Simulated annealing approach to vascular structure with application to the coronary arteries

Keelan, Jonathan; Chung, Emma; Hague, J. P.

doi:10.1098/rsos.150431

Cited by 24 publications

(50 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where i, j and k are voxel coordinates, S is the line segment corresponding to the vessel and D ijk is the distance map value, which is calculated from MRI data as discussed in the next section [6]. Cerebral arterioles with diameters less than ∼ 100µm are responsible for penetrating deep within cortical tissue [2].…”

Section: Exclusion Of Large Arteriesmentioning

confidence: 99%

“…To computationally obtain globally optimised configurations of arteries, the authors recently proposed a novel Simulated Annealing Vascular Optimisation algorithm (SAVO) [6]. Advantages of this algorithm include the ability to identify the most efficient 'ideal' tree with minimal metabolic demand.…”

Section: Introductionmentioning

confidence: 99%

“…All length scales are treated using identical optimisation principles. The algorithm was previously applied to modelling the coronary vasculature, which involved optimising an extensive (>6000 branch) arterial tree for a challenging hollow organ (the heart) [6]. The resulting idealised coronary artery structure was a close match to porcine cardiac morphological data…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Development of a globally optimised model of the cerebral arteries

Keelan¹,

Chung²,

Hague³

2019

Phys. Med. Biol.

Self Cite

View full text Add to dashboard Cite

The cerebral arteries are difficult to reproduce from first principles, featuring interwoven territories, and intricate layers of grey and white matter with differing metabolic demand. The aim of this study was to identify the ideal configuration of arteries required to sustain an entire brain hemisphere based on minimisation of the energy required to supply the tissue. The 3D distribution of grey and white matter within a healthy human brain was first segmented from Magnetic Resonance Images. A novel simulated annealing algorithm was then applied to determine the optimal configuration of arteries required to supply brain tissue. The model is validated through comparison of this ideal, entirely optimised, brain vasculature with the known structure of real arteries. This establishes that the human cerebral vasculature is highly optimised; closely resembling the most energy efficient arrangement of vessels. In addition to local adherence to fluid dynamics optimisation principles, the optimised vasculature reproduces global brain perfusion territories with well defined boundaries between anterior, middle and posterior regions. This validated brain vascular model and algorithm can be used for patient-specific modelling of stroke and cerebral haemodynamics, identification of sub-optimal conditions associated with vascular disease, and optimising vascular structures for tissue engineering and artificial organ design.

show abstract

Section: Exclusion Of Large Arteriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development of a globally optimised model of the cerebral arteries

Keelan¹,

Chung²,

Hague³

2019

Phys. Med. Biol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Cardiac veins carry blood with a poor level of oxygen from the myocardium to the right atrium. The anatomy of the veins of the heart is quite variable [35].…”

Section: Behaviors Of Coronary Circulation Systemmentioning

confidence: 99%

Artificial Coronary Circulation System; A new bio-inspired metaheuristic algorithm

Kaveh

Kooshkebaghi

2019

Scientia Iranica

View full text Add to dashboard Cite

A new swarm intelligence optimization technique, called Arti cial Coronary Circulation System (ACCS), is proposed in this study. This optimization method simulates the growth of coronary arteries (veins) in the human heart. In this algorithm, each capillary is considered a candidate solution. This algorithm starts with a random initial population of candidate solutions and evaluates them by using Coronary Growth Factor (CGF). In each run, the best candidate solution is selected as the main coronary vessel (artery or vein), and the other capillaries are considered as searchers of the search space. Then, the heart decides whether other candidates move toward/away from the main coronary vessels and searches for the optimal solution by using heart memory. Finally, the application of the proposed algorithm is demonstrated with respect to some benchmark functions and some mechanical problems, con rming the potential and capability of the new algorithm.

show abstract

“…CCO was recently extended to work on neural trees at the surface of the heart by Ulysses et al [24]. Another recent method has been proposed by Keelan et al [15], that also handles non convex territory for vascular networks. It minimizes pumping power and blood volume with a simulated annealing approach to generate left and right coronary models.…”

Section: Introductionmentioning

confidence: 99%

Generation of Patient-Specific Cardiac Vascular Networks: A Hybrid Image-Based and Synthetic Geometric Model

Jaquet

Najman

Talbot

et al. 2019

IEEE Trans. Biomed. Eng.

View full text Add to dashboard Cite

Abstract-Objective: In this paper, we propose an algorithm for the generation of a patient-specific cardiac vascular network starting from segmented epicardial vessels down to the arterioles.Method: We extend a tree generation method based on satisfaction of functional principles, named Constrained Constructive Optimization (CCO), to account for multiple, competing vascular trees. The algorithm simulates angiogenesis under vascular volume minimization with flow-related and geometrical constraints adapting the simultaneous tree growths to patient priors. The generated trees fill the entire left ventricle myocardium up to the arterioles.Results: From actual vascular tree models segmented from CT images, we generated networks with 6000 terminal segments for 6 patients. These networks contain between 33 and 62 synthetic trees. All vascular models match morphometry properties previously described.Conclusion and significance: Image-based models derived from CT angiography are being used clinically to simulate blood flow in the coronary arteries of individual patients to aid in the diagnosis of disease and planning treatments. However, image resolution limits vessel segmentation to larger epicardial arteries. The generated model can be used to simulate blood flow and derived quantities from the aorta into the myocardium. This is an important step for diagnosis and treatment planning of coronary artery disease.

show abstract

Simulated annealing approach to vascular structure with application to the coronary arteries

Cited by 24 publications

References 54 publications

Development of a globally optimised model of the cerebral arteries

Development of a globally optimised model of the cerebral arteries

Artificial Coronary Circulation System; A new bio-inspired metaheuristic algorithm

Generation of Patient-Specific Cardiac Vascular Networks: A Hybrid Image-Based and Synthetic Geometric Model

Contact Info

Product

Resources

About