Publications by authors named "F Azoury"
Article Synopsis
- Dedicated brain imaging for cancer patients is rarely recommended unless symptoms arise, and brain metastases are often difficult to identify on non-enhanced CT (NE-CT).
- This research aims to create a 3D Convolutional Neural Network (3D-CNN) using NE-CT scans to effectively distinguish between cancer patients with and without brain metastases.
- The study utilized a dataset of 200 patients (100 with and 100 without brain abnormalities), achieving high accuracy (ACC of 0.983) and sensitivity (0.983) in detecting brain metastases, indicating the potential for a reliable diagnostic tool with further validation needed.
Solitary large brain metastases (LBM) and high-grade gliomas (HGG) are sometimes hard to differentiate on MRI. The management differs significantly between these two entities, and non-invasive methods that help differentiate between them are eagerly needed to avoid potentially morbid biopsies and surgical procedures. We explore herein the performance and interpretability of an MRI-radiomics variational quantum neural network (QNN) using a quantum-annealing mutual-information (MI) feature selection approach.
View Article and Find Full Text PDFCoronary artery aneurysms are rare conditions with potentially devastating consequences. We describe the case of an athletic 40-year-old woman who received a diagnosis of giant right coronary artery aneurysm while she was undergoing a work-up for lower extremity varicose veins. She underwent successful surgical treatment without any complications.
View Article and Find Full Text PDFAims: To evaluate the effectiveness of a brief smoking cessation intervention in head and neck cancer patients (HNCP).
Study Design: A prospective randomized controlled trial that randomly assigns participants in two groups: a usual care group (UCG), and a standardized intervention group (SIG).
Material And Methods: Patients with a confirmed diagnosis of head and neck squamous cell carcinoma (HNSCC) and who are active smokers were prospectively approached by one of 4 trained Ear-nose-throat (ENT) residents.
Purpose: This work aims to evaluate the dosimetric consequences of replacing the Anisotropic Analytical Algorithm (AAA) by Acuros XB (AXB), dose-to-water (Dw) or dose-to-medium (Dm), for RapidArc plans of nasopharyngeal carcinomas (NPC).
Materials And Methods: Seventeen NPC plans created with AAA (v15.6) were recalculated with AXB (v15.