The purpose of this Educational Poster (EPOS) is to provide an insight into the use of low-dose CT scans in the diagnosis and management of chronic pulmonary diseases.

Computed tomography is widely used in clinical practice, thanks to its great availability and the high performance of current scanners. The considerable amount of radiation involved, along with its widespread use, has raised some concerns for the safety of patients undergoing CT scans. Fortunately, in recent years public institutions, scientific societies, and manufacturers have addressed a lot of attention to the issue Fig. 1, and new reconstruction algorithms have been developed, allowing to reduce the radiation dose to the patient without impairing significantly the imaging...

We searched for scientific papers addressing the issue, particularly those comparing low-dose and standard-dose techniques, in terms of image quality and quantitative analysis measurements provided. We used as web search engine "Pubmed". We have taken into account some of the most diffuse chronic diseases affecting the lung - i.e. emphysema, chronic obstructive diseases, interstitial lung diseases (ILDs), cystic fibrosis (CF). Mets OM et al.2, in a paper published in 2012, determined the influence of IR on quantitative CT measurements of emphysema, air trapping, and airway...

In our opinion, the use of LDCT in chest imaging should be encouraged. Low-dose and ultra-low-dose chest CT scans allow a great radiation dose reduction while maintaining high-quality images. However, there is still possibilityfor improvement. Hopefully, computers with higher computational capabilities will allow a reduction in post-processing time (approximately 45 minutes per series for MBIR algorithms10), while AI will help indeveloping more effective noise-reduction algorithmsand more effective quantitative analysis software.

R. Grasso; Catania/IT - nothing to disclose L. Fanzone; Catania/IT - nothing to disclose C. Ini'; Catania/IT - nothing to disclose S. Cosentino; Catania/IT - nothing to disclose S. Palmucci; Catania/IT - nothing to disclose A. Basile; Catania/IT - nothing to disclose A. Vancheri; Catania/IT - nothing to disclose C. Vancheri; Catania/IT - nothing to disclose A. G. Musumeci; Catania/IT - nothing to disclose

1 - LiuL Model-based Iterative Reconstruction: A Promising Algorithm for Today's Computed Tomography Imaging. J Med Imaging Radiat Sci. 2014 Jun;45(2):131-136. 2 - Mets OMet al. The effect of iterative reconstruction on computed tomography assessment of emphysema, air trapping and airway dimensions. Eur Radiol. 2012 Oct;22(10):2103-9. 3 - Nishio Met al. Emphysema Quantification Using Ultralow-Dose CT With Iterative Reconstruction and Filtered Back Projection.AJR Am J Roentgenol. 2016 Jun;206(6):1184-92. 4 - Zhao T et al.A convolutional neural network for ultra-low-dose CT denoising and emphysema screening. Med...