Ten conditions where lung ultrasonography may fail: limits, pitfalls and lessons learned from a computer-aided algorithmic approach

被引:6
作者
Corradi, Francesco [1 ,2 ]
Vetrugno, Luigi [3 ,4 ]
Isirdi, Alessandro [1 ]
Bignami, Elena [5 ]
Boccacci, Patrizia [6 ]
Forfori, Francesco [1 ]
机构
[1] Univ Pisa, Dept Surg Med & Mol Pathol & Crit Care Med, Pisa, Italy
[2] Galliera Hosp, Anaesthesia & Intens Care Unit, Genoa, Italy
[3] Univ G dAnnunzio, Dept Med Oral & Biotechnol Sci, Chieti, Italy
[4] SS Annunziata Hosp, Dept Anesthesiol Crit Care Med & Emergency, Chieti, Italy
[5] Univ Parma, Sect Anesthesiol, Div Crit Care & Pain Med, Dept Med & Surg, Parma, Italy
[6] Univ Genoa, Dept Informat Bioengn Robot & Syst Engn DIBRIS, Genoa, Italy
关键词
Computer-assisted diagnosis; Artificial intelligence; Respiratory insufficiency; Differential diagnosis; COVID-19; Extravascular lung water; HEART-FAILURE; ULTRASOUND; CONGESTION; PRESSURE; CT;
D O I
10.23736/S0375-9393.22.16195-X
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Lung ultrasonography provides relevant information on morphological and functional changes occurring in the lungs. However, it correlates weakly with pulmonary congestion and extra vascular lung water. Moreover, there is lack of consensus on scoring systems and acquisition protocols. The automation of this technique may provide promising easy-to use clinical tools to reduce inter-and intra-observer variability and to standardize scores, allowing faster data collection without increased costs and patients risks. (Cite this article as: Corradi F, Vetrugno L, Isirdi A, Bignami E, Boccacci P, Forfori F. Ten conditions where lung ultrasonography may fail: limits, pitfalls and lessons learned from a computer-aided algorithmic approach. Minerva Anestesiol 2022;88:308-13. DOI: 10.23736/S0375-9393.22.16195-X)
引用
收藏
页码:308 / 313
页数:6
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