Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling
- Autores
- Campbell, Graeme M; Peña, Jaime A; Giravent, Sarah; Thomsen, Felix Sebastian Leo; Damm, Timo; Glüer, Claus C.; Borggrefe, Jan
- Año de publicación
- 2017
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Multiple myeloma (MM) is a malignant plasma cell disease associated with severe bone destruction. Surgical intervention is often required to prevent vertebral body collapse and resulting neurological complications; however, its necessity is determined by measuring lesion size or number, without considering bone biomechanics. Finite element (FE) modeling, which simulates the physiological loading, may improve the prediction of fragility. To test this, we developed a quantitative computed tomography (QCT)-based FE model of the vertebra and applied it to a dataset of MM patients with and without prevalent fracture. FE models were generated from vertebral QCT scans of the T12 (T11 if T12 was fractured) of 104 MM patients, 45 with fracture and 59 without, using a low-dose scan protocol (1.5 mm slice thickness, 4.0 to 6.5 mSv effective dose). A calibration phantom enabled the conversion of the CT Hounsfield units to FE material properties. Compressive loading of the vertebral body was simulated and the stiffness, yield load, and work to yield determined. To compare the parameters between fracture and nonfracture groups, t tests were used, and standardized odds ratios (sOR, normalized to standard deviation) and 95% confidence intervals were calculated. FE parameters were compared to mineral and structural parameters using linear regression. Patients with fracture showed lower vertebral stiffness (–15.2%; p = 0.010; sOR = 1.73; 95% CI, 1.11 to 2.70), yield force (–21.5%; p = 0.002; sOR = 2.09; 95% CI, 1.27 to 3.43), and work to yield (–27.4%; p = 0.001; sOR = 2.28; 95% CI, 1.33 to 3.92) compared to nonfracture patients. All parameters correlated significantly with vBMD (stiffness: R2 = 0.57, yield force: R2 = 0.59, work to yield: R2 = 0.50, p < 0.001), BV/TV (stiffness: R2 = 0.56, yield force: R2 = 0.58, work to yield: R2 = 0.49, p < 0.001), and Tb.Sp (stiffness: R2 = 0.51, yield force: R2 = 0.53, work to yield: R2 = 0.45, p < 0.001). FE modeling identified MM patients with compromised mechanical integrity of the vertebra. Higher sOR values were obtained for the biomechanical compared to structural or mineral measures, suggesting that FE modeling improves fragility assessment in these patients.
Fil: Campbell, Graeme M. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat Hamburg; Alemania
Fil: Peña, Jaime A. University Hospital Schleswig‐HolsteinKiel; Alemania
Fil: Giravent, Sarah. University Hospital Schleswig‐HolsteinKiel; Alemania
Fil: Thomsen, Felix Sebastian Leo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica ; Argentina
Fil: Damm, Timo. University Hospital Schleswig‐HolsteinKiel; Alemania
Fil: Glüer, Claus C.. University Hospital Schleswig‐HolsteinKiel; Alemania
Fil: Borggrefe, Jan. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat zu Köln; Alemania - Materia
-
Biomechanics
Bone Qct
Primary Tumors of Bone And Cartilage
Radiology - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/55621
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Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element ModelingCampbell, Graeme MPeña, Jaime AGiravent, SarahThomsen, Felix Sebastian LeoDamm, TimoGlüer, Claus C.Borggrefe, JanBiomechanicsBone QctPrimary Tumors of Bone And CartilageRadiologyhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Multiple myeloma (MM) is a malignant plasma cell disease associated with severe bone destruction. Surgical intervention is often required to prevent vertebral body collapse and resulting neurological complications; however, its necessity is determined by measuring lesion size or number, without considering bone biomechanics. Finite element (FE) modeling, which simulates the physiological loading, may improve the prediction of fragility. To test this, we developed a quantitative computed tomography (QCT)-based FE model of the vertebra and applied it to a dataset of MM patients with and without prevalent fracture. FE models were generated from vertebral QCT scans of the T12 (T11 if T12 was fractured) of 104 MM patients, 45 with fracture and 59 without, using a low-dose scan protocol (1.5 mm slice thickness, 4.0 to 6.5 mSv effective dose). A calibration phantom enabled the conversion of the CT Hounsfield units to FE material properties. Compressive loading of the vertebral body was simulated and the stiffness, yield load, and work to yield determined. To compare the parameters between fracture and nonfracture groups, t tests were used, and standardized odds ratios (sOR, normalized to standard deviation) and 95% confidence intervals were calculated. FE parameters were compared to mineral and structural parameters using linear regression. Patients with fracture showed lower vertebral stiffness (–15.2%; p = 0.010; sOR = 1.73; 95% CI, 1.11 to 2.70), yield force (–21.5%; p = 0.002; sOR = 2.09; 95% CI, 1.27 to 3.43), and work to yield (–27.4%; p = 0.001; sOR = 2.28; 95% CI, 1.33 to 3.92) compared to nonfracture patients. All parameters correlated significantly with vBMD (stiffness: R2 = 0.57, yield force: R2 = 0.59, work to yield: R2 = 0.50, p < 0.001), BV/TV (stiffness: R2 = 0.56, yield force: R2 = 0.58, work to yield: R2 = 0.49, p < 0.001), and Tb.Sp (stiffness: R2 = 0.51, yield force: R2 = 0.53, work to yield: R2 = 0.45, p < 0.001). FE modeling identified MM patients with compromised mechanical integrity of the vertebra. Higher sOR values were obtained for the biomechanical compared to structural or mineral measures, suggesting that FE modeling improves fragility assessment in these patients.Fil: Campbell, Graeme M. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat Hamburg; AlemaniaFil: Peña, Jaime A. University Hospital Schleswig‐HolsteinKiel; AlemaniaFil: Giravent, Sarah. University Hospital Schleswig‐HolsteinKiel; AlemaniaFil: Thomsen, Felix Sebastian Leo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica ; ArgentinaFil: Damm, Timo. University Hospital Schleswig‐HolsteinKiel; AlemaniaFil: Glüer, Claus C.. University Hospital Schleswig‐HolsteinKiel; AlemaniaFil: Borggrefe, Jan. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat zu Köln; AlemaniaAmerican Society for Bone and Mineral Research2017-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/pdfhttp://hdl.handle.net/11336/55621Campbell, Graeme M; Peña, Jaime A; Giravent, Sarah; Thomsen, Felix Sebastian Leo; Damm, Timo; et al.; Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling; American Society for Bone and Mineral Research; Journal of Bone and Mineral Research; 32; 1; 1-2017; 151-1560884-0431CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/jbmr.2924info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/jbmr.2924info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:46:35Zoai:ri.conicet.gov.ar:11336/55621instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:46:35.411CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
title |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
spellingShingle |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling Campbell, Graeme M Biomechanics Bone Qct Primary Tumors of Bone And Cartilage Radiology |
title_short |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
title_full |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
title_fullStr |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
title_full_unstemmed |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
title_sort |
Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling |
dc.creator.none.fl_str_mv |
Campbell, Graeme M Peña, Jaime A Giravent, Sarah Thomsen, Felix Sebastian Leo Damm, Timo Glüer, Claus C. Borggrefe, Jan |
author |
Campbell, Graeme M |
author_facet |
Campbell, Graeme M Peña, Jaime A Giravent, Sarah Thomsen, Felix Sebastian Leo Damm, Timo Glüer, Claus C. Borggrefe, Jan |
author_role |
author |
author2 |
Peña, Jaime A Giravent, Sarah Thomsen, Felix Sebastian Leo Damm, Timo Glüer, Claus C. Borggrefe, Jan |
author2_role |
author author author author author author |
dc.subject.none.fl_str_mv |
Biomechanics Bone Qct Primary Tumors of Bone And Cartilage Radiology |
topic |
Biomechanics Bone Qct Primary Tumors of Bone And Cartilage Radiology |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.1 https://purl.org/becyt/ford/3 |
dc.description.none.fl_txt_mv |
Multiple myeloma (MM) is a malignant plasma cell disease associated with severe bone destruction. Surgical intervention is often required to prevent vertebral body collapse and resulting neurological complications; however, its necessity is determined by measuring lesion size or number, without considering bone biomechanics. Finite element (FE) modeling, which simulates the physiological loading, may improve the prediction of fragility. To test this, we developed a quantitative computed tomography (QCT)-based FE model of the vertebra and applied it to a dataset of MM patients with and without prevalent fracture. FE models were generated from vertebral QCT scans of the T12 (T11 if T12 was fractured) of 104 MM patients, 45 with fracture and 59 without, using a low-dose scan protocol (1.5 mm slice thickness, 4.0 to 6.5 mSv effective dose). A calibration phantom enabled the conversion of the CT Hounsfield units to FE material properties. Compressive loading of the vertebral body was simulated and the stiffness, yield load, and work to yield determined. To compare the parameters between fracture and nonfracture groups, t tests were used, and standardized odds ratios (sOR, normalized to standard deviation) and 95% confidence intervals were calculated. FE parameters were compared to mineral and structural parameters using linear regression. Patients with fracture showed lower vertebral stiffness (–15.2%; p = 0.010; sOR = 1.73; 95% CI, 1.11 to 2.70), yield force (–21.5%; p = 0.002; sOR = 2.09; 95% CI, 1.27 to 3.43), and work to yield (–27.4%; p = 0.001; sOR = 2.28; 95% CI, 1.33 to 3.92) compared to nonfracture patients. All parameters correlated significantly with vBMD (stiffness: R2 = 0.57, yield force: R2 = 0.59, work to yield: R2 = 0.50, p < 0.001), BV/TV (stiffness: R2 = 0.56, yield force: R2 = 0.58, work to yield: R2 = 0.49, p < 0.001), and Tb.Sp (stiffness: R2 = 0.51, yield force: R2 = 0.53, work to yield: R2 = 0.45, p < 0.001). FE modeling identified MM patients with compromised mechanical integrity of the vertebra. Higher sOR values were obtained for the biomechanical compared to structural or mineral measures, suggesting that FE modeling improves fragility assessment in these patients. Fil: Campbell, Graeme M. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat Hamburg; Alemania Fil: Peña, Jaime A. University Hospital Schleswig‐HolsteinKiel; Alemania Fil: Giravent, Sarah. University Hospital Schleswig‐HolsteinKiel; Alemania Fil: Thomsen, Felix Sebastian Leo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica ; Argentina Fil: Damm, Timo. University Hospital Schleswig‐HolsteinKiel; Alemania Fil: Glüer, Claus C.. University Hospital Schleswig‐HolsteinKiel; Alemania Fil: Borggrefe, Jan. University Hospital Schleswig‐HolsteinKiel; Alemania. Universitat zu Köln; Alemania |
description |
Multiple myeloma (MM) is a malignant plasma cell disease associated with severe bone destruction. Surgical intervention is often required to prevent vertebral body collapse and resulting neurological complications; however, its necessity is determined by measuring lesion size or number, without considering bone biomechanics. Finite element (FE) modeling, which simulates the physiological loading, may improve the prediction of fragility. To test this, we developed a quantitative computed tomography (QCT)-based FE model of the vertebra and applied it to a dataset of MM patients with and without prevalent fracture. FE models were generated from vertebral QCT scans of the T12 (T11 if T12 was fractured) of 104 MM patients, 45 with fracture and 59 without, using a low-dose scan protocol (1.5 mm slice thickness, 4.0 to 6.5 mSv effective dose). A calibration phantom enabled the conversion of the CT Hounsfield units to FE material properties. Compressive loading of the vertebral body was simulated and the stiffness, yield load, and work to yield determined. To compare the parameters between fracture and nonfracture groups, t tests were used, and standardized odds ratios (sOR, normalized to standard deviation) and 95% confidence intervals were calculated. FE parameters were compared to mineral and structural parameters using linear regression. Patients with fracture showed lower vertebral stiffness (–15.2%; p = 0.010; sOR = 1.73; 95% CI, 1.11 to 2.70), yield force (–21.5%; p = 0.002; sOR = 2.09; 95% CI, 1.27 to 3.43), and work to yield (–27.4%; p = 0.001; sOR = 2.28; 95% CI, 1.33 to 3.92) compared to nonfracture patients. All parameters correlated significantly with vBMD (stiffness: R2 = 0.57, yield force: R2 = 0.59, work to yield: R2 = 0.50, p < 0.001), BV/TV (stiffness: R2 = 0.56, yield force: R2 = 0.58, work to yield: R2 = 0.49, p < 0.001), and Tb.Sp (stiffness: R2 = 0.51, yield force: R2 = 0.53, work to yield: R2 = 0.45, p < 0.001). FE modeling identified MM patients with compromised mechanical integrity of the vertebra. Higher sOR values were obtained for the biomechanical compared to structural or mineral measures, suggesting that FE modeling improves fragility assessment in these patients. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/55621 Campbell, Graeme M; Peña, Jaime A; Giravent, Sarah; Thomsen, Felix Sebastian Leo; Damm, Timo; et al.; Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling; American Society for Bone and Mineral Research; Journal of Bone and Mineral Research; 32; 1; 1-2017; 151-156 0884-0431 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/55621 |
identifier_str_mv |
Campbell, Graeme M; Peña, Jaime A; Giravent, Sarah; Thomsen, Felix Sebastian Leo; Damm, Timo; et al.; Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling; American Society for Bone and Mineral Research; Journal of Bone and Mineral Research; 32; 1; 1-2017; 151-156 0884-0431 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1002/jbmr.2924 info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/jbmr.2924 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/vnd.openxmlformats-officedocument.wordprocessingml.document application/pdf |
dc.publisher.none.fl_str_mv |
American Society for Bone and Mineral Research |
publisher.none.fl_str_mv |
American Society for Bone and Mineral Research |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842268804654039040 |
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13.13397 |