Publications by authors named "M F Boomsma"
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
View Article and Find Full Text PDF[How well does artificial intelligence detect fractures in the cervical spine on CT?].
Ned Tijdschr Geneeskd
September 2024
Objective: To compare diagnostic accuracy of artificial intelligence (AI) for cervical spine (C-spine) fracture detection on CT with attending radiologists.
Design: Retrospective, diagnostic accuracy study.
Methods: AI analyzed 2368 scans from patients screened for C-spine fracture with CT (2007-2014, fracture prevalence 9.
Magnetic Resonance-Guided Focused Ultrasound Surgery for Gynecologic Indications.
Magn Reson Imaging Clin N Am
November 2024
Article Synopsis
- MRgFUS is a promising and safe treatment for uterine fibroids and adenomyosis, especially for women looking to preserve their fertility.
- It has shown potential in relieving pain for conditions like endometriosis and recurrent gynecologic cancers, but further research is required.
- Widespread reimbursement for MRgFUS is limited due to insufficient large-scale studies comparing it to standard treatment options.
Background: Accumulating data implicate interleukin (IL)-33, a proinflammatory cytokine released locally upon epithelial cell damage, in the pathogenesis of COPD. In a phase 2 study, itepekimab, a human monoclonal antibody against IL-33, reduced exacerbations and improved lung function in a subgroup analysis of former smokers with COPD with an acceptable safety profile.
Methods: The study designs of AERIFY-1 and AERIFY-2 are described in this article.
Background: Metallic artefacts caused by metal implants, are a common problem in computed tomography (CT) imaging, degrading image quality and diagnostic accuracy. With advancements in artificial intelligence, novel deep learning (DL)-based metal artefact reduction (MAR) algorithms are entering clinical practice.
Objective: This systematic review provides an overview of the performance of the current supervised DL-based MAR algorithms for CT, focusing on three different domains: sinogram, image, and dual domain.