A Novel Training Model to Improve Diagnostic Accuracy of Cervical Fine-Needle Aspiration.

Abstract

Introduction: This study aims to improve the diagnostic yield of cervical fine-needle aspiration (FNA) through training on a novel liver model. Ultrasonography-guided fine-needle aspiration (US-FNA) is crucial for diagnosing head and neck lumps but requires meticulous execution. Limited resources often hinder systematic teaching, making practical models essential for training.

Methods: Fifteen otorhinolaryngology residents trained using a liver model with inserted Sensorium spheres to simulate cervical masses. The training involved viewing an instructional video, performing US-FNA on the model, and completing pre- and posttraining self-assessments. Performance was evaluated using visual analog scales (VAS), an adapted version of objective structured assessment of ultrasound skills (adapted OSAUS), and timing of procedures. Clinical impact was assessed by comparing diagnostic rates of US-FNA before and after training.

Results: Participants reported increased comfort and proficiency in US-FNA techniques posttraining. Adapted OSAUS scores improved significantly for image recognition and both in-plane and out-of-plane techniques. The diagnostic yield of US-FNA in clinical practice increased from 71% to 85%. No significant influence of gender, preferred ultrasound orientation, age, or experience on the learning curve was found. However, male participants showed a more substantial benefit from the training.

Conclusion: The liver model effectively enhances US-FNA skills, reflected in improved clinical diagnostic rates. Training on such models should be incorporated into medical education to reduce inconclusive punctures and enhance patient satisfaction. This study demonstrates the feasibility and effectiveness of a cost-efficient, reproducible model for US-FNA training, emphasizing the importance of practical training in medical education.