Simulated Rehearsal for Percutaneous Nephrolithotomy

Surgical simulation provides opportunities for surgeons to practice specific skills, prior to performing complex tasks on patients, with the goal of reducing potential errors and providing a safer procedure for the patient. The investigators will use a novel approach to simulation (patient-specific rehearsals) i.e., practice a short time prior to the live event that uses gel models of organs created by a 3D printer, and that are specific to each patient versus models that represent an ideal training model. The investigators' overarching goals are to improve patient outcomes by developing the best platform for surgeons to efficiently enhance performance prior to live surgery.

Surgical simulation provides opportunities for both medical residents and expert surgeons to practice specific skills, prior to performing complex tasks on patients, with the goal of reducing potential errors and providing a safer procedure for the patient. Most studies have addressed surgical simulation carried out in dry and animation laboratories at a significantly different time than the actual surgery on patients. For most surgeons-in-training, there is no intermediate stage between practice and performance. Learning takes place in isolation, and surgeons do not routinely experience how dexterity skills are affected by context until they perform an actual operation. The investigators will use a unique approach to simulation (just-in-time simulation i.e., practicing in close proximity to live surgery). The investigators believe that this approach will be most beneficial for highly technical procedures such as Percutaneous Nephrolithotomy (PCNL), because this approach could familiarize the surgeon with the case, enable them to try different approaches, identify potential dangers, and even optimize the selection of tools for the procedure. This type of simulation is usually performed using idealized or generic models that can improve a surgeon's technical, cognitive, and hand - eye coordination performance, of this specific procedure prior to the live surgery but is not personalized for an individual patient.

The investigators' efforts at the Simulation Innovation Laboratory (SIL) at the University of Rochester in combining 3D printing technology with polymer research has provided a platform for reproducing patient specific water-based gel models with accurate portrayal of anatomical characteristics including individual patient variations, but also with the capacity to reproduce tissue characteristics and replicate the comprehensive operative experience. Patient specific simulations, however, allow surgeons to practice, plan and address potential problems related to a specific patient's surgery before performing the actual surgery. The investigators developed three-dimensional (3D) models, which reproduce patient-specific anatomy and tissue characteristics, allowing for a rehearsal that is an accurate representation of an actual procedure to be done, in this case Percutaneous Nephrolithotomy for the treatment of complex renal stones.

In the present era of simulation, no standard form of simulation exists that is performed directly prior to the live surgery, nor is there any form of personalized simulation for each patient. In this study the investigators aim to compare just-in-time simulation using either patient-specific or idealized training models and compare their impact on operative performance following Percutaneous Nephrolithotomy (PCNL). Secondary objectives are to assess their impact on patient outcomes following PCNL. The investigators overarching goals are to improve patient outcomes by developing the best platform for surgeons to efficiently enhance their performance prior to live surgery.

Eligibility Criteria:
Inclusion Criteria:

* All patients scheduled to undergo PCNL surgery at the University of Rochester Medical Center
* Ability to give informed consent
* Willing to participate in the study
* Any racial or ethnic origin

Exclusion Criteria:

* Inability to give informed consent