Introduction: Quality control test is used to achieve the highest levels of quality for tomography device. Such standard quality control is very difficult and needs lot of time. The solution is the idea, better known as the Optimage project. This project is based on the digital control of image quality through evaluation of test images with diagnostic image transmitted via the intranet to the computer where the images are processed in Optimage software. This solution offers automatic storage in the database and managing the dynamics of the results, appropriate response and perception of changes regarding basic conditions, but also allows the determination of sufficient level of image display, appropriate parameters of the device in accordance with the manufacturers instructions for use and constant quality parameters of the device.
Purpose: The purpose of the master's thesis is to obtain information on the bringing software tool Optimage into clinical practice, study the automation of the process of quality control for testing the quality of computed tomography image.
Methods: Review of literature and recommendations on the quality of CT images. In addition, we performed cross-sectional study of quality control CT devices in General Hospital Čakovec in Croatia in the period from August to September 2016, using quantitative methods work. In our study we used information obtained with GE Healthcare Optima CT660 according to standard QC protocol, with GE Healthcare phantom (PMMA glass, diameter 20cm) for checking the quality of CT images and with the computer. On the basis daily measurements with scanning GE Healthcare phantom, all images were analyzed by Optimage software.
Results: The Optimage is very easy to install on each computer, to which its use is very simple and fast. Software Optimage is offering us a graphical result representation of each parameter over time. All the values that we have obtained are within the reference values. Statistics are set according to the time and number of scanning which could affect the picture quality. Statistical analysis and study of the impact of load devices for computer tomography on quality parameters, we count the Pearson coefficient. According to the level of risk (p> 0.05) the impact was not statistically significant for the value of CT number, noise and uniformity in the four ROI (south, north, east and west). Utilization of the unit and the value of uniformity in the center of the boys are marginal, but statistically significantly associated (r = 0.64, p = 0.043). Linear regression showed us that the impact of time on quality parameters of CT is not statistically significant (p> 0.05). By analyzing one-way ANOVA, we found that the differences in the value of HU in different ROI are not statistically significant (ANOVA, Factor = ROI area, F = 0,901, p = 0,472).
Discussion and conclusion: The greater quality can be guaranteed, if we have less errors. The solution lays in knowledge that we have available software in digital control of image quality, because we do not need to calculate any parameter on paper, but Optimage with its statistical methods to calculate and determine whether it exceeded the permitted margin of tolerance. With Optimage we automate quality control procedures, which thus become more predictable and include less chance of error. Therefore, we believe that the Optimage is excellent contribution from the applicational point of view, because medical staff can much easier to work with medical devices, and allows for a constant level of picture quality.