A novel surface registration algorithm with biomedical modeling applications.

In this paper, we propose a novel surface matching algorithm for arbitrarily shaped but simply connected 3-D objects. The spherical harmonic (SPHARM) method is used to describe these 3-D objects, and a novel surface registration approach is presented. The proposed technique is applied to various applications of medical image analysis. The results are compared with those using the traditional method, in which the first-order ellipsoid is used for establishing surface correspondence and aligning objects. In these applications, our surface alignment method is demonstrated to be more accurate and flexible than the traditional approach. This is due in large part to the fact that a new surface parameterization is generated by a shortcut that employs a useful rotational property of spherical harmonic basis functions for a fast implementation. In order to achieve a suitable computational speed for practical applications, we propose a fast alignment algorithm that improves computational complexity of the new surface registration method from O(n3) to O(n2).

Transcriptional profiling in coronary artery disease: indications for novel markers of coronary collateralization.

BACKGROUND: The development of collateral circulation plays an important role in protecting tissues from ischemic damage, and its stimulation has emerged as one of principal approaches to therapeutic angiogenesis. Clinical observations have documented substantial differences in the extent of collateralization among patients with coronary artery disease (CAD), with some individuals demonstrating marked abundance and others showing nearly complete absence of these vessels. Recent studies have suggested that circulating monocytes play a major role in collateral growth. The present study was undertaken to determine transcriptional profiles of circulating monocytes in CAD patients with different extents of collateral growth. METHODS AND RESULTS: Monocyte transcriptomes from CAD patients with and without collateral vessels were obtained by use of high-throughput expression profiling. Using a newly developed redundancy-based data mining method, we have identified a set of molecular markers characteristic of a "noncollateralgenic" phenotype. Moreover, we show that these transcriptional abnormalities are independent of the severity of CAD or any other known clinical parameter thought to affect collateral development and correlated with protein expression levels in monocytes and plasma. CONCLUSIONS: Monocyte transcription profiling identifies sets of patients with extensive versus poorly developed collateral circulation. Thus, genetic factors may heavily influence coronary collateral vessel growth in CAD and affect prognosis and response to therapeutic interventions.

Cardiac motion analysis to improve pacing site selection in CRT.

RATIONALE AND OBJECTIVES: The aim of the study is to build cardiac wall motion models to characterize mechanical dyssynchrony and predict pacing sites for the left ventricle of the heart in cardiac resynchronization therapy (CRT). MATERIALS AND METHODS: Cardiac magnetic resonance imaging data from 20 patients are used, in which half have heart failure problems. We propose two spatio-temporal ventricular motion models to analyze the mechanical dyssynchrony of heart: radial motion series and wall motion series (a time series of radial length or wall thickness change). The hierarchical agglomerative clustering technique is applied to the motion series to find candidate pacing sites. All experiments are performed separately on each ventricular motion model to facilitate performance comparison among models. RESULTS: The experimental results demonstrate that the proposed methods perform as well as we expect. Our techniques not only effectively generate the candidate pacing sites list that can help guide CRT, but also derive clustering results that can distinguish the heart conditions between patients and normals perfectly to help medical diagnosis and prognosis. After comparing the results between two different ventricular motion models, the wall motion series model shows a better performance. CONCLUSION: In a traditional CRT device deployment, pacing sites are selected without efficient prediction, which runs the risk of suboptimal benefits. Our techniques can extract useful wall motion information from ventricular mechanical dyssynchrony and identify the candidate pacing sites with maximum contraction delay to assist pacemaker implantation in CRT.

Arteriogenesis: noninvasive quantification with multi-detector row CT angiography and three-dimensional volume rendering in rodents.

PURPOSE: To evaluate two-dimensional (2D) multi-detector row computed tomographic (CT) angiography and three-dimensional (3D) volume rendering for depiction of patterns of arterial growth and quantification of blood vessel density and volume. MATERIALS AND METHODS: The institutional animal care and use committee approved this study. The right femoral artery and its branches were ligated and excised in 16 inbred Lewis rats; animals were randomly assigned to receive 70 microL Dulbecco's modified Eagle's medium (DMEM) or 1.5 x 10(7) bone marrow-derived mononuclear cells (BMC) from isogenic donor rats in 70 microL DMEM. At 2 weeks, CT angiography was performed with injection of 0.45 mL barium sulfate suspension at 0.7 mL/min, followed by silver staining. Number of blood vessels, area, mean area, volume, and blood vessel size distribution derived from digitally subtracted 2D CT angiographic sections were quantified; 3D images were reconstructed. Two-way analysis of variance and paired and unpaired Student t tests were performed. RESULTS: CT angiography showed two patterns of arterial growth: collateral arterial formation and branching arteriogenesis. Two-way analysis of variance indicated that differences within subjects (ischemic vs nonischemic legs) and between subjects (BMC vs DMEM treatment) were significant for total blood vessel area, total blood vessel volume, and mean of blood vessel area (P < .001). In the BMC group, there were significantly more arteries (mean, 241.6 +/- 77.0 [standard deviation] vs 196.4 +/- 75.2, P = .028), but mean cross-sectional area of these arteries was smaller in ischemic versus nonischemic legs (5.4 mm(2) +/- 1.2 vs 6.8 mm(2) +/- 1.3, P = .006). Total arterial area and volume did not differ significantly between ischemic and nonischemic legs. CONCLUSION: BMC injection had a substantial effect on arteriogenesis, with normalization of total arterial area and volume in the BMC group; this effect was successfully depicted.

Tumor classification based on DNA copy number aberrations determined using SNP arrays.

High-density single nucleotide polymorphism (SNP) array is a recently introduced technology that genotypes more than 10,000 human SNPs on a single array. It has been shown that SNP arrays can be used to determine not only SNP genotype calls, but also DNA copy number (DCN) aberrations, which are common in solid tumors. In the past, effective cancer classification has been demonstrated using microarray gene expression data, or DCN data derived from comparative genomic hybridization (CGH) arrays. However, the feasibility of cancer classification based on DCN aberrations determined by SNP arrays has not been previously investigated. In this study, we address this issue by applying state-of-the-art classification algorithms and feature selection algorithms to the DCN aberration data derived from a public SNP array dataset. Performance was measured via leave-one-out cross-validation (LOOCV) classification accuracy. Experimental results showed that the maximum accuracy was 73.33%, which is comparable to the maximum accuracy of 76.5% based on CGH-derived DCN data reported previously in the literature. These results suggest that DCN aberration data derived from SNP arrays is useful for etiology-based tumor classification.

Early lung cancer detection based on registered perfusion MRI.

Lung cancer remains the most common fatal malignancy in both men and women in the United States and elsewhere around the world among people who have been exposed passively or actively to tobacco smoke. Technological advances have produced imaging modalities that are proving to be useful for the early detection of lung cancer. In the usual modes, computed tomography (CT) and magnetic resonance imaging (MRI) can identify suspicious lesions, but further work is needed to detect cancer in its early stage. Tumor angiogenesis assessed by perfusion-sensitive MRI is a promising method for early and accurate identification of lung cancer that avoids patient stress and the potential progression to a less treatable stage inherent in serial imaging. However, compensating for the respiratory and anatomical structure motion is a challenge. In order to use perfusion MRI in a signal imaging session to define metabolic and vascular characteristics of tumors, we present a novel affine registration method for perfusion MRI that can register points of interest by tracking image intensity changes around the target point. The registration results are used to generate accurate time intensity curves (TIC) of different regions of interest (ROI). The patterns of different TICs are mapped on the cancer and other structures. The method is computationally efficient and performs well in our perfusion MRI sequence analysis.

Spatio-temporal modeling of lung images for cancer detection.

Perfusion magnetic resonance imaging (pMRI) is an important tool in assessing tumor angiogenesis for the early detection of lung cancer. This study presents a novel integrated framework for spatio-temporal modeling of pulmonary nodules in pMRI image sequences. After localizing a nodule region in each image, we perform segmentation in the region to extract the nodule boundary, then use thin-plate spline interpolation for nodule registration along the temporal dimension. The resulting spatio-temporal model can lead to many types of nodule characterization, e.g. a time-intensity profile of a nodule region, and be used to capture important angiogenic patterns in the lung that can distinguish between cancer and benign nodules and assist in early detection.

Impact of mouse strain differences in innate hindlimb collateral vasculature.

OBJECTIVE: To assess the importance of genetic background for collateral artery development. METHODS AND RESULTS: C57BL/6, BALB/c and 129S2/Sv mice were studied after femoral artery ligation by laser Doppler imaging, visible light oximetry, time-of-flight-magnetic resonance imaging, and treadmill testing; C57BL/6 and BALB/c also underwent electron paramagnetic resonance (EPR) oximetry, x-ray angiography, and histology. C57BL/6 had the least initial distal ischemia and most complete recovery. BALB/c had the most severe initial ischemia and poorest recovery. BALB/c had some vasodilatory reserve in their ligated limbs not seen in the other strains at 3 weeks. By in vivo TOF-magnetic resonance angiography, C57BL/6 had larger preexistent and developed collaterals. By x-ray angiography, C57BL/6 had a higher collateral-dependent filling score and number of visible collaterals immediately after femoral ligation and a higher number of visible collaterals at 1 week but not at 4 weeks. EPR oximetry and histology revealed hypoxia and tissue damage in regions of collateral growth of BALB/c but not C57BL/6 mice. In C57BL/6 BrdUrd uptake in the thigh was limited to larger vessels and isolated perivascular cells. Proliferative activity in collateral arterioles was similar in both strains. CONCLUSIONS: Genetic differences in preexistent collateral vasculature can profoundly affect outcome and milieu for compensatory collateral artery growth after femoral artery occlusion.

Adenoviral PR39 improves blood flow and myocardial function in a pig model of chronic myocardial ischemia by enhancing collateral formation.

Angiogenic therapy with individual growth factors or "master switch" genes is being evaluated for treatment of advanced coronary artery disease. In this study, we investigated the efficacy and mechanism of PR39, a gene capable of activating VEGF and fibroblast growth factor (FGF)-2-dependent pathways. PR39 enhances hypoxia-inducible factor-1alpha (HIF-1alpha)-dependent gene expression by selectively inhibiting proteasome degradation of this transcription factor. In addition, PR39 also stimulates expression of the FGF receptors (FGFR)-1 and syndecan-4. In a pig model of chronic myocardial ischemia, we used angiography, MRI, and microsphere regional blood flow to evaluate the efficacy of intramyocardial adenoviral protein arginine-rich peptide (Ad-PR39) injections. Ad-PR39 improved collateral scores, regional perfusion, and regional function in a dose-dependent manner. Local VEGF, VEGFR-1, VEGFR-2, syndecan, and FGFR-1 levels were 16-75% upregulated after Ad-PR39 injections as assessed by real-time PCR, suggesting upregulation of VEGF and FGF pathways. PR39 is an angiogenic peptide that improves perfusion and function of ischemic myocardium, at least in part, through collateral formation. The dual mechanism, i.e., stimulation of HIF-1alpha and FGF receptor expression, likely accounts for the functional benefits of PR39.

Automated migration analysis based on cell texture: method & reliability.

BACKGROUND: In this paper, we present and validate a way to measure automatically the extent of cell migration based on automated examination of a series of digital photographs. It was designed specifically to identify the impact of Second Hand Smoke (SHS) on endothelial cell migration but has broader applications. The analysis has two stages: (1) preprocessing of image texture, and (2) migration analysis. RESULTS: The output is a graphic overlay that indicates the front lines of cell migration superimposed on each original image, with automated reporting of the distance traversed vs. time. Expert preference compares to manual placement of leading edge shows complete equivalence of automated vs. manual leading edge definition for cell migration measurement. CONCLUSION: Our method is indistinguishable from careful manual determinations of cell front lines, with the advantages of full automation, objectivity, and speed.

Modeling Time-Intensity Profiles for Pulmonary Nodules in MR Images.

Perfusion magnetic resonance imaging (pMRI) is an important tool to assess tumor angiogenesis for the early detection of lung cancer. This paper presents a novel integrated framework for spatio-temporal modeling of pulmonary nodules in pMRI image sequences. After localizing a nodule region in each image, we perform segmentation in the region to extract nodule boundary, and then use thin-plate spline interpolation for nodule registration along the temporal dimension. The resulting spatio-temporal model can lead to many types of nodule characterization. Time intensity profiles of nodules region capture important angiogenic patterns in the lung that can distinguish between cancer and benign nodules and help early detection.

Surface alignment of 3D spherical harmonic models: application to cardiac MRI analysis.

The spherical harmonic (SPHARM) description is a powerful surface modeling technique that can model arbitrarily shaped but simply connected 3D objects and has been used in many applications in medical imaging. Previous SPHARM techniques use the first order ellipsoid for establishing surface correspondence and aligning objects. However, this first order information may not be sufficient in many cases; a more general method for establishing surface correspondence would be to minimize the mean squared distance between two corresponding surfaces. In this paper, a new surface matching algorithm is proposed for 3D SPHARM models to achieve this goal. This algorithm employs a useful rotational property of spherical harmonic basis functions for a fast implementation. Applications of medical image analysis (e.g., spatio-temporal modeling of heart shape changes) are used to demonstrate this approach. Theoretical proofs and experimental results show that our approach is an accurate and flexible surface correspondence alignment method.

A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis.

We propose a novel framework to predict pacing sites in the left ventricle (LV) of a heart and its result can be used to assist pacemaker implantation and programming in cardiac resynchronization therapy (CRT), a widely adopted therapy for heart failure patients. In a traditional CRT device deployment, pacing sites are selected without quantitative prediction. That runs the risk of suboptimal benefits. In this work, the spherical harmonic (SPHARM) description is employed to model the ventricular surfaces and a novel SPHARM-based surface correspondence approach is proposed to capture the ventricular wall motion. A hierarchical agglomerative clustering technique is applied to the time series of regional wall thickness to identify candidate pacing sites. Using clinical MRI data in our experiments, we demonstrate that the proposed framework can not only effectively identify suitable pacing sites, but also distinguish patients from normal subjects perfectly to help medical diagnosis and prognosis.

HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data.

MOTIVATION: Recent studies have shown that microarray gene expression data are useful for phenotype classification of many diseases. A major problem in this classification is that the number of features (genes) greatly exceeds the number of instances (tissue samples). It has been shown that selecting a small set of informative genes can lead to improved classification accuracy. Many approaches have been proposed for this gene selection problem. Most of the previous gene ranking methods typically select 50-200 top-ranked genes and these genes are often highly correlated. Our goal is to select a small set of non-redundant marker genes that are most relevant for the classification task. RESULTS: To achieve this goal, we developed a novel hybrid approach that combines gene ranking and clustering analysis. In this approach, we first applied feature filtering algorithms to select a set of top-ranked genes, and then applied hierarchical clustering on these genes to generate a dendrogram. Finally, the dendrogram was analyzed by a sweep-line algorithm and marker genes are selected by collapsing dense clusters. Empirical study using three public datasets shows that our approach is capable of selecting relatively few marker genes while offering the same or better leave-one-out cross-validation accuracy compared with approaches that use top-ranked genes directly for classification. AVAILABILITY: The HykGene software is freely available at http://www.cs.dartmouth.edu/~wyh/software.htm CONTACT: wyh@cs.dartmouth.edu SUPPLEMENTARY INFORMATION: Supplementary material is available from http://www.cs.dartmouth.edu/~wyh/hykgene/supplement/index.htm.

Novel double contrast MRI technique for intramyocardial detection of percutaneously transplanted autologous cells.

Bone marrow cells (BMC) labeled with iron particles can be injected into the heart and detected with MRI. Improvement in conspicuity of labelled cells would be advantageous. This study examined if double contrast with iron oxide and Gd-DTPA enhances cell MRI after transvascular transplantation in myocardial infarction. Ten pigs with week-old myocardial infarction had transvascular peri-infarct delivery of microspheres alone (Group I, n = 3) or mixed with iron-labeled BMCs (Group II, n = 7). Gradient-echo MRI before and 1 min after systemic Gd-DTPA administration produced regions of interest with hypoenhancement that were compared to contralateral regions for contrast-to-noise (CNR) and signal-to-noise (SNR) ratios. All hearts were harvested for gross and microscopic analysis. Areas of focal hypoenhancement corresponding to the BMCs were detected in the myocardium in Group II. Early after administration of Gd-DTPA CNR increased from 17.58 +/- 8.5 to 27.25 +/- 15.8 (P < 0.05) and SNR from 24.87 +/- 9.6 to 35.08 +/- 15.5 (P < 0.05). There was no hypoenhancement in Group I. Tissue examination confirmed presence of iron-containing cells and microspheres in corresponding segments of the heart. The distribution of microspheres was similar between the groups. Double contrast with cellular iron and Gd-DTPA in surrounding myocardium resulted in improved cell localization by MRI.

Detection of exercise-induced ischemia by changes in B-type natriuretic peptides.

OBJECTIVES: The purpose of this study was to examine the effect of exercise-induced ischemia on levels of B-type natriuretic peptide (BNP) and its inactive N-terminal fragment (NT-pro-BNP)and to determine whether measurement of these peptides can improve the diagnostic accuracy of exercise testing. BACKGROUND: The ability of exercise testing to detect coronary artery disease (CAD) is limited by modest sensitivity and specificity. B-type natriuretic peptides (NT-pro-BNP and BNP) are released by ventricular myocytes in response to wall stress. We hypothesized that exercise-induced ischemia results in increased wall stress and triggers release of NT-pro-BNP and BNP. METHODS: A total of 74 patients with known CAD, normal left ventricular function, and normal resting levels of NT-pro-BNP and BNP who were referred for exercise testing with radionuclide imaging, and 21 healthy volunteers, were enrolled. Blood was drawn before and after maximal exercise and analyzed for NT-pro-BNP and BNP. RESULTS: Of the patients with CAD, 40 had ischemia on perfusion images and 34 did not. Median post-exercise increases in NT-pro-BNP and BNP (DeltaNT-pro-BNP and DeltaBNP) were approximately four-fold higher in the ischemic group than in the nonischemic group (DeltaNT-pro-BNP 14.5 vs. 4 pg/ml, p < 0.0001; DeltaBNP 36.5 vs. 7.5 pg/ml, p < 0.0001). In volunteers, median DeltaNT-pro-BNP was almost identical to that of the nonischemic patient group. At equal specificity to the electrocardiogram (ECG) (58.8%), the sensitivities of DeltaNT-pro-BNP and DeltaBNP for detecting ischemia were 90% and 80%, respectively; in contrast, the sensitivity of the exercise ECG was 37.5%. CONCLUSIONS: Measurement of exercise-induced increases in BNPs more than doubles the sensitivity of the exercise test for detecting ischemia with no loss of specificity.

An extensible framework for sharing clinical guidelines and services.

Accurate and descriptive information from clinical studies guides improvements in health care. Clinical guidelines established by authoritative medical organizations provide such information in a standard form for medical professionals' reference. Previous work on electronically sharing clinical guidelines focuses on the idea of building unified clinical terminologies and sharing resources through centralized data repositories. In this paper we propose a novel five-layer framework called the Extensible Clinical Guidelines and Services Sharing Architecture (ECGSSA). This framework provides for clinical guideline sharing among autonomous service providers over a distributed architecture. Requests for exchange of guidelines are disseminated through Web Services through a registry mechanism. Currently we have adopted the Guideline Interchange Format (GLIF) from InterMed as the representation format and use the Open Grid Services Architecture (OGSA) to attain virtual organization of shared guideline and service resources. This approach will allow more flexibility for medical professionals to exchange their practice guidelines in an effort to improve quality of health care. Also, it extends the possibility of solving clinic-related computational problems through collaborative sharing of analytical services. A sample scenario is presented to explain the application of ECGSSA in distributed task assignment and service matching in medical image processing.

Efficient similarity retrieval for temporal shape sequences: a case study using cardiac MR images.

The spherical harmonics (SPHARM) approach has been used for the representation of shapes in many types of biomedical image data. We propose a SPHARM-based similarity comparison for shape sequences that allows fast similarity searches for dynamic objects and demonstrate it using 3D images of a beating heart. By using spherical harmonics to extract a small number of features that represent cardiac shape in each sequential state, we enable indexing and pruning of database entries with a multidimensional index tree (e.g. R*-tree) for fast retrieval. Our approach relies on obtaining selected landmarks to allow normalization within and between sequences. This framework is extensible to other application domains.

BP-neural network based-characterization of electrographic magnetohydrodynamic signals in MR.

Electrocardiographs (ECG) signal collected during magnetic resonance (MR) imaging is affected by signal artifact because magnetic fields produce competing signals, from moving conductors in the large vessels. That is called the magnetohydrodynamic effect, which makes it difficult to recognize ST-T changes from ECG signal collected in a magnetic field (MRI). Resolving that problem is important both for accurate triggering (elimination of false triggers from tall peaked T waves) and for monitoring (identifying if or when patient develops ischemia or myocardial injury). This work describes an algorithm based on neural network that is designed to cancel this artifact for ECG signal acquired during MR imaging.

An adaptive approach for image subtraction.

Image subtraction is widely used in angiography as a means of highlighting differences induced by contrast agents. New knowledge of previously unsuspected causes of disease, in particular, secondhand smoke exposure, spurs interest in pushing the limits of early accurate diagnosis. Simple image subtraction induces artifacts causing problems for ensuing measurements and 3D reconstruction. Image registration techniques have been used to partially solve this problem. However, a complete registration is slow, and misregistration often occurs in images where bones are surrounded by vessels with similar image characteristics. We propose an approach based on the idea of global match followed by local refinements. In the global match, an image pair is aligned using a similarity measure so as to reduce overall difference. In the local refinements, localized displacements and deformations of tissue are handled by a combination of techniques: image registration, region growing, erosion, and dilation. This approach is fast compared to registration based image subtraction and it can find vessels abutting a bone. It is designed to be especially suitable for large cross-section image stacks. With additional vessel connectivity analysis between adjacent slices, the algorithm provides a good foundation for 3D vessel reconstruction.