Robotic caudo-peripheral approach for liver parenchymal transection in anatomical liver resections for hepatocellular carcinoma

Alessia Fassari , Vito De Blasi , Benedetto Ielpo , Alessandro Anselmo , Bernardo Dalla Valle , Edoardo Rosso

Artificial Intelligence Surgery ›› 2024, Vol. 4 ›› Issue (3) : 139 -48.

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Artificial Intelligence Surgery ›› 2024, Vol. 4 ›› Issue (3) :139 -48. DOI: 10.20517/ais.2024.21
Technical Note

Robotic caudo-peripheral approach for liver parenchymal transection in anatomical liver resections for hepatocellular carcinoma

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Abstract

Liver parenchymal transection is a challenging step during hepatic resection, particularly when using robotic platforms that require specific skills to optimize this phase. Pedicle division at the beginning of the liver parenchyma helps to better identify the resection plane and minimizes blood loss. The three-dimensional (3D) high-definition vision and the robotic Maryland allow for clear identification of the hepatic pedicles that could be dissected or divided without the need for a laparoscopic ultrasonic dissector. The caudo-peripheral technique, combined with the Maryland bipolar Kelly clamp crushing technique, is a useful approach to complete parenchymal transection and achieve safe anatomical resections in cases of hepatocellular carcinoma (HCC) with multi-pronged bleeding control. This is essential for expediting the procedure, reducing the number of intermittent clamping times, and minimizing the risk of ischemia-reperfusion injury. In this setting, perfect synchronization between the surgeon operating at the console and the bedside assistant is crucial. Advances in artificial intelligence (AI) systems have shown great potential to redefine clinical care management, preoperative planning, and intraoperative decision making for patients with HCC. This paper describes the most relevant details of our technique, its theoretical background, advantages, and limitations. Moreover, minimally invasive surgery offers the opportunity to share surgical experiences and technical progress through multimedia videos. This represents a modern and effective teaching tool to accelerate the learning process and overcome the challenges of the most complex procedures by offering surgeons various solutions to common technical problems.

Keywords

Hepatocellular carcinoma / robotic surgery / hepatic surgery / anatomical liver resection

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Alessia Fassari, Vito De Blasi, Benedetto Ielpo, Alessandro Anselmo, Bernardo Dalla Valle, Edoardo Rosso. Robotic caudo-peripheral approach for liver parenchymal transection in anatomical liver resections for hepatocellular carcinoma. Artificial Intelligence Surgery, 2024, 4(3): 139-48 DOI:10.20517/ais.2024.21

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References

[1]

Otsuka Y,Cleary SP,Cai X.What is the best technique in parenchymal transection in laparoscopic liver resection? Comprehensive review for the clinical question on the 2nd International Consensus Conference on Laparoscopic Liver Resection.J Hepatobiliary Pancreat Sci2015;22:363-70

[2]

Navinés-López J,Cremades Pérez M,Zárate Pinedo A.Microfracture-coagulation for the real robotic liver parenchymal transection.J Robot Surg2024;18:101 PMCID:PMC10904403

[3]

European Association for the Study of the Liver. EASL Clinical Practice Guidelines: management of hepatocellular carcinoma.J Hepatol2018;69:182-236

[4]

Child CG.Surgery and portal hypertension.Major Probl Clin Surg1964;1:1-85

[5]

Pugh RN,Dawson JL,Williams R.Transection of the oesophagus for bleeding oesophageal varices.Br J Surg1973;60:646-9

[6]

Tanaka S,Kubo S.Validation of index-based IWATE criteria as an improved difficulty scoring system for laparoscopic liver resection.Surgery2019;165:731-40

[7]

Xu FWX,Soh HN,Bonney GK.Augmenting care in hepatocellular carcinoma with artificial intelligence.Art Int Surg2023;3:48-63

[8]

Shinkawa H.Artificial intelligence-based technology for enhancing the quality of simulation, navigation, and outcome prediction for hepatectomy.Art Int Surg2023;3:69-79

[9]

Grewal M,Javed AA.Current state of radiomics in hepatobiliary and pancreatic malignancies.Art Int Surg2023;3:217-32

[10]

Ishizawa T.“Bon mariage” of artificial intelligence and intraoperative fluorescence imaging for safer surgery.Art Int Surg2023;3:163-5

[11]

Brozzetti S,Bini S.Surgical resection is superior to TACE in the treatment of HCC in a well selected cohort of BCLC-B elderly patients-a retrospective observational study.Cancers2022;14:4422 PMCID:PMC9496726

[12]

Liu R,Wakabayashi G.International experts consensus guidelines on robotic liver resection in 2023.World J Gastroenterol2023;29:4815-30 PMCID:PMC10494765

[13]

Di Benedetto F, Petrowsky H, Magistri P, Halazun KJ. Robotic liver resection: hurdles and beyond.Int J Surg2020;82S:155-62

[14]

Gotohda N,Geller DA.Expert Consensus Guidelines: how to safely perform minimally invasive anatomic liver resection.J Hepatobiliary Pancreat Sci2022;29:16-32

[15]

Kawasaki Y,Idichi T.Usefulness of cranio-dorsal approach for laparoscopic left lateral sectionectomy.Updates Surg2023;75:889-95

[16]

D’hondt M.Robotic versus laparoscopy approach for glissonean pedicle dissection. In: Ielpo B, Rosso E, Anselmo A, editors. Glissonean pedicles approach in minimally invasive liver surgery. Cham: Springer 2023. pp. 165-9.

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