Publications by authors named "W L Dahut"
Background And Objective: Our aim was to examine worldwide patterns and trends for prostate cancer (PC) incidence and mortality using high-quality, up-to-date, population-based data.
Methods: We analyzed age-standardized PC incidence and mortality rates by country and region from the 2022 GLOBOCAN estimates and temporal trends in incidence (50 countries/territories) and mortality (59 countries/territories) rates using data from the Cancer Incidence in Five Continents series and the World Health Organization mortality database.
Key Findings And Limitations: Estimated PC rates across regions in 2022 varied 13-fold for incidence and 9.
Article Synopsis
- * Experts in the field gathered to discuss and improve the language surrounding this disease to make it less intimidating.
- * The goal is to establish a clearer and more accurate way to define the nomenclature related to advanced prostate cancer for better patient understanding.
Objective: To evaluate MRI-based measurements of androgen-sensitive perineal/pelvic muscles in men with prostate cancer before and after androgen deprivation therapy (ADT) as a novel imaging marker for end-organ effects of hypogonadism. Diagnosing hypogonadism or testosterone deficiency (TD) requires both low serum testosterone and clinical symptoms, such as erectile dysfunction and reduced libido. However, the non-specific nature of many TD symptoms makes it challenging to initiate therapy.
View Article and Find Full Text PDFTelemedicine has routinely been used in cancer care delivery for the past 3 years. The current state of digital health provides convenience and efficiency for both health-care professional and patient, but challenges exist in equitable access to virtual services. As increasingly newer technologies are added to telehealth platforms, it is essential to eliminate barriers to access through technical, procedural, and legislative improvements.
View Article and Find Full Text PDFPurpose: Sequential PET/CT studies oncology patients can undergo during their treatment follow-up course is limited by radiation dosage. We propose an artificial intelligence (AI) tool to produce attenuation-corrected PET (AC-PET) images from non-attenuation-corrected PET (NAC-PET) images to reduce need for low-dose CT scans.
Methods: A deep learning algorithm based on 2D Pix-2-Pix generative adversarial network (GAN) architecture was developed from paired AC-PET and NAC-PET images.