Objective This study examined the diagnostic performance of the prediction models using baseline characteristics, biochemical indicators, and adenohypophysis MRI features for differentiating idiopathic short stature (ISS) from growth hormone deficiency (GHD). Methods A total of 96 patients with short stature underwent hypophysial CUBE T1-weighted imaging on 3.0-T scanner and GH stimulation testing between February 2021 and February 2024 and were classified into ISS and GHD groups according to GH stimulation testing results. Two-independent-sample T-test was tested for the differences between groups. The partial correlation analysis was conducted after controlling for demographic data. The prediction models were established using stepwise binary logistic regression method. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of the models. Results ISS group (29 boys and 29 girls) and GHD group (21 boys and 17 girls) showed significant differences in pituitary height (aPH) and pituitary volume (aPV), GHmax, LHmax and cortisol but no difference in demographic data (gender, age, height, weight and BMI). After controlling for those demographic data, aPH, aPV, FSHmax and LHmax showed positive correlation with GHmax. Using binary logistic regression, three prediction models were built; Model 1 had the highest AUC value (0.862) followed by Model 3 with AUC value of 0.858 and Model 2 with the lowest AUC value (0.725). Conclusion A useful prediction model using adenohypophysis MRI features, age, and BMI had great potential in differentiation between GHD and ISS. Key Points <Emphasis Type="BoldItalic">Question</Emphasis> Distinguishing growth hormone deficiency (GHD) from idiopathic short stature (ISS) among prepubescent children is important but difficult, time-consuming, and costly with growth hormone stimulation testing. <Emphasis Type="BoldItalic">Findings</Emphasis> The proposed model using clinical and radiomics features offered sufficient diagnostic performance on differentiating GHD and ISS. <Emphasis Type="BoldItalic">Clinical relevance</Emphasis> We propose a low-cost, time-saving, and non-invasive model based on adenohypophysis MRI features and baseline characteristics to differentiate GHD and ISS. Graphical Abstract

Pituitary MRI features in identifying idiopathic short stature from growth hormone deficiency in children with short stature

期刊论文
发表日期：

2025年4月11日

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Longbiao Cai,
Xiongjing Cao,
Jianjian Cai,
Qin Liu,
Yunyun Zhao,
Xianrong Kong,
Guojun Ding,
Tian Tian,
Weiyin Vivian Liu,
Dong Liu

摘要

Objective

This study examined the diagnostic performance of the prediction models using baseline characteristics, biochemical indicators, and adenohypophysis MRI features for differentiating idiopathic short stature (ISS) from growth hormone deficiency (GHD).

Methods

A total of 96 patients with short stature underwent hypophysial CUBE T1-weighted imaging on 3.0-T scanner and GH stimulation testing between February 2021 and February 2024 and were classified into ISS and GHD groups according to GH stimulation testing results. Two-independent-sample T-test was tested for the differences between groups. The partial correlation analysis was conducted after controlling for demographic data. The prediction models were established using stepwise binary logistic regression method. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of the models.

Results

ISS group (29 boys and 29 girls) and GHD group (21 boys and 17 girls) showed significant differences in pituitary height (aPH) and pituitary volume (aPV), GH_max, LH_max and cortisol but no difference in demographic data (gender, age, height, weight and BMI). After controlling for those demographic data, aPH, aPV, FSH_max and LH_max showed positive correlation with GH_max. Using binary logistic regression, three prediction models were built; Model 1 had the highest AUC value (0.862) followed by Model 3 with AUC value of 0.858 and Model 2 with the lowest AUC value (0.725).

Conclusion

A useful prediction model using adenohypophysis MRI features, age, and BMI had great potential in differentiation between GHD and ISS.

Key Points

Question Distinguishing growth hormone deficiency (GHD) from idiopathic short stature (ISS) among prepubescent children is important but difficult, time-consuming, and costly with growth hormone stimulation testing.

Findings The proposed model using clinical and radiomics features offered sufficient diagnostic performance on differentiating GHD and ISS.

Clinical relevance We propose a low-cost, time-saving, and non-invasive model based on adenohypophysis MRI features and baseline characteristics to differentiate GHD and ISS.

Graphical Abstract