Testicular quantitative ultrasound: A noninvasive monitoring method for evaluating spermatogenic function in busulfan-induced testicular injury mouse models

Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound

ABSTRACT

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.

Modeling methods for busulfan-induced oligospermia and asthenozoospermia in mice: a systematic review and meta-analysis

OBJECTIVE

Modeling methods for busulfan-induced oligoasthenozoospermia are controversial. We aimed to systematically review the modeling method of busulfan-induced oligospermia and asthenozoospermia, and analyze changes in various evaluation indicators at different busulfan doses over time.

METHODS

We searched the Cochrane Library, PubMed databases, Web of Science, the Chinese National Knowledge Infrastructure, and the Chinese Biomedical Literature Service System until April 9, 2022. Animal experiments of busulfan-induced spermatogenesis dysfunction were included and screened. The model mortality and parameters of the evaluation indicators were subjected to meta-analysis.

RESULTS

Twenty-nine animal studies were included (control/model: 669/1829). The mortality of mice increased with busulfan dose. Significant spermatogenesis impairment occurred within 5 weeks, regardless of busulfan dose (10-40 mg/kg). Testicular weight (weighted mean difference [WMD]: - 0.04, 95% CI: - 0.05, - 0.03), testicular index (WMD: - 2.10, 95% CI: - 2.43, - 1.76), and Johnsen score (WMD: - 4.67, 95% CI: - 5.99, - 3.35) were significantly decreased. The pooled sperm counts of the model group were reduced by 32.8 × 106/ml (WMD: - 32.8, 95% CI: - 44.34, - 21.28), and sperm motility decreased by 37% (WMD: - 0.37, 95% CI: - 0.47, - 0.27). Sperm counts decreased slightly (WMD: - 3.03, 95% CI: - 3.42, - 2.64) in an intratesticular injection of low-dose busulfan (4 - 6 mg/kg), and the model almost returned to normal after one seminiferous cycle.

CONCLUSION

The model using low-dose busulfan (10 - 20 mg/kg) returned to normal after 10 - 15 weeks. However, in some spermatogenesis cycles, testicular weight reduction and testicular spermatogenic function damage were not proportional to busulfan dose. Sperm counts and motility results in different studies had significant heterogeneity. Standard protocols for sperm assessment in animal models were needed to reduce heterogeneity between studies.