Tesi etd-11092021-172251
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Tipo di tesi
Corso Ordinario Ciclo Unico 6 Anni
Autore
CANNAS, SAMUELE
URN
etd-11092021-172251
Titolo
A Step-By-Step Insight in Robotic Pancreatic Surgery:
from Avant-Garde Minimally Invasive Techniques to a Novel Assessment of the Corresponding Learning Curves
Struttura
Cl. Sc. Sperimentali - Medicina
Corso di studi
SCIENZE MEDICHE - SCIENZE MEDICHE
Commissione
Tutor Prof. RECCHIA, FABIO ANASTASIO
Relatore Prof. BOGGI, UGO
Presidente Prof. EMDIN, MICHELE
Membro Prof. LIONETTI, VINCENZO
Membro Dott.ssa CASIERI, VALENTINA
Membro Dott. GIANNONI, ALBERTO
Membro Prof.ssa ANGELONI, DEBORA
Membro Prof. PASSINO, CLAUDIO
Membro Prof. COCEANI, FLAVIO
Relatore Prof. BOGGI, UGO
Presidente Prof. EMDIN, MICHELE
Membro Prof. LIONETTI, VINCENZO
Membro Dott.ssa CASIERI, VALENTINA
Membro Dott. GIANNONI, ALBERTO
Membro Prof.ssa ANGELONI, DEBORA
Membro Prof. PASSINO, CLAUDIO
Membro Prof. COCEANI, FLAVIO
Parole chiave
- Learning Curve
- Minimally Invasive Surgery
- Pancreatic Adenocarcinoma
- Pancreatoduodenectomy
- Robotic Pancreatic Surgery
Data inizio appello
20/12/2021;
Disponibilità
parziale
Riassunto analitico
The present Thesis explores the theoretical background and practical implementation of Robotic Pancreatic Surgery, with a particular reference to the assessment of the learning curves and the thorough description of novel minimally invasive techniques.
Firstly, the dissertation recapitulates the anatomy and embryology of the pancreatic gland under the lens of the Hepato-Pancreato-Biliary (HPB) surgeon. Secondly, the hallmarks of pancreatic cancer are examined, including early diagnosis, imaging and staging. Thirdly, technically demanding and challenging robotic pancreatic surgeries are introduced, with an unprecedented light on complications and outcomes. Finally, the learning curves of robot-assisted complex pancreatic resections have been characterized with an innovative combination of powerful statistical and bioinformatic tools.
Firstly, the dissertation recapitulates the anatomy and embryology of the pancreatic gland under the lens of the Hepato-Pancreato-Biliary (HPB) surgeon. Secondly, the hallmarks of pancreatic cancer are examined, including early diagnosis, imaging and staging. Thirdly, technically demanding and challenging robotic pancreatic surgeries are introduced, with an unprecedented light on complications and outcomes. Finally, the learning curves of robot-assisted complex pancreatic resections have been characterized with an innovative combination of powerful statistical and bioinformatic tools.
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