Annals of Biomedical Engineering最新文献

Tooth cracks, one of the most common dental diseases, can result in the tooth falling apart without prompt treatment; dentists also have difficulty locating cracks, even with X-ray imaging. Indocyanine green (ICG) assisted near-infrared fluorescence (NIRF) dental imaging technique can solve this problem due to the deep penetration of NIR light and the excellent fluorescence characteristics of ICG. This study extracted 593 human cracked tooth images and 601 non-cracked tooth images from NIR imaging videos. Multiple imaging analysis methods such as classification, object detection, and super-resolution were applied to the dataset for cracked image analysis. Our results showed that machine learning methods could help analyze tooth crack efficiently: the tooth images with cracks and without cracks could be well classified with the pre-trained residual network and squeezenet1_1 models, with a classification accuracy of 88.2% and 94.25%, respectively; the single shot multi-box detector (SSD) was able to recognize cracks, even if the input image was at a different size from the original cracked image; the super-resolution (SR) model, SR-generative adversarial network demonstrated enhanced resolution of crack images using high-resolution concrete crack images as the training dataset. Overall, deep learning model-assisted human crack analysis improves crack identification; the combination of our NIR dental imaging system and deep learning models has the potential to assist dentists in crack diagnosis.

An estimated 6.8 million people in the United States have an unruptured intracranial aneurysms, with approximately 30,000 people suffering from intracranial aneurysms rupture each year. Despite the development of population-based scores to evaluate the risk of rupture, retrospective analyses have suggested the limited usage of these scores in guiding clinical decision-making. With recent advancements in imaging technologies, artery wall motion has emerged as a promising biomarker for the general study of neurovascular mechanics and in assessing the risk of intracranial aneurysms. However, measuring arterial wall deformations in vivo itself poses several challenges, including how to image local wall motion and deriving the anisotropic wall strains over the cardiac cycle. To overcome these difficulties, we first developed a novel in vivo MRI-based imaging method to acquire cardiac gated images of the human basilar artery (BA) over the cardiac cycle. Next, complete BA endoluminal surfaces from each frame were segmented, producing high-resolution point clouds of the endoluminal surfaces. From these point clouds we developed a novel B-spline-based surface representation, then exploited the local support nature of B-splines to determine the local endoluminal surface strains. Results indicated distinct regional and temporal variations in BA wall deformation, highlighting the heterogeneous nature BA function. These included large circumferential strains (up to $\sim$ 20 $\%$ ), and small longitudinal strains, which were often contractile and out of phase with the circumferential strains patterns. Of particular interest was the temporal phase lag in the maximum circumferential perimeter length, which indicated that the BA deforms asynchronously over the cardiac cycle. In summary, the proposed method enabled local deformation analysis, allowing for the successful reproduction of local features of the BA, such as regional principal stretches, areal changes, and pulsatile motion. Integrating the proposed method into existing population-based scores has the potential to improve our understanding of mechanical properties of human BA and enhance clinical decision-making.

Contemporary injury tolerance of the lumbar spine for under-body blast references axial compression and bending moments in a limited range. Since injuries often occur in a wider range of flexion and extension with increased moment contribution, this study expands a previously proposed combined loading injury criterion for the lumbar spine. Fifteen cadaveric lumbar spine failure tests with greater magnitudes of eccentric loading were incorporated into an existing injury criterion to augment its applicability and a combined loading injury risk model was proposed by means of survival analysis. A loglogistic distribution was the most representative of injury risk, resulting in optimized critical values of F_r,crit = 6011 N, and M_y,crit = 904 Nm for the proposed combined loading metric. The 50% probability of injury resulted in a combined loading metric value of 1, with 0.59 and 1.7 corresponding to 5 and 95% injury risk, respectively. The inclusion of eccentric loaded specimens resulted in an increased contribution of the bending moment relative to the previously investigated flexion/extension range (previous M_y,crit = 1155 Nm), with the contribution of the resultant sagittal force reduced by nearly 200 N (previous F_r,crit = 5824 N). The new critical values reflect an expanded flexion/extension range of applicability of the previously proposed combined loading injury criterion for the human lumbar spine during dynamic compression.

Purpose: Ultrasound imaging is key in the management of patients with an abdominal aortic aneurysm (AAA). It was recently shown that the cyclic diameter variations between diastole and systole, which can be quantified with US imaging, increase significantly with the strength of the applied probe pressure on the patient's abdomen. The goal of this study is to investigate this effect more thoroughly.

Methods: With finite-element modeling, pulsatile blood pressure and probe pressure are simulated in three patient-specific geometries. Two distinct models for the aortic wall were simulated: a nonlinear hyperelastic and a linear elastic model. In addition, varying stiffness was considered for the surrounding tissues. The effect of light, moderate, and firm probe pressure was quantified on the stresses and strains in the aortic wall, and on two in vivo stiffness measures. In addition, the Elasticity Loss Index was proposed to quantify the change in stiffness due to probe pressure.

Results: Firm probe pressure decreased the measured aortic stiffness, and material stiffness was affected only when the wall was modeled as nonlinear, suggesting a shift in the stress-strain curve. In addition, stiffer surrounding tissues and a more elongated aneurysm sac decreased the responsiveness to the probe pressure.

Conclusion: The effect of probe pressure on the AAA wall stiffness was clarified. In particular, the AAA wall nonlinear behavior was found to be of primary importance in determining the probe pressure response. Thus, further work will intend to make use of this novel finding in a clinical context.

The Ozaki procedure is a surgical technique which avoids to implant foreign aortic valve prostheses in human heart, using the patient's own pericardium. Although this approach has well-identified benefits, it is still a topic of debate in the cardiac surgical community, which prevents its larger use to treat valve pathologies. This is linked to the actual lack of knowledge regarding the dynamics of tissue deformations and surrounding blood flow for this autograft pericardial valve. So far, there is no numerical study examining the coupling between the blood flow characteristics and the Ozaki leaflets dynamics. To fill this gap, we propose here a comprehensive comparison of various performance criteria between a healthy native valve, its pericardium-based counterpart, and a bioprosthetic solution, this is done using a three-dimensional fluid-structure interaction solver. Our findings reveal similar physiological dynamics between the valves but with the emergence of fluttering for the Ozaki leaflets and higher velocity and wall shear stress for the bioprosthetic heart valve.

Purpose: To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood flow by applying a physics-guided neural network (div-mDCSRN-Flow) to 4D flow MRI.

Methods: The div-mDCSRN-Flow network was developed to improve spatial resolution and denoise 4D flow MRI. The network was trained with patches of paired high-resolution and low-resolution synthetic 4D flow MRI data derived from computational fluid dynamic simulations of CSF flow within the cerebral ventricles of five healthy cases and five Alzheimer's disease cases. The loss function combined mean squared error with a binary cross-entropy term for segmentation and a divergence-based regularization term for the conservation of mass. Performance was assessed using synthetic 4D flow MRI in one healthy and one Alzheimer' disease cases, an in vitro study of healthy cerebral ventricles, and in vivo 4D flow imaging of CSF as well as flow in arterial and venous blood vessels. Comparison was performed to trilinear interpolation, divergence-free radial basis functions, divergence-free wavelets, 4DFlowNet, and our network without divergence constraints.

Results: The proposed network div-mDCSRN-Flow outperformed other methods in reconstructing high-resolution velocity fields from synthetic 4D flow MRI in healthy and AD cases. The div-mDCSRN-Flow network reduced error by 22.5% relative to linear interpolation for in vitro core voxels and by 49.5% in edge voxels.

Conclusion: The results demonstrate generalizability of our 4D flow MRI super-resolution and denoising approach due to network training using flow patches and physics-based constraints. The mDCSRN-Flow network can facilitate MRI studies involving CSF flow measurements in cerebral ventricles and association of MRI-based flow metrics with cerebrovascular health.

Rotational mechanics is a fundamental determinant of left ventricular ejection fraction (LVEF). The coding system currently employed in clinical practice does not distinguish between rotational patterns. We propose an alternative coding system that makes possible to identify the rotational pattern of the LV and relate it to myocardial function. Echocardiographic images were used to generate speckle tracking-derived transmural global longitudinal strain (tGLS) and rotational parameters. The existence of twist (basal and apical rotations in opposite directions) is expressed as a rotational gradient with a positive value that is the sum of the basal and apical rotation angles. Conversely, when there is rigid rotation (basal and apical rotations in the same direction) the resulting gradient is assigned a negative value that is the subtraction between the two rotation angles. The rotational patterns were evaluated in 87 healthy subjects and 248 patients with LV hypertrophy (LVH) and contrasted with their myocardial function. Our approach allowed us to distinguish between the different rotational patterns. Twist pattern was present in healthy controls and 104 patients with LVH and normal myocardial function (tGLS ≥ 17%, both). Among 144 patients with LVH and myocardial dysfunction (tGLS < 17%), twist was detected in 83.3% and rigid rotation in 16.7%. LVEF was < 50% in 34.7%, and all patients with rigid rotation had a LVEF < 50%. The gradient rotational values showed a close relationship with LVEF (r = 0.73; p < 0.001). The proposed coding system allows us to identify the rotational patterns of the LV and to relate their values with LVEF.

The hemodynamics in Fontan patients with single ventricles rely on favorable flow and energetics, especially in the absence of a subpulmonary ventricle. Age-related changes in energetics for extracardiac and lateral tunnel Fontan procedures are not well understood. Vorticity (VOR) and viscous dissipation rate (VDR) are two descriptors that can provide insights into flow dynamics and dissipative areas in Fontan pathways, potentially contributing to power loss. This study examined power loss and its correlation with spatio-temporal flow descriptors (vorticity and VDR). Data from 414 Fontan patients were used to establish a relationship between the superior vena cava (SVC) to inferior vena cava (IVC) flow ratio and age. Computational flow modeling was conducted for both extracardiac conduits (ECC, n = 16) and lateral tunnels (LT, n = 25) at different caval inflow ratios of 2, 1, and 0.5 that corresponded with ages 3, 8, and 15+. In both cohorts, vorticity and VDR correlated well with PL, but ECC cohort exhibited a slightly stronger correlation for PL-VOR (>0.83) and PL-VDR (>0.89) than that for LT cohort (>0.76 and > 0.77, respectively) at all ages. Our data also suggested that absolute and indexed PL increase (p < 0.02) non-linearly as caval inflow changes with age and are highly patient-specific. Comparison of indexed power loss between our ECC and LT cohort showed that while ECC had a slightly higher median PL for all 3 caval inflow ratio examined (3.3, 8.3, 15.3) as opposed to (2.7, 7.6, 14.8), these differences were statistically non-significant. Lastly, there was a consistent rise in pressure gradient across the TCPC with age-related increase in IVC flows for both ECC and LT Fontan patient cohort. Our study provided hemodynamic insights into Fontan energetics and how they are impacted by age-dependent change in caval inflow. This workflow may help assess the long-term sustainability of the Fontan circulation and inform the design of more efficient Fontan conduits.

Older adults have difficulty maintaining balance when faced with postural disturbances, a task that is influenced by the stiffness of the triceps surae and Achilles tendon. Age-related changes in Achilles tendon stiffness have been reported at matched levels of effort, but measures typically have not been made at matched loads, which is important due to age-dependent changes in strength. Moreover, there has been limited investigation into age-dependent changes in muscle stiffness. Here, we investigate how age alters muscle and tendon stiffness and their influence on ankle stiffness. We hypothesized that age-related changes in muscle and tendon contribute to reduced ankle stiffness in older adults and evaluated this hypothesis when either load or effort were matched. We used B-mode ultrasound with joint-level perturbations to quantify ankle, muscle, and tendon stiffness across a range of loads and efforts in seventeen healthy younger and older adults. At matched loads relevant to standing and the stance phase of walking, there was no significant difference in ankle, muscle, or tendon stiffness between groups (all p > 0.13). However, at matched effort, older adults exhibited a significant decrease in ankle (27%; p = 0.008), muscle (37%; p = 0.02), and tendon stiffness (22%; p = 0.03) at 30% of maximum effort. This is consistent with our finding that older adults were 36% weaker than younger adults in plantarflexion (p = 0.004). Together, these results indicate that, at the loads tested in this study, there are no age-dependent changes in the mechanical properties of muscle or tendon, only differences in strength that result in altered ankle, muscle, and tendon stiffness at matched levels of effort.

The ability of articular cartilage to withstand significant mechanical stresses during activities, such as walking or running, relies on its distinctive structure. Integrating detailed tissue properties into subject-specific biomechanical models is challenging due to the complexity of analyzing these characteristics. This limitation compromises the accuracy of models in replicating cartilage function and impacts predictive capabilities. To address this, methods revealing cartilage function at the constituent-specific level are essential. In this study, we demonstrated that computational modeling derived individual constituent-specific biomechanical properties could be predicted by a novel nanoparticle contrast-enhanced computer tomography (CECT) method. We imaged articular cartilage samples collected from the equine stifle joint (n = 60) using contrast-enhanced micro-computed tomography (µCECT) to determine contrast agents' intake within the samples, and compared those to cartilage functional properties, derived from a fibril-reinforced poroelastic finite element model. Two distinct imaging techniques were investigated: conventional energy-integrating µCECT employing a cationic tantalum oxide nanoparticle (Ta₂O₅-cNP) contrast agent and novel photon-counting µCECT utilizing a dual-contrast agent, comprising Ta₂O₅-cNP and neutral iodixanol. The results demonstrate the capacity to evaluate fibrillar and non-fibrillar functionality of cartilage, along with permeability-affected fluid flow in cartilage. This finding indicates the feasibility of incorporating these specific functional properties into biomechanical computational models, holding potential for personalized approaches to cartilage diagnostics and treatment.