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Neurofibromatosis type 2 (NF2) is an autosomal dominant genetic disorder resulting from germline mutations in the NF2 gene. Bilateral vestibular schwannomas, tumors on cranial nerve VIII, are pathognomonic for NF2 disease. Furthermore, schwannomas also commonly develop in other cranial nerves, dorsal root ganglia and peripheral nerves. These tumors are a major cause of morbidity and mortality, and medical therapies to treat them are limited. Animal models that accurately recapitulate the full anatomical spectrum of human NF2-related schwannomas, including the characteristic functional deficits in hearing and balance associated with cranial nerve VIII tumors, would allow systematic evaluation of experimental therapeutics prior to clinical use. Here, we present a genetically engineered NF2 mouse model generated through excision of the Nf2 gene driven by Cre expression under control of a tissue-restricted 3.9kbPeriostin promoter element. By 10 months of age, 100% of Postn-Cre; Nf2(flox/flox) mice develop spinal, peripheral and cranial nerve tumors histologically identical to human schwannomas. In addition, the development of cranial nerve VIII tumors correlates with functional impairments in hearing and balance, as measured by auditory brainstem response and vestibular testing. Overall, the Postn-Cre; Nf2(flox/flox) tumor model provides a novel tool for future mechanistic and therapeutic studies of NF2-associated schwannomas.

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Predicting survival of oral squamous cell carcinoma through the use of prediction modeling has been underused, and the development of prediction models would augment clinicians' ability to provide absolute risk estimates for individual patients.OBJECTIVES To develop a prediction model using machine learning for 5-year overall survival among patients with oral squamous cell carcinoma and compare this model with a prediction model created from the TNM (Tumor, Node, Metastasis) clinical and pathologic stage. DESIGN, SETTING, AND PARTICIPANTSA retrospective cohort study was conducted of 33 065 patients with oral squamous cell carcinoma from the National Cancer Data Base between January 1, 2004, and December 31, 2011. Patients were excluded if the treatment was considered palliative, staging demonstrated T0 or Tis, or survival or staging data were missing. Patient, tumor, treatment, and outcome information were obtained from the National Cancer Data Base. The data were split into a distribution of 80% for training and 20% for testing. The model was created using 2-class decision forest architecture. Permutation feature importance scores were used to determine the variables that were used in the model's prediction and their order of significance. Statistical analysis was conducted from August 1, 2018, to January 10, 2019.MAIN OUTCOMES AND MEASURES Ability to predict 5-year overall survival assessed through area under the curve, accuracy, precision, and recall. RESULTS Among the 33 065 patients in the study, the mean (SD) age was 64.6 (14.0) years, 19 791 were men (59.9%), 13 274 were women (40.1%), and 29 783 (90.1%) were white. At 60 months, there were 16 745 deaths (50.6%). The median time of follow-up was 56.8 months (range, 0-155.6 months). Age, pathologic T stage, positive margins at the time of surgery, lymph node size, and institutional identification were identified among the most significant variables. The calculated area under the curve for this machine learning model was 0.80 (95% CI, 0.79-0.81), accuracy was 71%, precision was 71%, and recall was 68%. In comparison, the calculated area under the curve of the TNM staging system was 0.68 (95% CI, 0.67-0.70), accuracy was 65%, precision was 69%, and recall was 52%.CONCLUSIONS AND RELEVANCE Using machine learning algorithms, a prediction model was created based on patient social, demographic, clinical, and pathologic features. The developed prediction model proved to be better than a prediction model that exclusively used TNM pathologic and clinical stage according to all performance metrics. This study highlights the role that machine learning may play in individual patient risk estimation in the era of big data.

Objective: Hearing loss remains a significant morbidity for patients with vestibular schwannomas (VS). A growing number of reports suggest audibility with cochlear implantation following VS resection; however, there is little consensus on preferred timing and cochlear implant (CI) performance. Data Sources: A systematic literature search of the Ovid Medline, Embase, Scopus, and clinicaltrails.gov databases was performed on 9/7/2018. PRISMA reporting guidelines were followed. Study Selection: Included studies reported CI outcomes in an ear that underwent a VS resection. Untreated VSs, radiated VSs, and CIs in the contralateral ear were excluded. Data Extraction: Primary outcomes were daily CI use and attainment of open-set speech. Baseline tumor and patient characteristics were recorded. Subjects were divided into two groups: simultaneous CI placement with VS resection (Group 1) versus delayed CI placement after VS resection (Group 2). Data Synthesis: Twenty-nine articles with 93 patients met inclusion criteria. Most studies were poor quality due to their small, retrospective design. Group 1 had 46 patients, of whom 80.4% used their CI on a daily basis and 50.0% achieved open-set speech. Group 2 had 47 patients, of whom 87.2% used their CI on a daily basis and 59.6% achieved open-set speech. Group 2 had more NF2 patients and larger tumors. CI timing did not significantly impact outcomes. Conclusions: Audibility with CI after VS resection is feasible. Timing of CI placement (simultaneous versus delayed) did not significantly affect performance. Overall, 83.9% used their CI on a daily basis and 54.8% achieved open-set speech.

Incidence of SVT is significantly underreported and may predispose patients to increase risk for CSF leak. Staged and translabyrinthine approaches demonstrate an increased trend toward thrombosis risk. Our findings suggest it may not be necessary to treat asymptomatic SVT.

Hearing loss is common and caused by a wide range of molecular and cellular pathologies. Current diagnosis of hearing loss depends on a combination of physiologic testing, patient history, and in some cases genetic testing. Currently, no biopsy or equivalent procedure exists to diagnose inner ear disorders. MicroRNAs (miRNA) are short ribonucleic acids that regulate a variety of cellular processes. They have been found to be reliable markers for a variety of disease processes. In particular, a variety of miRNAs that are markers for neurodegenerative disease have been identified in cerebrospinal fluid. The aim of this study was to determine whether miRNAs could be identified in human perilymph potentially leading to the development of biomarkers for inner ear disease. Prospective sampling of human perilymph and its analysis were carried out. Patients undergoing surgery in which the inner ear is opened as part of the procedure (cochlear implantation, stapedectomy, labyrinthectomy) were recruited. A total of 2-5 μl of perilymph was collected and analyzed using Affymetrix GeneChip miRNA 4.0 microarrays. MiRNA common to all sampling approaches were selected. Analysis of miRNAs was carried out by evaluating miRNA targets in a cochlear transcriptome library using the Ingenuity Pathway Analysis software package. MiRNAs could be isolated from the perilymph of all patients. Evaluation of miRNAs shows the presence of miRNA populations that are predicted to interact with genes expressed in the inner ear. Additional analysis of miRNA populations shows that perilymph miRNAs could be linked to pathways associated with hearing disorders. Sampling of human perilymph is feasible and can potentially identify miRNAs associated with hearing disorders.

Objective Our objective is to evaluate the safety in patients with cochlear implants (CIs) and auditory brainstem implants (ABI) undergoing 1.5 Tesla (T) magnetic resonance imaging (MRI). Secondly, we want to raise awareness on CI and MRI safety, and advocate for continued improvement and advancement to minimize morbidity for our CI patients. Methods Retrospective case series from 2006 to 2018 at a single tertiary academic center. Data was collected on patients with CI or auditory brainstem implants undergoing MRI. Outcomes collected include demographic data, age at time of MRI, MRI characteristics, complications, CI manufacturer, and image quality. Results Eighteen patients with CI or ABI collectively underwent a total of 62 MRI scans. Five of 15 (33%) CI patients with magnet had complications: five total of 24 MRI scans (21%). Two patients had magnet removal prior to 29 MRI scans without complications. Four of five MRI‐related complications were equipped with a U.S. Food and Drug Administration‐approved head wrap. Three of five required a trip to the operating room to explore and reposition the CI magnet; two could not complete MRI secondary to pain. Of the complications, two were Cochlear (Sydney, Australia), two Advanced Bionics (Valencia, CA), and one MED‐EL (Innsbruck, Austria). Synchrony model (MED‐EL) had 0 of seven complications, with a total of 19 MRI scans, which features a freely rotating and self‐aligning magnet. Conclusion Our series offers a diverse number of CI manufacturers and is in accordance with other literature that CI MRI‐related adverse events are occurring at an unacceptable frequency. We can promote CI MRI safety through our institutions' MRI CI patient protocols, raise awareness that diagnostic MRI benefits must outweigh CI‐related complications, and advocate for continued industry technological innovation. Level of Evidence 4 Laryngoscope, 129:482–489, 2019