Radiogenomics, Breast Cancer Diagnosis and Characterization: Current Status and Future Directions

Abstract

Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with –omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).

The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics

“…For methods and analyses to be standardized and optimized, more study is required. AI can potentially be utilized to improve the results’ accuracy and enable the use of radiogenomics in clinical settings [ 123 , 129 ].…”

“…The ideal database should contain genomic data (mutations, copy number variations, etc. ), radiomic feature data, epigenomic (non-coding RNAs), metabolomic data, proteomic data, immunohistochemical data, and transcriptomic data [ 123 ]. Artificial intelligence can assist in the handling and mining of data.…”

How has the field of metastatic breast cancer in bones evolved over the past 22 years?

“…This might be related to the fact that 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) is significantly better than Tc-99 m in diagnosing MBCB [33] . In recent years, FDG-PET/CT has become more widely used and has achieved encouraging results in terms of diagnosing certain conditions, clinical staging, and detecting recurrence [31] , [34] , [35] . However, it is worth noting that FDG-PET/CT is currently not applicable to the clinical staging of early and operable advanced BC [31] .…”

Radiomics in Breast Imaging: Future Development

“…Mao et al [ 51 ], in a 2021 multicenter study, demonstrated with a AUC of 0.92 how the application of the radiomics model in mammography could predict the risk of breast cancer [ 49 ]. Woodard et al [ 52 ], in 2018, showed how BI-RADS descriptors could assume the role of imaging biomarkers for breast cancer through the analysis of radiomic qualitative features obtained from the correlation between the genomic tests used in clinical practice, OncotypeDX recurrence risk scores, and the semantic characteristics used in the lexicon of mammography [ 53 ].…”