From subjective to objective: A pilot study on testicular radiomics analysis as a measure of gonadal function

Abstract

Background:The connection between testicular ultrasound (US) parameters and testicular function, including both spermato-and steroidogenesis has been largely suggested, but their predictive properties are not routinely applied. Radiomics, a new engineering approach to radiological imaging, could overcome the visual limit of the sonographer.Objectives: This study is aimed at extracting objective testicular US features, correlating with testicular function, including both spermato-and steroidogenesis, using an engineering approach, in order to overcome the operator-dependent subjectivity. Materials and methods: Prospective observational pilot study from December 2019 to December 2020 on normozoospermic subjects and patients with semen variables alterations, excluding azoospermia. All patients underwent conventional semen analysis, pituitary-gonadal hormones assessment, and testicular US, performed by the same operator. US images were analyzed by Biolab (Turin) throughout image segmentation, image pre-processing, and texture features extraction.Results: One hundred seventy US testicular images were collected from 85 patients (age 38.6 ± 9.1 years). A total of 44 first-order and advanced features were extracted.US inhomogeneity defined by radiomics significantly correlates with the andrologist definition, showing for the first time a mathematical quantification of a subjective US evaluation. Thirteen US texture features correlated with semen parameters, predicting sperm concentration, total sperm number, progressive motility, total motility and morphology, and with gonadotropins serum levels, but not with total testosterone serum levels. Classification analyses confirmed that US textural features predicted patients' classification according to semen parameters alterations. Conclusions:Radiomics texture features qualitatively describe the testicular parenchyma with objective and reliable quantitative parameters, reflecting both the testicular spermatogenic capability and the action of pituitary gonadotropins. This is an innovative model in which US texture features represent a mirror of the pituitary-gonadal homeostasis in terms of reproductive function.

Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics

“…AI applications can be utilized in several important fields [ 4 14 15 19 35 43 54 69 109 128 129 ]. A summary of AI applications in andrology is provided in Table 2 [ 9 43 44 57 61 63 79 82 130 131 132 133 134 135 136 137 138 139 140 141 ].…”

“…The technique allows the evaluation of testicular spermatogenesis and hypothalamic-pituitary axis effects during image segmentation, image preprocessing, and texture features extraction image analysis. Image analyses were performed using Biolab [ 35 ].…”

“…Furthermore, many of these features also had a predictive value on gonadotropin levels but not testosterone levels. The authors of this pilot study suggested the possibility of predicting the gonadal function of patients using a subjective evaluation (testicular echogenicity) and turning it into an objective evaluation based on numerical values [ 35 ]. In contrast, no studies to date have evaluated the use of AI in ultrasound imaging of inflammation of the epididymis and seminal vesicles.…”

Ultrasound-based deep learning radiomics nomogram for risk stratification of testicular masses: a two-center study

“…It utilizes quantitative analysis techniques to extract extensive lesion information from conventional medical images, conducting in-depth exploration and analysis of medical images to reveal hidden, intricate details within the images (Lafata et al 2022 ). Earlier studies have investigated its use in predicting testicular and other urinary system diseases (Santi et al 2022 ; Fan et al 2022 ; Xue et al 2023 ; Baessler et al 2020 ). Lately, deep learning (DL) algorithms have gained widespread recognition and adoption in the field of medical image analysis (Beuque et al 2023 ; Tong et al 2022 ).…”

A survey of testicular texture in canine ultrasound images

“…This type of texture analysis has a long history in image analysis and has been reported for a variety of applications, including medical ultrasound images of breast ( 19 ), liver ( 20 ), and muscle ( 21 ). Variations in GLCM texture features extracted from testicular ultrasound images have been reported to occur in association with abnormal testicular spermatogenic capability and as a result of the action of pituitary gonadotropins in men ( 22 ).…”