Investigation of the predictive value of Hounsfield units in predicting stone culture results in urinary stone disease.

This study aimed to investigate the predictive ability of Hounsfield unit (HU) measurements for microorganism growth observed microbiologically in stone cultures after stone surgery and to create a model by adding other predictive factors for predicting stone culture positivity. Patients who underwent percutaneous nephrolithotomy, retrograde intrarenal surgery, or ureteroscopy and had stone cultures performed were included in the study. Demographic and clinical data, including age, gender, body mass index, stone size, stone volume, hydronephrosis grade, stone location, energy used, presence of preoperative stent or nephrostomy, operation duration, midstream urine culture, renal pelvic urine culture, stone culture results, and postoperative fever and systemic inflammatory response syndrome criteria, were recorded. Non-contrast computed tomography images were used to measure the HU at the stone's core (HU), the proximal surface of the stone periphery in the collecting system (HU), the distal surface of the stone periphery in the collecting system (HU), and the average HU of the stone periphery (HU). Absolute and relative differences between these values were calculated. A total of 383 patients were included, with microorganism growth observed in the stone cultures of 75 patients (19.6%). Radiological cut-off values distinguishing stones with positive cultures included HU < 81.8, HU < 807.0, and HU > 179.5. Factors associated with a statistically significant increase in the likelihood of positive stone cultures included longer operation duration (odds ratio [OR] = 1.102, 95% confidence interval [CI]: 1.053-1.154, p < 0.001), higher preoperative hydronephrosis grade (OR = 1.898, 95% CI: 1.289-2.795, p < 0.001), and the presence of preoperative stents or nephrostomy (OR = 4.232, 95% CI: 1.551-11.543, p = 0.005) in addition to the identified radiological HU cut-off values. HU values, as a radiological parameter, can predict microorganism growth in stone cultures, enabling identification of patients at risk for postoperative infectious complications.