ABSTRACT
Synthetic biomaterials play a crucial role in developing tissue-engineered heart valves (TEHVs) due to their versatile mechanical properties. Achieving the right balance between mechanical strength and manufacturability is essential. Thermoplastic polyurethanes (TPUs) and elastomers (TPEs) garner significant attention for TEHV applications due to their notable stability, fatigue resistance, and customizable properties such as shear strength and elasticity. This study explores the additive manufacturing technique of selective laser sintering (SLS) for TPUs and TPEs to optimize process parameters to balance flexibility and strength, mimicking aortic valve tissue properties. Additionally, it aims to assess the feasibility of printing aortic valve models with submillimeter membranes. The results demonstrate that the SLS-TPU/TPE technique can produce micrometric valve structures with soft shape memory properties, resembling aortic tissue in strength, flexibility, and fineness. These models show promise for surgical training and manipulation, display intriguing echogenicity properties, and can potentially be personalized to shape biocompatible valve substitutes.
ABSTRACT
BACKGROUND: Automatic tools for detecting new lesions in patients with MS between two MRI scans are now available to clinicians. They have been assessed from the radiologist's point of view, but their impact on the therapeutic strategies that neurologists offer their patients has not yet been documented. OBJECTIVES: To compare neurologist's decisions according to whether a lesion detection support system had been used and describe variability between neurologists on decision-making for the same clinical cases. METHODS: We submitted 28 clinical cases associated with pairs of MRI images and radiological reports (produced by the same radiologist without vs. with the help of a system to detect new lesions) to 10 neurologists who regularly follow patients with MS. They examined each clinical case twice (without vs. with support system) in two sessions several weeks apart, and their patient management decisions were recorded. RESULTS: There was considerable variability between neurologists on decision-making (both with and without support system). When the support system had been used, neurologists more often made changes to patient management (75 % vs. 68 % of cases, p = 0.01) and spent significantly less time analyzing the clinical cases (249 s vs. 216 s, p == 3.10-4). CONCLUSION: The use of a lesion detection support system has an impact not only on radiologists' reports, but also on neurologists' subsequent decision-making. This observation constitutes another strong argument for promoting the wider use of such systems in clinical routine. However, despite their use, there is still considerable variability in decision-making across neurologists, which should encourage us to refine the guidelines.
