Cai Longbiao, Cao Xiongjing, Cai Jianjian, Liu Qin, Zhao Yunyun, Kong Xianrong, Ding Guojun, Tian Tian, Liu Weiyin Vivian, Liu Dong
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Nosocomial Infection Management, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Eur Radiol. 2025 Apr 11. doi: 10.1007/s00330-025-11556-7.
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).
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.
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, LH and cortisol but no difference in demographic data (gender, age, height, weight and BMI). After controlling for those demographic data, aPH, aPV, FSH and LH showed positive correlation with GH. 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).
A useful prediction model using adenohypophysis MRI features, age, and BMI had great potential in differentiation between GHD and ISS.
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.
本研究探讨了利用基线特征、生化指标和腺垂体MRI特征的预测模型对特发性矮小（ISS）和生长激素缺乏症（GHD）进行鉴别的诊断性能。
2021年2月至2024年2月期间，共有96例身材矮小患者在3.0-T扫描仪上接受了垂体容积T1加权成像检查，并进行了生长激素刺激试验，根据生长激素刺激试验结果分为ISS组和GHD组。采用两独立样本t检验比较两组间的差异。在控制人口统计学数据后进行偏相关分析。采用逐步二元逻辑回归方法建立预测模型。绘制受试者工作特征（ROC）曲线分析以评估模型的诊断效能。
ISS组（29例男孩和29例女孩）和GHD组（21例男孩和17例女孩）在垂体高度（aPH）、垂体容积（aPV）、生长激素、促黄体生成素和皮质醇方面存在显著差异，但在人口统计学数据（性别、年龄、身高、体重和BMI）方面无差异。在控制这些人口统计学数据后，aPH、aPV、促卵泡生成素和促黄体生成素与生长激素呈正相关。采用二元逻辑回归建立了三个预测模型；模型1的AUC值最高（0.862），其次是模型3，AUC值为0.858，模型2的AUC值最低（0.725）。
利用腺垂体MRI特征、年龄和BMI建立的有效预测模型在鉴别GHD和ISS方面具有很大潜力。
问题 在青春期前儿童中区分生长激素缺乏症（GHD）和特发性矮小（ISS）很重要，但生长激素刺激试验耗时、昂贵且难度大。发现 所提出的利用临床和影像组学特征的模型在鉴别GHD和ISS方面具有足够的诊断性能。临床意义 我们提出了一种基于腺垂体MRI特征和基线特征的低成本、省时且无创的模型来鉴别GHD和ISS。
