ANALISIS VARIASI WINDOW WIDTH TERHADAP INFORMASI CITRA ANATOMI MSCT STONOGRAFI
Abstract
ABSTRACT
Background : Multi Slice Computed Tomography is a diagnostic imaging method that can display cross section anatomy in the axial, sagital, and coronal areas. MSCT Stonography imaging both visualizes the anatomy of the urinary tract and stone pathology supported by the presence of ureter tracking techniques and without using contrast media. On this method, the appropriate window width will produce an optimal anatomical picture. The Study aims to determine the effect of window width on anatomical image information on MSCT Stonography.
Methods : Type of research is quantitative experimental approach, conducted in January-February 2020 in Hasan Sadikin Bandung hospital, Bandung. Research with variations in window width 300 HU, 350 HU, 400 HU, 450 HU, and 500 HU on MSCT stonography og 10 patients. Criteria’s patients is patients with clinical kidney stones, willing to be a research sample. Result imagery rated two respondents, include parenchymal kidney, pelvic calices kidney, ureters, vesica urinary, and stones kidney. Then do Kappa test continued testing Friedman to know the highest mean rank and the influence og the window width oh the image og MSCT stonography.
Results : Based on the result of the Friedman statistical test overall anatomy obtained significance value (p-value) = 0.000 < 0.05 means that there is an influence of window width value, the contrast resolution will increase and the better the firm boundary, but the resulting image will be more radioluscent. Based on Friedman’s mean rank test result obtained the highest mean rank of 3,54 in a variation of window width 300. The most optical window displays anatomy information using window width 300.
Conclussion : There are difference in anatomical image information of MSCT stonography among 5 variation window width on examination MSCT stonography. Window width 300 HU is better at anatomy information on MSCT stonography to show better contrast, crisp sharpness, no blur image.
