ESPE2024 Poster Category 2 Late Breaking (107 abstracts)
1Faculty of Medicine, University of Thessaly, Larisa, Greece. 2Department of Pediatrics, Division of Endocrinology, Medical School, University of Patras, Patras, Greece. 3Pediatric Endocrine Clinics, Athens Medical Center, Athens, Greece. 4Department of Pediatrics and Neonatology, University Hospital of Larisa, Faculty of Medicine, School of Health Sciences, University of Thessaly, Greece, Larisa, Greece. 5Aretaieion University Hospital, National and Kapodistrian University of Athens, Athens, Greece. 6Neonatal-Pediatric-Adolescent Endocrinology Unit, Department of Pediatrics and Neonatology, University Hospital of Larisa, Faculty of Medicine, School of Health Sciences, University of Thessaly, Greece, Larisa, Greece
Introduction: The assessment of bone maturation with artificial intelligence (AI) has introduced new straightforward indicators of bone health monitoring related the much more complex and expensive method of measuring bone density with DEXA (Dual-Energy X-Ray Absorptiometry). Bone Health Index (BHI) describes bone mass as a function of cortical thickness, width and length of the three middle metacarpals, using digital hand X-rays for bone age evaluation from DICOM files whilst Metacarpal Index (MCI) from digitized files expresses the cortical thickness standardized for the outer bone diameter at the measuring site (second metacarpal or three metacarpal bones of both hands), both expressed in SDS for the relative bone age (BA). Bone health is mainly dependent on vitamin D (25OHD) and parathyroid hormone.
Objective: Evaluation of the clinical usefulness of BHI and MCI to detect children and adolescents with calcium metabolism disorders i.e. subclinical hyperparathyroidism due to nutritional rickets, and primary genetic disorders such as osteogenesis imperfecta.
Method: A retrospective non-interventional study using anonymous laboratory data registered in the Growth Analyzer EPRS in children and adolescents evaluated in the pediatric endocrine clinic with a BA. Patients with any pathology interfering with bone health were excluded. BHI/MCI SDS were assessed with the AI software BoneXpert (Visiana, Denmark), classified as normal > -1, possible osteopenia ≤-1 and >-2, possible osteoporosis ≤ -2, and were correlated with Ca metabolism parameters: Ca, P, ALP, 25(OH)D, PTH. Statistical analysis was performed with XLSTAT PREMIUM AI v. 2023.1.4 (Addinsoft).
Results: 2.355 patients were included. The distributions of BHI/MCI SDS were found identical (P <0.001), and both indices can be considered equally credible. 50.81% of children and adolescents had BHI/MCI compatible with osteopenia or osteoporosis with a negatively skewed distribution (P <0.005). A significant linear correlation was found between vitamin D (P <0.001, R2=0.37), PTH (P <0.001, R2=0.365) as well as the product D3xPTH (P <0.001, R2= 0.303) and BHI/MCI SDS. D3xPTH, comprising the two most important parameters of calcium metabolism, was the only parameter that differed significantly between children with normal bone density and those with osteoporosis (P = 0.021).
Conclusion: The use of BHI/ MCI SDS may contribute to the early detection of calcium metabolism disorders in children leading to early diagnosis and prompt treatment, especially for those with BHI/MCI ≤ -2 SDS, who appear to have affected indices of calcium metabolism, and notably the novel parameter D3xPTH.