ABSTRACT
Background: High-resolution computed tomography (HRCT) chest is rapid and has a strong sensitivity for diagnosing viral pneumonia including COVID 19 disease in its early stages in comparison to RT-PCR, thus being crucial in triaging patients for treatment and isolation, to prevent further transmission of the disease. In this study we are going to analyse the temporal changes in imaging findings of COVID-19 on HRCT chest. Methods: prospective study was conducted in the Department of Radiology of an exclusive 500 bedded COVID Hospital in Bhubaneswar, Odisha, India. Evaluation of hundred patients was done based on inclusion and exclusion criteria, after obtaining informed consent over a period of 2 years from September 2020 to September 2022. All pertinent epidemiological data was gathered from hospital records. All COVID 19 RT-PCR positive patients who underwent HRCT Chest on admission and repeat scan within 30 days, following the progression of the disease were included. Those who were clinically suspected COVID cases but were RT PCR negative on RT-PCR testing, were excluded. Results: HRCT chest demonstrated diffuse ground glass opacities to be the predominant finding (55%) with the associated findings of sub pleural atelectatic bands (31%) and septal thickening (23%). There was a positive correlation of blood parameters like CRP in COVID patients. A higher incidence was found in patients with Type-2 diabetes mellitus, followed by those with hypertension. In majority of the cases (80%) bilateral lungs and in about 81% cases, two or more lung lobes were involved. Mild and moderately ill patients were found to have a CTSS (CT severity score) in the score range of 15-25. Typical category was the most common type followed by atypical and indeterminate categories. Conclusions: 'Typical pattern' along with diffuse ground glass opacities of multiple lobes in the HRCT chest was the most common pattern of lung involvement. High Computer Tomography Severity Score (CTSS) corresponds to a higher disease severity, which helps in taking a timely decision for early treatment. HRCT Thorax has early and fast diagnostic capability as compared to RT-PCR in the detection of COVID-19. The elderly and those with comorbidities are at a higher risk of developing severe disease. Blood parameters like CRP can be used for disease monitoring and follow-up purposes. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Introduction: Computed Tomography (CT) is rapid and sensitive enough to identify COVID-19 pneumonia in its early stages. But because of the disease's high case load, it is difficult for the talented radiologists to report the cases. Therefore, using Artificial Intelligence (AI) to support radiologists' work will be crucial for producing prompt and precise results. Objective: To determine diagnostic effectiveness of AI in identifying different COVID-19 CT patterns and to correlate the AI findings with the findings appreciated by skilled Radiologists. Material and Methods: A prospective study consisting of 500 patients with RT-PCR positive COVID- 19 patients were evaluated, after obtaining informed consent. Data was analysed and represented in the form of frequencies and proportions. Collected data were analysed by Pearson's correlation coefficient (r), Intra Class Correlation (ICC) coefficient, Bland--Altman analysis. Results: AI can assess the severity of disease quickly and with good accuracy compared to manual analysis by decreasing the time taken to analyse the scan by 50%, and overall accuracy of approximately 90%. Conclusion: We conclude that as manual analysis of Chest CT in COVID-19 high case load scenario is comparatively more time-consuming, there is a need for a quick, accurate, and automated technique for identification and quantification of common findings in COVID-19. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Background The occurrence of invasive fungal infections in COVID-19 patients is on surge in countries like India. Several reports related to rhino-nasal-sinus mucormycosis in COVID patients have been published in recent times;however, very less has been reported about invasive pulmonary fungal infections caused mainly by mucor, aspergillus or invasive candida species. We aimed to present 6 sputum culture proved cases of invasive pulmonary fungal infection (four mucormycosis and two invasive candidiasis) in COVID patients, the clues for the diagnosis of fungal invasion as well as difficulties in diagnosing it due to superimposed COVID imaging features. Case presentation The HRCT imaging features of the all 6 patients showed signs of fungal invasion in the form of cavities formation in the pre-existing reverse halo lesions or development of new irregular margined soft tissue attenuating growth within the pre-existing or in newly formed cavities. Five out of six patients were diabetics. Cavities in cases 1, 2, 3 and 4 of mucormycosis were aggressive and relatively larger and showed relatively faster progression into cavities in comparison with cases 5 and 6 of invasive candidiasis. Conclusion In poorly managed diabetics or with other immunosuppressed conditions, invasive fungal infection (mucormycosis, invasive aspergillosis and invasive candidiasis) should be considered in the differential diagnosis of cavitary lung lesions.