A novel computer modeling and simulation technique for bronchi motion tracking in human lungs under respiration

In this work, we proposed a novel computer modeling and simulation technique for motion tracking of lung bronchi (or tumors) under respiration using 9 cases of computed tomography (CT)-based patient-specific finite element (FE) models and Ogden's hyperelastic model. In the fabrication of patient-specific FE models for the respiratory system, various organs such as the mediastinum, diaphragm, and thorax that could affect the lung motions during breathing were considered. To describe the nonlinear material behavior of lung parenchyma, the comparative simulation for biaxial tension-compression of lung parenchyma was carried out using several hyperelastic models in ABAQUS, and then, Ogden's model was adopted as an optimal model. Based on the aforementioned FE models and Ogden's material model, the 9 cases of respiration simulation were carried out from exhalation to inhalation, and the motion of lung bronchi (or tumors) was tracked. In addition, the changes in lung volume, lung cross-sectional area on the axial plane during breathing were calculated. Finally, the simulation results were quantitatively compared to the inhalation/exhalation CT images of 9 subjects to validate the proposed technique. Through the simulation, it was confirmed that the average relative errors of simulation to clinical data regarding to the displacement of 258 landmarks in the lung bronchi branches of total subjects were 1.10%~2.67%. In addition, the average relative errors of those with respect to the lung cross-sectional area changes and the volume changes in the superior-inferior direction were 0.20%~5.00% and 1.29 ~ 9.23%, respectively. Hence, it was considered that the simulation results were coincided well with the clinical data. The novelty of the present study is as follows: (1) The framework from fabrication of the human respiratory system to validation of the bronchi motion tracking is provided step by step. (2) The comparative simulation study for nonlinear material behavior of lung parenchyma was carried out to describe the realistic lung motion. (3) Various organs surrounding the lung parenchyma and restricting its motion were considered in respiration simulation. (4) The simulation results such as landmark displacement, lung cross-sectional area/volume changes were quantitatively compared to the clinical data of 9 subjects.

A newly developed image fusion algorithm between CECT image and CT image: A feasibility study

Cancer cases have been on the rise over the world. Cancer treatment can benefit from an early accurate diagnosis. Percutaneous needle biopsy under the guidance of CT images is the most common method to obtain tumor samples for accurate diagnosis. However, due to the lack of vascular information in the CT images, the biopsy procedure is at great risk, especially for the tumor surrounded by vessels. In this study, a biomechanical model and surface elastic registration-based fusion algorithm were developed to map the vessels from contrast-enhanced CT images of the liver and lung to the corresponded CT image. Radiologists could observe vessels in the CT images during the biopsy procedure so that the risk can be decreased. The developed algorithm was tested through 20 groups of lung data and 16 groups of liver data. The results show that the fusion errors (mean ± standard deviation) were 2.35 ± 0.85, 2.08 ± 0.41, 2.31 ± 0.49, and 2.37 ± 0.62 mm for portal vein, hepatic vein, pulmonary artery, and pulmonary vein, respectively. The accuracy of this method was satisfied in clinical application

N-Phase Local Expansion Ratio for Characterizing Out-of-Phase Lung Ventilation

Out-of-phase ventilation occurs when local regions of the lung reach their maximum or minimum volumes at breathing phases other than the global end inhalation or exhalation phases. This paper presents the N-phase local expansion ratio (LER _N ) as a surrogate for lung ventilation. A common approach to estimate lung ventilation is to use image registration to align the end exhalation and inhalation 3DCT images and then analyze the resulting correspondence map. This 2-phase local expansion ratio (LER₂) is limited because it ignores out-of-phase ventilation and thus may underestimate local lung ventilation. To overcome this limitation, LER _N measures the maximum ratio of local expansion and contraction over the entire breathing cycle. Comparing LER₂ to LER _N provides a means for detecting and characterizing locations of the lung that experience out-of-phase ventilation. We present a novel in-phase/out-of-phase ventilation (IOV) function plot to visualize and measure the amount of high-function IOV that occurs during a breathing cycle. Treatment planning 4DCT scans collected during coached breathing from 32 human subjects with lung cancer were analyzed in this study. Results show that out-of-phase breathing occurred in all subjects and that the spatial distribution of out-of-phase ventilation varied from subject to subject. For the 32 subjects analyzed, 50% of the out-of-phase regions on average were mislabeled as low-function by LER₂ (high-function threshold of 1.1, IOV threshold of 1.05). 4DCT and Xenon-enhanced CT of four sheep showed that LER₈ is more accurate than LER₂ for measuring lung ventilation.

Estimation of the hyperelastic parameters of fresh human oropharyngeal soft tissues using indentation testing

Patient-specific finite element (FE) modeling of the upper airway is an effective tool for accurate assessment of obstructive sleep apnea (OSA) syndrome. It is also useful for planning minimally invasive surgical procedures under severe OSA conditions. A major requirement of FE modeling is having reliable data characterizing the biomechanical properties of the upper airway tissues, particularly oropharyngeal soft tissue. While some data characterizing this tissue's linear elastic regime is available, reliable data characterizing its hyperelasticity is scarce. The aim of the current study is to estimate the hyperelastic mechanical properties of the oropharyngeal soft tissues, including the palatine tonsil, soft palate, uvula, and tongue base. Fresh tissue specimens of human oropharyngeal tissue were acquired from 13 OSA patients who underwent standard surgical procedures. Indentation testing was performed on the specimens to obtain their force-displacement data. To determine the specimens' hyperelastic parameters using these data, an inverse FE framework was utilized. In this work, the hyperelastic parameters corresponding to the commonly used Yeoh and 2nd order Ogden models were obtained. Both models captured the experimental force-displacement data of the tissue specimens reasonably accurately with mean errors of 11.65% or smaller. This study has provided estimates of the hyperelastic parameters of all upper airway soft tissues using fresh human tissue specimens for the first time.

Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning

4-Dimensional cone-beam computed tomography (4D-CBCT) offers several key advantages over conventional 3D-CBCT in moving target localization/delineation, structure de-blurring, target motion tracking, treatment dose accumulation and adaptive radiation therapy. However, the use of the 4D-CBCT in current radiation therapy practices has been limited, mostly due to its sub-optimal image quality from limited angular sampling of cone-beam projections. In this study, we summarized the recent developments of 4D-CBCT reconstruction techniques for image quality improvement, and introduced our developments of a new 4D-CBCT reconstruction technique which features simultaneous motion estimation and image reconstruction (SMEIR). Based on the original SMEIR scheme, biomechanical modeling-guided SMEIR (SMEIR-Bio) was introduced to further improve the reconstruction accuracy of fine details in lung 4D-CBCTs. To improve the efficiency of reconstruction, we recently developed a U-net-based deformation-vector-field (DVF) optimization technique to leverage a population-based deep learning scheme to improve the accuracy of intra-lung DVFs (SMEIR-Unet), without explicit biomechanical modeling. Details of each of the SMEIR, SMEIR-Bio and SMEIR-Unet techniques were included in this study, along with the corresponding results comparing the reconstruction accuracy in terms of CBCT images and the DVFs. We also discussed the application prospects of the SMEIR-type techniques in image-guided radiation therapy and adaptive radiation therapy, and presented potential schemes on future developments to achieve faster and more accurate 4D-CBCT imaging.

Material properties of human lumbar intervertebral discs across strain rates

BACKGROUND CONTEXT

The use of finite element (FE) methods to study the biomechanics of the intervertebral disc (IVD) has increased over recent decades due to their ability to quantify internal stresses and strains throughout the tissue. Their accuracy is dependent upon realistic, strain-rate dependent material properties, which are challenging to acquire.

PURPOSE

The aim of this study was to use the inverse FE technique to characterize the material properties of human lumbar IVDs across strain rates.

STUDY DESIGN

A human cadaveric experimental study coupled with an inverse finite element study.

METHODS

To predict the structural response of the IVD accurately, the material response of the constituent structures was required. Therefore, compressive experiments were conducted on 16 lumbar IVDs (39±19 years) to obtain the structural response. An FE model of each of these experiments was developed and then run through an inverse FE algorithm to obtain subject-specific constituent material properties, such that the structural response was accurate.

RESULTS

Experimentally, a log-linear relationship between IVD stiffness and strain rate was observed. The material properties obtained through the subject-specific inverse FE optimization of the annulus fibrosus (AF) fiber and AF fiber ground matrix allowed a good match between the experimental and FE response. This resulted in a Young modulus of AF fibers (-MPa) to strain rate (ε˙, /s) relationship of YMAF=31.5ln(ε˙)+435.5, and the C₁₀ parameter of the Neo-Hookean material model of the AF ground matrix was found to be strain-rate independent with an average value of 0.68 MPa.

CONCLUSIONS

These material properties can be used to improve the accuracy, and therefore predictive ability of FE models of the spine that are used in a wide range of research areas and clinical applications.

CLINICAL SIGNIFICANCE

Finite element models can be used for many applications including investigating low back pain, spinal deformities, injury biomechanics, implant design, design of protective systems, and degenerative disc disease. The accurate material properties obtained in this study will improve the predictive ability, and therefore clinical significance of these models.

Efficient Sensitivity Based Reconstruction Technique to Accomplish Breast Hyperelastic Elastography

Hyperelastic models have been acknowledged as constitutive equations which reliably model the nonlinear behaviors observed from soft tissues under various loading conditions. Among them, the Mooney-Rivlin, Yeoh, and polynomial models have been proved capable of accurately modeling responses of breast tissues to applied compressions. Hyperelastic elastography technique takes advantage of the disparities between hyperelastic parameters of varied tissues and the change in hyperelastic parameters in pathological processes. The precise reconstruction of hyperelastic parameters of a completely unknown pathology in the breast in a noninvasive and nondestructive way using the ultrasound elastography has been scrutinized in this paper. In the ultrasound elastography, tissue displacement field is extracted from radio frequency signals or images recorded using the ultrasound medical imaging system; hence the exact displacement field might not be obtained. Our results indicate that the parameters estimated by manipulating the iterative sensitivity-matrix based method converge to tissue's real hyperelastic parameters providing appropriate parameters are assigned to the hypothetical hyperelastic and regularization parameters. Iterative methods have therefore been proposed to compute proper hypothetical hyperelastic and regularization parameters. Accurate estimates of hyperelastic parameters of obscure breast pathology have been achieved even from imprecise measurements of displacements induced in the tissue by the ramp excitation.

Simple empirical model for identifying rheological properties of soft biological tissues

Understanding the rheological properties of soft biological tissue is a key issue for mechanical systems used in the health care field. We propose a simple empirical model using fractional dynamics and exponential nonlinearity (FDEN) to identify the rheological properties of soft biological tissue. The model is derived from detailed material measurements using samples isolated from porcine liver. We conducted dynamic viscoelastic and creep tests on liver samples using a plate-plate rheometer. The experimental results indicated that biological tissue has specific properties: (i) power law increase in the storage elastic modulus and the loss elastic modulus of the same slope; (ii) power law compliance (gain) decrease and constant phase delay in the frequency domain; (iii) power law dependence between time and strain relationships in the time domain; and (iv) linear dependence in the low strain range and exponential law dependence in the high strain range between stress-strain relationships. Our simple FDEN model uses only three dependent parameters and represents the specific properties of soft biological tissue.

Material properties of bovine intervertebral discs across strain rates

The intervertebral disc (IVD) is a complex structure responsible for distributing compressive loading to adjacent vertebrae and allowing the vertebral column to bend and twist. To study the mechanical behaviour of individual components of the IVD, it is common for specimens to be dissected away from their surrounding tissues for mechanical testing. However, disrupting the continuity of the IVD to obtain material properties of each component separately may result in erroneous values. In this study, an inverse finite element (FE) modelling optimisation algorithm has been used to obtain material properties of the IVD across strain rates, therefore bypassing the need to harvest individual samples of each component. Uniaxial compression was applied to ten fresh-frozen bovine intervertebral discs at strain rates of 10^-3-1/s. The experimental data were fed into the inverse FE optimisation algorithm and each experiment was simulated using the subject specific FE model of the respective specimen. A sensitivity analysis revealed that the IVD's response was most dependent upon the Young's modulus (YM) of the fibre bundles and therefore this was chosen to be the parameter to optimise. Based on the obtained YM values for each test corresponding to a different strain rate (ε̇), the following relationship was derived:YM=35.5lnε̇+527.5. These properties can be used in finite element models of the IVD that aim to simulate spinal biomechanics across loading rates.

Determination of mechanical properties of spatially heterogeneous breast tissue specimens using contact mode atomic force microscopy (AFM)

This paper outlines a comprehensive parametric approach for quantifying mechanical properties of spatially heterogeneous thin biological specimens such as human breast tissue using contact-mode Atomic Force Microscopy. Using inverse finite element (FE) analysis of spherical nanoindentation, the force response from hyperelastic material models is compared with the predicted force response from existing analytical contact models, and a sensitivity study is carried out to assess uniqueness of the inverse FE solution. Furthermore, an automation strategy is proposed to analyze AFM force curves with varying levels of material nonlinearity with minimal user intervention. Implementation of our approach on an elastic map acquired from raster AFM indentation of breast tissue specimens indicates that a judicious combination of analytical and numerical techniques allow more accurate interpretation of AFM indentation data compared to relying on purely analytical contact models, while keeping the computational cost associated an inverse FE solution with reasonable limits. The results reported in this study have several implications in performing unsupervised data analysis on AFM indentation measurements on a wide variety of heterogeneous biomaterials.

The roles of cellular nanomechanics in cancer

The biomechanical properties of cells and tissues may be instrumental in increasing our understanding of cellular behavior and cellular manifestations of diseases such as cancer. Nanomechanical properties can offer clinical translation of therapies beyond what are currently employed. Nanomechanical properties, often measured by nanoindentation methods using atomic force microscopy, may identify morphological variations, cellular binding forces, and surface adhesion behaviors that efficiently differentiate normal cells and cancer cells. The aim of this review is to examine current research involving the general use of atomic force microscopy/nanoindentation in measuring cellular nanomechanics; various factors and instrumental conditions that influence the nanomechanical properties of cells; and implementation of nanoindentation methods to distinguish cancer cells from normal cells or tissues. Applying these fundamental nanomechanical properties to current discoveries in clinical treatment may result in greater efficiency in diagnosis, treatment, and prevention of cancer, which ultimately can change the lives of patients.