Evidence map›Paper›PMID 38123878›Full record

ArticleEndocrine2024

Adaptation and validation of an artificial intelligence based digital radiogrammetry tool for assessing bone health of indian children and youth with type-1 diabetes.

Chirantap Oza, Misha Antani, Shruti Mondkar, Shital Bhor, Neha Kajale, Shilpa Kajale, Pranay Goel, Vaman Khadilkar, Anuradha Khadilkar

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Article in Endocrine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chirantap OzaDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.
Misha AntaniDepartment of pathology, B.J. Medical college, Ahmedabad, India.
Shruti MondkarDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.
Shital BhorDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.
Neha KajaleDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.
Shilpa KajaleConsultant Radiologist, Department of radiology, Jehangir Hospital, Pune, India.
Pranay GoelDepartment of Biology, Indian Institute of Science Education and Research Pune, Pune, India.
Vaman KhadilkarDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India.
Anuradha KhadilkarDepartment of Paediatric growth and Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India. anuradhavkhadilkar@gmail.com.ORCID 0000-0002-3399-3235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesBoneXpert (BX) is an artificial intelligence software used primarily for bone age assessment. Besides, it can also be used to screen for bone health using the digital radiogrammetry tool called bone health index (BHI) for which normative reference values available are calculated from healthy European children. Due to ethnic difference in bone geometry, in a previous study, we generated reference curves based on healthy Indian children. The objectives of this study were: 1) To assess and compare bone health of Indian children with Type 1 diabetes (T1D) using both European and Indian BHI SDS reference data and 2) To identify determinants of poor bone health in Indian children and youth with T1D by using BHI tool (based on BHI-SDS Indian reference data) of BX.

methodThe BHI was assessed retrospectively in 1159 subjects with T1D using digitalised left-hand x-rays and SDS were computed using European and Indian data. The demographic, anthropometric, clinical, biochemistry, dual x-ray absorptiometry (DXA) data and peripheral quantitative computed tomography (pQCT) data collection were performed using standard protocols and were extracted from hospital records.

resultsThe BHI correlated well with DXA and pQCT parameters in subjects with T1D. BHI-SDS calculated using Indian reference data had better correlation with height and DXA parameters. 8.6% study participants had low (less than -2) BHI-SDS (Indian), with height SDS having significant effect. Subjects with low BHI-SDS were older, shorter and had higher duration of diabetes. They also had lower IGF1 and vitamin D concentrations, bone mineral density, and trabecular density. Female gender, increased duration of illness, poor glycaemic control, and vitamin D deficiency/insufficiency were significant predictors of poor BHI-SDS.

conclusionOur study highlights the utility of digital radiogrammetry AI tool to screen for bone health of children with T1D and demonstrates and highlights the necessity of interpretation using ethnicity specific normative data.

Indexed as

Bone DensityDiabetes Mellitus, Type 1Absorptiometry, PhotonAdolescentAnthropometryArtificial IntelligenceChildFemaleHumansRetrospective Studies

Identifiers

PMID38123878
PMCPMC10987335

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