 Hello everyone, my name is Dr. Ashin Finto. So I'll be presenting my paper on the role of higher resolution computer tomography in assessing various manifestations of COVID-19 infection for the CTPRS conference 2021. The co-authors of my paper are Dr. Manu Pratap Sir, Dr. Prajit Kumar Sian, Dr. Sanjay Yadav and Dr. Madhu Srimal. So coming to the introduction, so we know that the COVID-19 has become a major health problem causing severe acute respiratory illness. Currently we have the RTPCR study which is a standard method to make a definitive diagnosis of COVID-19. But the RTPCR results can be affected by sampling errors and low virus growth. That is why medical imaging techniques have a potentially important role to play in the early diagnosis and managing the treatment of patients with COVID-19. Small pattern chemical changes can be missed on X-ray. That is why CT is particularly important for the early diagnosis of patients, especially in those with a negative chest X-ray and high clinical suspicion of COVID-19. The early diagnosis of a patient will enable the patient to be isolated and treated early and is essential for avoiding the spread of the disease to improve the prognosis and to reduce the mortality of the patients. So AMS and Objectives is basically to describe the HRCT findings in the thorax and the imaging characteristics in patients with COVID-19 infection. So coming to materials and methods, so a descriptive study was conducted in our department, a tertiary care hospital, care hospital attached to myso-medical college for a period of six months. 78 patients were included after taking informed consent. The inclusion criteria was either sex, patients of either sex more than 18 years of age who were positive for COVID-19, RTPCR positive, and also patients of either sex having a high suspicion of COVID-19 above 18 years of age with lung changes. Exclusion criteria where pediatric age group people and the pregnant women they were excluded from the study because of concern of radiation hazard and also patients without lung changes were excluded from this study. In each house, this patient was subjected to higher resolution computer tomography of the chest using the machine. Siemens 128 slice somatotome dual CT scanner. So coming to the scanning protocol, a region from both the apex of the lung to the adrenals were included. Patient position was supine with the arms above the head and the following parameters were used. 20 MAS, 100 KVP, slice thickness of 0.6 mm, a scan orientation from cranial to cordil, and images were reconstructed in the sagittal and coronal plane, and all examinations were evaluated for the number and which of the lobes were involved. The distribution, the patterns and other parent table changes. So here in this table, you can see that the pie chart is showing the male preponderance 73% of the patients were male patients. And in this age distribution bar chart, you can see that the age of 41 to 15 years of 50 years of age and 51 to 60 years of age where the majority of the age groups which were involved in our study and followed by the 61 to 70 years. So elderly patients were more involved. And coming to this bar chart, which is depicting the location of the gg1, the consolidation. So the center of parent came a location was the least common, then followed by the subdue location and the combination of both was the most common in our study. Then coming to the distribution, the frequency distribution of gg1 consolidation, pure ground glass opacities were found in 41% of the patients, pure consolidation was seen in 32% of the patients. And the combination of both of this was seen in 27% of the patients. And this is the pie chart depicting the other findings of COVID-19. So among this, the majority were the linear opacities and the interlovelous septal thickening at 35.9%. And the other patterns we've seen were halosine, reverse halosine, air bronchogram, interlovelous septal thickening, pure liquefusion, pericardial liquefusion, lymphadenopathy. So coming to the results, so the majority of the patients were male patients. The most common age group affected was 4th and 5th decade, 4th to 5th decade, and the youngest patient was 23 where the oldest was 85, a mean age group of 50 years of age. The most common pattern was pure ground glass opacities, which was seen. And the distribution predominantly was seen both central and peripheral distribution. And additional patterns which we've seen were interlovelous septal thickening, crazy paving pattern, halosine, reverse halosine, cavitations, pericardial liquefusion, medicinal lymphadenopathy in their percentages, which we've seen in the graphs. So coming to the discussions, we know that the characteristic CT findings of COVID-19 infection are bilateral, multifocal, patchy, ground glass opacities, which progressively will coalesce and form consultatory patches. Following this, there's gradual resorption over the weeks, and then they'll result in sequelae in the form of fibrotic strips. So these lesions are initially peripheral in distribution and subtrude in distribution, and then they come more centrally and involve central areas and bronchopulmonary distribution as the disease progresses. And we have the other findings, which other CT findings which we've seen in the graph. So these findings together help differentiate COVID-19 pneumonia from other forms of pneumonia. So coming to discussions, so ground glass opacities, which is the most common pattern is basically because of partial air space filling and interstitial thickening. So the hallmark of CT finding is basically bilateral peripheral distribution of ground glass opacities and consolidation. Okay, so GGOs associated with consolidation is the most frequently encountered pattern. And a study conducted by Wang et al showed that predominantly GGO pattern was seen at the symptom onset, and following by which as the disease progressed over the period of six to seven days, there was presence of consolidation as well, which were with the percentage of 24% over the following days. And a study conducted by Zhu et al reported that in the first postpartum biopsy conducted, they observed that the mechanism for this GGOs was basically because of pulmonary edema and hyaline membrane formation. So this is a high charge image of a patient which is showing ground glass opacities. So basically ground glass opacities if a vessel passes through, you can see the vessel clearly, but in consolidation, it is obscured. And this is the subterranean distribution of the ground glass opacities in another patient. Then coming to consolidation, so basically consolidation means not partial but complete replacement of the alveolar air spaces by pathological fluids and cells. So these two also can be multifocal, they can be patchy, they can be segmental, subtural or very bronchovascular distribution. So what is the mechanism of this consolidation is basically because of accumulation of cellular fibromix or dexudates in the alveolar spaces. So a study conducted by Keiichi et al showed that so whatever changes we see in the pulmonary interstitium, that is the interstitial thickening and all is basically because of inflammatory cell infiltration edema and interstitial thickening. Whereas the pulmonary parankamal changes are basically because of alveolar hemorrhage edema, cell exudation and hyaline membrane formation. The third most common pattern we saw is reticular pattern. So this is basically a network of linear opacities because of interlobular and interlobular septal thickening just because of lymphocytes infiltration. And then we have the crazy paving pattern, which is basically the ground glass opacities with superimposed interlobular septal thickening, which gives appearance of a paving stones. So this is reported in 5 to 36% of the patients. So this is considered as a sign of progression. So a sign of progression of GTOs and consolidation is basically crazy paving pattern. So in this one of the, in one of the patients, you can see this is the actual HRCT image, which is showing subtle distribution of consolidation. So if a vessel passes through here, we cannot see it because the consolidation means the areas obscured obscures the bronchial walls and the vessels. This is another HRCT image showing crazy paving pattern predominantly in the subprol location. Then coming to air bronchograms, which are basically air filled bronchial, which is seen in the background of consolidation. So a study conducted by EA at all proposed that bronchial ectasis is a better terminology to be used. And he hypothesized that the high viscosity of the mucus, which is present in the bronchioles, this will lead to the bronchial damage. And this is what results in bronchial ectasis and the characteristic dry cough seen in COVID-19 patients. And then we have the other airway related mechanisms, that is bronchial ectasis and thickening of the bronchial wall. This is basically because of the inflammatory changes, which causes destruction of the walls, which results in fibrosis and consequent adjacent fractional bronchial ectasis. Then nodules, which are seen in the viral pneumonia is basically rounded irregular parenchymal opacities of less than 3 centimeter in diameter. And the most common plural changes, which was seen in COVID-19 patients in our study was plural thickening in 32% of the patients and less commonly, plural effusion in 5% of the patients. So these findings usually are seen in critical patients who are in ICUs and all, as proven by the study, Kaichi Liu et al. And it indicates poor prognosis. So this is an ideal HSCT image, which is showing reticular opacities and fibrosis with resultant adjacent fractional bronchial ectasis. And this is another patient with COVID-19 showing consolidated changes with air bronchogram, which is seen clearly in the consolidation. Then coming to halosine. So we all know that halosine is basically a nodular mass, which is surrounded by a ground glass opacity. So this is not a specific sign. It's a non-specific sign of COVID-19 infection, which is also seen in other, which is the basic mechanism of this is because of angelinvasive fungal infections. Sometimes it can also be seen in aspergillosis or mucormycosis. And also because of other causes like perillational hemorrhage, viral infections, hypervascular metastases also. Then coming to a reverse halosine. So basically compared to the halosine, the reverse halosine means there is surrounding consolidation and a central clearing of ground glass opacities. So previously to COVID-19 infection, this finding was initially described in cryptogenic organising pneumonia. Then medial senile lymphadenopathy is basically when the short axis diameter is more than 1 centimeter. So this finding has been reported in 4 to 8% of the patients of COVID-19. Basically, it is because of a bacterial super infection, which occurs along with the COVID-19 patients. So that is the most common cause apart from COVID-19. And then pericardial effusion is a rare finding, which was seen in 5% of the patients. So this occurs because of severe inflammation and usually seen in severely affected critical patients or ICU patients. So this is an axial HRCT image. You can see the nodule, which is surrounded by a ground glass opacity, which is the halosine. And in this second image, you can see a patient axial HRCT image. You can see a consolidation with central clearing of the, there is central ground glass opacity, which is the reverse halosine. Then coming to CT severity score. So CT severity score. So the severity of the lung involvement in the CT, it correlates with the severity of the disease. So by this method, we can give percentage to each of the phylobs. So we grade them from 1 to 5 each low. So less than 5% involvement, 5 to 25, 25 to 50, 50 to 75 and more than 75. So we give a score from 1 to 5 for each low. And the maximum is 25. And all phylobs are involved and more than 75% involvement. And minimal is 0 with no involvement. Then corads, we all know the full form is COVID-19 reporting and data system. So 0 stands for the study is not interpretable and technically it is insufficient to assign a score. Score of 1 means very low suspicion. Either the study is normal or some non-infectious findings are seen. If corage 2 criteria, it means the suspicion level of COVID is low. So the findings are typical for other infection, but not COVID-19. And corage 3 means it is equivocal. So it can be compatible with COVID-19, but also these findings can be seen in other diseases. Corage 4 is high suspicion, suspicious for COVID-19. Corage 5 is very high suspicion, which is not suspicion, but typical for COVID-19, but they have to be proven by RTPSR, may be proven, but may not be proven. Proven cases are RTPSR positive SARS COVID-19 patients with the lung changes. So in conclusion, to conclude the interpretation of HRCT images of COVID-19 pneumonia are important in the diagnosis and management of COVID-19 infection. In comparison to other forms of pneumonia, the hallmark pattern and distribution of COVID-19 pneumonia shows bilateral multifocal ground glass opacities predominantly in the subcurtial and basal location, often seen with consolidation and interstitial thickening. Because of low sensitivity of the lab investigation RTPSR, CHESH-HRCT ensures early detection of COVID-19 pneumonia in the correct clinical setting. So also it plays an important role in the fall-up investigation to assess the progression of the disease which may parallel the disease severity. The only possible limitation of CT is the radiation hazard, as COVID does not spare any, it does not spare even newborns or pregnant women also. So these are the references which I have used during my study. Thank you very much.