Ultrasound multifrequency strategy to estimate the lung surface roughness, in silico and in vitro results.

Lung ultrasound (LUS) is an important imaging modality to assess the state of the lung surface. Nevertheless, LUS is limited to the visual evaluation of imaging artifacts, especially the vertical ones. These artifacts are observed in pathologies characterized by a reduction of dimensions of air-spaces (alveoli). In contrast, there exist pathologies, such as chronic obstructive pulmonary disease (COPD), in which an enlargement of air-spaces can occur, which causes the lung surface to behave essentially as a perfect reflector, thus not allowing ultrasound penetration. This characteristic high reflectivity could be exploited to characterize the lung surface. Specifically, air-spaces of different sizes could cause the lung surface to have a different roughness, whose estimation could provide a way to assess the state of the lung surface. In this study, we present a quantitative multifrequency approach aiming at estimating the lung surface's roughness by measuring image intensity variations along the lung surface as a function of frequency. This approach was tested both in silico and in vitro, and it showed promising results. For the in vitro experiments, radiofrequency (RF) data were acquired from a novel experimental model. The results showed consistency between in silico and in vitro experiments.

The Beating Heart of Untapped Business Opportunities for Additive Manufacturing.

This article presents a case that joins user-driven innovation and additive manufacturing (AM) towards latent business opportunities in the preparation for life threatening operations. Surgeons, confronted with a patient with a delicate heart condition, collaborated with a prototyping facility to print a realistic 3D model of the patient's aortic aneurysm. The model allowed the surgeons to first study and then experiment to determine the most effective operation procedure before the actual operation, which shortened the surgery time by approximately 70%. Reducing surgery time creates two forms of value: improving patient outcomes and reducing costs. Shorter times under anesthetic and on cardiopulmonary bypass correlate with better surgical results. Reducing healthcare costs brings broad societal benefits in both publicly and privately funded healthcare systems. We outline a case for makerspaces to capture value by joining their expertise and manufacturing equipment with the needs of nearby healthcare systems for novel business developments.