Mass casualty incidents with multiple burn victims: rationale for a Swiss burn plan.

INTRODUCTION: Mass casualty incidents involving victims with severe burns pose difficult and unique problems for both rescue teams and hospitals. This paper presents an analysis of the published reports with the aim of proposing a rational model for burn rescue and hospital referral for Switzerland. METHODS: Literature review including systematic searches of PubMed/Medline, reference textbooks and journals as well as landmark articles. RESULTS: Since hospitals have limited surge capacities in the event of burn disasters, a special approach to both prehospital and hospital management of these victims is required. Specialized rescue and care can be adequately met and at all levels of needs by deploying mobile burn teams to the scene. These burn teams can bring needed skills and enhance the efficiency of the classical disaster response teams. Burn teams assist with both primary and secondary triage, contribute to initial patient management and offer advice to non-specialized designated hospitals that provide acute care for burn patients with Total Burn Surface Area (TBSA) <20-30%. The main components required for successful deployments of mobile burn teams include socio-economic feasibility, streamlined logistical implementation as well as partnership coordination with other agencies including subsidiary military resources. CONCLUSIONS: Disaster preparedness plans involving burn specialists dispatched from a referral burn center can upgrade and significantly improve prehospital rescue outcome, initial resuscitation care and help prevent an overload to hospital surge capacities in case of multiple burn victims. This is the rationale behind the ongoing development and implementation of the Swiss burn plan.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.