Enhanced pneumothorax visualization in ICU patients using portable chest radiography

被引:3
作者
Ley-Zaporozhan, Julia [1 ,2 ]
Shoushtari, Hassan [1 ]
Menezes, Ravi [1 ]
Zelovitzky, Leon [1 ]
Odedra, Devang [1 ]
Jimenez-Juan, Laura [3 ]
Brunet, Karyn [1 ]
Karimzad, Yasser [1 ]
Paul, Narinder S. [1 ,4 ,5 ,6 ]
机构
[1] Toronto Gen Hosp, Univ Hlth Network, Dept Med Imaging, Toronto, ON, Canada
[2] Ludwig Maximilians Univ Munchen, Univ Hosp Munich, Dept Radiol, Munich, Germany
[3] Sunnybrook Hlth Sci Ctr, Dept Med Imaging, Toronto, ON, Canada
[4] London Hlth Sci Ctr, Dept Med Imaging, London, ON, Canada
[5] Robarts Res Inst, St Josephs Healthcare, London, ON, Canada
[6] Lawson Res Inst, St Josephs Healthcare, London, ON, Canada
关键词
X-RAYS; TUBES;
D O I
10.1371/journal.pone.0209770
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Objective Pneumothorax development can cause precipitous deterioration in ICU patients, therefore quick and accurate detection is vital. Portable chest radiography is commonly performed to exclude pneumothoraces but is hampered by supine patient position and overlying internal and external material. Also, the initial evaluation of the chest radiograph may be performed by a relatively inexperienced physician. Therefore, a tool that could significantly improve pneumothorax detection on portable radiography would be helpful in patient care. The aim of this study was to evaluate the clinical utility of novel enhancement software for pneumothorax detection in readers with varied clinical experience of detecting/excluding pneumothoraces on portable chest radiographs in ICU patients. Subjects and methods 206 portable ICU chest radiographs, 103 with pneumothoraces, were processed with and without enhancement software and reviewed by 5 readers who varied in reading experience. Images were grouped for different complexity levels. Results The mean AUC for pneumothorax detection increased for 4/5 readers from 0.846-0.957 to 0.88-0.971 with a largest improvement for the reader with least experience. No significant change was noted for the reader with the longest reading experience. The image complexity had no impact on the interpretation result. Conclusion Pneumothorax detection improves with novel enhancement software; the largest improvement is seen in less experienced readers.
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页数:11
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