Segmentectomies made easy series: robotic-assisted right S3 segmentectomy

Robotic-assisted thoracic surgery has become an increasingly valuable technique for performing complex lung resections, offering high-definition visualization, refined instrument control and tremor-free precision. When compared to open thoracotomy, robotic approaches are linked to lower perioperative morbidity, shorter hospitalizations and quicker recovery times. Nonetheless, sublobar resections such as segmentectomy remain technically and anatomically challenging procedures, particularly in the presence of anatomical anomalies, as demonstrated in this case involving the right S3 segment. Combined three-dimensional reconstruction imaging enables detailed preoperative mapping of pulmonary anatomy, allowing surgeons to visualize bronchovascular structures with greater clarity and tailor dissection plans accordingly. Despite its proven benefits, the routine use of three-dimensional virtual imaging in thoracic surgery remains vastly underutilized and under-represented in the current literature. This video tutorial forms part of the Segmentectomies Made Easy atlas and presents a robotic right S3 segmentectomy for an incidental small pulmonary lesion. Preoperative three-dimensional reconstruction revealed a unique anatomical variation, which proved critical in guiding the dissection strategy. The tutorial offers a comprehensive, step-by-step overview of the operative process-from port configuration to anatomical isolation and resection-highlighting the value of three-dimensional imaging in improving surgical precision, intraoperative decision making and overall outcomes in robotic segmental lung surgery.

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Publication Details

Journal
Multimedia Manual of Cardio-Thoracic Surgery
Published
2025-08-11
DOI
https://doi.org/10.1510/mmcts.2025.063
Primary Topic
Surgical Simulation and Training
Type
article
Field-Weighted Citation Impact
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article

Segmentectomies made easy series: robotic-assisted right S3 segmentectomy

Zakariya Mouyer, Ayyoub Elfiky, Aishah Z Mughal, Ahmed M Habib
Multimedia Manual of Cardio-Thoracic Surgery
Surgical Simulation and Training
article

Segmentectomies made easy series: robotic-assisted right S3 segmentectomy

Zakariya Mouyer, Ayyoub Elfiky, Aishah Z Mughal, Ahmed M Habib
article en

Abstract

Robotic-assisted thoracic surgery has become an increasingly valuable technique for performing complex lung resections, offering high-definition visualization, refined instrument control and tremor-free precision. When compared to open thoracotomy, robotic approaches are linked to lower perioperative morbidity, shorter hospitalizations and quicker recovery times. Nonetheless, sublobar resections such as segmentectomy remain technically and anatomically challenging procedures, particularly in the presence of anatomical anomalies, as demonstrated in this case involving the right S3 segment. Combined three-dimensional reconstruction imaging enables detailed preoperative mapping of pulmonary anatomy, allowing surgeons to visualize bronchovascular structures with greater clarity and tailor dissection plans accordingly. Despite its proven benefits, the routine use of three-dimensional virtual imaging in thoracic surgery remains vastly underutilized and under-represented in the current literature. This video tutorial forms part of the Segmentectomies Made Easy atlas and presents a robotic right S3 segmentectomy for an incidental small pulmonary lesion. Preoperative three-dimensional reconstruction revealed a unique anatomical variation, which proved critical in guiding the dissection strategy. The tutorial offers a comprehensive, step-by-step overview of the operative process-from port configuration to anatomical isolation and resection-highlighting the value of three-dimensional imaging in improving surgical precision, intraoperative decision making and overall outcomes in robotic segmental lung surgery.

Multimedia Manual of Cardio-Thoracic SurgeryVol. 2025
New Cross Hospital (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 67%
Surgical Simulation and Training
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