Risk factors associated with vestibulocochlear nerve schwannoma: systematic review

Corona, Ana Paula; Oliveira, Jacqueline Carneiro; Souza, Fàbia Pinheiro Andrade de; Santana, Liane Viana; Rêgo, Marco Antônio Vasconcelos

doi:10.1590/s1808-86942009000400020

Cited by 5 publications

(5 citation statements)

References 36 publications

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“…4 About 25 to 48% of all cases affect the region of the head and neck; in the oral cavity, it is mainly seen in the tongue, the buccal mucosa, and the lips. 5 Its pathology is characterized by solid, subcutaneous, asymptomatic lesions; 6 histologically it is composed of prototypes of cell organization called Antoni A and Antoni B.…”

Section: Introductionmentioning

confidence: 99%

“…3 En la mayoría de los casos, el tumor inicia entre los 20 y 60 años de edad; 4 la tasa de incidencia mundial es de 1 a 20 casos por 1.000.000 de habitantes por año. 4 Cerca del 25 al 48% de los casos afecta la región de la cabeza y cuello; en la cavidad oral se observa principalmente en lengua, mucosa bucal y labio. 5 Su anatomía patológica se caracteriza por lesiones só-lidas, subcutáneas y asintomáticas; 6 histológicamente está compuesto por prototipos de organización celular denominados Antoni A y Antoni B.…”

Section: Introductionunclassified

“…2 Una vez realizada la escisión quirúrgica de la lesión, el diagnóstico tiene lugar en el momento en que se lleve a cabo el estudio histopatológico. 4 De igual forma, una tomografía computarizada o una imagen de resonancia magnética pueden mostrar la extensión de la lesión. 10 Las pruebas inmunohistoquímicas muestran que las células del schwannoma son positivas para la proteína S-100.…”

Section: Introductionunclassified

“…4 Similarly, a CT scan or a magnetic resonance image can show the extent of the lesion. 10 The immunohistochemical tests show that the schwannoma cells are positive for protein S-100.…”

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confidence: 99%

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Clinical, Pathological, And Immunohistochemical Analysis Of Schwannoma In Oral Cavity: A Case Report

Mercado

Osorio

Tasamá

et al. 2017

Rev. Fac. Odontol. Univ. Antioq.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionunclassified

“…4 Similarly, a CT scan or a magnetic resonance image can show the extent of the lesion. 10 The immunohistochemical tests show that the schwannoma cells are positive for protein S-100.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Clinical, Pathological, And Immunohistochemical Analysis Of Schwannoma In Oral Cavity: A Case Report

Mercado

Osorio

Tasamá

et al. 2017

Rev. Fac. Odontol. Univ. Antioq.

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“…Patients with sporadic vestibular schwannomas most commonly present with unilateral sensorineural hearing loss (94%) and tinnitus (83%), and less frequently vestibular symptoms such as vertigo or unsteadiness (3,5). These symptoms unfortunately are nonspecific, and there are no clearly defined characteristics around which to create screening criteria (6–8). Therefore, workup and diagnosis are typically prompted by asymmetric sudden or progressive sensorineural hearing loss.…”

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confidence: 99%

Machine Learning for Vestibular Schwannoma Diagnosis Using Audiometrie Data Alone

Carey

Jacobson

Warburton

et al. 2022

Otology &Amp; Neurotology

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Objective:The aim of this study is to compare machine learning algorithms and established rule-based evaluations in screening audiograms for the purpose of diagnosing vestibular schwannomas. A secondary aim is to assess the performance of rule-based evaluations for predicting vestibular schwannomas using the largest dataset in the literature.Study Design:Retrospective case-control study.Setting:Tertiary referral center.Patients:Seven hundred sixty seven adult patients with confirmed vestibular schwannoma and a pretreatment audiogram on file and 2000 randomly selected adult controls with audiograms.Intervention(s):Audiometric data were analyzed using machine learning algorithms and standard rule-based criteria for defining asymmetric hearing loss.Main Outcome Measures:The primary outcome is the ability to identify patients with vestibular schwannomas based on audiometric data alone, using machine learning algorithms and rule-based formulas. The secondary outcome is the application of conventional rule-based formulas to a larger dataset using advanced computational techniques.Results:The machine learning algorithms had mildly improved specificity in some fields compared with rule-based evaluations and had similar sensitivity to previous rule-based evaluations in diagnosis of vestibular schwannomas.Conclusions:Machine learning algorithms perform similarly to rule-based evaluations in identifying patients with vestibular schwannomas based on audiometric data alone. Performance of established rule-based formulas was consistent with earlier performance metrics, when analyzed using a large dataset.

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Acoustic neuroma risk in relation to mobile telephone use: Results of the INTERPHONE international case–control study

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Cancer Epidemiology

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Risk factors associated with vestibulocochlear nerve schwannoma: systematic review

Cited by 5 publications

References 36 publications

Clinical, Pathological, And Immunohistochemical Analysis Of Schwannoma In Oral Cavity: A Case Report

Clinical, Pathological, And Immunohistochemical Analysis Of Schwannoma In Oral Cavity: A Case Report

Machine Learning for Vestibular Schwannoma Diagnosis Using Audiometrie Data Alone

Acoustic neuroma risk in relation to mobile telephone use: Results of the INTERPHONE international case–control study

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