Spectral Imaging
Principles of Spectroscopy in Biology
The reasons for measuring the spectroscopic properties of biological systems are
many. Native or stained tissue and cells absorb and emit light in such a way as
to leave distinct spectral signatures. Spectroscopy provides us a means to directly
identify and quantify substances by way of this unique fingerprint spectrum, and
can be thought of as a type of "chemical vision". By measuring subtle changes to
the spectral profiles of histological and cytological samples for example, or even
of in vivo tissue through use of fibre-optic probes, one has a means of determining
the onset and nature of neoplasia. Spectroscopic detection can also be used to examine
retinal disease states.
In fluorescence microscopy, fixed or living cells are often labelled with multiple
fluorescent probes, each specific to a particular intracellular component. The challenge
then becomes - how do we separate the various distinct, but often spectrally overlapping,
signals from this battery of fluorescent labels to enable us to build up an accurate,
high-contrast and quantitative representation of the location, concentration and
interactions of the intracellular components under investigation? This is an important
and justifiable challenge, as in the post-genomic era, modern techniques involving
multi-labelling are revolutionising how we directly probe and understand protein
function and key physiological mechanisms of the cell, and associated disease states.
Finally Raman spectroscopy, while being an inherently weak phenomenon, carries the
considerable advantage that Raman bands have very narrow bandwidths compared to
typical fluorescence bands. As such, Raman is ideal for spectral discrimination
of multiple spatially overlapped species, all the more powerful when combined with
deconvolution and multi-variate analysis.
Origins and Principles of Spectral Imaging and HyperSpectral Imaging
The concept of spectral imaging, generating quantitative 2D spatial images over
a third spectral dimension to yield a "data cube", has been originally substantiated
within fields such as airborne surveillance or satellite imaging, in order to generate
spectroscopic data detailing the chemical composition of test areas. Such a configuration
might involve focusing a line of incoming signal into an imaging spectrograph where
the resulting spectrally dispersed light from that line is cast over an area of
the imaging CCD.
The airborne craft, and therefore the attached detection system, is "scanned" over
the surface of the ground with the CCD operating at a sufficiently fast frame rate,
and 3D information is rapidly built up. The data cube can be viewed in two principle
ways:
a) one can derive a spectrum from any spatial point on the image
b) one can generate a series of discrete single wavelength images
When the spectrum is dispersed over many spectral channels (or pixels in the case
of using CCDs), the technique is often called hyper- or multi-spectral imaging.
Development of the spectral imaging approach within areas such as surveillance has
been continuing for over 20 years, and much of the information learned can be carried
over to help solve biological problems.
Representation of overlapped fluorescent protein emission spectra. Typically broad
autofluorescence is shown also.
Within fluorescence microscopy, particularly on living cells, the concept of multi-spectral
imaging is being embraced as a means to collect full and detailed dynamic information
from extensively labelled samples. Quantitative spectral "unmixing" algorithms (of
which a number exist) can be applied to deconvolve the spectra from each image point
into its constituent emitting species and their relative contribution.
Importantly, unmixing can be successfully applied to cases where there is significant
spectral overlapping of multiple dyes. This facilitates use of fluorescent proteins
such as GFP and its most common mutations, CFP, YFP and ds-RED, in techniques such
as co-localization and FRET. FRET, by its very nature, is particularly prone to
significant spectral "cross-talk". For efficient FRET, there needs to be a significant
degree of overlap between the emission spectrum of the donor dye and the absorption
spectrum of the acceptor. This condition is often inextricably accompanied by considerable
overlie of the two emission spectra, as is the case for the common FRET pair GFP/YFP.
It is possible to carry out successful FRET using a combination of narrow band filters,
and split the spectrally distinct images onto either two cameras or adjacent fields
of view within the same camera (up to four fields can be achieved at present). Excitation
of both donor and acceptor species, and subsequent unmixing from as little as two
"filter-based channels" can be executed to minimize effects of cross-talk. This
method has the advantage of affording rapid and simultaneous imaging of two or three
fluorophores. Where we deal with a greater number of fluorophores however, and especially
when they are significantly spectrally overlapped, cross-talk becomes much more
of an issue and we require more spectral channels to effectively separate the signals.
It is conceivable however, that rather that using narrow band filters to separate
signal from closely overlapping fluorophores, we instead perform rapid multi-spectral
imaging and collect the full unfiltered emission spectra, followed by unmixing.
If this configuration can be realised, better signal to noise images are obtained
as we do not have to "throw away" the majority of emitted photons through use of
narrow band filters. Furthermore, through spectral imaging and unmixing, we can
also separate out and remove any autofluorescence from the sample.
However, while the benefits of such an approach to multi-spectral image separation
are substantial, as too are the technical challenges. The ideal spectral imaging
system would have a number of key attributes. It would be capable of rapidly collecting
spectral data for generation of data cubes with maximum speed, facilitating both
throughput and study of dynamic samples. The system would be sufficiently sensitive
in terms of high optical throughput, minimal detector noise and maximum detector
Quantum Efficiency (QE), to yielding a high signal to noise – it has been shown
that efficacy of spectral unmixing is substantially greater under such conditions.
Spectral resolution should be sufficient as to enable effective separation of the
constituent contributing species – the number of spectral channels practically required
is driven by:
a) the number of contributing overlapped species
b) whether or not we can use existing reference emission spectra for unmixing (or
whether we are recording "unknowns").
As mentioned previously above, if the method involves collecting the entire overlapped
spectrum over the wavelength range and therefore avoiding use of narrow band filters
as the detection channels, one does not have to waste photons in achieving the desired
spectral resolution and separation, resulting in higher Signal to Noise (S/N), better
resolution and more accurate quantification.
Stretching Electron Multiplying CCD (EMCCD) Into the Spectral Dimension
EMCCD technology is ideal for incorporation into your ultra-sensitive spectral imaging
set-up. The extraordinary S/N offered is significantly greater than that afforded
by conventional CCD cameras operating at fast readout speeds. Furthermore, since
it is a fast-readout imaging device the EMCCD yields frame rates that are ideally
suited to the likes of dynamic FRET events or recording of faster data cubes.
Underlying all direct imaging studies of living cells, is the desire to preserve
the living subject for as long as possible, through minimization of both phototoxic
cell/tissue damage and also photo-bleaching of the incorporated fluorophores. As
such, the techniques benefit markedly from using EMCCD detection technology, which
not only exhibits the sensitivity and speed to capture, with high S/N, spectrally
resolved image sets from weakly emitting species, but furthermore enables the laser
excitation power to be attenuated. Through minimization of excitation powers, the
rates of dye photo-bleaching and cell phototoxicity are significantly reduced.
The traditional way of spectroscopically resolving wavelengths with CCDs, has been
to use a dispersive element such as a grating, which will cast the wavelength separated
light across one dimension of the array. Indeed, dedicated spectroscopic CCD formats
exist specifically for this usage – these tend to be elongated in shape, typical
pixel formats being 1024 x 128 or 1600 x 200.
In standard spectroscopy readout mode, the light is dispersed along the longer horizontal
dimension giving > 1000 "spectral channels" and the vertical columns are binned
on chip (full vertical binning), creating a larger light collection area and speeding
up the obtainable spectral frame rate.
Spectral Dispersion
Spectral dispersion from a line illumination
Other useful ways of reading out EMCCDs spectroscopically are commonly called upon.
For example, it is possible to make use of an imaging spectrograph that will provide
spatial resolution along the dimension of the entrance slit.
The EMCCD can be read out as a complete image, with spectral resolution along the
horizontal axis and the vertical spatial dimension perpendicular to this.
The sensor can even be read out in multiple horizontal tracks down the array, of
software-configurable size and position, each one giving a separate spectrum, corresponding
for example to the input of an optical fibre from a point in the sample.
Fast Kinetics
Fast kinetics readout
If we need to achieve extraordinarily fast spectral rates, two options are available,
but for each we must be able to ensure that light is dispersed only over a limited
number of rows on the sensor with no light falling onto the remainder of the active
area.
The fastest time resolution is obtained by reading out an imaging EMCCD in "fast
kinetics mode". In this configuration, the spectrum is dispersed over a few rows
at the very top of the sensor.
The "dark rows" beneath are subsequently used for storing the spectra shifted down
from the exposed area, this continuing until the entire sensor is filled – the whole
area is then read out as normal, and the software processes the multiple spectra.
Thus one can achieve time resolution down to the time taken to shift these few rows
down by one step achieving up to 1999 storage rows dependent on EMCCD sensor used.
Cropped Sensor
Cropped sensor mode
If your experiment dictates that you need both fast spectral time resolution but
cannot be constrained by the storage size of the sensor, then it is feasible to
readout the EMCCD in a "cropped sensor" mode.
In this mode, we can "fool" the sensor into thinking it is smaller than it actually
is, and readout continuously at a much faster frame rate! The spectral time resolution
is dictated by the time taken to readout the smaller defined section of the sensor.
Pioneering Spectral Imaging Techniques Involving EMCCDs
A number of novel spectral imaging techniques have been implemented to date that
harness the rapid readout and ultrasensitive characteristics of EMCCDs.
Spectral Confocal Point Scanning
An area that is being addressed is that of next-generation multi-spectral confocal
scanning. A number of commercial systems for multi-spectral confocal point scanning
microscopy exist, but with some considerable drawbacks. Two formats in particular
are worth mentioning. One configuration involves employing a grating to disperse
the confocal signal from each scanned point over a linear array of 32 Photomultiplier
Tubes (PMTs). This suffers primarily from the notably low QE of PMTs (especially
towards the red) and diverse responses of neighbouring channels. Another current
commercial format employs a single PMT for detection, and tilt-scans a grating across
the spectral range during the dwell-time of laser on an image point. It is not hard
to conceive that it takes a considerable time to perform spectral scans on > 250,000
pixels of a 512 x 512 image, and such a configuration is not well suited to spectral
study of dynamic systems, as well as suffering the adverse effects of extensive
sample illumination.
To overcome these performance shortcomings, it is possible to implement EMCCDs system
for multi-spectral confocal scanning. The > 90% quantum efficiency of the back-illuminated
sensor, single photon sensitivity, array architecture and rapid pixel readout speed
is exploited to markedly improve this approach.
The laser dwell-time should be set to coincide with the time to expose and read-out
a short row of approx 32 pixels - sufficient spectral channels to yield effective
unmixing of several known emitting dyes. Faster speeds still can be expected with
fewer spectral channels. There is a clear sensitivity advantage of EMCCD pixels
over the usually employed PMT-technology, which is circa 5-fold in the blue-green
and up to ten-fold in the red.
Line Scan Spectral Imaging
Line scan spectral imaging
It is possible also to perform multi-spectral imaging in microscopy through making
use of modules that contain transmissive dispersion gratings. The optical principle
of dispersion and detection in these systems is somewhat analogous to that described
earlier for airborne monitoring. Such unit is mounted between microscope and EMCCD
and light is collected from an illuminated line in the x-direction across the sample
– line illumination coming either from filtered lamp or laser.
The collected light from the line is dispersed over the area of the EMCCD array,
or even part of the available area for faster frame rates with lower spectral range
or resolution. Thus the pixels across the columns of the EMCCD provide resolution
in λ.
The y-direction is scanned through moving the sample incrementally via a motorized
stage. For every stage step (typically 512), one needs to expose and readout the
area of the array that has been illuminated. The ultra-sensitive performance of
EMCCDs is ideal for this approach, enabling both shorter exposure times and faster
readout performance.
λ Image Stacks Using Tuneable Filters
EMCCD performance can readily be applied to speed up a spectral imaging approach
whereby a liquid crystal tuneable emission filter is employed to sequentially acquire
a λ-stack of images across a spectral range, involving illumination and imaging
of the entire area, wavelength-at-a-time. This technique has traditionally suffered
from speed of acquisition limitations but is boosted by EMCCD sensitivity and readout
speed advantages.
Excitation Spectroscopic Imaging
Excitation spectroscopic imaging can also be carried out, by scanning a tuneable
wavelength excitation source, analyzing the resultant emission intensity. Spectral
unmixing algorithms can be applied just as readily to data acquired in this fashion.
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