A 2-D/3-D model-based method to quantify the complexity of microvasculature imaged by in vivo multiphoton microscopy

Revisiting Superquadric Fitting: A Numerically Stable Formulation

Superquadric surfaces play an important role in many different research fields due to their ability to model a variety of shapes with a small number of parameters. One of their core applications is the estimation of object shape characteristics from a set of discrete samples from the surface of an object. However, the corresponding optimization problem is prone to numerical instabilities in some regions of the parameter space. To mitigate this problem, lower bound constraints to the shape parameters are applied during the optimization thus limiting the range of shapes which can be accurately represented by superquadrics. Therefore, the exact modeling of very common shapes like cuboids and cylinders is error-prone in practice. In this article we investigate this problem and provide a numerically stable formulation for the evaluation of the superquadric surface function and for its gradient. This new formulation enables numerically stable fitting of superquadrics in the previously constrained region, i.e., in its full range including cuboids and cylinders. In addition, the new formulation also leads to faster convergence speed. The theoretical contributions are substantiated by experiments on synthetic as well as real data.

Online chromatic and scale-space microvessel-tracing analysis for transmitted light optical images

Limited contrast in transmitted light optical images from intravital microscopy is problematic for analysing tumour vascular morphology. Moreover, in some cases, changes in vasculature are visible to a human observer but are not easy to quantify. In this paper two online algorithms are presented: scale-space vessel tracing and chromatic decomposition for analysis of the vasculature of SW1222 human colorectal carcinoma xenografts growing in dorsal skin-fold "window" chambers in mice. Transmitted light optical images of tumours were obtained from mice treated with the tumour vascular disrupting agent, combretastatin-A-4-phosphate (CA4P), or saline. The tracing algorithm was validated against hand-traced vessels with accurate results. The measurements extracted with the algorithms confirmed the known effects of CA4P on tumour vascular topology. Furthermore, changes in the chromaticity suggest a deoxygenation of the blood with a recovery to initial levels in CA4P-treated tumours relative to the controls. The algorithms can be freely applied to other studies through the CAIMAN website (CAncer IMage ANalysis: http://www.caiman.org.uk).

Reduction of neurovascular damage resulting from microelectrode insertion into the cerebral cortex using in vivo two-photon mapping

Penetrating neural probe technologies allow investigators to record electrical signals in the brain. The implantation of probes causes acute tissue damage, partially due to vasculature disruption during probe implantation. This trauma can cause abnormal electrophysiological responses and temporary increases in neurotransmitter levels, and perpetuate chronic immune responses. A significant challenge for investigators is to examine neurovascular features below the surface of the brain in vivo. The objective of this study was to investigate localized bleeding resulting from inserting microscale neural probes into the cortex using two-photon microscopy (TPM) and to explore an approach to minimize blood vessel disruption through insertion methods and probe design. 3D TPM images of cortical neurovasculature were obtained from mice and used to select preferred insertion positions for probe insertion to reduce neurovasculature damage. There was an 82.8 +/- 14.3% reduction in neurovascular damage for probes inserted in regions devoid of major (>5 microm) sub-surface vessels. Also, the deviation of surface vessels from the vector normal to the surface as a function of depth and vessel diameter was measured and characterized. 68% of the major vessels were found to deviate less than 49 microm from their surface origin up to a depth of 500 microm. Inserting probes more than 49 microm from major surface vessels can reduce the chances of severing major sub-surface neurovasculature without using TPM.

Robust adaptive 3-D segmentation of vessel laminae from fluorescence confocal microscope images and parallel GPU implementation

This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8 x speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.1-1.6) voxels per mesh face for peak signal-to-noise ratios from (110-28 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively.

Application of intravital microscopy in studies of tumor microcirculation

To grow and progress, solid tumors develop a vascular network through co-option and angiogenesis that is characterized by multiple structural and functional abnormalities, which negatively influence therapeutic outcome through direct and indirect mechanisms. As such, the morphology and function of tumor blood vessels, plus their response to different treatments, are a vital and active area of biological research. Intravital microscopy (IVM) has played a key role in studies of tumor angiogenesis, and ongoing developments in molecular probes, imaging techniques, and postimage analysis methods have ensured its continued and widespread use. In this review we discuss some of the primary advantages and disadvantages of IVM approaches and describe recent technological advances in optical microscopy (e.g., confocal microscopy, multiphoton microscopy, hyperspectral imaging, and optical coherence tomography) with examples of their application to studies of tumor angiogenesis.

MDL constrained 3-D grayscale skeletonization algorithm for automated extraction of dendrites and spines from fluorescence confocal images

This paper presents a method for improved automatic delineation of dendrites and spines from three-dimensional (3-D) images of neurons acquired by confocal or multi-photon fluorescence microscopy. The core advance presented here is a direct grayscale skeletonization algorithm that is constrained by a structural complexity penalty using the minimum description length (MDL) principle, and additional neuroanatomy-specific constraints. The 3-D skeleton is extracted directly from the grayscale image data, avoiding errors introduced by image binarization. The MDL method achieves a practical tradeoff between the complexity of the skeleton and its coverage of the fluorescence signal. Additional advances include the use of 3-D spline smoothing of dendrites to improve spine detection, and graph-theoretic algorithms to explore and extract the dendritic structure from the grayscale skeleton using an intensity-weighted minimum spanning tree (IW-MST) algorithm. This algorithm was evaluated on 30 datasets organized in 8 groups from multiple laboratories. Spines were detected with false negative rates less than 10% on most datasets (the average is 7.1%), and the average false positive rate was 11.8%. The software is available in open source form.

Three-dimensional tissue cytometer based on high-speed multiphoton microscopy

Image cytometry technology has been extended to 3D based on high-speed multiphoton microscopy. This technique allows in situ study of tissue specimens preserving important cell-cell and cell-extracellular matrix interactions. The imaging system was based on high-speed multiphoton microscopy (HSMPM) for 3D deep tissue imaging with minimal photodamage. Using appropriate fluorescent labels and a specimen translation stage, we could quantify cellular and biochemical states of tissues in a high throughput manner. This approach could assay tissue structures with subcellular resolution down to a few hundred micrometers deep. Its throughput could be quantified by the rate of volume imaging: 1.45 mm(3)/h with high resolution. For a tissue containing tightly packed, stratified cellular layers, this rate corresponded to sampling about 200 cells/s. We characterized the performance of 3D tissue cytometer by quantifying rare cell populations in 2D and 3D specimens in vitro. The measured population ratios, which were obtained by image analysis, agreed well with the expected ratios down to the ratio of 1/10(5). This technology was also applied to the detection of rare skin structures based on endogenous fluorophores. Sebaceous glands and a cell cluster at the base of a hair follicle were identified. Finally, the 3D tissue cytometer was applied to detect rare cells that had undergone homologous mitotic recombination in a novel transgenic mouse model, where recombination events could result in the expression of enhanced yellow fluorescent protein in the cells. 3D tissue cytometry based on HSMPM demonstrated its screening capability with high sensitivity and showed the possibility of studying cellular and biochemical states in tissues in situ. This technique will significantly expand the scope of cytometric studies to the biomedical problems where spatial and chemical relationships between cells and their tissue environments are important.

A computational model for C. elegans locomotory behavior: application to multiworm tracking

A computational approach is presented for modeling and quantifying the structure and dynamics of the nematode C. elegans observed by time-lapse microscopy. Worm shape and conformations are expressed in a decoupled manner. Complex worm movements are expressed in terms of three primitive patterns--peristaltic progression, deformation, and translation. The model has been incorporated into algorithms for segmentation and simultaneous tracking of multiple worms in a field, some of which may be interacting in complex ways. A recursive Bayesian filter is used for tracking. Unpredictable behaviors associated with interactions are resolved by multiple-hypothesis tracking. Our algorithm can track worms of diverse sizes and conformations (coiled/uncoiled) in the presence of imaging artifacts and clutter, even when worms are overlapping with others. A two-observer performance assessment was conducted over 16 image sequences representing wild-type and uncoordinated mutants as a function of worm size, conformation, presence of clutter, and worm entanglement. Overall detected tracking failures were 1.41%, undetected tracking failures were 0.41%, and segmentation errors were 1.11% of worm length. When worms overlap, our method reduced undetected failures from 12% to 1.75%, and segmentation error from 11% to 5%. Our method provides the basis for reliable morphometric and locomotory analysis of freely behaving worm populations.

Characteristic quantities of microvascular structures in CLSM volume datasets

A method for fully automated morphological and topological quantification of microvascular structures in confocal laser scanning microscopy (CLSM) volume datasets is presented. Several characteristic morphological and topological quantities are calculated in a series of image-processing steps and can be used to compare single components as well as whole networks of microvascular structures to each other. The effect of the individual image-processing steps is illustrated and characteristic quantities of measured volume datasets are presented and discussed.

Molecular-functional imaging of cancer: to image and imagine

The integration of advances in molecular biology, synthetic chemistry and visualization techniques has catapulted imaging into a molecular-functional realm, so that imaging is finding basic-research, preclinical and translational applications in cancer. Currently, molecular-imaging capabilities include the ability to image gene expression, receptors, signaling pathways, apoptosis, multidrug resistance and the extracellular matrix (ECM). Functional-imaging capabilities include the ability to assess angiogenesis, hypoxia and metabolism. Traditionally, imaging has played an important role in cancer diagnosing and determining response to treatment. However, it is the realization of the goal of noninvasively visualizing molecules and molecular pathways and relating these to function that makes multi-modality imaging such an exciting and powerful means for studying a multifaceted disease such as cancer.

Effect of vascular normalization by antiangiogenic therapy on interstitial hypertension, peritumor edema, and lymphatic metastasis: insights from a mathematical model

Preclinical and clinical evidence shows that antiangiogenic agents can decrease tumor vessel permeability and interstitial fluid pressure (IFP) in a process of vessel "normalization." The resulting normalized vasculature has more efficient perfusion, but little is known about how tumor IFP and interstitial fluid velocity (IFV) are affected by changes in transport properties of the vessels and interstitium that are associated with antiangiogenic therapy. By using a mathematical model to simulate IFP and IFV profiles in tumors, we show here that antiangiogenic therapy can decrease IFP by decreasing the tumor size, vascular hydraulic permeability, and/or the surface area per unit tissue volume of tumor vessels. Within a certain window of antiangiogenic effects, interstitial convection within the tumor can increase dramatically, whereas fluid convection out of the tumor margin decreases. This would result in increased drug convection within the tumor and decreased convection of drugs, growth factors, or metastatic cancer cells from the tumor margin into the peritumor fluid or tissue. Decreased convection of growth factors, such as vascular endothelial growth factor-C (VEGF-C), would limit peritumor hyperplasia, and decreased VEGF-A would limit angiogenesis in sentinel lymph nodes. Both of these effects would reduce the probability of lymphatic metastasis. Finally, decreased fluid convection into the peritumor tissue would decrease peritumor edema associated with brain tumors and ascites accumulation in the peritoneal or pleural cavity, a major complication with a number of malignancies.

Solid breast masses: neural network analysis of vascular features at three-dimensional power Doppler US for benign or malignant classification

PURPOSE

To retrospectively evaluate the accuracy of neural network analysis of tumor vascular features at three-dimensional (3D) power Doppler ultrasonography (US) for classification of breast tumors as benign or malignant, with histologic findings as the reference standard.

MATERIALS AND METHODS

This study was approved by the local ethics committee; informed consent was waived. Three-dimensional power Doppler US images of 221 solid breast masses (110 benign, 111 malignant) were obtained in 221 women (mean age, 46 years; range, 25-71 years). After narrowing down vessels to skeletons with a 3D thinning algorithm, six vascular feature values--vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter-were computed. A neural network was used to classify tumors by using these features. Independent-samples t test and receiver operating characteristic (ROC) curve analysis were used.

RESULTS

Mean values of vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter were 0.0089 +/- 0.0073 (standard deviation), 26.41 +/- 14.73, 23.02 cm +/- 19.53, 8.44 cm +/- 10.38, 36.31 +/- 37.06, and 0.088 cm +/- 0.021 in malignant tumors, respectively, and 0.0028 +/- 0.0021, 9.69 +/- 6.75, 5.17 cm +/- 4.78, 1.68 cm +/- 1.79, 6.05 +/- 7.55, and 0.064 cm +/- 0.028 in benign tumors, respectively (P < .001 for all six features). Area under ROC curve (A(z)) values of the six features were 0.84, 0.87, 0.87, 0.82, 0.84, and 0.75, respectively. Accuracy, sensitivity, specificity, and positive and negative predictive values were 85% (187 of 221), 83% (96 of 115), 86% (91 of 106), 86% (96 of 111), and 83% (91 of 110), respectively, with A(z) of 0.92 based on all six feature values.

CONCLUSION

Three-dimensional power Doppler US images and neural network analysis of features can aid in classification of breast tumors as benign or malignant.

Probing the microenvironment of mammary tumors using multiphoton microscopy

Advances in optical imaging technologies that allow the subcellular resolution of undissected tissue have begun to offer new clues into the biology of development and disease. For cancer, such advances mean that the primary tumor is no longer a black box and that the disease can be studied throughout the metastatic cascade and not just as an endpoint. In this review we examine the advances in multiphoton imaging technology that have been used to define the microenvironment and its role in delineating the invasion and intravasation steps of metastasis inside living mammary tumors. Results show that the tumor microenvironment is a dynamic place where interactions between tumor cells, macrophages, blood vessels, and extracellular matrix fibers define the metastatic phenotype.