Optical Projection Tomography (OPT) - Biomedicum Imaging Unit ...

Optical Projection Tomography 

(OPT) 

Jim Swoger 

Sharpe Lab 

Systems Biology Programme 

Centre for Genomic Regulation (CRG) 

Barcelona, Spain 

03/12/2008

Outline 

� Motivation 

� OPT: How It Works 

� Depth of Focus Issues 

� Image Processing 

� Resolution 

� Applications, Fixed: - transmission / fluorescence 

- disease studies 

- mouse limb development 

� Applications, Live: - plant 

- mouse eye 

- mouse limb development 

� Conclusions

Motivation

10 �m 

100 �m 1mm 1cm 10 cm 

CONFOCAL MRI 

CELLS TISSUES 

Motivation 

? 

OPT 

ORGANS, 

EMBRYOS 

ORGANISMS 

SPIM, ultramicroscopy, serial sectioning … 

Multi-photon, OCT, SHG, structured illum… X-ray CT, ultrasound, …

- E.g. DIC does not relate directly 

to physical properties of sample 

- “depth info” isn’t real 

Motivation 

QUALITATIVE vs. QUANTITATIVE imaging 

- E.g. fluorescence OPT: brightness corresponds 

to dye concentration 

- Distances/positions can be measured in 3D 

projections 

slices

SIMPLE 

Motivation 

Modeling vertebrate limb development 

36 hours 

PATTERNING 

MORPHOGENESIS 

DIFFERENTIATION 

MECHANICS 

COMPLEX

OPT: How It Works

OPT: How it Works 

Projection tomography - an X-ray CT scanner 

source 

detector 

Scan Reconstruction 

(back-projection)


Transmission: Fluorescence: wide-field illum. 

“back-projection” 

3D RECONSTRUCTION



3D RECONSTRUCTION


Same done for 

every section 


3D RECONSTRUCTION



3D RECONSTRUCTION

Depth of Focus Issues

Depth of Focus Issues 

numerical aperture: NA = n sin� 

depth of focus: �z ~ NA -2 

lateral resolution: �r ~ NA -1 

high low NA 

�r 

�r 

�z �z 

Decrease NA: 

� �r Depth of Focus (good) 

� �z Lateral Resolution 

(bad) 

� 

�


numerical aperture: NA = n sin� 

depth of focus: �z ~ NA -2 

lateral resolution: �r ~ NA -1 

Reconstruction: 

Decrease NA: 

� �r Depth of Focus (good) 

� �z Lateral Resolution 

(bad) 

3D resolution limited by �r 

sample size limited by �z


High NA Low NA 

projections of reconstructions

Image Processing

Pre-Reconstruction Processing 

Image Processing for 3D Reconstructions - Details 

1) Correction for photo-bleaching during scanning 

2) Determination of rotation axis position & orientation 

3) Combination of anti-parallel projections 

4) Filtered back-projection 

? 

0° 

180° 

+ � �

Reconstruction Algorithms 

“Simple” Back-Projection 

1. Distribute each projection back 

thru sample space, 

with the appropriate orientation 

2. Sum these back-projections


z 

“Simple” Back-Projection – Real Data 

r 

P(r,z,�)


z = z o 

z 

“Simple” Back-Projection – Real Data 

r 

� 

P(r,z,�) r P(r,�,z=zo ) x I(x,y,z=zo ) 

y


The Fourier Transform: 

The Fourier Projection/Slice Relationship: 

A projection in physical space transforms to a slice in Fourier space.


Physical Space: Projections Fourier Space: Slices 

y 

Low-density sampling of high frequencies 

x 

v 

High-density sampling of low frequencies 

Reconstruction emphasizes low frequencies � low resolution! 

u


Filtered Back-projection 

z = z o 

z 

r 

� 

P(r,z,�) r P(r,�,z=zo ) x I(x,y,z=zo ) 

Back-projection 

y

Resolution & Sample Characteristics

Resolution: Optical Clearing of Samples 

uncleared transmission cleared, enhanced contrast 

- optically, clearing is good.

Resolution Example: Mouse Embryo 

3.7 mm 

reconstructed OPT 

Mouse embryo 

Dehydrated, cleared in BABB 

Neurofilament: Alexa 488

Resolution Example: Mouse Embryo 

3.7 mm 

reconstructed OPT reconstructed OPT, cropped & zoomed 

~ 12 µm isotropic resolution 

1.0 mm

Resolution Example: Single-Cell Imaging 

Fauver et al, Opt. Express 13, pp. 4210-4223 (2005) 

sub-micron resolution 

- Isolated lung fibroblast nucleus 

- hematoxylin staining, 

(transmission) 

- thick section of 3D 

reconstruction 

- pseudo-colour visualization

Resolution Example: Live Mouse Tissue 

400 µm 

Reconstructions of fluorescence (implanted beads) 

& transmission of an embryonic mouse limb 

2 

fluorescence transmission overlay 

1 

3 4 

6 

5 

max-projections 

slices

Resolution Example: Live Mouse Tissue 

bead 1 

bead 3 

Bead # Volume [µm^3] bead Mean 2Radius 

[µm] Mean Intensity [a.u.] Max Intensity [a.u.] 

1 3957 9.81 0.684 34.89 

2 44579 22.00 0.643 8.3 

3 

4 

1469 

2246 

7.05 

8.12 

normalized 1.532 

1.614 

225.89 

153.02 

5 2279 8.16 1.921 275.26 

6 1862 7.63 2.529 304.73 

anisotropic, context-dependent resolution

Applications: Fixed Sample Imaging

Transmission: Whole-mount In Situ 

raw OPT projection reconstructed slices 

OPT scan of Sox9 expression (RNA in-situ hybridisation) 

E11.5, WT mouse

Transmission: Whole-mount In Situ 

OPT vs. serial sectioning 

raw OPT 

projection 

Science 296 pp. 541-545 (2002) 

serial section reconstructed 

OPT section 

reconstructed OPT section 

serial section

Fluorescence: Mouse Embryo 

E10.5 mouse embryo 

Multi-Channel Fluorescence OPT 

Raw Projections Reconstruction 

Red: autofluorescence 

Blue: HNF3�, Alexa 488 

Green: neurofilament, Cy3 

antibody labelling

Fluorescence: Mouse Embryo 

E10.5 mouse embryo 

Multi-Channel Fluorescence OPT 

Raw Projections Reconstruction 

3D Rendering

Arabidopsis Silque, heart-stage embryos 

520 µm 

Reconstructions from autofluorescence (TXR channel) OPT scans 

Lee et al, The Plant Cell, 18, pp. 2145-2156 (2006)

Mouse Models of Diabetes 

Adult mouse pancreas 

White – autofluor. 

(GFP filter set) 

Red – Islets of Langerhans 

(TxR filter set) 

Nature Methods 4 pp. 31-33 (2007)

Mouse Models of Diabetes 

Normal 

Diabetic 

Nature Methods 4 pp. 31-33 (2007)

Mouse Models of Immune Response 

Lymph nodes: important part of the immune system 

lymphocytes introduced to antigens 

can become inflamed during infection 

mouse peripheral lymph node, 

whole-mount staining 

White – autofluor. 

Green – B-cell follicles, Alexa 488 

conjugated anti-B220 

www.tki.unibe.ch/stein.htm

Gene Expression Patterning in Mouse 

Limb Development 

Newman & Frisch (1979) 

mid E12 

late E12 

early E13 

Digit patterning during mammalian limb development 

Cleared in BABB 

Whole-mount in situ for 

Sox9 expression

Resolution: Optical Clearing of Samples 

uncleared transmission cleared, enhanced contrast

Applications: Live Sample Imaging

Live OPT: Arabidopsis Development 

4 hours 

100 µm 

9 

24 

49 

Reconstructions from transmission OPT scans 

Lee et al, The Plant Cell, 18, pp. 2145-2156 (2006) 

72 

High magnification slices, @ 30 hours

The Bioptonics OPT System 

More OPT info: U.K. Medical Research Council: 

www.bioptonics.com

Live Mammalian OPT: Hardware 

Live OPT machine: 

- Built inside a climate-controlled chamber 

- All alignment & sample manipulation (x, y, z, roll, pitch, yaw) controls 

are external

Live Mammalian OPT: Hardware 

XY translation stage 

magnet 

concave surface 

oil

Live OPT: Mouse Lens Induction 

Mouse embryo, E9.5 

Pax6-GFP in ectoderm, prospective retina, forebrain 

Raw OPT projections 

Prospective retina bulges inward due to growth of lens 

Reconstructed slice, t = 0 

t = +6 hours

Applications: Mouse Limb Development

Goals 

Quantitative modeling of mammalian organ development 

Specifically, can we understand the processes that turn Ainto 

B 

i.e. Mouse limb development (E10.75 � E12.25) 

A B 

36 hours 

To construct a 4D finite-element model 

we require quantitative data on: 

1) gene expression patterning 2) morphology 3) local tissue motion

Quantifying Gene Expression & 

Morphology 

Dynamic gene expression patterns in 4D?... 

Boot et al, Nat. Methods, 5, pp. 609-612 (2008)


Morphology 

t 0 (E11.5) 

Scleraxis-GFP transgenic mouse line 

Ronen Schweitzer 

Oregon, USA 

Dynamic gene expression patterns in 4D?... 



Morphology 

t 0 (E11.5) 

Scleraxis-GFP transgenic mouse line 

Ronen Schweitzer 

Oregon, USA 

t 0 + 19 hours 

Dynamic gene expression patterns in 4D?... . 



Morphology 

E16.5 mouse embryo: scans through OPT reconstructions 

transmission fluorescence overlay

Tracking Ectodermal Motion 

Can only track shape changes 

Cannot track tissue movements 

Require Landmarks 

the model we want to make 

the data we have (morphology)


Fluorescent beads attached to limb surface 

Boot et al, Nat. Methods, 5, pp. 609-612 (2008) 

raw OPT projections 

1 time-point; multiple views


Fluorescent beads attached to limb surface 



time-series; single view


OPT reconstructions 

vectors connecting time-points 



time-series; single view


OPT reconstructions 

vectors connecting time-points 


Overlay multiple experiments


Analyze: “vortices” are apparent 

Interpolate for uniform coverage: 

Green: “original” bead vectors 

Red: Interpolated 


Overlay multiple experiments

Tracking Volumetric Growth 

Tamoxifen-inducible Cre-Lox EYFP stochastic clonal labelling 

Arques et al, Development, 134, pp. 3713-3722 (2007)

Tracking Volumetric Growth 

reconstuction, 1st clone tracking 

time-point reconstuction, time-series

Quantitative Modeling 

Mesh for a Finite Element model 

of a limb bud 

Color encodes proliferation rate 

(blue high; red low) 

For the model we need: 

Gene Expression: what genes are 

expressed in what regions 

Morphology: the limb shape 

Tissue Motion: node movements 

between iterations 

Q: Given morphologies at t 1 & t 2 , what tissue motions are consistent with this? 

Q: Can proliferation rates alone account for measured morphology?

Conclusions

Acknowledgements 

Sharpe Lab 

Jean-François Colas – limb bud culturing 

Laura Quintana – fixed OPT 

Sahdia Raja – Sox9 imaging, proliferation data 

Henrik Westerberg – visualization, post-processing 

Bernd Böhm – finite element modelling 

Centre for Genomic Regulation, Barcelona, Spain 

Marit Boot – limb development 

Human Genetics Unit, Medical Research Council 

Edinburgh, U.K. 

Miguel Torres & Juan José Sanz – live OPT development 

CNB, CSIC, Madrid, Spain – Cre-Lox EYFP mouse 

Ronen Schweitzer – Scx-GFP mice 

Shriners Hospital for Children, Portland, U.S.A. 

Ulf Ahlgren – pancreatic collaborations 

Umeå U., Sweden 

Jens Stein – lymphatic collaborations 

U. Bern, Switzerland

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