Neuro-fuzzy systems for computer-aided myocardial viability assessment

Physiological fusion of functional and structural images for cardiac deformation recovery

The recent advances in meaningful constraining models have resulted in increasingly useful quantitative information recovered from cardiac images. Nevertheless, as most frameworks utilize either functional or structural images, the analyses cannot benefit from the complementary information provided by the other image sources. To better characterize subject-specific cardiac physiology and pathology, data fusion of multiple image sources is essential. Traditional image fusion strategies are performed by fusing information of commensurate images through various mathematical operators. Nevertheless, when image data are dissimilar in physical nature and spatiotemporal quantity, such approaches may not provide meaningful connections between different data. In fact, as different image sources provide partial measurements of the same cardiac system dynamics, it is more natural and suitable to utilize cardiac physiological models for the fusions. Therefore, we propose to use the cardiac physiome model as the central link to fuse functional and structural images for more subject-specific cardiac deformation recovery through state-space filtering. Experiments were performed on synthetic and real data for the characteristics and potential clinical applicability of our framework, and the results show an increase of the overall subject specificity of the recovered deformations.

A normalized framework for the design of feature spaces assessing the left ventricular function

A through description of the left ventricle functionality requires combining complementary regional scores. A main limitation is the lack of multiparametric normality models oriented to the assessment of regional wall motion abnormalities (RWMA). This paper covers two main topics involved in RWMA assessment. We propose a general framework allowing the fusion and comparison across subjects of different regional scores. Our framework is used to explore which combination of regional scores (including 2-D motion and strains) is better suited for RWMA detection. Our statistical analysis indicates that for a proper (within interobserver variability) identification of RWMA, models should consider motion and extreme strains.

Magnetic Resonance Imaging Based Bone Marrow Segmentation for Quantitative Calculation of Pure Red Marrow Metabolism Using 2-Deoxy-2-[F-18]fluoro-d-glucose- Positron Emission Tomography: a Novel Application with Significant Implications for Combined Structure–Function Approach

AIMS

The aim of this study was to introduce a new concept for accurate measurement of the global metabolic activity of the red marrow by combining segmented volumetric data from structural imaging techniques such as magnetic resonance imaging (MRI) and quantitative metabolic information provided by functional modalities such as positron emission tomography (PET).

MATERIALS AND METHODS

Imaging studies from five subjects who had undergone both MRI and 2-deoxy-2-[F-18]fluoro-D-glucose(FDG)-PET were selected for this analysis to test the feasibility of this approach. In none of the subjects, there were any marrow abnormalities as determined either by the MRI or by FDG-PET studies. The mean blood glucose level was 96+/-25 mg/dl. The first step was to calculate vertebral volume at L1, L3, and L5 from the available MRI studies. The red and yellow marrows were then segmented within the lumbar vertebrae using the 3DVIEWNIX software system from which the respective volumes were also calculated for each. This also allowed calculating the bone volume in each of the vertebral bodies examined. By employing the standard techniques, the mean of the maximum standardized uptake values (mean SUVmax) for the bone marrow were calculated in L1, L3 and L5 of the lumbar spine, and then global red marrow activity was calculated using the following approach: (1) Whole vertebral metabolic activity (WVMA)=vertebral volume x mean SUVmax of the entire marrow, (2) whole vertebral metabolic activity for yellow marrow (WVMAYM)=yellow marrow volume x mean SUVmax of fat (obtained from measurements of subcutaneous fat), (3) whole vertebral metabolic activity for red marrow (WVMARM)=WVMA-WVMAYM; and finally, (4) SUVmax for pure red marrow=whole vertebral metabolic activity for red marrow (WVMARM)/red marrow volume (obtained from the segmentation data).

RESULTS

The mean volume of the lumbar vertebral body was 15.6+/-1.4 cm3, the bone marrow mean SUVmax was 1.5+/-0.3, and the MVP for the lumbar vertebral body was 23.4+/-5.9. The mean volume of the yellow marrow in the lumbar vertebral body was 7.7+/-1.1 cm3, the yellow marrow mean SUVmax was estimated to be 0.38+/-0.1 and the MVP for the yellow marrow in the lumbar vertebral body was 2.9+/-0.9. The mean volume of the red marrow in lumbar vertebral body was 7.9+/-1.1 cm3, the red marrow mean SUVmax was estimated to be 2.6+/-0.6, and the MVP for the red marrow in the lumbar vertebral body was 20.5+/-5.9.

CONCLUSION

Estimation of the individual component of the bone marrow is plausible using medical image segmentation with combined structure-function approach. This can have potential research and clinical applications concerning the study of global metabolic activity of the individual component and diagnosis of benign and malignant bone marrow disorders.

Novel Quantitative Techniques for Assessing Regional and Global Function and Structure Based on Modern Imaging Modalities: Implications for Normal Variation, Aging and Diseased States

In this review, we describe the current approaches used for quantitative assessment of regional and global function with positron emission tomography (PET) imaging (combined with structural imaging modalities) with emphasis on both research and clinical applications of this powerful approach. We particularly refer to the impact of such measurements in assessing physiological processes such as aging and measuring response to treatment in serious disorders such as cancer. Although a multitude of methods has been described in literature, the optimal approaches that are both accurate and practical in clinical settings need to be defined and refined. Standardized uptake value (SUV) continues to be the most widely used index in the current practice. Calculating SUV at a single time point and assigning standard regions of interest are inadequate and suboptimal for the purposes adopted by the medical community. The concepts of partial volume correction for measured values in small lesions, dual-time point and delayed PET imaging, and global metabolic activity for assessment of various stages of disease may overcome deficiencies that are associated with the current quantitative (ie, SUV) techniques. Serious consideration of these concepts will enhance the role and reliability of these quantitative techniques, and therefore compliment the World Health Organization or the Response Evaluation Criteria in Solid Tumors (RECIST) criteria for managing patients with cancer and other disorders, including physiological states such as aging and serious diseases such as atherosclerosis and neurological diseases. We also introduce the concepts that allow for segmentation of various structural components of organs like the brain for accurate measurement of functional parameters. We also describe complicated kinetic modeling and methodologies that have been used frequently for assessing metabolic and pharmacological parameters in the brain and other organs. Simplified quantitative techniques based on these concepts are described, but should be validated against the kinetic models to test their role as practical tools.

Tagged magnetic resonance imaging of the heart: a survey

Magnetic resonance imaging (MRI) of the heart with magnetization tagging provides a potentially useful new way to assess cardiac mechanical function, through revealing the local motion of otherwise indistinguishable portions of the heart wall. While still an evolving area, tagged cardiac MRI is already able to provide novel quantitative information on cardiac function. Exploiting this potential requires developing tailored methods for both imaging and image analysis. In this paper, we review some of the progress that has been made in developing such methods for tagged cardiac MRI, as well as some of the ways these methods have been applied to the study of cardiac function.

A 3-D model-based registration approach for the PET, MR and MCG cardiac data fusion

In this paper, a new approach is presented for the assessment of a 3-D anatomical and functional model of the heart including structural information from magnetic resonance imaging (MRI) and functional information from positron emission tomography (PET) and magnetocardiography (MCG). The method uses model-based co-registration of MR and PET images and marker-based registration for MRI and MCG. Model-based segmentation of MR anatomical images results in an individualized 3-D biventricular model of the heart including functional parameters from PET and MCG in an easily interpretable 3-D form.

A review of cardiac image registration methods

In this paper, the current status of cardiac image registration methods is reviewed. The combination of information from multiple cardiac image modalities, such as magnetic resonance imaging, computed tomography, positron emission tomography, single-photon emission computed tomography, and ultrasound, is of increasing interest in the medical community for physiologic understanding and diagnostic purposes. Registration of cardiac images is a more complex problem than brain image registration because the heart is a nonrigid moving organ inside a moving body. Moreover, as compared to the registration of brain images, the heart exhibits much fewer accurate anatomical landmarks. In a clinical context, physicians often mentally integrate image information from different modalities. Automatic registration, based on computer programs, might, however, offer better accuracy and repeatability and save time.