Designer ‘blueprint’ for vascular trees: morphology evolution ofvascular tissue constructs

V. Mironov*, J. Zhang*, C. Gentile, K. Brakkea, T. Trusk, K. Jakabb, G. Forgacsb, V. Kasyanov,R. P. Visconti and R. R. Markwald

Bioprinting Research Center, Department of Cell Biology and Anatomy Medical University of South Carolina,

Charleston, SC 29425, USAaMathematics Department, Susquehanna University, Selinsgrove, PA 17870-1164, USA

bDepartment of Physics, Biology and Biomedical Engineering University of Missouri, Columbia, MO 65211, USA

(Received 26 November 2008)

Organ printing is a variant of the biomedical application of rapid prototyping technology

or layer-by-layer additive biofabrication of 3D tissue and organ constructs using self-

assembled tissue spheroids as building blocks. Bioengineering of perfusable intraorgan

branched vascular trees incorporated into 3D tissue constructs is essential for the survival

of bioprinted thick 3D tissues and organs. In order to design the optimal ‘blueprint’ for

digital bioprinting of intraorgan branched vascular trees, the coefficients of tissue

retraction associated with post-printing vascular tissue spheroid fusion and remodelling

must be determined and incorporated into the original CAD. Using living tissue spheroids

assembled into ring-like and tube-like vascular tissue constructs, the coefficient of tissue

retraction has been experimentally evaluated. It has been shown that the internal diameter

of ring-like and the height of tubular-like tissue constructs are significantly reduced

during tissue spheroid fusion. During the tissue fusion process, the individual tissue

spheroids also change their shape from ball-like to a conus-like form. A simple formula

for the calculation of the necessary number of tissue spheroids for biofabrication of ring-

like structures of desirable diameter has been deduced. These data provide sufficient

information to design optimal CAD for bioprinted branched vascular trees of desirable

final geometry and size.

Keywords: organ printing; vascular tree; tissue spheroids; tissue fusion

1. Introduction

Biomedical applications represent new and fast-evolving

frontiers for rapid prototyping technology (Chua et al.

2003, Gibson 2006, Bidanda and Bartolo 2007). Applica-

tions of rapid prototyping or computer-aided additive

biofabrication in tissue engineering opens unique opportu-

nities for robotic computer-aided large-scale industrial

biofabrication of 3D living human tissues and organs

(Sun and Lal 2002, Leong et al. 2003, Mironov et al.,

2003, Hutmacher et al. 2004, Jakab et al. 2004, 2008, Yeong

et al. 2004, Hollister 2005, Tsang and Bhatia 2007, Wang

et al. 2007, Peltola et al. 2008). Organ printing is a variant

of the biomedical application of rapid prototyping technol-

ogy or layer-by-layer additive biofabrication of 3D tissue

and organ constructs using self-assembled tissue spheroids

as building blocks (Mironov et al., 2003, 2007, 2008, Jakab

et al. 2004, 2008). Organ printing technology using self-

assembled tissue spheroids in certain aspects is conceptually

*Corresponding author. Email: mironovv@musc.edu

Virtual and Physical Prototyping, Vol. 00, No. 00, Month 2009, 1�12

Virtual and Physical PrototypingISSN 1745-2759 print/ISSN 1745-2767 online # 2009 Taylor & Francis

http://www.tandf.co.uk/journalsDOI: 10.1080/17452750802657202

very close to the recently proposed novel concept of digital

printing (Hiller and Lipson 2007, 2008). Conventional

freeform fabrication has already been adapted for printing

a variety of sophisticated 3D tissue engineered scaffolds

from synthetic biodegradable polymers with sequential

bioreactor-based cellularisation (two-step biofabrication

process), making them especially suitable for orthopedic

applications (Sun and Lal 2002, Leong et al. 2003,

Hutmacher et al. 2004, Yeong et al. 2004, Hollister 2005,

Peltola et al. 2008). The continuous rapid prototyping

technology based on simultaneous robotic dispensing or

photopolymerisation of stimuli-sensitive biomaterials con-

taining living cells (one-step biofabrication process) was

also recently applied to bioprinting soft tissue such as liver

(Tsang and Bhatia 2007, Wang et al. 2007). However,

continuous (analogue) rapid prototyping technology is

usually limited to a single, homogeneous material such as

hydrogels or hydrogel mixture with specific rheological and

stimuli-sensitive properties ensuring non-destructive bio-

processing of living cells into a 3D living tissue construct

(Tsang and Bhatia 2007, Wang et al. 2007).

Digital printing offers much more flexibility in selection

of materials for bioprinting. Digital (discrete) materials are

fundamentally different from analogue (continuous) mate-

rials (Hiller and Lipson 2007, 2008). Digital materials may

be broken into two main classes. The first class involves

accurate placement of drops of material that harden in

place like droplets jetted from an inkjet system. The second

class of digital materials involves assembling of prefabri-

cated voxels. In this context, a voxel is defined as ‘a physical

bit in digital matter’ (Hiller and Lipson 2007, 2008).

According to the digital printing concept, ‘the physical

voxel’ must passively self-align with its neighbours

while being capable of self-assembly and be easy to make

precisely in large quantities. Tissue spheroids could be

considered as ‘spherical physical voxels’ that are relatively

easy to fabricate at standard size, desirable size and at large

scale (Hiller and Lipson 2007, 2008). The attractiveness of

using tissue spheroids is based on their relatively easy

industrial biofabrication at large scale and potential suit-

ability for both emerging variants of bioprinting technol-

ogy. In analogue bioprinting, tissue spheroids could be

continuously dispensed with hydrogel or ‘punched’ into

sequentially sprayed layers of hydrogel. In digital bioprint-

ing, tissue spheroids could be used as a discrete materials or

‘physical voxels’.

Bioprinting of a branched vascular tree that has desirable

geometry and is suitable for perfusion is an essential step

for maintaining viability of printed 3D thick tissue and

organ constructs. We previously reported that, at least

theoretically, two types of tissue spheroids � solid spheroids

and uni-lumenal vascular tissue spheroids � are sufficient

for fabrication of a complete intraorgan branched vascular

tree (Mironov et al. 2008). Moreover, we have recently

shown that vascular tissue spheroids can be robotically

bioprinted into branched vascular-like tubular tissue con-

structs or branched segments of a vascular tree (Jakab

et al. 2008).

Although modern clinical imaging modalities enable

image acquisition with sufficient level of resolution and

sequential developing CAD of organo-specific vascular

trees in STL files (Smith et al. 2000, Burrowes et al. 2005,

Kaimovitz et al. 2005, Mittal et al. 2005, Nordsletten et al.

2006, Dankelman et al. 2007, Yu et al. 2007), these

‘blueprints’ could not be directly used in unmodified form

for bioprinting of soft organs such as liver and kidney,

because the living tissue constructs assembled from vascular

tissue spheroids undergo significant geometrical reconfi-

gurations due to tissue fusion, compaction and remodel-

ling. Tissue fusion of closely placed living tissue spheroids

driven by surface tension is essential and an essential

technological step as well as a biological and biophysical

foundation of emerging organ printing technology (Mir-

onov et al. 2003, 2007, 2008, Jakab et al. 2004, 2008). Thus,

in order to design the optimal ‘blueprint’ for bioprinting

intraorgan branched vascular trees of desirable final

geometry and sizes, the coefficients of tissue retraction

and compaction must be determined and incorporated into

an original CAD derived from patient-specific clinical

imaging.

In this study the coefficients of tissue retraction during

the tissue fusion process and associated geometrical recon-

figurations of individual tissue spheroids and tissue con-

structs have been experimentally evaluated and compared

with theoretical calculations. Moreover, a formula for

estimation of the optimal number of tissue spheroids for

biofabrication of ring-like and tubular-like segmental

structures of a vascular tree of desirable final diameter

has been deduced. Taken together, these data provide

sufficient information to design in silico the optimal CAD

for bioprinting intraorgan branched vascular trees of

desirable final geometry and size.

2. Materials and methods

2.1 Cell culture

Human aortic smooth muscle cells (AoSMCs) were ob-

tained from Lonza (USA), propagated in supplemented

SMBM-2M medium and used between passages 3 and 10.

Cells are cultured at 378C in 5% CO2 in air and media are

completely replaced every 2 days. StemPro† human adi-

pose-derived stem cells (StemPro† cells) were obtained

from Invitrogen (USA) and propagated using commercial

cell culture media and supplements (Invitrogen) according

to Invitrogen protocols. In some cases Chinese hamster

ovary cells (CHO cells) have been used as described in detail

before (Jakab et al. 2004).

2 V. Mironov

2.2 Labelling of tissue spheroids

In order to visualise possible cell migration from one

tissue spheroid into another, adjacent tissue spheroid during

the tissue fusion process, CellTracker Green CMFDA

(5-chloromethylfluorescein diacetate) and Red CMTPX

(Invitrogen) were used to label spheroids following the

manufacturer’s protocols.

2.3 Fabrication of vascular tissue spheroids

Human AoSMCs and StemPro† cells were propagated to

confluency in 75-cm2 T-flasks. Once confluent, the cells

were rinsed with 5 ml of sterile phosphate-buffered saline

and then incubated in 3 ml of 1� Trypsin for 5 minutes to

create a single cell suspension. Eleven ml of culture medium

containing FBS was then added and the cell suspension was

centrifuged (1100�g, 5 minutes) using an IEC Centra 2

centrifuge (IEC). The resulting cell pellet was then resus-

pended in 1 ml of complete culture medium and the cells

were counted at a 1:1 dilution in Trypan Blue using a

hemacytometer. Vascular tissue spheroids were generated

by culturing 40,000 AoSMCs and StemPro† cells in 25-ml

hanging drops at 378C in 5% CO2 in air. To create hanging

drop cultures, 25-ml drops of culture medium containing

smooth muscle cells were placed onto the inverted lid of a

60-mm Petri dish (Fisher Scientific, Norcross, GA) using a

Figure 1. Biofabricated vascular ring formed from 10

vascular tissue spheroids composed of human vascular

smooth muscle cells. Fifty per cent of spheroids were

fabricated from cells labelled with red vital fluorescent stain

and 50% fabricated from cells labelled with green vital

fluorescent stain. There is no apparent cell mixing during

tissue spheroid fusion.

Figure 2. Sequential steps of morphology evolution and associated geometric change during tissue fusion in a tube-like tissue

construct biofabricated from three layers of tissue spheroids labelled with different colour vital stains. There is no significant

cell mixing. Dramatic reduction in external diameter and height of the tube-like tissue construct is demonstrated (according to

Jakab, K. et al., 2008. Tissue engineering by self-assembly of cells printed into topologically defined structures. Tissue

Engineering Part A, 14 (3), 413�421, with permission).

3Virtual and Physical Prototyping

P200 pipetman. The lids were then placed onto the culture

dish to create hanging drops and the cell mixtures were

cultured for 3 days (378C, 5% CO2) in a humidified

chamber until spheroids had formed.

2.4 Fabrication of vascular tissue constructs

Ten vascular tissue spheroids were placed within a chilled

Collagen type I matrix, generated by mixing 800 ml of

Collagen type I (3.89 mg/ml, BD Biosciences, Bedford,

MA) with 1100 ml of complete medium and 100 ml of

water. The spheroids were placed in order to generate a

ring-like structure. In the case of labelled spheroids, they

were alternately placed in order that each spheroid was in

contact with another one of a different colour. In the case of

assembly of 3D tube-like constructs, three layers of tissue

spheroids were assembled step by step one upon another.

Gelification was performed for 1 hr at 378C, 5% CO2. Then

complete medium was added on top of the collagen gel, and

fusion was followed for 2�3 days. Experiments have been

repeated at least three times for each cell type.

2.5 Microscopy

Conventional fluorescence or differential interference con-

trast images of vascular tissue spheroids were obtained at

22oC using a Leica DMR research-grade microscope

equipped with Leica objectives (5�, 10�, 20�/0.7,

40�/0.85) and a SPOT-RT camera (Vashaw Scientific,

Raleigh, NC, USA). Images were acquired using SPOT-

RT 3.5.7 software, and contrast adjustments were made by

using PhotoShop C3.

2.6 Morphometry

Internal diameter of ring-like structures, external diameter

and height of 3D tube-like structures as well as diameters of

individual tissue spheroids were estimated under light

microscopy using an ocular micrometer and linear mor-

phometry at different stages of tissue construct evolution at

standard magnification. At least three tissue engineered

vascular constructs were used at each time point.

2.7 Computer simulation

Originally developed by one author of the present study (Ken

Brakke), ‘Surface Evolver’ computer software (http://

www.susqu.edu/brakke/evolver/evolver.html) was used to

simulate geometrical changes of individual tissue spheroids

and tube-like tissue constructs associated with the tissue

fusion process. Tube-like tissue constructs from tissue

spheroids of standard size were virtually assembled assuming

Figure 3. Sequential steps of morphology evolution and geometric changes during tissue fusion in a ring-like tissue construct

biofabricated from tissue spheroids generated from cells genetically labelled with green fluorescent protein. Dramatic

reduction of internal ring diameter is demonstrated. Impression of increasing tissue spheroid diameter at late stages is at least

partly a result of cell spreading and migration into the collagen gel (according to Jakab, K., et al., 2004. Engineering biological

structures of prescribed shape using self-assembling multicellular systems. Proceedings of the National Academy of Sciences of

the USA, 101 (9), 2864�2869, with permission).

4 V. Mironov

maximum possible packing density for a regular triangular

lattice (f max�0,9058).

2.8 Statistics

The diameter of cell aggregates (tissue spheroids) and

internal radius of ring-like and tube-like tissue constructs

during fusion were expressed as mean values plus one

standard deviation. At least three tissue constructs were

used for each time point. A total of 15 data points in each

group were analysed. Groups of data were analysed by

single-factor ANOVA. A p value of less than 0.05 was

considered statistically significant. When only two groups

were being compared, data were analysed using Student

t-tests with a p value of less than 0.05 indicating statistical

significance.

3. Results

3.1 1. Morphological and morphometrical analysis of the

printed tissue constructs

In order to investigate potential cell migration during the

tissue fusion process, tissue spheroids were labelled with

vital fluorescent stains. Our data demonstrate the absence

of cell migration from adjacent tissue spheroids in ring-like

(Figure 1) and tube-like (Figure 2) tissue constructs as they

fuse. We also show that there is gradual geometrical

reconfiguration of individual tissue spheroids from the

original sphere-like shape into a conus-like form (Figures

1�4).

Morphometrical analyses have shown dramatic reduction

of internal and external diameters as well as height of tube-

like tissue constructs (Figure 5). The reduction of internal

diameters has also been shown in printed ring-like tissue

constructs (Figure 6). The diameter of tissue spheroids is

relatively stable during the tissue fusion process (Figure 7).

Increasing diameter probably reflects migration of cells

onto the collagen hydrogel rather than geometrical changes

induced by the tissue fusion process (Figures 3 and 7).

3.2 2. Calculation of optimal tissue spheroids numbers

Let’s consider an ideal packing of aggregates (Figure 8a).

The interrelation between the inner radius Ri of a tubular

construct before fusion of aggregates and a radius of the

aggregate r can be found from a condition where the length

of a circle with middle radius Rm�Ri�r is equal a common

length of all aggregates:

2p(Ri�r)�2rn (1)

where Ri�inner radius before fusion, r�radius of the

aggregate and n�number of aggregates.

Figure 4. Sequential steps of morphology evolution and

geometric changes during tissue fusion in a ring-like tissue

construct biofabricated from tissue spheroids composed of

human smooth muscle cells. (a) 0 hour, (b) 12 hours, (c) 24

hours. Dramatic reduction of internal ring diameter is

demonstrated. No changes in diameter of tissue spheroids

were observed.

5Virtual and Physical Prototyping

From here:

Ri�r(n � p)

p(2)

In the first approach, we assume that after fusion of all

aggregates the ideal packing (Figure 8a) becomes a torus

with a thickness 2r (Figure 8b).

The radius of a torus is R�Rf�r, where Rf is the inner

radius of the torus after fusion and r is the radius of

aggregate. It is known that the volume of the torus is

/V�2p2r2R or V �2p2r2(Rf �r):

The volume of one aggregate is v�4=3(pr3) and the

common volume of n aggregates is V�n v. We assume that

the volume of all aggregates before fusion and the volume

of the torus after fusion is equal. In this case:

4n=3(pr3)�2p2r2(Rf �r) (3)

From this equation, the inner radius of the torus after

fusion is:

Rf �r(2n � 3p)

3p(4)

The coefficient of retraction of the inner radius after fusion

is Kr�Ri/Rf, or

Kr�3(n � p)

2n � 3p(5)

There is a nonlinear relationship between this coefficient

and the number of aggregates (Figure 9). This coefficient is

practically constant when the quantity of aggregates is more

than 20.

The quantity of the aggregates that are necessary for

the beginning of their fusion and formation of a tubular

construct with the specified internal radius Rf after fusion

Figure 5. Morphometric analysis of morphology evolution

of a tube-like tissue construct biofabricated from vascular

tissue spheroids composed of CHO cells during the tissue

fusion process. (a) Dramatic reduction in height of the tube-

like tissue construct; (b) dramatic reduction in the outer

diameter of the tube-like tissue construct.

Figure 6. Morphometric analysis of morphology evolution

of a ring-like tissue construct biofabricated from tissue

spheroids consisting of CHO cells during the tissue fusion

process. (a) No significant change in individual tissue

spheroid diameters until late stage; (b) dramatic reduction

in internal diameter of the ring-like tissue construct.

6 V. Mironov

can be found from Equation (4):

n�1:5p(Rf � r)

r(6)

Thus, from this equation it is possible calculate how many

aggregates are needed to generate the tubular construct

with a specified inner radius after fusion.

3.3 3. Computer simulation of tissue fusion

Results of computer simulation using ‘Surface Evolver’

computer software of the evolution of printed tissue

constructs are presented in Figure 10. In agreement with

reported experimental data, computer simulation demon-

strated dramatic reduction of geometric parameters asso-

ciated with the tissue fusion process. Computer simulation

of geometrical changes of individual tissue spheroids during

tissue fusion is presented in Figure 11. In agreement with

reported experimental data, computer simulation demon-

strated a gradual change from the original sphere-like shape

toward a conus-like form.

4. Discussion

The vascularisation of 3D thick tissue constructs is an

unsolved problem in tissue engineering. Effective perfusion

Figure 7. Morphometric analysis of morphology evolution

of a ring-like tissue construct biofabricated from vascular

tissue spheroids consisting of human smooth muscle cells

during the tissue fusion process. (a) No significant change in

individual tissue spheroid diameters; (b) dramatic reduction

in internal diameter of the ring-like tissue construct.

Figure 8. Scheme demonstrating calculation of morphol-

ogy evolution of closely placed tissue spheroids in a ring-

like tissue construct (a) into torus-like tissue constructs (b).

Diameter of tissue spheroids is constant during the tissue

fusion process. Internal diameter of the ring is dramatically

reduced.

7Virtual and Physical Prototyping

employing an intraorgan branched vascular tree is essential

for maintaining viability of thick 3D tissue and organ

constructs. The fast-emerging organ printing technology

employing layer by layer deposition of self-assembled tissue

spheroids offers a unique opportunity to solve the problem

of vascularisation by computer-aided biofabrication of

thick 3D living tissue and organ constructs with a ‘built

in’ intraorgan vascular tree suitable for post-processing

perfusion. Tissue fusion of closely placed tissue spheroids

driven by surface tension forces is a fundamental bioengi-

neering principle enabling biofabrication of 3D tissue

constructs in organ printing technology. Our data demon-

strate that fusion of tissue spheroids occurs relatively

rapidly without significant cell mixing, which strongly

suggests that physical surface tension force rather than

directed cell migration is the main driving force behind

observed and quantified geometrical changes and reconfi-

guration. The fact that both epithelial and smooth muscle

cells used in this study produce practically the same result

supports this conclusion.

As described in this study, geometrical reconfigurations

associated with the tissue fusion process alter the original

diameter and size of bioprinted tissue constructs and

significantly reduce the internal diameter of vascular ring-

like constructs. The experimentally observed geometrical

reconfigurations of individual tissue spheroids in fabricated

tissue constructs associated with the tissue fusion process

resemble the changes predicted by ‘Surface Evolver’software

originally developed by an author of this current study (Ken

Brakke). This software has been broadly used for studying

bubble packing and the evolution of foams. This and other

similar applications can be viewed at http://www.susqu.

edu/brakke/evolver/evolver.html and http://www.susqu.edu/

brakke/. The results of this study are summarised in the

unified scheme illustrating tissue fusion-driven evolution of

Figure 9. Nonlinear relationship between the coefficient of

retraction and number of cell aggregates (tissue spheroids).

Figure 10. Computer simulation (using ‘Surface Evolver’ software) of morphology evolution of a tube-like vascular tissue

construct during tissue fusion. (a, c) External view; (b, d) sectional view. The initial tube-like vascular tissue construct (a, b) is

becoming shorter and more narrow (c, d). The hexagonal pattern of tissue spheroid packing is clearly demonstrated (c).

8 V. Mironov

printed 3D tubular constructs bioassembled from vascular

tissue spheroids (Figure 12).

The fact that differentiated and induced human smooth

muscle progenitors have been used in this study provides

a certain clinical perspective. It indicates the potential

feasibility of using these cells as a potential cell source for

bioprinting intraorgan vascular trees. Human smooth

muscle cells directly differentiated from human fat tissue-

derived progenitors are especially attractive due to their

availability in large number and potential autologous nature.

Thus, designing the ‘blueprint’ for desirable geometry

and size of segments of a vascular tree must incorporate a

retraction coefficient reflecting post-printing geometrical

reconfigurations (Figure 13). It has been experimentally

estimated that the internal diameter of ring-like and tube-

like tissue constructs is reduced 50%. We have generated a

relatively simple geometrical formula that permits estima-

tion of the number of tissue spheroids required for

designing ring-like tissue engineered structures of desirable

final internal diameter. These data provide required and

sufficient information and open an opportunity to design

in silico a ‘blueprint’ or CAD of 3D human organs for

bioprinting.

Recent progress in clinical bioimaging makes it possible

to acquire the gross anatomical characteristics of living

organs, including their intraorgan branched vascular tree,

even while they are still inside patients. The advantage of

this approach, based on using modern clinical bioimaging

modalities such as MRI and micro-CT, lies in its capacity to

demonstrate the patient’s specific anatomical information

(Smith et al. 2000, Burrowes et al. 2005, Kaimovitz et al.

2005, Mittal et al. 2005, Nordsletten et al. 2006, Dankelman

et al. 2007, Yu et al. 2007). However, the resolution of this

technique has not yet reached the desirable histological and

cellular level.

A second approach is based on computer-aided 3D

reconstruction of serial histological sections (Lagerveld

et al. 2007). This method provides a high level of resolution

and information about the size and shape of the organ, as

well as details about its composition and histostructures.

The problem inherent in this method lies in the fact that

human organs are available for this sort of analysis only

after death, and are therefore subject to post-mortem

changes as well as tissue fixation and processing-associated

shrinkage and geometrical distortion. Other limitations

of the histological approach are that it is enormously

Figure 11. Computer simulation (using ‘Surface Evolver’ software) of morphology evolution of individual tissue spheroid

shape changes (a�d) in a tube-like vascular tissue construct during tissue fusion. Tissue spheroid shape gradually changes from

sphere-like to conus-like.

9Virtual and Physical Prototyping

labour-intensive and is basically not patient-specific. How-

ever, considering that organs have a polymeric structure and

consist of repeating structural-functional units, it is possible

to initially reconstruct only one typical structural-func-

tional unit of the organ and then assemble the whole organ

in silico by adding a reconstructed unit based on the gross

anatomical structure or by filling the available space.

A third approach is based on mathematical computa-

tional anatomical modelling. For example, by knowing the

laws of optimal vascular branching (Murray 1926, Kamiya

and Togawa 1972, Zamir 1976), it is possible to reconstruct

Figure 13. Scheme for designing a patient-specific ‘blueprint’’ of a vascular tree. (a) Image acquisition; (b) skeletonisation; (c)

skeletonised model, (c) enlargement of skeletonised model using the coefficient of tissue retraction; (d) ‘blueprint’ model; (e)

final printed segment of vascular tree.

Figure 12. Scheme of biofabrication of a tubular segment of a vascular tree using vascular tissue spheroids. (a) Initial

placement of tissue spheroids just after bioprinting; (b) initial steps of tissue spheroid fusion; (c) advanced steps of tissue

spheroid fusion; (d) fabrication of tubular vascular segment as a result of final tissue fusion.

10 V. Mironov

a very realistic model of a branched vascular tree (Karch

et al. 1999) and then incorporate the model in silico in a

patient-specific organ CAD. Systematic employment of

principle optimality by computer simulation and design of

hypothetical intraorgan branching vascular trees has re-

sulted in surprisingly realistic and natural-like vascular

patterns. In silico placing of such computer-simulated

branched vascular patterns onto organ shapes acquired

using clinical modalities can optimise such models and also

increase the level of patient-specificity. It is logical to

predict that combination and seamless integration of the

three approaches described above will probably provide the

best possible outcome. Some computer-generated anatomi-

cal models of intraorgan vascular trees of the heart, kidney

and liver are presented (Figure 14). Currently available

commercial software permits the creation of a realistic

anatomical model using already existing clinical imaging

modalities. Thus, the development of computer-aided

design of bioprinted organs is feasible, although the exis-

ting software will need to be upgraded to embody greater

capacities and flexibility to incorporate experimentally

estimated coefficients of tissue retraction.

5. Conclusion

Organ printing technology based on using self-assembling

tissue spheroid enables bioprinting of 3D living tissue and

organ constructs with a ‘built in’ intraorgan branched

vascular tree suitable for perfusion to ensure the post-

printing viability of printed tissue constructs. Living

vascular tissue spheroids were assembled into ring-like

and tube-like tissue constructs and coefficients of retraction

were evaluated. We have demonstrated that during the

tissue fusion process, ring-like and tube-like tissue con-

structs fabricated from tissue spheroids reduce their dia-

meter and length. We have further shown, using vital dyes,

that tissue fusion of vascular tissue spheroids occurs

without significant cell mixing, which strongly suggests

that it is driven predominantly by tissue surface tension

forces. The correlation between number of tissue spheroids

and final internal diameter of torus-like tissue constructs

was established. These data permit proper correction of

original CAD acquired from clinical imaging modalities

and, thus, enable bioprinting of ‘built in’ intraorgan

branched vascular trees of desirable final geometry and

size inside 3D thick tissue and organ constructs.

Acknowledgements

Work was funded by NSF FIBR and MUSC Bioprinting

Research Center grants, P20-RR1-16434 from the NCRR

and P20-RR1-6461 from the SC IDeA Network of Biome-

dical Research Excellence. Author thanks Dr. Brooke

Damon for technical help.

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11Virtual and Physical Prototyping

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