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Surgical Techniques Development
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Surgical Techniques Development
Article . 2024
Data sources: DOAJ
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Three-Dimensional Computed Tomography-Assisted Complex Lung Segmentectomies for Challenging Oncological Cases

Authors: Riccardo Orlandi; Lorenzo Gherzi; Michele Ferrari; Giovanni Mattioni; Marco Alifano; Alessandro Pardolesi;

Three-Dimensional Computed Tomography-Assisted Complex Lung Segmentectomies for Challenging Oncological Cases

Abstract

Background: anatomic lung segmentectomies allow accurate resection of pulmonary lesions, maximizing healthy tissue preservation, and reducing unnecessary loss of lung function. In this setting, accurate preoperative planning is crucial. We present our early experience, detailing the successful use of 3D-CT models in tailoring therapeutic strategies for three patients undergoing complex anatomical lung resections due to neoplastic diseases. Case Presentation: (1) 60-year-old male patient with significant pulmonary functional impairment underwent successful right lower lobe bi-segmentectomy (S7–S8) for carcinoid, stage IA1. (2) 65-year-old female patient with previous left lung resection and functional impairment underwent uneventful right upper lobe bi-segmentectomy (S1–S2) for double lung adenocarcinoma, stage IIb. (3) 67-year-old male with previous ipsilateral lung resection underwent left lower lobe segmentectomy (S8) for metastatic colic adenocarcinoma without any complications. Conclusion: 3D-CT imaging, particularly through VPTM platform, enhances the safety and precision of complex lung segmentectomy, providing a valuable surgical map for improved outcomes.

Keywords

lung cancer, tailored surgery, RD1-811, lung nodules, 3D-CT, Surgery, lung segmentectomy

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold
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Cancer Research