Publications by authors named "B Festa"
Objective: To evaluate the accuracy of diffusion-weighted magnetic resonance imaging (DWI-MRI) in diagnosing persistent/recurrent head and neck squamous cell carcinomas (HNSCCs) after primary chemoradiotherapy (CRT).
Data Sources: Scopus, PubMed/MEDLINE, and Cochrane Library databases were searched for relevant publications until April 18, 2023.
Review Methods: A systematic review and meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses of Diagnostic Test Accuracy statement.
Article Synopsis
- The study aims to evaluate outcomes and complication rates after CCA/ICA resection in patients with head and neck squamous cell carcinoma (HNSCC).
- A total of 276 patients were analyzed, finding 1-year overall survival rates at 52.7% and disease-specific survival rates at 58.6%; the median follow-up was 11 months.
- The study suggests that CCA/ICA resection can be a viable treatment option for certain patients, advocating for further research to create a predictive score to aid in treatment decisions.
Comparison between the high-definition 3D exoscope and the operating microscope in head and neck reconstruction.
Int J Oral Maxillofac Surg
June 2024
The purpose of this study was to compare the three-dimensional (3D) operating exoscope (OE) with the conventional operating microscope (OM) in head and neck reconstruction. A retrospective cohort study was performed including 50 consecutive patients with no history of previous surgery or irradiation (32 male, 18 female; mean age 59.2 ± 13.
View Article and Find Full Text PDFPurpose: To predict the necessity of enteral nutrition at 28 days after surgery in patients undergoing major head and neck oncologic procedures for oral and oropharyngeal cancers.
Material And Methods: Data from 193 patients with oral cavity and oropharyngeal squamous cell carcinoma were retrospectively collected at two tertiary referral centers to train (n = 135) and validate (n = 58) six supervised machine learning (ML) models for binary prediction employing 29 clinical variables available pre-operatively.
Results: The accuracy of the six ML models ranged between 0.