Work

Machine Learning-enhanced X-ray-based Radiomics in the Identification of Post-COVID Patients

Year: 2024

Type: article

Abstract: Machine Learning-enhanced X-ray-based Radiomics in the Identification of Post-COVID PatientsTo the Director, Post-COVID syndrome substantially affects the patient's quality of life, yet diagnosis is often difficult.1 Therefore, there is an unmet need for developing and validating novel biomarkers that will not only help to establish the diagnosis but also enable defining treatment response.Although both CT-based and X-ray-based radiomic studies successfully distinguish COVID-19 pneumonia from other types of pneumonia and allow the prognostic evaluation of the disease, 2,3 there are no evident radiomic features to date that are predictive of the development of long-term symptoms.Therefore, in this work, we aimed to evaluate the role of deep learning-boosted X-ray radiomics in diagnosing post-COVID patients.The study population consisted of 260, 278, and 435 COVID-19 (mild to moderate acute disease), post-COVID and non-COVID patients, respectively.According to the World Health Organization's (WHO) definition, patients who continued to have or developed new symptoms three months after the initial SARS-CoV-2 infection (with these symptoms lasting for at least two months with no other explanation) were considered individuals with post-COVID syndrome.4 These patients mostly presented with respiratory symptoms (e.g.persistent dyspnea and/or coughing); however, individuals with cardiovascular (e.g.palpitation) manifestations were also included.Post-COVID individuals were diagnosed and examined at the Institution's multidisciplinary post-COVID department.Of note, upon enrollment, all patients were required to complete a standardized questionnaire that covered various aspects of previous infections and symptoms, and they underwent clinical testing to confirm the diagnosis of post-COVID syndrome.As for the COVID-19 patients, inclusion criteria consisted of a confirmed diagnosis of acute SARS-CoV-2 infection by PCR assay requiring hospitalization.Post-COVID and COVID-19 patients with a recent history of intensive care unit admission were excluded.Non-COVID patients were referred from our institution's outpatient department.These patients were diagnosed with mild forms of chronic lung disease, including chronic obstructive pulmonary disease or asthma, and their chest X-rays (CXRs) were performed as part of the routine check-up in the pre-pandemic era (at least six months before the COVID-19 outbreak).All aspects of the current study were conducted in strict compliance with the ethical standards and principles outlined in the Declaration of Helsinki.The study protocol was approved by the national-level Ethics Committee (3270-3/2022/EÜIG).Radiomic workflow began with lung segmentation and cardiothoracic ratio (CTR) determination.For the initial steps of algorithm development for lung segmentation we used the Japanese Society

Source: Archivos de Bronconeumología

DOI: 10.1016/j.arbres.2024.12.004