Theranostics in oncology: What radiologists want to know

Radiotheranostic Agents in Hematological Malignancies

Radioimmunotherapy (RIT) is a cancer treatment that combines radiation therapy with tumor-directed monoclonal antibodies (Abs). Although RIT had been introduced for the treatment of CD20 positive non-Hodgkin lymphoma decades ago, it never found a broad clinical application. In recent years, researchers have developed theranostic agents based on Ab fragments or small Ab mimetics such as peptides, affibodies or single-chain Abs with improved tumor-targeting capacities. Theranostics combine diagnostic and therapeutic capabilities into a single pharmaceutical agent; this dual application can be easily achieved after conjugation to radionuclides. The past decade has seen a trend to increased specificity, fastened pharmacokinetics, and personalized medicine. In this review, we discuss the different strategies introduced for the noninvasive detection and treatment of hematological malignancies by radiopharmaceuticals. We also discuss the future applications of these radiotheranostic agents.

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients’ risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these “big data” in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.