Identifying and training deep learning neural networks on biomedical-related datasets.

This manuscript describes the development of a resources module that is part of a learning platform named 'NIGMS Sandbox for Cloud-based Learning' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on implementing deep learning algorithms for biomedical image data in an interactive format that uses appropriate cloud resources for data access and analyses. Biomedical-related datasets are widely used in both research and clinical settings, but the ability for professionally trained clinicians and researchers to interpret datasets becomes difficult as the size and breadth of these datasets increases. Artificial intelligence, and specifically deep learning neural networks, have recently become an important tool in novel biomedical research. However, use is limited due to their computational requirements and confusion regarding different neural network architectures. The goal of this learning module is to introduce types of deep learning neural networks and cover practices that are commonly used in biomedical research. This module is subdivided into four submodules that cover classification, augmentation, segmentation and regression. Each complementary submodule was written on the Google Cloud Platform and contains detailed code and explanations, as well as quizzes and challenges to facilitate user training. Overall, the goal of this learning module is to enable users to identify and integrate the correct type of neural network with their data while highlighting the ease-of-use of cloud computing for implementing neural networks. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Label-Free Optical Metabolic Imaging in Cells and Tissues.

Over the last half century, the autofluorescence of the metabolic cofactors NADH (reduced nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide) has been quantified in a variety of cell types and disease states. With the spread of nonlinear optical microscopy techniques in biomedical research, NADH and FAD imaging has offered an attractive solution to noninvasively monitor cell and tissue status and elucidate dynamic changes in cell or tissue metabolism. Various tools and methods to measure the temporal, spectral, and spatial properties of NADH and FAD autofluorescence have been developed. Specifically, an optical redox ratio of cofactor fluorescence intensities and NADH fluorescence lifetime parameters have been used in numerous applications, but significant work remains to mature this technology for understanding dynamic changes in metabolism. This article describes the current understanding of our optical sensitivity to different metabolic pathways and highlights current challenges in the field. Recent progress in addressing these challenges and acquiring more quantitative information in faster and more metabolically relevant formats is also discussed.

Mechanical Models of Collagen Networks for Understanding Changes in the Failure Properties of Aging Skin.

Skin undergoes mechanical alterations due to changes in the composition and structure of the collagenous dermis with aging. Previous studies have conflicting findings, with both increased and decreased stiffness reported for aging skin. The underlying structure-function relationships that drive age-related changes are complex and difficult to study individually. One potential contributor to these variations is the accumulation of nonenzymatic crosslinks within collagen fibers, which affect dermal collagen remodeling and mechanical properties. Specifically, these crosslinks make individual fibers stiffer in their plastic loading region and lead to increased fragmentation of the collagenous network. To better understand the influence of these changes, we investigated the impact of nonenzymatic crosslink changes on the dermal microstructure using discrete fiber networks representative of the dermal microstructure. Our findings suggest that stiffening the plastic region of collagen's mechanical response has minimal effects on network-level stiffness and failure stresses. Conversely, simulating fragmentation through a loss of connectivity substantially reduces network stiffness and failure stress, while increasing stretch ratios at failure.

Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model.

The objective of this study was to investigate if delivering multiple doses of N-acetylcysteine (NAC) post-surgery in addition to pre-incisional administration significantly impacts the wound healing process in a rat model. Full-thickness skin incisions were carried out on the dorsum of 24 Sprague-Dawley rats in six locations. Fifteen minutes prior to the incision, half of the sites were treated with a control solution, with the wounds on the contralateral side treated with solutions containing 0.015%, 0.03% and 0.045% of NAC. In the case of the NAC treated group, further injections were given every 8 h for three days. On days 3, 7, 14 and 60 post-op, rats were sacrificed to gather material for the histological analysis, which included histomorphometry, collagen fiber organization analysis, immunohistochemistry and Abramov scale scoring. It was determined that scars treated with 0.015% NAC had significantly lower reepithelization than the control at day 60 post-op (p = 0.0018). Scars treated with 0.045% NAC had a significantly lower collagen fiber variance compared to 0.015% NAC at day 14 post-op (p = 0.02 and p = 0.04) and a lower mean scar width than the control at day 60 post-op (p = 0.0354 and p = 0.0224). No significant differences in the recruitment of immune cells and histological parameters were found. The results point to a limited efficacy of multiple NAC injections post-surgery in wound healing.

Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading.

Skin is a complex tissue whose biomechanical properties are generally understood in terms of an incompressible material whose microstructure undergoes affine deformations. A growing number of experiments, however, have demonstrated that skin has a high Poisson's ratio, substantially decreases in volume during uniaxial tensile loading, and demonstrates collagen fiber kinematics that are not affine with local deformation. In order to better understand the mechanical basis for these properties, we constructed multiscale mechanical models (MSM) of mouse skin based on microstructural multiphoton microscopy imaging of the dermal microstructure acquired during mechanical testing. Three models that spanned the cases of highly aligned, moderately aligned, and nearly random fiber networks were examined and compared to the data acquired from uniaxially stretched skin. Our results demonstrate that MSMs consisting of networks of matched fiber organization can predict the biomechanical behavior of mouse skin, including the large decrease in tissue volume and nonaffine fiber kinematics observed under uniaxial tension.

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label-Free Multiphoton Microscopy Using Convolutional Neural Networks.

BACKGROUND AND OBJECTIVES: Histological analysis is a gold standard technique for studying impaired skin wound healing. Label-free multiphoton microscopy (MPM) can provide natural image contrast similar to histological sections and quantitative metabolic information using NADH and FAD autofluorescence. However, MPM analysis requires time-intensive manual segmentation of specific wound tissue regions limiting the practicality and usage of the technology for monitoring wounds. The goal of this study was to train a series of convolutional neural networks (CNNs) to segment MPM images of skin wounds to automate image processing and quantification of wound geometry and metabolism. STUDY DESIGN/MATERIALS AND METHODS: Two CNNs with a 4-layer U-Net architecture were trained to segment unstained skin wound tissue sections and in vivo z-stacks of the wound edge. The wound section CNN used 380 distinct MPM images while the in vivo CNN used 5,848 with both image sets being randomly distributed to training, validation, and test sets following a 70%, 20%, and 10% split. The accuracy of each network was evaluated on the test set of images, and the effectiveness of automated measurement of wound geometry and optical redox ratio were compared with hand traced outputs of six unstained wound sections and 69 wound edge z-stacks from eight mice. RESULTS: The MPM wound section CNN had an overall accuracy of 92.83%. Measurements of epidermal/dermal thickness, wound depth, wound width, and % re-epithelialization were within 10% error when evaluated on six full wound sections from days 3, 5, and 10 post-wounding that were not included in the training set. The in vivo wound z-stack CNN had an overall accuracy of 89.66% and was able to isolate the wound edge epithelium in z-stacks from eight mice across post-wound time points to quantify the optical redox ratio within 5% of what was recorded by manual segmentations. CONCLUSION: The CNNs trained and presented in this study can accurately segment MPM imaged wound sections and in vivo z-stacks to enable automated and rapid calculation of wound geometry and metabolism. Although MPM is a noninvasive imaging modality well suited to imaging living wound tissue, its use has been limited by time-intensive user segmentation. The use of CNNs for automated image segmentation demonstrate that it is possible for MPM to deliver near real-time quantitative readouts of tissue structure and function. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Tissue Imaging and Quantification Relying on Endogenous Contrast.

Cell-matrix interactions play an important role in regulating a variety of essential processes in multicellular organisms, and are closely associated with numerous diseases. Modified interactions have major effects upon key features of both cells and extracellular matrix (ECM), and a thorough understanding of changes in these features can lead to critically important insights of diseases as well as the identification of effective therapeutic targets. Here, we summarize recent advances in quantitative, optical imaging of cellular metabolism and ECM spatial organization using endogenous sources of contrast. Specifically, we focus on the two-photon excited fluorescence (TPEF) imaging of autofluorescent cellular coenzymes, NAD(P)H and FAD, for the extraction of metabolic information described by optical biomarkers including cellular redox state, NAD(P)H fluorescence lifetime, and mitochondrial clustering. We show representative applications in assessing adipose tissue function and detecting malignant lesions in human skin, and further demonstrate that a combination of these optical metrics can provide complementary insights into the underlying biological mechanisms. In addition, we review the development of quantitative analysis methods to extract spatial orientation and organization metrics of collagen fibers, a major ECM component, and demonstrate applications of these approaches in two and three dimensions in several diseases, including would healing, osteoarthritis and cancer, as well as assessments of matrix remodeling in hormone-regulated engineered breast tissues. Finally, we summarize this chapter and discuss important research directions that we expect will evolve in the near future.

N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing-An Animal Model Study.

The aim of the study was to evaluate if a pre-incisional N-acetylcysteine (NAC) treatment altered the process of wound healing in a rat model. The dorsal skin of 24 Sprague-Dawley rats was incised in six locations. Before the incisions were made, skin was injected either with lidocaine and epinephrine (one side) or with these agents supplemented with 0.015%, 0.03%, or 0.045% NAC (contralaterally). Photographic documentation of the wound healing process was made at 11 time points. Rats were sacrificed 3, 7, 14, or 60 days after incision to excise scars for histological analysis. They included: Abramov scale scoring, histomorphometry analysis, and collagen fiber arrangement assessment. Skin pretreated with 0.03% NAC produced the shortest scars at all analyzed time points, though this result was statistically insignificant. At this NAC concentration the scars had smaller areas on the third day and were narrower on the day 4 compared with all the other groups (p < 0.05). On day 7, at the same concentration of NAC, the scars had a higher superficial concentration index (p = 0.03) and larger dermal proliferation area (p = 0.04). NAC addition to pre-incisional anesthetic solution decreased wound size and width at an early stage of scar formation at all concentrations; however, with optimal results at 0.03% concentration.

Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFß1 and Growth Factors in Rat Wound Healing.

In this study, we aimed to investigate the influence of N-acetylcysteine (NAC) on the gene expression profile, neoangiogenesis, neutrophils and macrophages in a rat model of incisional wounds. Before creating wounds on the backs of 24 Sprague-Dawley rats, intradermal injections were made. Lidocaine-epinephrin solutions were supplemented with 0.015%, 0.03% or 0.045% solutions of NAC, or nothing (control group). Scars were harvested on the 3rd, 7th, 14th and 60th day post-surgery. We performed immunohistochemical staining in order to visualize macrophages (anti-CD68), neutrophils (anti-MPO) and newly formed blood vessels (anti-CD31). Additionally, RT-qPCR was used to measure the relative expression of 88 genes involved in the wound healing process. On the 14th day, the number of cells stained with anti-CD68 and anti-CD31 antibodies was significantly larger in the tissues treated with 0.03% NAC compared with the control. Among the selected genes, 52 were upregulated and six were downregulated at different time points. Interestingly, NAC exerted a significant effect on the expression of 45 genes 60 days after its administration. In summation, a 0.03% NAC addition to the pre-incisional anesthetic solution improves neovasculature and increases the macrophages' concentration at the wound site on the 14th day, as well as altering the expression of numerous genes that are responsible for the regenerative processes.

Label-free optical biomarkers detect early calcific aortic valve disease in a wild-type mouse model.

BACKGROUND: Calcific aortic valve disease (CAVD) pathophysiology is a complex, multistage process, usually diagnosed at advanced stages after significant anatomical and hemodynamic changes in the valve. Early detection of disease progression is thus pivotal in the development of prevention and mitigation strategies. In this study, we developed a diet-based, non-genetically modified mouse model for early CAVD progression, and explored the utility of two-photon excited fluorescence (TPEF) microscopy for early detection of CAVD progression. TPEF imaging provides label-free, non-invasive, quantitative metrics with the potential to correlate with multiple stages of CAVD pathophysiology including calcium deposition, collagen remodeling and osteogenic differentiation. METHODS: Twenty-week old C57BL/6J mice were fed either a control or pro-calcific diet for 16 weeks and monitored via echocardiography, histology, immunohistochemistry, and quantitative polarized light imaging. Additionally, TPEF imaging was used to quantify tissue autofluorescence (A) at 755 nm, 810 nm and 860 nm excitation, to calculate TPEF 755-860 ratio (A860/525/(A755/460 + A860/525)) and TPEF Collagen-Calcium ratio (A810/525/(A810/460 + A810/525)) in the murine valves. In a separate experiment, animals were fed the above diets till 28 weeks to assess for later-stage calcification. RESULTS: Pro-calcific mice showed evidence of lipid deposition at 4 weeks and calcification at 16 weeks at the valve commissures. The valves of pro-calcific mice also showed positive expression for markers of osteogenic differentiation, myofibroblast activation, proliferation, inflammatory cytokines and collagen remodeling. Pro-calcific mice exhibited lower TPEF autofluorescence ratios, at locations coincident with calcification, that correlated with increased collagen disorganization and positive expression of osteogenic markers. Additionally, locations with lower TPEF autofluorescence ratios at 4 and 16 weeks exhibited increased calcification at later 28-week timepoints. CONCLUSIONS: This study suggests the potential of TPEF autofluorescence metrics to serve as a label-free tool for early detection and monitoring of CAVD pathophysiology.

Differences in colonic crypt morphology of spontaneous and colitis-associated murine models via second harmonic generation imaging to quantify colon cancer development.

BACKGROUND: Colorectal cancer remains the second leading cause of cancer death in the United States, and increased risk in patients with ulcerative colitis (a subset of inflammatory bowel disease) has motivated studies into early markers of dysplasia. The development of clinically translatable multiphoton imaging systems has allowed for the potential of in vivo label-free imaging of epithelial crypt structures via autofluorescence and/or second harmonic generation (SHG). SHG has been used to investigate collagen structures in various types of cancer, though the changes that colorectal epithelial collagen structures undergo during tumor development, specifically colitis-associated tumors, have not been fully investigated. METHODS: This study used two murine models, using A/J mice, one for spontaneous carcinoma and one for colitis-associated carcinoma, to investigate and quantify SHG image features that could potentially inform future study designs of endoscopic multiphoton imaging systems. The spontaneous tumor model comprised a series of six weekly injections of azoxymethane (AOM model). The colitis-associated tumor model comprised a single injection of AOM, followed by cycles of drinking water with dissolved dextran sodium sulfate salt (AOM-DSS model). SHG images of freshly resected murine colon were acquired with a multiphoton imaging system, and image features, such as crypt size, shape and distribution, were quantified using an automated algorithm. RESULTS: The comparison of quantified features of crypt morphology demonstrated the ability of our quantitative image feature algorithms to detect differences between spontaneous (AOM model) and colitis-associated (AOM-DSS model) murine colorectal tissue specimens. There were statistically significant differences in the mean and standard deviation of nearest neighbor (distance between crypts) and circularity between the Control cohort, AOM and AOM-DSS cohorts. We also saw significance between AOM and AOM-DSS cohorts when calculating nearest neighbor in images acquired at fixed depths. CONCLUSION: The results provide insight into the ability of SHG imaging to yield relevant data about the crypt microstructure in colorectal epithelium, specifically the potential to distinguish between spontaneous and colitis-associated murine models using quantification of crypt shape and distribution, informing future design of translational multiphoton imaging systems and protocols.

Characterizing differences in the collagen fiber organization of skin wounds using quantitative polarized light imaging.

Collagen fiber organization requires characterization in many biomedical applications, but it is difficult to objectively quantify in standard histology tissue sections. Quantitative polarized light imaging is a low-cost technique that allows for rapid measurement of collagen fiber orientation and thickness. In this study, we utilize a quantitative polarized light imaging system to characterize fiber orientation and thickness from wound sections. Full thickness skin wound sections that were previously stained with hematoxylin and eosin were used to assess collagen fiber content and organization at different points during the wound healing process. Overall, wounds exhibited a measurable increase in collagen fiber thickness and a nonlinear change in fiber reorganization within the wound. Our study demonstrates that quantitative polarized light imaging is an inexpensive alternative or supplement to standard histology protocols, requiring no additional stains or dyes, and yields repeatable quantitative assessments of collagen organization.

Noninvasive assessment of mitochondrial organization in three-dimensional tissues reveals changes associated with cancer development.

Mitochondrial organization is often altered to accommodate cellular bioenergetic and biosynthetic demands. Changes in metabolism are a hallmark of a number of diseases, including cancer; however, the interdependence between mitochondrial metabolic function and organization is not well understood. Here, we present a noninvasive, automated and quantitative method to assess mitochondrial organization in three-dimensional (3D) tissues using exclusively endogenous two-photon excited fluorescence (TPEF) and show that mitochondrial organization reflects alterations in metabolic activities. Specifically, we examine the organization of mitochondria within live, engineered epithelial tissue equivalents that mimic normal and precancerous human squamous epithelial tissues. We identify unique patterns of mitochondrial organization in the different tissue models we examine, and we attribute these to differences in the metabolic profiles of these tissues. We find that mitochondria are clustered in tissues with high levels of glycolysis and are more highly networked in tissues where oxidative phosphorylation is more dominant. The most highly networked organization is observed within cells with high levels of glutamine consumption. Furthermore, we demonstrate that mitochondrial organization provides complementary information to traditional morphological hallmarks of cancer development, including variations in nuclear size. Finally, we present evidence that this automated quantitative analysis of endogenous TPEF images can identify differences in the mitochondrial organization of freshly excised normal and pre-cancerous human cervical tissue specimens. Thus, this method could be a promising new modality to assess the role of mitochondrial organization in the metabolic activity of 3D tissues and could be further developed to serve as an early cancer clinical diagnostic biomarker.

An automated image processing method to quantify collagen fibre organization within cutaneous scar tissue.

Standard approaches to evaluate scar formation within histological sections rely on qualitative evaluations and scoring, which limits our understanding of the remodelling process. We have recently developed an image analysis technique for the rapid quantification of fibre alignment at each pixel location. The goal of this study was to evaluate its application for quantitatively mapping scar formation in histological sections of cutaneous burns. To this end, we utilized directional statistics to define maps of fibre density and directional variance from Masson's trichrome-stained sections for quantifying changes in collagen organization during scar remodelling. Significant increases in collagen fibre density are detectable soon after burn injury in a rat model. Decreased fibre directional variance in the scar was also detectable between 3 weeks and 6 months after injury, indicating increasing fibre alignment. This automated analysis of fibre organization can provide objective surrogate endpoints for evaluating cutaneous wound repair and regeneration.

Cell-tethered ligands modulate bone remodeling by osteoblasts and osteoclasts.

The goals of the present study are to establish an in vitro co-culture model of osteoblast and osteoclast function and to quantify the resulting bone remodeling. The bone is tissue engineered using well-defined silk protein biomaterials in 2D and 3D formats in combination with human cells expressing tethered agonists for selected G protein-coupled receptors (GPCRs). The tethered constructs are introduced with the objective of triggering sustained and localized GPCR signaling. The cell-modified biomaterial surfaces are reconstructed from SEM images into 3D models using image processing for quantitative measurement of surface characteristics. Parathyroid hormone (PTH) and glucose-dependent insulinotropic peptide (GIP) are selected because of their roles in bone remodeling for expression in tethered format on bone marrow derived human mesenchymal stem cells (hMSCs). Increased calcium deposition and increased surface roughness are found in 3D digital surface models constructed from SEM images of silk protein films remodeled by the co-cultures containing the tethered PTH, and decreased surface roughness is found for the films remodeled by the tethered GIP co-cultures. Increased surface roughness is not found in monocultures of hMSCs expressing tethered PTH, suggesting that osteoclast-osteoblast interactions in the presence of PTH signaling are responsible for the increased mineralization. These data point towards the design of in vitro bone models in which osteoblast-osteoclast interactions are mimicked for a better understanding of bone remodeling.

Quantification of age-related changes in the structure and mechanical function of skin with multiscale imaging.

The mechanical properties of skin change during aging but the relationships between structure and mechanical function remain poorly understood. Previous work has shown that young skin exhibits a substantial decrease in tissue volume, a large macro-scale Poisson's ratio, and an increase in micro-scale collagen fiber alignment during mechanical stretch. In this study, label-free multiphoton microscopy was used to quantify how the microstructure and fiber kinematics of aged mouse skin affect its mechanical function. In an unloaded state, aged skin was found to have less collagen alignment and more non-enzymatic collagen fiber crosslinks. Skin samples were then loaded in uniaxial tension and aged skin exhibited a lower mechanical stiffness compared to young skin. Aged tissue also demonstrated less volume reduction and a lower macro-scale Poisson's ratio at 10% uniaxial strain, but not at 20% strain. The magnitude of 3D fiber realignment in the direction of loading was not different between age groups, and the amount of realignment in young and aged skin was less than expected based on theoretical fiber kinematics affine to the local deformation. These findings provide key insights on how the collagen fiber microstructure changes with age, and how those changes affect the mechanical function of skin, findings which may help guide wound healing or anti-aging treatments.

A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression.

BACKGROUND: Calcific aortic valve disease (CAVD) is one of the most common forms of valvulopathy, with a 50 % elevated risk of a fatal cardiovascular event, and greater than 15,000 annual deaths in North America alone. The treatment standard is valve replacement as early diagnostic, mitigation, and drug strategies remain underdeveloped. The development of early diagnostic and therapeutic strategies requires the fabrication of effective in vitro valve mimetic models to elucidate early CAVD mechanisms. METHODS: In this study, we developed a multilayered physiologically relevant 3D valve-on-chip (VOC) system that incorporated aortic valve mimetic extracellular matrix (ECM), porcine aortic valve interstitial cell (VIC) and endothelial cell (VEC) co-culture and dynamic mechanical stimuli. Collagen and glycosaminoglycan (GAG) based hydrogels were assembled in a bilayer to mimic healthy or diseased compositions of the native fibrosa and spongiosa. Multiphoton imaging and proteomic analysis of healthy and diseased VOCs were performed. RESULTS: Collagen-based bilayered hydrogel maintained the phenotype of the VICs. Proteins related to cellular processes like cell cycle progression, cholesterol biosynthesis, and protein homeostasis were found to be significantly altered and correlated with changes in cell metabolism in diseased VOCs. This study suggested that diseased VOCs may represent an early, adaptive disease initiation stage, which was corroborated by human aortic valve proteomic assessment. CONCLUSIONS: In this study, we developed a collagen-based bilayered hydrogel to mimic healthy or diseased compositions of the native fibrosa and spongiosa layers. When the gels were assembled in a VOC with VECs and VICs, the diseased VOCs revealed key insights about the CAVD initiation process. STATEMENT OF SIGNIFICANCE: Calcific aortic valve disease (CAVD) elevates the risk of death due to cardiovascular pathophysiology by 50 %, however, prevention and mitigation strategies are lacking, clinically. Developing tools to assess early disease would significantly aid in the prevention of disease and in the development of therapeutics. Previously, studies have utilized collagen and glycosaminoglycan-based hydrogels for valve cell co-cultures, valve cell co-cultures in dynamic environments, and inorganic polymer-based multilayered hydrogels; however, these approaches have not been combined to make a physiologically relevant model for CAVD studies. We fabricated a bi-layered hydrogel that closely mimics the aortic valve and used it for valve cell co-culture in a dynamic platform to gain mechanistic insights into the CAVD initiation process using proteomic and multiphoton imaging assessment.

Optical imaging using endogenous contrast to assess metabolic state.

Optical microscopic imaging offers opportunities to perform noninvasive assessments of numerous parameters associated with the biochemistry, morphology, and functional state of biological samples. For example, it is possible to detect the endogenous fluorescence from a small number of important biomolecules, including NADH and FAD, which are two coenzymes involved in key metabolic pathways such as glycolysis, the Krebs cycle, and oxidative phosphorylation. Here, we review different imaging approaches to isolate the fluorescence from these chromophores in two- and three-dimensional samples and discuss the origins and potential interpretation of the observed signals in terms of cell metabolic status. Finally, we discuss the challenges and limitations of these approaches, as well as important research directions that we expect will evolve in the near future.

Autocorrelation method for fractal analysis in nonrectangular image domains.

We report an autocorrelation-based approach that accurately measures fractal organization within arbitrarily shaped (nonrectangular) regions of interest of gray-scale images. It extends fractal analysis beyond what is possible using fast Fourier transforms and improves on a previous autocorrelation algorithm. We illustrate its use in detecting subtle changes in mitochondrial organization within murine fibroblasts expressing the human papillomavirus E7 oncogene.