While artificial intelligence (AI) is known to benefit radiotherapy (RT), its applications in carbon ion RT (CIRT) is yet to be surveyed. This scoping review aims to examine the current landscape of AI in CIRT and highlight future directions.
Intratumor heterogeneity (ITH) describes the diversity of cancer cells within a single tumor. This heterogeneity includes differences in the cells’ phenotypes, genotypes, and functions. As a result, cancer cells can vary in their morphology, gene expression and protein profiles, metabolic behavior, and their ability to proliferate and invade surrounding tissues.
Preclinical immunotherapy research relies heavily on animal tumor models, which can be broadly classified into four categories: genetically engineered, carcinogen-induced, spontaneous, and humanized transplantation platforms.
Cancer is one of the leading causes of death worldwide, and early tumor detection can significantly reduce mortality rates. Liquid biopsy is a minimally invasive, repeatable method with a high economic benefit ratio, and it shows excellent prospects for tumor diagnosis. However, the detection methods relying on classical biomarkers have limited sensitivity and accuracy.
Choriocarcinoma is a malignant neoplasia which develops from trophoblastic cells. In males it is rare and often associated with other non-seminomatous germ cell tumours of the testis. Choriocarcinoma often presents with metastatic disease and elevated βHCG levels.
Many studies have highlighted that elevated body mass index (BMI) not only correlates with an elevated likelihood of developing breast cancer (BC) but may also influence patients’ responsiveness to therapeutic regimens and long-term survival outcomes. The impact of BMI on therapeutic response to neoadjuvant chemotherapy (NAC) in patients with BC remains inconclusive. This study seeks to evaluate the effect of BMI on treatment response in the BC population undergoing NAC via a meta-analysis, thereby providing evidence-based support for clinical decision-making.
Medical decision analysis is a method to make rational clinical decisions under uncertainty, enabling a mathematical combination of probabilities and utilities (i.e. values assigned to outcomes under risk). Decision analysis is commonly used in health economics, but it is underexploited in the clinic.
De novo metastatic breast cancer (dnMBC) is diagnosed when breast cancer has spread at presentation and accounts for 5–10% of cases. The benefit of postoperative radiotherapy (PORT) after primary tumor surgery in this setting remains uncertain.
We conducted a review and meta-analysis of observational studies published between 2013 and 2024. Two databases (PubMed and Embase) were searched and the review followed PRISMA 2020 guidelines.
The Italian region of Sardinia is the second largest and one of the least populated islands in the Mediterranean Sea. While renowned for its stunning coastline, scientists know it better for the unique genetic features among the local population,1 which have been preserved through millennia of isolation and selective pressure exerted by malaria.
To improve precision medicine in breast cancer (BC) decision-making, radio-genomics is an emerging branch of artificial intelligence (AI) that links cancer characteristics assessed radiologically with the histopathology and genomic properties of the tumour. By employing MRIs, mammograms, and ultrasounds to uncover distinctive radiomics traits that potentially predict genomic abnormalities, this review attempts to find literature that links AI-based models with the genetic mutations discovered in BC patients.