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Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery

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Published on: May 4, 2022

Development of a CT image-based virtual atelectasis simulation model and noninvasive lung nodule localization system.

Intae Hwang¹, Sungwon Ham¹, Chohee Kim²

¹Healthcare Readiness Institute for Unified Korea, Korea University College of Medicine, Seoul, Republic of Korea.

Journal of Thoracic Disease

|December 16, 2024

Summary

This study developed a virtual atelectasis simulation system using CT scans to accurately predict lung nodule locations during surgery. This improves precision for video-assisted thoracoscopic surgery (VATS) lung nodule resection planning.

Keywords:

3D atelectasis simulation image similarity evaluation lung nodule video-assisted thoracoscopic surgery (VATS)

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Area of Science:

Medical Imaging
Thoracic Surgery
Computational Modeling

Background:

Lung nodule resection via VATS often faces localization challenges due to discrepancies between preoperative CT scans (inspiration phase) and intraoperative lung status (atelectasis).
This difference complicates the precise identification of small or subsolid nodules during surgery.

Purpose of the Study:

To develop a CT-based virtual atelectasis simulation system for noninvasive lung nodule localization.
To enhance the precision of presurgical planning for lung nodule resections.

Main Methods:

Retrospective analysis of 20 patients undergoing VATS for lung nodules.
Conversion of preoperative CT images into 3D lung models.
Simulation of lung atelectasis by manipulating mesh points to mimic gravity and surgical posture, aligning nodule locations with intraoperative views.
Comparison of simulated lung shapes and nodule positions against surgical video recordings.

Main Results:

The simulation achieved an average lung shrinkage rate of 48.6%.
High conformity between simulation images and surgical videos was observed, with average Dice (90.27%) and Jaccard (88.25%) similarity coefficients.
Accurate nodule localization was confirmed, with an average Hausdorff distance of 6.39 mm.

Conclusions:

A CT-based virtual atelectasis simulation system was successfully developed, closely matching intraoperative surgical video findings.
This simulation system is expected to improve the accuracy of nodule localization.
The integration of this tool promises more efficient and precise surgical planning for lung nodule resections.