Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study
BackgroundThe aim of the study was to explore a radiomic model that could assist physicians in the diagnosis of central precocious puberty (CPP). A predictive model based on radiomic features (RFs), extracted form magnetic resonance imaging (MRI) of the pituitary gland, was thus developed to disting...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Endocrinology |
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| author | Michele Maddalo Maddalena Petraroli Francesca Ormitti Alice Fulgoni Margherita Gnocchi Marco Masetti Eugenia Borgia Benedetta Piccolo Emanuela C. Turco Viviana D. Patianna Nicola Sverzellati Susanna Esposito Susanna Esposito Caterina Ghetti Maria E. Street Maria E. Street |
| author_facet | Michele Maddalo Maddalena Petraroli Francesca Ormitti Alice Fulgoni Margherita Gnocchi Marco Masetti Eugenia Borgia Benedetta Piccolo Emanuela C. Turco Viviana D. Patianna Nicola Sverzellati Susanna Esposito Susanna Esposito Caterina Ghetti Maria E. Street Maria E. Street |
| author_sort | Michele Maddalo |
| collection | DOAJ |
| description | BackgroundThe aim of the study was to explore a radiomic model that could assist physicians in the diagnosis of central precocious puberty (CPP). A predictive model based on radiomic features (RFs), extracted form magnetic resonance imaging (MRI) of the pituitary gland, was thus developed to distinguish between CPP and control subjects.Methods45 girls with confirmed diagnosis of CPP (CA:8.4 ± 0.9 yr) according to the current criteria and 47 age-matched pre-pubertal control subjects (CA:8.7 ± 1.2 yr) were retrospectively enrolled. Two readers (R1, R2) blindly segmented the pituitary gland on MRI studies for RFs and performed a manual estimation of the pituitary volume. Radiomics was compared against pituitary volume in terms of predictive performances (metrics: ROC-AUC, accuracy, sensitivity and specificity) and reliability (metric: intraclass correlation coefficient, ICC). Pearson correlation between RFs and auxological, biochemical, and ultrasound data was also computed.ResultsTwo different radiomic parameters, Shape Surface Volume Ratio and Glrlm Gray Level Non-Uniformity, predicted CPP with a high diagnostic accuracy (ROC-AUC 0.81 ± 0.08) through the application of our ML algorithm. Anthropometric variables were not confounding factors of these RFs suggesting that premature thelarche and/or pubarche would not be potentially misclassified. The selected RFs correlated with baseline and peak LH (p < 0.05) after GnRH stimulation. The diagnostic sensitivity was improved compared to pituitary volume only (0.76 versus 0.68, p<0.001) and demonstrated higher inter-reader reliability (ICC>0.57 versus ICC=0.46).DiscussionRadiomics is a promising tool to diagnose CPP as it reflects also functional aspects. Further studies are warranted to validate these preliminary data. |
| format | Article |
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| institution | Kabale University |
| issn | 1664-2392 |
| language | English |
| publishDate | 2025-02-01 |
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| series | Frontiers in Endocrinology |
| spelling | doaj-art-90d5fbdc8b484616a8d93e9476eb50aa2025-02-05T05:17:45ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922025-02-011610.3389/fendo.2025.14965541496554Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot studyMichele Maddalo0Maddalena Petraroli1Francesca Ormitti2Alice Fulgoni3Margherita Gnocchi4Marco Masetti5Eugenia Borgia6Benedetta Piccolo7Emanuela C. Turco8Viviana D. Patianna9Nicola Sverzellati10Susanna Esposito11Susanna Esposito12Caterina Ghetti13Maria E. Street14Maria E. Street15Medical Physics Department, University Hospital of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyNeuroradiology Unit, University Hospital of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyMedical Physics Department, University Hospital of Parma, Parma, ItalyUnit of Pediatrics, Department of Mother and Child, University Hospital of Parma, Parma, ItalyDepartment of Medicine and Surgery, University of Parma, Parma, ItalyBackgroundThe aim of the study was to explore a radiomic model that could assist physicians in the diagnosis of central precocious puberty (CPP). A predictive model based on radiomic features (RFs), extracted form magnetic resonance imaging (MRI) of the pituitary gland, was thus developed to distinguish between CPP and control subjects.Methods45 girls with confirmed diagnosis of CPP (CA:8.4 ± 0.9 yr) according to the current criteria and 47 age-matched pre-pubertal control subjects (CA:8.7 ± 1.2 yr) were retrospectively enrolled. Two readers (R1, R2) blindly segmented the pituitary gland on MRI studies for RFs and performed a manual estimation of the pituitary volume. Radiomics was compared against pituitary volume in terms of predictive performances (metrics: ROC-AUC, accuracy, sensitivity and specificity) and reliability (metric: intraclass correlation coefficient, ICC). Pearson correlation between RFs and auxological, biochemical, and ultrasound data was also computed.ResultsTwo different radiomic parameters, Shape Surface Volume Ratio and Glrlm Gray Level Non-Uniformity, predicted CPP with a high diagnostic accuracy (ROC-AUC 0.81 ± 0.08) through the application of our ML algorithm. Anthropometric variables were not confounding factors of these RFs suggesting that premature thelarche and/or pubarche would not be potentially misclassified. The selected RFs correlated with baseline and peak LH (p < 0.05) after GnRH stimulation. The diagnostic sensitivity was improved compared to pituitary volume only (0.76 versus 0.68, p<0.001) and demonstrated higher inter-reader reliability (ICC>0.57 versus ICC=0.46).DiscussionRadiomics is a promising tool to diagnose CPP as it reflects also functional aspects. Further studies are warranted to validate these preliminary data.https://www.frontiersin.org/articles/10.3389/fendo.2025.1496554/fullcentral precocious pubertypituitary glandradiomicsmachine learningmagnetic resonance imagingprecocious puberty, puberty |
| spellingShingle | Michele Maddalo Maddalena Petraroli Francesca Ormitti Alice Fulgoni Margherita Gnocchi Marco Masetti Eugenia Borgia Benedetta Piccolo Emanuela C. Turco Viviana D. Patianna Nicola Sverzellati Susanna Esposito Susanna Esposito Caterina Ghetti Maria E. Street Maria E. Street Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study Frontiers in Endocrinology central precocious puberty pituitary gland radiomics machine learning magnetic resonance imaging precocious puberty, puberty |
| title | Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study |
| title_full | Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study |
| title_fullStr | Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study |
| title_full_unstemmed | Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study |
| title_short | Magnetic resonance imaging -based radiomics of the pituitary gland is highly predictive of precocious puberty in girls: a pilot study |
| title_sort | magnetic resonance imaging based radiomics of the pituitary gland is highly predictive of precocious puberty in girls a pilot study |
| topic | central precocious puberty pituitary gland radiomics machine learning magnetic resonance imaging precocious puberty, puberty |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2025.1496554/full |
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