ArticleQuantitative imaging in medicine and surgery2026
Magnetic resonance imaging-based adenohypophyseal volume for diagnosing hypothalamic-pituitary-gonadal axis activation in pre- and at-puberty children.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Central precocious puberty (CPP) results from premature activation of the hypothalamic-pituitary-gonadal (HPG) axis. Although the gonadotropin-releasing hormone (GnRH) stimulation test remains the diagnostic standard for evaluating HPG axis activation, its invasive nature limits clinical utility. Magnetic resonance imaging (MRI)-derived pituitary measurements offer a promising alternative, yet previous studies on two-dimensional measurements have reported limited accuracy. This study aimed to assess the value of adenohypophysis volume (aPV) and height (aPH) precisely measured with the three-dimensional (3D) CUBE T1 sequence (GE HealthCare) in diagnosing HPG axis activation. Methods: A cohort of 593 children (196 boys and 397 girls; mean age 8.22±2.28 years) who underwent pituitary MRI and GnRH stimulation testing was included. Partial correlation analysis, controlling for sex, age, height, weight, and body mass index (BMI), examined the associations of aPV and aPH with peak luteinizing hormone (LH) and the LH to follicle-stimulating hormone (FSH) ratio (LH/FSH). Multiple linear regression models were constructed, and their diagnostic performance was evaluated via receiver operating characteristic (ROC) analysis. Results: aPV showed moderate significant correlations with peak LH (r=0.543; P<0.001) and LH/FSH ratio (r=0.480; P<0.001), which remained significant after controlling for confounders (LH: r=0.283, P<0.001; LH/FSH: r=0.207, P<0.001); meanwhile, the aPH correlations were weaker. Multiple linear regression identified age and aPV as significant predictors for LH peak (aPV: B=0.030; P<0.001), while age, weight, and aPV were significant predictors for LH/FSH (aPV: B=0.002; P<0.001). The regression model for predicting LH/FSH >0.6 yielded an area under the curve (AUC) of 0.841 [95% confidence interval (CI): 0.808-0.871], with a sensitivity of 74.5% and a specificity of 84.9% at the optimal threshold. Conclusions: aPV may have significant potential to be a noninvasive diagnostic biomarker for assessing HPG axis activation in children with CPP. The developed regression models, incorporating aPV, age, and weight, provide promising diagnostic performance and may potentially reduce the reliance on invasive GnRH stimulation tests.
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