. https://doi.org/10.3171/2021.2.Jns203609

    Article  PubMed  Google Scholar 

  3. Reznitsky M, Petersen M, West N, Stangerup SE, Cayé-Thomasen P (2019) Epidemiology of vestibular schwannomas—prospective 40-year data from an unselected national cohort. Clin Epidemiol 11:981–986. https://doi.org/10.2147/clep.S218670

    Article  PubMed  PubMed Central  Google Scholar 

  4. Carlson ML, Habermann EB, Wagie AE, Driscoll CL, Van Gompel JJ, Jacob JT, Link MJ (2015) The changing landscape of vestibular schwannoma management in the united states—a shift toward conservatism. Otolaryngol Head Neck Surg 153(3):440–446. https://doi.org/10.1177/0194599815590105

    Article  PubMed  Google Scholar 

  5. Jethanamest D, Rivera AM, Ji H, Chokkalingam V, Telischi FF, Angeli SI (2015) Conservative management of vestibular schwannoma: Predictors of growth and hearing. Laryngoscope 125(9):2163–2168. https://doi.org/10.1002/lary.25159

    Article  PubMed  Google Scholar 

  6. Stangerup SE, Thomsen J, Tos M, Cayé-Thomasen P (2010) Long-term hearing preservation in vestibular schwannoma. Otol Neurotol 31(2):271–275. https://doi.org/10.1097/MAO.0b013e3181c34bda

    Article  PubMed  Google Scholar 

  7. Joo JD, Oh SJ, Kim YH, Han JH, Choi BY, Koo JW, Kim CY (2017) Prognostic factors of hearing outcome in untreated vestibular schwannomas: implication of subdivision of their growth by volumetric analysis. World Neurosurg 106:768–774. https://doi.org/10.1016/j.wneu.2017.07.051

    Article  PubMed  Google Scholar 

  8. Hunter JB, Dowling EM, Lohse CM, O’Connell BP, Tombers NM, Lees KA, Thompson RS, Haynes DS, Carlson ML (2018) Hearing outcomes in conservatively managed vestibular schwannoma patients with serviceable hearing. Otol Neurotol 39(8):e704–e711. https://doi.org/10.1097/mao.0000000000001914

    Article  PubMed  Google Scholar 

  9. Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, Hoebers F, Rietbergen MM, Leemans CR, Dekker A, Quackenbush J, Gillies RJ, Lambin P (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5:4006. https://doi.org/10.1038/ncomms5006

    Article  CAS  PubMed  Google Scholar 

  10. Zhang B, Tian J, Dong D, Gu D, Dong Y, Zhang L, Lian Z, Liu J, Luo X, Pei S, Mo X, Huang W, Ouyang F, Guo B, Liang L, Chen W, Liang C, Zhang S (2017) Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma. Clin Cancer Res 23(15):4259–4269. https://doi.org/10.1158/1078-0432.Ccr-16-2910

    Article  PubMed  Google Scholar 

  11. Leijenaar RT, Carvalho S, Hoebers FJ, Aerts HJ, van Elmpt WJ, Huang SH, Chan B, Waldron JN, O’Sullivan B, Lambin P (2015) External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma. Acta Oncol 54(9):1423–1429. https://doi.org/10.3109/0284186x.2015.1061214

    Article  CAS  PubMed  Google Scholar 

  12. Itoyama T, Nakaura T, Hamasaki T, Takezaki T, Uentani H, Hirai T, Mukasa A (2022) Whole tumor radiomics analysis for risk factors associated with rapid growth of vestibular schwannoma in contrast-enhanced T1-weighted images. World Neurosurg 166:e572–e582. https://doi.org/10.1016/j.wneu.2022.07.058

    Article  PubMed  Google Scholar 

  13. Langenhuizen P, Zinger S, Leenstra S, Kunst HPM, Mulder JJS, Hanssens PEJ, de With PHN, Verheul JB (2020) Radiomics-based prediction of long-term treatment response of vestibular schwannomas following stereotactic radiosurgery. Otol Neurotol 41(10):e1321–e1327. https://doi.org/10.1097/mao.0000000000002886

    Article  PubMed  Google Scholar 

  14. Rorden C, Brett M (2000) Stereotaxic display of brain lesions. Behav Neurol 12(4):191–200. https://doi.org/10.1155/2000/421719

    Article  PubMed  Google Scholar 

  15. Lee SH, Cho HH, Lee HY, Park H (2019) Clinical impact of variability on CT radiomics and suggestions for suitable feature selection: a focus on lung cancer. Cancer Imaging 19(1):54. https://doi.org/10.1186/s40644-019-0239-z

    Article  PubMed  PubMed Central  Google Scholar 

  16. Tixier F, Le Rest CC, Hatt M, Albarghach N, Pradier O, Metges JP, Corcos L, Visvikis D (2011) Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 52(3):369–378. https://doi.org/10.2967/jnumed.110.082404

    Article  PubMed  Google Scholar 

  17. Chong Y, Kim JH, Lee HY, Ahn YC, Lee KS, Ahn MJ, Kim J, Shim YM, Han J, Choi YL (2014) Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy? PLoS ONE 9(2):e88598. https://doi.org/10.1371/journal.pone.0088598

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Aerts HJ, Grossmann P, Tan Y, Oxnard GR, Rizvi N, Schwartz LH, Zhao B (2016) Defining a radiomic response phenotype: a pilot study using targeted therapy in NSCLC. Sci Rep 6:33860. https://doi.org/10.1038/srep33860

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts H (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77(21):e104–e107. https://doi.org/10.1158/0008-5472.Can-17-0339

    Article  PubMed  PubMed Central  Google Scholar 

  20. Breiman L (2001) Random forests. Mach Learn 45(1):5–32. https://doi.org/10.1023/A:1010933404324

    Article  Google Scholar 

  21. Janitza S, Hornung R (2018) On the overestimation of random forest’s out-of-bag error. PLoS ONE 13(8):e0201904. https://doi.org/10.1371/journal.pone.0201904

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Patel NS, Huang AE, Dowling EM, Lees KA, Tombers NM, Lohse CM, Marinelli JP, Van Gompel JJ, Neff BA, Driscoll CLW, Link MJ, Carlson ML (2020) The influence of vestibular schwannoma tumor volume and growth on hearing loss. Otolaryngol Head Neck Surg 162(4):530–537. https://doi.org/10.1177/0194599819900396

    Article  PubMed  Google Scholar 

  23. Walsh RM, Bath AP, Bance ML, Keller A, Rutka JA (2000) Consequences to hearing during the conservative management of vestibular schwannomas. Laryngoscope 110(2 Pt 1):250–255. https://doi.org/10.1097/00005537-200002010-00012

    Article  CAS  PubMed  Google Scholar 

  24. Lapsiwala SB, Pyle GM, Kaemmerle AW, Sasse FJ, Badie B (2002) Correlation between auditory function and internal auditory canal pressure in patients with vestibular schwannomas. J Neurosurg 96(5):872–876. https://doi.org/10.3171/jns.2002.96.5.0872

    Article  PubMed  Google Scholar 

  25. Kano H, Kondziolka D, Khan A, Flickinger JC, Lunsford LD (2009) Predictors of hearing preservation after stereotactic radiosurgery for acoustic neuroma. J Neurosurg 111(4):863–873. https://doi.org/10.3171/2008.12.Jns08611

    Article  PubMed  Google Scholar 

  26. Song D, Zhai Y, Tao X, Zhao C, Wang M, Wei X (2021) Prediction of blood supply in vestibular schwannomas using radiomics machine learning classifiers. Sci Rep 11(1):18872. https://doi.org/10.1038/s41598-021-97865-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Plotkin SR, Stemmer-Rachamimov AO, Barker FG 2nd, Halpin C, Padera TP, Tyrrell A, Sorensen AG, Jain RK, di Tomaso E (2009) Hearing improvement after bevacizumab in patients with neurofibromatosis type 2. N Engl J Med 361(4):358–367. https://doi.org/10.1056/NEJMoa0902579

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cayé-Thomasen P, Werther K, Nalla A, Bøg-Hansen TC, Nielsen HJ, Stangerup SE, Thomsen J (2005) VEGF and VEGF receptor-1 concentration in vestibular schwannoma homogenates correlates to tumor growth rate. Otol Neurotol 26(1):98–101. https://doi.org/10.1097/00129492-200501000-00017

    Article  PubMed  Google Scholar 

  29. de Vries M, Briaire-de Bruijn I, Malessy MJ, de Bruïne SF, van der Mey AG, Hogendoorn PC (2013) Tumor-associated macrophages are related to volumetric growth of vestibular schwannomas. Otol Neurotol 34(2):347–352. https://doi.org/10.1097/MAO.0b013e31827c9fbf

    Article  PubMed  Google Scholar 

  30. Kontorinis G, Crowther JA, Iliodromiti S, Taylor WA, Locke R (2016) Neutrophil to lymphocyte ratio as a predictive marker of vestibular schwannoma growth. Otol Neurotol 37(5):580–585. https://doi.org/10.1097/mao.0000000000001026

    Article  PubMed  Google Scholar 

  31. Cho HH, Lee G, Lee HY, Park H (2020) Marginal radiomics features as imaging biomarkers for pathological invasion in lung adenocarcinoma. Eur Radiol 30(5):2984–2994. https://doi.org/10.1007/s00330-019-06581-2

    Article  PubMed  Google Scholar 

Download references

Funding

This study was supported by (1) a Korea University Grant, (2) a Grant of the Medical data-driven hospital support project through the Korea Health Information Service (KHIS), funded by the Ministry of Health and Welfare, Republic of Korea, and (3) the MSIT (Ministry of Science and ICT), Korea, under the ICAN (ICT Challenge and Advanced Network of HRD) program (IITP-2023-RS-2022-00156439) supervised by the IITP (Institute of Information and Communications Technology Planning and Evaluation).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to June Choi.

Ethics declarations

Conflict of interest

All authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

This study was approved by the Institutional Review Board of Korea University Ansan Hospital (No: 2022AS0300). The requirement for informed consent was waived due to the retrospective nature of the study.

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 30 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, K.H., Lee, Sh., Song, I. et al. Analysis of the association between vestibular schwannoma and hearing status using a newly developed radiomics technique. Eur Arch Otorhinolaryngol 281, 2951–2957 (2024). https://doi.org/10.1007/s00405-023-08410-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00405-023-08410-1

Keywords

Navigation