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Updated: Jun 26, 2025
Anogenital Distance and Perineal Measurements of the Pelvic Organ Prolapse POP Quantification System
Published on: September 20, 2018
Development and verification of machine learning model based on anogenital distance, penoscrotal distance, and 2D:4D
Zirong He1, Bo Yang1, Yunman Tang1
1Department of Pediatric Surgery of Children's Medical Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Insights
Anogenital distance and penoscrotal distance can help predict midshaft and proximal hypospadias in children. The anogenital distance (AGD2) is recommended as the most reliable indicator for hypospadias classification.
Area of Science:
- Pediatric Urology
- Medical Imaging
- Biostatistics
Background:
- Hypospadias is a congenital condition affecting the urethra's opening.
- Accurate classification of hypospadias is crucial for effective surgical planning and outcomes.
- Prepubertal anthropometric data's utility in predicting hypospadias classification remains an area of investigation.
Purpose of the Study:
- To evaluate the predictive value of commonly used anthropometric indices in classifying hypospadias in prepubertal children.
- To develop and validate machine learning models for predicting hypospadias classification based on these indices.
Main Methods:
- Retrospective and prospective data collection of 389 prepubertal hypospadias cases.
- Measurement of penoscrotal distance, anogenital distance (AGD2), and 2D:4D finger ratio.
- Application of receiver operating characteristic curve analysis, logistic regression, random forest, and support vector machine models.
Main Results:
- Anogenital distance (AGD2) and penoscrotal distance showed predictive value for midshaft and proximal hypospadias.
- The 2D:4D finger ratio demonstrated minimal predictive value for hypospadias classification.
- Machine learning models exhibited varying sensitivity in classifying hypospadias subtypes, with no significant improvement for distal type using three-classification models.
Conclusions:
- Anogenital distance (AGD2) and penoscrotal distance are valuable predictors for midshaft and proximal hypospadias.
- AGD2 is recommended as a preferred indicator due to its test efficiency and stability.
- The 2D:4D finger ratio is not a reliable predictor for hypospadias classification.
Objectives:
To describe the anatomical abnormalities of hypospadias before puberty using current commonly used anthropometric index data and predict postoperative diagnostic classification.
Methods:
Children with hypospadias before puberty who were initially treated at Sichuan Provincial People's Hospital from April 2021 to September 2022 were selected. We recorded their preoperative penoscrotal distance, anogenital distance, 2D:4D finger ratio, and postoperative hypospadias classification. The receiver operating character curve was used for univariate analysis of the diagnostic predictive value of each index for hypospadias classification in the training set. Binary logistic regression, random forest, and support vector machine models were constructed. In addition, we also prospectively collected data from October 2022 to September 2023 as a test set to verify the constructed machine learning models.
Results:
This study included 389 cases, with 50 distal, 167 midshaft, and 172 proximal cases. In the validation set, the sensitivity of the binary LR, RF, and SVM was 17%, 17% and 0% for identifying the distal type, 61%, 55% and 64% for identifying the midshaft type, and 56%, 60% and 48% for identifying the proximal type, respectively. The sensitivity of the three-classification RF and SVM models was 17% and 17% for distal type, 64% and 73% for midshaft type, 60% and 60% for proximal type, respectively. In the Testing set, the sensitivity of the binary LR, RF and SVM was 6%, 0% and 0% for identifying the distal type, 64%, 55% and 66% for identifying the midshaft type, and 48%, 62% and 39% for identifying the proximal type, respectively. The sensitivity of the three-classification RF and SVM models was 12% and 0% for distal type, 57% and 77% for midshaft type, and 65% and 53% for proximal type, respectively. Compared with binary classification models, the sensitivity of the three-classification models for distal type was not improved.
Conclusion:
Anogenital distance and penoscrotal distance have a favorable predictive value for midshaft and proximal hypospadias, among which AGD2, with higher test efficiency and stability, is recommended as the preferred anogenital distance indicator. The 2D:4D finger ratio (RadioL, RadioR) has little predictive value for hypospadias classification.
