Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.
Matteo FerroOttavio de CobelliMihai Dorin VartolomeiGiuseppe LucarelliFelice CrocettoBiagio BaroneAlessandro SciarraFrancesco Del GiudiceMatteo MutoMartina MaggiGiuseppe CarrieriGian Maria BusettoUgo FalagarioDaniela TerraccianoLuigi CormioGennaro MusiOctavian Sabin TătaruPublished in: International journal of molecular sciences (2021)
Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.
Keyphrases
- prostate cancer
- high resolution
- artificial intelligence
- magnetic resonance imaging
- machine learning
- contrast enhanced
- radical prostatectomy
- single cell
- deep learning
- lymph node metastasis
- big data
- end stage renal disease
- systematic review
- chronic kidney disease
- ejection fraction
- healthcare
- magnetic resonance
- fluorescence imaging
- clinical trial
- randomized controlled trial
- open label
- electronic health record
- health information
- squamous cell
- phase ii
- phase iii