Quantitative assessment and objective improvement of the accuracy of neurosurgical planning through digital patient-specific 3D models

Abstract

ObjectiveNeurosurgical patient-specific 3D models have been shown to facilitate learning, enhance planning skills and improve surgical results. However, there is limited data on the objective validation of these models. Here, we aim to investigate their potential for improving the accuracy of surgical planning process of the neurosurgery residents and their usage as a surgical planning skill assessment tool.MethodsA patient-specific 3D digital model of parasagittal meningioma case was constructed. Participants were invited to plan the incision and craniotomy first after the conventional planning session with MRI, and then with 3D model. A feedback survey was performed at the end of the session. Quantitative metrics were used to assess the performance of the participants in a double-blind fashion.ResultsA total of 38 neurosurgical residents and interns participated in this study. For estimated tumor projection on scalp, percent tumor coverage increased (66.4 ± 26.2%–77.2 ± 17.4%, p = 0.026), excess coverage decreased (2,232 ± 1,322 mm2–1,662 ± 956 mm2, p = 0.019); and craniotomy margin deviation from acceptable the standard was reduced (57.3 ± 24.0 mm–47.2 ± 19.8 mm, p = 0.024) after training with 3D model. For linear skin incision, deviation from tumor epicenter significantly reduced from 16.3 ± 9.6 mm–8.3 ± 7.9 mm after training with 3D model only in residents (p = 0.02). The participants scored realism, performance, usefulness, and practicality of the digital 3D models very highly.ConclusionThis study provides evidence that patient-specific digital 3D models can be used as educational materials to objectively improve the surgical planning accuracy of neurosurgical residents and to quantitatively assess their surgical planning skills through various surgical scenarios.

Narrative review of patient-specific 3D visualization and reality technologies in skull base neurosurgery: enhancements in surgical training, planning, and navigation

“…Continuous technological advancements and rigorous testing are crucial to improving these systems’ robustness and reliability. Collaboration with software developers to enhance compatibility and reduce latency is essential ( 106 ). Moreover, with ongoing progress in AI and machine learning, significant enhancements in automating and perfecting the procedure of generating 3D models are possible.…”