Chest Ultrasound Can Reduce the Use of Roentgenograms in Postoperative Care After Thoracic Surgery

Malík, Marek; Dzian, Anton; Skaličanová, Michaela; Hamada, Ĺuboš; Zeleňák, Kamil; Grendár, Marian

doi:10.1016/j.athoracsur.2020.10.019

Cited by 8 publications

(31 citation statements)

References 23 publications

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“…Four studies reported changes in patient care after X-raying patients for various other indications. As reported above, three studies allowed patients to be subcategorized into more than one group depending on the indication of the X-ray [ 1 , 4 , 5 ].…”

Section: Resultsmentioning

confidence: 99%

“…The third part comes when the drain can be removed. There are studies supporting the clamping of the drain before removal in order to avoid unnecessary interventions, especially in patients following pneumothorax surgery, where the rate of re-interventions has been estimated at 6.5% [ 5 ]. One of the studies in our review reported a change in patient management in 14% of the patients after an X-ray with a clamped drain [ 4 ].…”

Section: Discussionmentioning

confidence: 99%

“…Three of the included studies allowed patients to be subcategorized into more than one group depending on the indication for the X-ray [ 1 , 4 , 5 ]. For this reason, the number of X-rays and not the number of patients was used for the statistical analysis.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Are Routine Chest X-rays Necessary following Thoracic Surgery? A Systematic Literature Review and Meta-Analysis

Galata

Ortolano

Shafiei

et al. 2022

Cancers

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(1) Background: The number of chest X-rays that are performed in the perioperative window of thoracic surgery varies. Many clinics X-ray patients daily, while others only perform X-rays if there are clinical concerns. The purpose of this study was to assess the evidence of perioperative X-rays following thoracic surgery and estimate the clinical value with regard to changes in patient care. (2) Methods: A systematic literature research was conducted up until November 2021. Studies reporting X-ray outcomes in adult patients undergoing general thoracic surgery were included. (3) Results: In total, 11 studies (3841 patients/4784 X-rays) were included. The X-ray resulted in changes in patient care in 488 cases (10.74%). In patients undergoing mediastinoscopic lymphadenectomy or thoracoscopic sympathectomy, postoperative X-ray never led to changes in patient care. (4) Conclusions: There are no data to recommend an X-ray before surgery or to recommend daily X-rays. X-rays immediately after surgery seem to rarely have any consequences. It is probably reasonable to keep requesting X-rays after drain removal since they serve multiple purposes and alter patient care in 7.30% of the cases.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Are Routine Chest X-rays Necessary following Thoracic Surgery? A Systematic Literature Review and Meta-Analysis

Galata

Ortolano

Shafiei

et al. 2022

Cancers

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“…LUS was performed every time CXR was performed, but the strategy varied from postoperative examination [16,18], examination after chest tube removal [18,19], combination of postoperative examination and examination prior to chest tube removal [22,23], postoperative examination and examination after chest tube removal [20], postoperative examination and examinations prior and also after chest tube removal [25] and daily routine examination until chest tube removal [26]. The LUS was performed to detect PTX and lung re-expansion only [17,19,20,25]; or to detect PTX and PE [15,22,23]; or evaluation of PTX, PE, and lung consolidations [26]; or detection of PTX, PE, lung consolidations, subcutaneous emphysema and diaphragm position [16,18]. Evaluated LUS signs varied from detection of lung sliding only [17] to the use of complex protocols with additional signs [19,20].…”

Section: Summary Of the Reviewed Trials Methodsmentioning

confidence: 99%

Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review

Malík,

Dzian,

Števík

et al. 2023

Diagnostics

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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.

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“…The standard imaging method for monitoring post-surgery complications such as pneumothorax and pleural effusion after thoracic surgery is a chest X-ray. Previous clinical trials showed that a lung ultrasound could be used successfully as a primary imaging modality after non-cardiac thoracic surgery for the diagnostics of pneumothorax and pleural effusion [1,2]. The advantages of LUS include avoiding unnecessary radiation exposure [3], reducing the need for in-hospital transfers of patients with inserted chest drains (a flexible plastic tube that is inserted through the chest wall and into the pleural cavity), and lowering economic costs.…”

Section: Introductionmentioning

confidence: 99%

Detecting the Absence of Lung Sliding in Lung Ultrasounds Using Deep Learning

et al. 2021

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Certain post-thoracic surgery complications are monitored in a standard manner using methods that employ ionising radiation. A need to automatise the diagnostic procedure has now arisen following the clinical trial of a novel lung ultrasound examination procedure that can replace X-rays. Deep learning was used as a powerful tool for lung ultrasound analysis. We present a novel deep-learning method, automated M-mode classification, to detect the absence of lung sliding motion in lung ultrasound. Automated M-mode classification leverages semantic segmentation to select 2D slices across the temporal dimension of the video recording. These 2D slices are the input for a convolutional neural network, and the output of the neural network indicates the presence or absence of lung sliding in the given time slot. We aggregate the partial predictions over the entire video recording to determine whether the subject has developed post-surgery complications. With a 64-frame version of this architecture, we detected lung sliding on average with a balanced accuracy of 89%, sensitivity of 82%, and specificity of 92%. Automated M-mode classification is suitable for lung sliding detection from clinical lung ultrasound videos. Furthermore, in lung ultrasound videos, we recommend using time windows between 0.53 and 2.13 s for the classification of lung sliding motion followed by aggregation.

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Chest Ultrasound Can Reduce the Use of Roentgenograms in Postoperative Care After Thoracic Surgery

Cited by 8 publications

References 23 publications

Are Routine Chest X-rays Necessary following Thoracic Surgery? A Systematic Literature Review and Meta-Analysis

Are Routine Chest X-rays Necessary following Thoracic Surgery? A Systematic Literature Review and Meta-Analysis

Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review

Detecting the Absence of Lung Sliding in Lung Ultrasounds Using Deep Learning

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