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Purpose: Appropriate reconstruction of the canal wall or maintenance of the middle ear pressure in cholesteatoma may help in preventing recurrence. Retrograde mastoidectomy with canal wall reconstruction (RMR) can overcome the challenge of a wider canal wall defect or temporal bone immaturity, which possibly increases the recurrence risk. This study compared the outcomes of RMR and intact canal wall tympanomastoidectomy (ICW) for cholesteatomas with minimal mastoid extension and quantitatively evaluate the relationship between anatomical features and recurrence. Methods: This single-center retrospective cohort study included patients who had undergone primary ICW or RMR for pars flaccida cholesteatoma with minimal mastoid extension from 2009 to 2019. The main outcome measures were anatomical measurements of the shortest distance between the cranial fossa and the upper canal wall (SCU), attic volume, and bony defect area of the canal wall (BDC) on computed tomography; recidivism; and postoperative air–bone gap (ABG). Results: There were no significant differences in the preoperative anatomical factors, recidivism incidence, and postoperative ABG between the RMR (n = 20) and ICW (n = 60) groups. However, the median BDC was significantly greater in the RMR group (58.3 vs. 37.0 mm2). There was no significant difference in the SCU and attic volume between patients with and without recurrence. Conclusion: Selection of RMR or ICW may not affect recidivism and hearing outcomes in cholesteatoma with minimal mastoid extension. Bony defect size and attic narrowness were not associated with recurrence. Considering wider visualization and one-staged operation, RMR can be more adaptable than ICW for cholesteatoma with minimal mastoid extension. [ABSTRACT FROM AUTHOR]

Cholesteatoma is a progressive middle ear disease that can only be treated surgically but with a high recurrence rate. Depending on the extent of the disease, a surgical approach, such as microsurgery with a retroarticular incision or transcanal endoscopic surgery, is performed. However, the current examination cannot sufficiently predict the progression before surgery, and changes in approach may be made during the surgery. Large amounts of data are typically required to train deep neural network models; however, the prevalence of cholesteatomas is low (1-in-25, 000). Developing analysis methods that improve the accuracy with such a small number of samples is an important issue for medical artificial intelligence (AI) research. This paper presents an AI-based system to automatically detect mastoid extensions using CT. This retrospective study included 164 patients (80 with mastoid extension and 84 without mastoid extension) who underwent surgery. This study adopted a relatively lightweight neural network model called MobileNetV2 to learn and predict the CT images of 164 patients. The training was performed with eight divided groups for cross-validation and was performed 24 times with each of the eight groups to verify accuracy fluctuations caused by randomly augmented learning. An evaluation was performed by each of the 24 single-trained models, and 24 sets of ensemble predictions with 23 models for 100% original size images and 400% zoomed images. Fifteen otolaryngologists diagnosed the images and compared the results. The average accuracy of predicting 400% zoomed images using ensemble prediction model was 81.14% (sensitivity = 84.95%, specificity = 77.33%). The average accuracy of the otolaryngologists was 73.41% (sensitivity, 83.17%; specificity, 64.13%), which was not affected by their clinical experiences. Noteworthily, despite the small number of cases, we were able to create a highly accurate AI. These findings represent an important first step in the automatic diagnosis of the cholesteatoma extension. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to clarify the usefulness of high-resolution computed tomography (HRCT) and establish HRCT criteria for presurgical assessment of the mastoid extension in pars flaccida cholesteatomas of the middle ear.Methods: Retrospective observational study. Patients who underwent primary surgery for pars flaccida cholesteatoma and those who underwent temporal bone HRCT for pretreatment evaluation were reviewed. The distance in the anterior-most portion of the mastoid sinus on HRCT was measured, and the presence of surgically verified mastoid extension of cholesteatoma was evaluated. All cases were subclassified as M+ (surgically mastoid extension-positive) or M- (surgically mastoid extension-negative).Results: A total of 107 patients with pars flaccida cholesteatoma were included. The distance in the M+ cases was significantly longer than that in the M- cases, and the cutoff value was 3.6 mm. The difference between the ipsilateral/diseased-side distance and the contralateral/evaluable side (difference value) in M+ cases was larger than that in M- cases, with a cutoff value of 0.6 mm. The inter-rater reliability of this distance measurement was excellent, regardless of imaging experience.Conclusions: The cutoff values of the distance and the difference value can be used for pretreatment HRCT evaluation of mastoid extension in middle ear cholesteatoma with relatively high accuracy, regardless of the experience and skill levels of the evaluator. [ABSTRACT FROM AUTHOR]