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1.
Rofo ; 194(10): 1088-1099, 2022 10.
Article in English | MEDLINE | ID: mdl-35545103

ABSTRACT

Osteoporosis is a highly prevalent systemic skeletal disease that is characterized by low bone mass and microarchitectural bone deterioration. It predisposes to fragility fractures that can occur at various sites of the skeleton, but vertebral fractures (VFs) have been shown to be particularly common. Prevention strategies and timely intervention depend on reliable diagnosis and prediction of the individual fracture risk, and dual-energy X-ray absorptiometry (DXA) has been the reference standard for decades. Yet, DXA has its inherent limitations, and other techniques have shown potential as viable add-on or even stand-alone options. Specifically, three-dimensional (3 D) imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), are playing an increasing role. For CT, recent advances in medical image analysis now allow automatic vertebral segmentation and value extraction from single vertebral bodies using a deep-learning-based architecture that can be implemented in clinical practice. Regarding MRI, a variety of methods have been developed over recent years, including magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) that enable the extraction of a vertebral body's proton density fat fraction (PDFF) as a promising surrogate biomarker of bone health. Yet, imaging data from CT or MRI may be more efficiently used when combined with advanced analysis techniques such as texture analysis (TA; to provide spatially resolved assessments of vertebral body composition) or finite element analysis (FEA; to provide estimates of bone strength) to further improve fracture prediction. However, distinct and experimentally validated diagnostic criteria for osteoporosis based on CT- and MRI-derived measures have not yet been achieved, limiting broad transfer to clinical practice for these novel approaches. KEY POINTS:: · DXA is the reference standard for diagnosis and fracture prediction in osteoporosis, but it has important limitations.. · CT- and MRI-based methods are increasingly used as (opportunistic) approaches.. · For CT, particularly deep-learning-based automatic vertebral segmentation and value extraction seem promising.. · For MRI, multiple techniques including spectroscopy and chemical shift imaging are available to extract fat fractions.. · Texture and finite element analyses can provide additional measures for vertebral body composition and bone strength.. CITATION FORMAT: · Sollmann N, Kirschke JS, Kronthaler S et al. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. Fortschr Röntgenstr 2022; 194: 1088 - 1099.


Subject(s)
Osteoporosis , Osteoporotic Fractures , Spinal Fractures , Absorptiometry, Photon/methods , Bone Density , Humans , Lumbar Vertebrae , Osteoporosis/diagnostic imaging , Osteoporotic Fractures/diagnostic imaging , Protons , Spinal Fractures/diagnostic imaging , Water
2.
Biomedical Engineering Letters ; (4): 153-168, 2019.
Article in English | WPRIM (Western Pacific) | ID: wpr-785511

ABSTRACT

The paper aims to provide a state-of-the-art review of methods for evaluating the effectiveness and effect of unloader knee braces on the knee joint and discuss their limitations and future directions. Unloader braces are prescribed as a non-pharmacological conservative treatment option for patients with medial knee osteoarthritis to provide relief in terms of pain reduction, returning to regular physical activities, and enhancing the quality of life. Methods used to evaluate and monitor the effectiveness of these devices on patients' health are categorized into three broad categories (perception-, biochemical-, and morphology-based), depending upon the process and tools used. The main focus of these methods is on the short-term clinical outcome (pain or unloading efficiency). There is a significant technical, research, and clinical literature gap in understanding the short- and long-term consequences of these braces on the tissues in the knee joint, including the cartilage and ligaments. Future research directions may complement existing methods with advanced quantitative imaging (morphological, biochemical, and molecular) and numerical simulation are discussed as they offer potential in assessing long-term and post-bracing effects on the knee joint.


Subject(s)
Humans , Braces , Cartilage , Complement System Proteins , Joints , Knee Joint , Knee , Ligaments , Methods , Motor Activity , Osteoarthritis, Knee , Quality of Life , Review Literature as Topic
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