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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-06212021-152521


Tipo di tesi
Tesi di laurea magistrale LM6
Autore
CANNAS, SAMUELE
URN
etd-06212021-152521
Titolo
Robotic Liver Surgery for Hepatic Resections: from basic principles to advanced robotic design and development
Dipartimento
RICERCA TRASLAZIONALE E DELLE NUOVE TECNOLOGIE IN MEDICINA E CHIRURGIA
Corso di studi
MEDICINA E CHIRURGIA
Relatori
relatore Prof. Boggi, Ugo
correlatore Prof.ssa Menciassi, Arianna
Parole chiave
  • hepatic resection
  • Jacobian matrix
  • minimally invasive surgery
  • parenchymal-sparing surgery
  • robotic surgery
Data inizio appello
14/07/2021
Consultabilità
Non consultabile
Data di rilascio
14/07/2091
Riassunto
Robot-assisted surgery (or computer-assisted surgery) epitomizes the last frontier in the field of surgery. The surgeon, instead of directly handling the surgical instruments, is able to issue commands to robotic arms by means of a remote computer-aided console. The robot accurately emulates the wrist movements of the operator, allowing the maximum degree of dexterity and precision.

This work focuses on the role of robotic surgery in complex liver procedures, analyzing the clinical, technical and robotic challenges of postero-superior hepatic resections. Notably, the study has brought forward two simultaneous research projects, one in the hospital setting and the other in the computational playground. The learning curve of laparoscopic and robot-assisted complex liver resections has been assessed with a novel combination of CUSUM analyses and a comprehensive difficulty score index, while the da Vinci robotic arm has been modelled and its orientation and position have been simulated.

The results clearly demonstrated the great potential of robotic surgery in both average and challenging interventions, as well as its efficacy in ameliorating the laparoscopic performance itself.

In conclusion, this study lays the groundwork for an ever-increasing future of robotics in the healthcare industry, paving the way for a new generation of self-governing surgical robotic systems.
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