Chest CT abnormalities in COVID-19: a systematic review

Abstract

Computed tomography (CT) of the chest is one of the main diagnositic tools for coronavirus disease 2019 (COVID-19) infection. To document the chest CT findings in patients with confirmed COVID-19 and their association with the clinical severity, we searched related literatures through PubMed, MEDLINE, Embase, Web of Science (inception to May 4, 2020) and reviewed reference lists of previous systematic reviews. A total of 31 case reports (3768 patients) on CT findings of COVID-19 were included. The most common comorbid conditions were hypertension (18.4%) and diabetes mellitus (8.3%). The most common symptom was fever (78.7%), followed by cough (60.2%). It took an average of 5.6 days from symptom onset to admission. The most common chest CT finding was vascular enlargement (84.8%), followed by ground-glass opacity (GGO) (60.1%), air-bronchogram (47.8%), and consolidation (41.4%). Most lung lesions were located in the lung periphery (72.2%) and involved bilateral lung (76%). Most patients showed normal range of laboratory findings such as white blood cell count (96.4%) and lymphocyte (87.2%). Compared to previous published meta-analyses, our study is the first to summarize the different radiologic characteristics of chest CT in a total of 3768 COVID-19 patients by compiling case series studies. A comprehensive diagnostic approach should be adopted for patients with known COVID-19, suspected cases, and for exposed individuals.

Características clínicas, imagenológicas y de laboratorio de pacientes con COVID-19 según requerimiento de ingreso a UCI en Cali, Colombia

“…El patrón de vidrio esmerilado (14.28%) fue la característica de mayor frecuencia después de la consolidación (31.25%), pero no se encontraron diferencias significativas entre ambos grupos En la TAC de tórax el hallazgo más común fue el patrón de vidrio esmerilado (46.93%). Varios estudios también reportaron estos hallazgos como los más frecuentes (4,10,39,42). Se ha identificado que las opacidades en vidrio esmerilado corresponden al daño alveolar difuso que está asociado a la patogénesis de infecciones virales (4).…”

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia

“… Lesion distribution, with each of the following properties described by a binary label (yes/no): Bilateral, when pulmonary lesions are visible in both lungs in an approximately similar percentage (Fig. 3 ) [ 24 ]; Basal predominant: lesions affect mainly the bases of the lungs with relative sparing of the upper regions (Fig. 4 ) [ 4 ].…”

Automated diagnosis of COVID-19 using radiological modalities and Artificial Intelligence functionalities: A retrospective study based on chest HRCT database

“…While monitoring these parameters in manual and traditional way,in many cases it is time consuming, tedious and repetative. Machine Learning (ML) and Deep Learning (DL) tools may provide a helping hand to the physicians so as to increase the screening rate [16] , [17] , [18] , [19] , [19] . The automated ML and DL algorithms can be used in biomedical platforms and can be used as AI-based tools to design predictive models.…”