Development of a CT Image-Based Virtual Atelectasis Simulation Model and Noninvasive Lung Nodule Localization System

초록

Introduction This study aimed to develop a computed tomography-based virtual atelectasis simulation system for noninvasive lung nodule localization to improve the precision of presurgical planning for pulmonary nodule resections. Methods Contrast-enhanced computed tomography images of the lungs of 20 patients diagnosed with pulmonary nodules at Korea University Ansan Hospital between June 2021 and February 2024 were acquired, and image data were converted into three-dimensional models using 3D slicer. The mesh points extracted from these lung models were then manipulated to simulate the effects of gravity, by adjusting the lung shapes and nodule positions to align with the respective surgical postures. Subsequently, we assessed the similarity of the simulation by comparing the resulting deformed lung shape and nodule locations with the corresponding perspectives observed in the surgical videos. Results Overall, the average volume of the entire lung was 2,226 cm3 (±588) and the lung shrinkage rate was 48.6% (±12.9). Evaluations of an average of 15 pairs of images per case revealed significant conformity between atelectasis simulation images and surgical video snapshots, with average Dice and Jaccard similarity coefficient values of 90.28 and 88.25, respectively. Furthermore, the alignment of nodule positions between the simulations and surgical anticipation demonstrated notable accuracy, with an average Hausdorff distance of 6.39mm. Conclusions We developed a simulation of lung atelectasis based on preoperative computed tomography scans. The integration is anticipated to enhance the accuracy of locating nodules contributing to efficient and precise surgical planning.