Diagnostic accuracy of quantitative dual-energy CT-based bone mineral density assessment in comparison to Hounsfield unit measurements using dual x-ray absorptiometry as standard of reference
Introduction
Osteoporosis is a frequent metabolic bone disorder, characterized by decrease of bone mineral density (BMD) [1]. It is associated with increased fracture risk, deformations and immobility, therefore entailing a substantial economic and social burden [2].
Dual x-ray absorptiometry (DXA) is cost-effective, widely available and represents the current gold-standard for BMD assessment according to the World Health Organization (WHO) [1]. In 1994 the WHO proposed DXA as the preferred osteoporosis screening approach due to high reproducibility and evidence [1]. The WHO recommended using sex-related standard deviation parameters for the diagnosis of osteoporosis due to significant differences between men and women regarding BMD, especially due to the great importance of postmenopausal osteoporosis. In this context, the T score (the comparison with healthy 30-year old individuals of the same sex) represents the gold standard for diagnosing osteoporosis (osteoporotic BMD [T < −2.5], osteopenic BMD [−1.0 ≤ T ≤ −2.5], normal BMD [T < −1.0]. Basis for the establishment of sex-related DXA-based BMD threshold values and the corresponding T score were large studies evaluating BMD for fracture prediction [[3], [4], [5], [6]]. However, various limitations of DXA have been described such as distortion of estimated bone mass values caused by overlying soft tissue, vascular calcifications, bowel contents and degenerative spine changes [7,8]. In addition, DXA only permits areal BMD assessment of the entire vertebral body despite the fact that osteoporosis primarily affects the metabolically active trabecular rather than cortical bone [9,10]. Quantitative computed tomography (QCT) has been established for volumetric BMD assessment of specifically trabecular bone. While some studies showed similar diagnostic accuracy of QCT and DXA for diagnosing osteoporosis [9], other studies demonstrated greater sensitivity of spinal QCT for BMD assessment and fracture prediction compared to DXA [[11], [12], [13]]. However, the application of QCT remains limited by the need for calibration phantoms that do not represent the true composition of trabecular bone and prevent retrospective opportunistic BMD assessment [14,15].
The wide incidence and socioeconomic impact of osteoporosis suggests the usefulness of opportunistic BMD assessment during computed tomography (CT) examinations. Multiple studies investigated trabecular Hounsfield unit (HU) measurements for opportunistic BMD assessment and screening for osteoporosis during regularly performed CT examinations with promising results [[16], [17], [18], [19]]. However, performing a single HU measurement in a single vertebral body to measure BMD, as recently suggested by Jang et al., is likely to give only a partial, over-simplified insight into BMD dynamics and is presumably unfit to rule out or confirm the diagnosis of osteoporosis [19]. Therefore, several studies suggest multilevel vertebral HU assessment for diagnosing osteoporosis [[20], [21], [22]]; the combination with calibration approaches may further improve the diagnostic performance [23]. Nevertheless, the inhomogeneous composition of trabecular bone consisting of bone minerals, collagen matrix, water, bone marrow and adipose tissue is likely to cause inaccuracy of HU analysis in order to assess osteoporosis [14,24,25].
Dual-energy CT (DECT) allows for material differentiation by using energy dependence of the photoelectric effect at different x-ray spectra [26,27]. This technique has provided novel clinically relevant information regarding various musculoskeletal (MSK) applications compared to conventional CT [28]. Initial studies involving early dual-energy CT concepts for BMD assessed were published more than two decades ago [[29], [30], [31], [32]]. Recently, a phantomless DECT postprocessing algorithm which allows for volumetric opportunistic BMD assessment of lumbar trabecular bone has been described [27]. Initial studies have shown promising results in vivo for the detection of osteoporosis compared with DXA and in vitro compared with pull-out-forces in human cadaver vertebra specimens [33,34].
We hypothesized that phantomless volumetric DECT BMD assessment based on material decomposition may yield more accurate BMD values and higher diagnostic accuracy for the detection of osteoporosis compared to HU measurements. Thus, the purpose of this study was to compare the diagnostic accuracy of both approaches using DXA as reference standard for BMD assessment according to the WHO.
Section snippets
Materials and methods
This retrospective study was approved by the institutional review board. The requirement to obtain written informed consent was waived.
Results
A total of 200 lumbar vertebrae in 53 patients (28 male and 25 female) were analyzed. Detailed patient characteristics are shown in Table 1.
DXA-derived calculated average BMD of L1–L4 was 0.970 ± 0.238 g/cm² (range, 0.108 g/cm²–1.641 g/cm²). According to the WHO guidelines, DXA measurements of at least two vertebrae or more identified 15 patients (28 %) with an osteopenic BMD. A total of 23 patients (43 %) showed an osteoporotic BMD. The remaining 15 patients (28 %) were categorized as normal
Discussion
The results of this retrospective study demonstrate phantomless volumetric material-decomposition-based DECT BMD assessment of the lumbar spine yields superior diagnostic accuracy for the detection of osteoporosis as well as for the differentiation between abnormal and normal BMD compared to HU measurements using the DXA-derived T-score as reference standard. Furthermore, DXA-derived BMD values showed higher correlation with decomposition-based BMD compared to CT numbers. Our results indicate
Sources of funding
C.B. received speaking fees from Siemens Healthineers. M.H.A. received speaking fees from Siemens Healthineers and Bracco. I.Y. received a speaking fee from Siemens Healthineers. J.L.W. is an employee of Siemens Healthineers and received speaking fees from Siemens Healthineers and GE Healthcare in the past.
CRediT authorship contribution statement
Christian Booz: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft. Jochen Noeske: Data curation, Formal analysis, Software. Moritz H. Albrecht: Conceptualization, Data curation, Investigation, Methodology, Visualization, Supervision, Writing - review & editing. Lukas Lenga: Formal analysis, Supervision, Validation. Simon S. Martin: Formal analysis, Supervision, Validation. Ibrahim Yel: Conceptualization, Data curation, Formal
Declaration of Competing Interest
The other authors have no potential conflict of interest to disclose.
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