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The company Dasel SL of Arganda will develop the first ultrasound scanner for early detection of Covid-19

Article published on July 28th, 2020 in Madrid365.es

The company Dasel SL, a SME specializing in ultrasound technology from Arganda del Rey, will develop, together with the CSIC, the Universidad Complutense de Madrid, and the Universitario La Paz Hospital, the first 100% Spanish ultrasound scanner designed for the early detection and monitoring of coronavirus.

As reported by the Consistory of the town in a statement, named ‘Ultracov’ it is the first ultrasound scanner oriented to detect lung pathologies and has the support of the Center for the Development of Industrial Technology (CDTI) for the  extraordinary aid to R & D projects to address the health emergency.

The objective of the project, which has a duration of 18 months and is expected to begin clinical trials of the prototype in early 2021, is the development of an ultrasound scanner designed for the early detection and monitoring of Covid-19 disease, specially designed for pandemic situations and high healthcare pressure.

Artificial Intelligence

Through interactive artificial intelligence tools that simplify the performance of the examination process and the interpretation of the images, the goal is to extend lung ultrasound to a greater number of professionals and services, from primary care to intensive care.

This is a «very specific tool” for the evaluation of pulmonary condition at all stages of the disease, including potential chronic problems in the medium and long term. In addition, it would also be useful for the diagnosis and care of patients with other potentially serious lung pathologies in vulnerable groups.

The City Council explained that «there is consensus that bedside lung ultrasound is a valuable tool for the diagnosis and follow-up of patients with coronavirus, as it is innocuous, very specific and can be performed at the patient’s bedside». However, they stressed that «it is a technique that is still not widely used, mainly due to the fact that the interpretation of lung images is complex and to the shortage of personnel with specific training”.