Introduction: Improvements in computed tomography (CT) technology in terms of image quality and reduction in absorbed dose have increased its applications in medical imaging. Diagnostic reference levels (DRLs) help to identify high radiation doses that are unusually delivered to patients undergoing exposure to ionising radiation. The aim of this review was to provide an overview of published studies by African researchers towards establishing paediatric CT DRLs in Africa.
Methods: The search for articles was conducted using some relevant literature search engines including PubMed, Scopus, Science Direct, Google Scholar and Web of Science. Two reviewers were involved in the article selection process which involved a three-stage screening process of identifying; article titles, abstracts and full-test reading.
Results: One hundred and seventy-four articles were identified from the database, PubMed (30), Scopus (21), Google Scholar (53), Web of Science (25) and Science Direct (45). Fifty duplicated articles were excluded before screening. Twelve peer-reviewed articles were included in this study based on the inclusion criteria. DRL values in terms of computed tomography dose index volume of head for the age groupings 0-1, 1-5, 5-10 and 10-15 were 27, 36.6, 39.5 and 47.5 mGy while the dose length product values were 461.6, 664, 872 and 978 mGy.cm respectively. The DRLs were calculated as 75th percentile of the local DRLs reported by the 12 articles included in this review.
Conclusion: This review has shown that only few of the African countries (19%) have published studies on paediatric CT DRLs. There were variations in the DRLs published by the various authors which indicate that harmonisation and standardisation of paediatric CT protocols is essential for the optimisation of paediatric doses.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/jmrs.824 | DOI Listing |
J Med Internet Res
January 2025
Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.
View Article and Find Full Text PDFThe current study aimed to objectively evaluate the fit of a rectangular, tapered stem to the severely dysplastic hips on the basis of the proximal femoral anatomy and the dimensional properties of the stem. It was hypothesized that the stem size planned with accordance to the diaphyseal canal width alone can accommodate the distal femur successfully with no sizing mismatch. Forty-six patients (53 hips) suffering from secondary osteoarthritis due to hip dysplasia scheduled for total hip arthroplasty (THA) with a subtrochanteric transverse shortening osteotomy were included.
View Article and Find Full Text PDFJ Bone Miner Res
January 2025
Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
The socioeconomic burden of hip fractures, the most severe osteoporotic fracture outcome, is increasing and the current clinical risk assessment lacks sensitivity. This study aimed to develop a method for improved prediction of hip fracture by incorporating measurements of bone microstructure and composition derived from high-resolution peripheral quantitative computed tomography (HR-pQCT). In a prospective cohort study of 3028 community-dwelling women aged 75 to 80, all participants answered questionnaires and underwent baseline examinations of anthropometrics and bone by dual x-ray absorptiometry (DXA) and HR-pQCT.
View Article and Find Full Text PDFIn 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. However, traditional image processing methods may lead to high false positive rates, which is unacceptable in disease monitoring and early warning.
View Article and Find Full Text PDFActa Bioeng Biomech
September 2024
Laboratory of Physiotherapy and Physioprevention, Institute of Physiotherapy and Health Sciences, Academy of Physical Education, Katowice, Poland.
: The main aim of this paper was to perform the morphological assessment of children's mandibles of different etiology of dys-functions within the temporomandibular joint, from isolated idiopathic ankylosis to craniofacial malformations co-existing with genetic disorders. : The investigations encompassed seven patients at the age of 0-3. Measurements were conducted on the basis of data obtained from computed tomography.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!