Lirit Levi

All Publications

• Machine learning of endoscopy images to identify, classify, and segment sinonasal masses. International forum of allergy & rhinology Levi, L., Ye, K., Fieux, M., Renteria, A., Lin, S., Xing, L., Ayoub, N. F., Patel, Z. M., Nayak, J. V., Hwang, P. H., Chang, M. T. 2025

  Abstract

  We developed and assessed the performance of a machine learning model (MLM) to identify, classify, and segment sinonasal masses based on endoscopic appearance.A convolutional neural network-based model was constructed from nasal endoscopy images from patients evaluated at an otolaryngology center between 2013 and 2024. Images were classified into four groups: normal endoscopy, nasal polyps, benign, and malignant tumors. Polyps and tumors were confirmed with histopathological diagnosis. Images were annotated by an otolaryngologist and independently verified by two other otolaryngologists. We used high- and low-quality images to mirror real-world conditions. The models used for classification (EfficientNet-B2) and segmentation (nnUNet) were trained, validated, and tested at an 8:1:1 ratio. The performance accuracy was averaged across a 10-fold cross-validation assessment. Segmentation accuracy was assessed via Dice similarity coefficients.A total of 1242 images from 311 patients were used. The MLM was trained, validated, and tested on 663 normal, 276 polyps, 157 benign, and 146 malignant tumors images. Overall, the model performed at 84.1 ± 4.3% accuracy in the validation set and 80.4 ± 1.7% in the test set. The model correctly identified the presence of a sinonasal mass at 90.5 ± 1.2% accuracy rate. The MLM accuracy performance rates were 86.2 ± 1.0% for polyps and 84.1 ± 1.8% for tumors. Benign and malignant tumor subclassification achieved 87.8 ± 2.1% and 94.0 ± 2.4% accuracy, respectively. Segmentation accuracies for polyps were 72.3% and 72.8% for tumors.An MLM for nasal endoscopy images can perform with moderate to high accuracy in identifying, classifying, and segmenting sinonasal masses. Performance in future iterations may improve with larger and more diverse training datasets.

  View details for DOI 10.1002/alr.23525

  View details for PubMedID 39776302

• Stepwise Empty Nose Syndrome Evaluation (SENSE) test-A modified cotton test for reduced bias in office diagnosis of empty nose syndrome. International forum of allergy & rhinology Levi, L., Yang, A., Tsai, E. F., Ma, Y., Ibrahim, N., Dholakia, S. S., Rao, V. K., Renteria, A., Cao, X., Chang, M. T., Nayak, J. V. 2024

  Abstract

  Diagnosis of empty nose syndrome (ENS) relies on the ENS six-item questionnaire (ENS6Q) with a score of ≥11, followed by a "positive" cotton test yielding seven-point reduction from baseline ENS6Q score via cotton placement to the inferior meatus (IM). Given the intricacies of diagnosing ENS and the propensity for false positives with the standard cotton test, we modified the classic single-step cotton test into a four-part Stepwise Empty Nose Syndrome Evaluation (SENSE) cotton test to reduce bias and evaluate the placebo effect.Individuals diagnosed with ENS underwent the SENSE test, a single-blinded, four-step, office-based cotton test, without topical anesthesia or decongestants. Conditions included: (1) placebo/no cotton placed; (2) complete cotton-blockade of nasal vestibule; (3) cotton placed medially against the nasal septum; and (4) cotton placed laterally in the IM (site of inferior turbinate tissue loss). With each condition, patients completed an ENS6Q.Forty-eight ENS patients were included. Twenty-nine percent demonstrated a placebo effect (p < 0.001), 40.4% had a positive response to complete cotton-blockade (p < 0.001), 64.4% to septum-placed cotton, and 79.1% to IM-placed cotton (p < 0.001), corresponding to a mean ENS6Q reduction of 11.9 points (p < 0.001). Notably, the mean difference in ENS6Q scores between septum and IM placement was 1.7 (p < 0.001).The SENSE test offers further insight into subtleties of nasal breathing experienced by ENS patients. The placebo effect can be prominent and important to consider with individual patients. While most ENS patients prefer any intranasal cotton placement over baseline, blinded testing reveals these patients can accurately discriminate minimal changes in nasal aerodynamics.

  View details for DOI 10.1002/alr.23442

  View details for PubMedID 39373717