Management of robotic bleeding complications

Novellis, Pierluigi; Jadoon, Mehmood; Cariboni, Umberto; Bottoni, Edoardo; Pardolesi, Alessandro; Veronesi, Giulia

doi:10.21037/asvide.2019.097

Cited by 3 publications

(4 citation statements)

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“…In anatomical segmentectomy or subsegmentectomy, it is extremely important to master the types of the segmental and subsegmental bronchus. When planning a major lung resection the risk of conversion vary from 6.2% to 9.6%, being higher in video-assisted thoracic surgery (VATS) with unexpected bleeding as the leading cause (21,23). Accurate preoperative study (24,25) can reduce this risk to 2.6% and up to 0%, when a printed 3D model is available.…”

Section: Discussionmentioning

confidence: 99%

Anatomical analysis of variations in the bronchus pattern of the left upper lobe using three-dimensional computed tomography angiography and bronchography

He¹,

Wang²,

Wang³

et al. 2022

Ann Transl Med

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Background: The number of sublobar resections performed is increasing, thoracic surgeons must be familiar with bronchus anatomy and preoperative planning plays an important role in predicting anatomical variations. However, there is few report showing anatomic variations of the left upper lobe (LUL) using three-dimensional computed tomography angiography and bronchography (3D-CTAB), and no in Chinese population. The present study aimed to use 3D-CTAB to describe variations of the pulmonary bronchus of LUL in Chinese population.

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Section: Discussionmentioning

confidence: 99%

Anatomical analysis of variations in the bronchus pattern of the left upper lobe using three-dimensional computed tomography angiography and bronchography

He¹,

Wang²,

Wang³

et al. 2022

Ann Transl Med

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“…To validate our algorithm, we used 15 recorded videos of robotic surgery (5 for parameter identification and 10 for testing), obtained from online public sources, including the US National Library of Medicine 23 (the links to the videos are available upon request). The videos cover various human surgical procedures such as middle lobectomy, right upper lobectomy, thoracotomy, thoracoscopic lung surgery and prostatectomy.…”

Section: Methodsmentioning

confidence: 99%

“…Each video had an occurrence of arterial bleeding in the form of sputtering. The bleedings occurred due to different reasons such as cutting of the artery vessel by the surgeon, hitting the vessel with the tip of robotic hook, significant and inappropriate movement of surgical tools, and exerting extra force on vascular surfaces 23 . Although the reasons for the bleedings were not explained in all videos and could not be identified by inspection, it is still appropriate for our algorithm development with respect to bleeding detection and localization.…”

Section: Methodsmentioning

confidence: 99%

An entropy‐based approach to detect and localize intraoperative bleeding during minimally invasive surgery

Rahbar

Reisner

Ying

et al. 2020

Robotics Computer Surgery

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Background: During minimally invasive surgery (either robotic or traditional laparoscopic), vascular injuries may occur because of inadvertent surgical tool movements or actions. These vascular injuries can lead to arterial or venous bleeding with varying degrees of severity that may be life-threatening. Materials and Methods: Given that a bloody spot is characterized by homogenous and uniform texture, our algorithm automatically scans the entire surgical video frame-by-frame using a local entropy filter to segment each image into different regions sequence. By comparing changes in entropy in the frames sequences, the algorithm detects the moment of bleeding occurrence and its pixel location. We preliminarily tested the algorithm using ten minimally invasive-surgery videos., each of which contains one surgical-tool-induced bleeding. Results: Our results show that the algorithm can detect bleeding within 0.635 s, on average, after their occurrences and locate the bleeding sources within, on average, 2.5% of discrepancy in pixels from their origins. Conclusion: In this study, we present a novel and promising local-entropy-based image processing algorithm that detects spurts of blood and locate their source in real-time.

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“…These authors reported the incidence of major vascular injury during robotic lobectomy as 2.6% and for robotic segmentectomy as 1.5%. Novellis et al [2] reported an overall conversion rate of 6.2% (21/338) for major robotic lung resections, of which 1.1% (4/338) were due to bleeding. Other authors have reported overall conversion rates of 1.5%-9% with pulmonary artery or pulmonary vein injury resulting in conversion in 0.5%-2.6% [3][4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Technique of robotic lobectomy III: control of major vascular injury, the 5 “P”’s

Gharagozloo¹,

Meyer²

2020

Mini-invasive Surg

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Robotic Lobectomy has been evolving over the past decade and has been shown to be an oncologically efficacious procedure. Although robotic lobectomy is performed more frequently in centers around the world, it accounts for a small percentage of all lobectomies. One of the major causes of reluctance to adopt robotic lobectomy and segmentectomy procedures by surgeons is the fear of bleeding complications, as well as the lack of a standardized reproducible approach to these potentially catastrophic events. This paper outlines a proven strategy for control of bleeding complications during robotic lobectomy and segmentectomy procedures: the 5 "P"'s of Prevention, Preparedness, Poise, Pressure, and Proximal Control.

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Management of robotic bleeding complications

Cited by 3 publications

References 0 publications

Anatomical analysis of variations in the bronchus pattern of the left upper lobe using three-dimensional computed tomography angiography and bronchography

Anatomical analysis of variations in the bronchus pattern of the left upper lobe using three-dimensional computed tomography angiography and bronchography

An entropy‐based approach to detect and localize intraoperative bleeding during minimally invasive surgery

Technique of robotic lobectomy III: control of major vascular injury, the 5 “P”’s

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