2556
Diagnostic value of adenohypophyseal magnetic resonance imaging features in girls with precocious puberty
Dong Liu1, Weiyin Vivian Liu2, and Wenzhen Zhu1
1Department of Radiology, Tongji Hosptial, Tongji Medical College, Huazhong University of Science and Technology, Wu han, China, 2MR Research, GE Healthcare, Bei jing, China
1Department of Radiology, Tongji Hosptial, Tongji Medical College, Huazhong University of Science and Technology, Wu han, China, 2MR Research, GE Healthcare, Bei jing, China
Synopsis
Keywords: Normal Development, Pediatric, Diagnosis; Precocious puberty.
Motivation: Gonadotropin-releasing hormone (GnRH) stimulation test is time- and labor- consuming. A prediction model composed of MRI-derived variables for precocious puberty is useful for diagnosis.
Goal(s): This study aimed to evaluate the diagnostic value of adenohypophyseal MRI features for precocious puberty in girls.
Approach: Pearson correlation and stepwise multivariate linear regression analysis were used to examine the best association of MRI features and clinical data for 126 girls and build prediction models.
Results: Two Models were built to predict LH and LH/FSH. ROC analysis showed the predicted LH, predicted LH/FSH, and aPV were the top 3 best predictors in distinguishing CPP group from controls.
Impact: The adenohypophysis volume itself and the prediction models including main adenohypophyseal MRI features increased diagnosis efficiency for PP and offered a non-invasive and credible diagnostic method.
Background and Purpose
Precocious puberty (PP) is clinically defined by the development of secondary sexual characteristics before the age of 8 years in girls. The peak value of luteinizing hormone exceeding 5 mUI/ml after GnRH analogue stimulation indicates activation of the HPG axis and the peak of both luteinizing hormone to follicle-stimulating hormone ratio (LH/FSH) over 0.6 indicates CPP. Moreover, incomplete PP (IPP) is defined as premature thelarche, premature pubarche, and isolated menarche with incomplete activation of the HPG axis when secondary sexual characteristics occur. To early detect the progression of PP is important in clinical diagnosis.GnRH stimulation test is invasive and relatively high-cost and requires clinician prescription and multiple samplings. Frequent blood collection can impose a psychological burden on pediatric patients and also cause financial and time-related implications. The height and shape of the pituitary gland on sellar MRI revealed significant correlations with the weight, height, Tanner stage, and LH levels of CPP patients. but the roles of MRI features and correlations with hormones still remain unclear for PP diagnosis.
The objective of this study was to develop and evaluate the diagnostic efficacy of adenohypophysis MRI features and laboratory testing characteristics in PP girls and also establish a prediction model composed of MRI-derived variables for PP.
Materials and Methods
A total of 126 girls (37, 57 and 32 girls clinically diagnosed as patients with central PP [CPP] and incomplete PP [IPP], and controls) were enrolled in this study. Data in the three groups were collected and analyzed using analysis of variance. Pearson correlation and stepwise multivariate linear regression analysis were used to examine the association and build prediction models. ROC analysis was used to evaluate the diagnostic efficacy.Results
Correlations between adenohypophyseal MRI features (aPV, aPH, and SIR) and main clinical data (Height and Weight) and GnRH agonist stimulation test results (LHpeak and LH/FSH)Pearson correlation analysis demonstrated that aPV, aPH, Height and Weight were positively associated with LHpeak and LH/FSH (all P ＜ 0.001) while SIR was positively associated with LH/FSH (P = 0.021). The stepwise multivariate linear regression analysis showed predicted LH values (pLH) using aPV, Weight, and aPH as contributors in model 1(R2 = 0.271) : $$pLH=0.045×aPV+0.484×Weight+1.567×aPH-21.001
and predicted LH/FSH values (pLH/FSH) using SIR, aPV, and Height as contributors in model 2 (R2 = 0.311) : $$pLH/FSH=-0.042×SIR+0.002×aPV+0.034×Height-3.686
ROC curves of adenohypophyseal MRI features (aPV, aPH, and SIR) and predicted values (pLH and pLH/FSH) in the three groups
Between the control and CPP groups, the best predictor was pLH with the AUC (with 95% confidence intervals [CIs]) of 0.969 (0.934-1.000). Between the control and IPP groups, the best predictor was pLH/FSH with the AUC (with 95% CIs) was 0.829 (0.739-0.919), the best sensitivity of 98.25% (90.71%, 99.91%) and the best NPV of 94.4% (70.3%, 99.2%). Between the IPP and CPP groups, the best predictor was pLH/FSH with the AUC (with 95% CIs) of 0.828 (0.736, 0.921).
For distinguishing heathy girls from PP, pLH, pLH/FSH and aPV had credible values while for distinguishing different periods of PP, pLH and pLH/FSH had credible values. aPV showed the best diagnostic value among three groups when using adenohypophyseal MRI features alone, but SIR showed the best sensitivity.
Discussion
Our study found clinical data, adenohypophyseal MRI features and laboratory testing characteristics can reflect PP, assisting us to better comprehend the sophisticated biological process of sexual development and the activation of the HPG axis. Adenohypophyseal MRI features alone had a reliable diagnostic value in identification of precocious puberty. However, a predicted model including both clinical data and adenohypophyseal MRI features built with multivariate linear regression analysis showed better diagnostic efficacy to discriminate IPP from CPP.Owing to the disadvantages of the GnRH stimulation testing, numerous studies have attempted to simplify its procedure or explore alternative methods. MRI is the preferred approach to evaluate the pituitary gland and is conducted in many tertiary care centers to exclude brain abnormalities in CPP-confirmed girls. ROC curves showed aPV could only distinguish CPP from the control groups even with AUC, sensitivity and specificity of 0.938, 91.89% and 81.25% at the cutoff value of 207.3 mm3, but not between any other two groups. The built model 2 in prediction of pLH/FSH showed the good to best diagnostic performance with AUC of 0.949 between CPP and control groups, 0.829 between IPP and control groups, and 0.828 between CPP and IPP groups.
In conclusions, the adenohypophysis volume itself and the prediction models including main adenohypophyseal MRI features increased diagnosis efficiency for PP and offered a non-invasive and credible diagnostic method.
Acknowledgements
No acknowledgement found.References
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Figures
Figure 1. Flowchart of participant selection criteria.
IPP = Incomplete precocious puberty, CPP = Central precocious puberty
Figure 2. The regions of interest of the adenohypophysis have been manually delineated on CUBE T1WI images.
A: the ROI of adenohypophysis axial images; B: the ROI of adenohypophysis sagittal images; C: the ROI of adenohypophysis coronal images; D: the reformat volume image of adenohypophysis;
Figure 3. ROC curves of adenohypophyseal
MRI features (aPV, aPH, and SIR) and predicted values (pLH and pLH/FSH) for
diagnosis among the three groups.
ROC curves of aPV, aPH, SIR, pLH and
pLH/FSH for discrimination between (A) control and CPP groups, (B) control and IPP groups, and (C) between IPP and CPP groups.
IPP=incomplete
precocious puberty, CPP=central precocious puberty, SIR= signal
intensity ratio, aPH=height of the adenohypophysis, aPV=volume of the adenohypophysis,
pLH= predicted value of LHpeak in model 1; pLH/FSH=
predicted value of LH/FSH in model 2.
DOI: https://doi.org/10.58530/2024/2556