Radiological Innovations for Monitoring Bone Regeneration and Fracture Healing

Accurate monitoring of bone regeneration and fracture healing is essential for optimizing orthopedic outcomes and guiding timely clinical interventions. While radiography, computed tomography (CT), and magnetic resonance imaging (MRI) remain standard tools, their limitations, particularly in detecting early biological activity and evaluating healing around implants, have prompted exploration of advanced imaging techniques. This narrative review was conducted through a structured search of PubMed, Scopus, and Web of Science databases for studies published between 2000 and 2025 using predefined keywords related to bone healing and imaging. Peer-reviewed original studies, systematic reviews, and clinically relevant preclinical research focusing on radiological assessment of fracture healing were included, while non-English articles, conference abstracts, and non-peer-reviewed sources were excluded. Study quality and potential sources of bias were appraised based on clarity of methodology, imaging reproducibility, and applicability to clinical practice. Recent innovations, such as high-resolution and functional MRI, quantitative CT (qCT), hybrid positron emission tomography (PET) imaging, and advanced ultrasound modalities, provide deeper insights into trabecular microarchitecture, perfusion, and osteoblastic activity. Metabolic PET tracers, radiomics, artificial intelligence (AI), and 3D printing further enhance diagnostic precision and support personalized treatment planning. Despite their promise, these modalities face challenges including high cost, limited accessibility, lack of standardization, and the need for robust clinical validation. This review summarizes the current radiological landscape, highlights emerging opportunities, and outlines future steps required for integrating advanced imaging tools into routine orthopedic practice.

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Publication Details

Journal
Cureus
Published
2025-11-24
DOI
https://doi.org/10.7759/cureus.97659
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

Radiological Innovations for Monitoring Bone Regeneration and Fracture Healing

1 citations
Cureus
Radiomics and Machine Learning in Medical Imaging
1.36
article

Radiological Innovations for Monitoring Bone Regeneration and Fracture Healing

article en
1 citations

Abstract

Accurate monitoring of bone regeneration and fracture healing is essential for optimizing orthopedic outcomes and guiding timely clinical interventions. While radiography, computed tomography (CT), and magnetic resonance imaging (MRI) remain standard tools, their limitations, particularly in detecting early biological activity and evaluating healing around implants, have prompted exploration of advanced imaging techniques. This narrative review was conducted through a structured search of PubMed, Scopus, and Web of Science databases for studies published between 2000 and 2025 using predefined keywords related to bone healing and imaging. Peer-reviewed original studies, systematic reviews, and clinically relevant preclinical research focusing on radiological assessment of fracture healing were included, while non-English articles, conference abstracts, and non-peer-reviewed sources were excluded. Study quality and potential sources of bias were appraised based on clarity of methodology, imaging reproducibility, and applicability to clinical practice. Recent innovations, such as high-resolution and functional MRI, quantitative CT (qCT), hybrid positron emission tomography (PET) imaging, and advanced ultrasound modalities, provide deeper insights into trabecular microarchitecture, perfusion, and osteoblastic activity. Metabolic PET tracers, radiomics, artificial intelligence (AI), and 3D printing further enhance diagnostic precision and support personalized treatment planning. Despite their promise, these modalities face challenges including high cost, limited accessibility, lack of standardization, and the need for robust clinical validation. This review summarizes the current radiological landscape, highlights emerging opportunities, and outlines future steps required for integrating advanced imaging tools into routine orthopedic practice.

CureusVol. 17(11)
Universidad de Ciencias Medicas (CR), Shri Venkateshwara University (IN), Allama Iqbal Medical College (PK), Sherwood Forest Hospitals NHS Foundation Trust (GB), Universidad Nacional de Colombia (CO), Northern Lincolnshire and Goole Hospitals NHS Foundation Trust (GB), Doncaster and Bassetlaw Teaching Hospitals NHS Foundation Trust (GB), University of Pittsburgh Medical Center (US), Metropolitan Hospital (GR), Manipal Hospital (IN), Institute of Medical Sciences (IN)
Openalex Percentile: Top 13%
Radiomics and Machine Learning in Medical Imaging
1.36
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