Litcius/Paper detail

PET/CT Radiomics in Lung Cancer: An Overview

Francesco Bianconi, Isabella Palumbo, Angela Spanu, Susanna Nuvoli, Mario Luca Fravolini, Barbara Palumbo

2020Applied Sciences62 citationsDOIOpen Access PDF

Abstract

Quantitative extraction of imaging features from medical scans (‘radiomics’) has attracted a lot of research attention in the last few years. The literature has consistently emphasized the potential use of radiomics for computer-assisted diagnosis, as well as for predicting survival and response to treatment. Radiomics is appealing in that it enables full-field analysis of the lesion, provides nearly real-time results, and is non-invasive. Still, a lot of studies suffer from a series of drawbacks such as lack of standardization and repeatability. Such limitations, along with the unmet demand for large enough image datasets for training the algorithms, are major hurdles that still limit the application of radiomics on a large scale. In this paper, we review the current developments, potential applications, limitations, and perspectives of PET/CT radiomics with specific focus on the management of patients with lung cancer.

Topics & Concepts

RadiomicsLung cancerStandardizationMedicineMedical physicsComputer scienceRadiologyPathologyOperating systemRadiomics and Machine Learning in Medical ImagingAdvanced X-ray and CT ImagingLung Cancer Diagnosis and Treatment