Parametric response mapping of CT images provides early detection of local bone loss in a rat model of osteoporosis
Abstract Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses...
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Published in: | Bone (New York, N.Y.) Vol. 51; no. 1; pp. 78 - 84 |
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Abstract | Abstract Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. |
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AbstractList | Abstract Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. ► PRM was an early biomarker of bone remodeling in a rat model of osteoporosis. ► Bone loss identified by PRM preceded changes observed by standard CT based metrics. ► PRM detected cancellous bone loss and cortical expansion within 2weeks. ► PRM provides a higher sensitivity and spatial context in detecting bone changes. Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss. |
Author | Galbán, Stefanie Johnson, Timothy D Ross, Brian D Van Poznak, Catherine H Kozloff, Kenneth M Jacobson, Jon A Rehemtulla, Alnawaz Hoff, Benjamin A Boes, Jennifer L Meyer, Charles R Brisset, Jean-Christophe Galbán, Craig J |
AuthorAffiliation | 2 Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, Michigan, 48109, USA 5 Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, 48109, USA 3 Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, 48109, USA 4 Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, 48109, USA 1 Department of Radiology, University of Michigan, Ann Arbor, Michigan, 48109, USA |
AuthorAffiliation_xml | – name: 1 Department of Radiology, University of Michigan, Ann Arbor, Michigan, 48109, USA – name: 2 Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, Michigan, 48109, USA – name: 3 Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, 48109, USA – name: 5 Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, 48109, USA – name: 4 Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, 48109, USA |
Author_xml | – sequence: 1 fullname: Hoff, Benjamin A – sequence: 2 fullname: Kozloff, Kenneth M – sequence: 3 fullname: Boes, Jennifer L – sequence: 4 fullname: Brisset, Jean-Christophe – sequence: 5 fullname: Galbán, Stefanie – sequence: 6 fullname: Van Poznak, Catherine H – sequence: 7 fullname: Jacobson, Jon A – sequence: 8 fullname: Johnson, Timothy D – sequence: 9 fullname: Meyer, Charles R – sequence: 10 fullname: Rehemtulla, Alnawaz – sequence: 11 fullname: Ross, Brian D – sequence: 12 fullname: Galbán, Craig J |
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CitedBy_id | crossref_primary_10_1016_j_clinbiomech_2018_05_014 crossref_primary_10_1088_1742_6596_489_1_012032 crossref_primary_10_1002_jor_22407 crossref_primary_10_1088_1742_6596_489_1_012031 crossref_primary_10_1164_rccm_201604_0871OC crossref_primary_10_1593_tlo_14121 crossref_primary_10_1007_s00261_014_0087_z crossref_primary_10_1148_radiol_2021210658 crossref_primary_10_1371_journal_pone_0123877 crossref_primary_10_1088_0031_9155_59_22_7039 crossref_primary_10_1148_radiol_2015151484 |
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Keywords | Response Osteoporosis CT Biomarker Ovariectomy Imaging Cartography Radiodiagnosis Rat Diseases of the osteoarticular system Rodentia Biological marker Vertebrata Mammalia Treatment Surgery Animal Morphology Medical imagery Models Computerized axial tomography Osteopenia |
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Snippet | Abstract Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and... Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization.... |
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StartPage | 78 |
SubjectTerms | Animals Biological and medical sciences Biomarker Bone Density - physiology Diseases of the osteoarticular system Female Fundamental and applied biological sciences. Psychology Imaging Medical sciences Orthopedics Osteoporosis Osteoporosis - diagnosis Osteoporosis - diagnostic imaging Osteoporosis. Osteomalacia. Paget disease Ovariectomy Radiography Rats Rats, Sprague-Dawley Response Surgery (general aspects). Transplantations, organ and tissue grafts. Graft diseases Surgery of the genital tract and mammary gland Vertebrates: anatomy and physiology, studies on body, several organs or systems |
Title | Parametric response mapping of CT images provides early detection of local bone loss in a rat model of osteoporosis |
URI | https://www.clinicalkey.es/playcontent/1-s2.0-S8756328212008289 https://dx.doi.org/10.1016/j.bone.2012.04.005 https://www.ncbi.nlm.nih.gov/pubmed/22542461 https://search.proquest.com/docview/1019619958 https://search.proquest.com/docview/1635043219 https://pubmed.ncbi.nlm.nih.gov/PMC3371150 |
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