Risk of vertebral compression fractures in multiple myeloma patients: A finite-element study

Reduction of material groups for vertebral bone finite element simulation: cross comparison of grouping methods

In patient-specific biomechanical modeling, the process of image-to-mesh-material mapping is important, and various strategies have been explored for assigning the number of groups of unique material properties to the mesh. This study aims to cross-compare different grouping strategies to identify the minimum number of unique groups necessary for accurately calculating the fracture load of vertebral bones. We analyzed 12 vertebral specimens by experimentally determining the biomechanical fracture load and acquiring corresponding CT scans. After geometry extraction and meshing, we applied commonly used fixed-value strategies for reducing the number of unique groups, such as Modulus Gaping and Percentual Thresholding. Additionally, we introduced a patient-specific adaptive grouping method based on K-means clustering, which allowed us to maintain a consistent number of groups of unique material properties across the study. A total of 204 simulations were performed, achieving a potential 98% reduction in the number of individual material parameters while maintaining a strong correlation with experimental results when utilizing Percentual Thresholding or Adaptive Clustering, compared to Modulus Gaping. The findings demonstrate the feasibility of significantly reducing simulation complexity while maintaining the accuracy of patient-specific models that strongly correlate with experimental results. This reduction enables efficient processing of patient-specific biomechanical models derived from image data, offering potential benefits for clinicians, particularly in resource-constrained settings.

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

Fracture rate after conventional external beam radiation therapy to the spine in multiple myeloma patients

BACKGROUND CONTEXT

Conventional external beam radiation therapy (cEBRT) is used in multiple myeloma (MM) to treat severe pain, spinal cord compression, and disease-related bone disease. However, radiation may be associated with an increased risk of vertebral compression fractures (VCFs), which could substantially impair survival and quality of life. Additionally, the use of the Spinal Instability Neoplastic Score (SINS) in MM is debated in MM.

PURPOSE

To determine the incidence of VCFs after cEBRT in patients with MM and to assess the applicability of the SINS score in the prediction of VCFs in MM.

STUDY DESIGN

Retrospective multicenter cohort study.

PATIENT SAMPLE

MM patients with spinal myeloma lesions who underwent cEBRT between January 2010 and December 2021.

OUTCOME MEASURES

Frequency of new or progressed VCFs and subdistribution hazard ratios for potentially associated factors.

METHODS

Patient and treatment characteristics were manually collected from the patients' electronic medical records. Computed tomography (CT) scans from before and up to 3 years after the start of radiation were used to score radiographic variables at baseline and at follow-up. Multivariable Fine and Gray competing risk analyses were performed to evaluate the diagnostic value of the SINS score to predict the postradiation VCF rate.

RESULTS

A total of 127 patients with 427 eligible radiated vertebrae were included in this study. The mean age at radiation was 64 years, and 66.1% of them were male. At the start of radiation, 57 patients (44.9%) had at least one VCF. There were 89 preexisting VCFs (18.4% of 483 vertebrae). Overall, 39 of 127 patients (30.7%) reported new fractures (number of vertebrae (n)=12) or showed progression of existing fractures (n=36). This number represented 11.2% of all radiated vertebrae. Five of the 39 (12.8%) patients with new or worsened VCFs received an unplanned secondary treatment (augmentation [n=2] or open surgery [n=3]) within 3 years. Both the total SINS score (SHR 1.77; 95% confidence interval (CI) 1.54-2.03; p<.001) and categorical SINS score (SHR 10.83; 95% CI 4.20-27.94; p<.001) showed an independent association with higher rates of new or progressed VCFs in adjusted analyses. The use of bisphosphonates was independently associated with a lower rate of new or progressed VCFs (SHR 0.47 [95% CI 0.24-0.92; p=.027]).

CONCLUSIONS

This study demonstrated that new or progressed VCFs occurred in 30.7% of patients within 3 years, in a total of 11.2% of vertebrae. The SINS score was found to be independently associated with the development or progression of VCFs and could thus be applied in MM for fracture prediction and possibly prevention.

Patient-Specific Finite Element Modeling of the Whole Lumbar Spine Using Clinical Routine Multi-Detector Computed Tomography (MDCT) Data-A Pilot Study

(1) Background: To study the feasibility of developing finite element (FE) models of the whole lumbar spine using clinical routine multi-detector computed tomography (MDCT) scans to predict failure load (FL) and range of motion (ROM) parameters. (2) Methods: MDCT scans of 12 subjects (6 healthy controls (HC), mean age ± standard deviation (SD): 62.16 ± 10.24 years, and 6 osteoporotic patients (OP), mean age ± SD: 65.83 ± 11.19 years) were included in the current study. Comprehensive FE models of the lumbar spine (5 vertebrae + 4 intervertebral discs (IVDs) + ligaments) were generated (L1−L5) and simulated. The coefficients of correlation (ρ) were calculated to investigate the relationship between FE-based FL and ROM parameters and bone mineral density (BMD) values of L1−L3 derived from MDCT (BMDQCT-L1-3). Finally, Mann−Whitney U tests were performed to analyze differences in FL and ROM parameters between HC and OP cohorts. (3) Results: Mean FE-based FL value of the HC cohort was significantly higher than that of the OP cohort (1471.50 ± 275.69 N (HC) vs. 763.33 ± 166.70 N (OP), p < 0.01). A strong correlation of 0.8 (p < 0.01) was observed between FE-based FL and BMDQCT-L1-L3 values. However, no significant differences were observed between ROM parameters of HC and OP cohorts (p = 0.69 for flexion; p = 0.69 for extension; p = 0.47 for lateral bending; p = 0.13 for twisting). In addition, no statistically significant correlations were observed between ROM parameters and BMDQCT- L1-3. (4) Conclusions: Clinical routine MDCT data can be used for patient-specific FE modeling of the whole lumbar spine. ROM parameters do not seem to be significantly altered between HC and OP. In contrast, FE-derived FL may help identify patients with increased osteoporotic fracture risk in the future.

Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure

Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.

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

PURPOSE

Osteoporosis is prevalent and entails alterations of vertebral bone and marrow. Yet, the spine is also a common site of metastatic spread. Parameters that can be non-invasively measured and could capture these alterations are the volumetric bone mineral density (vBMD), proton density fat fraction (PDFF) as an estimate of relative fat content, and failure displacement and load from finite element analysis (FEA) for assessment of bone strength. This study's purpose was to investigate if osteoporotic and osteoblastic metastatic changes in lumbar vertebrae can be differentiated based on the abovementioned parameters (vBMD, PDFF, and measures from FEA), and how these parameters correlate with each other.

MATERIALS AND METHODS

Seven patients (3 females, median age: 77.5 years) who received 3-Tesla magnetic resonance imaging (MRI) and multi-detector computed tomography (CT) of the lumbar spine and were diagnosed with either osteoporosis (4 patients) or diffuse osteoblastic metastases (3 patients) were included. Chemical shift encoding-based water-fat MRI (CSE-MRI) was used to extract the PDFF, while vBMD was extracted after automated vertebral body segmentation using CT. Segmentation masks were used for FEA-based failure displacement and failure load calculations. Failure displacement, failure load, and PDFF were compared between patients with osteoporotic vertebrae versus patients with osteoblastic metastases, considering non-fractured vertebrae (L1-L4). Associations between those parameters were assessed using Spearman correlation.

RESULTS

Median vBMD was 59.3 mg/cm³ in osteoporotic patients. Median PDFF was lower in the metastatic compared to the osteoporotic patients (11.9% vs. 43.8%, p=0.032). Median failure displacement and failure load were significantly higher in metastatic compared to osteoporotic patients (0.874 mm vs. 0.348 mm, 29,589 N vs. 3,095 N, p=0.034 each). A strong correlation was noted between PDFF and failure displacement (rho -0.679, p=0.094). A very strong correlation was noted between PDFF and failure load (rho -0.893, p=0.007).

CONCLUSION

PDFF as well as failure displacement and load allowed to distinguish osteoporotic from diffuse osteoblastic vertebrae. Our findings further show strong associations between PDFF and failure displacement and load, thus may indicate complimentary pathophysiological associations derived from two non-invasive techniques (CSE-MRI and CT) that inherently measure different properties of vertebral bone and marrow.

Fracture Risk Evaluation of Bone Metastases: A Burning Issue

Major progress has been achieved to treat cancer patients and survival has improved considerably, even for stage-IV bone metastatic patients. Locomotive health has become a crucial issue for patient autonomy and quality of life. The centerpiece of the reflection lies in the fracture risk evaluation of bone metastasis to guide physician decision regarding physical activity, antiresorptive agent prescription, and local intervention by radiotherapy, surgery, and interventional radiology. A key mandatory step, since bone metastases may be asymptomatic and disseminated throughout the skeleton, is to identify the bone metastasis location by cartography, especially within weight-bearing bones. For every location, the fracture risk evaluation relies on qualitative approaches using imagery and scores such as Mirels and spinal instability neoplastic score (SINS). This approach, however, has important limitations and there is a need to develop new tools for bone metastatic and myeloma fracture risk evaluation. Personalized numerical simulation qCT-based imaging constitutes one of these emerging tools to assess bone tumoral strength and estimate the femoral and vertebral fracture risk. The next generation of numerical simulation and artificial intelligence will take into account multiple loadings to integrate movement and obtain conditions even closer to real-life, in order to guide patient rehabilitation and activity within a personalized-medicine approach.

MDCT-Based Finite Element Analysis for the Prediction of Functional Spine Unit Strength-An In Vitro Study

(1) Objective: This study aimed to analyze the effect of ligaments on the strength of functional spine unit (FSU) assessed by finite element (FE) analysis of anatomical models developed from multi-detector computed tomography (MDCT) data. (2) Methods: MDCT scans for cadaveric specimens were acquired from 16 donors (7 males, mean age of 84.29 ± 6.06 years and 9 females, mean age of 81.00 ± 11.52 years). Two sets of FSU models (three vertebrae + two disks), one with and another without (w/o) ligaments, were generated. The vertebrae were segmented semi-automatically, intervertebral disks (IVD) were generated manually, and ligaments were modeled based on the anatomical location. FE-predicted failure loads of FSU models (with and w/o ligaments) were compared with the experimental failure loads obtained from the uniaxial biomechanical test of specimens. (3) Results: The mean and standard deviation of the experimental failure load of FSU specimens was 3513 ± 1029 N, whereas of FE-based failure loads were 2942 ± 943 N and 2537 ± 929 N for FSU models with ligaments and without ligament attachments, respectively. A good correlation (ρ = 0.79, and ρ = 0.75) was observed between the experimental and FE-based failure loads for the FSU model with and with ligaments, respectively. (4) Conclusions: The FE-based FSU model can be used to determine bone strength, and the ligaments seem to have an effect on the model accuracy for the failure load calculation; further studies are needed to understand the contribution of ligaments.

MDCT-Based Finite Element Analyses: Are Measurements at the Lumbar Spine Associated with the Biomechanical Strength of Functional Spinal Units of Incidental Osteoporotic Fractures along the Thoracolumbar Spine?

Assessment of osteoporosis-associated fracture risk during clinical routine is based on the evaluation of clinical risk factors and T-scores, as derived from measurements of areal bone mineral density (aBMD). However, these parameters are limited in their ability to identify patients at high fracture risk. Finite element models (FEMs) have shown to improve bone strength prediction beyond aBMD. This study aims to investigate whether FEM measurements at the lumbar spine can predict the biomechanical strength of functional spinal units (FSUs) with incidental osteoporotic vertebral fractures (VFs) along the thoracolumbar spine. Multi-detector computed tomography (MDCT) data of 11 patients (5 females and 6 males, median age: 67 years) who underwent MDCT twice (median interval between baseline and follow-up MDCT: 18 months) and sustained an incidental osteoporotic VF between baseline and follow-up scanning were used. Based on baseline MDCT data, two FSUs consisting of vertebral bodies and intervertebral discs (IVDs) were modeled: one standardly capturing L1-IVD-L2-IVD-L3 (FSU_L1-L3) and one modeling the incidentally fractured vertebral body at the center of the FSU (FSU_F). Furthermore, volumetric BMD (vBMD) derived from MDCT, FEM-based displacement, and FEM-based load of the single vertebrae L1 to L3 were determined. Statistically significant correlations (adjusted for a BMD ratio of fracture/L1-L3 segments) were revealed between the FSU_F and mean load of L1 to L3 (r = 0.814, p = 0.004) and the mean vBMD of L1 to L3 (r = 0.745, p = 0.013), whereas there was no statistically significant association between the FSU_F and FSU_L1-L3 or between FSU_F and the mean displacement of L1 to L3 (p > 0.05). In conclusion, FEM measurements of single vertebrae at the lumbar spine may be able to predict the biomechanical strength of incidentally fractured vertebral segments along the thoracolumbar spine, while FSUs seem to predict only segment-specific fracture risk.

Prediction of Incidental Osteoporotic Fractures at Vertebral-Specific Level Using 3D Non-Linear Finite Element Parameters Derived from Routine Abdominal MDCT

To investigate whether finite element (FE) analysis of the spine in routine thoracic/abdominal multi-detector computed tomography (MDCT) can predict incidental osteoporotic fractures at vertebral-specific level; Baseline routine thoracic/abdominal MDCT scans of 16 subjects (8(m), mean age: 66.1 ± 8.2 years and 8(f), mean age: 64.3 ± 9.5 years) who sustained incidental osteoporotic vertebral fractures as confirmed in follow-up MDCTs were included in the current study. Thoracic and lumbar vertebrae (T5-L5) were automatically segmented, and bone mineral density (BMD), finite element (FE)-based failure-load, and failure-displacement were determined. These values of individual vertebrae were normalized globally (g), by dividing the absolute value with the average of L1-3 and locally by dividing the absolute value with the average of T5-12 and L1-5 for thoracic and lumbar vertebrae, respectively. Mean-BMD of L1-3 was determined as reference. Receiver operating characteristics (ROC) and area under the curve (AUC) were calculated for different normalized FE (Kload, Kdisplacement,K(load)g, and K(displacement)g) and BMD (KBMD, and K(BMD)g) ratio parameter combinations for identifying incidental fractures. Kload, K(load)g, KBMD, and K(BMD)g showed significantly higher discriminative power compared to standard mean BMD of L1-3 (BMDStandard) (AUC = 0.67 for Kload; 0.64 for K(load)g; 0.64 for KBMD; 0.61 for K(BMD)g vs. 0.54 for BMDStandard). The combination of Kload, Kdisplacement, and KBMD increased the AUC further up to 0.77 (p < 0.001). The combination of FE with BMD measurements derived from routine thoracic/abdominal MDCT allowed an improved prediction of incidental fractures at vertebral-specific level.

Predicting Vertebral Bone Strength Using Finite Element Analysis for Opportunistic Osteoporosis Screening in Routine Multidetector Computed Tomography Scans-A Feasibility Study

Purpose

To investigate the feasibility of using routine clinical multidetector computed tomography (MDCT) scans for conducting finite element (FE) analysis to predict vertebral bone strength for opportunistic osteoporosis screening.

Methods

Routine abdominal MDCT with and without intravenous contrast medium (IVCM) of seven subjects (five male; two female; mean age: 71.86 ± 7.40 years) without any bone disease were used. FE analysis was performed on individual vertebrae (T11, T12, L1, and L2) including the posterior elements to investigate the effect of IVCM and slice thickness (1 and 3 mm) on vertebral bone strength. Another subset of data from subjects with vs. without osteoporotic vertebral fractures (n = 9 age and gender-matched pairs) was analyzed for investigating the ability of FE-analysis to differentiate the two cohorts. Bland-Altman plots, box plots, and coefficient of correlation (R2) were calculated to determine the variations in FE-predicted failure loads for different conditions.

Results

The FE-predicted failure loads obtained from routine MDCT scans were strongly correlated with those from without IVCM (R2 = 0.91 for 1mm; R2 = 0.92 for 3mm slice thickness, respectively) and different slice thicknesses (R2 = 0.93 for 1mm vs. 3mm with IVCM). Furthermore, a good correlation was observed for 3mm slice thickness with IVCM vs. 1mm without IVCM (R2 = 0.87). Significant difference between FE-predicted failure loads of healthy and fractured patients was observed (4,705 ± 1,238 vs. 4,010 ± 1,297 N; p=0.026).

Conclusion

Routine clinical MDCT scans could be reliably used for assessment of fracture risk based on FE analysis and may be beneficial for patients who are at increased risk for osteoporotic fractures.

Identifying predictive factors for vertebral collapse fractures in multiple myeloma patients

BACKGROUND CONTEXT

Vertebral compression fractures (VCFs) are a common complication for patients with multiple myeloma. These fractures are associated with significant morbidity and mortality due to severe back pain, spinal instability, increased risk of new fractures, neurologic dysfunction, and other physical symptoms.

PURPOSE

To identify risk factors associated with the development of VCFs which may help to predict them in future patients.

STUDY DESIGN

A retrospective multicenter cohort study.

PATIENT SAMPLE

Patients with multiple myeloma diagnosed between 2012 and 2018 and appropriate baseline- and follow-up imaging studies (>6 months after diagnosis) were included.

OUTCOME MEASURES

Individual odds ratios for each of the fifteen potential risk factors including patient factors and radiographical characteristics.

METHODS

Relevant clinical baseline data were extracted from the patient charts. Computed tomography (CT) scans were used to score all radiographic variables. VCFs were graded following the Genant grading system. General Linear Mixed Models were used to analyze risk factors associated with vertebral fractures.

RESULTS

A total of 143 patients with 1,605 eligible vertebrae were included in the study with a mean follow-up time of 25 months. Mean age at diagnosis was 65 years and 39% were female. Among 1,605 vertebrae, there were 192 (12%) VCFs (Genant grade 1 or higher) at the time of diagnosis and 111 (7%) occurred during follow-up. In a General Linear Mixed Model, significant predictors were gender (odds ratio [OR]=1.5), International Staging System stage 2 and 3 (OR=3.6 and OR=4.1 respectively), and back pain (OR=2.7). Furthermore, lower Hounsfield Unit score, lytic lesions and abnormal alignment were risk factors for (the development of) VCFs.

CONCLUSIONS

This study investigated both patient characteristics and vertebra-specific risk factors for VFCs in multiple myeloma patients. The factors found in this study might be useful for identifying patients at higher risk of VFCs to help clinical management to prevent vertebral collapse and the development of spinal deformities.

Effect of the intervertebral disc on vertebral bone strength prediction: a finite-element study

BACKGROUND CONTEXT

Osteoporotic vertebral fractures (OVFs) are a prevalent skeletal condition in the elderly but the mechanism behind these fractures remain unclear due to the complex biomechanical interplay between spinal segments such as the vertebra and intervertebral discs (IVDs).

PURPOSE

To investigate the biomechanical influence of IVDs by (1) comparing finite element (FE)-predicted failure load with experimentally measured failure load of functional spinal units (FSUs) and (2) comparing this correlation with those of FE-predicted failure load and bone mineral density (BMD) of the single central vertebra with experimentally measured failure load.

STUDY DESIGN

A computational biomechanical analysis.

PATIENT SAMPLE

Ten thoracic FSUs consisting of a central vertebra, the adjacent IVDs, and the upper and lower halves of the adjacent vertebrae were harvested from formalin-fixed human donors (4 males, 6 females; mean age of 82±9 years).

OUTCOME MEASURES

The outcome measures included the prediction of vertebral strength and determination of BMD in FSUs and the single central vertebra and the correlation of both measures with experimentally measured vertebral strength of the FSUs.

METHODS

The FSUs underwent clinical multidetector computed tomography (MDCT) (spatial resolution: 250×250×600 μm³). BMD was determined for the FSUs from the MDCT images of the central vertebrae. FE-predicted failure load was calculated in the single central vertebra of the FSUs alone and the entire FSUs. Experimentally measured failure load of the FSUs was determined in a uniaxial biomechanical test.

RESULTS

BMD of the central vertebrae correlated significantly with experimentally measured failure load (R²=0.66, p<.02), whereas FE-predicted failure load of the central vertebra showed no significant correlation with experimentally measured failure load (p=.07). However, FE-predicted failure load of FSUs best predicted experimentally measured failure load of FSUs (R²=0.93, p<.0001).

CONCLUSIONS

This study demonstrated that routine clinical MDCT images can be an accurate and feasible tool for prediction of OVFs using patient-specific FE analysis of FSU models.

CLINICAL SIGNIFICANCE

Improved management of OVFs is essential amidst current clinical challenges. Implementation of a vertebral strength assessment tool could result in more accurate prediction of osteoporotic fracture risk and aid clinicians with better targeted early treatment strategies.

Low-dose and sparse sampling MDCT-based femoral bone strength prediction using finite element analysis

This study aims to evaluate the impact of dose reduction through tube current and sparse sampling on multi-detector computed tomography (MDCT)-based femoral bone strength prediction using finite element (FE) analysis. FE-predicted femoral failure load obtained from MDCT scan data was not significantly affected by 50% dose reductions through sparse sampling. Further decrease in dose through sparse sampling (25% of original projections) and virtually reduced tube current (50% and 25% of the original dose) showed significant effects on the FE-predicted failure load results.

PURPOSE

To investigate the effect of virtually reduced tube current and sparse sampling on multi-detector computed tomography (MDCT)-based femoral bone strength prediction using finite element (FE) analysis.

METHODS

Routine MDCT data covering the proximal femur of 21 subjects (17 males; 4 females; mean age, 71.0 ± 8.8 years) without any bone diseases aside from osteoporosis were included in this study. Fifty percent and 75% dose reductions were achieved by virtually reducing tube current and by applying a sparse sampling strategy from the raw image data. Images were then reconstructed with a statistically iterative reconstruction algorithm. FE analysis was performed on all reconstructed images and the failure load was calculated. The root mean square coefficient of variation (RMSCV) and coefficient of correlation (R²) were calculated to determine the variation in the FE-predicted failure load data for dose reductions, using original-dose MDCT scan as the standard of reference.

RESULTS

Fifty percent dose reduction through sparse sampling showed lower RMSCV and higher correlations when compared with virtually reduced tube current method (RMSCV = 5.70%, R² = 0.96 vs. RMSCV = 20.78%, R² = 0.79). Seventy-five percent dose reduction achieved through both methods (RMSCV = 22.38%, R² = 0.80 for sparse sampling; RMSCV = 24.58%, R² = 0.73 for reduced tube current) could not predict the failure load accurately.

CONCLUSION

Our simulations indicate that up to 50% reduction in radiation dose through sparse sampling can be used for FE-based prediction of femoral failure load. Sparse-sampled MDCT may allow fracture risk prediction and treatment monitoring in osteoporosis with less radiation exposure in the future.

Effect of Statistically Iterative Image Reconstruction on Vertebral Bone Strength Prediction Using Bone Mineral Density and Finite Element Modeling: A Preliminary Study

Statistical iterative reconstruction (SIR) using multidetector computed tomography (MDCT) is a promising alternative to standard filtered back projection (FBP), because of lower noise generation while maintaining image quality. Hence, we investigated the feasibility of SIR in predicting MDCT-based bone mineral density (BMD) and vertebral bone strength from finite element (FE) analysis. The BMD and FE-predicted bone strength derived from MDCT images reconstructed using standard FBP (FFBP) and SIR with (FSIR) and without regularization (FSIRB0) were validated against experimental failure loads (Fexp). Statistical iterative reconstruction produced the best quality images with regard to noise, signal-to-noise ratio, and contrast-to-noise ratio. Fexp significantly correlated with FFBP, FSIR, and FSIRB0. FFBP had a significant correlation with FSIRB0 and FSIR. The BMD derived from FBP, SIRB0, and SIR were significantly correlated. Effects of regularization should be further investigated with FE and BMD analysis to allow for an optimal iterative reconstruction algorithm to be implemented in an in vivo scenario.

MDCT-based Finite Element Analysis of Vertebral Fracture Risk: What Dose is Needed?

PURPOSE

The aim of this study was to compare vertebral failure loads, predicted from finite element (FE) analysis of patients with and without osteoporotic vertebral fractures (OVF) at virtually reduced dose levels, compared to standard-dose exposure from multidetector computed tomography (MDCT) imaging and evaluate whether ultra-low dose derived FE analysis can still differentiate patient groups.

MATERIALS AND METHODS

An institutional review board (IRB) approval was obtained for this retrospective study. A total of 16 patients were evaluated at standard-dose MDCT; eight with and eight without OVF. Images were reconstructed at virtually reduced dose levels (i. e. half, quarter and tenth of the standard dose). Failure load was determined at L1-3 from FE analysis and compared between standard, half, quarter, and tenth doses and used to differentiate between fracture and control groups.

RESULTS

Failure load derived at standard dose (3254 ± 909 N and 3794 ± 984 N) did not significantly differ from half (3390 ± 890 N and 3860 ± 1063 N) and quarter dose (3375 ± 915 N and 3925 ± 990 N) but was significantly higher for one tenth dose (4513 ± 1762 N and 4766 ± 1628 N) for fracture and control groups, respectively. Failure load differed significantly between the two groups at standard, half and quarter doses, but not at tenth dose. Receiver operating characteristic (ROC) curve analysis also demonstrated that standard, half, and quarter doses can significantly differentiate the fracture from the control group.

CONCLUSION

The use of MDCT enables a dose reduction of at least 75% compared to standard-dose for an adequate prediction of vertebral failure load based on non-invasive FE analysis.