Application of lipid and polymeric-based nanoparticles for treatment of inner ear infections via XGBoost.

Taking hearing loss as a prevalent sensory disorder, the restricted permeability of blood flow and the blood-labyrinth barrier in the inner ear pose significant challenges to transporting drugs to the inner ear tissues. The current options for hear loss consist of cochlear surgery, medication, and hearing devices. There are some restrictions to the conventional drug delivery methods to treat inner ear illnesses, however, different smart nanoparticles, including inorganic-based nanoparticles, have been presented to regulate drug administration, enhance the targeting of particular cells, and decrease systemic adverse effects. Zinc oxide nanoparticles possess distinct characteristics that facilitate accurate drug delivery, improved targeting of specific cells, and minimized systemic adverse effects. Zinc oxide nanoparticles was studied for targeted delivery and controlled release of therapeutic drugs within specific cells. XGBoost model is used on the Wideband Absorbance Immittance (WAI) measuring test after cochlear surgery. There were 90 middle ear effusion samples (ages = 1-10 years, mean = 34.9 months) had chronic middle ear effusion for four months and verified effusion for seven weeks. In this research, 400 sets underwent wideband absorbance imaging (WAI) to assess inner ear performance after surgery. Among them, 60 patients had effusion Otitis Media with Effusion (OME), while 30 ones had normal ears (control). OME ears showed significantly lower absorbance at 250, 500, and 1000 Hz than controls (p < 0.001). Absorbance thresholds >0.252 (1000 Hz) and >0.330 (2000 Hz) predicted a favorable prognosis (p < 0.05, odds ratio: 6). It means that cochlear surgery and WAI showed high function in diagnosis and treatment of inner ear infections. Regarding the R2 0.899 and RMSE 1.223, XGBoost shows excellent specificity and sensitivity for categorizing ears as having effusions absent or present or partial or complete flows present, with areas under the curve (1-0.944).

Refining feasibility assessment of endoscopic ear surgery: a radiomics model utilizing machine learning on external auditory canal CT scans.

BACKGROUND: Feasibility assessment of endoscopic ear surgery (EES) relies solely on subjective evaluation by surgeons. OBJECTIVE: Extracting radiomic features from preoperative CT images of the external auditory canal, we aim to classify EES patients into easy and difficult groups and improve accuracy in determining surgery feasibility. METHODS: 85 patients' external auditory canal CT scans were collected and 139 radiomic features were extracted using PyRadiomics. The most relevant features were selected and three machine learning algorithms (logistic regression, support vector machine, and random forest) were compared using K-fold cross-validation (k = 5) to predict surgical feasibility. RESULTS: The best-performing machine learning model, the support vector machine (SVM), was selected to predict the difficulty of EES. The proposed model achieved a high accuracy of 86.5%, and F1 score of 84.6%. The area under the ROC curve was 0.93, indicating good discriminatory power. CONCLUSIONS AND SIGNIFICANCE: The proposed machine learning model provides a reliable and accurate method for classifying patients undergoing otologic surgery based on preoperative imaging data. The model can help clinicians to better prepare for challenging surgical cases and optimize treatment plans for individual patients.

Transcanal endoscopic management of isolated congenital middle ear malformations.

BACKGROUND: A few studies have reported transcanal endoscopic management of isolated congenital middle ear malformations (CMEMs). OBJECTIVE: The purpose of this study is to describe our surgical experience in endoscopic ear surgery for isolated CMEMs and evaluate the surgical effect of hearing reconstruction. METHODS: From January 2017 to January 2022, a retrospective study was performed on 36 patients (37 ears) with isolated CMEMs who all underwent endoscopic surgery. Demographic data, high-resolution computed tomography (HRCT) findings, intraoperative findings, surgical management and audiometric data were recorded. RESULTS: Anomalies were categorized according to the Teunissen and Cremers classification system: 8 ears were categorized as class I, 8 ears as class II, 19 ears as class III and 2 ears as class IV. The air conduction pure tone average (AC-PTA) of 37 cases was 61.5 ± 8.6 dB preoperatively and 29.6 ± 6.9 dB postoperatively (p < 0.001). The mean preoperative air-bone gap (ABG) significantly decreased from 43.1 ± 8.7 dB to 12.8 ± 5.5 dB postoperatively. 36 of 37 cases (97%) met the criteria for successful operation. CONCLUSION: Isolated CMEMs are mainly manifested as aplasia of the stapes' superstructure and dysplasia of the long process of the incus. Transcanal endoscopic surgery seems a safe technique for the management of isolated CMEMs.