Artificial Intelligence and Democratization of the Use of Lung Ultrasound in COVID-19: On the Feasibility of Automatic Calculation of Lung Ultrasound Score

Abstract

During the COVID-19 pandemic, lung ultrasound has been revealed as a powerful technique for diagnosis and follow-up of pneumonia, the principal complication of SARS-CoV-2 infection. Nevertheless, being a relatively new and unknown technique, the lack of trained personnel has limited its application worldwide. Computer-aided diagnosis could possibly help to reduce the learning curve for less experienced physicians, and to extend such a new technique such as lung ultrasound more quickly. This work presents the preliminary results of the ULTRACOV (Ultrasound in Coronavirus disease) study, aimed to explore the feasibility of a real-time image processing algorithm for automatic calculation of the lung ultrasound score (LUS). A total of 28 patients positive on COVID-19 were recruited and scanned in 12 thorax zones following the lung score protocol, saving a 3 s video at each probe position. Those videos were evaluated by an experienced physician and by a custom developed automated detection algorithm, looking for A-Lines, B-Lines, consolidations, and pleural effusions. The agreement between the findings of the expert and the algorithm was 88.0% for B-Lines, 93.4% for consolidations and 99.7% for pleural effusion detection, and 72.8% for the individual video score. The standard deviation of the patient lung score difference between the expert and the algorithm was ±2.2 points over 36. The exam average time with the ULTRACOV prototype was 5.3 min, while with a conventional scanner was 12.6 min. Conclusion: A good agreement between the algorithm output and an experienced physician was observed, which is a first step on the feasibility of developing a real-time aided-diagnosis lung ultrasound equipment. Additionally, the examination time was reduced to less than half with regard to a conventional ultrasound exam. Acquiring a complete lung ultrasound exam within a few minutes is possible using fairly simple ultrasound machines that are enhanced with artificial intelligence, such as the one we propose. This step is critical to democratize the use of lung ultrasound in these difficult times.

Inter-rater Variability in the Evaluation of Lung Ultrasound on Videos Acquired from COVID-19 Patients

“…Furthermore, we did not include AI tools able to evaluate the acquired videos and compare them with human observers. In this work, the AI tool used in [8,16] was not compared, and it will be part of future work.…”

“…The acquisitions corresponded to patients with COVID-19 diagnosed by nasopharyngeal RT-PCR for SARS-CoV-2 obtained in the internal medicine service of two different hospitals in Madrid collected during the summer of 2021 [8]. All scans were collected by 2 of the study authors (YT-C, AT-V).…”

“…No patient had more than one scan in the database. In all cases, the data was acquired with the ULTRACOV ultrasound scanner prototype using a 3.5 MHz convex probe with 128-channel ultrasound electronics [8]. This resulted in a total of 480 videos (28,800 frames).…”

“…The imaging depth in all cases was set to 13 cm. More details of the data acquisition can be found in [8].…”

“…LUS has demonstrated the ability to provide immediate information on the condition of COVID-19 patients [4,7]. There are multiple pulmonary manifestations of COVID-19 that can be observed with LUS, such as the presence of pleural effusion, B-line artifacts, or consolidations [8][9][10].…”