Pulmonary tuberculosis and COVID-19 coinfection: A new medical challenge

Radiological findings in chest radiography and respiratory symptomatology represent a great challenge of interpretation during the COVID-19 (Coronavirus Disease 2019) pandemic, as their patterns can generate uncertainty at the time of diagnosis. This case highlights the importance in achieving an adequate correlation between diagnostic imaging and the clinical picture. We present a male adult who was admitted for 8 days of respiratory symptoms. Management with steroids was initiated according to the RECOVERY (Randomized Evaluation of COVID-19 Therapy) protocol and later confirmation of SARS-CoV-2 infection was received. In the following weeks, he deteriorated slowly and progressively clinically, without reaching respiratory failure. Imaging showed a thick-walled cavitation in the right lower lobe. Tuberculosis was suspected and confirmed. The uniqueness of this case of COVID-19 coinfection in a patient with undiagnosed tuberculosis, represents a diagnostic and clinical management challenge, where the proper interpretation of chest radiology is a fundamental tool.

Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation

The coronavirus disease 2019 (COVID-19) pandemic has made test screening much needed. Currently, the most commonly used is the swab type. Although in fact, there is also a screening method with chest radiology. The purpose of this study is to develop a COVID-19 early detection system based on X-ray images of the patient's thorax in the form of a computer-aided diagnosis. This case is based on the fact that X-ray modalities are available in several health care centers in Indonesia, compared to other modalities such as computed tomography (CT) scan or magnetic resonance imaging (MRI). In this paper, we emphasize the X-ray thorax image segmentation process to explore the morphological information of the thorax. We use the Bradley thresholding segmentation method. The results obtained are promising to be further developed with a performance percentage of 73.33% for the thorax for COVID-19 patients and 54% for the thorax for normal patients.

Chest CT imaging features of Covid-19 patients: Single center observational study

Objective: The aim of this study was to explore the chest Computer Tomography (CT) features of COVID-19 patients and compare the diagnostic performance of chest CT with that of RT-PCR at our center. Material and Methods: The study was conducted by retrospectively scanning the files of patients admitted to the Emergency Department of Karaman State Hospital under suspicion of COVID-19 between March 15 and May 18, 2020. The study included 218 patients (124 males, 94 females, 1-90 years of age, median 48.5) who met the inclusion criteria. Chest CT scan findings were recorded in detail by two radiologists with experience in chest radiology. Furthermore, the CT findings were categorized into four groups in the form of typical, indeterminate, atypical, and negative CT according to the structured reporting system. Results: The RT-PCR results were positive in 41% of 139 cases with positive CT results, while the RT-PCR results were positive in 15.2% of the cases with negative CT results. Regarding the analysis between CT and RT-PCR, the sensitivity was 82.61%, the specificity was 44.97%, the PPV was 41.01%, the NPV was 84.81%. The positivity rate was 82.9% in those with typical imaging findings, 51.5% in those assessed as indeterminate. Those with a typical appearance had a higher rate of positivity than others. Conclusion: The chest CT scan was found to have a high correlation with the RT-PCR in the patients with typical imaging findings in CT. The specificity was found to be low in the CT scan findings without subgroup analysis.

The Classification of Covid-19 cases through the Employment of Transfer Learning on X-ray images

Covid-19 is a contagious disease that known to cause respirotary infection in humans. Almost 219 countries are effected by the outbreak of the latest coronavirus pandemic, exceed 100 millions of confirmed cases and about 2 million death recorded aound the world. This condition is alarming as some of the people who are infected with the virus show no symptoms of the disease. Due to the number of confirmed cases rapidly rising around the world, it is crucial find another method to diagnose the disease at the beginnings stage in order to control the spreading of the virus. Another alternative test from the main screening method is by using chest radiology image based detection which are X-ray or CT scan images. The aim of this research is to classify the Covid-19 cases by using the image classification technique.The dataset consist of 2000 images of chest X-ray images and have two classes which are Covid and Non-Covid. Each of the class consists of 1000 images.This research compare the performance of the various Transfer Learning models (VGG-16, VGG-19, and Inception V3) in extracting the feature from X-ray image combined with machine learning model (SVM, kNN, and Random Forest) as a classifier. The experiment result showed the VGG-19, VGG-16, and Inception V3 coupled with optimized SVM pipelines are comparably efficient in classifying the cases as compared to other pipelines evaluated in this reaseach and could archieved 99% acuuracy on the test datasets.

XANTHO-GRANULOMATOUS OSTEOMYELITIS OF STERNUM, RESEMBLING A TUMOR: FIRST REPORTED CASE

Xantho-granulomatous inflammation is a rare type of chronic inflammation, when seen in the bones it is known as xanthogranulomatous osteomyelitis (XO). Here we present a rare case XO of the manubrium sterni, to best of our knowledge this is the first diagnosed. XO of the manubrium sterni mimics radiologically as tuberculosis and as eosinophillic granuloma. We have a 23 year old lady who presented with pain and swelling in the anterior chest, radiology was done and finally the lesion was biopsied. We accepted the patient as Xanthomatous Osteomyelitis and planned for into excision of manubrium sterni, with a flap comprising of ribs and muscle advancements to cover the midline gap in the chest wall, that would have been created. Meanwhile she was put on a short course of antibiotics. It had been observed that the first open biopsy scar had exhibited a tendency for keloid formation. Hence, the risk of final surgery incision producing a disfiguring keloid was informed to the patient, which unfortunately led the patient deter surgery indefinitely, since she was to be married soon. We proposed a local injection of steroid into the lesion to minimize the inflammation. Under image intensifier we injected 40 mg of methyl prednisolone into the tumor. There was some tolerable discomfort the next day of injection that eventually subsided in 3 days. However, the biopsy came inconclusive second core needle biopsy came as XO. Since 1984 with the first case by Cozzutto et al, only 17 cases have been reported in the worldwide literature including us.