AI Article Synopsis
- The study aimed to determine if 3D reconstructed images can accurately represent lung adenocarcinoma tumors and help in surgical planning.
- Retrospective analysis of 18 patients who underwent segmentectomy and 3D reconstruction showed that the measurements from the 3D models correlated well with actual pathology results, particularly for resection margins.
- The findings suggest that 3D models enhance understanding of lung anatomy and support confident pre-operative planning, making them a practical tool for segmentectomy procedures.
Article Abstract
Background: The objective of our study was to assess if 3D reconstructed images could be extrapolated to reflect pathologies, as evaluated by early-stage lung adenocarcinoma tumor size and simulated segmentectomy resection margin.
Methods: Retrospectively selected patients ( = 18) who underwent segmentectomy at Changhua Christian Hospital between 2012 and 2018 and then had pulmonary 3D reconstruction using Ziostation2 were included in our study. Tumor size and simulated segmentectomy resection distance on a 3D model were measure and compared to pathology.
Results: Both tumor size and segmentectomy resection margin showed positive correlations between 3D image measurements and pathological measurements. The resection margin showed a stronger correlation and was beneficial in pre-operative planning.
Conclusions: A 3D reconstructed model aided understanding of pulmonary anatomy, prompting confidence in surgical approaches and ensured segmentectomy outcome success. Regardless of age and pulmonary function, 3D simulation can accurately mimic segmentectomy, making it a simple, effective and feasible pre-operative planning tool.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605571 | PMC |
| http://dx.doi.org/10.3390/jcm11206155 | DOI Listing |
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