Publications by authors named "L Strigari"
Purpose: This systematic review aimed to assess the feasibility, safety, and efficacy of using modern external beam radiotherapy (EBRT) techniques, such as intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), and stereotactic body radiotherapy (SBRT) as alternative approaches to brachytherapy (BRT) in adjuvant treatment of endometrial cancer (EC).
Material And Methods: A systematic review was conducted following PRISMA guidelines. The research question was framed using the PICO method, focusing on patients with EC [P] and comparing modern EBRT techniques (IMRT, VMAT, SBRT) [I] vs.
This review examines the significant influence of Digital Twins (DTs) and their variant, Digital Human Twins (DHTs), on the healthcare field. DTs represent virtual replicas that encapsulate both medical and physiological characteristics-such as tissues, organs, and biokinetic data-of patients. These virtual models facilitate a deeper understanding of disease progression and enhance the customization and optimization of treatment plans by modeling complex interactions between genetic factors and environmental influences.
View Article and Find Full Text PDFIntroduction: Metastatic prostate cancer (PCa) presents a significant challenge in oncology due to its high mortality rate and the absence of effective biomarkers for predicting patient outcomes. Building on previous research that highlighted the critical role of the long noncoding RNA (lncRNA) H19 and cell adhesion molecules in promoting tumor progression under hypoxia and estrogen stimulation, this study aimed to assess the potential of these components as prognostic biomarkers for PCa at the biopsy stage.
Methods: This research utilized immunohistochemistry and droplet digital PCR to analyze formalin-fixed paraffin-embedded (FFPE) biopsies, focusing on specific markers within the H19/cell adhesion molecules pathway.
Article Synopsis
- This review investigates how artificial intelligence (AI) can improve interventional radiotherapy (IRT) by making workflows more efficient and enhancing patient care.
- Analyzing 78 studies from 2002 to 2024, it highlights advancements in areas like treatment planning, contouring, outcome prediction, and quality assurance.
- While AI shows potential for reducing procedure times and personalizing treatments, challenges like clinical validation and quality assurance remain important to address.