Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review
Background: Chest X-ray (CXR) remains the standard imaging modality in postoperative care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in CXR reduction. The aim of this review was to identify areas where the evaluation of LUS videos by artificial intelligence co...
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| Format: | Article |
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MDPI AG
2023-09-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/13/18/2995 |
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| author | Marek Malík Anton Dzian Martin Števík Štefánia Vetešková Abdulla Al Hakim Maroš Hliboký Ján Magyar Michal Kolárik Marek Bundzel František Babič |
| author_facet | Marek Malík Anton Dzian Martin Števík Štefánia Vetešková Abdulla Al Hakim Maroš Hliboký Ján Magyar Michal Kolárik Marek Bundzel František Babič |
| author_sort | Marek Malík |
| collection | DOAJ |
| description | Background: Chest X-ray (CXR) remains the standard imaging modality in postoperative care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in CXR reduction. The aim of this review was to identify areas where the evaluation of LUS videos by artificial intelligence could improve the implementation of LUS in thoracic surgery. Methods: A literature review of the replacement of the CXR by LUS after thoracic surgery and the evaluation of LUS videos by artificial intelligence after thoracic surgery was conducted in Medline. Results: Here, eight out of 10 reviewed studies evaluating LUS in CXR reduction showed that LUS can reduce CXR without a negative impact on patient outcome after thoracic surgery. No studies on the evaluation of LUS signs by artificial intelligence after thoracic surgery were found. Conclusion: LUS can reduce CXR after thoracic surgery. We presume that artificial intelligence could help increase the LUS accuracy, objectify the LUS findings, shorten the learning curve, and decrease the number of inconclusive results. To confirm this assumption, clinical trials are necessary. This research is funded by the Slovak Research and Development Agency, grant number APVV 20-0232. |
| first_indexed | 2024-03-10T22:52:03Z |
| format | Article |
| id | doaj.art-54952b7ad6bc43939b3be586c182cbb8 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T22:52:03Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-54952b7ad6bc43939b3be586c182cbb82023-11-19T10:14:27ZengMDPI AGDiagnostics2075-44182023-09-011318299510.3390/diagnostics13182995Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic ReviewMarek Malík0Anton Dzian1Martin Števík2Štefánia Vetešková3Abdulla Al Hakim4Maroš Hliboký5Ján Magyar6Michal Kolárik7Marek Bundzel8František Babič9Department of Thoracic Surgery, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital in Martin, Kollárova 4248/2, 036 59 Martin, SlovakiaDepartment of Thoracic Surgery, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital in Martin, Kollárova 4248/2, 036 59 Martin, SlovakiaRadiology Department, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital in Martin, Kollárova 4248/2, 036 59 Martin, SlovakiaRadiology Department, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital in Martin, Kollárova 4248/2, 036 59 Martin, SlovakiaDepartment of Thoracic Surgery, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava and University Hospital in Martin, Kollárova 4248/2, 036 59 Martin, SlovakiaDepartment of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 040 01 Košice, SlovakiaDepartment of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 040 01 Košice, SlovakiaDepartment of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 040 01 Košice, SlovakiaDepartment of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 040 01 Košice, SlovakiaDepartment of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 040 01 Košice, SlovakiaBackground: Chest X-ray (CXR) remains the standard imaging modality in postoperative care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in CXR reduction. The aim of this review was to identify areas where the evaluation of LUS videos by artificial intelligence could improve the implementation of LUS in thoracic surgery. Methods: A literature review of the replacement of the CXR by LUS after thoracic surgery and the evaluation of LUS videos by artificial intelligence after thoracic surgery was conducted in Medline. Results: Here, eight out of 10 reviewed studies evaluating LUS in CXR reduction showed that LUS can reduce CXR without a negative impact on patient outcome after thoracic surgery. No studies on the evaluation of LUS signs by artificial intelligence after thoracic surgery were found. Conclusion: LUS can reduce CXR after thoracic surgery. We presume that artificial intelligence could help increase the LUS accuracy, objectify the LUS findings, shorten the learning curve, and decrease the number of inconclusive results. To confirm this assumption, clinical trials are necessary. This research is funded by the Slovak Research and Development Agency, grant number APVV 20-0232.https://www.mdpi.com/2075-4418/13/18/2995lung ultrasoundartificial intelligencedeep learningthoracic surgerypostoperative management |
| spellingShingle | Marek Malík Anton Dzian Martin Števík Štefánia Vetešková Abdulla Al Hakim Maroš Hliboký Ján Magyar Michal Kolárik Marek Bundzel František Babič Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review Diagnostics lung ultrasound artificial intelligence deep learning thoracic surgery postoperative management |
| title | Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review |
| title_full | Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review |
| title_fullStr | Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review |
| title_full_unstemmed | Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review |
| title_short | Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review |
| title_sort | lung ultrasound reduces chest x rays in postoperative care after thoracic surgery is there a role for artificial intelligence systematic review |
| topic | lung ultrasound artificial intelligence deep learning thoracic surgery postoperative management |
| url | https://www.mdpi.com/2075-4418/13/18/2995 |
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