METHODOLOGY OF PROCESSING MEDICAL IMAGES WITH ASSESSMENT OF CRYSTALLINITY DEGREE OF RENAL STONES

Introduction. Urolithiasis is one of the most common urological diseases. The modern approach to the treatment of this pathology involves the use of a wide range of minimally invasive surgical interventions, the main stage of which is the destruction of the stone with subsequent removal of its fragments. Preoperative diagnosis of physicochemical parameters of kidney stones is of great practical importance in the aspect of choosing a treatment method, especially in the case of planning extracorporeal shock wave lithotripsy. The aim of the study was to determine the peculiarities of tomographic images of kidney stones with various structural features. Materials and methods. The research consisted in the study of the microstructure of stones removed as a result of minimally invasive surgical interventions (extracorporeal shock wave, percutaneous and ureteroscopic lithotripsy) in 63 patients with urolithiasis, by the method of crystal-optical analysis on a polarizing microscope, with subsequent digital analysis of their tomographic images, according to using the ImageJ software package, with determination of the average pixel intensity (PI) in the gray scale range of 0–250. Results. During the crystal-optical analysis, it was established that regardless of the mineral composition of the stone, the inorganic components that make up its composition can be in an amorphous or crystalline state. The structural types of kidney stones were determined based on the determination of the volume fraction of the crystalline phase (VFCP) in the structure of the urolith. When analyzing tomographic images, it was found that kidney stones belonging to different structural types were characterized by different average pixel intensity (PI). A positive correlation between VFCP and PI was established, as well as reliable differences in the PI indicator between groups of stones of the first and third degree of crystallinity, which allows considering this indicator as a tomographic criterion of the degree of crystallinity of a kidney stone, the determination of which is expedient at the stage of choosing a lithotripsy method. Conclusions. Detection of the structural state of renal stones during tomographic examination could be performed with the methodology of determining the pixel intensity index using ImageJ software. In particular, 3 groups of renal stones can be distinguished according to pixel intensity: grade 1 (84–124), grade 2 (125–165) and grade 3 (166–206). This indicator is determined by the volume ratio of the amorphous and crystalline phases of mineral compounds of kidney stones and should be taken into account when choosing the optimal lithotripsy method.