Feasibility of video-based skill assessment for percutaneous nephrostomy training in Senegal.

Percutaneous nephrostomy can be an effective means of preventing irreparable renal damage from obstructive renal disease thereby providing patients with more time to access treatment to remove the source of the blockage. In sub-Saharan Africa, where there is limited access to treatments such as dialysis and transplantation, a nephrostomy can be life-saving. Training this procedure in simulation can allow trainees to develop their technical skills without risking patient safety, but still requires an ex-pert observer to provide performative feedback.

An effective and open source interactive 3D medical image segmentation solution.

3D medical image segmentation is a key step in numerous clinical applications. Even though many automatic segmentation solutions have been proposed, it is arguably that medical image segmentation is more of a preference than a reference as inter- and intra-variability are widely observed in final segmentation output. Therefore, designing a user oriented and open-source solution for interactive annotation is of great value for the community.

Facial Nerve Tractography Using Diffusion MRI: A Comparison of Acquisition b -Values and Single- and Multifiber Tracking Strategies.

Hypothesis: This study investigates the impact of different diffusion magnetic imaging (dMRI) acquisition settings and mathematical fiber models on tractography performance for depicting cranial nerve (CN) VII in healthy young adults.

Background: The aim of this study is to optimize visualization of CN VII for preoperative assessment in surgeries near the nerve in the cerebellopontine angle, reducing surgery-associated complications. The study analyzes 100 CN VII in dMRI images from the Human Connectome Project, using three separate sets with different b values ( b = 1,000 s/mm 2 , b =2,000 s/mm 2 , b =3,000 s/mm 2 ) and four different tractography methods, resulting in 1,200 tractographies analyzed.

End-to-end reproducible AI pipelines in radiology using the cloud.

Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a significant portion of the published literature lacks transparency and reproducibility, which hampers sustained progress toward clinical translation. Although several reporting guidelines have been proposed, identifying practical means to address these issues remains challenging.