Literature DB >> 34479191

Improved estimates of strength and stiffness in pathologic vertebrae with bone metastases using CT-derived bone density compared with radiographic bone lesion quality classification.

Ron N Alkalay1, Michael W Groff2, Marc A Stadelmann3, Florian M Buck4, Sven Hoppe5, Nicolas Theumann6, Umesh Mektar7, Roger B Davis8, David B Hackney9.   

Abstract

OBJECTIVE: The aim of this study was to compare the ability of 1) CT-derived bone lesion quality (classification of vertebral bone metastases [BM]) and 2) computed CT-measured volumetric bone mineral density (vBMD) for evaluating the strength and stiffness of cadaver vertebrae from donors with metastatic spinal disease.
METHODS: Forty-five thoracic and lumbar vertebrae were obtained from cadaver spines of 11 donors with breast, esophageal, kidney, lung, or prostate cancer. Each vertebra was imaged using microCT (21.4 μm), vBMD, and bone volume to total volume were computed, and compressive strength and stiffness experimentally measured. The microCT images were reconstructed at 1-mm voxel size to simulate axial and sagittal clinical CT images. Five expert clinicians blindly classified the images according to bone lesion quality (osteolytic, osteoblastic, mixed, or healthy). Fleiss' kappa test was used to test agreement among 5 clinical raters for classifying bone lesion quality. Kruskal-Wallis ANOVA was used to test the difference in vertebral strength and stiffness based on bone lesion quality. Multivariable regression analysis was used to test the independent contribution of bone lesion quality, computed vBMD, age, gender, and race for predicting vertebral strength and stiffness.
RESULTS: A low interrater agreement was found for bone lesion quality (κ = 0.19). Although the osteoblastic vertebrae showed significantly higher strength than osteolytic vertebrae (p = 0.0148), the multivariable analysis showed that bone lesion quality explained 19% of the variability in vertebral strength and 13% in vertebral stiffness. The computed vBMD explained 75% of vertebral strength (p < 0.0001) and 48% of stiffness (p < 0.0001) variability. The type of BM affected vBMD-based estimates of vertebral strength, explaining 75% of strength variability in osteoblastic vertebrae (R2 = 0.75, p < 0.0001) but only 41% in vertebrae with mixed bone metastasis (R2 = 0.41, p = 0.0168), and 39% in osteolytic vertebrae (R2 = 0.39, p = 0.0381). For vertebral stiffness, vBMD was only associated with that of osteoblastic vertebrae (R2 = 0.44, p = 0.0024). Age and race inconsistently affected the model's strength and stiffness predictions.
CONCLUSIONS: Pathologic vertebral fracture occurs when the metastatic lesion degrades vertebral strength, rendering it unable to carry daily loads. This study demonstrated the limitation of qualitative clinical classification of bone lesion quality for predicting pathologic vertebral strength and stiffness. Computed CT-derived vBMD more reliably estimated vertebral strength and stiffness. Replacing the qualitative clinical classification with computed vBMD estimates may improve the prediction of vertebral fracture risk.

Entities:  

Keywords:  bone mineral density; mechanical testing; oncology; prediction of pathologic vertebral mechanics; radiographic classification; vertebral bone metastases

Mesh:

Year:  2021        PMID: 34479191      PMCID: PMC9210826          DOI: 10.3171/2021.2.SPINE202027

Source DB:  PubMed          Journal:  J Neurosurg Spine        ISSN: 1547-5646


  37 in total

1.  Strength reductions of thoracic vertebrae in the presence of transcortical osseous defects: effects of defect location, pedicle disruption, and defect size.

Authors:  M J Silva; J A Hipp; D P McGowan; T Takeuchi; W C Hayes
Journal:  Eur Spine J       Date:  1993-10       Impact factor: 3.134

Review 2.  Intra- and interobserver reliability of the Spinal Instability Neoplastic Score system for instability in spine metastases: a systematic review and meta-analysis.

Authors:  Zach Pennington; A Karim Ahmed; Ethan Cottrill; Erick M Westbroek; Matthew L Goodwin; Daniel M Sciubba
Journal:  Ann Transl Med       Date:  2019-05

Review 3.  Cancer treatment and survivorship statistics, 2012.

Authors:  Rebecca Siegel; Carol DeSantis; Katherine Virgo; Kevin Stein; Angela Mariotto; Tenbroeck Smith; Dexter Cooper; Ted Gansler; Catherine Lerro; Stacey Fedewa; Chunchieh Lin; Corinne Leach; Rachel Spillers Cannady; Hyunsoon Cho; Steve Scoppa; Mark Hachey; Rebecca Kirch; Ahmedin Jemal; Elizabeth Ward
Journal:  CA Cancer J Clin       Date:  2012-06-14       Impact factor: 508.702

Review 4.  Molecular Regulation of Bone Metastasis Pathogenesis.

Authors:  Meng-Yu Wu; Chia-Jung Li; Giou-Teng Yiang; Yeung-Leung Cheng; Andy Po-Yi Tsai; Yueh-Tseng Hou; Yu-Chieh Ho; Ming-Feng Hou; Pei-Yi Chu
Journal:  Cell Physiol Biochem       Date:  2018-04-18

Review 5.  Contemporary spinal oncology treatment paradigms and outcomes for metastatic tumors to the spine: A systematic review of breast, prostate, renal, and lung metastases.

Authors:  Amy Yao; Christopher A Sarkiss; Travis R Ladner; Arthur L Jenkins
Journal:  J Clin Neurosci       Date:  2017-04-24       Impact factor: 1.961

Review 6.  Instability and impending instability of the thoracolumbar spine in patients with spinal metastases: a systematic review.

Authors:  Michael H Weber; Shane Burch; Jenny Buckley; Meic H Schmidt; Michael G Fehlings; Frank D Vrionis; Charles G Fisher
Journal:  Int J Oncol       Date:  2011-01       Impact factor: 5.650

7.  Clinical outcome of vertebral compression fracture after single fraction spine radiosurgery for spinal metastases.

Authors:  Isabelle M Germano; Andrea Carai; Puneet Pawha; Seth Blacksburg; Yeh-Chi Lo; Sheryl Green
Journal:  Clin Exp Metastasis       Date:  2015-11-17       Impact factor: 5.150

8.  Spine stereotactic body radiotherapy for renal cell cancer spinal metastases: analysis of outcomes and risk of vertebral compression fracture.

Authors:  Isabelle Thibault; Ameen Al-Omair; Giuseppina Laura Masucci; Laurence Masson-Côté; Fiona Lochray; Renée Korol; Lu Cheng; Wei Xu; Albert Yee; Michael G Fehlings; Georg A Bjarnason; Arjun Sahgal
Journal:  J Neurosurg Spine       Date:  2014-08-29

9.  μFE models can represent microdamaged regions of healthy and metastatically involved whole vertebrae identified through histology and contrast enhanced μCT imaging.

Authors:  Chetan Choudhari; Katelyn Chan; Margarete K Akens; Cari M Whyne
Journal:  J Biomech       Date:  2016-02-24       Impact factor: 2.712

10.  Conventional finite element models estimate the strength of metastatic human vertebrae despite alterations of the bone's tissue and structure.

Authors:  Marc A Stadelmann; Denis E Schenk; Ghislain Maquer; Christopher Lenherr; Florian M Buck; Dieter D Bosshardt; Sven Hoppe; Nicolas Theumann; Ron N Alkalay; Philippe K Zysset
Journal:  Bone       Date:  2020-08-20       Impact factor: 4.626

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  2 in total

1.  Finite Element Analysis of Osteoporotic and Osteoblastic Vertebrae and Its Association With the Proton Density Fat Fraction From Chemical Shift Encoding-Based Water-Fat MRI - A Preliminary Study.

Authors:  Tobias Greve; Nithin Manohar Rayudu; Michael Dieckmeyer; Christof Boehm; Stefan Ruschke; Egon Burian; Christopher Kloth; Jan S Kirschke; Dimitrios C Karampinos; Thomas Baum; Karupppasamy Subburaj; Nico Sollmann
Journal:  Front Endocrinol (Lausanne)       Date:  2022-07-11       Impact factor: 6.055

2.  Evaluation of Load-To-Strength Ratios in Metastatic Vertebrae and Comparison With Age- and Sex-Matched Healthy Individuals.

Authors:  Dennis E Anderson; Michael W Groff; Thomas F Flood; Brett T Allaire; Roger B Davis; Marc A Stadelmann; Philippe K Zysset; Ron N Alkalay
Journal:  Front Bioeng Biotechnol       Date:  2022-08-05
  2 in total

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