Radiomics and liver: Where we are and where we are headed?

• Published in: European journal of radiology 2024-02, Vol.171, p.111297-111297, Article 111297
• Main Authors: Maino, Cesare, Vernuccio, Federica, Cannella, Roberto, Franco, Paolo Niccolò, Giannini, Valentina, Dezio, Michele, Pisani, Antonio Rosario, Blandino, Antonino Andrea, Faletti, Riccardo, De Bernardi, Elisabetta, Ippolito, Davide, Gatti, Marco, Inchingolo, Riccardo
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Cholangiocarcinoma; Computed Tomography; Deep Learning; Diagnosis; Hepatocellular carcinoma; Humans; Liver metastases; Liver Neoplasms - diagnostic imaging; Liver Neoplasms - pathology; Machine Learning; Magnetic Resonance Imaging; Prognosis; Radiography; Radiomics; Texture analysis; Tomography, X-Ray Computed
• ISSN: 0720-048X; 1872-7727
• DOI: 10.1016/j.ejrad.2024.111297

•Radiomics should be considered a useful tool in liver pathologies.•Radiomics can help the evaluation of fatty liver disease and inflammation.•Radiomics can stage fibrosis, outperforming clinical indexes.•Radiomics can increase accuracy in the diagnosis, staging, and prognosis of HCC.•Radiomics can help the differential diagnosis between CCC, HCC, and HCC-CCC.•Radiomics can be applied to liver metastases, especially from colorectal cancer. Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.