A Survey on Automatic Delineation of Radiotherapy Target Volume based on Machine Learning

Radiotherapy is one of the main treatment methods for cancer,and the delineation of the radiotherapy target area is the basis and premise of precise treatment.Artificial intelligence technology represented by machine learning has done a lot of research in this area,improving the accuracy and efficiency of target delineation.This article will review the applications and research of machine learning in medical image matching,normal organ delineation and treatment target delineation according to the procudures of doctors to delineate the target volume,and give an outlook on the development prospects.

Nanoparticles for targeted cancer radiotherapy

Radiotherapy,where ionizing radiation is locally delivered either through an external beam or by surgically implanting radionuclide-based seeds in the tumor,is one of the gold standard treatments for cancer.Due to the non-selective nature of radiation,healthy tissue surrounding the cancerous region is usually affected by the treatment.Hence,new strategies,including targeted alpha therapy,are being studied to improve the selectivity of the treatment and minimize side effects.Several challenges,however,limit the current development of targeted radiotherapy,such as the functionalization of the therapeutic agent with targeting vectors and controlling the release of recoiling daughters.Nanoparticles offer unique opportunities as drug delivery vehicles,since they are biocompatible,enhance the cellular uptake of drugs,and are easily functionalized with targeting molecules.In this review,we examine how nanoparticles can be used for targeted radiotherapy,either as sensitizers of external beams or as delivery vehicles for therapeutic radionuclides.We describe the clinical relevance of different types of nanoparticles,followed by an analysis of how these nanoconstructs can solve some of the main limitations of conventional radiotherapy.Finally,we critically discuss the current situation of nanoparticle-based radiotherapy in clinical settings and challenges that need to be overcome in the future for further development of the field.

Time to give up traditional methods for the management of gastrointestinal neuroendocrine tumours

Neuroendocrine tumors(NETs)are a rare and heterogeneous disease group and constitute 0.5%of all malignancies.The annual incidence of NETs is increasing worldwide.The reason for the increase in the incidence of NETs is the detection of benign lesions,incidental detection due to the highest use of endoscopic and imaging procedures,and higher recognition rates of pathologists.There have been exciting developments regarding NET biology in recent years.Among these,first of all,somatostatin receptors and downstream pathways in neuroendocrine cells have been found to be important regulatory mechanisms for protein synthesis,hormone secretion,and proliferation.Subsequently,activation of the mammalian target of rapamycin pathway was found to be an important mechanism in angiogenesis and tumor survival and cell metabolism.Finally,the importance of proangiogenic factors(platelet-derived growth factor,vascular endothelial growth factor,fibroblastic growth factor,angiopoietin,and semaphorins)in the progression of NET has been determined.Using the combination of biomarkers and imaging methods allows early evaluation of the appropriateness of treatment and response to treatment.