An Example
Charles A. DiMarzio
GEU110
Northeastern University
September 2003
Chuck DiMarzio, Northeastern University
10379-5-1
The Design Process
• Remember these
phases are not absolute
• The edges are rough
• We often use multiple
loops
• Usually we don’t think
about the process at all
• It’s best taught by
examples
September 2003
Needs
Assessment
Implementation
11
Analysis
8,9,10
Abstraction
and Synthesis
6,7
Chuck DiMarzio, Northeastern University
Ch. 2
Problem
Formulation
3, 4, 5
10379-5-2
Optical Components of PreImplantation Embryos
• ~105 Mitocondria per cell
Mitochondria
• (0.5µm2X1.5 / 100 µm3 ) x 105 =
4% by volume
~ 1.5 µm x 0.5 µm x
0.5 µm
•Volume of each cell ~100 µm3
Nuclear
Membrane
Cell Membrane ≤ 100 nm
Cell Body
Nc = 1.37
Nucleus ~10 µm
dimension
Nn = 1.39
September 2003
Chuck DiMarzio, Northeastern University
10379-5-3
Taxonomy of 3DFM Microscopy
Techniques
DIC
QTM
RCM
LSCM
TPLSM
Staring
Scanning
3DFM
September 2003
Chuck DiMarzio, Northeastern University
10379-5-4
Three Biological Models
Mouse
Oocytes and
Embryos
Zebrafish
Neural Stem
Cells
Melanoma and
Non-Melanoma
Skin Cancers
5-50mm Cells
1cm Objects
10-100mm Cells
100mm Objects
Existing Work:
QTM, DIC,
Some
Fluorescence
Confocal, A
Little 2-Photon
September 2003
Fluorescence
Confocal
Chuck DiMarzio, Northeastern University
Reflectance
Confocal, Some
Hyperspectral
10379-5-5
The Embryo-Stem Cell Circle
DIC
DIC
Concepts and Graphics
by Carol Warner and
Judy Newmark,
Northeastern.Biology
8-cell
2-cell
Morula
(16-cell)
Zygote

Oocyte
Embryonic Stem (ES)
Cells
Bone
Blastocyst
E:\images\02.10.17\blastocyst1
Neurons
Cardiac muscle
Blood
Skin
September 2003
Other
Chuck DiMarzio, Northeastern University
10379-5-6
α1-tubulin/GFP expressing transgenic zebrafish larva
nose
Olfactory Placodes
left
eye
forebrain
right
eye
M. Beverly & I. Zhdanova, unpublished data transgenic line courtesy of
D. Goldman; U. Mich. in Transgenic Research 10:21-33, 2001.
September 2003
Chuck DiMarzio, Northeastern University
10379-5-7
Thanks to Don O’Malley Northeastern.Biology
Skin Cancer Geometries
Stratum
Corneum,
5-10mm
keratinocytes
(RCM, 2hn)
melanocytes
(RCM)
Epidermis,
50-100mm
Basal cell
cancer
(RCM)
Dermis,
few mm
September 2003
collagen (2hn, SHG, RCM) and
elastin (SHG, RCM)
Chuck DiMarzio, Northeastern University
10379-5-8
Thanks to Milind Rajadhyaksha Northeastern
Some Questions About Embryos
• Where are the
mitochondria?
September 2003
• Multi-Cell: How
many cells in the Inner
Cell Mass?
Chuck DiMarzio, Northeastern University
10379-5-9
Fluorescence Confocal Images
• Plan to Do Full Z, Other Scanning Modes,
and Fuse with Staring Modes
young healthy egg
September 2003
old unhealthy egg
Chuck DiMarzio, Northeastern University
10379-5-10
Thanks to Judy Newmark, Northeastern Biology
Mitochondrial Distributions
Uniformly Distributed
September 2003
Aggregated
Chuck DiMarzio, Northeastern University
10379-5-11
Multi-Cell Embryo
Differential Interference
Contrast
QTM Unwrapped
Phase, Radians
250
8
8
50
200
100
150
150
200
250
100
300
350
400
50
450
100
200
300
400
500
600
0
September 2003
Chuck DiMarzio, Northeastern University
10379-5-12
-8
-8
Confocal Microscopy
Laser
Detector
Polygonal
Mirror
Scanner
Sample
September 2003
Galvo
Scanner
Chuck DiMarzio, Northeastern University
10379-5-13
Mitochondrial Distribution Data
Requirements
• Biology goal is to determine whether
mitochondria are perinuclear, uniformly
distributed, or aggregated.
• Therefore we want to determine either;
– Statistical Properties; Size distribution of
clumps vs. individual mitochondria, (Per 10mm
Voxel), or
– Spatial distribution of mitochondria in an image
to derive the above
September 2003
Chuck DiMarzio, Northeastern University
10379-5-14
Mitochondrial Distribution
Measurement (1)
• Fluorescence Confocal with Mitotracker Green FM
– Proven Technique
– Have 2-D data, may be able to get z stacks
• Reflectance Confocal
– Have two 3-D data sets at 1 mm lateral by 3 mm axial resolution
with images spaced 3 mm apart in the axial direction
– Problems are speckle (average speckle size and mitochondria are
both equal to lateral resolution) and clutter from other organelles
•
QTM
– Probably best detected by examining diffraction
– Need to figure out how to scan (need a model)
September 2003
Chuck DiMarzio, Northeastern University
10379-5-15
Mitochondrial Distribution
Measurement (2)
• 2hn
–
–
–
–
–
Coming when 3DFM is assembled
Use Mitotracker CMXRos at 1156 Excitation
or NADH at 730
Processing same as Fluorescence Confocal
Probably biggest problem will be low SNR (quantum noise)
September 2003
Chuck DiMarzio, Northeastern University
10379-5-16
Cell Counting Data
Requirements
• Biology rationale is that the growth rate of
cells in the inner cell mass (ICM) is an
indication of health of the embryo
• Therefore we want to count the cells in the
inner cell mass, from 1 through 64.
• Note: counting Nuclei is easier
– Boundaries between cells are not well defined
in the inner cell mass and thus harder to detect.
September 2003
Chuck DiMarzio, Northeastern University
10379-5-17
Cell Counting Approaches
• Fluorescence Confocal with Hoechst Dye and UV
Excitation to count the nuclei
– Limited data avalable
• Reflectance Confocal to count nucleii
– May validate Fluorescence, but edges of nucleii are not
sharp
• QTM to actually count the cell bodies
– Data available and we can collect more
• Can do z stacks, but need to know how to scan
– Later can do tomographic imaging
September 2003
Chuck DiMarzio, Northeastern University
10379-5-18
3DFM Layout
September 2003
Chuck DiMarzio, Northeastern University
10379-5-19
Components and Connections
PMT
APD
633
Tungsten
630
636
488/etc
z scan
x-y
Scanner
780
Eyepiece
532
TiSap
Computer
September 2003
Optical Cx
Interface
ill
obj
4x
Grab
QTM
Hg
tube
Safety Sw
Chuck DiMarzio, Northeastern University
Cooled Cam
Rcvr
PMT Set
10379-5-20
3DFM Fabrication Timeline
Ti:Sapphire Laser, 25 Oct
Scanner 8 Nov
Microscope 15 Dec
(Demo Shown Below)
Table, 22 Sept
September 2003
Chuck DiMarzio, Northeastern University
10379-5-21
Status
of
the
Keck
3DFM
rcm
fcm
2hn
dic
qtm
September 2003
Chuck DiMarzio, Northeastern University
10379-5-22
Thanks to Gustavo Herrera, Northeastern ECE
The Team
• Biology
– Warner, Newmark, O’Malley, Rajadhyaksha
• Hardware Engineering
– DiMarzio, Rajadhayksha, Townsend, Katkar, Herrera
• Phantoms
– Rockward, Quarles, Thomas
• Models
– Rappaport, Morgenthaler, Dunn, DiMarzio, Hollman
• Computation
– Kaeli, Meleis
• Signal Processing
– Brooks, Miller, Karl, McKnight, Smith
September 2003
Chuck DiMarzio, Northeastern University
10379-5-23
Who Do We Need?
• Good Engineers
– Electrical
• E/M and Optics
• Controls
• Computers
– Mechanical
• Good Biologists
• Good Bio-Engineers?
September 2003
Bio-Imaging of Embryos
B
i
o
l
o
g
y
Chuck DiMarzio, Northeastern University
I
m
a
g
i
n
g
10379-5-24