Biomedical subjects

Elizabeth Bullitt

Publications and source records attributed to Elizabeth Bullitt.

At least 19 recordsLinked to original sources

PubMed2006

Multi-modal image set registration and atlas formation.

In this paper, we present a Bayesian framework for both generating inter-subject large deformation transformations between two multi-modal image sets of the brain and for forming multi-class brain atlases. In this framework, the estimated transformations are generated using maximal information about the underlying neuroanatomy present in each of the different modalities. This modality independent registration framework is achieved by jointly estimating the posterior probabilities associated with the multi-modal image sets and the high-dimensional registration transformations mapping these posteriors. To maximally use the information present in all the modalities for registration, Kullback-Leibler divergence between the estimated posteriors is minimized. Registration results for image sets composed of multi-modal MR images of healthy adult human brains are presented. Atlas formation results are presented for a population of five infant human brains.

Algorithms↗

PubMed2005

Magnetic resonance angiography visualization of abnormal tumor vasculature in genetically engineered mice.

Previous research on the vasculature of tumor-bearing animals has focused upon the microvasculature. Magnetic resonance angiography (MRA) offers a noninvasive, complementary approach that provides information about larger vessels. Quantitative analysis of MRA images of spontaneous preclinical tumor models has not been previously reported. Eleven TgT121;p53+/- mice, which invariably develop choroid plexus carcinoma (CPC), and nine age-matched healthy controls were imaged using T1, T2, and a high-resolution three-dimensional time-of-flight MRA sequences at 3 T. Tumors and vessels were segmented to determine tumor volume and vascular attributes, including number of terminal branches, vessel count, and the average vessel radii of MRA-visible vessels within the tumor. Differences in the vasculature between tumor-bearing animals and healthy controls were analyzed statistically. Although the spatial resolution of MRA prohibits visualization of capillaries, a high density of intratumor blood vessels was visualized in CPC mice. A significant increase in terminal branch count and vessel count, but not average vessel radius, was observed in CPCs when compared with normal controls. Both terminal branch count and vessel count were highly correlated with tumor volume. This study represents the first MRA analysis of a spontaneous preclinical brain tumor model. Although the spatial resolution of MRA is less than histologic analysis, MRA-obtained vascular attributes provide useful information with full brain coverage. We show that consistent tumor vasculature properties can be determined by MRA. Such methods are critical for developing preclinical therapeutic testing and will help guide the development of human brain tumor analyses.

Animals↗

PubMed2005

Synthetic ground truth for validation of brain tumor MRI segmentation.

Validation and method of comparison for segmentation of magnetic resonance images (MRI) presenting pathology is a challenging task due to the lack of reliable ground truth. We propose a new method for generating synthetic multi-modal 3D brain MRI with tumor and edema, along with the ground truth. Tumor mass effect is modeled using a biomechanical model, while tumor and edema infiltration is modeled as a reaction-diffusion process that is guided by a modified diffusion tensor MRI. We propose the use of warping and geodesic interpolation on the diffusion tensors to simulate the displacement and the destruction of the white matter fibers. We also model the process where the contrast agent tends to accumulate in cortical csf regions and active tumor regions to obtain contrast enhanced T1w MR image that appear realistic. The result is simulated multi-modal MRI with ground truth available as sets of probability maps. The system will be able to generate large sets of simulation images with tumors of varying size, shape and location, and will additionally generate infiltrated and deformed healthy tissue probabilities.

Algorithms↗

PubMed2005

Effects of healthy aging measured by intracranial compartment volumes using a designed MR brain database.

A publicly available database of high-quality, multi-modal MR brain images of carefully screened healthy subjects, equally divided by sex, and with an equal number of subjects per age decade, would be of high value to investigators interested in the statistical study of disease. This report describes initial use of an accumulating healthy database currently comprising 50 subjects aged 20-72. We examine changes by age and sex to the volumes of gray matter, white matter and cerebrospinal fluid for subjects within the database. We conclude that traditional views of healthy aging should be revised. Significant atrophy does not appear in healthy subjects 60 or 70 years old. Gray matter loss is not restricted to senility, but begins in early adulthood and is progressive. The percentage of white matter increases with age. A carefully-designed healthy database should be useful in the statistical analysis of many age- and non-age-related diseases.

Adult↗

PubMed2005

Spatial graphs for intra-cranial vascular network characterization, generation, and discrimination.

Graph methods that summarize vasculature by its branching topology are not sufficient for the statistical characterization of a population of intra-cranial vascular networks. Intra-cranial vascular networks are typified by topological variations and long, wandering paths between branch points. We present a graph-based representation, called spatial graphs, that captures both the branching patterns and the spatial locations of vascular networks. Furthermore, we present companion methods that allow spatial graphs to (1) statistically characterize populations of vascular networks, (2) generate the central vascular network of a population of vascular networks, and (3) distinguish between populations of vascular networks. We evaluate spatial graphs by using them to distinguish the gender and handedness of individuals based on their intra-cranial vascular networks.

Algorithms↗

PubMed2005

Comparison of simultaneous and sequential two-view registration for 3D/2D registration of vascular images.

Accurate 3D/2D vessel registration is complicated by issues of image quality, occlusion, and other problems. This study performs a quantitative comparison of 3D/2D vessel registration in which vessels segmented from preoperative CT or MR are registered with biplane x-ray angiograms by either a) simultaneous two-view registration with advance calculation of the relative pose of the two views, or b) sequential registration with each view. We conclude on the basis of phantom studies that, even in the absence of image errors, simultaneous two-view registration is more accurate than sequential registration. In more complex settings, including clinical conditions, the relative accuracy of simultaneous two-view registration is even greater.

Algorithms↗

PubMed2005

Vessel tortuosity and brain tumor malignancy: a blinded study.

RATIONALE AND OBJECTIVES: Malignancy provokes regional changes to vessel shape. Characteristic vessel tortuosity abnormalities appear early during tumor development, affect initially healthy vessels, spread beyond the confines of tumor margins, and do not simply mirror tissue perfusion. The ability to detect and quantify tortuosity abnormalities on high-resolution magnetic resonance angiography (MRA) images offers a new approach to the noninvasive diagnosis of malignancy. This report evaluates a computerized, statistical method of analyzing the shapes of vessels extracted from MRA in diagnosing cancer. MATERIALS AND METHODS: The regional vasculature of 34 healthy subjects was compared with the tumor-associated vasculature of 30 brain tumors before surgical resection. The operator performing the analysis was blinded to the diagnosis. Vessels were segmented from an MRA of each subject, a region of interest was defined in each tumor patient and was mapped to all healthy controls, and a statistical analysis of vessel shape measures was then performed over the region of interest. Many difficult cases were included, such as pinpoint, hemorrhagic, and irradiated tumors, as were hypervascular benign tumors. Tumors were identified as benign or malignant on the basis of histological evaluation. RESULTS: A discriminant analysis performed at the study's conclusion successfully classified all but one of the 30 tumors as benign or malignant on the basis of vessel tortuosity. CONCLUSIONS: Quantitative, statistical measures of vessel shape offer a new approach to the diagnosis and staging of disease. Although the methods developed under the current report must be tested against a new series of cases, initial results are promising.

Adult↗

PubMed2005

Analyzing attributes of vessel populations.

Almost all diseases affect blood vessel attributes (vessel number, radius, tortuosity, and branching pattern). Quantitative measurement of vessel attributes over relevant vessel populations could thus provide an important means of diagnosing and staging disease. Unfortunately, little is known about the statistical properties of vessel attributes. In particular, it is unclear whether vessel attributes fit a Gaussian distribution, how dependent these values are upon anatomical location, and how best to represent the attribute values of the multiple vessels comprising a population of interest in a single patient. The purpose of this report is to explore the distributions of several vessel attributes over vessel populations located in different parts of the head. In 13 healthy subjects, we extract vessels from MRA data, define vessel trees comprising the anterior cerebral, right and left middle cerebral, and posterior cerebral circulations, and, for each of these four populations, analyze the vessel number, average radius, branching frequency, and tortuosity. For the parameters analyzed, we conclude that statistical methods employing summary measures for each attribute within each region of interest for each patient are preferable to methods that deal with individual vessels, that the distributions of the summary measures are indeed Gaussian, and that attribute values may differ by anatomical location. These results should be useful in designing studies that compare patients with suspected disease to a database of healthy subjects and are relevant to groups interested in atlas formation and in the statistics of tubular objects.

Cerebral Arteries↗

PubMed2004

A brain tumor segmentation framework based on outlier detection.

This paper describes a framework for automatic brain tumor segmentation from MR images. The detection of edema is done simultaneously with tumor segmentation, as the knowledge of the extent of edema is important for diagnosis, planning, and treatment. Whereas many other tumor segmentation methods rely on the intensity enhancement produced by the gadolinium contrast agent in the T1-weighted image, the method proposed here does not require contrast enhanced image channels. The only required input for the segmentation procedure is the T2 MR image channel, but it can make use of any additional non-enhanced image channels for improved tissue segmentation. The segmentation framework is composed of three stages. First, we detect abnormal regions using a registered brain atlas as a model for healthy brains. We then make use of the robust estimates of the location and dispersion of the normal brain tissue intensity clusters to determine the intensity properties of the different tissue types. In the second stage, we determine from the T2 image intensities whether edema appears together with tumor in the abnormal regions. Finally, we apply geometric and spatial constraints to the detected tumor and edema regions. The segmentation procedure has been applied to three real datasets, representing different tumor shapes, locations, sizes, image intensities, and enhancement.

Algorithms↗

PubMed2004

Extracting branching tubular object geometry via cores.

Blood vessels and other anatomic objects in the human body can be described as trees of branching tubes. The focus of this paper is the extraction of the branching geometry in three-dimensional, as well as the extraction of the tubes themselves, via skeletons computed as cores. Cores are height ridges of a graded measure of medial strength called medialness, which measures how much a given location resembles the middle of an object as indicated by image intensities. Object bifurcations are detected using an affine-invariant corner detector and computations on the core's medialness values. The methods presented in this paper are evaluated on synthetic images of branching tubular objects as well as on blood vessels in head MR angiogram data. Results show impressive resistance to noise and the ability to detect branches spanning a variety of widths and branching angles. An extension that allows cores to extract general branching structures, not only branching tubes, is introduced.

Cerebrovascular Circulation↗

PubMed2004

Abnormal vessel tortuosity as a marker of treatment response of malignant gliomas: preliminary report.

Despite multiple advances in medical imaging, noninvasive monitoring of therapeutic efficacy for malignant gliomas remains problematic. An underutilized observation is that malignancy induces characteristic abnormalities of vessel shape. These characteristic shape abnormalities affect both capillaries and much larger vessels in the tumor vicinity, involve larger vessels prior to sprout formation, and are generally not present in hypervascular benign tumors. Vessel shape abnormalities associated with malignancy thus may appear independently of increase in vessel density. We hypothesize that an automated, computerized analysis of vessel shape as defined from high-resolution MRA can provide valuable information about tumor activity during the treatment of malignant gliomas. This report describes vessel shape properties in 10 malignant gliomas prior to treatment, in 2 patients in remission during treatment, and in 2 patients with recurrent disease. One subject was scanned multiple times. The method involves an automated, statistical analysis of vessel shape within a region of interest for each tumor, normalized by the values obtained from the vessels within the same region of interest of 34 healthy subjects. Results indicate that untreated tumors display statistically significant vessel tortuosity abnormalities. These abnormalities involve vessels not only within the tumor margins as defined from MR but also vessels in the surrounding tissue. The abnormalities resolve during effective treatment and recur with tumor recurrence. We conclude that vessel shape analysis could provide an important means of assessing tumor activity.

Cerebrovascular Circulation↗

PubMed2004

Correlation of MR perfusion imaging and vessel tortuosity parameters in assessment of intracranial neoplasms.

Advances in noninvasive imaging techniques such as magnetic resonance perfusion imaging have been found useful in grading cerebral neoplasms and have potential for significant clinical benefit. The purpose of this study was to determine the correlation between tumor vessel tortuosity as measured from vessels extracted from magnetic resonance angiograms (MRA) and perfusion parameters of cerebral blood flow (CBF) and cerebral blood volume (CBV) in intracranial neoplasms. We hypothesized that tumor blood vessel tortuosity measures and perfusion measures would be correlated, since both are increased by tumor angiogenesis. 18 patients with 19 cerebral neoplasms were evaluated with conventional MR imaging and dynamic contrast-enhanced T2-weighted perfusion MR imaging (PWI). Both benign and malignant lesions were included, as were hyper- and hypovascular tumors. Regions of interest were plotted within the tumor area to locate foci of maximum CBV and CBF. CBV and CBF measurements were also recorded in contralateral normal appearing white matter to calculate relative CBV (rCBV) and relative CBF (rCBF). Vessel tortuosity analyses were conducted upon vessels segmented from MRA images of the same patients using two tortuosity descriptors (SOAM and ICM), which have previously been demonstrated to have efficacy in separating benign from malignant disease. Linear regression analyses were conducted to determine if correlations exist between CBV or CBF and the two tortuosity measurements. For the overall set of tumors, no significant correlations were found between flow or volume measures and the tortuosity measures. However, when the 7 glioblastoma multiforme tumors were examined as a subgroup, the following significant correlations were found: rCBV and SOAM (R2=0.799), rCBV and ICM (R2=0.214). Our results demonstrate that MR perfusion imaging data do not correlate significantly with vessel tortuosity parameters as determined from the larger vessels seen by MRA. However, for subgroups of a particular tumor type such as GBM, there may be significant correlations. It appears that perfusion and tortuosity data may provide independently useful data in the assessment of cerebral neoplasms.

Brain Neoplasms↗

PubMed2003

Practical consideration for 3T imaging.

In the past 10 to 15 years, 1.5T has been one of the most commonly used field strengths for day-to-day clinical operations. However, recent advances in high field technology and the increased availability of high field (> 1.5T) human scanners have opened the doors for a variety of exciting improvements in clinical and research applications of MR imaging. In particular, 3T has continued to gain wide acceptance as one of the main field strengths for clinical and research studies. Therefore, in this article the authors focus on the pros and cons of 3T imaging and comparisons between results obtained at 3T and 1.5T.

Brain↗

PubMed2003

Automatic brain tumor segmentation by subject specific modification of atlas priors.

RATIONALE AND OBJECTIVES: Manual segmentation of brain tumors from magnetic resonance images is a challenging and time-consuming task. An automated system has been developed for brain tumor segmentation that will provide objective, reproducible segmentations that are close to the manual results. Additionally, the method segments white matter, grey matter, cerebrospinal fluid, and edema. The segmentation of pathology and healthy structures is crucial for surgical planning and intervention. MATERIALS AND METHODS: The method performs the segmentation of a registered set of magnetic resonance images using an expectation-maximization scheme. The segmentation is guided by a spatial probabilistic atlas that contains expert prior knowledge about brain structures. This atlas is modified with the subject-specific brain tumor prior that is computed based on contrast enhancement. RESULTS: Five cases with different types of tumors are selected for evaluation. The results obtained from the automatic segmentation program are compared with results from manual and semi-automated methods. The automated method yields results that have surface distances at roughly 1-4 mm compared with the manual results. CONCLUSION: The automated method can be applied to different types of tumors. Although its performance is below that of the semi-automated method, it has the advantage of requiring no user supervision.

Automation↗

PubMed2003

Structural and radiometric asymmetry in brain images.

This paper presents a general framework for analyzing structural and radiometric asymmetry in brain images. In a healthy brain, the left and right hemispheres are largely symmetric across the mid-sagittal plane. Brain tumors may belong to one or both of the following categories: mass-effect, in which the diseased tissue displaces healthy tissue; and infiltrating, in which healthy tissue has become diseased. Mass-effect brain tumors cause structural asymmetry by displacing healthy tissue, and may cause radiometric asymmetry in adjacent normal structures due to edema. Infiltrating tumors have a different radiometric response from healthy tissue. Thus, structural and radiometric asymmetries across the mid-sagittal plane in brain images provide important cues that tumors may be present. We have developed a framework that registers images with their reflections across the mid-sagittal plane. The registration process accounts for tissue displacement through large deformation image warping. Radiometric differences are taken into account through an additive intensity field. We present an efficient multi-scale algorithm for the joint estimation of structural and radiometric asymmetry. Results for nine MR images of patients with tumors and four normal control subjects are presented.

Algorithms↗

PubMed2003

Measuring tortuosity of the intracerebral vasculature from MRA images.

The clinical recognition of abnormal vascular tortuosity, or excessive bending, twisting, and winding, is important to the diagnosis of many diseases. Automated detection and quantitation of abnormal vascular tortuosity from three-dimensional (3-D) medical image data would, therefore, be of value. However, previous research has centered primarily upon two-dimensional (2-D) analysis of the special subset of vessels whose paths are normally close to straight. This report provides the first 3-D tortuosity analysis of clusters of vessels within the normally tortuous intracerebral circulation. We define three different clinical patterns of abnormal tortuosity. We extend into 3-D two tortuosity metrics previously reported as useful in analyzing 2-D images and describe a new metric that incorporates counts of minima of total curvature. We extract vessels from MRA data, map corresponding anatomical regions between sets of normal patients and patients with known pathology, and evaluate the three tortuosity metrics for ability to detect each type of abnormality within the region of interest. We conclude that the new tortuosity metric appears to be the most effective in detecting several types of abnormalities. However, one of the other metrics, based on a sum of curvature magnitudes, may be more effective in recognizing tightly coiled, "corkscrew" vessels associated with malignant tumors.

Brain↗

PubMed2002

Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction.

The extraction of the centerlines of tubular objects in two and three-dimensional images is a part of many clinical image analysis tasks. One common approach to tubular object centerline extraction is based on intensity ridge traversal. In this paper, we evaluate the effects of initialization, noise, and singularities on intensity ridge traversal and present multiscale heuristics and optimal-scale measures that minimize these effects. Monte Carlo experiments using simulated and clinical data are used to quantify how these "dynamic-scale" enhancements address clinical needs regarding speed, accuracy, and automation. In particular, we show that dynamic-scale ridge traversal is insensitive to its initial parameter settings, operates with little additional computational overhead, tracks centerlines with subvoxel accuracy, passes branch points, and handles significant image noise. We also illustrate the capabilities of the method for medical applications involving a variety of tubular structures in clinical data from different organs, patients, and imaging modalities.

Algorithms↗

PubMed2002

Volume rendering of segmented image objects.

This paper describes a new method of combining ray-casting with segmentation. Volume rendering is performed at interactive rates on personal computers, and visualizations include both "superficial" ray-casting through a shell at each object's surface and "deep" ray-casting through the confines of each object. A feature of the approach is the option to smoothly and interactively dilate segmentation boundaries along all axes. This ability, when combined with selective "turning off" of extraneous image objects, can help clinicians detect and evaluate segmentation errors that may affect surgical planning. We describe both a method optimized for displaying tubular objects and a more general method applicable to objects of arbitrary geometry. In both cases, select three-dimensional points are projected onto a modified z buffer that records additional information about the projected objects. A subsequent step selectively volume renders only through the object volumes indicated by the z buffer. We describe how our approach differs from other reported methods for combining segmentation with ray-casting, and illustrate how our method can be useful in helping to detect segmentation errors.

Algorithms↗