Evaluating the impact of image guidance in the surgical setting: A systematic review

BACKGROUND: Image guidance has been clinically available for over a period of 20 years. Although research increasingly has a translational emphasis, overall the clinical uptake of image guidance systems in surgery remains low. The objective of this review was to establish the metrics used to report on the impact of surgical image guidance systems used in a clinical setting. METHODS: A systematic review of the literature was carried out on all relevant publications between January 2000 and April 2016. Ovid MEDLINE and Embase databases were searched using a title strategy. Reported outcome metrics were grouped into clinically relevant domains and subsequent sub-categories for analysis. RESULTS: In total, 232 publications were eligible for inclusion. Analysis showed that clinical outcomes and system interaction were consistently reported. However, metrics focusing on surgeon, patient and economic impact were reported less often. No increase in the quality of reporting was observed during the study time period, associated with study design, or when the clinical setting involved a surgical specialty that had been using image guidance for longer. CONCLUSIONS: Publications reporting on the clinical use of image guidance systems are evaluating traditional surgical outcomes and neglecting important human and economic factors, which are pertinent to the uptake, diffusion and sustainability of image-guided surgery. A framework is proposed to assist researchers in providing comprehensive evaluation metrics, which should also be considered in the design phase. Use of these would help demonstrate the impact in the clinical setting leading to increased clinical integration of image guidance systems

A Hybrid Framework to Investigate Physical Stress Evolution in Peripheral Nerves

The level of physical stress rules the adaptative response of peripheral nerves, which is crucial to assess their physiological and pathological states. To this aim, in this work, a hybrid computational approach was presented to model the stress response of in vitro peripheral nerves undergoing longitudinal stretch. In addition, the rate of change of stiffness with strain was investigated and quantified through the secant modulus in order to achieve a quantitative framework, providing crucial information for both physical rehabilitation and biomaterial science