ArticleEuropean archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery2024
Analysis of the association between vestibular schwannoma and hearing status using a newly developed radiomics technique.
Article in European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
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Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it, 2 citations in OpenAlex.
- Machine learning for functional outcome prediction after vestibular schwannoma surgery: a systematic review and diagnostic test accuracy meta-analysis.Journal of neuro-oncology · 2026Pooled it
- Beyond the naked eye: a systematic review on the current state of radiomics approaches to the vestibular schwannoma.Journal of neuro-oncology · 2026Pooled it
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Authors and funding
9 authors at 1 institution in 2 countries.
Funding
Abstract
purposeVestibular 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.
methodsWe 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.
resultsThe 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.
conclusionsNewly developed radiomics features are associated with hearing status in patients with vestibular schwannoma and could provide information when deciding the treatment modality.
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