Imaging of the Osteoporotic Spine – Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk

Author:

Sollmann Nico1234ORCID,Kirschke Jan Stefan34ORCID,Kronthaler Sophia5,Boehm Christof5,Dieckmeyer Michael3,Vogele Daniel1,Kloth Christopher1,Lisson Christoph Gerhard1,Carballido-Gamio Julio6,Link Thomas Marc2,Karampinos Dimitrios Charalampos5,Karupppasamy Subburaj78,Beer Meinrad1,Krug Roland2,Baum Thomas3

Affiliation:

1. Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany

2. Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States

3. Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

4. TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

5. Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

6. Department of Radiology, University of Colorado – Anschutz Medical Campus, Aurora, CO, United States

7. Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore

8. Sobey School of Business, Saint Mary’s University, Halifax, NS, Canada

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:  Citation Format

Funder

German Society of Musculoskeletal Radiology

B. Braun Foundation

Dr.-Ing. Leonhard Lorenz Foundation

Deutsche Forschungsgemeinschaft

H2020 European Research Council

Publisher

Georg Thieme Verlag KG

Subject

Radiology, Nuclear Medicine and imaging

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