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

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

Zusammenfassung

Osteoporose ist eine systemische Skeletterkrankung mit sehr hoher Prävalenz, die durch verminderte Knochensubstanz und mikrostrukturelle Verschlechterung des Knochens gekennzeichnet ist. Osteoporose prädisponiert zu Frakturen, welche an verschiedenen Stellen des Skeletts auftreten können, wobei hierunter Wirbelkörper-Frakturen besonders häufig sind. Präventionsmaßnahmen sowie rechtzeitige Interventionen basieren auf einer zuverlässigen Diagnose sowie einer Abschätzung des individuellen Frakturrisikos, wobei die Doppelröntgen-Absorptiometrie (DXA) seit Jahrzehnten als Referenzstandard gilt. Die DXA-Methode hat jedoch inhärente Limitationen, während andere Techniken ein hohes Potenzial als praktikable ergänzende oder sogar alleinige Alternativen gezeigt haben. Im Speziellen spielen dreidimensionale (3 D) Modalitäten der Bildgebung, wie die Computertomografie (CT) und die Magnetresonanztomografie (MRT), eine zunehmend wichtige Rolle. In Bezug auf die CT erlauben aktuelle Entwicklungen aus dem Bereich der medizinischen Bildanalyse inzwischen eine automatisierte Segmentierung und Extraktion relevanter Maßzahlen einzelner Wirbelkörper unter Verwendung von „Deep-Learning“-Algorithmen, welche in die klinische Praxis implementiert werden können. In Bezug auf die MRT stehen dank der Entwicklungen über die letzten Jahre eine Vielzahl an Methoden zur Verfügung, insbesondere die Magnetresonanzspektroskopie (MRS) sowie die Bildgebung mittels „Chemical Shift Enconding-Based“ Wasser-Fett-Differenzierung zur Gewinnung der „Proton Density Fat Fraction“ (PDFF) eines Wirbelkörpers als vielversprechendem Surrogatmarker der Knochengesundheit. Bildgebungsdaten der CT oder MRT könnten jedoch noch effizienter genutzt werden durch eine Kombination mit fortschrittlichen Analyse-Techniken, wie beispielsweise Texturanalyse (TA; zur räumlich hoch aufgelösten Auswertung des Wirbelkörperaufbaus) oder Finite-Elemente-Analyse (FEA; zur Abschätzung der Knochenstärke) zur weiteren Verbesserung der Frakturvorhersage. Bisweilen konnten jedoch noch keine spezifischen und experimentell validierten Diagnosekriterien für die Osteoporose anhand CT- und MRT-basierter Parameter etabliert werden, was die breitere Translation in die klinische Praxis für diese neuen Ansätze erschwert.

Kernaussagen: 

• Die DXA-Methode stellt den Referenzstandard für die Diagnose und Frakturabschätzung bei Osteoporose dar, hat jedoch wichtige Limitationen.

• CT- und MRT-basierte Techniken werden zunehmend im Rahmen (opportunistischer) Ansätze genutzt.

• In Bezug auf die CT ist insbesondere die „Deep-Learning“-basierte automatische Wirbelkörpersegmentierung mit Extraktion von Maßzahlen bedeutsam.

• Für die MRT stehen vielfältige Techniken inklusive der Spektroskopie und der „Chemical-Shift“-Bildgebung zur Extraktion der „Fat Fraction“ zur Verfügung.

• Textur- und Finite-Elemente-Analysen können eine zusätzliche Bestimmung des Wirbelkörper-Aufbaus und der Knochenstärke ermöglichen.

Key words

bone mineral density - computed tomography - magnetic resonance imaging - proton density fat fraction - quantitative imaging - vertebral fracture

Publication History

Received: 02 September 2021

Accepted: 03 February 2022

Article published online:
11 May 2022

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