RESUMEN
The incidence and recurrence rates of urinary stone diseases have remained high recently, and stone analysis is of great significance for further understanding of the pathophysiological processes of urinary stones and to develop effective prevention strategies and precise treatment. Imaging evaluation is the main method of preoperative stone analysis, and dual-energy CT has shown its potential in identifying common main components of stones. The emergence of photon counting spectral CT is expected to achieve accurate analysis of stone components at the pixel level. The intraoperative stone analysis mainly relies on the automatic recognition of endoscopic images, and using machine learning algorithms can more reliably predict common stone composition. It is of great significance for stone analysis and assessment of metabolic causes by introducing morpho-constitutional classification (MCC)and observing and describing the papillary renal lesions during operation. This article reviews the progress of preoperative and intraoperative stone analysis, in order to improve clinicians' understanding of the importance of stone analysis, and provide a direction for further clinical research.
RESUMEN
Objective:To compare the consistency of tomographic infrared spectrum analysis with conventional infrared spectrum analysis for the composition analysis of large-volume of urinary stones in vitro.Methods:Postoperative urinary stone specimens collected from 105 patients admitted to Beijing Tsinghua Changgung Hospital from January 2019 to June 2021 were analyzed, including 81 (77.14%) kidney stones, 16 (15.24%) ureteral stones, and 8 (7.62%) bladder stones. All stones measured ≥0.8 cm in maximum diameter on preoperative imaging. Eighty-four specimens, which were mainly stone fragments, were collected from percutaneous nephrolithotomy and ureteroscopic lithotripsy. These 84 specimens were analyzed and retested for stone composition using conventional infrared spectrum analysis by random multiple sampling. Other 21 renal stone specimens were obtained by laparoscopic lithotomy or standard percutaneous nephrolithotomy after November 1, 2020. These 21 specimens had a maximum diameter of ≥0.8 cm measured postoperatively. Based on intraoperative observation, stone specimens with typical layered structures were chosed. Then, all 21 samples were analyzed and retested by conventional infrared spectrum analysis and tomographic infrared spectrum analysis, respectively. When using tomographic infrared spectrum analysis, we need to take two maximum cross sections with a vertical spacing of these sections >2 mm, then perform multiple points sampling according to the morphological stratification of the first section. If the section's structure was homogeneous, we equidistantly took 2 to 3 samples from the center to the periphery. Otherwise, every layer needed to take a stone sample according to the stratification. Putting all the results of one section together, we obtained complete tomographic infrared spectrum analysis data. Take another coaxial cross-section of the same specimen for retesting. We recorded the characteristics of the three-dimensional distribution of stone composition in 21 stone specimens. Meanwhile, we compared the consistency of the results of conventional infrared spectrum analysis and tomographic infrared spectrum analysis for the same sample.Results:The consistency rate of the conventional infrared spectrum analysis was 56.19% (59/105), and that of tomographic infrared spectrum analysis was 80.95% (17/21). The difference in consistency between two methods was statistically significant ( χ2=4.447, P=0.035). Among 21 specimens, the consistency rate of conventional infrared spectrum analysis was 38.10% (8/21), which was significantly lower than that of tomographic infrared spectrum analysis ( χ2=7.814, P=0.005). Regarding the characteristics of the three-dimensional distribution of the components, the color and crystal morphology of five common types of stone components were different, and layered structure in the cross-section of the stones were observed. When the calculi were of the same composition, they were displayed in different morphology. We observed a trending change in the composition ratio between sublayers from the center to the edge in some compound-composition stones. Conclusions:For the composition analysis of larger-volume urinary stones, tomographic infrared spectrum analysis showed a higher consistency of retesting than conventional infrared spectrum analysis, and the three-dimensional distribution of stone composition had some characteristic features.