RESUMO
PURPOSE: The goal of this study was to examine changes in testicular stiffness at various intervals after the induction of testicular torsion, as well as to assess the predictive value of testicular stiffness for testicular spermatogenesis after torsion. METHODS: Sixty healthy male rabbits were randomly assigned to one of three groups: complete testicular torsion, incomplete testicular torsion, or control. All rabbits underwent preoperative and postoperative scrotal ultrasonography, including shear wave elastography (SWE), at predetermined intervals. Changes in SWE values were analyzed and compared using repeatedmeasures analysis of variance. To assess the diagnostic performance of SWE in determining the degree of spermatogenic function impairment, the areas under the receiver operating characteristic curves (AUCs) were calculated. RESULTS: SWE measurements in both central and peripheral zones of the testicular parenchyma affected by torsion demonstrated significant negative correlations with spermatogenesis, with coefficients of r=-0.759 (P<0.001) and r=-0.696 (P<0.001), respectively. The AUCs of SWE measurements in the central or peripheral zones of the torsed testicular parenchyma were 0.886 (sensitivity, 83.3%; specificity, 100%) and 0.824 (sensitivity, 83.3%; specificity, 73.3%) for distinguishing between hypospermatogenesis and spermatogenic arrest, respectively (P=0.451, DeLong test). CONCLUSION: Variations in the stiffness of both central and peripheral regions of the testicular parenchyma correlate with the extent and duration of torsion, exhibiting a specific pattern. The "stiff ring sign" is the characteristic SWE finding associated with testicular torsion. SWE appears to aid in the non-invasive determination of the extent of spermatogenic damage in torsed testes.
RESUMO
Purpose: To develop and validate a three-dimensional ultrasound (3D US) radiomics nomogram for the preoperative prediction of extrathyroidal extension (ETE) in papillary thyroid cancer (PTC). Methods: This retrospective study included 168 patients with surgically proven PTC (non-ETE, n = 90; ETE, n = 78) who were divided into training (n = 117) and validation (n = 51) cohorts by a random stratified sampling strategy. The regions of interest (ROIs) were obtained manually from 3D US images. A larger number of radiomic features were automatically extracted. Finally, a nomogram was built, incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were performed to validate the capability of the nomogram on both the training and validation sets. The nomogram models were compared with conventional US models. The DeLong test was adopted to compare different ROC curves. Results: The area under the receiver operating characteristic curve (AUC) of the radiologist was 0.67 [95% confidence interval (CI), 0.580-0.757] in the training cohort and 0.62 (95% CI, 0.467-0.746) in the validation cohort. Sixteen features from 3D US images were used to build the radiomics signature. The radiomics nomogram, which incorporated the radiomics signature, tumor location, and tumor size showed good calibration and discrimination in the training cohort (AUC, 0.810; 95% CI, 0.727-0.876) and the validation cohort (AUC, 0.798; 95% CI, 0.662-0.897). The result suggested that the diagnostic efficiency of the 3D US-based radiomics nomogram was better than that of the radiologist and it had a favorable discriminate performance with a higher AUC (DeLong test: p < 0.05). Conclusions: The 3D US-based radiomics signature nomogram, a noninvasive preoperative prediction method that incorporates tumor location and tumor size, presented more advantages over radiologist-reported ETE statuses for PTC.
