Background: Four-dimensional computed tomography (4D CT) is rapidly emerging as a diagnostic tool for the investigation of dynamic upper limb disorders. Dynamic elbow pathologies are challenging to diagnose, and at present, limitations exist in current imaging modalities.
Objective: We aimed to assess the clinical utility of 4D CT in detecting potential dynamic elbow disorders.
Methods: Twenty-eight elbow joints from 26 patients with symptoms of dynamic elbow pathology were included in this study. They were first assessed by a senior orthopedic surgeon with subsequent qualitative data obtained via a Siemens Force Dual Source CT scanner (Erlangen, Germany), producing two- and three-dimensional "static" images and 4D dynamic "movie" images for assessment in each clinical scenario. Clinical assessment before and after scan was compared.
Results: Use of 4D CT scan resulted in a change of diagnosis in 16 cases (57.14%). This included a change in primary diagnosis in 2 cases (7.14%) and secondary diagnosis in 14 cases (50%). In 25 cases (89.29%), the 4D CT scan allowed us to understand the pathological anatomy in greater detail which led to a change in the management plan of 15 cases (53.57%).
Conclusion: 4D CT is a promising diagnostic tool in the management of dynamic elbow disorders and may be considered in clinical practice. Future studies need to compare it with other diagnostic modalities such as three-dimensional CT.
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http://dx.doi.org/10.1016/j.jseint.2021.09.013 | DOI Listing |
Life (Basel)
November 2024
Department of Electronic Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
After a fracture, patients have reduced willingness to bend and extend their elbow joint due to pain, resulting in muscle atrophy, contracture, and stiffness around the elbow. Moreover, this may lead to progressive atrophy of the muscles around the elbow, resulting in permanent functional loss. Currently, a goniometer is used to measure the range of motion, ROM, to evaluate the recovery of the affected limb.
View Article and Find Full Text PDFMusculoskeletal ultrasound (MSKUS) has emerged as a valuable diagnostic tool in the evaluation and management of lateral elbow pathologies. This imaging modality provides high-resolution, dynamic visualization of superficial soft tissue structures, making it particularly advantageous for assessing conditions such as lateral epicondylitis (tennis elbow), ligamentous injuries, radial tunnel syndrome, and other common disorders. This article reviews the utility of MSKUS for rehabilitation providers, focusing on its role in accurately identifying pathoanatomical changes, guiding treatment strategies, and monitoring therapeutic outcomes.
View Article and Find Full Text PDFInjury
December 2024
Department of Orthopaedics, Larnaca General Hospital, State Health Services Organisation, Larnaca, Cyprus.
The purpose of this study was to establish typical dose values at orthopaedic operating rooms of the Larnaca General Hospital (LGH). Kerma area product (KAP), fluoroscopy time (FT) and cumulative air-kerma (K) measurements were collected for 821 patients who underwent common and reproducible trauma surgery over a five-year period, with three mobile C-arm systems; two equipped with an image-intensifier and one with a flat-panel detector. Dose indices were automatically extracted from radiation dose structured reports or DICOM meta-data files archived in the PACS, using custom-made software.
View Article and Find Full Text PDFShoulder Elbow
December 2024
Sports and Exercise Medicine Center, Swiss Olympic Medical Center, Lausanne University Hospital, Lausanne, Switzerland.
Background: Elbow injuries are likely to generate a decreased range of motion (ROM), which might negatively affect athletic performance. To date, the effect of elbow stiffness on endurance running performance has never been studied. We conducted an observational, prospective, cross-over study to examine the impact of elbow stiffness on running economy.
View Article and Find Full Text PDFFront Neurorobot
December 2024
Faculty of Computer Science and AI, Air University, Islamabad, Pakistan.
Introduction: Recognizing human actions is crucial for allowing machines to understand and recognize human behavior, with applications spanning video based surveillance systems, human-robot collaboration, sports analysis systems, and entertainment. The immense diversity in human movement and appearance poses a significant challenge in this field, especially when dealing with drone-recorded (RGB) videos. Factors such as dynamic backgrounds, motion blur, occlusions, varying video capture angles, and exposure issues greatly complicate recognition tasks.
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