Chest Radiograph (CXR) Manifestations of the Novel Coronavirus Disease 2019 (Covid-19) - A Mini-Review

Background Coronavirus disease 2019 (COVID-19) is highly contagious and has claimed more than one million lives, besides causing hardship and disruptions. The Fleischner Society has recommended chest X-ray (CXR) in detecting cases with high risk for disease progression, for triaging suspected patients with moderate-to-severe illness, and to eliminate false negatives in areas with high pre-test probability or limited resources. Although CXR is less sensitive than real-time reverse transcription polymerase chain reaction (RT-PCR) in detecting mild COVID-19, it is nevertheless useful because of equipment portability, low cost and practicality in serial assessments of disease progression among hospitalized patients. Objective This study aims to review the typical and relatively atypical CXR manifestations of COVID-19 pneumonia in a tertiary care hospital. Methods The CXRs of 136 COVID-19 patients confirmed through real-time RT-PCR from March to May 2020 were reviewed. Literature search was performed using PubMed. Results A total of 54 patients had abnormal CXR whilst the others were normal. Typical CXR findings included pulmonary consolidation or ground-glass opacities in a multifocal, bilateral peripheral or lower zone distribution, whereas atypical CXR features comprised cavitation and pleural effusion. Conclusion Typical findings of COVID-19 infection in chest computed tomography studies can also be seen in CXR. The presence of atypical features is associated with worse disease outcome. Recognition of these features on CXR will improve accuracy and speed of diagnosing COVID-19 patients

MRI of Breast Lymphoma: A Report of Two Cases with Emphasis on Diffusion Weighted Imaging and Apparent Diffusion Coefficient Value

Breast lymphoma is a rare neoplasm that accounts for approximately 0.04-0.5% of breast malignancies. Most breast lymphomas are B-cell type non-Hodgkin lymphomas. The imaging features of breast lymphoma on mammography and ultrasound are nonspecific. There have been several reports on magnetic resonance imaging characteristics of breast lymphoma but only few have described features on diffusion weighted imaging. Herein, we describe the magnetic resonance imaging findings, with emphasis on diffusion weighted imaging and the apparent diffusion coefficient sequences, of two cases of breast lymphoma and compare them with the magnetic resonance imaging features reported in the literature

Magnetic resonance imaging features of invasive breast cancer association with the tumour stromal ratio.

ObjectiveTo assess the association between breast cancer tumour stroma and magnetic resonance imaging (MRI) features.Materials and methodsA total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.ResultsThere was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p ConclusionBreast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR