2015Unpublished venueRequires access

Dual-energy digital radiography in the assessment of bone characteristics

Päivi S Toljamo

Open publisher page 3 citations

Abstract

Today, the diagnosis of osteoporosis and assessment of fracture risk is based on estimation of bone mineral density (BMD) determined by dual-energy X-ray absorptiometry (DXA). A lack has been shown in the prediction of individual fracture risk using DXA-based BMD (BMDDXA). Digital radiography (DR) has eased the application of dual-energy techniques for separating bone and soft tissue, but the direct application of dual-energy digital radiography (DEDR) to determine BMD has not been investigated. Additionally, with BMD and bone mass, bone geometry affects strongly the mechanical strength of bone. Geometrical parameters can also be determined from the DR images. This study aimed to investigate the ability of DEDR to determine BMD and whether the combination of DEDR-based BMD and geometry improves the prediction of maximal load. Fracture and osteoporosis diagnoses could thus be done with one examination, i.e. with DEDR, whereas in the current routine both DR imaging and DXA examination are needed for diagnoses. Reindeer femora were imaged by DR with two different energies (79 and 100 kVp). The different geometrical parameters were also determined from the 79 kVp images. The BMD measured by DEDR (BMDDEDR) were calculated using the calculation principle of DXA. The ability of BMDDEDR to predict BMDDXA was investigated. The femora were mechanically tested in an axial loading configuration with the shaft in a vertical position to determine mechanical parameters. The best combination of BMDDEDR and geometrical parameters to predict bone maximal load was explored. BMDDXA was used for comparison. Significant moderate to high linear correlations were observed in all regions of the upper femur (femoral neck, Ward’s triangle, trochanter and inter-trochanter) between BMDDEDR and BMDDXA. BMDDEDR of the femoral neck and BMDDXA of the femoral neck predicted maximal load similarly. The best combination of parameters to predict maximal load was BMDDEDR at Ward’s triangle, femoral shaft diameter (FSD) and femoral shaft axis length (FNAL) (r = 0.79, p < 0.05). The study shows that DEDR is a suitable method to determine BMD in vitro and the combination of BMD and geometry improves the prediction of bone maximal load when compared to BMDDEDR of femoral neck or trochanter only. The thesis also includes unpublished data from a preliminary human study.

About this research paper

What this paper is about

Today, the diagnosis of osteoporosis and assessment of fracture risk is based on estimation of bone mineral density (BMD) determined by dual-energy X-ray absorptiometry (DXA). A lack has been shown in the prediction of individual fracture risk using DXA-based BMD (BMDDXA). Digital radiography (DR) has eased the application of dual-energy techniques for separating bone and soft tissue, but the direct application of dual-energy digital radiography (DEDR) to determine BMD has not been investigated. Additionally, with BMD and bone mass, bone geometry affects strongly the mechanical strength of bone. Geometrical parameters can also be determined from the DR images. This study aimed to investigate the ability of DEDR to determine BMD and whether the combination of DEDR-based BMD and geometry improves the prediction of maximal load. Fracture and osteoporosis diagnoses could thus be done with one examination, i.e. with DEDR, whereas in the current routine both DR imaging and DXA examination are needed for diagnoses. Reindeer femora were imaged by DR with two different energies (79 and 100 kVp). The different geometrical parameters were also determined from the 79 kVp images. The BMD measured by DEDR (BMDDEDR) were calculated using the calculation principle of DXA. The ability of BMDDEDR to predict BMDDXA was investigated. The femora were mechanically tested in an axial loading configuration with the shaft in a vertical position to determine mechanical parameters. The best combination of BMDDEDR and geometrical parameters to predict bone maximal load was explored. BMDDXA was used for comparison. Significant moderate to high linear correlations were observed in all regions of the upper femur (femoral neck, Ward’s triangle, trochanter and inter-trochanter) between BMDDEDR and BMDDXA. BMDDEDR of the femoral neck and BMDDXA of the femoral neck predicted maximal load similarly. The best combination of parameters to predict maximal load was BMDDEDR at Ward’s triangle, femoral shaft diameter (FSD) and femoral shaft axis length (FNAL) (r = 0.79, p < 0.05). The study shows that DEDR is a suitable method to determine BMD in vitro and the combination of BMD and geometry improves the prediction of bone maximal load when compared to BMDDEDR of femoral neck or trochanter only. The thesis also includes unpublished data from a preliminary human study.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Today, the diagnosis of osteoporosis and assessment of fracture risk is based on estimation of bone mineral density (BMD) determined by dual-energy X-ray absorptiometry (DXA). A lack has been shown in the prediction of individual fracture risk using DXA-based BMD (BMDDXA). Digital radiography (DR) has eased the application of dual-energy techniques for separating bone and soft tissue, but the direct application of dual-energy digital radiography (DEDR) to determine BMD has not been investigated. Additionally, with BMD and bone mass, bone geometry affects strongly the mechanical strength of bone. Geometrical parameters can also be determined from the DR images. This study aimed to investigate the ability of DEDR to determine BMD and whether the combination of DEDR-based BMD and geometry improves the prediction of maximal load. Fracture and osteoporosis diagnoses could thus be done with one examination, i.e. with DEDR, whereas in the current routine both DR imaging and DXA examination are needed for diagnoses. Reindeer femora were imaged by DR with two different energies (79 and 100 kVp). The different geometrical parameters were also determined from the 79 kVp images. The BMD measured by DEDR (BMDDEDR) were calculated using the calculation principle of DXA. The ability of BMDDEDR to predict BMDDXA was investigated. The femora were mechanically tested in an axial loading configuration with the shaft in a vertical position to determine mechanical parameters. The best combination of BMDDEDR and geometrical parameters to predict bone maximal load was explored. BMDDXA was used for comparison. Significant moderate to high linear correlations were observed in all regions of the upper femur (femoral neck, Ward’s triangle, trochanter and inter-trochanter) between BMDDEDR and BMDDXA. BMDDEDR of the femoral neck and BMDDXA of the femoral neck predicted maximal load similarly. The best combination of parameters to predict maximal load was BMDDEDR at Ward’s triangle, femoral shaft diameter (FSD) and femoral shaft axis length (FNAL) (r = 0.79, p < 0.05). The study shows that DEDR is a suitable method to determine BMD in vitro and the combination of BMD and geometry improves the prediction of bone maximal load when compared to BMDDEDR of femoral neck or trochanter only. The thesis also includes unpublished data from a preliminary human study.

Key concepts: Bone mineral, Osteoporosis, Dual energy, Dual-energy X-ray absorptiometry, Radiography, Medicine, Digital radiography, Densitometry

Related papers

Back to paper searchBrowse research topicsOriginal source
Dual-energy digital radiography in the assessment of bone characteristics — Research Paper | ScholarLens