Evidence map›Paper›PMID 34479191›Full record

ArticleJournal of neurosurgery. Spine2022

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 Alkalay, Michael W Groff, Marc A Stadelmann, Florian M Buck, Sven Hoppe, Nicolas Theumann, Umesh Mektar, Roger B Davis, David B Hackney

Open access · greenAbstract read
In one paragraph

Article in Journal of neurosurgery. Spine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 7 institutions in 3 countries.

Ron N Alkalay1Center for Advanced Orthopedic Studies, Department of Orthopedic Surgery.
Michael W Groff2Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts.
Marc A Stadelmann3ARTORG Center for Biomedical Engineering Research, University of Bern.
Florian M Buck4University of Zurich & MRI Schulthess Clinic, Zurich.
Sven Hoppe5Department of Orthopedic Surgery, Inselspital, Bern University Hospital, Bern; and.
Nicolas Theumann6Clinique Bois-Cerf, Radiology Department, Lausanne, Switzerland.
Umesh Mektar7Department of Orthopedics.
Roger B Davis8Department of Medicine, and.
David B Hackney9Department of Radiology, Beth Israel Deaconess Medical Center, Boston.
Advanced Center for Orthopedics · USBrigham and Women's Hospital · USHadassah Medical Center · ILHirslanden Clinique Bois-Cerf · CHSchulthess-Klinik · CHUniversity Hospital of Bern · CHUniversity of Bern · CH

Funding

The Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0M
Predicting Fracture Risk in Patients Treated with Radiotherapy for Spinal Metastatic DiseaseR01AR075964 · NIAMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI ALKALAY, RON N, BALBONI, TRACY A. · 2020 to 2024
$3.2M
Pre-Operative QCT Planning Protocol for Treating the Structural Deficiency of SpiR01AR055582 · NIAMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI ALKALAY, RON N · 2008 to 2011
$1.5M
Predicting Fracture Risk in Patients Treated with Radiotherapy for Spinal Metastatic DiseaseR56AR075964 · NIAMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI ALKALAY, RON N, BALBONI, TRACY A. · 2019 to 2019
$662k
NCATS NIH HHS UL1 TR002541NIAMS NIH HHS R01 AR055582NIAMS NIH HHS R01 AR075964NIAMS NIH HHS R56 AR075964
6 · The paper itself

Abstract

objectiveThe 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.

methodsForty-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.

resultsA 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.

conclusionsPathologic 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.

Indexed as

Bone DensityTomography, X-Ray ComputedAgedCadaverFemaleHumansLumbar VertebraeMaleMiddle AgedObserver VariationReproducibility of ResultsSpinal NeoplasmsThoracic Vertebraebone mineral densitymechanical testingoncologyprediction of pathologic vertebral mechanicsradiographic classificationvertebral bone metastases

Identifiers

PMID34479191
PMCPMC9210826
OpenAlexW3196617480

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.