Radiomics in Oncology, Part 1: Technical Principles and Gastrointestinal Application in CT and MRI

Abstract

Radiomics has been playing a pivotal role in oncological translational imaging, particularly in cancer diagnosis, prediction prognosis, and therapy response assessment. Recently, promising results were achieved in management of cancer patients by extracting mineable high-dimensional data from medical images, supporting clinicians in decision-making process in the new era of target therapy and personalized medicine. Radiomics could provide quantitative data, extracted from medical images, that could reflect microenvironmental tumor heterogeneity, which might be a useful information for treatment tailoring. Thus, it could be helpful to overcome the main limitations of traditional tumor biopsy, often affected by bias in tumor sampling, lack of repeatability and possible procedure complications. This quantitative approach has been widely investigated as a non-invasive and an objective imaging biomarker in cancer patients; however, it is not applied as a clinical routine due to several limitations related to lack of standardization and validation of images acquisition protocols, features segmentation, extraction, processing, and data analysis. This field is in continuous evolution in each type of cancer, and results support the idea that in the future Radiomics might be a reliable application in oncologic imaging. The first part of this review aimed to describe some radiomic technical principles and clinical applications to gastrointestinal oncologic imaging (CT and MRI) with a focus on diagnosis, prediction prognosis, and assessment of response to therapy.

Radiomics of Contrast-Enhanced Computed Tomography: A Potential Biomarker for Pretreatment Prediction of the Response to Bacillus Calmette-Guerin Immunotherapy in Non-Muscle-Invasive Bladder Cancer

“…In addition, MRI is susceptible to many artifacts, such as image and signal distortion consequences due to contiguous gas-filled bowls and gas bubbles within the bladder (Lin and Chen, 2015) which could complicate the reproducibility of measurements. In studies on CT radiomics, automatic acquisition protocol and test-retest analysis have proven to be useful in overcoming the bias of acquisition protocols (Caruso et al, 2021). In light of the above limitations, radiomic models based on MRI are more difficult to reproduce across institutions than those based on CT images (Harding-Theobald et al, 2021).…”

A Potential Prognostic Marker for Recognizing VEGF-Positive Hepatocellular Carcinoma Based on Magnetic Resonance Radiomics Signature

“…Radiomics is a new domain in medicine that utilizes high-throughput quantitative image features based on images from imaging examinations that cannot be resolved by the naked eye for diagnosis and prognosis ( 16 ). These features potentially capture the intratumoral heterogeneity, which can offer information about the tumor microenvironment and the phenotype of cancer ( 17 ).…”

MRI-Based Radiomics Features to Predict Treatment Response to Neoadjuvant Chemotherapy in Locally Advanced Rectal Cancer: A Single Center, Prospective Study

“…Furthermore, 3.0T MRI scanner perform better than the 1.5T MRI in the visual assessment of the complete response patients of rectal cancer (10). In spatially and temporally heterogeneous solid cancers, invasive biopsies specimens cannot reflect the overall characteristics of the tumor, which limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging ( 11 ). Radiomics, as a new term, was first proposed by Lambin et al.…”