A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19.

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.

Design, validation, and clinical practice of standardized imaging diagnostic report for COVID-19. / COVID-19规范化影像学诊断报告的设计、验证与临床实践.

OBJECTIVES: To design a standardized imaging diagnostic reporting mode for screening coronavirus disease 2019 (COVID-19), and to prospectively verify its effectiveness in clinical practice. METHODS: A new classification and standardized imaging diagnosis report mode of viral pneumonia was established by studying and summarizing the imaging findings of various kinds of viral pneumonia, combining with lesion density, interstitial changes, pleural effusion, lymph nodes, and some special signs. After systematic training, the radiologist experienced clinical practice for screening CT features. COVID-19 cases were screened retrospectively in the single-center. The confirmed cases were verified, and the diagnostic efficacy of the standardized imaging reporting system in screening COVID-19 was tested. RESULTS: There were 912 patients in this stage receiving the screening imaging examination. Of them, 190 patients were screened in the report mode and 30 patients were diagnosed as COVID-19. The CT manifestation of COVID-19 was characterized by pure ground glass lesions or with a few solid components, predominant subpleural distribution, no lymph node enlargement and pleural effusion, and often with paving-way sign and air bronchus sign. In combination with the above signs, the diagnostic efficacy of COVID-19 was 0.942. CONCLUSIONS: The standardized imaging diagnosis report mode based on COVID-19 chest image features is effective and practical, which should be popularized.