Measuring rib cortical bone thickness and cross section from CT

AFSegNet: few-shot 3D ankle-foot bone segmentation via hierarchical feature distillation and multi-scale attention and fusion

Accurate segmentation of ankle and foot bones from CT scans is essential for morphological analysis. Ankle and foot bone segmentation challenges due to the blurred bone boundaries, narrow inter-bone gaps, gaps in the cortical shell, and uneven spongy bone textures. Our study endeavors to create a deep learning framework that harnesses advantages of 3D deep learning and tackles the hurdles in accurately segmenting ankle and foot bones from clinical CT scans. A few-shot framework AFSegNet is proposed considering the computational cost, which comprises three 3D deep-learning networks adhering to the principles of progressing from simple to complex tasks and network structures. Specifically, a shallow network first over-segments the foreground, and along with the foreground ground truth are used to supervise a subsequent network to detect the over-segmented regions, which are overwhelmingly inter-bone gaps. The foreground and inter-bone gap probability map are then input into a network with multi-scale attentions and feature fusion, a loss function combining region-, boundary-, and topology-based terms to get the fine-level bone segmentation. AFSegNet is applied to the 16-class segmentation task utilizing 123 in-house CT scans, which only requires a GPU with 24 GB memory since the three sub-networks can be successively and individually trained. AFSegNet achieves a Dice of 0.953 and average surface distance of 0.207. The ablation study and comparison with two basic state-of-the-art networks indicates the effectiveness of the progressively distilled features, attention and feature fusion modules, and hybrid loss functions, with the mean surface distance error decreased up to 50 %.

Finite Element Analysis of a Rib Cage Model: Influence of Four Variables on Fatigue Life during Simulated Manual CPR

Cardiopulmonary resuscitation (CPR) is a life-saving technique used in emergencies when the heart stops beating, typically involving chest compressions and ventilation. Current adult CPR guidelines do not differentiate based on age beyond infancy and childhood. This oversight increases the risk of fatigue fractures in the elderly due to decreased bone density and changes in thoracic structure. Therefore, this study aimed to investigate the correlation and impact of factors influencing rib fatigue fractures for safer out-of-hospital manual cardiopulmonary resuscitation (OHMCPR) application. Using the finite element analysis (FEA) method, we performed fatigue analysis on rib cage models incorporating chest compression conditions and age-specific trabecular bone properties. Fatigue life analyses were conducted on three age-specific rib cage models, each differentiated by trabecular bone properties, to determine the influence of four explanatory variables (the properties of the trabecular bone (a surrogate for the age of the subject), the site of application of the compression force on the breastbone, the magnitude of applied compression force, and the rate of application of the compression force) on the fatigue life of the model. Additionally, considering the complex interaction of chest compression conditions during actual CPR, we aimed to predict rib fatigue fractures under conditions simulating real-life scenarios by analyzing the sensitivity and interrelation of chest compression conditions on the model's fatigue life. Time constraints led to the selection of optimal analysis conditions through the use of design of experiments (DOE), specifically orthogonal array testing, followed by the construction of a deep learning-based metamodel. The predicted fatigue life values of the rib cage model, obtained from the metamodel, showed the influence of the four explanatory variables on fatigue life. These results may be used to devise safer CPR guidelines, particularly for the elderly at a high risk of acute cardiac arrest, safeguarding against potential complications like fatigue fractures.

Artificial Intelligence-enabled Chest X-ray Classifies Osteoporosis and Identifies Mortality Risk

A deep learning model was developed to identify osteoporosis from chest X-ray (CXR) features with high accuracy in internal and external validation. It has significant prognostic implications, identifying individuals at higher risk of all-cause mortality. This Artificial Intelligence (AI)-enabled CXR strategy may function as an early detection screening tool for osteoporosis. The aim of this study was to develop a deep learning model (DLM) to identify osteoporosis via CXR features and investigate the performance and clinical implications. This study collected 48,353 CXRs with the corresponding T score according to Dual energy X-ray Absorptiometry (DXA) from the academic medical center. Among these, 35,633 CXRs were used to identify CXR- Osteoporosis (CXR-OP). Another 12,720 CXRs were used to validate the performance, which was evaluated by the area under the receiver operating characteristic curve (AUC). Furthermore, CXR-OP was tested to assess the long-term risks of mortality, which were evaluated by Kaplan‒Meier survival analysis and the Cox proportional hazards model. The DLM utilizing CXR achieved AUCs of 0.930 and 0.892 during internal and external validation, respectively. The group that underwent DXA with CXR-OP had a higher risk of all-cause mortality (hazard ratio [HR] 2.59, 95% CI: 1.83-3.67), and those classified as CXR-OP in the group without DXA also had higher all-cause mortality (HR: 1.67, 95% CI: 1.61-1.72) in the internal validation set. The external validation set produced similar results. Our DLM uses CXRs for early detection of osteoporosis, aiding physicians to identify those at risk. It has significant prognostic implications, improving life quality and reducing mortality. AI-enabled CXR strategy may serve as a screening tool.

Signal-difference-to-noise comparison of temporal subtraction, kV-switching dual-energy and photon-counting dual-energy x-ray angiography

BACKGROUND

Dual-energy (DE) x-ray angiography with photon-counting detectors (PCDs) may enable single-exposure DE imaging of coronary vasculature.

PURPOSE

To compare the iodine signal-difference-to-noise ratio (SDNR) of single-exposure DE angiography with digital subtraction angiography (DSA) and kV-switching DE angiography for matched patient x-ray exposure.

METHODS

In a phantom study, we determined the technique parameters that maximized the iodine SDNR per root entrance air kerma for DSA, kV-switching DE angiography and single-exposure DE angiography. We measured SDNR from images of a phantom consisting of an iodine step-wedge immersed in a water tank of either 20  or 30 cm in thickness. We also imaged a phantom with simulated vessels embedded in background clutter and measured vessel SDNR. For this second phantom, we also applied anti-correlated noise reduction (ACNR) and calculated the resulting iodine SDNR. All images were acquired using a cadmium telluride PCD with two energy bins and analog charge summing for charge sharing suppression. The energy-discrimination capabilities were only used for the single-exposure DE approach. Optimized techniques were compared in terms of SDNR per root air kerma for two levels of x-ray scatter.

RESULTS

For the same patient x-ray exposure, the SDNR of single-exposure DE imaging without ACNR was 75% to 85% of that of kV-switching DE imaging (also without ACNR) and DSA, the latter two of which had nearly equal SDNR. The single-exposure DE approach required ∼50% of the tube load of the kV-switching approach to achieve the same SDNR. For matched patient air kermas, the single exposure approach required only ∼25% of the tube load of the kV-switching approach. ACNR increased SDNR by 2.4 and 3.0 for kV-switching and single-exposure DE imaging, respectively.

CONCLUSIONS

Photon-counting, single-exposure DE angiography can suppress soft tissues and provide iodine SDNR levels comparable to DSA and kV-switching DE angiography for matched patient radiation exposures. When ACNR is used to reduce DE image noise, the SDNR of single-exposure DE imaging and kV-switching DE imaging exceed that of DSA by more than a factor of two. Compared to kV-switching DE imaging, single-exposure DE imaging requires substantially lower tube loading to achieve the same SDNR.

Cross-sectional properties of rib geometry from an adult population

Introduction: Human body models (HBMs) play a key role in improving modern vehicle safety systems to protect broad populations. However, their geometry is commonly derived from single individuals chosen to meet global anthropometric targets, thus their internal anatomy may not fully represent the HBM's target demographic. Past studies show sixth rib cross-sectional geometry differences between HBM ribs and population-derived ribs, and corrections to HBM ribs based on these data have improved HBM's abilities to predict rib fracture locations. Methods: We measure and report average and standard deviations (SDs) in rib cross-sectional geometric properties derived from live subject CT scans of 240 adults aged 18-90. Male and female results are given as functions of rib number and rib lengthwise position for ribs 2 through 11. Population means/SDs are reported for measures of rib total area, rib cortical bone area, and rib endosteal area, as well as inertial moment properties of these rib sections. These population corridors are compared between males and females, and against the baseline rib geometries defined in six current HBMs. Results: Total cross-sectional area results found average males ribs to be larger than those of females by between approximately 1-2 SDs depending on rib number and position, and larger in cortical bone cross-sectional area by between 0-1 SDs. Inertial moment ratios showed female ribs being between approximately 0-1 SDs more elongated than male ribs, dependent again on rib number and position. Rib cross-sectional areas from 5 of the 6 HBMs were found to be overly large along substantial portions of most ribs when compared to average population corridors. Similarly, rib aspect ratios in HBMs deviated from average population data by up to 3 SDs in regions towards sternal rib ends. Discussion: Overall, while most HBMs capture overall trends such as reductions in cross-section along shaft lengths, many also exhibit local variation that deviates from population trends. This study's results provide the first reference values for assessing the cross-sectional geometry of human ribs across a wide range of rib levels. Results also further provide clear guidelines to improve rib geometry definitions present in current HBMs in order to better represent their target demographic.

Cross-sectional geometry of the femoral diaphyseal cortical bones: analysis of central mass distribution

A detailed analysis of differences in skeletal shape among many individuals is expected to reveal the mechanical significance behind various morphological features. To confirm the distribution of the cortical bone region in cross sections, the relative position of the central mass distribution (CMD) of the cortical bone region to the CMD of the entire cross section was examined. A total of 90 right human femoral skeletons were examined using clinical multi-slice computed tomography. For nine cross sections of each femur, we determined the CMD of the whole area, including both cortical bone and medullary areas, as CMD-W, and that of the cortical bone region in the same cross section as CMD-C, and they were compared. The medial and anterior portion of the cortex was relatively thick just below the lesser trochanter. The posterior cortical bone tended to be relatively thick in the region from the center to the distal part of the diaphysis. Females had a significantly more medially deviated CMD than males throughout the entire diaphysis. These results suggest that femurs with advanced cortical bone thinning tend to have a concentration of cortical bone in their medial portion. CMD-C was located farther from the diaphysis axis as the degree of medial bending increased. Conversely, the greater the lateral bending of the diaphysis, the closer CMD-C was to the diaphysis axis. As the amount of bone decreases with age, self-adjustment could occur so that the cortical bone's critical area remains to prevent a decrease in mechanical strength.

Deep Learning for Bone Mineral Density and T-Score Prediction from Chest X-rays: A Multicenter Study

Although the number of patients with osteoporosis is increasing worldwide, diagnosis and treatment are presently inadequate. In this study, we developed a deep learning model to predict bone mineral density (BMD) and T-score from chest X-rays, which are one of the most common, easily accessible, and low-cost medical imaging examination methods. The dataset used in this study contained patients who underwent dual-energy X-ray absorptiometry (DXA) and chest radiography at six hospitals between 2010 and 2021. We trained the deep learning model through ensemble learning of chest X-rays, age, and sex to predict BMD using regression and T-score for multiclass classification. We assessed the following two metrics to evaluate the performance of the deep learning model: (1) correlation between the predicted and true BMDs and (2) consistency in the T-score between the predicted class and true class. The correlation coefficients for BMD prediction were hip = 0.75 and lumbar spine = 0.63. The areas under the curves for the T-score predictions of normal, osteopenia, and osteoporosis diagnoses were 0.89, 0.70, and 0.84, respectively. These results suggest that the proposed deep learning model may be suitable for screening patients with osteoporosis by predicting BMD and T-score from chest X-rays.

Rib cortical bone thickness variation in adults by age and sex

Rib fractures are a common and serious outcome of blunt thoracic trauma and their likelihood is greater in older individuals. Osteoporotic bone loss is a well-documented aging phenomenon with sex-specific characteristics, but within rib bones, neither baseline maps of regional thickness nor the rates of bone thinning with age have been quantified across whole ribs. This study presents such data from 4014 ribs of 240 adult subjects aged 20-90. A validated cortical bone mapping technique was applied to clinical computed tomography scans to obtain local rib cortical bone thickness measurements over the surfaces of ribs 2 through 11. Regression models to age and sex gave rates of cortex thinning in local zones and aggregated across whole ribs. The statistical parametric mapping provided these relationships regionally as a function of rib surface location. All models showed significant reductions in bone thickness with age (p < 0.01). Average whole-rib thinning occurred at between 0.011 to 0.032 mm/decade (males) and 0.035 to 0.043 mm/decade (females), with sex and age accounting for up to 37% of population variability (R² ). Rates of thinning differed regionally and by rib, with the highest bone loss of up to 0.074 mm/decade occurring in mid-rib cutaneous and superior regions of ribs 2-6. Rates were consistently higher in females than males (significantly so across whole ribs but not all local regions) and were more pronounced in cutaneous, superior, and inferior rib aspects (average 0.025 mm/decade difference in ribs 4-8) compared to pleural aspects which had the thickest cortices but saw only minor differences in thinning rates by sex (0.045 mm/decade for females and 0.040 mm/decade for males). Regional analysis showed male and female bone thickness differences that were not statistically significant at 20 years of age (p > 0.05 across practically all regions) but subsequent cortex thinning meant that substantial pleural and cutaneous regions were thinner (p < 0.05) in females than males by 55 years of age. The techniques and results from this study can be applied to assess rib bone content loss in clinical settings across wide populations. Additionally, average cortex thickness results can be mapped directly to finite element models of the thorax, and regression results are used to modify such models to represent the ribs of men and women across their full adult lifespan.

Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning: Development and External Validation With a Cohort Dataset

Osteoporosis is a common, but silent disease until it is complicated by fractures that are associated with morbidity and mortality. Over the past few years, although deep learning-based disease diagnosis on chest radiographs has yielded promising results, osteoporosis screening remains unexplored. Paired data with 13,026 chest radiographs and dual-energy X-ray absorptiometry (DXA) results from the Health Screening and Promotion Center of Asan Medical Center, between 2012 and 2019, were used as the primary dataset in this study. For the external test, we additionally used the Asan osteoporosis cohort dataset (1089 chest radiographs, 2010 and 2017). Using a well-performed deep learning model, we trained the OsPor-screen model with labels defined by DXA based diagnosis of osteoporosis (lumbar spine, femoral neck, or total hip T-score ≤ -2.5) in a supervised learning manner. The OsPor-screen model was assessed in the internal and external test sets. We performed substudies for evaluating the effect of various anatomical subregions and image sizes of input images. OsPor-screen model performances including sensitivity, specificity, and area under the curve (AUC) were measured in the internal and external test sets. In addition, visual explanations of the model to predict each class were expressed in gradient-weighted class activation maps (Grad-CAMs). The OsPor-screen model showed promising performances. Osteoporosis screening with the OsPor-screen model achieved an AUC of 0.91 (95% confidence interval [CI], 0.90-0.92) and an AUC of 0.88 (95% CI, 0.85-0.90) in the internal and external test set, respectively. Even though the medical relevance of these average Grad-CAMs is unclear, these results suggest that a deep learning-based model using chest radiographs could have the potential to be used for opportunistic automated screening of patients with osteoporosis in clinical settings. © 2021 American Society for Bone and Mineral Research (ASBMR).

Global and local characterization explains the different mechanisms of failure of the human ribs

Knowledge of the mechanics and mechanistic reasons inducing rib fracture is fundamental for forensic investigations and for the design of implants and cardiopulmonary resuscitation devices. A mechanical rationale to explain the different rib mechanisms of failure is still a challenge. The aim of this work was to experimentally characterize human ribs to test the hypothesis that a correlation exists between the ribs properties and the mechanism of failure. 89 ribs were tested in antero-posterior compression. The full-field strain distribution was measured through Digital Image Correlation. The fracture load ranged 7-132 N. Two main different mechanisms of failure were observed: brittle and buckling. The strain analysis showed that the direction of principal strains was either aligned with the ribs, or oblique, around 45°, with a rather uniform direction in the most strained area. The maximum principal strains were in the range between 1000 and 30000 microstrain and the minimum principal strain between -30000 and -800 microstrain. The ribs undergoing brittle fracture had significantly thicker cortical bone than those undergoing buckling. Also, larger tensile strains were observed in the specimens with brittle fracture than in the buckling ones. These findings support the focus of cortical thickness modelling which could help in sharpening computational models for the aforesaid purposes.

A fast full-wave solver for calculating ultrasound propagation in the body

Therapeutic ultrasound is a promising non-invasive method for inducing various beneficial biological effects in the human body. In cancer treatment applications, high-power ultrasound is focused at a target tissue volume to ablate the malignant tumour. The success of the procedure depends on the ability to accurately focus ultrasound and destroy the target tissue volume through coagulative necrosis whilst preserving the surrounding healthy tissue. Patient-specific treatment planning strategies are therefore being developed to increase the efficacy of such therapies, while reducing any damage to healthy tissue. These strategies require to use high-performance computing methods to solve ultrasound wave propagation in the body quickly and accurately. For realistic clinical scenarios, all numerical methods which employ volumetric meshes require several hours or days to solve the full-wave propagation on a computer cluster. The boundary element method (BEM) is an efficient approach for modelling the wave field because only the boundaries of the hard and soft tissue regions require discretisation. This paper presents a multiple-domain BEM formulation with a novel preconditioner for solving the Helmholtz transmission problem (HTP). This new formulation is efficient at high-frequencies and where high-contrast materials are present. Numerical experiments are performed to solve the HTP in multiple domains comprising: (i) human ribs, an idealised abdominal fat layer and liver tissue, (ii) a human kidney with a perinephric fat layer, exposed to the acoustic field generated by a high-intensity focused ultrasound (HIFU) array transducer. The time required to solve the equations associated with these problems on a single workstation is of the order of minutes. These results demonstrate the great potential of this new BEM formulation for accurately and quickly solving ultrasound wave propagation problems in large anatomical domains which is essential for developing treatment planning strategies.

Subject-specific rib finite element models with material data derived from coupon tests under bending loading

Rib fractures are common thoracic injuries in motor vehicle crashes. Several human finite element (FE) human models have been created to numerically assess thoracic injury risks. However, the accurate prediction of rib biomechanical response has shown to be challenging due to human variation and modeling approaches. The main objective of this study was to better understand the role of modeling approaches on the biomechanical response of human ribs in anterior-posterior bending. Since the development of subject specific rib models is a time-consuming process, the second objective of this study was to develop an accurate morphing approach to quickly generate high quality subject specific rib meshes. The exterior geometries and cortical-trabecular boundaries of five human 6th-level ribs were extracted from CT-images. One rib mesh was developed in a parametric fashion and the other four ribs were developed with an in-house morphing algorithm. The morphing algorithm automatically defined landmarks on both the periosteal and endosteal boundaries of the cortical layer, which were used to morph the template nodes to target geometries. Three different cortical bone material models were defined based on the stress-strain data obtained from subject-specific tensile coupon tests for each rib. Full rib anterior-posterior bending tests were simulated based on data recorded in testing. The results showed similar trends to test data with some sensitivity relative to the material modeling approach. Additionally, the FE models were substantially more resistant to failure, highlighting the need for better techniques to model rib fracture. Overall, the results of this work can be used to improve the biofidelity of human rib finite element models.

Morphomic Signatures Derived from Computed Tomography Predict Hepatocellular Carcinoma Occurrence in Cirrhotic Patients

BACKGROUND AND AIMS

Computed tomography (CT) provides scans of the human body from which digitized features can be extracted. The aim of this study was to examine the role of these digital biomarkers for predicting subsequent occurrence of hepatocellular carcinoma (HCC) in cirrhotic patients.

METHODS

A cohort of 269 patients with cirrhosis were recruited and prospectively followed for the occurrence of HCC in Taiwan. CT scans were retrospectively retrieved and computationally processed using analytic morphomics. A predictive score was constructed using Cox regression and the generalized iterative modeling method, maximizing the log likelihood of the time to HCC development. An independent cohort of 274 patients from University of Michigan was utilized to examine the predictive validity of this score in a Western population.

RESULTS

Of the 27 digitized features at the 12th thoracic vertebral level, six features were significantly associated with HCC occurrence. Two digitized features (fascia eccentricity and the bone mineral density) were able to stratify patients into high- and low-risk groups with distinct cumulative incidence of HCC in both the training and validation cohorts (P = 0.015 and 0.044, respectively). When the two digitized features were tested in the Michigan cohort, only bone mineral density remained an effective predictor.

CONCLUSION

Digitized features derived from the CT were effective in predicting subsequent occurrence of HCC in cirrhosis patients. The bone mineral density measured on CT was an effective predictor for patients in both Taiwan and USA.

Decreased mandibular cortical bone quality after botulinum toxin injections in masticatory muscles in female adults

This study aimed to clarify how masticatory muscle atrophy induced by botulinum toxin (BTX) injection affects cortical bone quality of the mandible using 3D modeling technology. A total of 39 young (26.9 ± 6.0 years) and 38 post-menopausal (55.3 ± 6.3 years) females were included. Computed tomography (CT) images were obtained before and after 12 months of treatment. Predictor variables were application of a stabilization splint, and/or two times of BTX injection in the bilateral temporalis and masseter muscles within a six-month interval. Outcome variables were changes in average Hounsfield units (HU) and cortical thickness of region of interest (ROI). 3D mandibular models were reconstructed using CT images, and models were used to calculate average HU and cortical thickness of ROIs, including inferior half of the lateral surface of ascending ramus, coronoid process, and temporomandibular joint condyle. Cortical bone quality at muscle insertion site was influenced by decreased muscle thickness but seemed not to be affected by decreased functional loading. Reduced functional loading seemed to influence cortical bone quality of the condyles. These effects were more remarkable in post-menopausal females. Hence, decreased masticatory muscle thickness may lead to alterations of the mandibular cortical structures, especially in post-menopausal females.

Detailed subject-specific FE rib modeling for fracture prediction

Objective: The current state of the art human body models (HBMs) underpredict the number of fractured ribs. Also, it has not been shown that the models can predict the fracture locations. Efforts have been made to create subject specific rib models for fracture prediction, with mixed results. The aim of this study is to evaluate if subject-specific finite element (FE) rib models, based on state-of-the-art clinical CT data combined with subject-specific material data, can predict rib stiffness and fracture location in anterior-posterior rib bending.Method: High resolution clinical CT data was used to generate detailed subject-specific geometry for twelve FE models of the sixth rib. The cortical bone periosteal and endosteal surfaces were estimated based on a previously calibrated cortical bone mapping algorithm. The cortical and the trabecular bone were modeled using a hexa-block algorithm. The isotropic material model for the cortical bone in each rib model was assigned subject-specific material data based on tension coupon tests. Two different modeling strategies were used for the trabecular bone.The capability of the FE model to predict fracture location was carried out by modeling physical dynamic anterior-posterior rib bending tests. The rib model predictions were directly compared to the results from the tests. The predicted force-displacement time history, strain measurements at four locations, and rotation of the rib ends were compared to the results from the physical tests by means of CORA analysis. Rib fracture location in the FE model was estimated as the position for the element with the highest first principle strain at the time corresponding to rib fracture in the physical test.Results: Seven out of the twelve rib models predicted the fracture locations (at least for one of the trabecular modeling strategies) and had a force-displacement CORA score above 0.65. The other five rib models, had either a poor force-displacement CORA response or a poor fracture location prediction. It was observed that the stress-strain response for the coupon test for these five ribs showed significantly lower Young's modulus, yield stress, and elongation at fracture compared to the other seven ribs.Conclusion: This study indicates that rib fracture location can be predicted for subject specific rib models based on high resolution CT, when loaded in anterior-posterior bending, as long as the rib's cortical cortex is of sufficient thickness and has limited porosity. This study provides guidelines for further enhancements of rib modeling for fracture location prediction with HBMs.

Regional maps of rib cortical bone thickness and cross-sectional geometry

Here we present detailed regional bone thickness and cross-sectional measurements from full adult ribs using high resolution CT scans processed with a cortical bone mapping technique. Sixth ribs from 33 subjects ranging from 24 to 99 years of age were used to produce average cortical bone thickness maps and to provide average ± 1SD corridors for expected cross-section properties (cross-sectional areas and inertial moments) as a function of rib length. Results obtained from CT data were validated at specific rib locations using direct measurements from cut sections. Individual thickness measurements from CT had an accuracy (mean error) and precision (SD error) of -0.013 ± 0.167 mm (R² coefficient of determination of 0.84). CT-based measurement errors for rib cross-sectional geometry were -0.1 ± 13.1% (cortical bone cross-sectional area) and 4.7 ± 1.8% (total cross-sectional area). Rib cortical bone thickness maps show the expected regional variation across a typical rib's surface. The local mid-rib maxima in cortical thickness along the pleural rib aspect ranged from range 0.9 to 2.6 mm across the study population with an average map maximum of 1.4 mm. Along the cutaneous aspect, rib cortical bone thickness ranged from 0.7 to 1.9 mm with an average map thickness of 0.9 mm. Average cross-sectional properties show a steady reduction in total cortical bone area from 10% along the rib's length through to the sternal end, whereas overall cross-sectional area remains relatively constant along the majority of the rib's length before rising steeply towards the sternal end. On average, male ribs contained more cortical bone within a given cross-section than was seen for female ribs. Importantly, however, this difference was driven by male ribs having larger overall cross-sectional areas, rather than by sex differences in the bone thickness observed at specific local cortex sites. The cortical bone thickness results here can be used directly to improve the accuracy of current human body and rib models. Furthermore, the measurement corridors obtained from adult subjects across a wide age range can be used to validate future measurements from more widely available image sources such as clinical CT where gold standard reference measures (e.g. such as direct measurements obtained from cut sections) are otherwise unobtainable.

Comparing rib cortical thickness measurements from computed tomography (CT) and Micro-CT

BACKGROUND

The objective of this study was to compare cortical thickness of rib specimens scanned with clinical computed tomography (clinical-CT) at 0.5 and 1.0 mm slice thickness versus micro-CT at 0.05 mm slice thickness. Cortical thickness variation and accuracy was explored by anatomical region (anterior vs. lateral) and cross-sectional quadrants (superior, interior, inferior, and exterior).

METHODS

A validated cortical thickness algorithm was applied to clinical-CT and micro-CT scans of 17 rib specimens from six male post mortem human subjects aged 42-81 years. Each rib specimen was segmented and the thickness measurements were partitioned into cross-sectional quadrants in the anterior and lateral regions of the rib. Within each rib quadrant, the following were calculated: average thickness ± standard deviation, mean thickness difference between clinical-CT and micro-CT, and a thickness ratio between clinical-CT and micro-CT. Correlations from linear regression and paired-t tests were determined for paired clinical-CT and micro-CT results.

RESULTS

On average, the 0.5 mm clinical-CT underestimated the micro-CT thickness by 0.005 mm, while the 1.0 mm clinical-CT overestimated the micro-CT thickness by 0.149 mm. Thickness derived from 0.5 mm clinical-CT showed greater significant linear correlations (p < 0.05) with micro-CT thickness compared to 1.0 mm clinical-CT.

CONCLUSIONS

The small mean differences and thickness ratios near 1 show validation for the cortical thickness algorithm when applied to rib clinical-CT scans. Using clinical-CT scans as way to accurately measure rib cortical thickness offers a non-invasive way to analyze millions of CT scans collected each year from males and females of all ages.

Sources of Variability in Structural Bending Response of Pediatric and Adult Human Ribs in Dynamic Frontal Impacts

Despite safety advances, thoracic injuries in motor vehicle crashes remain a significant source of morbidity and mortality, and rib fractures are the most prevalent of thoracic injuries. The objective of this study was to explore sources of variation in rib structural properties in order to identify sources of differential risk of rib fracture between vehicle occupants. A hierarchical model was employed to quantify the effects of demographic differences and rib geometry on structural properties including stiffness, force, displacement, and energy at failure and yield. Three-hundred forty-seven mid-level ribs from 182 individual anatomical donors were dynamically (~2 m/s) tested to failure in a simplified bending scenario mimicking a frontal thoracic impact. Individuals ranged in age from 4 - 108 years (mean 53 ± 23 years) and included 59 females and 123 males of diverse body sizes. Age, sex, body size, aBMD, whole rib geometry and cross-sectional geometry were explored as predictors of rib structural properties. Measures of cross-sectional rib size (Tt.Ar), bone quantity (Ct.Ar), and bone distribution (Z) generally explained more variation than any other predictors, and were further improved when normalized by rib length (e.g., robustness and WBSI). Cortical thickness (Ct.Th) was not found to be a useful predictor. Rib level predictors performed better than individual level predictors. These findings moderately explain differential risk for rib fracture and with additional exploration of the rib's role in thoracic response, may be able contribute to ATD and HBM development and alterations in addition to improvements to thoracic injury criteria and scaling methods.