An Image-based Approach for 3D Left Atrium Functional Measurements

There is growing interest in the assessment of function of the left atrium (LA) in patients with atrial fibrillation (AF). Existing methods of LA functional measurement only quantify a limited subset of the functional parameters from a single or biplane CINE-MRI scan through the LA. Here, we propose an image-based method for comprehensive evaluation of the function of the entire LA in 3D. 4D LA images were reconstructed from a series of CINE image stack covering the whole LA with small or no gap between thin slices. A segmentation from a high-resolution Magnetic Resonance Angiography (MRA) was registered and propagated through pairwise deformable registrations covering the cardiac cycle. Volume, LA ejection fraction and surface strain were computed for each timepoint and registered to Late Gadolinium Enhancement (LGE) scans for each of 52 patient scans. A correlation coefficient of -0.11 was calculated between LGE and strain, indicating that fibrotic tissue correlates with reduced elasticity.

Efficient Segmentation Pipeline Using Diffeomorphic Image Registration: A Validation Study

Functional measurements of the left atrium (LA) in atrial fibrillation (AF) patients is limited to a single CINE slice midway through the LA. Nonetheless, a full 3D characterization of atrial functional measurements would provide more insights into LA function. But this improved modeling capacity comes at a price of requiring LA segmentation of each 3D time point,a time-consuming and expensive task that requires anatomy-specific expertise.We propose an efficient pipeline which requires ground truth segmentation of a single (or limited) CINE time point to accurately propagate it throughout the sequence. This method significantly saves human effort and enable better characterization of LA anatomy. From a gated cardiac CINE MRI sequence we select a single CINE time point with ground truth segmentation, and assuming cyclic motion, we register other images corresponding to all time points using diffeomorphic registration in ANTs. The diffeomorphic registration fields allow us to map a given anatomical shape (segmentation) to each CINE time point, facilitating the construction of a 4D shape model.

Deformable multisurface segmentation of the spine for orthopedic surgery planning and simulation

Purpose: We describe a shape-aware multisurface simplex deformable model for the segmentation of healthy as well as pathological lumbar spine in medical image data. Approach: This model provides an accurate and robust segmentation scheme for the identification of intervertebral disc pathologies to enable the minimally supervised planning and patient-specific simulation of spine surgery, in a manner that combines multisurface and shape statistics-based variants of the deformable simplex model. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user assistance is allowed to disable the prior shape influence during deformation. Results: Results demonstrate validation against user-assisted expert segmentation, showing excellent boundary agreement and prevention of spatial overlap between neighboring surfaces. This section also plots the characteristics of the statistical shape model, such as compactness, generalizability and specificity, as a function of the number of modes used to represent the family of shapes. Final results demonstrate a proof-of-concept deformation application based on the open-source surgery simulation Simulation Open Framework Architecture toolkit. Conclusions: To summarize, we present a deformable multisurface model that embeds a shape statistics force, with applications to surgery planning and simulation.

Interatrial Septum and Appendage Ostium in Atrial Fibrillation Patients: A Population Study

Left atrial appendage (LAA) closure is performed in atrial fibrillation (AF) patients to help prevent stroke. LAA closure using an occlusion implant is performed under imaging guidance. However, occlusion can be a complicated process due to the highly variable and heterogeneous LAA shapes across patients. Patient-specific implant selection and insertion processes are keys to the success of the procedure, yet subjective in nature. A population study of the angle of entry at the interatrial septum relative to the appendage can assist in both catheter design and patient-specific implant choice. In our population study, we analyzed the inherent clusters of the angles that were obtained between the septum normal and the LAA ostium plane. The number of inherent angle clusters matched the LAA four morphological classifications reported in the literature. Further, our exploratory analysis revealed that the normal from the ostium plane does not intersect the septum in all the samples under study. The insights gained from this study can help assist in making objective decisions during LAA closure.

Does Alignment in Statistical Shape Modeling of Left Atrium Appendage Impact Stroke Prediction?

Evidence suggests that the shape of left atrium appendages (LAA) is a primary indicator in predicting stroke for patients diagnosed with atrial fibrillation (AF). Statistical shape modeling tools used to represent (i.e., parameterize) the underlying LAA variability are of crucial importance to learn shape-based predictors of stroke. Most shape modeling techniques use some form of alignment either as a data pre-processing step or during the modeling step. However, the LAA is a joint anatomy along with left atrium (LA), and the relative position and alignment plays a crucial part in determining risk of stroke. In this paper, we explore different alignment strategies for statistical shape modeling and how each strategy affects the stroke prediction capability. This allows for identifying a unified approach of alignment while analyzing the LAA anatomy for stroke. Here, we study three different alignment strategies, (i) global alignment, (ii) global translational alignment and (iii) cluster based alignment. Our results show that alignment strategies that take into account LAA orientation, i.e., (ii), or the inherent natural clustering of the population under study, i.e., (iii), provide significant improvement over global alignment in both qualitative as well as quantitative measures.

Left atrial shape predicts recurrence after atrial fibrillation catheter ablation

INTRODUCTION

Multiple markers left atrium (LA) remodeling, including LA shape, correlate with outcomes in atrial fibrillation (AF). Catheter ablation is an important treatment of AF, but better tools are needed to determine which patients will benefit. In this study, we use particle-based modeling to quantitatively assess LA shape, and determine to what degree it predicts AF recurrence after catheter ablation.

METHODS AND RESULTS

There were 254 patients enrolled in the DECAAF study who underwent cardiac magnetic resonance imaging of the LA prior to AF ablation and were followed for recurrence for up to 475 days. We performed particle-based shape modeling on each patient's LA shape. We selected shape parameters using the LASSO method and factor analysis, and then added them to a Cox regression model, which included multiple clinical parameters and LA fibrosis. We computed Harrell's C-statistic with and without shape in the model. We used the model to stratify patients into recurrence risk classes by both shape and shape and fibrosis combined. Three shape parameters were selected for inclusion. The C-statistic increased from 0.68 to 0.72 when shape was added to the model (P < 0.05). Visualized shapes showed that a more round LA shape with a shorter, more laterally rotated appendage was predictive of recurrence.

CONCLUSION

LA shape is an independent predictor of recurrence after AF ablation. When combined with LA fibrosis, shape analysis using PBM may improve patient selection for ablation.

Shape analysis of the basioccipital bone in Pax7-deficient mice

We compared the cranial base of newborn Pax7-deficient and wildtype mice using a computational shape modeling technology called particle-based modeling (PBM). We found systematic differences in the morphology of the basiooccipital bone, including a broadening of the basioccipital bone and an antero-inferior inflection of its posterior edge in the Pax7-deficient mice. We show that the Pax7 cell lineage contributes to the basioccipital bone and that the location of the Pax7 lineage correlates with the morphology most effected by Pax7 deficiency. Our results suggest that the Pax7-deficient mouse may be a suitable model for investigating the genetic control of the location and orientation of the foramen magnum, and changes in the breadth of the basioccipital.

Computational Shape Models Characterize Shape Change of the Left Atrium in Atrial Fibrillation

Shape change of the left atrium (LA) and LA appendage in atrial fibrillation (AF) patients is hypothesized to be linked to AF pathology and to play a role in thrombogenesis; however, many aspects of shape variation in the heart are poorly understood. To date, studies of the LA shape in AF have been limited to empirical observation and summary metrics, such as volume and its likeness to a sphere. This paper describes a more comprehensive approach to the study of the LA shape through the use of computationally derived statistical shape models. We describe practical approaches that we have developed to extract shape parameters automatically from the three-dimensional MR images of the patient. From these images and our techniques, we can produce a more comprehensive description of LA geometric variability than that has been previously possible. We present the methodology and results from two examples of specific analyses using shape models: (1) we describe statistically significant group differences between the normal control and AF patient populations (n = 137) and (2) we describe characteristic shapes of the LA appendage that are associated with the risk of thrombogenesis determined by transesophageal echocardiography (n = 203).

A Kalman Filtering Perspective for Multiatlas Segmentation

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity-neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy.

A Practical Algorithm for Improving Localization and Quantification of Left Ventricular Scar

Current approaches to classification of left ventricular scar rely on manual segmentation of myocardial borders and manual classification of scar tissue. In this paper, we propose an novel, semi-automatic approach to segment the left ventricular wall and classify scar tissue using a combination of modern image processing techniques. We obtained high-resolution magnetic resonance angiograms (MRA) and late-gadolinium enhanced magnetic resonance imaging (LGE-MRI) in 14 patients who had ventricular scar from a prior myocardial infarction. We applied (1) a level set-based segmentation approach using a combination of the MRA and LGE-MRI to segment the myocardium and then (2) an automated signal intensity algorithm (Otsu thresholding) to identify ventricular scar tissue. We compared results from both steps to those of expert observers. The LVgeometry using the semi-automated segmentation method had a mean overlap of 94% with the manual segmentations. The scar volumes obtained with the Otsu method correlated with the expert observer scar volumes (Dice comparison coefficient of 0.85± 0.11). This proof of concept segmentation pipeline provides a more objective method for identifying scar in the left ventricle than manual approaches.

Automatic segmentation of the left atrium from MRI images using salient feature and contour evolution

We propose an automatic approach for segmenting the left atrium from MRI images. In particular, the thoracic aorta is detected and used as a salient feature to find a seed region that lies inside the left atrium. A hybrid energy that combines robust statistics and localized region intensity information is employed to evolve active contours from the seed region to capture the whole left atrium. The experimental results demonstrate the accuracy and robustness of our approach.

A POINT-CORRESPONDENCE APPROACH TO DESCRIBING THE DISTRIBUTION OF IMAGE FEATURES ON ANATOMICAL SURFACES, WITH APPLICATION TO ATRIAL FIBRILLATION

This paper describes a framework for summarizing and comparing the distributions of image features on anatomical shape surfaces in populations. The approach uses a point-based correspondence model to establish a mapping among surface positions and may be useful for anatomy that exhibits a relatively high degree of shape variability, such as cardiac anatomy. The approach is motivated by the MRI-based study of diseased, or fibrotic, tissue in the left atrium of atrial fibrillation (AF) patients, which has been difficult to measure quantitatively using more established image and surface registration techniques. The proposed method is to establish a set of point correspondences across a population of shape surfaces that provides a mapping from any surface to a common coordinate frame, where local features like fibrosis can be directly compared. To establish correspondence, we use a previously-described statistical optimization of particle-based shape representations. For our atrial fibrillation population, the proposed method provides evidence that more intense and widely distributed fibrosis patterns exist in patients that do not respond well to radiofrequency ablation therapy.

Geodesic distances to landmarks for dense correspondence on ensembles of complex shapes

Establishing correspondence points across a set of biomedical shapes is an important technology for a variety of applications that rely on statistical analysis of individual subjects and populations. The inherent complexity (e.g. cortical surface shapes) and variability (e.g. cardiac chambers) evident in many biomedical shapes introduce significant challenges in finding a useful set of dense correspondences. Application specific strategies, such as registration of simplified (e.g. inflated or smoothed) surfaces or relying on manually placed landmarks, provide some improvement but suffer from limitations including increased computational complexity and ambiguity in landmark placement. This paper proposes a method for dense point correspondence on shape ensembles using geodesic distances to a priori landmarks as features. A novel set of numerical techniques for fast computation of geodesic distances to point sets is used to extract these features. The proposed method minimizes the ensemble entropy based on these features, resulting in isometry invariant correspondences in a very general, flexible framework.

Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation

Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts.

Dark regions of no-reflow on late gadolinium enhancement magnetic resonance imaging result in scar formation after atrial fibrillation ablation

OBJECTIVES

The aim of this study was to assess acute ablation injuries seen on late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) immediately post-ablation (IPA) and the association with permanent scar 3 months post-ablation (3moPA).

BACKGROUND

Success rates for atrial fibrillation catheter ablation vary significantly, in part because of limited information about the location, extent, and permanence of ablation injury at the time of procedure. Although the amount of scar on LGE MRI months after ablation correlates with procedure outcomes, early imaging predictors of scar remain elusive.

METHODS

Thirty-seven patients presenting for atrial fibrillation ablation underwent high-resolution MRI with a 3-dimensional LGE sequence before ablation, IPA, and 3moPA using a 3-T scanner. The acute left atrial wall injuries on IPA scans were categorized as hyperenhancing (HE) or nonenhancing (NE) and compared with scar 3moPA.

RESULTS

Heterogeneous injuries with HE and NE regions were identified in all patients. Dark NE regions in the left atrial wall on LGE MRI demonstrate findings similar to the "no-reflow" phenomenon. Although the left atrial wall showed similar amounts of HE, NE, and normal tissue IPA (37.7 ± 13%, 34.3 ± 14%, and 28.0 ± 11%, respectively; p = NS), registration of IPA injuries with 3moPA scarring demonstrated that 59.0 ± 19% of scar resulted from NE tissue, 30.6 ± 15% from HE tissue, and 10.4 ± 5% from tissue identified as normal. Paired t-test comparisons were all statistically significant among NE, HE, and normal tissue types (p < 0.001). Arrhythmia recurrence at 1-year follow-up correlated with the degree of wall enhancement 3moPA (p = 0.02).

CONCLUSIONS

Radiofrequency ablation results in heterogeneous injury on LGE MRI with both HE and NE wall lesions. The NE lesions demonstrate no-reflow characteristics and reveal a better predictor of final scar at 3 months. Scar correlates with procedure outcomes, further highlighting the importance of early scar prediction.

Particle based shape regression of open surfaces with applications to developmental neuroimaging

Shape regression promises to be an important tool to study the relationship between anatomy and underlying clinical or biological parameters, such as age. In this paper we propose a new method to building shape models that incorporates regression analysis in the process of optimizing correspondences on a set of open surfaces. The statistical significance of the dependence is evaluated using permutation tests designed to estimate the likelihood of achieving the observed statistics under numerous rearrangements of the shape parameters with respect to the explanatory variable. We demonstrate the method on synthetic data and provide a new results on clinical MRI data related to early development of the human head.

Shape modeling and analysis with entropy-based particle systems

This paper presents a new method for constructing compact statistical point-based models of ensembles of similar shapes that does not rely on any specific surface parameterization. The method requires very little preprocessing or parameter tuning, and is applicable to a wider range of problems than existing methods, including nonmanifold surfaces and objects of arbitrary topology. The proposed method is to construct a point-based sampling of the shape ensemble that simultaneously maximizes both the geometric accuracy and the statistical simplicity of the model. Surface point samples, which also define the shape-to-shape correspondences, are modeled as sets of dynamic particles that are constrained to lie on a set of implicit surfaces. Sample positions are optimized by gradient descent on an energy function that balances the negative entropy of the distribution on each shape with the positive entropy of the ensemble of shapes. We also extend the method with a curvature-adaptive sampling strategy in order to better approximate the geometry of the objects. This paper presents the formulation; several synthetic examples in two and three dimensions; and an application to the statistical shape analysis of the caudate and hippocampus brain structures from two clinical studies.

Diffuse bile duct tumors: guidelines for management

The majority of patients with bile duct cancer have small focal adenocarcinomas localized to the upper, middle, or lower third of the bile duct. In contrast, a small subgroup of patients have been identified with bile duct tumors that are diffuse, involving multiple segments of the extrahepatic biliary tract. Among 186 patients with documented bile duct cancer treated at the UCLA Medical Center between 1954 and 1988, 13 patients (7%) had diffuse lesions. Patients with diffuse tumors had markedly poorer survival rates than did those with focal lesions. As diffuse tumors are not amenable to resection, surgical management consists primarily of establishing suitable biliary drainage. All patients with bile duct cancer should undergo careful intraoperative evaluation to exclude a diffuse lesion before tumor resection.

Gastrointestinal complications after cardiac transplantation: a spectrum of diseases

Cardiac transplantation has become an accepted treatment modality for end-stage cardiac failure. The gastrointestinal (GI) tract represents a potential source of posttransplant morbidity and mortality. To define the scope of this problem, records of all patients undergoing cardiac transplantation at UCLA between January 1984 and July 1989 were reviewed. In all, there were 120 patients (90 males and 30 females) with a mean age of 45.4 yr. Among them, there were 61 patients (51%) who developed a total of 112 posttransplant GI complications. Of the entire 120 patients, 41 (34%) developed minor complications and 20 (17%) sustained major GI morbidity. Eighteen patients (15%) underwent either endoscopy or surgical intervention. These data suggest that most cardiac transplant recipients will experience some form of GI complication, although most are minor and can be managed conservatively. However, when major, life-threatening complications occur, evaluation and intervention should proceed expeditiously. The gastroenterologist and GI surgeon should play complimentary roles in the care of these complicated patients.

Heterogeneity of [3H]estradiol binding sites in the rat prostate: properties and distribution of type I and type II sites

In order to assess the rat prostate as a target tissue for receptor-mediated estrogen action, we have studied the properties and distributions of estrogen binding sites in the dorsolateral (DLP) and ventral (VP) prostate. Saturation analyses over a wide range of [3H]estradiol ([3H]E2) concentrations (0.5-100 nM) revealed two distinct types of binding sites in the cytosol and nuclear fractions of DLP of intact rats. The high affinity (type I) estrogen binding sites saturated at 2-4 nM of [3H]E2 and had a capacity of 170 fmol/mg DNA in the cytosol and 400 fmol/mg DNA in the nuclei. DLP type I sites had ligand specificity similar to that described for the classical estrogen receptors (ERs) found in female target tissues. The moderate affinity (type II) estrogen binding sites saturated at 15-30 nM of [3H]E2 and had a capacity of 850 fmol/mg DNA in the cytosol and 1600 fmol/mg DNA in the nuclei. DLP type II sites shared some characteristics of the type II ERs described for the rat uterus; they were estrogen specific, heat labile, and sensitive to reducing agents such as dithiothreitol. Saturation analyses on VP cytosols and nuclear fractions revealed only high affinity sites but no moderate affinity sites in the tissue preparations. Our finding that prostatic type II estrogen binding sites are present exclusively in the DLP supports the concept that basic biological differences exist between the two major prostatic lobes of the rat. Furthermore, our findings may help elucidate the observed differences in susceptibility between these two lobes to the hormonal induction of proliferative prostatic lesions.