Background CT is a very sensitive technique to detect pneumonia in COVID-19 patients. However, it is impaired by high costs, logistic issues and high risk of exposure. Chest x-ray (CXR) is a low-cost, low-risk, not time consuming technique and is emerging as the recommended imaging modality to use in COVID-19 pandemic. This technique, although less sensitive than CT-scan, can provide useful information about pulmonary involvement. Purpose To describe chest x-ray features of COVID-19 pneumonia and to evaluate the sensitivity of this technique in detecting pneumonia. A further scope is to assess the effectiveness of a post-processing algorithm in improving lung lesions detectability. Materials and Methods 72 patients with laboratory-confirmed COVID-19 underwent bedside chest X-ray. Two radiologists were asked to express their opinion about: (i) presence of pneumonia (negative or positive); (ii) localization (unilateral or bilateral); (iii) topography (according to pulmonary fields); (iv) density (non consolidative ground-glass or inhomogeneous opacities; consolidative nodulartype or triangular; mixed consolidative e non-consolidative); and (v) presence of pleural effusion. The point (i) was evaluated separately, while the other points in consensus. A quality assessment of post-processed x-ray images was performed by two different readers. Results The agreement about presence of pneumonia was almost perfect with K value of 0.933 and p < 0.001. Sensitivity was 69%. The following findings were seen: unilateral lung involvement in 50%; lower lung lesions in 54%; peripheral distribution in 48%; and non-consolidative pattern in 44%. Post-processed images improved the detection of lesions in 7 out 72 patients (≅10%) Conclusion CXR owns a good sensitivity in detecting COVID-19 lung involvement. Use of post-processing algorithm can improve detection of lesions. Our data support recommendations of the Radiological Society of North America (RSNA) to consider chest x-ray as first step imaging examination in Covid-19 patients.