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Lung Cancer Surgery in Octogenarians: Implications and Advantages of Artificial Intelligence in the Preoperative Assessment.

Authors :
Bassi, Massimiliano
Vaz Sousa, Rita
Zacchini, Beatrice
Centofanti, Anastasia
Ferrante, Francesco
Poggi, Camilla
Carillo, Carolina
Pecoraro, Ylenia
Amore, Davide
Diso, Daniele
Anile, Marco
De Giacomo, Tiziano
Venuta, Federico
Vannucci, Jacopo
Source :
Healthcare (2227-9032); Apr2024, Vol. 12 Issue 7, p803, 13p
Publication Year :
2024

Abstract

The general world population is aging and patients are often diagnosed with early-stage lung cancer at an advanced age. Several studies have shown that age is not itself a contraindication for lung cancer surgery, and therefore, more and more octogenarians with early-stage lung cancer are undergoing surgery with curative intent. However, octogenarians present some peculiarities that make surgical treatment more challenging, so an accurate preoperative selection is mandatory. In recent years, new artificial intelligence techniques have spread worldwide in the diagnosis, treatment, and therapy of lung cancer, with increasing clinical applications. However, there is still no evidence coming out from trials specifically designed to assess the potential of artificial intelligence in the preoperative evaluation of octogenarian patients. The aim of this narrative review is to investigate, through the analysis of the available international literature, the advantages and implications that these tools may have in the preoperative assessment of this particular category of frail patients. In fact, these tools could represent an important support in the decision-making process, especially in octogenarian patients in whom the diagnostic and therapeutic options are often questionable. However, these technologies are still developing, and a strict human-led process is mandatory. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279032
Volume :
12
Issue :
7
Database :
Complementary Index
Journal :
Healthcare (2227-9032)
Publication Type :
Academic Journal
Accession number :
176593705
Full Text :
https://doi.org/10.3390/healthcare12070803