Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields.

Srinivasan Rajagopalan, Richard A. Robb

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Tissue engineering integrates the principles of engineering and life sciences toward the design, construction, modification and growth of biological substitutes that restore, maintain, or improve tissue function. The structural integrity and ultimate functionality of such tissue analogs is defined by scaffolds- porous, three-dimensional "trellis-like" structures that, on implantation, provide a viable environment to regenerate damaged tissues. The orthogonal scaffold fabrication methods currently employed can be broadly classified into two categories: (a) conventional, irreproducible, stochastic techniques producing reasonably biomorphic scaffold architecture, and (b) rapidly emerging, repeatable, computer-controlled techniques producing straight edged "contra naturam" scaffold architecture. In this paper, we present the results of the first attempt in an image-based scaffold modeling and optimization strategy that synergistically exploits the orthogonal fabrication techniques to create repeatable, biomorphic scaffolds with optimal scaffold morphology. Motivated by the use of Gaussian random fields (GRF) to model cosmological structure formation, we use appropriately ordered and clipped stacks of GRF to model the three-dimensional pore-solid scaffold labyrinths. Image-based metrology, fabrication and mechanical characterization of these scaffolds reveal the possibility of enabling the previously elusive deployment of promising benchside tissue analogs to the clinical bedside.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages544-552
Number of pages9
Volume9
EditionPt 2
StatePublished - 2006

Fingerprint

Biomimetics
Tissue Engineering
Biological Science Disciplines
Inner Ear
Growth

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Rajagopalan, S., & Robb, R. A. (2006). Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 2 ed., Vol. 9, pp. 544-552)

Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields. / Rajagopalan, Srinivasan; Robb, Richard A.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 9 Pt 2. ed. 2006. p. 544-552.

Research output: Chapter in Book/Report/Conference proceedingChapter

Rajagopalan, S & Robb, RA 2006, Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 edn, vol. 9, pp. 544-552.
Rajagopalan S, Robb RA. Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 ed. Vol. 9. 2006. p. 544-552
Rajagopalan, Srinivasan ; Robb, Richard A. / Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 9 Pt 2. ed. 2006. pp. 544-552
@inbook{e2a0134a36ff4f3d9f3e3b95c0317e8a,
title = "Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields.",
abstract = "Tissue engineering integrates the principles of engineering and life sciences toward the design, construction, modification and growth of biological substitutes that restore, maintain, or improve tissue function. The structural integrity and ultimate functionality of such tissue analogs is defined by scaffolds- porous, three-dimensional {"}trellis-like{"} structures that, on implantation, provide a viable environment to regenerate damaged tissues. The orthogonal scaffold fabrication methods currently employed can be broadly classified into two categories: (a) conventional, irreproducible, stochastic techniques producing reasonably biomorphic scaffold architecture, and (b) rapidly emerging, repeatable, computer-controlled techniques producing straight edged {"}contra naturam{"} scaffold architecture. In this paper, we present the results of the first attempt in an image-based scaffold modeling and optimization strategy that synergistically exploits the orthogonal fabrication techniques to create repeatable, biomorphic scaffolds with optimal scaffold morphology. Motivated by the use of Gaussian random fields (GRF) to model cosmological structure formation, we use appropriately ordered and clipped stacks of GRF to model the three-dimensional pore-solid scaffold labyrinths. Image-based metrology, fabrication and mechanical characterization of these scaffolds reveal the possibility of enabling the previously elusive deployment of promising benchside tissue analogs to the clinical bedside.",
author = "Srinivasan Rajagopalan and Robb, {Richard A.}",
year = "2006",
language = "English (US)",
volume = "9",
pages = "544--552",
booktitle = "Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention",
edition = "Pt 2",

}

TY - CHAP

T1 - Cosmology inspired design of biomimetic tissue engineering templates with Gaussian random fields.

AU - Rajagopalan, Srinivasan

AU - Robb, Richard A.

PY - 2006

Y1 - 2006

N2 - Tissue engineering integrates the principles of engineering and life sciences toward the design, construction, modification and growth of biological substitutes that restore, maintain, or improve tissue function. The structural integrity and ultimate functionality of such tissue analogs is defined by scaffolds- porous, three-dimensional "trellis-like" structures that, on implantation, provide a viable environment to regenerate damaged tissues. The orthogonal scaffold fabrication methods currently employed can be broadly classified into two categories: (a) conventional, irreproducible, stochastic techniques producing reasonably biomorphic scaffold architecture, and (b) rapidly emerging, repeatable, computer-controlled techniques producing straight edged "contra naturam" scaffold architecture. In this paper, we present the results of the first attempt in an image-based scaffold modeling and optimization strategy that synergistically exploits the orthogonal fabrication techniques to create repeatable, biomorphic scaffolds with optimal scaffold morphology. Motivated by the use of Gaussian random fields (GRF) to model cosmological structure formation, we use appropriately ordered and clipped stacks of GRF to model the three-dimensional pore-solid scaffold labyrinths. Image-based metrology, fabrication and mechanical characterization of these scaffolds reveal the possibility of enabling the previously elusive deployment of promising benchside tissue analogs to the clinical bedside.

AB - Tissue engineering integrates the principles of engineering and life sciences toward the design, construction, modification and growth of biological substitutes that restore, maintain, or improve tissue function. The structural integrity and ultimate functionality of such tissue analogs is defined by scaffolds- porous, three-dimensional "trellis-like" structures that, on implantation, provide a viable environment to regenerate damaged tissues. The orthogonal scaffold fabrication methods currently employed can be broadly classified into two categories: (a) conventional, irreproducible, stochastic techniques producing reasonably biomorphic scaffold architecture, and (b) rapidly emerging, repeatable, computer-controlled techniques producing straight edged "contra naturam" scaffold architecture. In this paper, we present the results of the first attempt in an image-based scaffold modeling and optimization strategy that synergistically exploits the orthogonal fabrication techniques to create repeatable, biomorphic scaffolds with optimal scaffold morphology. Motivated by the use of Gaussian random fields (GRF) to model cosmological structure formation, we use appropriately ordered and clipped stacks of GRF to model the three-dimensional pore-solid scaffold labyrinths. Image-based metrology, fabrication and mechanical characterization of these scaffolds reveal the possibility of enabling the previously elusive deployment of promising benchside tissue analogs to the clinical bedside.

UR - http://www.scopus.com/inward/record.url?scp=79551690277&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79551690277&partnerID=8YFLogxK

M3 - Chapter

VL - 9

SP - 544

EP - 552

BT - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

ER -