Applications and limitations of radiomics

Abstract

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized medicine. In this technical review, we describe applications and challenges of the radiomic field. We will review radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.

Responsible Radiomics Research for Faster Clinical Translation

“…Other early radiomics studies followed (7,8), including some highlighting early on that the reliability of existing features is affected by acquisition protocol, reconstruction, test-retest consistency, preprocessing, and segmentation (9)(10)(11)(12)(13). The overall framework of radiomics was then explicitly described in 2012 (14), and in the years that followed, this emerging field experienced exponential growth (15).…”

Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non–Small Cell Lung Cancer

“…Therefore, accurate quantification of tumor heterogeneity from PET images may provide important information for the identification of mutation status and precision medicine. Heterogeneity in the tumor phenotype can be quantitatively described through radiomic features (23,27,28), which use advanced mathematic models to quantify the spatial relationship between image voxels (29).…”

PET/MRI: Reliability/Reproducibility of SUV Measurements

“…Furthermore, volume-based PET metrics such as the total lesion glycolysis (TLG), calculated by multiplying SUV mean by the metabolic tumor volume (MTV) [16], radiomic and texture analysis [17,18], and parametric imaging have been suggested [14,15]. The TLG, used to assess global metabolic response of the whole lesion thus providing complementary information to SUV and it variants, was shown to be highly correlated with other PET response parameters and is reproducible [19].…”

“…Recent advances in PET image segmentation and delineation of lesion contours [20] combined with progress in partial volume correction techniques have enabled to automate the calculation procedure. More recently, radiomics and texture analysis emerged as new promising approaches enabling to circumvent the limitations of the above described oversimplified approaches by providing additional features including intratumoral heterogeneity through advanced image processing techniques and knowledge in systems biology [17,18]. An increasing number of pioneering studies support the underlying assumptions of these hypotheses; however, further research and development efforts using large clinical databases are still required before these approaches can translate to valuable and reliable tools that can be adopted in the clinic.…”