Crazy Paving Research Articles

The Contribution of Thoracic CT Scan in the Diagnosis of COVID-19 Pneumonia

Our study is of a retrospective type involving 230 patients with Covid-19 pneumonia hospitalized at the HMA in Marrakech, in the various Covid-19 departments and explored in the medical imaging and radiodiagnostic department by a chest scanner over a period of approximately 04 months from September 01, 2020 to December 31, 2020. The median age of the patients was 58.41 with an interval between 17 and 88 years. The male sex was predominant with 78.26% and a sex ratio M/F of 3.6. Diabetes was the most frequent antecedent with a percentage of 33.04%. The predominant clinical situation was the moderate form with a percentage of 64.8%. On a biological/analytical level, the PCR displayed a positive result in 203 cases (88.26%). The CRP was more than 50mg / L in 63.91% of our cases. Furthermore, a predominant percentage of lymphopenia <1500 / mm3 in 69.6% of patients should be highlighted. On a radiology level, the sensitivity of chest CT scan in our study was of 91.74%. The most frequent lesion found was the ground glass opacities in 170 cases with a percentage of 73.91%, followed by Crazy Paving in 161 cases (70%). Regarding the extent of lung involvement between (25-50%), it was the most common with a percentage of 23.04%. Thoracic CT also revealed peripheral under pleural, and inferior involvement (Basal) with a percentage of 45.21% and 75.21%, respectively. Recovery-wise, the majority of patients recovered clinically with 184 cases (80%) of cures. Transfer to the intensive care unit followed by death was recorded in 23 cases (10%).

Crack lung: a difficult differential diagnosis of ground glass opacities in the emergency setting

BackgroundThe term 'Crack lung' refers to an acute syndrome of diffuse alveolar damage and hemorrhagic alveolitis that occurs within 48 hours of smoking freebase cocaine. Crack lung induces a variety of pulmonary complications, both acute and chronic, including pulmonary edema, alveolar hemorrhage, eosinophilic pneumonia, pneumothorax, and pulmonary thromboembolism. Ischaemia of pneumocytes because of crack use is induced by the following phenomena: thermal damage to the airways, direct toxicity, inflammatory damage, barotrauma and vasospasm. Diffuse alveolar damage and alveolar hemorrhage with eosinophilic cell infiltration and IgE deposits are found in the lung tissue.PurposeWe present two clinical cases of patients admitted to the emergency department of our university hospital with respiratory failure. HRCT scans showed bilaterally, subpleural, and peri-hilar lung parenchyma, extensive areas of parenchymal ground-glass hyperdensity, crazy paving aspects, and relative sparing of the apices. The temporal relationship between the appearance of the bilateral opacities, the history documenting drug use, and the onset of hypoxemia suggests the diagnosis of "Crack lung".ConclusionsIt is important to include drug abuse and crack lung in the differential diagnosis of acute respiratory symptoms with ground-glass opacities, as they are not uncommon in emergency departments and may rapidly progress to ARDS. CT findings are not specific, but it is important to accurately collect anamnestic data and collaborate with the clinician to achieve a diagnosis and establish proper therapy.

Bacillus megaterium infection presenting as pulmonary alveolar proteinosis, a case report

BackgroundPulmonary alveolar proteinosis (PAP) is a special clinical presentation mostly associated with autoimmune disorders. Here we report a rare case of PAP secondary to infection of Bacillus megaterium.Case presentationA 58-year-old woman presented with intermittent cough and dyspnea for half a year. Chest CT scan showed “crazy paving” pattern. B. megaterium was identified by percutaneous CT-guided needle biopsy. She continuously received antimicrobial treatment since the diagnosis and follow-up examination suggested great improvement.ConclusionsTo our knowledge, this is the first case of B. megaterium infection presented with PAP pattern in healthy individuals. Attention should be paid on the secondary causes including rare pathogen infection when patients presented with PAP syndrome.

Early temporal changes on CT chest in patients with COVID-19 pneumonia

Introduction: Computed tomography (CT) scan of the chest helps in the evaluation, prognostication, and follow-up of patients with Corona virus disease-19 (COVID-19) pneumonia.Objectives: To study the early temporal evolution of findings on CT chest in patients with COVID-19 pneumonia at 6 weeks follow up.Material and methods: A retrospective analysis was performed on 40 patients with confirmed COVID-19 pneumonia who underwent baseline chest CT scans followed by a repeat scan at six weeks. Patients were quantitatively assessed using an objective CT severity score and qualitatively assessed using imaging parameters like consolidation, ground glass opacities (GGOs), parenchymal bands, septal thickening, nodules and crazy paving pattern.Results: Mean age of our study population was 58.5 ± 10.2 years with 80% being males. The baseline CT scan revealed a total median CT severity score interquartile range (IQR) of 16/25 (range: 14-20) while the follow-up scan after six weeks revealed a median score (IQR) of 14/25 (range: 8-19). This difference was statistically significant (p=0.04). The difference in CT severity scores of bilateral upper lobes was statistically significant (p=0.04 on right side and p=0.009 on left side); however, the difference in scores of bilateral lower lobes was not statistically significant (p>0.05). The common imaging patterns on baseline imaging were GGO (97.5%), con-solidation (85%), septal thickening (85%), parenchymal bands (60%) and nodules (32.5%), which showed an interval resolution in the follow-up CT scan.Conclusion: Most of the patients with COVID-19 pneumonia showed interval resolution of lung findings seen on short-term follow-up CT scan.

Chest CT Features of Coronavirus Disease-19 (COVID-19) Pneumonia: Which Findings on Initial CT can Predict an Adverse Short-term Outcome?

Abstract Background COVID-19 is a highly contagious viral disease that caused daunting challenges to the health care system; early diagnosis plays a pivotal role in management and prognosis of the disease. Aim of the Work To study the spectrum of chest CT features in coronavirus disease-19 (COVID- 19) pneumonia and to identify the initial CT findings that may have the potential to predict a poor short-term outcome. Patients and Methods This was a retrospective study that included 60 patients (30 clinically improved and 30 clinically deteriorated patients) with RT-PCR confirmed COVID-19 infection who referred to the Radiodiagnosis Department at Ain Shams University Hospitals for chest HRCT examination. An acceptance from the ethical committee of the Radiology Department and the ethical committee of Faculty of Medicine - Ain Shams University was obtained to use the data stored on PACs system with the patient’s consent waived being a retrospective study. Results Shortness of breath, fatigue and presence of other comorbidities were more common in unstable group, seen in 93%, 86% and 66% respectively. CT severity score was higher in unstable group ranging from 12 to 26 together with anteroposterior distribution, central and peripheral distribution, crazy paving and consolidation with air bronchogram. Conclusion Comparison between clinically stable and unstable COVID-19 patients regarding clinical data at admission and initial CT chest findings revealed that higher percentage of total lung affection, central and peripheral involvement, anteroposterior distribution, crazy paving, consolidation with air bronchogram and vessel enlargement were the harbingers of poor prognosis especially in patients of old age, having other comorbidities and presented with shortness of breath.

Chest Computerized Tomography Findings in COVID-19 Patients Presenting to the ER with Gastrointestinal Symptoms

Abstract Background The world continues to face a life-threatening viral pandemic. SARS-CoV-2 has caused over 98 million cases and 2.2 million deaths since January 2020. Chest Computerized tomography is one of the main modalities in the screening and diagnosis of corona virus disease; yet it must correlate with the clinical and laboratory findings. Among available modalities for detecting COVID19, Chest Computerized tomography was done mainly in symptomatic and in high risk patients showing a sensitivity of 94.6% and specificity of 46.0%. Purpose of the Study Detecting COVID19 patients presenting initially or mainly with Gastrointestinal manifestations and to help preventing misdiagnosis and overlooking these patients. In addition to estimating the prevalence of these COVID19 patients presenting with gastrointestinal symptoms only versus those presenting with combined gastrointestinal and respiratory manifestations. Results This study included 95 patients recruited from the Ain-shams and Souad Kafafi University Hospitals from August 2021 till March 2022. These patients presented with gastrointestinal symptoms as their initial or main symptoms with positive PCR test. They were investigated by Chest CT and were interpreted by experienced radiologists in reading CT chest. From such patients, (32%) presented with gastrointestinal manifestations only. The rest of the patients were presenting mainly with gastrointestinal symptoms and associated with chest symptoms. A recurrently observed pattern of bilateral peripheral Ground glass opacities with basal predominance was found in gastrointestinal only group CT scans. Bilateral involvement, consolidation, crazy paving and multi lobar affection were statistically significantly higher in combined group in comparison to GIT only group. Conclusions Commonest Chest CT pattern was bilateral, peripheral GGO with basal predominance among Gastrointestinal only group. These findings indicate high possibility of COVID 19 even in the absence of chest symptoms. Consequently, a rapid diagnosis and earlier quarantine will assist in better treatment and prognosis.

Long-term COVID-19 Complications and Relevant Outcomes in Severe COVID-19 Survivors

Background: Long-term lung sequelae in patients who survived after severe COVID-19 are not clear. This study aims to evaluate complications and relevant outcomes of COVID-19 survivors within 6 months follow-up after discharge from the hospital. Methods: This study is a cohort of 50 patients with severe COVID-19 hospitalized in the intensive care unit (ICU) in 2020-2021 at Shahid Beheshti Hospital, Qom, Iran. The nasopharyngeal swab and reverse- transcription real-time PCR (RT-qPCR) assay were used to confirm COVID-19 in subjects. We used a checklist that compared symptoms, laboratory findings, and lung radiograph findings for patients at the time of admission and within 6 months follow-up after discharge from the hospital. The chest CT scans were used to verify lung involvement. The renal and liver function were assessed using alanine transaminase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), blood urea nitrogen (BUN), creatinine (Cr), and bilirubin. Results: 50 patients out of 384 participants who were hospitalized with severe COVID-19 were followed up within 6 months after discharge from the hospital. Findings revealed that, during the followup period, all clinical symptoms, except GI bleeding (p = 0.155), were significantly lower than the admission time (p < 0.001). Also, the mean of laboratory findings, including lymphocyte, neutrophil, lactate dehydrogenase, international normalized ratio, prothrombin, partial thromboplastin time, ESR, and CRP, were significantly lower than admission time (p < 0.001). Also, the mean of alanine transaminase (ALT) and aspartate aminotransferase (AST) between the admission and discharge time were significantly different (p < 0.001). Within 6 months of follow-up after discharge, the frequency of ground glass opacities, crazy paving, consolidation, spider web sign, and vascular thickening were significantly lower than in the admission time. Conclusion: Our findings revealed that among severe COVID-19 survivors, liver outcomes, inflammation, and clinical factors returned to normal range within 6 months of follow-up after discharge from the hospital. Also, during this period, the radiological findings were significantly lower than in the admission time.

Interest of Chest CT to Assess the Prognosis of SARS-CoV-2 Pneumonia: An In-Hospital-Based Experience in Sub-Saharan Africa.

We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis. The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 (p < 0.001). No case of pulmonary embolism and fibrosis had been documented. The lung lesions affecting 30% of the parenchyma were informative in predicting death (area under the ROC curve at 0.705, p = 0.017). In multivariate analysis, a percentage of lesions affecting 50% of the lung parenchyma increased the risk of dying by 7.194 (1.656-31.250). The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.

Chest CT Scan Features of COVID-19 in a Hospitalized High-Altitude Population

There is a lack of knowledge regarding the type of lung compromise in high-altitude residents with COVID-19. This study aims to evaluate the lung compromise in chest CT scans of high-altitude dwellers hospitalized with COVID-19. Retrospective study that took place in "Daniel Alcides Carrión" Regional Hospital, located 3,250 meters above sea level in the city of Huancayo, Perú. 464 medical charts and chest CT images of hospitalized patients with confirmed COVID-19 from January to March 2021 were reviewed. The mean age was 56 years, 63.1% of the patients were male, and 85.8% of individuals had a CORADS 5. Ground glass infiltrates were found in 93.8% of the patients; alveolar consolidations were present in 86% and were usually bilateral. Thickened septa were described in 46%, lattice pattern in 38.8%, reticular components in 39%, and the crazy paving pattern in 36.9%. Most patients (84.5%) had central and peripheral lesions; only 4% had limited peripheral compromise, and 10% solely central distribution. The left posterior basal segment was the most affected pulmonary segment in 27% of the cases, and the right basal posterior in 26%. Less affected segments were the right and left apical (14% and 13%, respectively). Lung compromise in patients with COVID-19 in this high-altitude population was severe, with mostly bilateral compromise, increased diameter of the pulmonary artery, periaortic and subaortic lymph nodes enlargement, and extensive ground glass and alveolar lesions.

Dyspnea and crazy paving on computed tomography: Is it easy to make the diagnosis?

Dyspnea and crazy paving on computed tomography: Is it easy to make the diagnosis?

HRCT chest: A valuable tool to differentiate other pneumonias from covid-19 pneumonia

To assess how COVID-19 pneumonia differs from other pneumonias in terms of the chest computed tomography features.In this study we included 170 clinically diagnosed cases pneumonia referred to department of radio diagnosis subjected to HRCT thorax which include out patients and in patients out of which 127 patients tested RT-PCR positive for Covid 19 pneumonia for a total duration of 1 year. (March 2020 to March 2021). The parenchymal abnormalities including Ground glass opacities (GGO), ground glass opacities with interlobular septal thickening (crazy paving), GGO with consolidation, consolidation, pulmonary nodules, tree in bud appearances, bronchiolar wall thickening, interlobular septal thickening , halo sign, reverse halo sign, cavitation and pleural effusion and were observed and categorized along with determination of pattern of distribution on chest CT.127 patients who tested positive for COVID 19 and 43 patients with other pneumonia (such as community-acquired pneumonia) were visited, and CT scans were analysed to determine the presence and distribution of the disease pattern.Patients with COVID 19 pneumonia primarily have peripheral-based lesions (90%), whereas patients with other pneumonias primarily have mixed patterns (70%)—a difference that is statistically different (p 0.05).Statistics show that COVID 19 had higher bilateral involvement than other pneumonia (p&amp;#60;0.05). In COVID-19 pneumonia, GGOs, GGOs with interlobular septal thickening (crazy paving), and GGOs with consolidation with peripheral and basal predominance in bilateral lung parenchyma are the most common imaging patterns and findings. These findings will help us distinguish COVID-19 pneumonia from other causes of pneumonia. There is less evidence of tree in bud, pure consolidation, cavitation, and bronchiolar wall thickening.

February 2024 Medical Image of the Month: Pulmonary Alveolar Proteinosis in Myelodysplastic Syndrome

No abstract available. Manuscript truncated after 150 words. Lymphadenopathy decreased after initiation of coccidiomycosis treatment, but symptoms and crazy paving findings continued to worsen. Further workup revealed a new diagnosis of myelodysplastic syndrome (MDS) and subsequent bronchoalveolar lavage (BAL) and histology results were consistent with secondary PAP, likely due to patient’s underlying hematologic disease. Pulmonary alveolar proteinosis (PAP) is a rare disease characterized by the accumulation of lipoproteinaceous material in the lung alveoli. There are two types of PAP that occur in adults: Idiopathic/ autoimmune and Secondary PAP. Idiopathic/autoimmune PAP is more common and is thought to result from antibody production against granulocyte-macrophage-colony-stimulating factor (GM-CSF) that regulates surfactant homeostasis. Secondary PAP results from a precipitating condition, often inhalation exposure, underlying malignancy, or immunocompromise. The clinical manifestations of PAP are nonspecific and includes dyspnea, nonproductive cough, fatigue, and weight loss. CT may show nonspecific findings of smooth, bilateral interlobular septal thickening superimposed on a background of ground-glass opacification (crazy-paving). Diagnosis is confirmed with …

HRCTCov19-a high-resolution chest CT scan image dataset for COVID-19 diagnosis and differentiation.

Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the utilization of advanced methods. Due to privacy concerns, publicly available COVID-19 CT image datasets are incredibly tough to come by, leading to it being challenging to research and create AI-powered COVID-19 diagnostic algorithms based on CT images. To address this issue, we created HRCTCov19, a new COVID-19 high-resolution chest CT scan image collection that includes not only COVID-19 cases of Ground Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation but also CT images of cases with negative COVID-19. The HRCTCov19 dataset, which includes slice-level and patient-level labeling, has the potential to assist in COVID-19 research, in particular for diagnosis and a distinction using AI algorithms, machine learning, and deep learning methods. This dataset, which can be accessed through the web at http://databiox.com , includes 181,106 chest HRCT images from 395 patients labeled as GGO, Crazy Paving, Air Space Consolidation, and Negative.

COVID-19 pneumonia in older patients: clinical features and outcomes of a 400 case series

Background Since late 2019, COVID-19 has been a major health issue worldwide. Older patients seemed more susceptible to severe forms and complications with higher mortality rates. This study aimed to identify the clinical features and outcomes of SARS-Cov-2 pneumonia in elderly patients. Methods Retrospective monocentric study in the internal medicine Covid-19 unit of the Ben Arous regional hospital, enrolling admitted patients with confirmed SARS-CoV-2 pneumonia, aged 65 years and above from September 2020 to September 2021. Results The study group counted 222 women (55.5%). The mean age was 74 years. At least one chronic disease was found in 84.75% of patients. The most common comorbidities were high blood pressure (55.75%), and diabetes mellitus (50%). The most frequent symptoms were dyspnoea (69.8%), fatigue (66.8%) and dry cough (65.8%). Corrected Qt interval was prolonged in 24.2% of cases. Chest computed tomography were performed in 277 cases (69.3%). Ground glass opacities (93.86%), consolidations (73.3%) and crazy paving (36%) were the main findings. Assessment of pulmonary extent found important involvement (41.87%), sever lesions (23.82%), moderate involvement (21.29%) and critical involvement (1.8%). C-reactive protein (CRP) was elevated in 94.25% of patients. Elevated D-dimer levels were common (68.8%). Antinuclear antibodies were positive in 22.85% cases, and lupus anticoagulant in 35.41%. Acute kidney failure was noted in 25% of patients. The incidence of pulmonary embolism in the current study was 12.99%. The death rate was 8%. According to multivariate logistic regression: older age (odds ratio:1.11, 95% CI: 1.058-1.167; P P&lt; .005), elevated C-reactive protein levels (odds ratio: 1.008, 95% CI: 1.003-1.013; P&lt; .005) and duration of hospital stay (odds ratio: 1.131, 95% CI: 1.062-1.204; P&lt; .005) were predictive factors of mortality. Conclusions Clinical presentation of covid-19 pneumonia in elderly patients is particular due to pre-existing comorbidities and frailty. Mortality risk factors are age, elevated CRP and length of hospitalization.

COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography.

When RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass opacities, consolidations, and crazy paving. Radiologists find the manual method for lesion detection in CT very challenging and tedious. Previously solo deep learning (SDL) was tried but they had low to moderate-level performance. This study presents two new cloud-based quantized deep learning UNet3+ hybrid (HDL) models, which incorporated full-scale skip connections to enhance and improve the detections. Annotations from expert radiologists were used to train one SDL (UNet3+), and two HDL models, namely, VGG-UNet3+ and ResNet-UNet3+. For accuracy, 5-fold cross-validation protocols, training on 3,500 CT scans, and testing on unseen 500 CT scans were adopted in the cloud framework. Two kinds of loss functions were used: Dice Similarity (DS) and binary cross-entropy (BCE). Performance was evaluated using (i) Area error, (ii) DS, (iii) Jaccard Index, (iii) Bland-Altman, and (iv) Correlation plots. Among the two HDL models, ResNet-UNet3+ was superior to UNet3+ by 17 and 10% for Dice and BCE loss. The models were further compressed using quantization showing a percentage size reduction of 66.76, 36.64, and 46.23%, respectively, for UNet3+, VGG-UNet3+, and ResNet-UNet3+. Its stability and reliability were proved by statistical tests such as the Mann-Whitney, Paired t-Test, Wilcoxon test, and Friedman test all of which had a p < 0.001. Full-scale skip connections of UNet3+ with VGG and ResNet in HDL framework proved the hypothesis showing powerful results improving the detection accuracy of COVID-19.

Temporal Evolution of CT Findings in COVID-19 Patients: An Observational Study

Introduction: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), presents a broad spectrum of clinical manifestations, from asymptomatic cases to severe pneumonia and acute respiratory distress syndrome (ARDS). Chest computed tomography (CT) has become a critical diagnostic tool, especially in regions with high disease prevalence. This study aims to assess the common CT findings, patterns of lung involvement, and severity of disease in RT-PCR positive COVID-19 patients to better understand and manage this pervasive disease. Materials and Methods: This observational cross-sectional study was conducted at Dr. Kamakshi Memorial Hospital, Chennai, from 2020 to 2021. The study included RT-PCR positive COVID-19 patients aged 18 to 95 years who presented to the fever clinic or COVID casualty and were referred to the radiology department for chest CT evaluation. Exclusion criteria included pregnancy, age under 18 years, and refusal to consent. Non-contrast chest CT scans were performed using a TOSHIBA Aquilion Lightening 16-slice CT machine. Scans were acquired in a single inspiratory breath-hold from the lung apex to the costophrenic angle. CT findings were analyzed and reported by two experienced radiologists, with discrepancies resolved through consensus. Results: Out of 349 patients, 213 (61%) were male and 136 (39%) were female, with a mean age of 47.7 years. The distribution of CT findings showed significant variability among the four groups. Group A had the highest percentage of normal CT scans (22%) and ground-glass opacities (52%). Group B exhibited a reduction in normal CT scans (9%) and an increase in ground-glass opacities (57%). Group C showed further decrease in normal CT scans (10.6%) with increased crazy paving (17.3%) and reticulation (14.6%). Group D had similar normal CT scans (10.8%) but significantly higher incidences of reticulation (24.3%) and ground-glass opacities (64%). Conclusion: This study highlights the critical role of chest CT in monitoring the progression of COVID-19 pneumonia. The findings demonstrate a clear temporal evolution of lung involvement, from ground-glass opacities in the early stages to more complex patterns such as crazy paving and reticulation in later stages.

Perbandingan CT-Scan thoraks pasien dengan infeksi COVID-19 varian Delta dan Omicron: sebuah systematic review

Background: During the COVID-19 pandemic, there have been a number of waves of infections that have resulted in a number of variants of concern (VoC), with the majority of the identified variants being the Delta and Omicron variants. A chest CT scan plays an important role in the diagnosis, complications, and prognosis of COVID-19 patients. This systematic review aims to compare chest CT scan images between COVID-19 patients infected with the Delta and Omicron variants. Methods: Study searches were conducted on three databases of electronic scientific journal publications, namely Google Scholar, PubMed, and Wiley Online Library. The study selection method used the PRISMA diagram with inclusion criteria are original study that examined a comparison of CT-scan images of the chest between COVID-19 patients with the Delta and Omicron variants. While the exclusion criteria set were studies in the form of commentaries, literature reviews, and meta-analyses, studies that were not available in Indonesian or English, and not available in full-text. Results: The ten studies included in this systematic review consisted of 10 retrospective cohort studies that compared CT-scan images of the chests of COVID-19 patients with Delta and Omicron variants. Radiological features evaluated from the ten studies included ground glass opacity (GGO), consolidation, crazy paving pattern, vascular dilation, air bronchogram, bronchial wall thickening, bronchiectasis, presence of reticulation, subpleural lines, fibrosis, halo sign, reverse halo sign (Atoll sign), air bubble sign, and presence of pleural effusion. The majority of these radiological features were found to be higher in the Delta variant compared to the Omicron. Whereas for the classification of chest CT scan images based on RSNA, typical images were also found more in the Delta variant. The CT severity score, CO-RADS score, and COV-RADS score were also found to be higher in the Delta variant compared to Omicron. Conclusion: In COVID-19 infection, the Delta variant showed a chest CT-scan showing typical COVID-19 pneumonia, whereas in the Omicron variant, more atypical features were found.

The macrostructure of lungs on multislice computed tomography scans in the long-term period after COVID-19 pneumonia

The purpose of the study using MSCT monitoring data was to investigate the semiotics of residual changes in the lungs in the long-term period (up to 2 years) after pneumonia associated with COVID-19 (COronaVIrus Disease 2019).Methods. A comparative analysis of MSCT data of the chest organs was carried out in 146 patients with a confirmed diagnosis of COVID-19-associated pneumonia in 2020 – 2021 and subsequent MSCT monitoring data until 2023. MSCT was performed using a 64-slice computed tomography scanner with data post-processed on the workstation.Results. Based on the analysis, 4 groups of patients were identified that differed in the severity of viral pneumonia and the prevalence of lung lesions. The first group of patients had the most beneficial course. In 90% of cases, there was a complete resolution of the consequences of viral pneumonia in terms macroscopic changes in lung tissue by the second year of observation. In the second group, which consisted primarily of older people, 27 (52.94%) patients in year 1 and in 33 (64.7%) patients in year 2 showed a recovery of macrostructure. This group demonstrated fibrous cords, reticular changes, reactions of pleura, and residual lesions (“ground glass”). A similar trend, but in a more severe form, was observed in group 3 patients. 40 patients (86.95%) had residual changes similar to those in group 2 (middle, elderly age and older people) with the addition of bronchial wall thickening and bronchiectasis. Only in 2 (22.22%) of 9 patients with atypical manifestations of COVID-19 pneumonia in the form of “crazy paving” changes in the form of reticular seals, fibrous cords, localized thickening of the pleura and lymphadenopathy persisted up to 2 years of observation.Conclusion. MSCT monitoring of the lungs of patients suffering from COVID-19-associated pneumonia up to 2 years after recovery showed that the prevalence and severity of post-COVID changes in the lungs depends on the severity of the disease (degree and nature of damage to the pulmonary parenchyma) and the patient’s age.

Computed tomography findings in COVID-19 and atypical pneumonia: a comparative study.

Computed tomography (CT) has an important role in the rapid diagnosis, treatment, and management of lower respiratory tract infections. This study aimed to explore different imaging characteristics between Coronavirus disease 2019 (COVID-19) and atypical pneumonia (non-COVID-19) on chest CT of patients admitted to the emergency department. CT features of 120 patients with positive Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse transcriptase-polymerase chain reaction (RT-PCR) and 83 patients with negative SARS-CoV-2 by RT-PCR but positive respiratory tract sample test results for other respiratory pathogens were retrospectively evaluated, findings were recorded and compared between the two groups. Compared to non-COVID-19, COVID-19 patients were more likely to have a peripheral (60.5% vs. 23.8%, p < 0.001) and bilateral distribution (72.3% vs. 41.3%, p < 0.001), patchy consolidations (45% vs. 28.9%, p = 0.021), ground glass opacity (GGO) (94.2% vs. 83.1%, p = 0.011), crazy paving patterns (55% vs. 31.3%, p < 0.001); but less likely to have centrilobular nodules (15% vs. 62.7%, p < 0.001), pleural effusion (3.3% vs. 10.8%, p = 0.032), multifocal consolidations (7.5% vs. 21.7%, p = 0.003), and random distribution (1.7% vs. 46.3%, p < 0.001). There were significant differences between the CT patterns of patients with COVID-19 and other atypical pneumonia. The presence of patchy consolidations, GGO, crazy paving patterns with typical peripheral, bilateral distribution, and absence of centrilobular nodules, pleural effusion, and multifocal consolidations may help to differentiate COVID-19 from atypical pneumonia.

Study of the Correlation between CT Pattern and Clinical Presentation in Confirmed Cases of COVID-19 Pneumonia

Abstract Background In Febreury, 2020 with start of COVID pandemic, chest CT outperformed lab testing in the diagnosis of 2019 novel corona virus disease (COVID-19). The researchers concluded that CT should be used as the primary screening tool for COVID-19 Early identification and treatment are therefore essential in COVID-19 management. Patients &amp; Methods We Observationally collected the records of patients with RT-PCR-confirmed COVID-19 in Ain-Shams University Hospitals from 12th of June 2021 till 12th of August 2021. A total of 100 patients with consecutively laboratory-confirmed COVID-19. All patients performed HRCT chest in the time of their presentations and the different CT findings were mentioned and severity of the disease were calculated according to summation of the areas affected in different lung lobes in both lobes using the Total Severity Score and accordingly cases classified into mild, moderate and severe. All clinical data including non-respiratory &amp; respiratory symptoms were recorded as well as oxygen saturation and correlated with CT severity. Results Mean age was 59.22 ±13.76 years; 65% were males and 35% were females. Non-respiratory symptoms only were present in 10 % of cases and respiratory symptoms were present in 90% of cases. The most common chest symptom was cough in 72% of our patients followed by dyspnea in 65% of them. The most common non-respiratory manifestations, were fever in 60 %, followed by fatigue in 15%, headache in 15% and diarrhea in 27% of patients. The most common CT findings were bilateral GGOs (63%), unilateral GGOs (17 %), both consolidation and GGOs (6%), while 9% had GGOs and crazy paving. According to severity index, 52 patients (52 %) were mild, 38 patients (38 %) were moderate and 10 patients (10 %) were advanced. There was a highly significant negative relation between radiological severity and oxygen saturation i.e., the more the severity score, the lower the oxygen saturation. Conclusion Bilateral peripheral (Ground Glass Opacities) GGO is the most common finding in COVID. CT severity score correlate significantly with Body aches, cough &amp; dyspneawith negative correlation between CT severity score and oxygen saturation.