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

Simulated low-dose multi-detector computed tomography: spatial effects on surrogate parameters of bone strength at the proximal femur

This study investigated simulated tube current reduction and sparse sampling for low-dose computed tomography (CT) regarding volumetric bone mineral density (vBMD) and cortical bone thickness (Ct.Th) of the proximal femur. Sparse sampling with dose reductions of up to 90% may still allow extraction of bone strength parameters with clinically acceptable accuracy.

INTRODUCTION

We aimed to investigate effects of CT with simulated lowered tube current and sparse sampling on trabecular and cortical vBMD as well as Ct.Th of the entire proximal femur, its subregions, and with detailed spatial assessments.

METHODS

Clinical routine multi-detector CT (MDCT) scans covering the hips from 40 patients were used for simulations of low-dose imaging with 50% and 10% of the original tube current (D50, D10) or projections (P50, P10) combined with statistical iterative reconstruction (SIR), which were then compared against original data with full dose (D100 P100) regarding trabecular vBMD, cortical vBMD, and Ct.Th. An automated framework for multi-parametric assessments was used. Relative errors by comparing measures from original data and simulated low-dose data, regression analyses, Bland-Altman analyses, and statistical parametric mapping (SPM, to assess the spatial distribution of accuracy) were computed.

RESULTS

Sparse sampling enabled drastic reductions of radiation exposure (down to 10% of original imaging) while still producing determinants of bone strength with clinically acceptable relative changes. Lower biases according to Bland-Altman analyses were observed for sparse sampling compared to imaging with virtually lowered tube currents (D10 P100 versus D100 P10) regarding trabecular vBMD, cortical vBMD, as well as Ct.Th. Better accuracy across the whole proximal femur for D100 P50 than for D50 P100 and for D100 P10 than for D10 P100 was observed.

CONCLUSIONS

Sparse sampling with SIR may enable drastic reductions of radiation exposure (up to 90% of original doses) for opportunistically measuring image-based surrogate parameters of bone strength.

Continuum finite element analysis generalizesin vivotrabecular bone microstructural strength measures between two CT scanners with different image resolution

Fragility of trabecular bone (Tb) microstructure is increased in osteoporosis, which is associated with rapid bone loss and enhanced fracture-risk. Accurate assessment of Tb strength usingin vivoimaging available in clinical settings will be significant for management of osteoporosis and understanding its pathogenesis. Emerging CT technology, featured with high image resolution, fast scan-speed, and wide clinical access, is a promising alternative forin vivoTb imaging. However, variation in image resolution among different CT scanners pose a major hurdle in CT-based bone studies. This paper presents nonlinear continuum finite element (FE) methods for computation of Tb strength fromin vivoCT imaging and evaluates their generalizability between two scanners with different image resolution. Continuum FE-based measures of Tb strength under different loading conditions were found to be highly reproducible (ICC ≥ 0.93) using ankle images of twenty healthy volunteers acquired on low- and high-resolution CT scanners 44.6 ± 2.7 days apart. FE stress propagation was mostly confined to Tb micro-network (2.3 ± 1.7 MPa) with nominal leakages over the marrow space (0.4 ± 0.5 MPa) complying with the fundamental principle of mechanics atin vivoimaging. In summary, nonlinear continuum FE-based Tb strength measures are reproducible among different CT scanners and suitable for multi-site longitudinal human studies.

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.

CT ‐based Stiffness Measures of Trabecular Bone Microstructure — Cadaveric Validation and In Vivo Application

Osteoporosis causes bone fragility and elevates fracture risk. Applications of finite element (FE) analysis (FEA) for assessment of trabecular bone (Tb) microstructural strength at whole‐body computed tomography (CT) imaging are limited due to challenges with Tb microstructural segmentation. We present a nonlinear FEA method for distal tibia CT scans evading binary segmentation of Tb microstructure, while accounting for bone microstructural distribution. First, the tibial axis in a CT scan was aligned with the FE loading axis. FE cubic mesh elements were modeled using image voxels, and CT intensity values were calibrated to ash density defining mechanical properties at individual elements. For FEA of an upright volume of interest (VOI), the bottom surface was fixed, and a constant displacement was applied at each vertex on the top surface simulating different loading conditions. The method was implemented and optimized using the ANSYS software. CT‐derived computational modulus values were repeat scan reproducible (intraclass correlation coefficient [ICC] ≥ 0.97) and highly correlated (r ≥ 0.86) with the micro‐CT (μCT)‐derived values. FEA‐derived von Mises stresses over the segmented Tb microregion were significantly higher (p < 1 × 10⁻¹¹) than that over the marrow space. In vivo results showed that both shear and compressive modulus for males were higher (p < 0.01) than for females. Effect sizes for different modulus measures between males and females were moderate‐to‐high (≥0.55) and reduced to small‐to‐negligible (<0.40) when adjusted for pure lean mass. Among body size and composition attributes, pure lean mass and height showed highest (r ∈ [0.45 0.56]) and lowest (r ∈ [0.25 0.39]) linear correlation, respectively, with FE‐derived modulus measures. In summary, CT‐based nonlinear FEA provides an effective surrogate measure of Tb microstructural stiffness, and the relaxation of binary segmentation will extend the scope for FEA in human studies using in vivo imaging at relatively low‐resolution. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Finite element analysis of trabecular bone microstructure using CT imaging and continuum mechanical modelling

Purpose

Osteoporosis is a bone disease associated with enhanced bone loss, microstructural degeneration, and fracture‐risk. Finite element (FE) modeling is used to estimate trabecular bone (Tb) modulus from high‐resolution three‐dimensional (3‐D) imaging modalities including micro‐computed tomography (CT), magnetic resonance imaging (MRI), and high‐resolution peripheral quantitative CT (HR‐pQCT). This paper validates an application of voxel‐based continuum finite element analysis (FEA) to predict Tb modulus from clinical CT imaging under a condition similar to in vivo imaging by comparing with measures derived by micro‐CT and experimental approaches.

Method

Voxel‐based continuum FEA methods for CT imaging were implemented using linear and nonlinear models and applied on distal tibial scans under a condition similar to in vivo imaging. First, tibial axis in a CT scan was aligned with the coordinate z‐axis at 150 μm isotropic voxels. FEA was applied on an upright cylindrical volume of interests (VOI) with its axis coinciding with the tibial bone axis. Voxel volume, edge, and vertex elements and their connectivity were defined as per the isotropic image grid. A calibration phantom was used to calibrate CT numbers in Hounsfield unit to bone mineral density (BMD) values, which was then converted into calcium hydroxyapatite (CHA) density. Mechanical properties at each voxel volume element was defined using its ash‐density defined on CT‐derived CHA density. For FEA, the bottom surface of the cylindrical VOI was fixed and a constant displacement was applied along the z‐direction at each vertex element on the top surface to simulate a physical axial compressive loading condition. Finally, a Poisson's ratio of 0.3 was applied, and Tb modulus (MPa) was computed as the ratio of average von Mises stress (MPa) of volume elements on the top surface and the applied displacement. FEA parameters including mesh element size, substep number, and different tolerance values were optimized.

Results

CT‐derived Tb modulus values using continuum FEA showed high linear correlation with the micro‐CT‐derived reference values (r ∈ [0.87 0.90]) as well as experimentally measured values (r ∈ [0.80 0.87]). Linear correlation of computed modulus with their reference values using continuum FEA with linear modeling was comparable with that obtained by nonlinear modeling. Nonlinear continuum FEA‐based modulus values (mean of 1087.2 MPa) showed greater difference from their reference values (mean of 1498.9 MPa using micro‐CT‐based FEA) as compared with linear continuum methods. High repeat CT scan reproducibility (intra‐class correlation [ICC] = 0.98) was observed for computed modulus values using both linear and nonlinear continuum FEA. It was observed that high stress regions coincide with Tb microstructure as fuzzily characterized by BMD values. Distributions of von Mises stress over Tb microstructure and marrow regions were significantly different (p < 10^–8).

Conclusion

Voxel‐based continuum FEA offers surrogate measures of Tb modulus from CT imaging under a condition similar to in vivo imaging that alleviates the need for segmentation of Tb and marrow regions, while accounting for bone distribution at the microstructural level. This relaxation of binary segmentation will extend the scope of FEA application to assess mechanical properties of bone microstructure at relatively low‐resolution imaging.

Finite Element Assessment of Bone Fragility from Clinical Images

PURPOSE OF REVIEW

We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.

RECENT FINDINGS

CT-to-FE is useful in longitudinal treatment evaluation and groups discrimination. In metastatic lesions, CT-to-FE strength alone accurately predicts impending femoral fractures. In osteoporosis, strength from CT-to-FE or DXA-to-FE predicts incident fractures similarly to DXA-aBMD. Coupling loads and strength (possibly in dynamic models) may improve prediction. One promising MRI-to-FE workflow may now be tested on clinical data. Evidence of artificial intelligence usefulness is appearing. CT-to-FE is already clinical in opportunistic CT screening for osteoporosis, and risk of metastasis-related impending fractures. Short-term keys to improve image-to-FE in osteoporosis may be coupling FE with fall risk estimates, pool FE results with other parameters through robust artificial intelligence approaches, and increase reproducibility and cross-validation of models. Modeling bone modifications over time and bone fracture mechanics are still open issues.

Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on quantitative paraspinal muscle assessment

Background

Wasting disease entities like cachexia or sarcopenia are associated with a decreasing muscle mass and changing muscle composition. For valid and reliable disease detection and monitoring diagnostic techniques offering quantitative musculature assessment are needed. Multi-detector computed tomography (MDCT) is a broadly available imaging modality allowing for muscle composition analysis. A major disadvantage of using MDCT for muscle composition assessment is the radiation exposure. In this study we evaluated the performance of different methods of radiation dose reduction for paravertebral muscle composition assessment.

Methods

MDCT scans of eighteen subjects (6 males, age: 71.5±15.9 years, and 12 females, age: 71.0±8.9 years) were retrospectively simulated as if they were acquired at 50%, 10%, 5%, and 3% of the original X-ray tube current or number of projections (i.e., sparse sampling). Images were reconstructed with a statistical iterative reconstruction (SIR) algorithm. Paraspinal muscles (psoas and erector spinae muscles) at the level of L4 were segmented in the original-dose images. Segmentations were superimposed on all low-dose scans and muscle density (MD) extracted.

Results

Sparse sampling derived mean MD showed no significant changes (P=0.57 and P=0.22) down to 5% of the original projections in the erector spinae and psoas muscles, respectively. All virtually reduced tube current series showed significantly different (P>0.05) mean MD in the psoas and erector spinae muscles as compared to the original dose except for the images of 5% of the original tube current in the erector spinae muscle.

Conclusions

Our findings demonstrated the possibility of considerable radiation dose reduction using MDCT scans for assessing the composition of the paravertebral musculature. The sparse sampling approach seems to be promising and a potentially superior technique for dose reduction as compared to tube current reduction.

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.

Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on the detection of degenerative spine diseases

OBJECTIVES

To investigate potential radiation dose reduction for multi-detector computed tomography (MDCT) exams of the spine by using sparse sampling and virtually lowered tube currents combined with statistical iterative reconstruction (SIR).

METHODS

MDCT data of 26 patients (68.9 ± 11.7 years, 42.3% males) were retrospectively simulated as if the scans were acquired at 50%, 10%, 5%, and 3% of the original X-ray tube current or number of projections, using SIR for image reconstructions. Two readers performed qualitative image evaluation considering overall image quality, artifacts, and contrast and determined the number and type of degenerative changes. Scoring was compared between readers and virtual low-dose and sparse-sampled MDCT, respectively.

RESULTS

Image quality and contrast decreased with virtual lowering of tube current and sparse sampling, but all degenerative changes were correctly detected in MDCT with 50% of tube current as well as MDCT with 50% of projections. Sparse-sampled MDCT with only 10% of initial projections still enabled correct identification of all degenerative changes, in contrast to MDCT with virtual tube current reduction by 90% where non-calcified disc herniations were frequently missed (R1: 23.1%, R2: 21.2% non-diagnosed herniations). The average volumetric CT dose index (CTDI_vol) was 1.4 mGy for MDCT with 10% of initial projections, compared with 13.8 mGy for standard-dose imaging.

CONCLUSIONS

MDCT with 50% of original tube current or projections using SIR still allowed for accurate diagnosis of degenerative changes. Sparse sampling may be more promising for further radiation dose reductions since no degenerative changes were missed with 10% of initial projections.

KEY POINTS

• Most common degenerative changes of the spine can be diagnosed in multi-detector CT with 50% of tube current or number of projections. • Sparse-sampled multi-detector CT with only 10% of initial projections still enables correct identification of degenerative changes, in contrast to imaging with 10% of original tube current. • Sparse sampling may be a promising option for distinct lowering of radiation dose, reducing the CTDI_vol from 13.8 to 1.4 mGy in the study cohort.

Finite Element Analysis-Based Vertebral Bone Strength Prediction Using MDCT Data: How Low Can We Go?

Objective: To study the impact of dose reduction in MDCT images through tube current reduction or sparse sampling on the vertebral bone strength prediction using finite element (FE) analysis for fracture risk assessment. Methods: Routine MDCT data covering lumbar vertebrae of 12 subjects (six male; six female; 74.70 ± 9.13 years old) were included in this study. Sparsely sampled and virtually reduced tube current-based MDCT images were computed using statistical iterative reconstruction (SIR) with reduced dose levels at 50, 25, and 10% of the tube current and original projections, respectively. Subject-specific static non-linear FE analyses were performed on vertebra models (L1, L2, and L3) 3-D-reconstructed from those dose-reduced MDCT images to predict bone strength. Coefficient of correlation (R²), Bland-Altman plots, and root mean square coefficient of variation (RMSCV) were calculated to find the variation in the FE-predicted strength at different dose levels, using high-intensity dose-based strength as the reference. Results: FE-predicted failure loads were not significantly affected by up to 90% dose reduction through sparse sampling (R² = 0.93, RMSCV = 8.6% for 50%; R² = 0.89, RMSCV = 11.90% for 75%; R² = 0.86, RMSCV = 11.30% for 90%) and up to 50% dose reduction through tube current reduction method (R² = 0.96, RMSCV = 12.06%). However, further reduction in dose with the tube current reduction method affected the ability to predict the failure load accurately (R² = 0.88, RMSCV = 22.04% for 75%; R² = 0.43, RMSCV = 54.18% for 90%). Conclusion: Results from this study suggest that a 50% radiation dose reduction through reduced tube current and a 90% radiation dose reduction through sparse sampling can be used to predict vertebral bone strength. Our findings suggest that the sparse sampling-based method performs better than the tube current-reduction method in generating images required for FE-based bone strength prediction models.