Computed Tomography Scan Of Thorax Research Articles

Predicting COVID-19 Outcomes: Machine Learning Predictions Across Diverse Datasets.

Background The COVID-19 infection has spread rapidly since its emergence and has affected a large part of the global population. With the increasing number of cases, researchers are trying to predict the prognosis of patients by using different data with artificial intelligence methods such as machine learning (ML). In this study, we aimed to predict mortality risk in COVID-19 patients using ML algorithms with different datasets. Methodology In this retrospective study, we evaluated the fever, oxygen saturation, laboratory results, thorax computed tomography (CT) findings, and comorbid diseases at admission to the hospital of 404 patients whose diagnosis was confirmed by the reverse transcription polymerase chain reaction test. Different datasets were created by combining the data. The Synthetic Minority Oversampling Technique was used to reduce the imbalance in the dataset. K-nearest neighbors, support vector machine, stochastic gradient descent, random forest, neural network, naive Bayes, logistic regression, gradient boosting, XGBoost, and AdaBoost models were used to create the ML algorithm, and the accuracy rates of mortality prediction were compared. Results When the dataset was created with CT parenchyma score, pulmonary artery and inferior vena cava diameters, and laboratory results, mortality was predicted with an accuracy of 98.4% with the gradient boosting model. Conclusions The study demonstrates that patient prognosis can be accurately predicted using simple measurements from thorax CT scans and laboratory findings.

Effect of vaccination status on CORADS and computed tomography severity score in hospitalized COVID-19 patients: A retrospective study.

The coronavirus disease 2019 (COVID-19) pandemic is continuing. The disease most commonly affects the lungs. Since the beginning of the pandemic thorax computed tomography (CT) has been an indispensable imaging method for diagnosis and follow-up. The disease is tried to be controlled with vaccines. Vaccination reduces the possibility of a severe course of the disease. The aim of this study is to investigate whether the vaccination status of patients hospitalized due to COVID-19 has an effect on the CT severity score (CT-SS) and CORADS score obtained during hospitalization. The files of patients hospitalized between April 1, 2021 and April 1, 2022 due to COVID-19 were retrospectively reviewed. A total of 224 patients who were older than 18 years of age, whose vaccination status was accessible, whose severe acute respiratory syndrome coronavirus 2 polymerase chain reaction result was positive, and who had a Thorax CT scan during hospitalization were included in the study. Among the patients included in the study, 52.2% were female and the mean age was 61.85 years. The patients applied to the hospital on the average 7th day of their complaints. While 63 patients were unvaccinated (Group 1), 20 were vaccinated with a single dose of CoronaVac (Group 2), 24 with a single dose of BioNTech (Group 3), 38 with 2 doses of CoronaVac (Group 4), 40 with 2 doses of BioNTech (Group 5), and 39 with 3 doses of vaccine (2 doses of CoronaVac followed by a single dose of BioNTech, Group 6). CT-SS ranged from 5 to 23, with a mean of 12.17.CT-SS mean of the groups were determined as 14.17, 13.35, 11.58, 10.87, 11.28, 10.85, respectively. Accordingly, as a result of the comparisons between the groups, the CT-SS levels of the unvaccinated patients found to be significantly higher than the other groups. As the vaccination rates increased, the rate of typical COVID-19 findings on CT was found to be significantly lower. Increased vaccination rates in COVID-19 patients reduce the probability of typical COVID-19 symptoms in the lungs. It also reduces the risk of severe disease and decreases CT Severity Scores. This may lead to a loss of importance of Thorax CT in the diagnosis of COVID-19 pneumonia as the end of the pandemic approaches.

On-cloud decision-support system for non-small cell lung cancer histology characterization from thorax computed tomography scans

Non-Small Cell Lung Cancer (NSCLC) accounts for about 85% of all lung cancers. Developing non-invasive techniques for NSCLC histology characterization may not only help clinicians to make targeted therapeutic treatments but also prevent subjects from undergoing lung biopsy, which is challenging and could lead to clinical implications. The motivation behind the study presented here is to develop an advanced on-cloud decision-support system, named LUCY, for non-small cell LUng Cancer histologY characterization directly from thorax Computed Tomography (CT) scans. This aim was pursued by selecting thorax CT scans of 182 LUng ADenocarcinoma (LUAD) and 186 LUng Squamous Cell carcinoma (LUSC) subjects from four openly accessible data collections (NSCLC-Radiomics, NSCLC-Radiogenomics, NSCLC-Radiomics-Genomics and TCGA-LUAD), in addition to the implementation and comparison of two end-to-end neural networks (the core layer of whom is a convolutional long short-term memory layer), the performance evaluation on test dataset (NSCLC-Radiomics-Genomics) from a subject-level perspective in relation to NSCLC histological subtype location and grade, and the dynamic visual interpretation of the achieved results by producing and analyzing one heatmap video for each scan. LUCY reached test Area Under the receiver operating characteristic Curve (AUC) values above 77% in all NSCLC histological subtype location and grade groups, and a best AUC value of 97% on the entire dataset reserved for testing, proving high generalizability to heterogeneous data and robustness. Thus, LUCY is a clinically-useful decision-support system able to timely, non-invasively and reliably provide visually-understandable predictions on LUAD and LUSC subjects in relation to clinically-relevant information.

The frequency of osteoporosis in the thoracic surgery patient population: An opportunity assessment from thorax computed tomography scans

Aim: To investigate the frequency of osteoporosis in thoracic surgery patients and highlight the clinical significance for physicians.Methods: Thoracic computed tomographies (CT) of 306 patients were examined for medullary density of the T12 vertebra. Men and women, as well as those under 70 and over 70, were compared in terms of Hounsfield units (HU). To evaluate the diagnostic performance of the age parameter in predicting osteoporosis, receiver operating characteristic (ROC) analysis, and logistic regression analysis were used. The rib cortical defects identified in this study group and their causes were explained.Results: HUs of 51 subjects (or 16.7%) were less than 110 (osteoporosis); 177 people (57.8%) were higher than 160 (normal). HU values ranged from 111 to 159 (borderline) for 78 individuals (25.5%). There was no significant difference between males and females. It was discovered that the difference between the population under 70 and the population over 70 was statistically significant (p<0.001). For predicting osteoporosis, the age exhibited an area under the curve of 0.857 (CI 0.806-0.908). The threshold value was 57 for women and 55 for men. Osteoporosis was shown to be accurately predicted by age with a 95.7 percent accuracy rate (p<0.001). Six patients were determined to have rib cortical defects seen on CT scans during the evaluation for osteoporosis, and two more patients had fractures noted during surgery.Conclusion: Within the 306 patients, only 57.8% had bone density within the normal range. The age parameter is valuable with high accuracy (95%) in predicting osteoporosis. The presence of osteoporosis over the age of 57 in women and over 55 in men should be evaluated and measures should be taken to protect the bones during the operation and postoperative care.

Determination of Embryo/Fetus Doses of Pregnants in Thorax Computed Tomography Scan

Determination of Embryo/Fetus Doses of Pregnants in Thorax Computed Tomography Scan

A rare case of migration of ballistic projectile from left to right main bronchus

A foreign body in the bronchus due to a ballistic projectile is very uncommon. A 45-year-old man presented to the hospital after being accidentally shot. The initial radiographic assessment found a bullet in his left thoracic cavity. With the help of an X-ray, an urgent left posterolateral thoracotomy was conducted, but no foreign body was found. The foreign body had migrated to the contralateral chest cavity, as determined by the C-arm. On the following day, a thorax computed tomography scan was conducted, and it was discovered that the foreign body had already migrated to the right lower bronchus. A right thoracotomy was then performed to remove the foreign body. He was moved to the intensive care unit and discharged with a stable condition. In conclusion, migration of a foreign body in the bronchus is rare. A thorough strategy is required to prevent the object from migrating even further.

Diagnostic Reference Range (DRR) in Computed Tomography (CT) Imaging Based on Clinical Indications Related to Thorax, Abdomen and Pelvic Regions

The concept of diagnostic reference range (DRR) is introduced to address the balance between a patient’s risk (radiation dose) and benefit (image quality necessary for an accurate diagnosis). R provides a minimum estimated dose that covers 25–75% range of dose distribution. The International Commission on Radiological Protection, ICRP (2017) recommended the 75th percentile as the upper d 25th percentile as the lower limit of DRR [1]. Dose below the lower range should compromise accurate interpretation of the image and dose above the upper range may be in excess and need to be reviewed. Meanwhile, Diagnostic Reference Levels (DRLs) are set at the 75th percentile of dose distribution and recommended by ICRP as a guidance to identify any unusual computed tomography (CT) procedures that consistently exceed the established DRLs.
 The aim of this study was to establish the local DRR for CT scanning based on clinical indications associated to thorax, abdomen, and pelvic regions in adult patients at Department of Radiology, Hospital Universiti Sains Malaysia (HUSM), Kelantan. This study involved a retrospective survey on data of adult patients underwent CT scanning based on 5 most common clinical indications related to thorax, abdomen, and pelvic regions at two departments, Radiology and Trauma Department, HUSM. This study obtained human ethical approval from the university ethical committee (Protocol code: USM/JEPeM/22010025). The CT dose metrics (dose length product, DLP and total DLP) and associated technical factors were collected.
 Results showed that the five most common clinical indications were cancer staging, coronary artery disease, pulmonary embolism, stones (CTU protocol) and stones (KUB protocol). The DLP values were varied based on their clinical indications and CT scanner types. Figure 1 shows boxplots representing the DRRs of DLP based on five most common clinical indications associated to CT scans of thorax, abdomen, and pelvic regions for Toshiba and Siemens CT scanners. The highest total DLP values was 4722 mGy.cm observed from CT scanning of cancer staging using Siemens scanner. While the lowest DLP value is 40 mGy.cm for stones scanning using the KUB protocol also using Siemens scanner. The main factor that contributes to higher DLP is the longer scanning length.
 This study demonstrates that the dose descriptor values, DLP and total DLP were varied for similar anatomical region based on different image quality requirement for each clinical indication. Thus, utilisation of both DRR and DRL are crucial to minimise the unnecessary dose to patient and ensure the optimum image quality is produced by each CT scanning.

AI Denoising Improves Image Quality and Radiological Workflows in Pediatric Ultra-Low-Dose Thorax Computed Tomography Scans.

(1) This study evaluates the impact of an AI denoising algorithm on image quality, diagnostic accuracy, and radiological workflows in pediatric chest ultra-low-dose CT (ULDCT). (2) Methods: 100 consecutive pediatric thorax ULDCT were included and reconstructed using weighted filtered back projection (wFBP), iterative reconstruction (ADMIRE 2), and AI denoising (PixelShine). Place-consistent noise measurements were used to compare objective image quality. Eight blinded readers independently rated the subjective image quality on a Likert scale (1 = worst to 5 = best). Each reader wrote a semiquantitative report to evaluate disease severity using a severity score with six common pathologies. The time to diagnosis was measured for each reader to compare the possible workflow benefits. Properly corrected mixed-effects analysis with post-hoc subgroup tests were used. Spearman’s correlation coefficient measured inter-reader agreement for the subjective image quality analysis and the severity score sheets. (3) Results: The highest noise was measured for wFBP, followed by ADMIRE 2, and PixelShine (76.9 ± 9.62 vs. 43.4 ± 4.45 vs. 34.8 ± 3.27 HU; each p < 0.001). The highest subjective image quality was measured for PixelShine, followed by ADMIRE 2, and wFBP (4 (4–5) vs. 3 (4–5) vs. 3 (2–4), each p < 0.001) with good inter-rater agreement (r ≥ 0.790; p ≤ 0.001). In diagnostic accuracy analysis, there was a good inter-rater agreement between the severity scores (r ≥ 0.764; p < 0.001) without significant differences between severity score items per reconstruction mode (F (5.71; 566) = 0.792; p = 0.570). The shortest time to diagnosis was measured for the PixelShine datasets, followed by ADMIRE 2, and wFBP (2.28 ± 1.56 vs. 2.45 ± 1.90 vs. 2.66 ± 2.31 min; F (1.000; 99.00) = 268.1; p < 0.001). (4) Conclusions: AI denoising significantly improves image quality in pediatric thorax ULDCT without compromising the diagnostic confidence and reduces the time to diagnosis substantially.

Incidence and Predictors of Cardiac Arrhythmias in Patients With COVID-19.

BackgroundCoronavirus disease 2019 (COVID-19) is a systemic disease caused by severe acute respiratory syndrome coronavirus 2. Arrhythmias are frequently associated with COVID-19 and could be the result of inflammation or hypoxia. This study aimed to define the incidence of arrhythmias in patients with COVID-19 and to correlate arrhythmias with pulmonary damage assessed by computed tomography (CT).MethodsAll consecutive patients with a COVID-19 diagnosis hospitalized at Universitair Ziekenhuis Brussel, Belgium, between March 2020 and May 2020, were screened. All included patients underwent a thorax CT scan and a CT severity score, a semiquantitative scoring system of pulmonary damage, was calculated. The primary endpoint was the arrhythmia occurrence during follow-up.ResultsIn this study, 100 patients were prospectively included. At a mean follow-up of 19.6 months, 25 patients with COVID-19 (25%) experienced 26 arrhythmic episodes, including atrial fibrillation in 17 patients, inappropriate sinus tachycardia in 7 patients, atrial flutter in 1 patient, and third-degree atrioventricular block in 1 patient. No ventricular arrhythmias were documented. Patients with COVID-19 with arrhythmias showed more often need for oxygen, higher oxygen maximum flow, longer QTc at admission, and worse damage at CT severity score. In univariate logistic regression analysis, significant predictors of the primary endpoint were: the need for oxygen therapy (odds ratio [OR] 4.59, 95% CI 1.44–14.67, p = 0.01) and CT severity score of pulmonary damage (OR per 1 point increase 1.25, 95% CI 1.11–1.4, p < 0.001).ConclusionsIn a consecutive cohort of patients with COVID-19 the incidence of cardiac arrhythmias was 25%. The need for oxygen therapy and CT severity score were predictors of arrhythmia occurrence during follow-up.

Lung Fibrosis due to Coronavirus Disease 2019 Pneumonia with Critical Symptoms: A Case Report

BACKGROUND: The pandemic that occurred at the end of 2019 was caused by the coronavirus 2 (Severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). Various speculations mention that the long-term effects of coronavirus disease 2019 (COVID-19) infection can cause pulmonary fibrosis. Acute respiratory distress syndrome (ARDS) is one that can cause pulmonary fibrosis due to injury to the lungs. CASE REPORT: This report discusses a case of pulmonary fibrosis caused by critical COVID-19 (Coronavirus disease) in 38-year-old male patient with hypertension and obesity comorbidities. The patient was treated for 51 days in intensive care unit with 60 L/min high flow nasal cannula assisted oxygenation; then his condition improved as evidenced by his negative Real Time - Polymerase Chain Reaction test result, and was subsequently transferred to a non-COVID-19 ward using non-rebreathing mask at 10–15 L/min, which was later titrated to 2–4 L/min nasal canulla. Patient was treated in the non-COVID ward for 16 days. The total number of days of hospitalization was 67 days. Patient had his thorax photo taken 3 times and non-contrast thorax computed tomography (CT) scan 3 times. Based on the evaluation of his thorax CT scan on day 23, we found a vast fibrosis in patient’s lungs. Many literatures state that lung fibrosis can be triggered by ARDS, a condition due to the infection from SARS-CoV-2. CONCLUSION: COVID-19 infection can progress overtime and may cause pulmonary fibrosis. The most serious phase of this virus infection is characterized by sudden and excessive release of proinflammatory mediators that lead to lung damage with large fibrosis and rapid onset of ARDS. To further our understanding of this issue, we present the case report of lung fibrosis caused by critical COVID-19 infection.

Can evaluating adrenal glands in computed tomography contribute to predicting the prognosis of hospitalized COVID-19 patients?

The novel coronavirus disease 2019 (COVID-19) may affect the adrenal glands. Therefore, it is important to evaluate the morphologic appearance of the adrenal glands by thorax computed tomography (CT). On CT scans, stranding in peripheral fatty tissue with enlarged adrenal glands may indicate signs of adrenal infarction (SAI). The present study aimed to evaluate the incidence of SAI and determine whether this finding may contribute to predictions of the prognosis of COVID-19. A total of 343 patients who had been hospitalized at Malatya Training and Research Hospital between September 1 and 30, 2020, with a diagnosis of COVID-19 were enrolled in this study. All patients underwent thorax CT scans that included their adrenal glands. Of the enrolled patients, 16.0% had SAI. Moreover, 41.8% of patients with SAI and 15.3% of patients without SAI were treated in the Intensive Care Unit (ICU). Patients with SAI had a significantly higher rate of ICU admission (p < 0.001). Mortality rates were also significantly higher among patients with SAI than those without p < 0.001). In this study, it was found that COVID-19 patients with SAI may have a poorer prognosis. More comprehensive studies are needed on this subject, but the present study may provide helpful preliminary information in terms of prognosis.

Gastrointestinal symptoms in COVID-19 patients

Background/Aim. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global threat and a huge problem for our community. There are so many open questions. The aim of this study was to establish the frequency of gastrointestinal (GI) symptoms in hospitalized patients with infection caused by this virus (coronavirus disease-19 ?COVID-19), but also to compare if patients with GI symptoms have a higher computed tomography (CT) scan severity score of interstitial pneumonia (IP) compared to patients with COVID-19 without GI symptoms. Methods. Our database comprised 322 patients with COVID-19 who were divided into two groups, patients with and without GI symptoms. All information was taken from anamnestic data and patients? history, followed by statistical analysis. Results. Thorax CT scans of 206 patients (63.9%) were described as bilateral IP, of which 76 CT scans (36.9%) were described by radiologists as the peak of infection. Moreover, 130 patients (40.4%) had GI symptoms, and even 58 out of 130 patients (44.6%) reported GI symptoms as the first manifestation of COVID-19 infection. The most commonly reported one was the lack of appetite (73 patients or 56.15%). Furthermore, 65 (50%) patients reported diarrhea, 25 (19.2%) patients reported nausea and vomiting, and 9 (6.9%) patients reported abdominal pain. In addition, among patients with bilateral IP and GI tract symptoms, 31 (40.79%) of them did not have a higher CT scan severity score at the peak of the disease compared to the patients without GI symptoms (45 of them or 59.2%), (p = 0.704). Conclusion. GI symptoms often are the first manifestation of COVID-19. Therefore, every patient with newly formed digestive tract symptoms should be tested for COVID-19. On the other hand, GI symptoms do not indicate COVID-19 patients will have a severe form of IP.

Correlation of neuroimaging and thorax CT findings in patients with COVID-19: A large single-center experience

The aim of this current study was to describe the neuroimaging findings among patients with COVID-19 and to compare them with thorax CT imaging findings and clinicobiological profiles. Between the period March 11 and December 31, 2020, we evaluated brain computed tomography (CT) and magnetic resonance (MR) images of patients with COVID-19. A total of 354 patients (mean age 65.2 ± 16.6, 52% female, 42% male) who had brain imaging were included in the study. Of this total sample, 218 had thorax CT scanning (65.5%). Neuroimaging and thorax CT findings, clinical course, neurologic findings, and laboratory data were evaluated. White matter lesions (WML) and thorax CT scans were scored. Participants were divided according to whether or not they had an infarction. The neuroimaging findings indicated infarcts, parenchymal hemorrhage, encephalitis, cortical signal abnormality, posterior reversible encephalopathy syndrome (PRES), and cranial nerve involvement. WML significantly positively correlated with age (p < 0.01) but not with sex (p > 0.05). Thorax CT findings did not demonstrate significant correlations with infarcts, WML, or hemorrhages (p> 0.05). D-dimer and ferritin levels were significantly higher among patients with infarcts (p < 0.05). Immune-mediated prothrombic state and cytokine storm appear to be more responsible for etiopathogenesis than direct viral neurotropism. Neuroimaging and thorax CT findings were not correlated among patients with COVID-19 in our study. These results suggest that neurological manifestations may occur independently of pulmonary involvement and age.

Stent deformation in a sutureless aortic valve bioprosthesis: a pilot observational analysis using imaging and three-dimensional modelling.

The goal of this analysis of the Perceval aortic bioprosthesis was to investigate the ovalization/deformation of the Perceval prosthesis stent after implantation and its propensity for cusp dysfunction, fluttering, fibrosis and blockage. Between August 2014 and May 2019, a total of 134 patients (52% female) underwent aortic valve replacement with the Perceval bioprosthesis. We reconstructed three-dimensional models of the Perceval stent using thorax computed tomography scans for 16 patients employing the software Mimics (Materialise NV, Leuven, Belgium) and analysed the ovality of the stents. Radial force (RF) measurements were performed to compare the stiffness of the Perceval bioprosthesis to that of other valves. The three-dimensional reconstructions showed that all Perceval stents exhibited some degree of deformation and ovalization. Ovality in the annulus and commissure section of the Perceval stents ranged from 6.8% to 45% with mean values of 13.6% and 21.9%, respectively. The RF of the Perceval prosthesis was noticeably lower than that of the Edwards Intuity and several transcatheter aortic valve implantation devices. The stent adopted the preoperative shape of the aorta in the 2 patients for whom pre- and postoperative computed tomography data existed. The Perceval bioprostheses were deformed to different degrees in all analysed cases. The comparably low RFs might be an explanation for the propensity towards this deformation, which can lead to fluttering, a reduction of the cusps' mobility. This condition could potentially result in fibrosis as well as increased transvalvular pressure gradients and might be the cause for the increase in lactate dehydrogenase and the decrease in platelet count.

A 2D\u20133D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy

BackgroundAccurate segmentation of lung lobe on routine computed tomography (CT) images of locally advanced stage lung cancer patients undergoing radiotherapy can help radiation oncologists to implement lobar-level treatment planning, dose assessment and efficacy prediction. We aim to establish a novel 2D–3D hybrid convolutional neural network (CNN) to provide reliable lung lobe auto-segmentation results in the clinical setting.MethodsWe retrospectively collected and evaluated thorax CT scans of 105 locally advanced non-small-cell lung cancer (NSCLC) patients treated at our institution from June 2019 to August 2020. The CT images were acquired with 5 mm slice thickness. Two CNNs were used for lung lobe segmentation, a 3D CNN for extracting 3D contextual information and a 2D CNN for extracting texture information. Contouring quality was evaluated using six quantitative metrics and visual evaluation was performed to assess the clinical acceptability.ResultsFor the 35 cases in the test group, Dice Similarity Coefficient (DSC) of all lung lobes contours exceeded 0.75, which met the pass criteria of the segmentation result. Our model achieved high performances with DSC as high as 0.9579, 0.9479, 0.9507, 0.9484, and 0.9003 for left upper lobe (LUL), left lower lobe (LLL), right upper lobe (RUL), right lower lobe (RLL), and right middle lobe (RML), respectively. The proposed model resulted in accuracy, sensitivity, and specificity of 99.57, 98.23, 99.65 for LUL; 99.6, 96.14, 99.76 for LLL; 99.67, 96.13, 99.81 for RUL; 99.72, 92.38, 99.83 for RML; 99.58, 96.03, 99.78 for RLL, respectively. Clinician's visual assessment showed that 164/175 lobe contours met the requirements for clinical use, only 11 contours need manual correction.ConclusionsOur 2D–3D hybrid CNN model achieved accurate automatic segmentation of lung lobes on conventional slice-thickness CT of locally advanced lung cancer patients, and has good clinical practicability.

Multiple non-syndromic basal cell carcinoma with the chest as primary site and lung metastases: A rare case.

Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in humans, usually affecting elderly Caucasian men and skin regions mostly exposed to the sun, that rarely metastasizes. We report an unusual and aggressive case of multiple, non-syndromic metastatic BCC with an uncommon primary site in the chest and pulmonary metastases, treated successfully with surgery and vismodegib. A 51-year-old woman presented with a large pigmentary lesion of the chest, close to the sternum. She had the lesion for > 25 years and lately noticed multiple facial lesions. The diagnosis of multiple BCC was suspected and a punch biopsy of the primary lesion was performed. Diagnosis was confirmed by immunohistochemistry (BerEp4+, EMA− phenotype). After excision, staging with a thorax computed tomography scan revealed metastatic micro-nodules in the left lung, confirmed histologically after video-assisted thoracic surgical biopsy. Adjuvant chemotherapy with vismodegib was proposed and administered. At 30 days follow-up, thorax computed tomography scan was unaltered and her facial lesions showed significant regression. Although prognosis remains poor, early diagnosis and prompt management complimented by novel biological agents, like vismodegib, targeting disease pathogenesis, seems to bring promising results.

Mortality and Reinfection Rates of the Patients with Mild COVID-19 at the Sixth Month after the Infection

Introduction: The management of the patients with COVID-19 is depend on the clinical presentation. We aimed to evaluate the hospitalization rates due to the progression of the illness in the fist month, the mortality and reinfection rates of the patients with mild COVID-19 during the six months follow-up. Materials and Methods: The study with retrospective design included all SARS CoV-2 PCR positive patients presenting with mild disease to our hospital and who were recommended at-home follow-up during the first month of the COVID-19 pandemic. Demographic characteristics, baseline symptoms, laboratory results and the treatments administered were recorded. The patients were called by phone at six months after the diagnosis. Patients were asked to report hospitalisation at first month, hospitalisation due to any reason and possi- ble reinfections and current symptoms at six month. We noted the mortality rates at first month and at six months from hospital records. Results: The study included 210 patients;130 patients were male. The mean age was 42.3 +/- 15.7 (16-96) years. At baseline, 168 patients (80%) were symptomatic. Fifty-two patients (75.2%) had comorbidities. Thorax computed tomography (CT) was congruent with COVID-19 infection in 46 patients (26%). Twenty-seven patients (16.5%) were hospitalised due to the progression of clinical condition and four (2.4%) needed intensive care transmission. In multivariate analysis, those with comorbidity had having 8.2 fold (95%CI 2.2933.12) D-dimer >= 1 ug/mL had 17.8 fold (OR: 17.8, %95 GA: 3.42-113.3), and diffuse infiltrations in thorax CT scan had 5.36-fold (95% CI 1.46-21.76) higher relative risk for post-COVID hospitalisation. Two (4.1%) out of 48 patients younger than 50 years old and with no risk factors and a normal thorax CT needed hospitalisation. There was no mortality at first month. Four patients (1.9%) died due to deterioration of underlying condition during the six-month follow up. Six patients (3.6%) were considered to be reinfected six months after the first episode. Twenty-six patients (15.6%) had current symptoms which they belived had occured after COVID-19 infection. Conclusion: In the case of the presence of comorbidities, high D-dimer value and diffuse infiltration in thorax CT scan in mild COVID-19 patients, hospitalisation may be the optimal approach.

The Effect Of COVID-19 Pandemic on The Anxiety Levels of Radiology Experts And Clinical Functioning

Objective: The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is a novel human corona virus rapidly spread all over the world and caused Corona Virus Disease-2019 (COVID-19) pandemic. Radiology clinics were reorganised according to the changes in health system in order to combat with this epidemic. We aimed to detect the changes in the functioning of radiology clinics and to state anxiety levels and relevant factors that induced anxiety in radiologists.Methods: The research is a descriptive study, population constitudes, radiology residents, specialists and scholars actively working in Turkey during COVID-19 pandemic. The data of the study were collected digitally, through the clinical activity scale and Back anxiety scale questionnaires created over the internet. The data collection period started on 18.04.2020 and ended on 8.6.2020.Results: Eightysix radiologists completed the survey. It was understood that the radiologists working during the pandemic had a high level of personal anxiety and worked under stress (3,74). A weak linear relationship was found between the changes in the functioning of radiology clinics and the personal concerns of radiology physicians at the p=0.05 error level (0.224). They stated that unnecessary thorax computed tomography (CT) demands increased (4,51) and they made the most thorax CT evaluation in the daily routine (4,42).Conclusion: In our study, it was shown that there were significant changes in the functioning of radiology clinics especially related with increased thorax CT scans at the beginning of the COVID-19 pandemic and that the anxiety levels of radiologists increased due to the pandemic.

Toraks Bilgisayarlı Tomografisinde Tesadüfen Saptanan Nadir Bir Anatomik Varyasyon: Azigos Lobu

Aim: An azygos lobe is an unusual anatomical variation of the upper lobe of the right lung. During the formation of the lungs, the right azygos lobe develops as the precursor of the azygos vein, moving along the pleural surface rather than arcing forward above the origin of the lung to reach the upper vena cava, enters the apex of the right lung in the upper thoracic region. The purpose of this study was to assess the prevalence of the right azygos lobe in a sample of the Turkish population.Methods: This study was conducted from February to October 2020. Each computed tomography (CT) scan was checked for the presence of a right azygos lobe and a fissure on the axial plane. The azygos lobe was described as the convex line in the paramediastinal portion of the upper right lung on the CT scan. Our exclusion criteria were previous thoracic surgery in the right lung or parenchymal distortion on CT examinations.Results: One thousand nine hundred and sixty-five thorax CT scans were evalu¬ated retrospectively. Nine hundred and forty-five of them were from men and the remainder were from women. A total of 15 right azygos lobe variations were detected (six females, nine males). The mean age of the patients was 52.87 ± 14.604 years (30–77). The azygos lobe frequency was 0.76%.Conclusion: The azygos lobe is typically an uncommon variation of the right lung and is not really a distinct lobe. It is a very important variation that should be known about as it can mimic pathological conditions such as cysts, abscesses, or lung le¬sions. Since the azygos lobe is usually an incidental finding, radiologists and sur¬geons should be aware of this this potential anomaly during the imaging and inter¬ventional procedures.

Spontaneous pneumomediastinum secondary to acute stress reaction: a case report

Objective: As spontaneous pneumomediastinum (PMS) is a rare and idiopathic entity, the present report proposes to record one of the few cases of a patient who presented PMS after intense cries induced by psychiatric illness. Case details: A 50-year-old male patient who was admitted to emergency department with agitation, cold sweating, tachycardia and echolalia, associated with screams. Symptoms lasted for about 15 hours and they have started after the patient witnessed a first-degree relative (father) dying at home due to COVID-19. A thorax computed tomography scan found a Pneumomediastinum that involved the upper mediastinum with mild extension to lower neck, near the Thyroid gland. After acute stress reaction diagnosis, accordingly with DSM-IV criteria, patient followed observation for two days and punctual benzodiazepines use, having no clinical complications during hospital stay. Pneumomediastinum was completely resolved. Final considerations: Screams motivated by psychiatric condition can be added to SPM causes list and should motivate phisician awareness, since it may bare life-threatening complications associated.