Metastatic spine disease alters spinal load-to-strength ratios in patients compared to healthy individuals

Abstract

Pathologic vertebral fractures (PVF) are common and serious complications in patients with metastatic lesions affecting the spine. Accurate assessment of cancer patients' PVF risk is an unmet clinical need. Load-to-strength ratios (LSRs) evaluated in vivo by estimating vertebral loading from biomechanical modeling and strength from computed tomography imaging (CT) have been associated with osteoporotic vertebral fractures in older adults. Here, for the first time, we investigate LSRs of thoracic and lumbar vertebrae of 135 spine metastases patients compared to LSRs of 246 healthy adults, comparable by age and sex, from the Framingham Heart Study under four loading tasks. Findings include: (1) Osteolytic vertebrae have higher LSRs than osteosclerotic and mixed vertebrae; (2). In patients' vertebrae without CT observed metastases, LSRs were greater than healthy controls. (3) LSRs depend on the spinal region (Thoracic, Thoracolumbar, Lumbar). These findings suggest that LSRs may contribute to identifying patients at risk of incident PVF in metastatic spine disease patients. The lesion-mediated difference suggests that risk thresholds should be established based on spinal region, simulated task, and metastatic lesion type.

Keywords: Framingham Heart Study cohort; Metastatic Spinal disease; Patient cohort; load-to-strength ratio; musculoskeletal models; vertebral strength.

Figure 1:

Spine LSRs in healthy people from the Framingham Heart Study (FHS) and patients with spine metastases – grouped by lesion type in three spinal regions – separately for four loading tasks (Rows) and by sex (Columns). NOL = no observed lesion.

Figure 2:

Least Square Mean (LSM) differences in Standardized Spine LSRs (calculated as linear combinations from the mixed effects regression model, normalized to the Neutral Standing task) comparing patients with spine metastases and healthy people from the Framingham Heart Study (FHS), grouped by lesion type in three spinal regions – separately for four loading tasks (Rows) and by sex (Columns). NOL = no observed lesion; OL = osteolytic; OS = osteosclerotic; MX = mixed. *P < 0.05 & **P < 0.001, for comparison vs. FHS. ⁺P<0.05 & ⁺⁺P<0.001 for comparison of lesions vs. NOL; P values are adjusted for multiple testing by the FDR correction

Figure 3:

Compressive vertebral strength estimated from CT data in healthy people from the Framingham Heart Study (FHS) and patients with spine metastases – grouped by lesion type and spinal region. NOL = no observed lesion.

Figure 4

Standardized load to strength ratio (LSR) estimated from clinical CT derived musculoskeletal models in patients with spine metastases and in healthy people from the Framingham Heart Study (FHS)- grouped by primary cancer and sex. NOL = no observed lesion. Dotted line indicates mean LSR value for FHS subjects.

Figure 5

The workflow for establishing individualized cancer patient and FHS subjects’ musculoskeletal (MSK) models to estimate task-specific vertebral loading is as follows. The patient / subject CT data is used to extract the subject-specific information [A: sex, height/ weight, muscle morphology, and spinal curvature, required to adjust our generic MSK model to the subject [B] . We then apply external loading and postures to simulate our selected sets of activities (Natural standing, standing with a weight of 10kg (Wt), Forward Flexion + Wt and Lateral Bending + Wt) (C). We use static optimization to predict muscle forces and calculate spinal joint loading using the joint analysis tool in OpenSim . The outcome of this analysis is individual vertebral loading [D]. From the CT data, and for each vertebral level, we estimate the integral bone mineral density (iBMD) and measure the vertebral cross, sectional area (CSA), [E], from which we used regression equation established in QCT-based finite-element analysis (FEA) and validated in cadaveric cancer vertebrae , to predict vertebral strength from the CT data [F]. We then use the modeled vertebral loading and predicted strength to calculate the vertebral specific load-to-strength ratio (LSR) [G].