The new technology of precise anatomical sublobar resection by using 3D medical image analyzer and a fluorescence guided surgery with transbronchial injection of indocyanine green
Author(s) -
Yasuo Sekine,
Eitetsu Koh,
Hodaka Oheda,
Hidehisa Hoshino
Publication year - 2020
Publication title -
journal of visualized surgery
Language(s) - English
Resource type - Journals
ISSN - 2221-2965
DOI - 10.21037/jovs.2019.12.12
Subject(s) - indocyanine green , resection , medicine , margin (machine learning) , resection margin , surgical margin , radiology , nuclear medicine , surgery , computer science , machine learning
Pulmonary sublobar resection has been recognized as an operative option for complete resection of early stage lung cancer (1) and metastatic lung tumor. The standard approach for anatomical lung segmentectomy is vascular and bronchial transections followed by division of intersegmental planes. However, this method has several problems. The identification of segmental bronchi and associated vessels is sometimes difficult and intraoperative inflation of the lung is an obstacle for thoracoscopic visualization. Although the confirmation of an appropriate resection margin from the tumor is crucial for reducing the risk of local recurrence (2), there has been no method of measurement. Original Article
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