Visualization and postprocessing of medical images – MPR, MIP, VRT, segmentation. Essence and application

The workload in radiology departments has been increasing substantially over the last few decades. This is due to the greater need of tomographic examinations, as well as the increasing number of slices in each examination, determined by the advancements in tomographic technology. In order to ameliorate this, it is necessary to implement means of optimising the workflow of the diagnostic radiologist. Among them the most widely spread and easily accessible are special methods for visualization and image postprocessing – multiplanar reformats, maximum intensity projections, volume rendering techniques, and segmentation. They enable easier differentiation of unclear findings, faster and more reliable discovery of fine small calibre lesions and thrombi, improved spatial orientation and pre-operative planning, as well as acquisition of reproducible and reliable medical scientific measurements. These methods are available as builtin modules in most medical imaging software packages (including ones with an open source) and are an integral part of radiological interpretation, saving time and effort. In the future they can be reinforced with highly specialized artificial intelligence, which could make automatic measurements and locate a specific type of finding

Epicardial fat as an imaging biomarker in the assessment of cardiometabolic risk in patients with type 1 diabetes with a duration of over 15 years

Diabetes mellitus is one of the most frequent metabolic diseases and is characterized by increased coronary risk. Data from epicardial fat quantification in long-term type 1 diabetes patients with poor control and healthy volunteers, performed with computed tomography and magnetic resonance tomography, is analyzed in relation to biochemical and anthropometric indicators. Statistically significant correlations are established between epicardial fat volume and body mass index in diabetic men, as well as between epicardial fat volume and dyslipidemic markers

Correlation between coronary calcium score and epicardial fat in patients with long-term type 1 diabetes and healthy controls – preliminary results

In recent years еpicardial adipose tissue has been reported to be an independent predictor of coronary risk, along with the already well established coronary calcium score. In our study we look for a corellation between these two markers in patients with long-term diabetes mellitus type 1 and healthy controls. Epicardial fat volume is quantified by semiautomatically and manually segmenting images acquired with computed tomography and magnetic resonance tomography. The two types of images demonstrate excellent correlation between them. A mild to moderate correlation between epicardial fat volume and coronary calcium score is found, regardless of which type of image the fat is calculated from