Vascular tree reconstruction by minimizing a physiological functional cost

Jiang, Yifeng; Zhuang, Zhenwu; Sinusas, Albert J.; Papademetris, Xenophon

doi:10.1109/cvprw.2010.5543593

Cited by 10 publications

(17 citation statements)

References 29 publications

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“…The 3D vascular tree was reconstructed using a recently published vascular tree reconstruction algorithm (69). The overall process consisted of 2 parts: (a) vessel detection and skeletonization and (b) connectivity.…”

Section: Figurementioning

confidence: 99%

“…(71). For vessel connectivity, we used our recently developed and validated physiologically constrained method that was described in detail previously (69). This method takes as inputs a set of disconnected vessel fragments (the output of the detection/skeletonization algorithms) and connects them to form an optimal 3D vascular tree by selecting the candidate vascular tree that minimizes the overall energy required to perfuse the heart muscle -a constraint that is formally derived from Murray's hypothesis (72).…”

Section: Figurementioning

confidence: 99%

“…This method takes as inputs a set of disconnected vessel fragments (the output of the detection/skeletonization algorithms) and connects them to form an optimal 3D vascular tree by selecting the candidate vascular tree that minimizes the overall energy required to perfuse the heart muscle -a constraint that is formally derived from Murray's hypothesis (72). This method was previously shown to have statistically significant performance improvements over prior simpler methods (e.g., minimum spanning tree) in this type of image (69). From the resulting 3D-connected model of the vascular tree, we proceeded to compute detailed morphometric descriptors of the vascular anatomy.…”

Section: Figurementioning

confidence: 99%

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NO triggers RGS4 degradation to coordinate angiogenesis and cardiomyocyte growth

Jaba¹,

Zhuang²,

Li³

et al. 2013

J. Clin. Invest.

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Myocardial hypertrophy is an adaptation to increased hemodynamic demands. An increase in heart tissue must be matched by a corresponding expansion of the coronary vasculature to maintain and adequate supply of oxygen and nutrients for the heart. The physiological mechanisms that underlie the coordination of angiogenesis and cardiomyocyte growth are unknown. We report that induction of myocardial angiogenesis promotes cardiomyocyte growth and cardiac hypertrophy through a novel NO-dependent mechanism. We used transgenic, conditional overexpression of placental growth factor (PlGF) in murine cardiac tissues to stimulate myocardial angiogenesis and increase endothelial-derived NO release. NO production, in turn, induced myocardial hypertrophy by promoting proteasomal degradation of regulator of G protein signaling type 4 (RGS4), thus relieving the repression of the Gβγ/PI3Kγ/AKT/mTORC1 pathway that stimulates cardiomyocyte growth. This hypertrophic response was prevented by concomitant transgenic expression of RGS4 in cardiomyocytes. NOS inhibitor L-NAME also significantly attenuated RGS4 degradation, and reduced activation of AKT/mTORC1 signaling and induction of myocardial hypertrophy in PlGF transgenic mice, while conditional cardiac-specific PlGF expression in eNOS knockout mice did not induce myocardial hypertrophy. These findings describe a novel NO/RGS4/Gβγ/PI3Kγ/AKT mechanism that couples cardiac vessel growth with myocyte growth and heart size. IntroductionRecent studies have increased appreciation for the relationship between cardiomyocyte growth and angiogenesis and its contribution to molecular regulation of the myocardial hypertrophic response. Myocardial hypertrophy, secondary to increased hemodynamic demands, requires commensurate growth of the coronary vasculature to provide adequate oxygen and nutrients to the increasing cardiac mass; lack of coordination between the myocyte-driven hypertrophic response and the production of angiogenic growth factors hallmarks the transition to heart failure (1). Although vascular endothelium controls a plethora of biological events contributing to cardiovascular homeostasis, including regulation of vascular tone, thrombosis, and myocardial stiffness, little is known about the effect of endothelial signaling on cardiomyocyte growth, regulation of myocardial hypertrophy, and heart size. Our previous observation that a NOS inhibitor, N G -nitro-l-arginine methyl ester (L-NAME), partially prevented angiogenesis-driven myocardial hypertrophy (2) suggests that endothelium-dependent NO production might be responsible for the hypertrophic effect on cardiomyocytes and the increase in heart size.Because there are no known mechanisms that link NO to stimulation of cardiomyocyte hypertrophy, we designed the present study to fill this gap. In cardiomyocytes, G protein-mediated hypertrophic signaling is negatively modulated by regulators of G protein signaling (RGS proteins). Among more than 20 RGS proteins, RGS subtype 4, a GTPase-activating protein for heterotrimeric Gq and ...

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Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

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NO triggers RGS4 degradation to coordinate angiogenesis and cardiomyocyte growth

Jaba¹,

Zhuang²,

Li³

et al. 2013

J. Clin. Invest.

Self Cite

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show abstract

“…However, both are challenging and beyond the scope of the current EMILOVE implementation. An intuitive solution would be to resolve ambiguities by using a path optimization like in [53] or a tree optimization algorithm in postprocessing that considers further physiological properties of vessels like [54].…”

Section: G Discussionmentioning

confidence: 99%

Efficient Monte Carlo Image Analysis for the Location of Vascular Entity

Skibbe

Reisert

Maeda

et al. 2015

IEEE Trans. Med. Imaging

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Tubular shaped networks appear not only in medical images like X-ray-, time-of-flight MRI- or CT-angiograms but also in microscopic images of neuronal networks. We present EMILOVE (Efficient Monte-carlo Image-analysis for the Location Of Vascular Entity), a novel modeling algorithm for tubular networks in biomedical images. The model is constructed using tablet shaped particles and edges connecting them. The particles encode the intrinsic information of tubular structure, including position, scale and orientation. The edges connecting the particles determine the topology of the networks. For simulated data, EMILOVE was able to accurately extract the tubular network. EMILOVE showed high performance in real data as well; it successfully modeled vascular networks in real cerebral X-ray and time-of-flight MRI angiograms. We also show some promising, preliminary results on microscopic images of neurons.

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“…While segmenting and tracing tubular structures is a longstanding field of interest in medical image computing [3][4][5][6], we approach here the wider -and somewhat neglected [7] -problem of extracting the full vascular network from image volumes under consideration of global geometric properties of the vascular structure.…”

Section: Introductionmentioning

confidence: 99%

Extracting Vascular Networks under Physiological Constraints via Integer Programming

Rempfler

Schneider

Ielacqua

et al. 2014

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014

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Abstract. We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a highresolution micro computed tomography (µCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography (µMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.

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Vascular tree reconstruction by minimizing a physiological functional cost

Cited by 10 publications

References 29 publications

NO triggers RGS4 degradation to coordinate angiogenesis and cardiomyocyte growth

NO triggers RGS4 degradation to coordinate angiogenesis and cardiomyocyte growth

Efficient Monte Carlo Image Analysis for the Location of Vascular Entity

Extracting Vascular Networks under Physiological Constraints via Integer Programming

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