Evaluating the Impact of 3d Anatomical Model Based Training on the Learning Curve of Endoscopic Endonasal Surgery

The complexity of surgical procedures necessitates continuous education andinnovative training methodologies for neurosurgeons. The learning curve inendoscopic endonasal approach (EEA) is challenging due to the intricateanatomical landscape and the advanced skills required for effective and safeexecution. (Koc et al., 2006; Younus et al., 2020). Structured training programsusing 3D-printed models provide a unique opportunity to enhance technicalskills while minimizing risks to patients. Such programs have been shown tosignificantly impact the confidence and proficiency of trainees, bridging the gapbetween theoretical knowledge and practical application (De Win et al., 2016;Gurses et al., 2024). This study evaluates the effectiveness of a 3D-printedmodel-based training program for EEA, focusing on its impact on the learningcurve of neurosurgery residents and specialists.MethodsThis prospective study was conducted in the clinical and application laboratoryat XXX University Department of Neurosurgery, focusing on the evaluation of astructured 3D-printed model-based training program for EEA. The courseincluded 24 participants, all practicing neurosurgeons, consisting of both residents and specialists with varying levels of prior experience in endoscopic pituitary surgery. The training program involved the use of 3D-printed anatomicalmodels designed to replicate the critical steps of EEA. The first step involvesharvesting the nasoseptal flap and identifying the nasal turbinates, sphenoidostium, and choana. The second step is performing a sphenoidotomy and identifying the anatomical landmarks within the sphenoid sinus. The third step involves performing a sellar osteotomy. Participants completed a pre-course andpost-course questionnaire to assess their self-perceived proficiency and confidence in performing the key steps of EEA. During independent practice session,procedural times of all participants are also recorded.ResultsThe analysis focused on responses to eight questions evaluating participants'ability to perform key steps in endoscopic endonasal pituitary surgery beforeand after the training (Table 1). Before the training, recognition of nasal turbinates was reported by 87.5% of participants, which improved to 100% after thetraining. Similarly, identification of the sphenoid ostium showed an increasefrom 66.7% pre-training to 100% post-training. The ability to perform anteriorsphenoidotomy rose from 54.2% to 100%, while recognition of sphenoid sinusstructures improved from 70.8% to 91.7%, although this change was not statistically significant (p < 0.125). Accessing the sella base saw a statisticallysignificant increase from 54.2% to 91.7% (p < 0.05), while opening the sellardura improved from 50% to 75%, but this change was not statistically significant(p < 0.109). Tumor removal capability increased modestly from 50% to 66.7%,with no statistical significance (p < 0.289). Lastly, nasoseptal flap preparationdemonstrated the most significant improvement, rising from 37.5% pre-trainingto 95.8% post-training (p < 0.001).ConclusionsThis study highlights the potential of 3D-printed anatomical models as a valuable tool in neurosurgical education. By providing an accessible and effectivetraining platform, these models have the capacity to significantly enhance thelearning curve of neurosurgeons in endoscopic endonasal approaches. Futureresearch should explore hybrid training methodologies and expand upon thefindings of this study to further optimize surgical education and patientoutcomes.