Fast algorithm for 3-D vascular tree modeling

Krȩtowski, Marek; Rolland, Yan; Bézy-Wendling, Johanne; Coatrieux, Jean-Louis

doi:10.1016/s0169-2607(01)00200-0

Cited by 31 publications

(22 citation statements)

References 15 publications

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“…During this last decade, several teams developed sophisticated computer models simulating the physiologic growing of the arterial tree (18,19), taking into account fluid turbulence and viscosity and optimizing blood pressure and vessels radii. However, only simulations of the arterial tree feeding up to 10,000 lobule clusters were reported.…”

Section: Posttherapy 90 Y Tof Petmentioning

confidence: 99%

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

Walrand

Hesse

Chiesa³

et al. 2013

J Nucl Med

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90 Y resin and glass microsphere liver radioembolizations delivering lobar doses of 70 and 120 Gy, respectively, display hepatic toxicity similar to 40-Gy fractionated external-beam radiotherapy. We investigated how the lower number of glass microspheres could induce a sufficiently nonuniform dose distribution explaining this paradox. Methods: Microscale dosimetry was assessed in the realistic liver model developed by Gulec et al. but using the Russell's dose deposition kernel. A lattice of hexagonal prisms represented the hepatic lobules. Two hepatic arterial tree models-that is, a fixed-length and a variable-branches length-were used for the microsphere transport. Equal or asymmetric microsphere relative-spreading probability between 2 daughter vessels was assumed. Several 120-Gy liver simulations were performed: periodic simulations, where 1 or 6 glass microspheres were trapped in all and in only 1 of 6 portal tracts, respectively, and random simulations, where glass microsphere trapping assumed an equal probability for all the portal tracts or a variable probability depending on the successions of artery connections leading to the portal tract, both for the 2 arterial tree models. Results: For the 2 uniform simulations, all hepatic structures received at least 100 Gy. The fast decrease of the 90 Y kernel as the inverse of the square of the distance r is counterbalanced by the number of contributing lobules containing microspheres that increases as r 2 . The random simulation with equal-spreading probability gave for the less irradiated tissue a lobule dose distribution centered around 103 Gy (full width at half maximum, 20 Gy). The distribution became significantly asymmetric with the 60%-40% relative-spreading probability, with a shift of the maximum from 103 down to 50 Gy, and about 17% of the lobules got a dose lower than 40 Gy to their different structures. Conclusion: The large nonuniform trapping produced by the microsphere transport in the arterial tree jointly with the low number of injected glass microspheres begins to explain their lower hepatic toxicity per Gray. In addition, the nonuniform trapping supports the fact that the granular aspect of 90 Y PET imaging observed in patients could represent some reality and not only statistical noise.

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Section: Posttherapy 90 Y Tof Petmentioning

confidence: 99%

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

Walrand

Hesse

Chiesa³

et al. 2013

J Nucl Med

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“…The next step consists in re-computing the characteristics of the whole tree (blood ow, pressure and radii). A fast algorithm has been deÿned to optimize this procedure, that allows to considerably reduce the computation time [20].…”

Section: Vesselsmentioning

confidence: 99%

Hepatic tumor enhancement in computed tomography: combined models of liver perfusion and dynamic imaging

Bézy-Wendling

Krȩtowski

Rolland

2003

Computers in Biology and Medicine

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The objective of this study is to show how computational modeling can be used to increase our understanding of liver enhancement in dynamic computer tomography. It relies on two models: (1) a vascular model, based on physiological rules, is used to generate the 3D hepatic vascular network; (2) the physical process of CT acquisition allows to synthesize timed-stamped series of images, aimed at tracking the propagation of a contrast material through the vessel network and the parenchyma. The coupled models are used to simulate the enhancement of a hyper-vascular tumor at di erent acquisition times, showing a maximum conspicuity during the arterial phase. ?

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“…There are two main methods for simulating vascular structures: (i) Lindenmayer systems: a set of production rules (grammar) used to iteratively generate complex shapes, often used to describe the growth of plants [18]; and (ii) iterative growth into a perfusion volume: growing a vascular structure by iteratively connecting new terminal nodes chosen from some volume [19,20,21,22]. We follow the latter approach because it allows greater control over the volume of the vasculature and is amenable to conforming to physical hemodynamics laws and blood vessel formation constraints, as we will see later.…”

Section: Introductionmentioning

confidence: 99%

VascuSynth: Simulating vascular trees for generating volumetric image data with ground-truth segmentation and tree analysis

Hamarneh

Jassi

2010

Computerized Medical Imaging and Graphics

134

125

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Automated segmentation and analysis of tree-like structures from 3D medical images are important for many medical applications, such as those dealing with blood vasculature or lung airways. However, there is an absence of large databases of expert segmentations and analyses of such 3D medical images, which impedes the validation and training of proposed image analysis algorithms. In this work, we simulate volumetric images of vascular trees and generate the corresponding ground truth segmentations, bifurcation locations, branch properties, and tree hierarchy. The tree generation is performed by iteratively growing a vascular structure based on a user-defined (possibly spatially varying) oxygen demand map. We describe the details of the algorithm and provide a variety of example results.

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Fast algorithm for 3-D vascular tree modeling

Cited by 31 publications

References 15 publications

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

Hepatic tumor enhancement in computed tomography: combined models of liver perfusion and dynamic imaging

VascuSynth: Simulating vascular trees for generating volumetric image data with ground-truth segmentation and tree analysis

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Fast algorithm for 3-D vascular tree modeling

Cited by 31 publications

References 15 publications

The Low Hepatic Toxicity per Gray of 90Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

The Low Hepatic Toxicity per Gray of 90Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

Hepatic tumor enhancement in computed tomography: combined models of liver perfusion and dynamic imaging

VascuSynth: Simulating vascular trees for generating volumetric image data with ground-truth segmentation and tree analysis

Contact Info

Product

Resources

About

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging

The Low Hepatic Toxicity per Gray of ⁹⁰Y Glass Microspheres Is Linked to Their Transport in the Arterial Tree Favoring a Nonuniform Trapping as Observed in Posttherapy PET Imaging