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Models to teach lung sonopathology and ultrasound-guided thoracentesis

Lung sonography allows rapid diagnosis of lung emergencies such as pulmonary edema, hemothorax or pneumothorax. The ability to timely diagnose an intraoperative pneumothorax is an important skill for the anesthesiologist. However, lung ultrasound exams require an interpretation of not only real imag...

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Detalles Bibliográficos
Autor principal: Wojtczak, Jacek A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medical Communications Sp. z o.o. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579714/
https://www.ncbi.nlm.nih.gov/pubmed/26672739
http://dx.doi.org/10.15557/JoU.2014.0038
Descripción
Sumario:Lung sonography allows rapid diagnosis of lung emergencies such as pulmonary edema, hemothorax or pneumothorax. The ability to timely diagnose an intraoperative pneumothorax is an important skill for the anesthesiologist. However, lung ultrasound exams require an interpretation of not only real images but also complex acoustic artifacts such as A-lines and B-lines. Therefore, appropriate training to gain proficiency is important. Simulated environment using ultrasound phantom models allows controlled, supervised learning. We have developed hybrid models that combine dry or wet polyurethane foams, porcine rib cages and human hand simulating a rib cage. These models simulate fairly accurately pulmonary sonopathology and allow supervised teaching of lung sonography with the immediate feedback. In-vitro models can also facilitate learning of procedural skills, improving transducer and needle positioning and movement, rapid recognition of thoracic anatomy and hand – eye coordination skills. We described a new model to teach an ultrasound guided thoracentesis. This model consists of the experimenter's hand placed on top of the water-filled container with a wet foam. Metacarpal bones of the human hand simulate a rib cage and a wet foam simulates a diseased lung immersed in the pleural fluid. Positive fluid flow offers users feedback when a simulated pleural effusion is accurately assessed.