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Volumetric MRI assessment of brain and pituitary structure in girls with central precocious puberty

医学 中枢性早熟 磁共振成像 性早熟 大脑大小 中枢神经系统 核磁共振扫描 内科学 垂体 分布(数学) 内分泌学 大脑定位 生理学 儿科 神经影像学 大脑发育 计算机断层摄影术 放射科 临床神经学 核医学
作者
Safa ÖZYILMAZ,Leyla Gizem Bolaç Özyılmaz,Deniz Çeliker,Fatma Dursun,Sevinç Taşar
出处
期刊:Journal of Pediatric Endocrinology and Metabolism [De Gruyter]
卷期号:39 (4): 324-331 被引量:1
标识
DOI:10.1515/jpem-2025-0725
摘要

Abstract Objectives To compare global and regional brain volumes and pituitary morphology between girls with central precocious puberty (CPP) and age-matched controls using intracranial-volume (ICV)-adjusted magnetic resonance imaging (MRI), and to assess associations between gonadotropins and brain volumetry. Methods This retrospective study included 182 girls (CPP n=91; controls n=91; age 6–9 years at MRI acquisition). Brain MRI (1.5 T) was segmented using the volBrain pipeline, and global and regional volumes were normalized to ICV. Pituitary height and volume were measured by two blinded radiologists. Group differences were analyzed with Welch t -tests; ANCOVA was applied for age and ICV adjustment. Multiple comparisons were FDR-corrected. Correlations with basal and GnRH-stimulated LH were evaluated using Spearman analysis. Results CPP patients had more advanced pubertal staging, higher height SDS, and greater pituitary height, while pituitary volume was similar. Global intracranial and total brain volumes did not differ. The WM/ICV fraction was modestly lower in CPP, whereas GM/ICV and CSF/ICV fractions were comparable. No regional brain volumes remained significant after FDR correction. In the stimulation-test subgroup, higher peak LH correlated with smaller total-brain/ICV and cerebrum/ICV fractions and with greater CSF/ICV. Conclusions After adjusting for age and intracranial volume, CPP showed preserved global and regional brain structure. Modest WM reduction and LH-related shifts in brain–CSF distribution suggest subtle hormonally mediated differences in maturational timing. This study provides the largest ICV-normalized volumetric MRI dataset in CPP.
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