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The Role of Artificial Intelligence in Pediatric Orthopedics: Useful Tool...
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The Role of Artificial Intelligence in Pediatric Orthopedics: Useful Tool or Hype

A special issue of Children (ISSN 2227-9067). This special issue belongs to the section "Pediatric Orthopedics & Sports Medicine".

Deadline for manuscript submissions: closed (20 May 2025) | Viewed by 533

Special Issue Editors

Dr. Pieter Bas de Witte

E-Mail Website
Guest Editor
Department of Orthopaedics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
Interests: paediatric orthopaedic surgery; hip surgery; trauma
Special Issues, Collections and Topics in MDPI journals
Dr. Jasper Gerbers

E-Mail Website
Guest Editor
Department of Orthopaedics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
Interests: child

Special Issue Information

Dear Colleagues,

It is common knowledge that artificial intelligence (AI) is playing an increasing role in various areas of healthcare, ranging from management and basic science to clinical practice. Despite rapid advancements, however, its role in orthopedics, more specifically pediatric orthopedics, is still limited.

However, there is great potential for the use of AI in pediatric orthopedics. Some papers have been published, investigating where AI is used for growth prediction and to determine skeletal age, the severity of developmental dysplasia of the hip or scoliosis, skeletal lesion characterization, gait analysis, etc. Beyond diagnostics, AI has the potential to facilitate outpatient clinical activities (e.g., automated medical records and workflow), reduce the complexity of surgical planning, and clinical decision making.

For this Special Issue in Children, we aim to address the role of artificial intelligence and other forms of computer-aided planning or assistance in pediatric orthopedics. We welcome contributions that pertain to this subject, covering various topics including, but not limited to, radiodiagnostic imaging, growth predictions, malalignment assessment, surgical planning, and skeletal age.

We accept original research from basic and clinical researchers and review articles on various aspects of AI in pediatric orthopedics.

Dr. Pieter Bas de Witte
Dr. Jasper Gerbers
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Children is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • pediatric orthopedic surgery
  • artificial intelligence
  • computer-aided planning
  • radiology
  • diagnosis
  • clinical decision making
  • surgical planning
  • malalignment assessment

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Published Papers (1 paper)

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Review

12 pages, 631 KiB  
Review
Current and Emerging Applications of Artificial Intelligence in Medical Imaging for Paediatric Hip Disorders—A Scoping Review
by Hilde W. van Kouswijk, Hizbillah Yazid, Jan W. Schoones, M. Adhiambo Witlox, Rob G. H. H. Nelissen and Pieter Bas de Witte
Children 2025, 12(5), 645; https://doi.org/10.3390/children12050645 - 16 May 2025
Viewed by 215
Abstract
Introduction: Paediatric hip disorders present unique challenges for artificial intelligence (AI)-aided assessments of medical imaging due to disease-related and age-dependent changes in hip morphology. This scoping review aimed to describe current and emerging applications of AI in medical imaging for paediatric hip disorders. [...] Read more.
Introduction: Paediatric hip disorders present unique challenges for artificial intelligence (AI)-aided assessments of medical imaging due to disease-related and age-dependent changes in hip morphology. This scoping review aimed to describe current and emerging applications of AI in medical imaging for paediatric hip disorders. Methods: A descriptive synthesis of articles identified through PubMed, Embase, Cochrane Library, Web of Science, Emcare, and Academic Search Premier databases was performed including articles published up until June 2024. Original research articles’ titles and abstracts were screened, followed by full-text screening. Two reviewers independently conducted article screening and data extraction (i.e., data on the article and the model and its performance). Results: Out of 871 unique articles, 40 were included. The first article was dated from 2017, with annual publication rates increasing thereafter. Research contributions were primarily from China (17 [43%]) and Canada (10 [25%]). Articles mainly focused on developing novel AI models (19 [47.5%]), applied to ultrasound images or radiographs of developmental dysplasia of the hip (DDH; 37 [93%]). The three remaining articles addressed Legg–Calvé–Perthes disease, neuromuscular hip dysplasia in cerebral palsy, or hip arthritis/osteomyelitis. External validation was performed in eight articles (20%). Models were mainly applied to the diagnosis/grading of the disorder (22 [55%]), or on screening/detection (17 [42.5%]). AI models were 17 to 124 times faster (median 30) in performing a specific task than experienced human assessors, with an accuracy of 86–100%. Conclusions: Research interest in AI applied to medical imaging of paediatric hip disorders has expanded significantly since 2017, though the scope remains restricted to developing novel models for DDH imaging. Future studies should focus on (1) the external validation of existing models, (2) implementation into clinical practice, addressing the current lack of implementation efforts, and (3) paediatric hip disorders other than DDH. Full article
(This article belongs to the Special Issue The Role of Artificial Intelligence in Pediatric Orthopedics: Useful Tool or Hype)
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