Time-resolved 3DRA with 4D VRTs and MPRs is technically feasible and provides a detailed display of the angioarchitecture at the fistulous point or the nidus. Visualization of all angiographic features demands additional post-processing. Further standardization of evaluation tools and studies with blinded independent reviewers are necessary before the new technique can replace conventional neuroangiographic approaches.

Activities of a clinical staff in healthcare environments must regularly be adapted to new treatment methods, medications, and technologies. This constant evolution requires the monitoring of the workflow, or the sequence of actions from actors involved in a procedure, to ensure quality of medical services. In this context, recent advances in sensing technologies, including Real-time Location Systems and Computer Vision, enable high-precision tracking of actors and equipment. The current state-of-the-art about healthcare workflow monitoring typically focuses on a single technology and does not discuss its integration with others. Such an integration can lead to better solutions to evaluate medical workflows. This study aims to fill the gap regarding the analysis of monitoring technologies with a systematic literature review about sensors for capturing the workflow of healthcare environments. Its main scientific contribution is to identify both current technologies used to track activities in a clinical environment and gaps on their combination to achieve better results. It also proposes a taxonomy to classify work regarding sensing technologies and methods. The literature review does not present proposals that combine data obtained from Real-time Location Systems and Computer Vision sensors. Further analysis shows that a multimodal analysis is more flexible and could yield better results.

Creating fused images of time-resolved 3D DSA and contrast-enhanced T1-weighted MPRAGE MR images might be beneficial for the preoperative and intrasurgical workflow in patients with AVMs. This new software tool fulfils the required quality and accuracy of the merged images. The clinical validation has to be proven in further studies.