Coronavirus Disease 2019 (COVID-19) in Italy: Double Reading of Chest CT Examination

Abstract

To assess the performance of the second reading of chest compute tomography (CT) examinations by expert radiologists in patients with discordance between the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test for COVID-19 viral pneumonia and the CT report. Three hundred and seventy-eight patients were included in this retrospective study (121 women and 257 men; 71 years median age, with a range of 29–93 years) and subjected to RT-PCR tests for suspicious COVID-19 infection. All patients were subjected to CT examination in order to evaluate the pulmonary disease involvement by COVID-19. CT images were reviewed first by two radiologists who identified COVID-19 typical CT patterns and then reanalyzed by another two radiologists using a CT structured report for COVID-19 diagnosis. Weighted k values were used to evaluate the inter-reader agreement. The median temporal window between RT-PCRs execution and CT scan was zero days with a range of (−9, 11) days. The RT-PCR test was positive in 328/378 (86.8%). Discordance between RT-PCR and CT findings for viral pneumonia was revealed in 60 cases. The second reading changed the CT diagnosis in 16/60 (26.7%) cases contributing to an increase the concordance with the RT-PCR. Among these 60 cases, eight were false negative with positive RT-PCR, and 36 were false positive with negative RT-PCR. Sensitivity, specificity, positive predictive value and negative predictive value of CT were respectively of 97.3%, 53.8%, 89.0%, and 88.4%. Double reading of CT scans and expert second readers could increase the diagnostic confidence of radiological interpretation in COVID-19 patients.

Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment

“…In the context of the COVID-19 outbreak, there is a painstaking need for ready-touse resources for data acquisition and artificial intelligence (AI) algorithms to accelerate the search for effective and safe treatments. The progressive integration of radiomics approaches and AI-based solutions in healthcare is already changing established paradigms in the entire healthcare ecosystem, leveraging the progressive digitalization of medical data [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53]. Specifically, diagnostic and decision support systems developed for medical imaging are the first successful examples of innovation for health.…”

“…AI-based methods have led to diagnostic applications that accelerate image acquisition, preprocessing, annotation and interpretation, offering an "augmentation" of the radiologists, rather than their unrealistic substitution. In particular, the application of AI in medical imaging has improved the assessment, diagnosis and early detection of neurodegenerative diseases, heart diseases, with a specifically high impact on breast and lung cancer [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53].…”

Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia

“…The reference standard for the diagnosis of SARS-CoV-2 infection is next-generation sequencing or real-time reverse transcription polymerase chain reaction (RT-PCR) methods applied to respiratory tract specimens [5]. However, due to intrinsic limitations of the method (i.e., site of specimen swabs, collection and transportation of samples and diagnostic kit performance), sensitivity of RT-PCR ranges between 63 and 78% [6,7].…”

Breast Cancer Screening during COVID-19 Emergency: Patients and Department Management in a Local Experience

“…Some centers [ 28 ] suggest PCR testing before breast interventional procedures in patient with a BIRADS 5 lesion, such as to reduce the waiting time before surgery. However, this would increase the cost of each procedure, and additionally, the waiting time (from 20 min to 2 h) before each interventional procedure [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ]. Consequently, it would increase the time lapse between the exams with a reduced number of procedures accomplished per day.…”