Two-dimensional Microwave Tomographic Imaging of Breast Tissues

Despite its recognized value in detecting and characterizing breast disease, X-ray mammography has important limitations that motivate the quest for alternatives to augment the diagnostic tools that are currently available to the radiologist. The rationale for pursuing electromagnetic methods are based on the significant dielectric contrast between normal and cancerous breast tissues, when exposed to microwaves. The present study analyzes two-dimensional microwave tomographic imaging on normal and malignant breast tissue samples extracted by mastectomy, to assess the suitability of the technique for early detection ofbreast cancer. The tissue samples are immersed in matching coupling medium and are illuminated by 3 GHz signal. 2-D tomographic images ofthe breast tissue samples are reconstructed from the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles, which is a clear indication of the presence of malignancy. Hence microwave tomographic imaging is proposed as an alternate imaging modality for early detection ofbreast cancer.

Mechanical tension as a driver of connective tissue growth in vitro

We propose the progressive mechanical expansion of cell-derived tissue analogues as a novel, growth-based approach to in vitro tissue engineering. The prevailing approach to producing tissue in vitro is to culture cells in an exogenous “scaffold” that provides a basic structure and mechanical support. This necessarily pre-defines the final size of the implantable material, and specific signals must be provided to stimulate appropriate cell growth, differentiation and matrix formation. In contrast, surgical skin expansion, driven by increments of stretch, produces increasing quantities of tissue without trauma or inflammation. This suggests that connective tissue cells have the innate ability to produce growth in response to elevated tension. We posit that this capacity is maintained in vitro, and that order-of-magnitude growth may be similarly attained in self-assembling cultures of cells and their own extracellular matrix. The hypothesis that growth of connective tissue analogues can be induced by mechanical expansion in vitro may be divided into three components: (1) tension stimulates cell proliferation and extracellular matrix synthesis; (2) the corresponding volume increase will relax the tension imparted by a fixed displacement; (3) the repeated application of static stretch will produce sustained growth and a tissue structure adapted to the tensile loading. Connective tissues exist in a state of residual tension, which is actively maintained by resident cells such as fibroblasts. Studies in vitro and in vivo have demonstrated that cellular survival, reproduction, and matrix synthesis and degradation are regulated by the mechanical environment. Order-of-magnitude increases in both bone and skin volume have been achieved clinically through staged expansion protocols, demonstrating that tension-driven growth can be sustained over prolonged periods. Furthermore, cell-derived tissue analogues have demonstrated mechanically advantageous structural adaptation in response to applied loading. Together, these data suggest that a program of incremental stretch constitutes an appealing way to replicate tissue growth in cell culture, by harnessing the constituent cells’ innate mechanical responsiveness. In addition to offering a platform to study the growth and structural adaptation of connective tissues, tension-driven growth presents a novel approach to in vitro tissue engineering. Because the supporting structure is secreted and organised by the cells themselves, growth is not restricted by a “scaffold” of fixed size. This also minimises potential adverse reactions to exogenous materials upon implantation. Most importantly, we posit that the growth induced by progressive stretch will allow substantial volumes of connective tissue to be produced from relatively small initial cell numbers.

Effect of partial H2O-D2O replacement on the anisotropy of transverse proton spin relaxation in bovine articular cartilage

Anisotropy of transverse proton spin relaxation in collagen-rich tissues like cartilage and tendon is a well-known phenomenon that manifests itself as the "magic-angle" effect in magnetic resonance images of these tissues. It is usually attributed to the non-zero averaging of intra-molecular dipolar interactions in water molecules bound to oriented collagen fibers. One way to manipulate the contributions of these interactions to spin relaxation is by partially replacing the water in the cartilage sample with deuterium oxide. It is known that dipolar interactions in deuterated solutions are weaker, resulting in a decrease in proton relaxation rates. In this work, we investigate the effects of deuteration on the longitudinal and the isotropic and anisotropic contributions to transverse relaxation of water protons in bovine articular cartilage. We demonstrate that the anisotropy of transverse proton spin relaxation in articular cartilage is independent of the degree of deuteration, bringing into question some of the assumptions currently held over the origins of relaxation anisotropy in oriented tissues.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Formalin fixation affects equilibrium partitioning of an ionic contrast agent-microcomputed tomography (EPIC-[mu]CT) imaging of osteochondral samples

Equilibrium Partitioning of an Ionic Contrast agent with microcomputed tomography (EPIC-[mu]CT) is a non-invasive technique to quantify and visualize the three-dimensional distribution of glycosaminoglycans (GAGs) in fresh cartilage tissue. However, it is unclear whether this technique is applicable to already fixed tissues. Therefore, this study aimed at investigating whether formalin fixation of bovine cartilage affects X-ray attenuation, and thus the interpretation of EPIC-[mu]CT data.Design Osteochondral samples (n = 24) were incubated with ioxaglate, an ionic contrast agent, for 22 h prior to [mu]CT scanning. The samples were scanned in both formalin-fixed and fresh conditions. GAG content was measured using a biochemical assay and normalized to wet weight, dry weight, and water content to determine potential reasons for differences in X-ray attenuation.Results The expected zonal distribution of contrast agent/GAGs was observed for both fixed and fresh cartilage specimens. However, despite no significant differences in GAG concentrations or physical properties between fixed and fresh samples, the average attenuation levels of formalin-fixed cartilage were 14.3% lower than in fresh samples.Conclusions EPIC-[mu]CT is useful for three-dimensional visualization of GAGs in formalin-fixed cartilage. However, a significant reduction in X-ray attenuation for fixed (compared to fresh) cartilage must be taken into account and adjusted for accordingly when quantifying GAG concentrations using EPIC-[mu]CT.

Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.

Imaging of human lens lipids by desorption electrospray ionization mass spectrometry

The lipid composition of the human lens is distinct from most other tissues in that it is high in dihydrosphingomyelin and the most abundant glycerophospholipids in the lens are unusual 1-O-alkyl-ether linked phosphatidylethanolamines and phosphatidylserines. In this study, desorption electrospray ionization (DESI) mass spectrometry-imaging was used to determine the distribution of these lipids in the human lens along with other lipids including, ceramides, ceramide-1-phosphates, and lyso 1-O-alkyl ethers. To achieve this, 25 μm lens slices were mounted onto glass slides and analyzed using a linear ion-trap mass spectrometer equipped with a custom-built, 2-D automated DESI source. In contrast to other tissues that have been previously analyzed by DESI, the presence of a strong acid in the spray solvent was required to desorb lipids directly from lens tissue. Distinctive distributions were observed for [M + H]+ ions arising from each lipid class. Of particular interest were ionized 1-O-alkyl phosphatidylethanolamines and phosphatidylserines, PE (18:1e/18:1), and PS (18:1e/18:1), which were found in a thin ring in the outermost region of the lens. This distribution was confirmed by quantitative analysis of lenses that were sectioned into four distinct regions (outer, barrier, inner, and core), extracted and analyzed by electrospray ionization tandem mass spectrometry. DESI-imaging also revealed a complementary distribution for the structurally-related lyso 1-O-alkyl phosphatidylethanolamine, LPE (18:1e), which was localized closer to the centre of the lens. The data obtained in this study indicate that DESI-imaging is a powerful tool for determining the spatial distribution of human lens lipids. © 2010 American Society for Mass Spectrometry.

Analytical solutions for diffuse fluorescence spectroscopy/imaging in biological tissues. Part I: zero and extrapolated boundary conditions

The mathematical model for diffuse fluorescence spectroscopy/imaging is represented by coupled partial differential equations (PDEs), which describe the excitation and emission light propagation in soft biological tissues. The generic closed-form solutions for these coupled PDEs are derived in this work for the case of regular geometries using the Green's function approach using both zero and extrapolated boundary conditions. The specific solutions along with the typical data types, such as integrated intensity and the mean time of flight, for various regular geometries were also derived for both time-and frequency-domain cases. (C) 2013 Optical Society of America

Analytical solutions for diffuse fluorescence spectroscopy/imaging in biological tissues. Part II: comparison and validation

The analytical solutions for the coupled diffusion equations that are encountered in diffuse fluorescence spectroscopy/ imaging for regular geometries were compared with the well-established numerical models, which are based on the finite element method. Comparison among the analytical solutions obtained using zero boundary conditions and extrapolated boundary conditions (EBCs) was also performed. The results reveal that the analytical solutions are in close agreement with the numerical solutions, and solutions obtained using EBCs are more accurate in obtaining the mean time of flight data compared to their counterpart. The analytical solutions were also shown to be capable of providing bulk optical properties through a numerical experiment using a realistic breast model. (C) 2013 Optical Society of America

Hyperpolarized Xe MR imaging of alveolar gas uptake in humans.

BACKGROUND: One of the central physiological functions of the lungs is to transfer inhaled gases from the alveoli to pulmonary capillary blood. However, current measures of alveolar gas uptake provide only global information and thus lack the sensitivity and specificity needed to account for regional variations in gas exchange. METHODS AND PRINCIPAL FINDINGS: Here we exploit the solubility, high magnetic resonance (MR) signal intensity, and large chemical shift of hyperpolarized (HP) (129)Xe to probe the regional uptake of alveolar gases by directly imaging HP (129)Xe dissolved in the gas exchange tissues and pulmonary capillary blood of human subjects. The resulting single breath-hold, three-dimensional MR images are optimized using millisecond repetition times and high flip angle radio-frequency pulses, because the dissolved HP (129)Xe magnetization is rapidly replenished by diffusive exchange with alveolar (129)Xe. The dissolved HP (129)Xe MR images display significant, directional heterogeneity, with increased signal intensity observed from the gravity-dependent portions of the lungs. CONCLUSIONS: The features observed in dissolved-phase (129)Xe MR images are consistent with gravity-dependent lung deformation, which produces increased ventilation, reduced alveolar size (i.e., higher surface-to-volume ratios), higher tissue densities, and increased perfusion in the dependent portions of the lungs. Thus, these results suggest that dissolved HP (129)Xe imaging reports on pulmonary function at a fundamental level.

Mass spectrometry imaging of glucosinolates in arabidopsis flowers and siliques

Glucosinolates are multi-functional plant secondary metabolites which play a vital role in plant defence and are, as dietary compounds, important to human health and livestock well-being. Knowledge of the tissue-specific regulation of their biosynthesis and accumulation is essential for plant breeding programs. Here, we report that in Arabidopsis thaliana, glucosinolates are accumulated differentially in specific cells of reproductive organs. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), distribution patterns of three selected compounds, 4-methylsulfinylbutyl (glucoraphanin), indol-3-ylmethyl (glucobrassicin), and 4-benzoyloxybutyl glucosinolates, were mapped in the tissues of whole flower buds, sepals and siliques. The results show that tissue localization patterns of aliphatic glucosinolate glucoraphanin and 4-benzoyloxybutyl glucosinolate were similar, but indole glucosinolate glucobrassicin had different localisation, indicating a possible difference in function. The high resolution images obtained by a complementary approach, cryo-SEM Energy Dispersive X-ray analysis (cryo-SEM-EDX), confirmed increased concentration of sulphur in areas with elevated amounts of glucosinolates, and allowed identifying the cell types implicated in accumulation of glucosinolates. High concentration of sulphur was found in S-cells adjacent to the phloem in pedicels and siliques, indicating the presence of glucosinolates. Moreover, both MALDI MSI and cryo-SEM-EDX analyses indicated accumulation of glucosinolates in cells on the outer surface of the sepals, suggesting that a layer of glucosinolate-accumulating epidermal cells protects the whole of the developing flower, in addition to the S-cells, which protect the phloem. This research demonstrates the high potential of MALDI MSI for understanding the cell-specific compartmentation of plant metabolites and its regulation.

Analysis of biological tissues in infant chest for the development of an equivalent radiographic phantom

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fluorescence and confocal laser scanning microscopy imaging of elastic fibers in hematoxylin-eosin stained sections

We have studied the possibility of associating fluorescence microscopy and hematoxylin-eosin staining for the identification of elastic fibers in elastin-rich tissues. Elastic fibers and elastic laminae were consistently identified by the proposed procedure, which revealed itself to be easy and useful for the determination of such structures and their distribution. The fluorescence properties of stained elastic fibers are due to eosin staining as revealed by fluorescence analysis of the dye in solution, with no or only minor contribution by the elastin autofluorescence. The main advantage of this technique resides in the possibility of studying the distribution of elastic fibers in file material without further sectioning and staining. The use of the confocal laser scanning microscope greatly improved the resolution and selectivity of imaging elastic fibers in different tissues. The determination of the three-dimensional distribution and structure of elastic fiber and laminae using the confocal laser scanning microscope was evaluated and also produced excellent results.

Histologic Characterization of Engineered Tissues in the Canal Space of Closed-apex Teeth with Apical Periodontitis

Introduction: The aim of this study was to investigate the capacity of endodontic regenerative procedures combining an induced blood clot, platelet-rich plasma (PRP), and bone marrow aspirate (BMA) to regenerate dental pulp in canine closed-apex necrotic teeth. Methods: Apical periodontitis was induced in 20 upper and lower premolars of 2 dogs. After biomechanical preparation, enlargement to a #60 file, and disinfection with a triantibiotic paste for 28 days, the roots were randomly assigned to 4 treatment groups: blood clot (BC), BC + PRP gel, BC + BMA gel, and BC + BMA/PRP gel. Negative controls were also included. After a 3-month follow-up period, the animals were killed. Results: Histologic analysis showed the presence of newly formed vital tissues (connective, cement-like, and bone-like tissue) in 23 of the 32 treated roots (71.87%). There was no statistically significant difference between the treatment groups. Conclusions: New vital tissues were formed and characterized as connective, cementum-like, or bone-like, but not as pulp-like tissue; PRP and/or BMA did not improve the tissue ingrowth. © 2013 American Association of Endodontists.

Nanoassisted Laser Desorption-Ionization-MS Imaging of Tumors

The ability of nanoassisted laser desorption-ionization mass spectrometry (NALDI-MS) imaging to provide selective chemical monitoring with proper spatial distribution of lipid profiles from tumor tissues after plate imprinting has been tested. NALDI-MS imaging identified and mapped several potential lipid biomarkers in a murine model of melanoma tumor (inoculation of B16/F10 cells). It also confirmed that the in vivo treatment of tumor bearing mice with synthetic supplement containing phosphoethanolamine (PHO-S) promoted an accentuated decrease in relative abundance of the tumor biomarkers. NALDI-MS imaging is a matrix-free LDI protocol based on the selective imprinting of lipids in the NALDI plate followed by the removal of the tissue. It therefore provides good quality and selective chemical images with preservation of spatial distribution and less interference from tissue material. The test case described herein illustrates the potential of chemically selective NALDI-MS imaging for biomarker discovery.