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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/55621

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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling 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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