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Artificial Intelligence in Bone Metastasis Imaging: Recent Progresses from Diagnosis to Treatment - A Narrative Review.
Caloro, Elena; Gnocchi, Giulia; Quarrella, Cettina; Ce, Maurizio; Carrafiello, Gianpaolo; Cellina, Michaela.
Affiliation
  • Caloro E; Università degli studi di Milano, via Festa del Perdono, 7, 20122 Milan, Italy.
  • Gnocchi G; Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milan, Italy.
  • Quarrella C; Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milan, Italy.
  • Ce M; Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, 20122 Milan, Italy.
  • Carrafiello G; Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milan, Italy; Radiology Department, Fondazione IRCCS Cà Granda, Policlinico di Milano Ospedale Maggiore, Università di Milano, 20122 Milan, Italy.
  • Cellina M; Radiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Milano, Piazza Principessa Clotilde 3, 20121, Milan, Italy.
Crit Rev Oncog ; 29(2): 77-90, 2024.
Article in En | MEDLINE | ID: mdl-38505883
ABSTRACT
The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be challenging but decisive, because it affects the diagnostic and therapeutic process, especially in case of metastases. Several studies have already demonstrated how the integration of AI-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection, increasing the diagnostic accuracy and reducing the overdiagnosis and the number of unnecessary deeper investigations. In addition, radiomics and radiogenomics approaches could go beyond the qualitative features, visible to the human eyes, extrapolating cancer genomic and behavior information from imaging, in order to plan a targeted and personalized treatment. In this article, we want to provide a comprehensive summary of the most promising AI applications in bone metastasis imaging and their role from diagnosis to treatment and prognosis, including the analysis of future challenges and new perspectives.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Genomics Limits: Humans Language: En Journal: Crit Rev Oncog Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Genomics Limits: Humans Language: En Journal: Crit Rev Oncog Year: 2024 Document type: Article