[A male with a pulsating ear drum]. / Een man met een kloppend trommelvlies.

A 28-year-old male presented with non-pulsatile tinnitus, rightsided hearing loss and an ipsilateral pulsating ear drum. A CT-scan revealed an aberrant internal carotid artery in the middle ear. This is an uncommon finding. Recognition of this birth analomy is important since ear manipulation or surgery can lead to life-threatening complications.

Fully Automated 3D Vestibular Schwannoma Segmentation with and without Gadolinium-based Contrast Material: A Multicenter, Multivendor Study.

Purpose: To develop automated vestibular schwannoma measurements on contrast-enhanced T1- and T2-weighted MRI scans. Materials and Methods: MRI data from 214 patients in 37 different centers were retrospectively analyzed between 2020 and 2021. Patients with hearing loss (134 positive for vestibular schwannoma [mean age ± SD, 54 years ± 12;64 men] and 80 negative for vestibular schwannoma) were randomly assigned to a training and validation set and to an independent test set. A convolutional neural network (CNN) was trained using fivefold cross-validation for two models (T1 and T2). Quantitative analysis, including Dice index, Hausdorff distance, surface-to-surface distance (S2S), and relative volume error, was used to compare the computer and the human delineations. An observer study was performed in which two experienced physicians evaluated both delineations. Results: The T1-weighted model showed state-of-the-art performance, with a mean S2S distance of less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.92 and 2.1 mm in the independent test set, respectively. T2-weighted images had a mean S2S distance less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.87 and 1.5 mm in the independent test set. The observer study indicated that the tool was similar to human delineations in 85%-92% of cases. Conclusion: The CNN model detected and delineated vestibular schwannomas accurately on contrast-enhanced T1- and T2-weighted MRI scans and distinguished the clinically relevant difference between intrameatal and extrameatal tumor parts.Keywords: MRI, Ear, Nose, and Throat, Skull Base, Segmentation, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms Supplemental material is available for this article. © RSNA, 2022.

A prediction model for recurrence after translabyrinthine surgery for vestibular schwannoma: toward personalized postoperative surveillance.

PURPOSE: The aim of this study is to compute and validate a statistical predictive model for the risk of recurrence, defined as regrowth of tumor necessitating salvage treatment, after translabyrinthine removal of vestibular schwannomas to individualize postoperative surveillance. METHODS: The multivariable predictive model for risk of recurrence was based on retrospectively collected patient data between 1995 and 2017 at a tertiary referral center. To assess for internal validity of the prediction model tenfold cross-validation was performed. A 'low' calculated risk of recurrence in this study was set at < 1%, based on clinical criteria and expert opinion. RESULTS: A total of 596 patients with 33 recurrences (5.5%) were included for analysis. The final prediction model consisted of the predictors 'age at time of surgery', 'preoperative tumor growth' and 'first postoperative MRI outcome'. The area under the receiver operating curve of the prediction model was 89%, with a C-index of 0.686 (95% CI 0.614-0.796) after cross-validation. The predicted probability for risk of recurrence was low (< 1%) in 373 patients (63%). The earliest recurrence in these low-risk patients was detected at 46 months after surgery. CONCLUSION: This study presents a well-performing prediction model for the risk of recurrence after translabyrinthine surgery for vestibular schwannoma. The prediction model can be used to tailor the postoperative surveillance to the estimated risk of recurrence of individual patients. It seems that especially in patients with an estimated low risk of recurrence, the interval between the first and second postoperative MRI can be safely prolonged.

Prognostic Factors for the Outcome of Translabyrinthine Surgery for Vestibular Schwannomas.

OBJECTIVE: To identify predictors of tumor recurrence and postoperative facial nerve function after translabyrinthine surgery for unilateral vestibular schwannomas. STUDY DESIGN: Retrospective study. SETTING: Tertiary referral center. PATIENTS: Between 1996 and 2017 a total of 596 patients with unilateral vestibular schwannoma underwent translabyrinthine surgery. Pre- and postoperative clinical status, radiological, and surgical findings were evaluated. INTERVENTIONS: Translabyrinthine surgery. MAIN OUTCOME MEASURES: Potential predictors for tumor recurrence and facial nerve outcome were analyzed using Cox regression and ordinal logistic regression, respectively. RESULTS: The extent of tumor removal was total in 32%, near-total in 58%, and subtotal in 10%. In 5.5% (33/596) of patients the tumor recurred. Subtotal tumor resection (p = 0.004, hazard ratios [HR] = 10.66), a young age (p = 0.008, HR = 0.96), and tumor progression preoperatively (p = 0.042, HR = 2.32) significantly increased the risk of recurrence, whereas tumor size or histologic composition did not. A good postoperative facial nerve function (House-Brackmann grade 1-2) was achieved in 85%. The risk of postoperative facial nerve paresis or paralysis increased with tumor size (p < 0.001, OR = 1.52), but was not associated with the extent of tumor removal, histologic composition, or patient demographics. CONCLUSIONS: Translabyrinthine surgery is an effective treatment for vestibular schwannoma, with a good local control rate and facial nerve outcome. The extent of tumor removal is a clinically relevant predictor for tumor recurrence, as are young patient age and preoperative tumor progression. A large preoperative tumor size is associated with a higher risk of postoperative facial nerve paresis or paralysis.

Impact of surgical intervention trials on healthcare: A systematic review of assessment methods, healthcare outcomes, and determinants.

BACKGROUND: Frameworks used in research impact evaluation studies vary widely and it remains unclear which methods are most appropriate for evaluating research impact in the field of surgical research. Therefore, we aimed to identify and review the methods used to assess the impact of surgical intervention trials on healthcare and to identify determinants for surgical impact. METHODS: We searched journal databases up to March 10, 2020 for papers assessing the impact of surgical effectiveness trials on healthcare. Two researchers independently screened the papers for eligibility and performed a Risk of Bias assessment. Characteristics of both impact papers and trial papers were summarized. Univariate analyses were performed to identify determinants for finding research impact, which was defined as a change in healthcare practice. RESULTS: Sixty-one impact assessments were performed in 37 included impact papers. Some surgical trial papers were evaluated in more than one impact paper, which provides a total of 38 evaluated trial papers. Most impact papers were published after 2010 (n = 29). Medical records (n = 10), administrative databases (n = 22), and physician's opinion through surveys (n = 5) were used for data collection. Those data were analyzed purely descriptively (n = 3), comparing data before and after publication (n = 29), or through time series analyses (n = 5). Significant healthcare impact was observed 49 times and more often in more recent publications. Having impact was positively associated with using medical records or administrative databases (ref.: surveys), a longer timeframe for impact evaluation and more months between the publication of the trial paper and the impact paper, data collection in North America (ref.: Europe), no economic evaluation of the intervention, finding no significant difference in surgical outcomes, and suggesting de-implementation in the original trial paper. CONCLUSIONS AND IMPLICATIONS: Research impact evaluation receives growing interest, but still a small number of impact papers per year was identified. The analysis showed that characteristics of both surgical trial papers and impact papers were associated with finding research impact. We advise to collect data from either medical records or administrative databases, with an evaluation time frame of at least 4 years since trial publication.