骨质疏松症
磁共振成像
医学
放射科
骨矿物
医学影像学
病理
作者
Nico Sollmann,Jan S. Kirschke,Sophia Kronthaler,Christof Boehm,Michael Dieckmeyer,Daniel Vogele,Christopher Kloth,Christoph Gerhard Lisson,Julio Carballido‐Gamio,Thomas M. Link,Dimitrios C. Karampinos,Karupppasamy Subburaj,Meinrad Beer,Roland Krug,Thomas Baum
出处
期刊:RöFo
[Thieme Medical Publishers (Germany)]
日期:2022-05-11
卷期号:194 (10): 1088-1099
被引量:21
摘要
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: Citation Format
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