1,293 research outputs found

    In vivo articular cartilage deformation: noninvasive quantification of intratissue strain during joint contact in the human knee

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    The in vivo measurement of articular cartilage deformation is essential to understand how mechanical forces distribute throughout the healthy tissue and change over time in the pathologic joint. Displacements or strain may serve as a functional imaging biomarker for healthy, diseased, and repaired tissues, but unfortunately intratissue cartilage deformation in vivo is largely unknown. Here, we directly quantified for the first time deformation patterns through the thickness of tibiofemoral articular cartilage in healthy human volunteers. Magnetic resonance imaging acquisitions were synchronized with physiologically relevant compressive loading and used to visualize and measure regional displacement and strain of tibiofemoral articular cartilage in a sagittal plane. We found that compression (of 1/2 body weight) applied at the foot produced a sliding, rigid-body displacement at the tibiofemoral cartilage interface, that loading generated subject- and gender-specific and regionally complex patterns of intratissue strains, and that dominant cartilage strains (approaching 12%) were in shear. Maximum principle and shear strain measures in the tibia were correlated with body mass index. Our MRI-based approach may accelerate the development of regenerative therapies for diseased or damaged cartilage, which is currently limited by the lack of reliable in vivo methods for noninvasive assessment of functional changes following treatment

    Intervertebral Disc Structure and Mechanical Function Under Physiological Loading Quantified Non-invasively Utilizing MRI and Image Registration

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    The intervertebral discs (IVD) functions to permit motion, distribute load, and dissipate energy in the spine. It performs these functions through its heterogeneous structural organization and biochemical composition consisting of several tissue substructures: the central gelatinous nucleus pulposus (NP), the surrounding fiber reinforced layered annulus fibrosus (AF), and the cartilaginous endplates (CEP) that are positioned between the NP and vertebral endplates. Each tissue contributes individually to overall disc mechanics and by interacting with adjacent tissues. Disruption of the disc\u27s tissues through aging, degeneration, or tear will not only alter the affected tissue mechanical properties, but also the mechanical behavior of adjacent tissues and, ultimately, overall disc segment function. Thus, there is a need to measure disc tissue and segment mechanics in the intact disc so that interactions between substructures are not disrupted. Such measurements would be valuable to study mechanisms of disc function and degeneration, and develop and evaluate surgical procedures and therapeutic implants. The objectives of this study were to develop, validate, and apply methods to visualize and quantify IVD substructure geometry and track internal deformations for intact human discs under axial compression. The CEP and AF were visualized through MRI parameter mapping and image sequence optimization for ideal contrast. High-resolution images enabled geometric measurements. Axial compression was performed using a custom-built loading device that permitted long relaxation times outside of the MRI, 300 m isotropic resolution images were acquired, and image registration methods applied to measure 3D internal strain. In conclusion, new methods to visualize and quantify CEP thickness, annular tear detection and geometric quantification, and non-invasively measure 3D internal disc strains were established. No correlation was found between CEP thickness and disc level; however the periphery was significantly thicker compared to central locations. Clear distinction of adjacent AF lamellae enabled annular tear detection and detailed geometric quantification. Annular tears demonstrated non-classic geometry through interconnecting radial, circumferential, and perinuclear formations. Regional strain inhomogeneity was observed qualitatively and quantitatively. Variation in strain magnitudes might be explained by geometry in axial and circumferential strain while peak radial strain in the posterior AF may have important implications for disc herniation

    Doctor of Philosophy

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    dissertationImage-based biomechanics, particularly numerical modeling using subject-specific data obtained via imaging, has proven useful for elucidating several biomechanical processes, such as prediction of deformation due to external loads, applicable to both normal function and pathophysiology of various organs. As the field evolves towards applications that stretch the limits of imaging hardware and acquisition time, the information traditionally expected as input for numerical routines often becomes incomplete or ambiguous, and requires specific acquisition and processing strategies to ensure physical accuracy and compatibility with predictive mathematical modeling. These strategies, often derivatives or specializations of traditional mechanics, effectively extend the nominal capability of medical imaging hardware providing subject-specific information coupled with the option of using the results for predictive numerical simulations. This research deals with the development of tools for extracting mechanical measurements from a finite set of imaging data and finite element analysis in the context of constructing structural atlases of the heart, understanding the biomechanics of the venous vasculature, and right ventricular failure. The tools include: (1) application of Hyperelastic Warping image registration to displacement-encoded MRI for reconstructing absolute displacement fields, (2) combination of imaging and a material parameter identification approach to measure morphology, deformation, and mechanical properties of vascular tissue, and (3) extrapolation of diffusion tensor MRI acquired at a single time point for the prediction the structural changes across the cardiac cycle with mechanical simulations. Selected tools were then applied to evaluate structural changes in a reversible animal model for right ventricular failure due to pressure overload

    Analysis of contrast-enhanced medical images.

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    Early detection of human organ diseases is of great importance for the accurate diagnosis and institution of appropriate therapies. This can potentially prevent progression to end-stage disease by detecting precursors that evaluate organ functionality. In addition, it also assists the clinicians for therapy evaluation, tracking diseases progression, and surgery operations. Advances in functional and contrast-enhanced (CE) medical images enabled accurate noninvasive evaluation of organ functionality due to their ability to provide superior anatomical and functional information about the tissue-of-interest. The main objective of this dissertation is to develop a computer-aided diagnostic (CAD) system for analyzing complex data from CE magnetic resonance imaging (MRI). The developed CAD system has been tested in three case studies: (i) early detection of acute renal transplant rejection, (ii) evaluation of myocardial perfusion in patients with ischemic heart disease after heart attack; and (iii), early detection of prostate cancer. However, developing a noninvasive CAD system for the analysis of CE medical images is subject to multiple challenges, including, but are not limited to, image noise and inhomogeneity, nonlinear signal intensity changes of the images over the time course of data acquisition, appearances and shape changes (deformations) of the organ-of-interest during data acquisition, determination of the best features (indexes) that describe the perfusion of a contrast agent (CA) into the tissue. To address these challenges, this dissertation focuses on building new mathematical models and learning techniques that facilitate accurate analysis of CAs perfusion in living organs and include: (i) accurate mathematical models for the segmentation of the object-of-interest, which integrate object shape and appearance features in terms of pixel/voxel-wise image intensities and their spatial interactions; (ii) motion correction techniques that combine both global and local models, which exploit geometric features, rather than image intensities to avoid problems associated with nonlinear intensity variations of the CE images; (iii) fusion of multiple features using the genetic algorithm. The proposed techniques have been integrated into CAD systems that have been tested in, but not limited to, three clinical studies. First, a noninvasive CAD system is proposed for the early and accurate diagnosis of acute renal transplant rejection using dynamic contrast-enhanced MRI (DCE-MRI). Acute rejection–the immunological response of the human immune system to a foreign kidney–is the most sever cause of renal dysfunction among other diagnostic possibilities, including acute tubular necrosis and immune drug toxicity. In the U.S., approximately 17,736 renal transplants are performed annually, and given the limited number of donors, transplanted kidney salvage is an important medical concern. Thus far, biopsy remains the gold standard for the assessment of renal transplant dysfunction, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The diagnostic results of the proposed CAD system, based on the analysis of 50 independent in-vivo cases were 96% with a 95% confidence interval. These results clearly demonstrate the promise of the proposed image-based diagnostic CAD system as a supplement to the current technologies, such as nuclear imaging and ultrasonography, to determine the type of kidney dysfunction. Second, a comprehensive CAD system is developed for the characterization of myocardial perfusion and clinical status in heart failure and novel myoregeneration therapy using cardiac first-pass MRI (FP-MRI). Heart failure is considered the most important cause of morbidity and mortality in cardiovascular disease, which affects approximately 6 million U.S. patients annually. Ischemic heart disease is considered the most common underlying cause of heart failure. Therefore, the detection of the heart failure in its earliest forms is essential to prevent its relentless progression to premature death. While current medical studies focus on detecting pathological tissue and assessing contractile function of the diseased heart, this dissertation address the key issue of the effects of the myoregeneration therapy on the associated blood nutrient supply. Quantitative and qualitative assessment in a cohort of 24 perfusion data sets demonstrated the ability of the proposed framework to reveal regional perfusion improvements with therapy, and transmural perfusion differences across the myocardial wall; thus, it can aid in follow-up on treatment for patients undergoing the myoregeneration therapy. Finally, an image-based CAD system for early detection of prostate cancer using DCE-MRI is introduced. Prostate cancer is the most frequently diagnosed malignancy among men and remains the second leading cause of cancer-related death in the USA with more than 238,000 new cases and a mortality rate of about 30,000 in 2013. Therefore, early diagnosis of prostate cancer can improve the effectiveness of treatment and increase the patient’s chance of survival. Currently, needle biopsy is the gold standard for the diagnosis of prostate cancer. However, it is an invasive procedure with high costs and potential morbidity rates. Additionally, it has a higher possibility of producing false positive diagnosis due to relatively small needle biopsy samples. Application of the proposed CAD yield promising results in a cohort of 30 patients that would, in the near future, represent a supplement of the current technologies to determine prostate cancer type. The developed techniques have been compared to the state-of-the-art methods and demonstrated higher accuracy as shown in this dissertation. The proposed models (higher-order spatial interaction models, shape models, motion correction models, and perfusion analysis models) can be used in many of today’s CAD applications for early detection of a variety of diseases and medical conditions, and are expected to notably amplify the accuracy of CAD decisions based on the automated analysis of CE images

    Intranuclear strain measured by iterative warping in cells under mechanical and osmotic stress

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    The nucleus is a membrane bound organelle and regulation center for gene expression in the cell. Mechanical forces transfer to the nucleus directly and indirectly through specific cellular cytoskeletal structures and pathways. There is increasing evidence that the transferred forces to the nucleus orchestrate gene expression activity. Methods to characterize nuclear mechanics typically study isolated cells or cells embedded in 3D gel matrices. Often report only aspect ratio and volume changes, measures that oversimplify the inherent complexity of internal strain patterns. This presents technical challenges to simultaneously observe small scale nuclear mechanics and gene expression levels inside the nuclei of cells embedded in their native extracellular environment. Therefore, a hybrid imaging and model based image registration technique has been developed to enabled us to explore links between biomechanical and biochemical signaling within individual cells. The hybrid technique uses an iterative warping deformable image registration to measure intranuclear strain fields that are correlated to nuclear structures. Three cell mechanics methods were developed to examine the mechanical response of the nucleus under different mechanical conditions. 1) Strain transfer from tissue to nuclei in a cartilage tissue deformation model paired with nascent RNA expression, 2) strain transfer to the nucleus with different cell types on a stretchable membrane, and 3) force traction microscopy of cells during osmotic stress. Intranuclear strain fields provide spatial details of the nucleus that when paired with single cell biochemical assays will provide insight into how mechanical forces transferred to the nucleus influence gene expression

    Tomographic measurement of all orthogonal components of three-dimensional displacement fields within scattering materials using wavelength scanning interferometry

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    Experimental mechanics is currently contemplating tremendous opportunities of further advancements thanks to a combination of powerful computational techniques and also fullfield non-contact methods to measure displacement and strain fields in a wide variety of materials. Identification techniques, aimed to evaluate material mechanical properties given known loads and measured displacement or strain fields, are bound to benefit from increased data availability (both in density and dimensionality) and efficient inversion methods such as finite element updating (FEU) and the virtual fields method (VFM). They work at their best when provided with dense and multicomponent experimental displacement (or strain) data, i.e. when all orthogonal components of displacements (or all components of the strain tensor) are known at points closely spaced within the volume of the material under study. Although a very challenging requirement, an increasing number of techniques are emerging to provide such data. In this Thesis, a novel wavelength scanning interferometry (WSI) system that provides three dimensional (3-D) displacement fields inside the volume of semi-transparent scattering materials is proposed. Sequences of two-dimensional interferograms are recorded whilst tuning the frequency of a laser at a constant rate. A new approach based on frequency multiplexing is used to encode the interference signal corresponding to multiple illumination directions at different spectral bands. Different optical paths along each illumination direction ensure that the signals corresponding to each sensitivity vector do not overlap in the frequency domain. All the information required to reconstruct the location and the 3-D displacement vector of scattering points within the material is thus recorded simultaneously in a single wavelength scan. By comparing phase data volumes obtained for two successive scans, all orthogonal components of the three dimensional displacement field introduced between scans (e.g. by means of loading or moving the sample under study) are readily obtained with high displacement sensitivity. The fundamental principle that describes the technique is presented in detail, including the correspondence between interference signal frequency and its associated depth within the sample, depth range, depth resolution, transverse resolution and displacement sensitivity. Data processing of the interference signal includes Fourier transformation, noise reduction, re-registration of data volumes, measurement of the illumination and sensitivity vectors from experimental data using a datum surface, phase difference evaluation, 3-D phase unwrapping and 3-D displacement field evaluation. Experiments consisting of controlled rigid body rotations and translations of a phantom were performed to validate the results. Both in-plane and the out-of-plane displacement components were measured for each voxel in the resulting data volume, showing an excellent agreement with the expected 3-D displacement

    Advanced Algorithms for 3D Medical Image Data Fusion in Specific Medical Problems

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    Fúze obrazu je dnes jednou z nejběžnějších avšak stále velmi diskutovanou oblastí v lékařském zobrazování a hraje důležitou roli ve všech oblastech lékařské péče jako je diagnóza, léčba a chirurgie. V této dizertační práci jsou představeny tři projekty, které jsou velmi úzce spojeny s oblastí fúze medicínských dat. První projekt pojednává o 3D CT subtrakční angiografii dolních končetin. V práci je využito kombinace kontrastních a nekontrastních dat pro získání kompletního cévního stromu. Druhý projekt se zabývá fúzí DTI a T1 váhovaných MRI dat mozku. Cílem tohoto projektu je zkombinovat stukturální a funkční informace, které umožňují zlepšit znalosti konektivity v mozkové tkáni. Třetí projekt se zabývá metastázemi v CT časových datech páteře. Tento projekt je zaměřen na studium vývoje metastáz uvnitř obratlů ve fúzované časové řadě snímků. Tato dizertační práce představuje novou metodologii pro klasifikaci těchto metastáz. Všechny projekty zmíněné v této dizertační práci byly řešeny v rámci pracovní skupiny zabývající se analýzou lékařských dat, kterou vedl pan Prof. Jiří Jan. Tato dizertační práce obsahuje registrační část prvního a klasifikační část třetího projektu. Druhý projekt je představen kompletně. Další část prvního a třetího projektu, obsahující specifické předzpracování dat, jsou obsaženy v disertační práci mého kolegy Ing. Romana Petera.Image fusion is one of today´s most common and still challenging tasks in medical imaging and it plays crucial role in all areas of medical care such as diagnosis, treatment and surgery. Three projects crucially dependent on image fusion are introduced in this thesis. The first project deals with the 3D CT subtraction angiography of lower limbs. It combines pre-contrast and contrast enhanced data to extract the blood vessel tree. The second project fuses the DTI and T1-weighted MRI brain data. The aim of this project is to combine the brain structural and functional information that purvey improved knowledge about intrinsic brain connectivity. The third project deals with the time series of CT spine data where the metastases occur. In this project the progression of metastases within the vertebrae is studied based on fusion of the successive elements of the image series. This thesis introduces new methodology of classifying metastatic tissue. All the projects mentioned in this thesis have been solved by the medical image analysis group led by Prof. Jiří Jan. This dissertation concerns primarily the registration part of the first project and the classification part of the third project. The second project is described completely. The other parts of the first and third project, including the specific preprocessing of the data, are introduced in detail in the dissertation thesis of my colleague Roman Peter, M.Sc.

    Measurement of intracellular strain on deformable substrates with texture correlation.

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    Mechanical stimuli are important factors that regulate cell proliferation, survival, metabolism and motility in a variety of cell types. The relationship between mechanical deformation of the extracellular matrix and intracellular deformation of cellular sub-regions and organelles has not been fully elucidated, but may provide new insight into the mechanisms involved in transducing mechanical stimuli to biological responses. In this study, a novel fluorescence microscopy and image analysis method was applied to examine the hypothesis that mechanical strains are fully transferred from a planar, deformable substrate to cytoplasmic and intranuclear regions within attached cells. Intracellular strains were measured in cells derived from the anulus fibrosus of the intervertebral disc when attached to an elastic silicone membrane that was subjected to tensile stretch. Measurements indicated cytoplasmic strains were similar to those of the underlying substrate, with a strain transfer ratio (STR) of 0.79. In contrast, nuclear strains were much smaller than those of the substrate, with an STR of 0.17. These findings are consistent with previous studies indicating nuclear stiffness is significantly greater than cytoplasmic stiffness, as measured using other methods. This study provides a novel method for the study of cellular mechanics, including a new technique for measuring intranuclear deformations, with evidence of differential magnitudes and patterns of strain transferred from the substrate to cell cytoplasm and nucleus
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