Preclinical Evaluation of a Companion Diagnostic Radiopharmaceutical, [18F]PSMA-1007, in a Subcutaneous Prostate Cancer Xenograft Mouse Model

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Recent advances in the molecular targeted drugs for prostate cancer

CONTEXT

Prostate cancer (PCa) is the second largest male tumor in the world and one of the most common malignant tumors in the urinary system. In recent years, the incidence rate of PCa in China has been increasing year by year. Meanwhile, refractory hormone resistance and adverse drug reactions of advanced PCa cause serious harm to patients.

OBJECTIVE

The present study aims to systematically review the recent advances in molecularly targeted drugs for prostate cancer and to use the retrieval and analysis of the literature library to summarize the adverse effects of different drugs so as to maximize the treatment benefits of targeted therapies.

EVIDENCE ACQUISITION

We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to March 2022 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Medical Subject Heading (MeSH) terms and keywords such as (prostate cancer) AND (molecular target drugs) AND (side effect) were used. No language restrictions were set on the search process, and all these results were processed independently by two authors. Consensus was reached through discussion once met with any disagreements. The primary endpoint was differential features between different molecular targeted drugs. Secondary endpoints were side effects of different drugs on the body and corresponding prognostic values.

EVIDENCE SYNTHESIS

The Cochrane Collaboration risk of bias tool was used to assess the study quality in terms of sequence generation, allocation concealment, blinding, the completeness of outcome data, selective reporting and other biases. We retrieved 332 articles, of which 49 met the criteria for inclusion. Included studies show that prostatic tumor cells, tumor neovascularization and immune checkpoints are the main means for targeted therapy. Common drugs include 177 Lu-PSMA, Olaparib, Rucaparib, Bevacizumab, Pazopanib, Sorafenib, Cabozantinib, Aflibercept, Ipilimumab, Atezolizumab, Avelumab, Durvalumab. A series of publicly available data suitable for further analysis of side effects. An over-representation analysis of these datasets revealed reasonable dosage and usage is the key to controlling the side effects of targeted drugs. Important information such as the publication year, the first author, location and outcome observation of adverse effects was extracted from the original article. If the study data has some insufficient data, contacting the corresponding authors is necessary. All the studies included prospective nonrandomized and randomized research. Retrospective reviews were also screened according to the relevant to the purpose of this study. Meeting abstracts as well as letters to the editor and editorials were excluded.

STATISTICAL ANALYSIS

Data analysis was based on Cochrane's risk of bias tools to obtain the quality assessment. The included randomized studies used RoB2 and non-randomized ones corresponded to ROBINS-I. Standardized mean differences (SMD) were used to determine relative risk (RR) and side effects between groups. The eggers' test was used to check the publication bias from variable information in the included studies. All p < 0.05 were considered to be significant, and 95% was set as the confidence interval.

CONCLUSIONS

With the approval of a variety of targeted drugs, targeted therapy will be widely used in the treatment of advanced or metastatic prostate cancer. Despite the existence of adverse reactions related to targeted drug treatment, it is still meaningful to adjust the drug dosage or treatment cycle to reduce the occurrence of adverse reactions, improving the treatment benefits of patients.