U.S. patent application number 11/396035 was filed with the patent office on 2006-11-16 for systems for transiently dynamic flow cytometer analysis.
This patent application is currently assigned to Dako Colorado, Inc.. Invention is credited to Carl E. Ellison, George C. Malachowski, Matthias J. Ottenberg, Paul Barclay Purcell.
Application Number | 20060259253 11/396035 |
Document ID | / |
Family ID | 36102102 |
Filed Date | 2006-11-16 |
United States Patent
Application |
20060259253 |
Kind Code |
A1 |
Ellison; Carl E. ; et
al. |
November 16, 2006 |
Systems for transiently dynamic flow cytometer analysis
Abstract
A flow cytometry apparatus and methods to process information
incident to particles or cells entrained in a sheath fluid stream
allowing assessment, differentiation, assignment, and separation of
such particles or cells even at high rates of speed. A first signal
processor individually or in combination with at least one
additional signal processor for applying compensation
transformation on data from a signal. Compensation transformation
can involve complex operations on data from at least one signal to
compensate for one or numerous operating parameters. Compensated
parameters can be returned to the first signal processor for
provide information upon which to define and differentiate
particles from one another.
Inventors: |
Ellison; Carl E.; (Fort
Collins, CO) ; Purcell; Paul Barclay; (Ouray, CO)
; Malachowski; George C.; (Fort Collins, CO) ;
Ottenberg; Matthias J.; (Fort Collins, CO) |
Correspondence
Address: |
SANTANGELO LAW OFFICES, P.C.
125 SOUTH HOWES, THIRD FLOOR
FORT COLLINS
CO
80521
US
|
Assignee: |
Dako Colorado, Inc.
4850 Innovation Drive
Fort Collins
CO
80525
|
Family ID: |
36102102 |
Appl. No.: |
11/396035 |
Filed: |
March 31, 2006 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10111026 |
Apr 18, 2002 |
7024316 |
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PCT/US00/41372 |
Oct 20, 2000 |
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11396035 |
Mar 31, 2006 |
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60160719 |
Oct 21, 1999 |
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Current U.S.
Class: |
702/50 |
Current CPC
Class: |
G01N 2015/1477 20130101;
G01N 2015/1488 20130101; G01N 15/1459 20130101; G01N 2015/149
20130101 |
Class at
Publication: |
702/050 |
International
Class: |
G01F 17/00 20060101
G01F017/00 |
Claims
1. A method of flow cytometry analysis, comprising the steps of:
establishing a fluid stream; entraining particles in said fluid
stream; sensing a first occurrence incident to at least one
particle; generating a first signal from said first occurrence
incident to said at least one particle; producing data from said
first signal; sensing at least one additional occurrence incident
to said at least one particle; generating at least one additional
signal from said at least one additional occurrence incident to
said at least one particle; producing data from said at least one
additional signal; processing data from said first signal;
processing data from said at least one additional signal; applying
at least one transformation operation to processed data from said
first signal; applying at least one transformation operation to
processed data from said at least one additional signal;
compensating at least one parameter shared by said first occurrence
and said at least one additional occurrence; and differentiating
said first occurrence from said at least one additional occurrence
based upon said at least one compensated parameter.
2. A method of flow cytometry analysis as described in claim 1,
wherein said steps of sensing a first occurrence incident to at
least one particle and sensing at least one additional occurrence
incident to said at least one particle comprise sensing occurrences
incident to a single particle.
3. A method of flow cytometry analysis as described in claim 1,
wherein said steps of sensing a first occurrence incident to at
least one particle and sensing at least one additional occurrence
incident to said at least one particle comprise sensing occurrences
incident to at least two particles.
4. A method of flow cytometry analysis as described in claim 1,
wherein said steps of applying at least one transformation
operation to processed data from said first signal and at least one
transformation operation to processed data from said at least one
additional signal comprises performing complex operations on said
processed data from first signal and on said processed data from
said at least one additional signal.
5. A method of flow cytometry analysis as described in claim 4,
wherein said step of performing complex operations on said
processed data from first signal and on said processed data from
said at least one additional signal comprises performing algebraic
operations.
6. A method of flow cytometry analysis as described in claim 5,
wherein performing algebraic operations comprises: applying a
parameter compensation transformation to said first signal and to
said at least one additional signal; generating a first compensated
signal and at least one additional compensated signal; and
comparing said first compensated signal and said at least one
additional compensated signal.
7. A method of flow cytometry analysis as described in claim 1,
further comprising the step of using a first signal processor and
at least one additional signal processor in said steps of
processing said data from said first signal and processing said
data from said at least one additional signal.
8. A flow cytometer analyzer comprising: a fluid stream; at least
one particle entrained in said fluid stream; a first sensor
responsive to said at least one particle entrained in said fluid
stream; at least one signal generator; data from said at least one
signal generator incident to a first occurrence; data from said at
least one signal generator incident to at least one additional
occurrence; a signal processor of said data from said at least one
signal generator; a transformation operation applied to at least a
portion of said data from said at least one signal generator
incident to said first occurrence; a transformation operation
applied to at least a portion of said data from said at least one
signal generator incident to said at least one additional
occurrence; a compensated parameter shared by said first occurrence
and by said at least one additional occurrence; and a particle
differentiation element configured to differentiate said first
occurrence from said at least one additional occurrence.
9. A flow cytometer analyzer as described in claim 8, wherein said
transformation operation applied to at least a portion of said data
from said at least one signal generator incident to said first
occurrence and to said transformation operation applied to at least
a portion of said data from said at least one signal generator
incident to said at least one additional occurrence comprises a
complex transformation operation.
10. A flow cytometer analyzer as described in claim 9, further
comprising at least one additional signal processor.
11. A flow cytometer analyzer as described in claim 10, wherein
said at least one additional signal processor performs said complex
transformation operation applied to said at least a portion of said
data from said at least one signal generator incident to said first
occurrence and applied to at least a portion of said data from said
at least one signal generator incident to said at least one
additional occurrence.
12. A flow cytometer analyzer as described in claim 11, wherein
said at least one additional signal processor is a digital signal
processor.
13. A method of flow cytometry analysis, comprising the steps of:
establishing a fluid stream; sensing an occurrence incident to said
fluid stream; generating a signal from said occurrence; processing
said signal using a first signal processor; processing said signal
using at least one additional signal processor in parallel with
said first signal processor; utilizing at least a portion of code
by said first signal processor and said at least one additional
signal processor; combining output from said first signal processor
and said at least one additional signal processor; and applying
said combined output to classify said occurrence.
14. A method of flow cytometry analysis as described in claim 13,
wherein said step of processing said signal using at least one
additional signal processor in parallel with said first signal
processor comprises processing at least a portion of said signal
using said first signal processor and said at least one additional
signal processor simultaneously.
15. A method of flow cytometry analysis as described in claim 13,
further comprising the steps of: performing compensation
transformation on said signal; and generating a compensated
signal.
16. A method of flow cytometry analysis as described in claim 15,
wherein said step of performing compensation transformation on said
signal comprises compensating a single parameter.
17. A method of flow cytometry analysis as described in claim 16,
wherein said step of compensating a single parameter comprises
compensating an analog signal.
18. A method of flow cytometry analysis, comprising the steps of:
establishing a fluid stream; sensing serial occurrences incident to
said fluid stream; generating an analog signal corresponding to
said serial occurrences; performing compensation transformation on
said analog signal corresponding to said serial occurrences; and
minimizing variations of said analog signal corresponding to said
serial occurrences, wherein variations are selected from the group
consisting of phase and shape.
19. A method of flow cytometry analysis as described in claim 18,
wherein said step of performing compensation transformation
comprises minimizing shared characteristics.
20. A method of flow cytometry analysis as described in claim 19,
wherein said step of minimizing shared characteristics comprises
reducing spectrum overlap.
Description
[0001] This application is a continuation of U.S. application Ser.
No. 10/111,026 filed Apr. 18, 2002, which was the United States
National Stage of International Application No. PCT/US00/41372
filed Oct. 20, 2000, which claims the benefit of U.S. Provisional
Application 60/160,719, filed Oct. 21, 1999, each hereby
incorporated by reference.
[0002] This application makes reference to a Computer Program
Listing Appendix submitted on two compact discs (which includes one
duplicate copy), having the file name, "computerprogram.doc"
containing 48 KB, all of which is hereby incorporated by reference
herein. The compact discs were created on Mar. 30, 2006.
I. TECHNICAL FIELD
[0003] Specifically, flow cytometry apparatus and methods to
process information incident to particles or cells entrained in a
sheath fluid stream allowing assessment, differentiation,
assignment, and separation of such particles or cells even at high
rates of speed.
II. BACKGROUND
[0004] Flow cytometry is a field which has existed for many years.
Basically, flow cytometer systems act to position small amounts of
a substance within a sheath fluid. Through hydrodynamic focusing
and laminar flow, the substance is split into individual particles,
cells, or the like. In many applications, sheath fluid together
with its entrained substance exits a nozzle in a jet and free falls
or is channeled in an optically transparent pathway for analysis.
The sheath fluid may form droplets encapsulating individual
particles which are separated and collected based upon assignment
of differentiated particle characteristics.
[0005] This type of analysis requires uniform conditions within the
jet, very precise timing, and consistent comparative parameters
incident to the entrained substances to separate such substances
accurately. In addition, there is a coincident commercial and
public sector demand for higher speed flow cytometry, the need to
differentiate substances based on more complex and multiple
parameter analysis, and for higher purity separation(s).
Unfortunately, variation in equipment operation, sheath fluid
stream dynamics, or observed particle characteristics still exists
and are exacerbated by increasing the speed at which entrained
substances are carried in the jet. As such, there is a need to
compensate for such variations to provide for accurate analysis and
separation of the substances entrained in the sheath fluid
stream.
[0006] An overview of some attempts to understand and react to
fluid stream and droplet dynamics can be seen in U.S. Pat. Nos.
4,317,520, 4,318,480, 4,318,481, 4,318,482, 4,318,483, and
4,325,483, each hereby incorporated by reference herein. As these
explain, traditionally the approach has been to assess the signals
and act directly upon such information. Some of the practical
problems which have also been recognized is the fact that only a
limited amount of space and time exists within which to conduct
sensing and analysis. As Japanese Patent 2024535 also recognizes
with respect to the sensing system alone, it may be desirable to
have an optical system which is as small as possible.
[0007] As can be understood, a substantial problem can be that the
data generated from an occurrence must be sensed and reacted upon
in an extremely short period of time. Given the speed of
microprocessors and the like, this might, at first glance, appear
to be readily achievable. The challenge for this unique flow
cytometry situation is that original or raw signal data can be
sub-optimal and even unusable. As such, if it is to be used, it
must be further processed in order to accomplish further analysis
or decision making. This processing can be complex and can require
more processing speed and power than is available not just with
typical commercial systems, but even with today's highest-speed
computer systems. Further, as the desire for higher processing
frequencies is pursued, problems can be compounded. An example of
the extremes to which speed has been taken is shown in U.S. Pat.
No.4,361,400, hereby incorporated by reference herein, where
droplet formation frequencies in the range of 300 to 800 kilohertz
had been achieved. Most practical droplet flow cytometers operate
in the range of 10 to 50 kHz. Although speed of analysis problems
have been known for years, prior to the present invention it has
apparently been an accepted attitude that digital analysis in the
flow cytometry context could not be achieved. This invention proves
this expectation to be untrue. As a result of the present
invention, droplet formation speeds in the 50-100-200 or higher kHz
ranges are now possible with adequate data compensation and the
like.
[0008] At any of these speeds, however, there appears to have been
an expectation that analog analysis was the only practical way to
achieve analysis of and to compensate for fluid dynamics, particle
characteristics, equipment variance, and the like. To some degree,
these expectations have been so prevalent that quality control,
good manufacturing practices, regulatory approval, and other
concerns have been set aside, diminished, or even compromised. The
previously existing technology governing the practices of those in
this field.
[0009] Another significant problem associated with conventional
analysis and compensation of variables in flow cytometry can be the
preservation of original signal data from an occurrence incident to
the fluid stream prior to subsequent processing steps. It may not
have been possible to preserve or store original signal data until
now due to the short amount of time in which to analyze or
compensate the original signal. As such, all or part of the
original or raw signal data may have been sacrificed to increase
the efficiency of analysis or provide feed back compensation
events. The practice of discarding original raw data may prevent
re-analysis of the data to improve quality control, to establish
good manufacturing practices, and attain procedural thresholds for
certain regulatory or statutory requirements.
[0010] Yet another problem with conventional analysis may be the
inability to process high speed serial occurrences, to compensate
multiple parameters, to perform complex operations, to provide
transformation compensation of original data, or to apply
compensated parameters. Conventional analysis can be limited by the
amount of information that can be processed and returned in between
serial events which can occur at a rates of at least 10,000 per
second.
[0011] A first aspect of this inability can be associated with the
nature of conventional signal processors used with flow cytometry.
Conventional flow cytometer signal processors, often because they
are analog, are not capable of dealing with large amounts of signal
information, cannot perform operations on low quality signal
information, cannot practically accomplish complex transformation
operations (such as those which use algebraic expressions or
structure), or they perform only reflexive feed back operations
rather than serial or multi-variant analysis followed by subsequent
parameter compensation.
[0012] A second aspect of this inability can be associated with the
infrastructure of conventional data handling. In part, conventional
infrastructure may not deal with how the streams of information are
allocated, aligned, and coordinated. Conventional processing of
flow cytometer information from occurrences incident to the fluid
stream are traditionally handled as isolated feedback loops. As
such, it can become increasingly difficult to synchronize various
aspects of flow cytometer operation as the number of feed back
loops increases. Moreover, these feed back loops may be completely
uncoupled. For example, stream parameters, such as droplet break
off location, may be completely uncoupled from the differential
analysis of and separation of particles within the fluid stream
being compensated.
[0013] A third aspect of this inability may be lack of symmetry
reduction in the application of transformed data. Again, analog
analysis can prevent or minimize symmetry reduction in the complex
analysis of serial occurrences or parallel multivariant analysis.
The lack of symmetry reduction or the inability to apply symmetry
reduction to analysis terms may increase execution time.
[0014] As mentioned above, there has been a long felt but
unsatisfied need for apparatus and methods which permit complex
signal transformation, and use of compensated parameters resulting
from complex signal transformation, real time analysis using
compensated parameters, or storage of original signal data
generated incident to the fluid stream, instrument variance, or
environmental variance. The present invention addresses each of the
above-mentioned problems with a practical solution. To some extent,
it is apparent that solutions have not been achieved because those
skilled in the art seem to have taken a direction which was away
from the technical direction pursued in the present invention. This
may have been the result of the fact that those skilled in the art
did not truly appreciate the nature of the problem or it may have
been the result of the fact that those skilled in the art were
misled by some of the presumptions and assumptions with respect to
the type of systems which could be considered. The present
invention uses digital signal processing (DSP) technology to
structure information from occurrences incident to flow cytometer
operation, and to perform complex transformation, compensation, or
analysis operations to achieve this long sought goal.
III. DISCLOSURE OF THE INVENTION
[0015] The present invention discloses a flow cytometer having DSP
technology to solve problems associated with high speed serial
occurrences, or multiple parameter analysis of occurrences, or both
individually or in combination. While specific examples are
provided in the context of flow cytometry applications to
illustrate the invention, this is not meant to limit the scope of
the invention to that field or to applications within flow
cytometry. As such, the invention may also have numerous
applications in various fields, for example, detection of defects
in products as disclosed by U.S. Pat. Nos. 4,074,809 and 4,501,366;
field flow fractionation, liquid chromatography, or electrophoresis
as disclosed by U.S. Pat. No. 5,503,994; computer tomography, gamma
cameras, or time of flight instruments as disclosed by U.S. Pat.
No.5,880,457, each of the above-mentioned patents are hereby
incorporated by reference herein. It should be understood that the
basic concepts of the invention may be applied not only to the area
of flow cytometry but may apply to each of the above mentioned
fields, or to other fields where the detection and analysis of
small differences in parameters, such as photo-generated signal
between serial occurrences having high incident light flux, or
serial occurrences generating data concerning multiple parameters,
or occurrences that generate a high number of signals in a short
period of time, may be necessary or desired. Moreover, it should be
understood that the invention can be divided into a number of
embodiments which may be combined in various permutations and
combinations. Naturally, as a result of these several different and
potentially independent aspects of the invention, the objects of
the invention are quite varied.
[0016] One broad object of an embodiment of the invention can be to
convert original signals incident to the environment, the
instrument, or a fluid stream, including but not limited to analog
signals, to digital signals. One aspect of this object of the
invention can be to harmonize a plurality of different types of
signals into a fresh digitized data stream for processing. Another
aspect of this object of the invention be to convert otherwise low
quality or unusable signal data into usable quality signal data. In
this regard, the original signal could be associated with a
characteristic or multiple characteristics of single particle, such
as a cell, within a fluid stream. Alternately, the original signal
could be associated with a characteristic or multiple
characteristics of a series of particles within a fluid stream. As
such, numerous signals may be generated from the sensing of
simultaneous occurrences (parallel occurrences) or the sensing of
discrete occurrences over time (serial occurrences) that represent
one, two, or any number of additional parameters. The rate of
occurrences sensed may vary between about 10,000 occurrences per
second to about 800,000 occurrences per second or more. The
occurrences may be, as examples, the change in fluid dynamics at
the jet or nozzle, the variation in performance of the equipment
itself (such as the change in the baseline electronic signal from a
photomultiplier tube), or the variation in performance of equipment
due to the change in external conditions such as temperature or
pressure. As to each, the occurrence, even when occurring at a high
rate, or occurring for a limited duration, or occurring in a
sub-optimal manner, may be sensed, converted to an original signal,
and digitized.
[0017] Another broad object of an embodiment of the invention can
be to perform compensation transformation on the original signal to
provide compensated parameters. One aspect of this object can be to
apply compensation transformation to processed data from a first
signal incident to a first occurrence and to then apply
compensation transformation to processed data from at least one
additional signal incident to one or more occurrences to compensate
a parameter(s) shared by the first occurrence and by at least one
additional occurrence. A second aspect of this object can be
compensation of parameter(s) that share characteristic(s) so that
"cross talk" can be eliminated or minimized. Elimination or
minimization of cross talk provides an increased ability to
differentiate a first occurrence from a second or more
occurrence(s). Differentiated occurrences may then be assigned to a
class, separated, and collected.
[0018] Another object of an embodiment of the invention is to
provide hardware or software infrastructure to allocate, align, or
coordinate data generated from the above-mentioned original
signals. One aspect of this object can be to provide multiple
signal processors that can operate in parallel to increase the
capacity to process signal data. The instant invention can utilize
at least two but could utilize many parallel signal processors. The
parallel signal processors could be stand aside hardware, or
hardware that can coupled together via ether-net or Internet
connections. A second aspect of this object of the invention can be
to allocate different functions to the various parallel signal
processors so as to optimize processing speed. A third aspect of
this object of the invention can be to use linear assemblers and
register usage to enhance parallel operation of and to coordinate
the specialized functions performed by at least two signal
processors. A fourth aspect of this object can be to provide
software which optimizes the use of parallel processing of digital
code. A fifth aspect of this object of the invention can be to
apply symmetry reduction to serial transformation operations to
reduce processing execution time.
[0019] Another object of an embodiment of the invention can be to
perform complex operations on the above-mentioned original signals.
Complex operations can be operations that were not possible or were
not practical prior to the invention due to the speed at which the
operations have to be performed in serial or in parallel, the
number of parameters involved, the utilization of algebraic
expressions or structure, the use of complex numbers to define
variables, or the like. Each of these aspects can be complex
individually or complex in combination.
[0020] Another object of an embodiment of the invention can be to
save the original signal in a memory element or memory storage
element. One aspect of this object can be to save the original
signal without altering the original quality or quantity of the
original signal. This may be necessary or desirable for quality
control concerns or to meet regulatory or statutory requirements.
Another aspect of this object can be to duplicate the original
signal for analysis during flow cytometer operation or to duplicate
the signal for future re-analysis.
[0021] Another object of an embodiment of the invention can be to
provide software to implement the various applications on DSP
technology. A first aspect of this object can be to provide
exemplary compensation transformation operations. This may include
compensation transformation for two-way compensation, three-way
compensation, and so on for higher order compensation sets. A
second aspect of this object can be to provide exemplary
compensation matrices and their various properties. A third aspect
of this object can be to provide exemplary symmetry reduction in
various aspects of the software notation. A fourth aspect can be to
provide an exemplary program for the subtraction of pairs or groups
of fluorescent signals in order to orthogonalize the color
sensitivity of each signal.
[0022] Yet another object of an embodiment of the invention can be
to provide analog to digital converter compensation of amplified
photomultiplier tube (PMT) outputs. Since emission spectra of
fluorescent antibody labels are broadband, they can overlap the
passbands of up to eight photomultiplier filters. Therefore, a
digitized PMT output from even one antibody label can contain the
effects of as many as eight antibody labels. See Shapiro,
"Practical Flow Cytometry", pp. 17-19, 163-166 (1995), hereby
incorporated by reference herein. This feature allows color
sensitivity to be orthogonalized for each signal, and specifically
allows for the application in the context of a flow cytometer such
as those sold under the trademark MOFLO.RTM..
[0023] Yet another object of an embodiment of the invention can be
to provide the ability to latch numerous parameters either
simultaneously or interchangeably, and to specifically latch any of
the maximum of sixty-four MOFLO.RTM. flow cytometers parameters as
inputs.
[0024] Another object of an embodiment of the invention can be to
provide cross beam time alignment in order to perform enhanced
compensation between a pair of parameters. One aspect of this
object can be to reduce the apparent inter-beam transition time to
not more than 1 part in 3000 or to a compensated beam to beam "time
jitter" of not more than one nanosecond, which appears to be beyond
the practical capability of analog circuit design.
[0025] Another object of an embodiment of the invention can be to
provide digital error compensation. Digital subtraction is
attractive because it avoids the problems of signal alignment,
however, major digitalization errors can occur. For example, when
bright signals are compensated over a large dynamic range digitized
errors, which can be visually discemable as a picket-fence
coarseness of the compensated population, can occur. Digital error
compensation can minimize these errors and hence improve the
quality of the digital information.
[0026] Another object of an embodiment of the invention can be to
provide log amplifier idealization. Typically log amplifiers vary
from ideal logarithmic behavior throughout their entire range. For
example, some log amplifiers have a 0.4 db variance. That is, for
any given input, the ratio of the output signal from a practical
log amplifier over the value expected of a perfect logarithmic
function is expressed in db as: Error=0.4 db=20 log 10(Vout/Videal)
Log amplifier idealization can provide values which more closely
approximate the ideal amplifier.
[0027] Another object of an embodiment of the invention can be to
provide off-loaded binning. The characteristics of, for example,
populations of particles can be stored in the memory of an
additional signal processor using binning transformations. The
statistical characterization of these populations, such as mean,
standard deviation, skewness and separation can be sent to a
separate processor, thus off-loading this task and hence increasing
the performance of the first processor and the separate
processor.
[0028] Naturally, further independent objects of the invention are
disclosed throughout other areas of the specification.
IV. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] FIG. 1 shows a schematic cross sectional view of a flow
cytometer embodiment of the invention showing the various features
combined.
[0030] FIG. 2 shows hardware schematic of an embodiment of the
invention.
V. MODE(S) FOR CARRYING OUT THE INVENTION
[0031] Specifically, an enhanced flow cytometer utilizing DSP
technology and methods to process raw or original signal
information incident to various parameters during operation,
including, but not limited to, environmental parameters, instrument
parameters, or parameters incident to the particles or cells
entrained in a sheath fluid stream allowing for complex assessment,
differentiation, assignment, and separation of such particles or
cells, even when the flow cytometer is operated at high speed.
Generally, a data acquisition, data transformation, parameter
compensation, and compensated parameter utilization system for the
differentiation, assignment, and separation of multiple parallel or
serial events that can be useful in numerous fields and
applications.
[0032] In discussing these aspects of the invention some references
may be made to MOFLO.RTM. (a trademark of Cytomation, Inc.) flow
cytometer systems and SUMMIT.RTM. (also a trademark of Cytomation,
Inc.) capabilities for such systems. Each of these systems
represent state-of-the-art flow cytometry capabilities which are
not only the fastest practical flow cytometer systems, but they
also are well known to those of ordinary skill in the art.
[0033] Referring now to FIG. 1, a preferred embodiment of the
invention can be seen in detail. A flow cytometer (1) having a
fluid stream source (2) can establish a fluid stream into which
particles (3) can be suspended. The source of particles (4) can
insert the particles from time to time such that at least one
particle becomes suspended in and is hydrodynamically focused in
the stream. An oscillator (5) responsive to the fluid stream
perturbs the fluid stream. A jet or fluid stream (6) comprised of
the fluid stream (2) and the particles (3) can then be established
below the tip of the nozzle (7) of the flow cytometer. The stream
can be established in a steady state condition such that droplets
(8) that encapsulate a single particle form and break away from the
contiguous part of the stream. When the stream is established in
this steady state fashion, a stable droplet break-off point can be
established. Below the droplet break-off point (9) a free fall zone
(10) can exist. This free fall zone embodies the area where the
droplets move once they break away from the contiguous part of the
stream. A sensor (12), such as a laser and receiver in combination
(or separately), can be used to monitor the stream for a particle.
The sensor can sense an occurrence and generates a signal (15). For
example, a coherent beam of light aimed at the fluid stream by the
sensor (12) intercepts a particle (3) in the stream (6) and
fluorescence or scattered light rays can then be emitted. The
emitted fluorescence can be captured by the receiver, such as a
photomultiplier tube, to generate the signal (15). Based upon
analysis of the signal generated by the sensor from the fluorescent
occurrence, the particle(s) may be differentiated, and assigned to
a class. A droplet charging location (11) can exist at a point
along the free fall zone. Based upon the assignment of the
particle, the droplet can be charged positively, negatively, or
left uncharged.
[0034] As the charged droplets fall in the free fall zone, they can
pass through an electrostatic field (20). If the droplets have been
charged with a positive or negative charge, an electric field
established between these electrostatic plates can deflect the
charged droplets such that the trajectory of the deflected droplets
(13) and the trajectory of the neutral droplets serves to separate
one type of particle class from another. These separated particles
can then be collected into a container(s) (14). Furthermore,
alternative techniques such as utilizing different quantities of
charge can be used to accomplish the assignment and separation of
numerous classes of particles. The rate of separating the classes
of particles or the sort rate can be at least 1000 per second.
[0035] The sensor (12) can be used to monitor or sense, and then
assist in or generate a signal (15) incident to a variety of
parameters (16) related to the operation of a flow cytometer or
numerous other instruments (used individually or in combination).
As described above, the raw or original signal(s) could be
associated with a characteristic or multiple characteristics of a
single particle (3), which could be a cell, entrained in the fluid
stream (2). Alternately, the original signal could be associated
with a characteristic or multiple characteristics of a series of
particles (3) or cells within the fluid stream (2). As further
mentioned above, numerous signals may be generated from the sensing
of simultaneous occurrences (parallel occurrences) or the sensing
of discrete occurrences over time (serial occurrences) that
represent one, two, or any number of additional parameters (at
least 64 parameters in the MOFLO.RTM. flow cytometer). The rate of
occurrences sensed may vary between few per second or could be
between about 10,000 occurrences per second to about 800,000
occurrences per second, or even higher. The original signal may
also represent, as examples, the change in fluid dynamics at the
jet or nozzle, the variation in performance of the equipment itself
(such as the change in the baseline electronic signal from a
photomultiplier tube), or the variation in performance of equipment
due to the change in external conditions such as temperature or
pressure. Specifically, as shown in FIG. I the parameters could be
a variety of aspects incident to the fluorescent emission of
fluorenyl isothiocyanate (FITC) upon excitation and include pulse
width, forward scatter, side scatter, raw FITC information, raw PE
(raw phycoerythrin), raw PE-CY5 (raw phycoerythrin CY5), and so
forth. Naturally, numerous other parameters could be also be
monitored and these specific examples are meant to be used as a
guide rather than an inclusive list.
[0036] The MOFLO.RTM., flow cytometer system, for example, monitors
some conventional twelve bit parameters containing pulse width,
analog to digital converter (ADC) channel outputs, timer outputs,
Look Up Table (LUT) outputs, and the Classifier output. MOFLO.RTM.,
flow cytometer system users can have need or desire to compute
additional parameters which include compensating ADC outputs for
the unwanted side effects of broadband fluorescence, computing
ratios of ADC channel, and calculating whether ADC parameters fall
inside, or outside 3D or higher dimensional regions, and the like.
To expand the capability of instruments such as the MOFLO.RTM. flow
cytometer system, other types of flow cytometer systems, or other
types of instruments, the invention employs at least one additional
signal processor (17) to apply compensation operations to the
processed data from a first signal and to the processed data from a
second or more signals. This may occur in parallel or simultaneous
with the data processing of a first signal processor (18). The
compensated output from the additional signal processor for at
least one parameter shared by the signals (or the occurrences which
generated the signals) allows enhanced differentiation between the
first signal and the second signal based for the compensated
parameter(s). The compensated data can then be combined into the
data handling functions of the first signal processor, for example,
and applied to classify and separate the occurrences.
[0037] Pass Through Transformation and Return. Again referring to
FIG. 1, and as mentioned above, the data emerging from the flow
cytometer may exploit at least one additional signal processor,
that can for example, be a parallel digital signal processor (17)
which may be used simultaneously with a first signal processor. The
original raw data or a portion of the original raw data from each
signal generated by the flow cytometer can be assembled as a table
of 32 or more 16 bit data words. The first 16 data words could be
the raw data outputs from an occurrence, such as fluorescent
emissions from excited fluorochromes used as surface or internal
markers. The first 16 data words may be passed through the
additional signal processor and the transformed output may be then
presented on the second (or more) 16 data words. The final
compensated parameters are returned to the first signal processor,
combined with the output of the first signal processor, and then
presented or displayed. This is often referred to as a pass-through
and return digital signal path.
[0038] Naturally, the numeric data formats for a particular
application may have to be matched. For example the raw 12 bit
MOFLO.RTM. flow cytometer data can be thought of as a unsigned
fixed point integers, in the format 12.0, that is 12 integer bits
to the left of the fixed point, and 0 fractional bits to the right
of the fixed point. This yields a range of 0.times.000 (0) to
0.times.FFF (4095). The compensated parameter output from the
second signal processor (17) may need to be in the same format. The
internal data manipulations can be changed as required, to perform
the required algorithms. Possible internal data formats that could
be used are 2's complement, signed integer, signed or unsigned
fractional fixed point numbers, or floating point decimal, as
examples. Various CPLD/FPGA (Complex Programmable Logic
Devices/Field Programmable Gate Arrays) or digital signal
processing Von Neuman or Harvard program, data, and I/O
architectures may be used as required to perform algorithms. The
algorithm and parameter coefficients for the compensated parameters
may be changed during instrument operation. If desired, for example
in the MOFLO.RTM. flow cytometer system, it should be able to be
downloaded at operation time from the system's first computer, for
example, through the MFIO Rev B Control Word Bus, using the same
programming convention.
[0039] The additional signal processor(s) used in parallel can
provide compensated parameters sufficiently fast that the data from
numerous signals, channels, or parameters can have compensation
transformation performed simultaneously. The speed of operation on
the first group of 16 data words can occur before the second group
of 16 data words becomes available. Each data word can pass through
the additional signal processor at a rate of at least every 150
nanoseconds. Consequently, the additional signal processor can
perform all operations to which it has been assigned for 16 data
words within a maximum period of about 2410 nanoseconds.
[0040] As such, compensation transformation operations on the data
from a signal(s) can provide compensated parameters to
differentiate occurrences during flow cytometer operation. For such
real time operation of a flow cytometer or other instrument, the
additional signal processor(s) can perform compensation
transformation operations for selected parameters even when the
occurrences which are being differentiated have a rate of at least
10,000 per second or up to 800,000 occurrences per second.
Naturally, the additional signal processor(s) could apply
compensation transformation operations to occurrences having lower
rates as well.
[0041] The compensated parameters generated by the additional
signal processor(s) are then returned to the first signal
processor. As such, the first signal processor can handle data for
different tasks than the additional signal processors. In one
embodiment of the invention, the first signal processor can perform
the task of data management and display while the additional signal
processors are performing, among other others, compensation
transformation functions on the original signals. Thus, the
separation of the tasks of data management and display and
parameter compensation transformation may be an essential
requirement to achieve accurate and reliable function.
[0042] As but one example of using the invention, with or without
additional signal processor(s), compensation transformation,
including complex operations, can be performed on the emission
spectra of fluorescent antibody labels which overlaps the passbands
of eight PMT filters. The compensation transformation operations
can take the following form, and while this may be a preferred
arrangement, a great variety of alternative embodiments are
possible.
Two-Way Compensation
Two linear signals from 0 to 1000 mV converted to a log signal in
such a fashion that the log and linear voltages are related:
V.sup.1.sub.log=A.log(V.sup.1.sub.lin/V.sub.th) (1)
V.sup.2.sub.log=A.log(V.sup.2.sub.lin/V.sub.th) (2) where
A=10000/log(10000/V.sub.th) V/.sub.th is normally 1 millivolt. This
formula ensures that an input from 1 millivolt to 10000 millivolts
will produce a log signal from 0 to 10000 millivolts with 2.5 volts
per decade. A compensated parameter is a parameter with cross-talk
subtracted out between two parameters. This is given by:
V.sup.1c.sub.lin=V.sup.1.sub.lin(1-C.sub.12)
V.sup.2.sub.lin/V.sup.1.sub.lin (3)
V.sup.2c.sub.lin=V.sup.2.sub.lin(1-C.sub.21)
V.sup.1.sub.lin/V.sup.2.sub.lin (4) In order to recover the
V.sup.1.sub.lin and V.sup.2.sub.lin from the log values, the
inverse functions of (1) and (2) may be evaluated:
V.sup.1.sub.lin=V.sub.th exp(V.sup.1.sub.log/A) (5)
V.sup.2.sub.lin=V.sub.th exp(V.sup.2.sub.log/A) (6) These linear
values may be then applied to (3) and (4) above and converted to
log by reapplication of (1) and (2). In practice, this calculation
will be performed on digital values whose linear range is 0 to 4095
(post digitization) and where the threshold value is 4095./10000.0.
Three-Way Compensation Mathematically this is the same process
except that the formulae for the compensation set is:
V.sup.1c.sub.lin=V.sup.1.sub.lin(1-C.sub.12)
V.sup.2.sub.lin/V.sup.1.sub.lin(1-C.sub.13)
V.sup.3.sub.lin/V.sup.1.sub.lin (7)
V.sup.2c.sub.lin=V.sup.2.sub.lin(1-C.sub.21)
V.sup.1.sub.lin/V.sup.2.sub.lin(1-C.sub.23)
V.sup.3.sub.lin/V.sup.2.sub.lin (8)
V.sup.3c.sub.lin=V.sup.3.sub.lin(1-C.sub.31)
V.sup.1.sub.lin/V.sup.3.sub.lin(1-C.sub.32)
V.sup.2.sub.lin/V.sup.3.sub.lin (9) and so on for higher order
compensation sets. The lookup tables could be used for N-color
compensation in the following way. Following this note on the
transformation it is clear that N-color compensation can be
deconstructed to N-1 2D lookups. For example, the 3-color
compensated output when followed through from anti-log and back to
log may look like this:
V.sup.1c.sub.log=V.sup.1.sub.log-exp(V.sup.2.sub.log-V.sup.1.sub.log)log(-
1-c.sub.12)-exp(V.sup.3.sub.log-V.sup.1.sub.log)log(1-c.sub.13)
Taking the first two terms together and the last term of this
expression it is equivalent to: V.sup.1c.sub.log=LUT(V.sup.1log,
V.sup.2.sub.log)-LUT(V.sup.1.sub.log, V.sup.3.sub.log) Applying the
Transformation The following notation convention is used to
describe an "eight by eight" compensation matrix: [0043] p.sub.nc
where n=0 to 7 are the compensated outputs [0044] p.sub.n are the
input log signals where n=0 to 7 [0045] c.sub.jk are the
compensation coefficients=-A*log(1-C.sub.jk) where C.sub.jk are the
fractional compensation values ranging from -0.999 to 0.999 [0046]
e(p.sub.n-p.sub.m)=exp((p.sub.n-p.sub.m)/A) [0047] A=4095.0/log
(10000)=444.6 The compensation matrix may be as follows:
p.sub.0c=p.sub.0-c.sub.01e(p.sub.1-p.sub.0)-c.sub.02e(p.sub.2-p.sub.0)-c.-
sub.03e(p.sub.3-p.sub.0)-c.sub.04e(p.sub.4-p.sub.0)-c.sub.06e(p.sub.6-p.su-
b.0)-c.sub.07e(p.sub.7-p.sub.0) (10)
p.sub.1c=-c.sub.10e(p.sub.0-p.sub.1)+p.sub.1-c.sub.12e(p.sub.2-p.sub.1)-c-
.sub.13e(p.sub.3-p.sub.1)-c.sub.14e(p.sub.4-p.sub.1)-c.sub.15e(p.sub.5-p.s-
ub.1)-c.sub.16e(p.sub.6-p.sub.1)-c.sub.17e(p.sub.7-p.sub.1) (11)
p.sub.2c=-c.sub.20e(p.sub.0-p.sub.2)-c.sub.21e(p.sub.1-p.sub.2)+
[0048]
p.sub.2-c.sub.23e(p.sub.3-p.sub.2)-c.sub.24e(p.sub.4-p.sub.2-c.sub-
.25e(p.sub.5-p.sub.2)-c.sub.26e(p.sub.6-p.sub.2)-c.sub.27e(p.sub.7-p.sub.2-
) (12) p.sub.3c=-c.sub.30e(p.sub.0-p.sub.3)-c.sub.31e
(p.sub.1-p.sub.3)-c.sub.32e(p.sub.2-p.sub.3)+p.sub.3c.sub.34e(p.sub.4-p.s-
ub.3)-c.sub.35e(p.sub.5-p.sub.3)-c.sub.36e(p.sub.6-p.sub.3)-c.sub.37e(p.su-
b.7-p.sub.3) (13) p.sub.4c=-c.sub.40e(p.sub.0-p.sub.4)-c.sub.41e
(p.sub.1-p.sub.4)-c.sub.42e(p.sub.2-p.sub.4)-c.sub.43e(p.sub.3-p.sub.4)+p-
.sub.4-c.sub.45e(p.sub.5-p.sub.4)-c.sub.46e(p.sub.6-p.sub.4)-c.sub.47e(p.s-
ub.7-p.sub.4) (14) p.sub.5c=-c.sub.50e(p.sub.0-p.sub.5)-c.sub.51e
(p.sub.1-p.sub.5)-c.sub.52e(p.sub.2-p.sub.5)-c.sub.53e(p.sub.3-p.sub.5)-c-
.sub.54e(p.sub.4-p.sub.5)+p.sub.5-c.sub.56e(p.sub.6-p.sub.5)-c.sub.57e(p.s-
ub.7-p.sub.5) (15) p.sub.6c=-c.sub.60e(p.sub.0-p.sub.6)-c.sub.61e
(p.sub.1-p.sub.6)-c.sub.62e(p.sub.2-p.sub.6)c.sub.63e(p.sub.3-p.sub.6)-c.-
sub.64e(p.sub.4-p.sub.6)-c.sub.65e(p.sub.5-p.sub.6)+p.sub.6-c.sub.67e(p.su-
b.7-p.sub.6) (16) p.sub.7c=-c.sub.70e(p.sub.0-p.sub.7)-c.sub.71e
(p.sub.1-p.sub.7)-c.sub.72e(p.sub.2-p.sub.7)-c.sub.73e(p.sub.3-p.sub.7)-c-
.sub.74e(p.sub.4-p.sub.7)-c.sub.75e(p.sub.5-p.sub.7)-c.sub.76e(p.sub.5-p.s-
ub.7)+p.sub.7 (17) Note that the c.sub.jk are positive or negative
and the parameters from which the others are subtracted are along
the diagonal of the matrix. Properties
[0049] There is symmetry around the diagonal in that the
e(p.sub.j-p.sub.k) terms one side of the diagonal are the inverse
of those on the other. However this is not a useful symmetry since
division is a time consuming operation on an integer arithmetic DSP
device.
[0050] The functions e(p.sub.j-p.sub.k) may range from exp(-4095/A)
to exp(4095/A) since p.sub.n may be always positive and in the
range 0 to 4095. This is a range from 1/10000 to 10000 which is an
eight decade range. In order to do fast integer arithmetic,
preferably the calculation of e(p.sub.j-p.sub.k) should be done
with a 16 bit map to preserve memory space, but the values in the
lower ranges less than 1.0 are badly represented. This means that
calculation accuracy cannot be maintained across all mapped values
of e(p.sub.k-p.sub.k).
[0051] It may be necessary to have two maps, one for positive and
the other for negative arguments of e( ) in order to maintain
accuracy.
[0052] Given these constraints, we can calculate the number of
operations which may be needed to resolve this matrix.
TABLE-US-00001 Operations Speed (clocks) Clocks Pointer Loads 4 4
16 (2 maps, p.sub.n pointer, c.sub.jk pointer Sum Initialization 8
1 8 Loads of p.sub.n 8 4 32 Subtracted Pairs 28 1 28 Mappings 56 4
224 Loads of c.sub.jk 56 4 224 Multiplies 56 2 112 Subtractions 56
1 56 Stores 8 1 8 Total 280 708
The 6201 DSP runs at a clock cycle of 5 ns. Thus, this calculation
for non-optimized execution is 5*708=3540 ns. The MOFLO.RTM. flow
cytometer system parameter bus runs at 150 ns per frame word, thus
the number of MOFLO.RTM. flow cytometer system data words is:
3540/150=23.6
[0053] The last compensation parameter is in slot 10. The output
needs to be ready at data word 16. The calculation matrix cannot be
done as each MOFLO.RTM. flow cytometer system parameter comes
across because the off-diagonal elements e(p.sub.j-p.sub.k) may be
mixtures of all parameters. The pipelining and parallel
architecture of the DSP can allow substantial reduction of this
calculation time.
[0054] Symmetry reductions can be made on this set in order to
reduce execution time. The equations above can be multiplied by
e(p.sub.n) and the diagonal terms moved to the left side
(p.sub.0c-p.sub.0)e(p.sub.o)=0-c.sub.01e(p.sub.1)-c.sub.02e(p.sub.2)-c.su-
b.03e(p.sub.3)-c.sub.04e(p.sub.4)-c.sub.05e(p.sub.5)-c.sub.06e(p.sub.6)-c.-
sub.07e(p.sub.7)
(p.sub.1c-p.sub.1)e(p.sub.1)=-c.sub.10e(p.sub.0)+0-c.sub.12e(p.sub.2)-c.s-
ub.13e(p.sub.3)-c.sub.14e(p.sub.4)-c.sub.15e(p.sub.5)-c.sub.16e(p.sub.6)-c-
.sub.17e(p.sub.7)
(p.sub.2c-p.sub.2)e(p.sub.2)=-c.sub.20e(p.sub.0)-c.sub.21e(p.sub.1)+0-c.s-
ub.23e(p.sub.3)-c.sub.24e(p.sub.4)-c.sub.25e(p.sub.5)-c.sub.26e(p.sub.6)-c-
.sub.27e(p.sub.7)
(p.sub.3c-p.sub.3)e(p.sub.3)=-c.sub.30e(p.sub.0)-c.sub.31e(p.sub.1)-c.sub-
.32e(p.sub.2)+0-c.sub.34e(p.sub.4)-c.sub.35e(p.sub.5)-c.sub.36e(p.sub.6)-c-
.sub.37e(p.sub.7)
(p.sub.4c-p.sub.4)e(p.sub.4)=-c.sub.40e(p.sub.0)-c.sub.41e(p.sub.1)-c.sub-
.42e(p.sub.2)-c.sub.43e(p.sub.3)+0-c.sub.45e(p.sub.5)-c.sub.46e(p.sub.6)-c-
.sub.47e(p.sub.7)
(p.sub.5c-p.sub.5)e(p.sub.5)=-c.sub.50e(p.sub.0)-c.sub.51e(p.sub.1)-c.sub-
.52e(p.sub.2)-c.sub.53e(p.sub.3)-c.sub.54e(p.sub.4)+0-c.sub.56e(p.sub.6)-c-
.sub.57e(p.sub.7)
(p.sub.6c-p.sub.6)e(p.sub.6)=-c.sub.60e(p.sub.0)-c.sub.61e(p.sub.1)-c.sub-
.62e(p.sub.2)-c.sub.63e(p.sub.3)-c.sub.64e(p.sub.4)-c.sub.65e(p.sub.5)+0-c-
.sub.67e(p.sub.7)
(p.sub.7c-p.sub.7)e(p.sub.7)=-c.sub.70e(p.sub.0)-c.sub.71e(p.sub.1)-c.sub-
.72e(p.sub.2)-c.sub.73e(p.sub.3)-c.sub.74e(p.sub.4)-c.sub.75e(p.sub.5)-c.s-
ub.76e(p.sub.6)+0 TABLE-US-00002 Operation Speed (clocks) Clocks
Pointer loads 4 2 8 Sum initialization 8 1 8 Loads of pn 8 4 32
Mappings 8 4 32 Loads of c.sub.jk 32 4 128 Multiplies 64 2 128
Subtractions 64 1 64 Post NORM 8 1 8 Post SHL 8 1 8 Pointer loads 2
2 4 Post loads 8 4 32 Post remap 8 4 32 Post multiples 8 2 16 Post
SHIFT ADD 8 1 8 Post SHR 8 1 8 Post adds 8 1 8 Stores 8 1 8 Total
532
[0055] The execution time for this matrix is 2660 ns which is
MOFLO.RTM. flow cytometer system frame words=2660/150=17.7
MOFLO.RTM. flow cytometer system data words.
[0056] Using the linear assembler and optimization of register
usage to enhanced parallel operation can yield the parallel code
set out in the Computer Program Listing Appendix. In the Computer
Program Listing Appendix, the parallel bars are operations
performed in one clock. The total number of clocks, ignoring the
stack saving before and after which are imbedded to test the code
from a C routine counts to 106 clocks or 540 ns. This gives the
total MOFLO.RTM. flow cytometer system data words as 540/150 (150
is the time between MOFLO.RTM. flow cytometer system data
words)=3.5 MOFLO.RTM. flow cytometer system data words.
[0057] This program, and the above-described example is not meant
to limit the invention to specific hardware, software, algorithms,
applications, or arrangements, but is provided as a guide in making
and using the invention which may take the form of various
embodiments. Particular embodiments of the invention, in the flow
cytometry context or otherwise, can be as follows.
[0058] In certain applications, occurrences can be separated in
time. Occurrences separated in time can be, in the flow cytometer
context, for example, different original or raw signals generated
for the same particle as it moves through the various flow
cytometer processes which as above-described involve entrainment
into a fluid stream, excitation of bound fluorochrome, assignment
to a class, and separation of particles to the assigned classes.
Occurrences separated in time can also involve a particle labeled
with several different fluorochromes with each type of fluorochrome
excited at different points in time. Again occurrences separated in
time, could be a series of discrete occurrences each monitored for
the same parameter, such as a fluorescent emission from a series of
labeled cells, or it could be a single occurrence monitored at
discrete periods in time, such as the characteristics of a
fluorescent emission as it decays. Of course, numerous other
examples could be provided which have occurrences separated in
time. The spatial separation of these occurrences leads to original
signal output which is separated in time. The use of additional
signal processor(s) using pass through, compensation
transformation, and return can remove this temporal separation. In
some cases this will enable certain application which were
heretofore not possible, such as the use of multiple separate
lasers to excite multiple fluorochromes over time, in other cases
it will allow the original signals to have compensation
transformation applied and more accurate differentiations made
between occurrences even during operation of the instrument.
Operations such as this which have a low tolerance for "time
jitter" often cannot be performed using an analog arrangement
because of the difficulty of removing the temporal separation with
analog circuitry.
[0059] In certain applications "cross talk" between the same or
different parameters can occur. Compensation transformation on the
original or raw signals can remove "cross-talk" between the same or
different parameters which are incident to the same or different
occurrences. As described above, the "cross talk" between different
types of fluorochrome emission was compensated. Compensation
transformation may allow the raw original fluorescent signals, or
numerous other types of signals, to be compensated so that the
resulting compensated parameter has the cross-talk accurately
removed and blank reference signals correctly positioned. This may
be particularly relevant to other types of applications such as the
detection of defects in products as disclosed by U.S. Pat. Nos.
4,074,809 and 4,501,366; field flow fractionation, liquid
chromatography, or electrophoresis as disclosed by U.S. Pat. No.
5,503,994; computer tomography, gamma cameras, or time of flight
instruments as disclosed by U.S. Pat. No. 5,880,457; or flow
cytometry as disclosed by U.S. Pat. No. 5,135,759 with respect to
bright fluorescent values, each hereby incorporated by reference
herein. This type of compensation transformation can be performed
on numerous channels simultaneously, at least 8 channels in the
above-described example, and provides orthogonalized data which can
be returned to the first signal processor.
[0060] Certain applications require multiple color compensation.
Compensation transformation for multiple color compensation can
take the format presented above and allow for at least 8 color
compensation embodied by a 64 element matrix of operations. The
transformation can operate on linear or logarithmic format data.
Naturally, as explained higher order set can be used providing for
N-color compensation.
[0061] Certain applications require analysis of parameter kinetics
or ratios. Ratios between two signals over time can be an important
measurement in the study of cell kinetics. The original signals can
be compensated such that the ratio can be used to provide a measure
of absolute differences between the signals. For example, calcium
release can be an important measurement for the study of cell
kinetics. A ratio of two fluorescent emission signals can be
required to provide a measure of calcium release. These fluorescent
emission signals can have compensation transformation applied to
provide compensated fluorescent emission signals for comparison in
the appropriate time frame required to maintain accuracy. Multiple
ratios can also be performed. Time can also be a parameter
essential for kinetic measurements and can be supplied by the
on-board clock. The on-board clock can have a time range from
microseconds to years allowing full flexibility in time-stamping
data streams.
[0062] Certain applications require differentiation of and tracking
of sub-populations. Flow cytometers depend on the stability of
various parameters, including, but not limited to, environmental
parameters, instrument parameters, occurrence parameters to analyze
and define the mean and width of particle populations.
Unfortunately, these parameters can be in continuous dynamic
instability. Stability can be controlled by compensation
transformation of the original signals from these various
parameters. Alternately, compensation transformation can track the
drift in these parameters. Compensation transformation of original
signal information can allow for the selection of parameters to
resolve or differentiate sub-population, to select the level of
resolution to be maintained between individuals of sub-populations,
to select the thresholds for assignment and separation of
individuals from sub-populations, to allow for continuous
differentiation and assignment of individuals from sub-populations
to various classes, to track sub-populations as parameters drift,
to assess the purity of pools of separated individuals without
re-analysis, among other applications.
[0063] In this regard, two dimensional, three dimensional, or
higher dimensional populations of particles can be differentiated
and assigned to various sub-populations and multi-dimension regions
can be used to separate the sub-populations when using the
invention. This provides a powerful and direct method of
multi-dimensional sub-population separation that has been
previously unavailable on flow cytometers, and on other types of
instruments, and in other fields of application.
[0064] Another aspect, of sub-population identification involves
closely overlapping sub-populations can be enumerated by
dynamically characterizing the overlap using compensation
transformations that may be designed to detect the proportion of
overlaps. The exact proportions, mean, width and separation of
multi-featured sub-populations can also be characterized with the
invention. Extensive populations of particles with small
sub-populations of interest can be focused upon and held in dynamic
amplification or focus through transformation compensation of
amplification parameters such that the sub-populations of interest
can be defined, located, analyzed, and separated. Without
transformation compensation, such accurate delineation may not be
possible.
[0065] In applications using flow cytometry, particles with various
population(s)/sub-populations of interest can be screened and
regions of interest can be created which delineate these
populations. These regions can be automatically assigned to the
sorting electronics of a flow cytometer so that real-time physical
separation of the particles of interest can be sorted. This
automation process can be important when flow cytometry is used to
separate high volumes of certain types of cells for culturing,
transfecting, insemination, biochemical recombination, protein
expression, or the like.
[0066] Populations of particles can be stored in the memory of the
addition signal processor(s) using binning transformations. The
statistical characterization of these populations, such as mean,
standard deviation, skewness and separation can be returned to the
first signal processor, that can be a workstation for display,
storage, or retrieval of data. Thus off-loading this task to the
additional signal processor can increase the performance of the
workstation.
[0067] The method described above and detailed in the Computer
Program Listing Appendix can preserve the raw signal data in a
memory storage element. Cost considerations often exclude this
feature on an analog systems. Saving raw or original signal data
also conforms to Good Manufacturing Practice in that the original
signal data can be retrieved if the transformed data has been
incorrectly manipulated. By saving the original signal data and
duplicating original signal data for further processing, elements
of the original raw signal data that may be lost by digital
`roofing` or `flooring` can be maintained. This can allow original
signal retrieval and data backtracking for FDA requirements and for
signal re-analysis.
[0068] Now referring to FIG. 2, a preferred embodiment of the
hardware with respect to an application of the invention with the
MOFLO.RTM. flow cytometer is shown. As can be understood, the
additional signal processor (17) can be located internal to or
external to the core of the instrument. A minimum data memory size
of 56 kilowords of 12 bits or wider may be required for each
compensation transformation operation (based on the example above).
A minimum I/O memory space of TBD kilowords may also be required.
Various CPLD/FPGA or digital signal processing Von Neuman and
Harvard program, data, and I/O architectures, or the like, may be
used to perform compensation transformation algorithms, such as
those specified above.
[0069] Additional processors (17) serve to increase the parallelism
of the operations, thus allowing transformations at hitherto
unachievable speeds. This increased power allows operations that
are algebraic as well as approximately transcendental.
Transcendental operations can be considered those requiring an
infinite number of steps. However extremely high processing rates
can provide approximations to the infinite that are practicable and
indistinguishable from an exact computation.
[0070] As can be easily understood from the foregoing, the basic
concepts of the present invention may be embodied in a variety of
ways. It involves both signal processing techniques as well as
devices to accomplish the appropriate signal processing. In this
application, the processing techniques are disclosed as part of the
results shown to be achieved by the various devices described and
as steps which are inherent to utilization. They are simply the
natural result of utilizing the devices as intended and described.
In addition, while some devices are disclosed, it should be
understood that these not only accomplish certain methods but also
can be varied in a number of ways. Importantly, as to all of the
foregoing, all of these facets should be understood to be
encompassed by this disclosure.
[0071] The discussion included in this application is intended to
serve as a basic description. The reader should be aware that the
specific discussion may not explicitly describe all embodiments
possible; many alternatives are implicit. It also may not fully
explain the generic nature of the invention and may not explicitly
show how each feature or element can actually be representative of
a broader function or of a great variety of alternative or
equivalent elements. Again, these are implicitly included in this
disclosure. Where the invention is described in
functionally-oriented terminology, each aspect of the function is
accomplished by a device, subroutine, or program. Apparatus claims
may not only be included for the devices described, but also method
or process claims may be included to address the functions the
invention and each element performs. Neither the description nor
the terminology is intended to limit the scope of the claims which
now be included.
[0072] Further, each of the various elements of the invention and
claims may also be achieved in a variety of manners. This
disclosure should be understood to encompass each such variation,
be it a variation of an embodiment of any apparatus embodiment, a
method or process embodiment, or even merely a variation of any
element of these. Particularly, it should be understood that as the
disclosure relates to elements of the invention, the words for each
element may be expressed by equivalent apparatus terms or method
terms--even if only the function or result is the same. Such
equivalent, broader, or even more generic terms should be
considered to be encompassed in the description of each element or
action. Such terms can be substituted where desired to make
explicit the implicitly broad coverage to which this invention is
entitled. As but one example, it should be understood that all
actions may be expressed as a means for taking that action or as an
element which causes that action. Similarly, each physical element
disclosed should be understood to encompass a disclosure of the
action which that physical element facilitates. Regarding this last
aspect, as but one example, the disclosure of a "processor" should
be understood to encompass disclosure of the act of
"processing"--whether explicitly discussed or not--and, conversely,
were there only disclosure of the act of "processing", such a
disclosure should be understood to encompass disclosure of a
"processor" and even a means for "processing". Such changes and
alternative terms are to be understood to be explicitly included in
the description.
[0073] Additionally, the various combinations and permutations of
all elements or applications can be created and presented. All can
be done to optimize the design or performance in a specific
application.
[0074] Any patents, publications, or other references mentioned in
this application for patent are hereby incorporated by reference.
Specifically, U.S. Patent Application No. 60/160,719 is hereby
incorporated by reference herein including any figures or
attachments.
[0075] In addition, as to each term used it should be understood
that unless its utilization in this application is inconsistent
with such interpretation, common dictionary definitions should be
understood as incorporated for each term and all definitions,
alternative terms, and synonyms such as contained in the Random
House Webster's Unabridged Dictionary, second edition are hereby
incorporated by reference. However, as to each of the above, to the
extent that such information or statements incorporated by
reference might be considered inconsistent with the patenting of
this/these invention(s) such statements are expressly not to be
considered as made by the applicant(s).
[0076] In addition, unless the context requires otherwise, it
should be understood that the term "comprise" or variations such as
"comprises" or "comprising", are intended to imply the inclusion of
a stated element or step or group of elements or steps but not the
exclusion of any other element or step or group of elements or
steps. Such terms should be interpreted in their most expansive
form so as to afford the applicant the broadest coverage legally
permissible in countries such as Australia and the like.
[0077] Thus, the applicant(s) should be understood to have support
to claim at least: i) each of the processing devices or subroutines
as herein disclosed and described, ii) the related methods
disclosed and described, iii) similar, equivalent, and even
implicit variations of each of these devices and methods, iv) those
alternative designs which accomplish each of the functions shown as
are disclosed and described, v) those alternative designs and
methods which accomplish each of the functions shown as are
implicit to accomplish that which is disclosed and described, vi)
each feature, component, and step shown as separate and independent
inventions, vii) the applications enhanced by the various systems
or components disclosed, viii) the resulting products produced by
such systems or components, ix) methods and apparatuses
substantially as described hereinbefore and with reference to any
of the accompanying examples, x) the various combinations and
permutations of each of the elements disclosed, xi) processes
performed with the aid of or on a computer as described throughout
the above discussion, xii) a programmable apparatus as described
throughout the above discussion, xiii) a digitally readable memory
encoded with data to direct a processor comprising means or
elements which function as described throughout the above
discussion, xiv) a computer configured as herein disclosed and
described, xv) individual or combined subroutines and programs as
herein disclosed and described, xvi) the related methods disclosed
and described, xvii) similar, equivalent, and even implicit
variations of each of these systems and methods, xviii) those
alternative designs which accomplish each of the functions shown as
are disclosed and described, xix) those alternative designs and
methods which accomplish each of the functions shown as are
implicit to accomplish that which is disclosed and described, xx)
each programmable feature, component, and step shown as separate
and independent inventions, and xxi) the various combinations and
permutations of each of the above.
* * * * *