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Page 6 of 10 Fasanella. Mini-invasive Surg 2024;8:5 https://dx.doi.org/10.20517/2574-1225.2023.79

tumor characteristics, bleeding, arterial clamping, respiration, and pneumoperitoneum are the main factors
implicated in tissue deformation. To date, this deformation can only be partially calculated by current
[57]
computer models , but at present, this problem can be overcome by using real-time intraoperative imaging
instead of preoperative imaging for image overlay.

One possibility is represented by IOUS superimposition , although it could be complex for the surgeon to
[58]
perform a resection at the same time as using the ultrasound probe, as this is in close contact with the
surface of the kidney. Intraoperative cone beam CT (CBCT) with intraoperative contrast represents another
real-time imaging alternative . Also, in this case, the possible interference of the CBCT C-arm with the
[56]
robot arms could represent a significant problem, requiring the temporary disconnection of the robot and
the use of a hybrid operating room and dedicated imaging technology.

Artificial intelligence
Artificial intelligence (AI) is defined as the ability of machines to perform tasks and solve problems for
which they were not explicitly programmed. In recent years, the interest in AI has increased significantly as
it contributes to improving diagnostic and therapeutic accuracy in clinical practice. Currently, it finds
application in the diagnosis, management, perioperative care, and follow-up of RCC. However, it is crucial
that healthcare professionals develop a basic understanding of the algorithms and decision-making process
[59]
of the applied AI method, often perceived as difficult to understand, to implement its use in daily practice .

The goal of AI is to build a machine capable of perceiving its environment and performing activities, trying
to obtain the maximum probability of success. This process makes use of different subcategories of AI such
as machine learning (ML), artificial neural networks (ANN) and deep learning (DL), natural language
processing (NLP), computer vision, predictive analytics, genetic informatics, expert systems, visual
[60]
recognition, and speech processing . ML and DL algorithms based on CT texture analysis have been
applied to differentiate renal masses , predict nuclear grade, identify genetic mutations, and predict
[61]
prognosis, recurrence risk, and overall survival (OS) . Kocak et al. applied ML techniques to identify the
[62]
nuclear grade of ccRCC and compare the results with those obtained with percutaneous biopsy . They
[63]
found that the algorithm could differentiate the nuclear grades in 85.1% of ccRCC cases. Ding et al.
conducted a study using AI to achieve higher accuracy in classifying the degree of ccRCC . Other
[64]
[65]
researchers have focused on tumor gene expression to predict OS and prognosis . Kocak et al., in another
study, applied algorithms based on ANN and ML to detect polybromo-1 (PBRM1) mutations, common in
ccRCC, allowing for identifying up to 88% of ccRCCs with PBRM1 mutation status .
[66]
In regards to robotic surgery, AI has mostly been used for proficiency assessment in robot-assisted prostate
surgery. Recently, some studies have also focused on RAPN. Nakawala et al. proposed in their study the
[67]
combined use of DL and knowledge management tools for surgical workflow recognition of RAPN . AI
would help the surgeon dissect the hilum during RAPN by detecting the slight movements of tissue surfaces
[68]
related to the pulsation of hidden blood vessels .

CONCLUSIONS
RAPN is a complex surgery for which various techniques have been developed to allow better intraoperative
visualization of the tumor, ensure more accurate vascular dissection, and facilitate overall tumor resection,
with an increasingly precise evaluation of the surgical margins. Ultrasound and fluorescence imaging are
techniques widely used to assist the surgeon in RAPN. IGC is particularly advantageous for differentiating
healthy tissue from tumor tissue, especially in the case of exophytic versus endophytic tumors, due to the
shallow penetration depth of light into the tissue. This limitation could be exceeded using the mode