Dynamic evaluation of lung involvement during coronavirus disease-2019 (COVID-19) with quantitative lung CT

Effect of body position on the redistribution of regional lung aeration during invasive and non-invasive ventilation of COVID-19 patients

Severe COVID-19-related acute respiratory distress syndrome (C-ARDS) requires mechanical ventilation. While this intervention is often performed in the prone position to improve oxygenation, the underlying mechanisms responsible for the improvement in respiratory function during invasive ventilation and awake prone positioning in C-ARDS have not yet been elucidated. In this prospective observational trial, we evaluated the respiratory function of C-ARDS patients while in the supine and prone positions during invasive (n = 13) or non-invasive ventilation (n = 15). The primary endpoint was the positional change in lung regional aeration, assessed with electrical impedance tomography. Secondary endpoints included parameters of ventilation and oxygenation, volumetric capnography, respiratory system mechanics and intrapulmonary shunt fraction. In comparison to the supine position, the prone position significantly increased ventilation distribution in dorsal lung zones for patients under invasive ventilation (53.3 ± 18.3% vs. 43.8 ± 12.3%, percentage of dorsal lung aeration ± standard deviation in prone and supine positions, respectively; p = 0.014); whereas, regional aeration in both positions did not change during non-invasive ventilation (36.4 ± 11.4% vs. 33.7 ± 10.1%; p = 0.43). Prone positioning significantly improved the oxygenation both during invasive and non-invasive ventilation. For invasively ventilated patients reduced intrapulmonary shunt fraction, ventilation dead space and respiratory resistance were observed in the prone position. Oxygenation is improved during non-invasive and invasive ventilation with prone positioning in patients with C-ARDS. Different mechanisms may underly this benefit during these two ventilation modalities, driven by improved distribution of lung regional aeration, intrapulmonary shunt fraction and ventilation-perfusion matching. However, the differences in the severity of C-ARDS may have biased the sensitivity of electrical impedance tomography when comparing positional changes between the protocol groups.Trial registration: ClinicalTrials.gov (NCT04359407) and Registered 24 April 2020, https://clinicaltrials.gov/ct2/show/NCT04359407 .

Giant compressive emphysema: a rare complication of COVID-19

Background

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a new ribonucleic acid (RNA) beta-coronavirus, responsible for a worldwide pandemic. Very few cases of SARS-COV-2-related emphysema have been described, except among patients with chronic obstructive pulmonary disease. The thoracic CT scan is the key examination for the diagnosis and allows to evaluate the severity of the pulmonary involvement. The prognosis of the patient with giant emphysema (GE) on coronavirus disease 2019 (COVID-19) in critical or severe form remains poor. We report an original case of COVID-19 pneumonia, critical form, complicated by a giant compressive left emphysema of 22.4 cm in a young subject without respiratory comorbidities.

Case presentation

A 34-year-old man was hospitalized for left laterothoracic pain. He had no prior medical history. The physical examination revealed tympany on percussion of the left lung. The CT scan confirmed COVID-19 pneumonia with 95% lung involvement. Also, the presence of a voluminous left sub pleural emphysema of 22.4 cm with compression of the ipsilateral pulmonary parenchyma as well as the mediastinal structures towards the right side. The diagnosis COVID-19 pneumonia, critical form, complicated by a compressive left giant emphysema was made. He was put on oxygen, a dual antibiotic therapy, a corticotherapy, and curative doses of enoxaparin. A thoracic drainage surgery was performed at 24th day of hospitalization, which confirmed the giant emphysema. The patient remains on long-term oxygen therapy.

Conclusion

The COVID-19 has polymorphic manifestations, pneumonia is the most important one. There are relatively few reports associating COVID-19 and emphysema; furthermore, reports associating COVID-19 and giant emphysema are extremely scarce. CT scans can confirm the diagnosis and differentiate it from a pneumothorax. The pulmonary prognosis of the association of COVID-19 in its severe or critical form with giant emphysema remains poor.

The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review

Diagnostic imaging is regarded as fundamental in the clinical work-up of patients with a suspected or confirmed COVID-19 infection. Recent progress has been made in diagnostic imaging with the integration of artificial intelligence (AI) and machine learning (ML) algorisms leading to an increase in the accuracy of exam interpretation and to the extraction of prognostic information useful in the decision-making process. Considering the ever expanding imaging data generated amid this pandemic, COVID-19 has catalyzed the rapid expansion in the application of AI to combat disease. In this context, many recent studies have explored the role of AI in each of the presumed applications for COVID-19 infection chest imaging, suggesting that implementing AI applications for chest imaging can be a great asset for fast and precise disease screening, identification and characterization. However, various biases should be overcome in the development of further ML-based algorithms to give them sufficient robustness and reproducibility for their integration into clinical practice. As a result, in this literature review, we will focus on the application of AI in chest imaging, in particular, deep learning, radiomics and advanced imaging as quantitative CT.