Pelvic ultrasound and pubertal attainment in girls with sexual precocity: the pivotal role of uterine volume in predicting the timing of menarche.

Introduction: Among girls assessed for pubertal precocity, pelvic ultrasound (pUS) may represent a pivotal tool to predict the time expected to elapse between sonographic assessment and the onset of menarche (TUS-M). Accordingly, the present analysis is meant to define the statistical relationship between sonographic parameters and TUS-M, in order to identify the most reliable predictor of the timing of menarche. Methods: Retrospective, multicenter analysis. Girls assessed for sexual precocity and showing sonographic and clinical findings consistent with pubertal onset upon referral were considered eligible. Patients treated with GnRH analogues were excluded and only those who had subsequently achieved complete and spontaneous pubertal attainment and for whom the exact date of menarche was available were included. Overall, we enrolled 184 girls from five tertiary care Italian Centers. Results: The time elapsed (months) between baseline endocrine assessment and spontaneous achievement of menarche showed a negative statistically significant correlation (p<0.0001) with LH (r:-0.61), FSH (r:-0.59), estradiol (r:-0.52) and stimulated LH values (r:-0.58). Among pUS parameters, ovarian volume (r:-0.17 left, -0.30 right) and uterine body-to-cervix ratio (r:-0.18) poorly correlated with TUS-M, while uterine diameters (r:-0.61 longitudinal, -0.64 anteroposterior) and volume (r:-0.70) achieved a highly statistical significance (p<0.0001). Uterine volume (UV) showed a negative logarithmic relationship with TUS-M and represented the most reliable predictor of the timing of menarche in uni- and multivariable analyses (p <0.001). ROC analyses identified the UV thresholds that best predict the onset of menarche within 18, 12 and 6 months, respectively: 3.76, 6.02 and 8.80 ml. Conclusion: The logarithm of UV shows the best statistical performance in predicting the timing of menarche in girls assessed for pubertal precocity. Accordingly, we developed a user-friendly online application that provides clinicians with an estimation of the months expected to elapse before menarche, based on the UV recorded upon pUS.

Evaluating breast ultrasonography as a complementary diagnostic method in girls with central precocious puberty.

BACKGROUND: Assessment of breast development by physical examination can be difficult in the early stages and in overweight girls. OBJECTIVE: To investigate ultrasonography (US) for evaluation of early breast development. MATERIALS AND METHODS: In a prospective study, 125 girls (age 7.1 ± 1.5 years) with breast development before 8 years underwent US breast staging, breast volume, and elastography, in addition to clinical/hormonal evaluation for precocious puberty. Accuracy of US for determining breast development and predicting progression to central precocious puberty was investigated. RESULTS: Physical examination revealed glandular breast enlargement in 100 and predominantly lipomastia in 25. Breast US in the former confirmed glandular breast development in 92 (group 1, physical examination and US positive), but not in 8 (group 2, physical examination positive, US negative). Comparison of the two groups demonstrated lower Tanner and US staging, bone age/chronological age, basal luteinizing hormone (LH), breast volume, and uterine volume in group 2. In the 25 lipomastia patients, US demonstrated no breast tissue in 19 (group 3, physical examination and US negative), but US stage ≥ II in 6 (group 4, physical examination negative, US positive) without differences in clinical parameters. After follow-up of 19.8 ± 4.2 months, 46/125 subjects were diagnosed with precocious puberty. US stage, total breast volume, and shear-wave speeds were significantly higher in these 46 patients. Multivariate analyses demonstrated breast volume > 3.4 cc had odds ratio of 11.0, sensitivity of 62%, and specificity of 89, in predicting progression to precocious puberty, being second only to stimulated LH for all variables. CONCLUSION: Breast US is a useful predictive tool for diagnosis of precocious puberty in girls. Higher US stages and higher breast volume on US increased the likelihood of eventual diagnosis of precocious puberty.

Meta-analysis of machine learning models for the diagnosis of central precocious puberty based on clinical, hormonal (laboratory) and imaging data.

Background: Central precocious puberty (CPP) is a common endocrine disorder in children, and its diagnosis primarily relies on the gonadotropin-releasing hormone (GnRH) stimulation test, which is expensive and time-consuming. With the widespread application of artificial intelligence in medicine, some studies have utilized clinical, hormonal (laboratory) and imaging data-based machine learning (ML) models to identify CPP. However, the results of these studies varied widely and were challenging to directly compare, mainly due to diverse ML methods. Therefore, the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for CPP remains elusive. The aim of this study was to investigate the diagnostic value of ML models based on clinical, hormonal (laboratory) and imaging data for CPP through a meta-analysis of existing studies. Methods: We conducted a comprehensive search for relevant English articles on clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP, covering the period from the database creation date to December 2023. Pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve, and area under the curve (AUC) were calculated to assess the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP. The I2 test was employed to evaluate heterogeneity, and the source of heterogeneity was investigated through meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. Results: Six studies met the eligibility criteria. The pooled sensitivity and specificity were 0.82 (95% confidence interval (CI) 0.62-0.93) and 0.85 (95% CI 0.80-0.90), respectively. The LR+ was 6.00, and the LR- was 0.21, indicating that clinical, hormonal (laboratory) and imaging data-based ML models exhibited an excellent ability to confirm or exclude CPP. Additionally, the SROC curve showed that the AUC of the clinical, hormonal (laboratory) and imaging data-based ML models in the diagnosis of CPP was 0.90 (95% CI 0.87-0.92), demonstrating good diagnostic value for CPP. Conclusion: Based on the outcomes of our meta-analysis, clinical and imaging data-based ML models are excellent diagnostic tools with high sensitivity, specificity, and AUC in the diagnosis of CPP. Despite the geographical limitations of the study findings, future research endeavors will strive to address these issues to enhance their applicability and reliability, providing more precise guidance for the differentiation and treatment of CPP.

Early breast development in girls: the power of greyscale sonography and sonoelastography.

OBJECTIVE: Accurate distinction between central pubertal precociousness (PP) and premature thelarche (PT) is important to guide treatment. Both greyscale ultrasonography (US) and sonoelastography can be used to examine breast tissue. The aim of this study is to investigate the performance of breast US and strain elastographic (SE) in the diagnosis of increased breast volume in girls. METHODS: Sixty-three girls with breast development up to 8 years of age and diagnosed with PP and PT were included in the prospective study. Basal luteinizing hormone (LH), follicle-stimulating hormone (FSH), and estradiol (E2) values were obtained. Each bud was considered as a unit in US. Mediolateral (ML) and anteroposterior diameters (AP) were measured, and US grading was performed. Breast SE was examined, and strain index (SI) was calculated. US and laboratory findings were compared. RESULTS: Of the 121 buds examined, 39 (32.2%) were with PP (6.97 ± 2.44 years) and 82 (67.8%) were with PT (6.51 ± 2.52 years). Diameters were correlated with bone age, LH, FSH, and US grade. The mean AP showed a moderate difference in favour of PP between the groups (P < .06). The mean ML was higher in PP (P < .01). There was a difference in mean SI values (P < .004). Sensitivity and specificity were 71% and 61% for ML and 72% and 56% for SI, respectively. CONCLUSION: Both ML and US grading may help discriminate PP from PT. The role of sonoelastography requires further investigation. ADVANCES IN KNOWLEDGE: Ultrasound and SE show significant differences between PP and PT, but these are not sufficiently reliable to be of clinical use. The contribution of sonoelastography requires further study before it can be recommended. However, SI of breast tissue can be helpful in distinguishing PP and PT from other causes of early increase in breast volume.

Diagnostic value of adenohypophyseal MRI features in female children with precocious puberty.

AIM: To evaluate the diagnostic value of adenohypophyseal magnetic resonance imaging (MRI) features for precocious puberty (PP) in female children and also to establish a non-invasive diagnostic approach in clinics. MATERIALS AND METHODS: A total of 126 female children (37, 57, and 32 female children clinically diagnosed with central PP [CPP], incomplete PP [IPP], and controls, respectively) were enrolled in this study. Data were collected and analysed using analysis of variance. Pearson correlation and stepwise multivariate linear regression analysis were used to examine the association and build prediction models. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficacy. RESULTS: The values of adenohypophysis volume (aPV), adenohypophysis height (aPH), and signal-intensity ratio (SIR), height, weight, and seven laboratory testing characteristics were correlated closely with the activation status of the hypothalamic-pituitary-gonad axis in the different groups (all p<0.05). Model 1 including aPV, weight, and aPH and Model 2 including SIR, aPV, and height were built to obtain predicted luteinising hormone (LH; R2 = 0.271) and LH/follicle stimulating hormone (FSH; R2 = 0.311). ROC analysis showed the predicted LH, predicted LH/FSH, and aPV were the top 3 best predictors in distinguishing CPP from controls (AUC = 0.969, 0.949, and 0.938) while predicted LH/FSH was the best predictor in distinguishing CPP from IPP and controls (AUC = 0.829 and 0.828). CONCLUSION: The adenohypophysis volume itself and the prediction models including main adenohypophyseal MRI features increased diagnostic efficiency for PP and offered a non-invasive and credible diagnostic method.

Correlation of pelvic ultrasonography with pubertal development in girls

Abstract Objectives: This study aims to correlate pelvic ultrasound with female puberty and evaluate the usual ultrasound parameters as diagnostic tests for the onset of puberty and, in particular, a less studied parameter: the Doppler evaluation of the uterine arteries. Methods: Cross-sectional study with girls aged from one to less than eighteen years old, with normal pubertal development, who underwent pelvic ultrasound examination from November 2020 to December 2021. The presence of thelarche was the clinical criterion to distinguish pubescent from non-pubescent girls. The sonographic parameters were evaluated using the ROC curve and the cutoff point defined through the Youden index (J). Results: 60 girls were included in the study. Uterine volume ≥ 2.45mL had a sensitivity of 93%, specificity of 90%, PPV of 90%, NPV of 93% and accuracy of 91% (AUC 0.972) for predicting the onset of puberty. Mean ovarian volume ≥ 1.48mL had a sensitivity of 96%, specificity of 90%, PPV of 90%, NPV of 97% and accuracy of 93% (AUC 0.966). Mean PI ≤ 2.75 had 100% sensitivity, 48% specificity, 62% PPV, 100% NPV and 72% accuracy (AUC 0.756) for predicting the onset of puberty. Conclusion: Pelvic ultrasound proved to be an excellent tool for female pubertal assessment and uterine and ovarian volume, the best ultrasound parameters for detecting the onset of puberty. The PI of the uterine arteries, in this study, although useful in the pubertal evaluation, showed lower accuracy in relation to the uterine and ovarian volume.

Basal gonadotropin levels combine with pelvic ultrasound and pituitary volume: a machine learning diagnostic model of idiopathic central precocious puberty.

OBJECTIVE: The current diagnosis of central precocious puberty (CPP) relies on the gonadotropin-releasing hormone analogue (GnRHa) stimulation test, which requires multiple invasive blood sampling procedures. The aim of this study was to construct machine learning models incorporating basal pubertal hormone levels, pituitary magnetic resonance imaging (MRI), and pelvic ultrasound parameters to predict the response of precocious girls to GnRHa stimulation test. METHODS: This retrospective study included 455 girls diagnosed with precocious puberty who underwent transabdominal pelvic ultrasound, brain MRI examinations and GnRHa stimulation testing were retrospectively reviewed. They were randomly assigned to the training or internal validation set in an 8:2 ratio. Four machine learning classifiers were developed to identify girls with CPP, including logistic regression, random forest, light gradient boosting (LightGBM), and eXtreme gradient boosting (XGBoost). The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, area under receiver operating characteristic (AUC) and F1 score of the models were measured. RESULTS: The participates were divided into an idiopathic CPP group (n = 263) and a non-CPP group (n = 192). All machine learning classifiers used achieved good performance in distinguishing CPP group and non-CPP group, with the area under the curve (AUC) ranging from 0.72 to 0.81 in validation set. XGBoost had the highest diagnostic efficacy, with sensitivity of 0.81, specificity of 0.72, and F1 score of 0.80. Basal pubertal hormone levels (including luteinizing hormone, follicle-stimulating hormone, and estradiol), averaged ovarian volume, and several uterine parameters were predictors in the model. CONCLUSION: The machine learning prediction model we developed has good efficacy for predicting response to GnRHa stimulation tests which could help in the diagnosis of CPP.

Evaluation of visceral adipose tissue thickness in precocious puberty.

OBJECTIVE: Although there is a relationship between earlier onset of puberty and increased adiposity tissue. Publications in the literature on adiposis in patients with central precocious puberty (CPP) and visceral fat thickness (VFT) have conflicting results. So, in this study, we aimed to evaluate the relationship between sexual maturation and obesity in the development of early puberty and to examine their relationship with pelvic sonographic parameters. PATIENTS AND METHODS: A total of 126 girls [patients - premature thelarche (PT) and CPP - and controls] were included in this study. Anthropometric and ultrasonographic evaluations were made by the same pediatric endocrinologist and pediatric radiologist, respectively. Pubertal stages were made according to the Tanner stages. Height, weight, and body mass index were measured as anthropometric measurements, and visceral, subcutaneous, and transabdominal fat thicknesses were measured in sonographic evaluation. RESULTS: The study population was divided into three groups: 44 healthy subjects to Group 1, 23 patients with PT to Group 2, and 59 patients with CPP to Group 3. When we evaluated the anthropometric and ultrasonographic parameters according to pubertal status, significant differences, especially between Group 1 and Group 3, were observed in all data. In the multiple logistic regression analysis, the endometrial thickness (OR = 7.521, p < 0.001) and VFT (OR = 1.530, p < 0.001) were found to be independent predictors of precocious puberty. CONCLUSIONS: It has been found that VFT and endometrial thickness measurements, which are evaluated quickly and accurately by USG, are important predictors of prepubertal precociousness.

Value of pelvic ultrasound combined with pituitary MRI in diagnosis of central precocious puberty in girls.

OBJECTIVE: This study aimed to investigate the value of pelvic ultrasound combined with pituitary magnetic resonance imaging (MRI) based on an artificial intelligence algorithm in the diagnosis of girls with central precocious puberty (CPP), providing reference for the prevention and control of CPP in girls. PATIENTS AND METHODS: 75 girls with CPP and 75 normal girls in Nantong First People's Hospital were studied. Pelvic ultrasound parameters were compared between the two groups based on an artificial intelligence algorithm. Pituitary MRI parameters were analyzed, and pituitary function parameters were explored. RESULTS: The results showed that the diagnostic sensitivity, specificity, and accuracy of the convolutional neural network (CNN) algorithm were 72.3%, 74.6%, and 78.3%, respectively. The sensitivity, specificity, and accuracy of CNN algorithm were significantly higher (p<0.05). The long diameter, anteroposterior diameter, and transverse diameter of the uterus in the precocious puberty (PP) group were significantly larger than those in the normal group (NG). The ovarian long diameter, ovarian anteroposterior diameter, and ovarian transverse diameter in PP group were significantly larger than those in NG. Uterine volume and ovarian volume in PP group were clearly higher than those in NG. The largest follicle diameter was clearly larger in PP patients than in NG patients. The coronal height, coronal width, sagittal height, and sagittal anteroposterior diameter of PP group were clearly higher than those of NG (p<0.05). The sagittal cross-sectional area of pituitary MRI morphology in PP group was significantly greater than that in NG. The pituitary MRI morphology pituitary volume was 272.68 mm in PP group and 191.37 mm in NG, and the pituitary volume was clearly larger in PP group than in NG. The pituitary function parameters estradiol (E2), luteinizing hormone (LH) peak, follicle-stimulating hormone (FSH) peak, and LH peak/FSH peak were greater in PP group than in NG. CONCLUSIONS: In summary, the uterine size and ovarian size of girls and the pituitary function index in PP group were larger. Pelvic ultrasound and pituitary MRI indexes can better diagnose CPP and can be widely used in clinical practice with positive diagnostic value.

Apparent diffusion coefficient (ADC) measurements and morphometric evaluation of the cranium in age-matched children with central precocious puberty.

OBJECTIVES: Central precocious puberty (CPP) is one of the common reasons for referral to pediatric endocrinology. Magnetic resonance imaging (MRI) is used to rule out intracranial pathologies. However, there is insufficient information in the literature about bone marrow abnormalities on MRI in CPP cases. The aim of this study was to evaluate the apparent diffusion coefficient (ADC) values obtained from bone marrow diffusion weight images (DWI) of cranial bone structures and the status of sphenooccipital synchondrosis (SOS) in CPP. METHODS: MRI data from 6-to 9-year-old girls with CPP and a healthy control group were evaluated. Anthropometric data, FSH, LH, and oestradiol tests were recorded, and the relationship between SOS status, DWI-ADC values of the clivus, parietal bone, and occipital protuberance were compared. RESULTS: The study included 146 girls, 79 CPP, and 67 healthy aged 6-9 years (median: 8 (2)). The diagnosis age was 8.30 ± 0.8 years. The ADC values were significantly lower on CPP than normal controls (p=<0.05). In the CPP group, pattern 1 was found at 2 % (n=2), pattern 2 at 3.5 % (n=3), and pattern 3 at 3.5 % (n=3) in clivus sphenooccipital synchondrosis. There was no correlation between the mean parietal, occipital, and clivus ADC values and any variable (p>0.05). CONCLUSIONS: DWI-MRI ADC analysis can be used as a quantitative radiological marker for early detection of CPP, even before changes in sphenooccipital synchondrosis.

Development and Validation of a Combined MRI Radiomics, Imaging and Clinical Parameter-Based Machine Learning Model for Identifying Idiopathic Central Precocious Puberty in Girls.

BACKGROUND: Idiopathic central precocious puberty (ICPP) impairs child development, without early intervention. The current reference standard, the gonadotropin-releasing hormone stimulation test, is invasive which may hinder diagnosis and intervention. PURPOSE: To develop a model for accurate diagnosis of ICPP, by integrating pituitary MRI, carpal bone age, gonadal ultrasound, and basic clinical data. STUDY TYPE: Retrospective. POPULATION: A total of 492 girls with PP (185 with ICPP and 307 peripheral precocious puberty [PPP]) were randomly divided by reference standard into training (75%) and internal validation (25%) data. Fifty-one subjects (16 with ICPP, 35 with PPP) provided by another hospital as external validation. FIELD STRENGTH/SEQUENCE: T1-weighted (spin echo [SE], fast SE, cube) and T2-weighted (fast SE-fat suppression) imaging at 3.0 T or 1.5 T. ASSESSMENT: Radiomics features were extracted from pituitary MRI after manual segmentation. Carpal bone age, ovarian, follicle and uterine volumes and endometrium presence were assessed from radiographs and gonadal ultrasound. Four machine learning methods were developed: a pituitary MRI radiomics model, an integrated image model (with pituitary MRI, gonadal ultrasound and bone age), a basic clinical model (with age and sex hormone data), and an integrated multimodal model combining all features. STATISTICAL TESTS: Intraclass correlation coefficients were used to assess consistency of segmentation. Receiver operating characteristic (ROC) curves and the Delong tests were used to assess and compare the diagnostic performance of models. P < 0.05 was considered statistically significant. RESULTS: The area under of the ROC curve (AUC) of the pituitary MRI radiomics model, integrated image model, basic clinical model, and integrated multimodal model in the training data was 0.668, 0.809, 0.792, and 0.860. The integrated multimodal model had higher diagnostic efficacy (AUC of 0.862 and 0.866 for internal and external validation). CONCLUSION: The integrated multimodal model may have potential as an alternative clinical approach to diagnose ICPP. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Frequency-dependent alterations in regional homogeneity associated with puberty hormones in girls with central precocious puberty: A resting-state fMRI study.

OBJECTIVE: Central precocious puberty (CPP) patients are at significantly higher risk of emotional, mental, and behavioral disorders than those normal pubertal population. However, to date, the definite mechanism of how puberty hormones affect patients with CPP remains unclear. This regional homogeneity (ReHo) study aimed to explore the impact of premature hypothalamus-pituitary-gonadal (HPG) axis activation on brain function alteration in girls with CPP, meanwhile, to explore the relationship between gonadotropin and gonadal hormones levels, abnormal brain activity and cognitive function. METHODS: In this prospective study, a total of 85 girls who were suspected of having CPP were enrolled from the Child Healthcare Department of the Second Affiliated Hospital of Wenzhou Medical University Hospital from June 2018 to May 2021, including 41 CPP girls and 44 non-CPP girls. All participants collected the 0, 30, 60 min blood luteinizing hormone (LH), follicle-stimulating hormone (FSH), 0, 30 min estradiol (E2) and baseline cortisol (COR) and prolactin (PRL) concentrations after gonadotrophin-releasing hormone (GnRH) stimulating test. Resting-state magnetic resonance imaging (rs-MRI) scans were performed for all participants at 2 weeks before the GnRH stimulating test, voxel-wise ReHo was calculated in the standard frequency band (0.01-0.10 Hz), and in slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz). Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV) was also collected. Independent-sample t-test or Mann-Whitney U test was used to compare the differences between two groups. The correlation analysis among abnormal brain regions, serum hormone levels and WISC-IV scores were performed by Spearman or partial correlation analysis. RESULTS: Compared to the non-CPP group, the CPP group showed higher regional homogeneity (ReHo) values in the left inferior temporal gyrus (ITG.L), as well as lower ReHo values in left superior temporal gyrus (STG.L), left superior occipital gyrus (SOG.L) and the right middle gyrus (MTG.R) in slow4.in slow5 frequency band, CPP group demonstrated decreased ReHo values in bilateral orbital part of superior frontal gyrus and medial superior frontal gyrus. LIMITATION: Due to the cross-section design of this study, further research is needed to explore the relationships between age, premature activation HPG axis and brain function changes. CONCLUSION: Our findings demonstrate that premature HPG axis activation and alterations in puberty hormones, may lead to changes in brain activity and cognitive function. This rs-fMRI study may enhance our understanding of the neuroendocrine mechanisms of mood, behavior, and cognitive function alterations in patients with CPP.

Precocious puberty related to Leydig cell testicular tumor: the diagnostic imaging keys.

BACKGROUND: We report the challenging case of a 6-year-old boy with precocious puberty related to histologically proven Leydig cell tumor. CASE PRESENTATION: Multiparametric ultrasound and magnetic resonance imaging (MRI) was performed. Interesting findings were scarcely or never reported in children and differed from adults Leydig cell tumors s such as the hyperechogenic halo surrounding the lesion and the dominant central vascularization using ultrasensitive Doppler. MRI revealed an enlarged testicle with strong enhancement of a tumor, a tumor apparent diffusion coefficient (ADC) of 600 × 10-3 mm2/s and a lower ADC value of the non-tumor parenchyma compared to the contralateral testis (ADC = 800 × 10-3 mm2/s vs 1100 × 10-3 mm2/s), attributed to the spermatogenesis induced by hormonal impregnation. CONCLUSION: We illustrate multiparametric US and MRI findings of a pediatric Leydig cell tumor, including the imaging changes attributed to local hormone secretion, which may be helpful in similar cases.

Accuracy and self-validation of automated bone age determination.

The BoneXpert method for automated determination of bone age from hand X-rays was introduced in 2009 and is currently running in over 200 hospitals. The aim of this work is to present version 3 of the method and validate its accuracy and self-validation mechanism that automatically rejects an image if it is at risk of being analysed incorrectly. The training set included 14,036 images from the 2017 Radiological Society of North America (RSNA) Bone Age Challenge, 1642 images of normal Dutch and Californian children, and 8250 images from Tübingen from patients with Short Stature, Congenital Adrenal Hyperplasia and Precocious Puberty. The study resulted in a cross-validated root mean square (RMS) error in the Tübingen images of 0.62 y, compared to 0.72 y in the previous version. The RMS error on the RSNA test set of 200 images was 0.45 y relative to the average of six manual ratings. The self-validation mechanism rejected 0.4% of the RSNA images. 121 outliers among the self-validated images of the Tübingen study were rerated, resulting in 6 cases where BoneXpert deviated more than 1.5 years from the average of the three re-ratings, compared to 72 such cases for the original manual ratings. The accuracy of BoneXpert is clearly better than the accuracy of a single manual rating. The self-validation mechanism rejected very few images, typically with abnormal anatomy, and among the accepted images, there were 12 times fewer severe bone age errors than in manual ratings, suggesting that BoneXpert could be safer than manual rating.

Ultrasonic evaluation of thelarche grading in 2-8-year-old obese girls suspected of precocious pubert.

INTRODUCTION: The prevalence of obesity in children is increasing. In obese children, clinical examination alone is not sufficient to differentiate lipomastia from thelarche. The aim of this study was to investigate the frequency of true thelarche in obese girls suspected of precocious puberty. MATERIAL AND METHODS: In a cross-sectional study, 100 obese girls between the ages of 2 and 8 years were screened. Maturity stages were determined based on the Tanner scale in the questionnaire. Breast ultrasound was performed for all cases. Other uterine and ovarian laboratory tests, including blood tests to determine plasma levels of LH, FSH, oestradiol, and bone age, were also performed. RESULTS: In ultrasonography examination of 80 children (80%), one breast was pubertal and in 72 people both breasts were pubertal in which ultrasonography of 78 children showed puberty of right breast and 74 children showed puberty of left breast. Twenty children showed bilateral lipomastia. In clinical examination, breasts of 18.9% children seemed lipoid, 35.8% children were seriously suspicious, and 45.3% children seemed pubescent. In pelvic ultrasound, the relationship between ovarian volume and breast ultrasound grade was significant, but uterine volume was not significantly related to breast ultrasound grade. Also, uterine volume with age at ultrasonography, bone age, birth height, left ovarian volume, right ovarian volume, right breast bud diameter, and left breast bud diameter were correlated. CONCLUSIONS: Ultrasound can help obese or overweight children to differentiate between true thelarche and lipomastia. The study also found that most suspected children had true thelarche.

Explainable Dynamic Multimodal Variational Autoencoder for the Prediction of Patients With Suspected Central Precocious Puberty.

Central precocious puberty (CPP) is the most common type of precocious puberty and has a significant effect on children. A gonadotropin-releasing hormone (GnRH)-stimulation test is the gold standard for confirming CPP. This test, however, is costly and unpleasant for patients. Therefore, it is critical to developing alternative methods for CPP diagnosis in order to alleviate patient suffering. This study aims to develop an artificial intelligence (AI) diagnostic system for predicting response to the GnRH-stimulation test using data from laboratory tests, electronic health records (EHRs), and pelvic ultrasonography and left-hand radiography reports. The challenges are in integrating these multimodal features into a comprehensive deep learning model in order to achieve an accurate diagnosis while also accounting for the missing or incomplete modalities. To begin, we developed a dynamic multimodal variational autoencoder (DMVAE) that can exploit intrinsic correlations between different modalities to impute features for missing modalities. Next, we combined features from all modalities to predict the outcome of a CPP diagnosis. The experimental results (AUROC 0.9086) demonstrate that our DMVAE model is superior to standard methods. Additionally, we showed that by setting appropriate operating thresholds, clinicians could diagnose about two-thirds of patients with confidence (1.0 specificity). Only about one-third of patients require confirmation of their diagnoses using GnRH (or GnRH analog)-stimulation tests. To interpret the results, we implemented an explainer Shapley additive explanation (SHAP) to analyze the local and global feature attributions.

Dedicated sellar magnetic resonance imaging protocols without contrast enhancement in girls with central precocious puberty: prevalence of pathologic lesions and clinical correlation

ABSTRACT Objective: Contrast-enhanced brain magnetic resonance imaging (MRI) is routinely performed in children with central precocious puberty (CPP). We evaluated the value of a dedicated sellar MRI protocol without contrast enhancement in girls with CPP. Subjects and methods: This study included 261 girls diagnosed with CPP. We performed sellar MRI scanning without gadolinium enhancement of the hypothalamic-pituitary area (HPA) at the pituitary level, including additional T2-weighted imaging of whole-brain scans to check for other lesions. We evaluated the prevalence of intracranial lesions via this MR protocol. In addition,the correlation between the clinical parameters and morphology of the pituitary gland on the images was assessed. Results: Intracranial lesions were detected in 17 (6.5%) of the 261 girls. Of the 17 girls with abnormalities, 16 (94.1%) had findings in brain areas other than the HPA. The weight, height, Tanner stage of patients were significantly (p < 0.05) higher in the group with greater pituitary height. Patient weight and height, Tanner stage of breast development, and luteinizing hormone (LH) levels were significantly (p < 0.05) greater in those with a higher pituitary grade as determined on sellar MRI. Conclusion: A dedicated unenhanced sellar MRI protocol provides valuable information on brain lesions and pituitary morphology. We found a significantly low prevalence of brain lesions among girls with CPP. Analysis of the height or shape of the pituitary gland on sellar MRI revealed significant correlations with the weight, height, Tanner stage, and LH levels of the patients.

The role of pelvic ultrasound for the diagnosis and management of central precocious puberty: An update.

Sexual precocity refers to the appearance of physical and hormonal signs of pubertal development at an earlier age. It may be considered as the expression of secondary sexual characteristics prior to the pubertal age In central precocious puberty (CPP), which is gonadotropin-dependent, early maturation of the entire hypothalamic-pituitary-gonadal (HPG) axis occurs, with the full spectrum of physical and hormonal changes of puberty. True precocious puberty in girls must also be distinguished from premature thelarche (PT), usually with breast development before the age of 3 years, and premature pubarche (PA), with the isolated development of pubic hair. These conditions are not usually associated with accelerated growth rate or advancement in bone age. Clinical, laboratory and instrumental evaluations are necessary for the diagnosis. Pelvic ultrasound could serve as a complementary tool for the diagnosis, treatment and follow-up of CPP. The interpretation of clinical, laboratory and strumental data must be performed by an expert pediatric endocrinologist to maximize the diagnostic value in females with pubertal disorders.

Dedicated sellar magnetic resonance imaging protocols without contrast enhancement in girls with central precocious puberty: prevalence of pathologic lesions and clinical correlation.

OBJECTIVE: Contrast-enhanced brain magnetic resonance imaging (MRI) is routinely performed in children with central precocious puberty (CPP). We evaluated the value of a dedicated sellar MRI protocol without contrast enhancement in girls with CPP. METHODS: This study included 261 girls diagnosed with CPP. We performed sellar MRI scanning without gadolinium enhancement of the hypothalamic-pituitary area (HPA) at the pituitary level, including additional T2-weighted imaging of whole-brain scans to check for other lesions. We evaluated the prevalence of intracranial lesions via this MR protocol. In addition,the correlation between the clinical parameters and morphology of the pituitary gland on the images was assessed. RESULTS: Intracranial lesions were detected in 17 (6.5%) of the 261 girls. Of the 17 girls with abnormalities, 16 (94.1%) had findings in brain areas other than the HPA. The weight, height, Tanner stage of patients were significantly (p < 0.05) higher in the group with greater pituitary height. Patient weight and height, Tanner stage of breast development, and luteinizing hormone (LH) levels were significantly (p < 0.05) greater in those with a higher pituitary grade as determined on sellar MRI. CONCLUSION: A dedicated unenhanced sellar MRI protocol provides valuable information on brain lesions and pituitary morphology. We found a significantly low prevalence of brain lesions among girls with CPP. Analysis of the height or shape of the pituitary gland on sellar MRI revealed significant correlations with the weight, height, Tanner stage, and LH levels of the patients.