Welcome to this Special Issue of Wiley’s Healthcare Technology Letters (HTL) journal dedicated to the 2023 edition of the Augmented Environments for Computer-Assisted Interventions (AE-CAI), Computer Assisted and Robotic Endoscopy (CARE), and Context-aware Operating Theatres (OR 2.0) joint workshop. We are pleased to present the proceedings of this exciting scientific gathering held in conjunction with the Medical Image Computing and Computer-Assisted Interventions (MICCAI) conference on October 8th, 2023 in Vancouver, British Columbia, Canada. We hope that you will enjoy reading this Special Issue and we look forward to your continuing support and participation in future editions of the AE-CAI, CARE and OR 2.0 workshops. Their continued success demands our ongoing commitment and support, and we hope to welcome you all to the next edition of the workshop at MICCAI 2024 in Marrakesh, Marocco.

Breast cancer is one of the most prevalent forms of cancer, affecting approximately 1 in 8 women during their lifetime. Deciding on breast cancer treatment, which includes the choice between surgical options, frequently demands prompt decision-making within an 8-week timeframe. However, many women lack the necessary knowledge and preparation for making informed decisions. Anxiety and unsatisfactory outcomes can result from inadequate decision-making processes, leading to decisional regret and revision surgeries. Shared decision-making and personalized decision aids have shown positive effects on patient satisfaction and treatment outcomes. We introduce Breamy, a prototype mobile health application that utilizes augmented reality (AR) technology to assist breast cancer patients in making more informed decisions. Breamy provides 3D visualizations of different surgical procedures, aiming to improve confidence in surgical decision-making, reduce decisional regret, and enhance patient well-being after surgery. To determine the perception of the usefulness of Breamy, we collected data from 166 participants through an online survey. The results suggest that Breamy has the potential to reduce patients’ anxiety levels and assist them in decision-making.

 Introduction: A brain connectome models the clusters of neurons as inter-connected nodes and can be obtained from different imaging techniques, including diffusion and functional MRI, for structural and functional connectivity, respectively. It offers us the opportunity to gain further insights regarding neural circuitry to better understand the mechanisms of brain functions and diseases. However, visualization, spatial understanding, and analysis of the network’s topology are difficult due to the neuroanatomy’s complex configuration of brain parcellation and 3D nature. Virtual reality (VR) off ers more intuitive visualization andinteraction for 3D data than traditional 2D displays and is a great fi t to tackle the challenges in visualizing andanalyzing brain connectomes. We introduce a novel immersive VR platform for connectomic data exploration, VRNConnect, with a user-friendly interface for quantitative network analysis and exploration. We demonstrated the functionalities of the system with structural connectivity. Methods: The VRNConnect software was built using the Unity 3D game engine (v2021.3) and Oculus integration SDKv38. An Occulus Quest2 VR headset was used for system development. To create the structural connectome, we used the DWI and T1w MRI of a single subject provided by the B.A.T.M.A.N tutorial. Whole braintractography was performed using the iFOD2 and SIFT algorithms in MRtrix3, and the connectivitymatrix was extracted with the HCP-MMP1 atlas, resulting in 360 nodes. To allow interactive networkanalysis, we employed the Brain Connectome Toolbox library (bctpy v0.6) as the backends for our VR userinterface to compute graph-based metrics, such as clustering coefficient and the shortest path betweennodes, which can be calculated on both hop count- or distance-based. Both controller- and hand gesture basednode and edge selection and interaction were implemented to pick the node of interest, and functions,including connectivity strength thresholding and brain model scaling and zooming. Furthermore, thesoftware allows users to import their connectomic data and/or utilize their own toolbox (with minor codingadjustments) for analysis.