Quantitative Ultrasound Biomarkers of Testicular Spermatogenic Function

IntroductionNon-obstructive azoospermia (NOA) represents the most severe form of male infertility. Current clinical tools have limited ability to predict sperm production or guide surgical sperm retrieval. Conventional B-mode ultrasound provides qualitative grayscale images and cannot characterize testicular microstructure relevant to spermatogenesis. Quantitative ultrasound (QUS) provides objective parameters from raw radiofrequency data, which quantitatively measure tissue heterogeneity. We hypothesize that men with spermatogenesis will have different QUS features compared to men without spermatogenesis (measured by total motile count, TMC, on semen analysis), with the goal of identifying imaging biomarkers for prognosis and intraoperative guidance. MethodsWe prospectively analyzed men presenting for infertility evaluation who underwent high-frequency ultrasound imaging and semen analysis. Imaging was performed using a 36-MHz transducer with fixed acquisition parameters. Ninety-two QUS features were extracted from manually annotated testicular regions of interest, including Nakagami distribution parameters (m, {omega}, k), envelope statistics, and texture features. Univariate associations between each QUS feature and TMC were assessed using Spearman correlation with Bonferroni correction. Top-performing features were evaluated using logistic regression and receiver operating characteristic (ROC) analysis to discriminate sperm presence or absence (TMC>0 vs TMC=0). ResultsThirty-seven men (18 azoospermic, 19 with sperm present in the ejaculate) contributed 135 regions of interest. Seventeen of 92 QUS features significantly correlated with TMC after correction. The coefficient of variation of the Nakagami k-factor within the superficial testicular parenchyma (K_Zone1_Cv) demonstrated the strongest correlation ({rho}=0.51, corrected p<0.001), suggesting that greater spatial heterogeneity in the superficial parenchyma was associated with higher sperm counts. K_Zone1_Cv discriminated sperm presence with an AUC of 0.77 (95% CI 0.60-0.92), sensitivity 73.7%, and specificity 83.3%. QUS features with the highest univariate association were highly intercorrelated, suggesting a shared biological signal. ConclusionQuantitative ultrasound-derived measures of testicular microstructure heterogeneity correlate with sperm production and demonstrate moderate discrimination of sperm presence. These findings suggest QUS may provide a non-invasive imaging biomarker of spermatogenesis. Study findings warrant further assessment and validation in male infertility for sperm retrieval prognosis and the potential for intra-operative surgical guidance.