U.S. patent application number 17/521062 was filed with the patent office on 2022-02-24 for device, system and method for determining a fibrinogen level in a blood sample.
The applicant listed for this patent is KONINKLIJKE PHILIPS N.V.. Invention is credited to Bart Jacob Bakker, Rene van den Ham, Hendrik Jan van Ooijen.
Application Number | 20220057414 17/521062 |
Document ID | / |
Family ID | 1000005958248 |
Filed Date | 2022-02-24 |
United States Patent
Application |
20220057414 |
Kind Code |
A1 |
van Ooijen; Hendrik Jan ; et
al. |
February 24, 2022 |
DEVICE, SYSTEM AND METHOD FOR DETERMINING A FIBRINOGEN LEVEL IN A
BLOOD SAMPLE
Abstract
The present invention relates to device for determining a
fibrinogen level in a sample comprising, a first input for
obtaining an attenuance signal over time indicative of a fibrin
polymerization of said sample, a second input for obtaining a
reactant concentration signal over time indicative of a reactant
concentration in said sample, wherein the reactant is any substance
leading to the cleavage of fibrinogen to fibrin, a simulation unit
running a model using the reactant concentration signal as an input
to provide a simulated attenuance signal over time, and an
evaluation unit configured to infer the fibrinogen level of said
sample by comparing the attenuance signal over time with the
simulated attenuance signal over time.
Inventors: |
van Ooijen; Hendrik Jan;
(Eindhoven, NL) ; Bakker; Bart Jacob; (Eindhoven,
NL) ; van den Ham; Rene; (Utrecht, NL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
KONINKLIJKE PHILIPS N.V. |
EINDHOVEN |
|
NL |
|
|
Family ID: |
1000005958248 |
Appl. No.: |
17/521062 |
Filed: |
November 8, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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15535784 |
Jun 14, 2017 |
11169161 |
|
|
PCT/EP2015/080379 |
Dec 17, 2015 |
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17521062 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 33/86 20130101;
G01N 2333/75 20130101 |
International
Class: |
G01N 33/86 20060101
G01N033/86 |
Foreign Application Data
Date |
Code |
Application Number |
Dec 18, 2014 |
EP |
14198867.5 |
Claims
1. Device for determining a fibrinogen level in a sample
comprising: a first input for obtaining an attenuance signal over
time indicative of a fibrin polymerization of said sample; a second
input for obtaining a reactant concentration signal over time
indicative of a reactant concentration in said sample, wherein the
reactant is any substance leading to the cleavage of fibrinogen to
fibrin; a simulation unit running a model using the reactant
concentration signal as an input to provide a simulated attenuance
signal over time; and an evaluation unit configured to infer the
fibrinogen level of said sample by comparing the attenuance signal
over time with the simulated attenuance signal over time.
2. Device according to claim 1, wherein the simulation unit is
configured to provide to the evaluation unit multiple simulated
attenuance signals over time for a range of fibrinogen levels.
3. Device according to claim 1, wherein the evaluation unit is
configured to extract one or more characteristic features from the
attenuance signal and further one or more characteristic features
from the simulated attenuance signal, wherein the evaluation unit
is further configured to match the one or more characteristic
features with the further one or more characteristic features.
4. Device according to claim 3, wherein at least one of the one or
more characteristic features and at least one of the further one or
more characteristic features is defined by the difference between
an initial attenuance and a final attenuance of the attenuance
signal.
5. Device according to claim 1, wherein the simulation unit is
configured to rerun the model at least one more time with a
parameter provided by the evaluation unit, such that an error
between the attenuance signal and the simulated attenuance signal
is minimized.
6. Device according to claim 1, wherein the simulation unit is
configured to run the model which uses at least one ordinary
differential equation indicative of a chemical reaction of fibrin
polymerization.
7. Device according to claim 6, wherein a state variable of said at
least one ordinary differential equation is the reactant
concentration signal.
8. Device according to claim 1, wherein the simulation unit is
configured to run the model which uses a set of coupled ordinary
differential equations, each being indicative of a chemical
reaction involved in fibrin polymerization, and said set is being
solved by the simulation unit numerically.
9. Device according to claim 1, wherein the simulation unit is
configured to run the model which uses at least a first algorithm
to determine concentrations of proteins and protein complexes over
time, a second algorithm to determine the average mass/length ratio
of fibrin molecules from said concentrations, and a third algorithm
to determine the attenuance of the sample from said mass/length
ratio.
10. Device according to claim 1, wherein the reactant concentration
signal over time is interpolated from a time-discrete signal to a
continuous signal using a reactant specific interpolation
formula.
11. System for determining a fibrinogen level in a sample
comprising: a measuring unit for providing an attenuance signal
over time indicative of a fibrin polymerization of said sample; and
a device according to claim 1.
12. System according to claim 11 further comprising: a further
measuring unit for providing an actual measurement of a reactant
concentration of said sample.
13. System according to claim 11, wherein the measuring unit and
said further measuring unit are configured to produce measurements
of said sample in parallel.
14. Method for determining a fibrinogen level in a sample
comprising: obtaining an attenuance signal over time indicative of
a fibrin polymerization of said sample; obtaining a reactant
concentration signal over time indicative of a reactant
concentration in said sample, wherein the reactant is any substance
leading to the cleavage of fibrinogen to fibrin; running a model
using the reactant concentration signal as an input to provide a
simulated attenuance signal over time; and inferring the fibrinogen
level of the sample by comparing the attenuance signal over time
with the simulated attenuance signal over time.
15. Computer program comprising program code means for causing a
computer to carry out the steps of the method as claimed in claim
14 when said computer program is carried out on the computer.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] The present application is a continuation of co-pending U.S.
patent application Ser. No. 15/535,784, filed Dec. 17, 2015, which
is the U.S. National Phase application under 35 U.S.C. .sctn. 371
of International Application No. PCT/EP2015/080379 filed Dec. 17,
2015, which claims the benefit of European Application No.
14198867.5 filed Dec. 18, 2014. These applications are hereby
incorporated by reference herein.
FIELD OF THE INVENTION
[0002] The present invention relates to a device, system and method
for determining a fibrinogen level in a blood sample using a model
of fibrin polymerization that is able to simulate the turbidity
build-up during a coagulation process based on a time-variant input
of a reactant concentration. The model is independent of
calibration plasma and standard curves.
BACKGROUND OF THE INVENTION
[0003] Hemostasis is the ability of the body to stop blood loss
from a vascular injury; the main process involved in hemostasis is
the formation of a hemostatic plug in response to the injury often
referred to as primary and secondary hemostasis. In healthy
situations the hemostatic plug covers the wound in the vasculature
quickly and precisely and thereby stops the blood leakage from the
wound without interrupting the blood flow in the vessel too much.
In pathological situations this hemostatic balance can be disturbed
resulting in on the one hand too much clotting or on the other hand
excessive bleeding. Examples of thrombosis are venous
thrombosis/thromboembolism, pulmonary embolism, ischemic stroke and
examples of bleeding are intracranial hemorrhage, hemophilia. The
hemostatic imbalance can be a result of three causes,
hyper/hypocoagulability, hemodynamic changes or endothelial injury
or dysfunction, historically also known as Virchow's triad.
[0004] Fibrinogen is an important protein involved in coagulation.
During normal blood flow, fibrinogen is soluble; however upon
activation of the coagulation system fibrinogen is eventually
converted by thrombin into fibrin. Fibrin subsequently polymerizes
into insoluble fibrin fibers that, together with (activated)
platelets, form a clot. The normal level of fibrinogen is
approximately 2.5 g/L (range about 1.5-3 g/L). Yet in many cases
the fibrinogen level might be outside the normal range, which might
be associated with pathological disorders. For example, in
hereditary hypofibrinogenemia patients with exceptionably low
levels of fibrinogen result in a bleeding tendency. Also trauma or
surgery patients might develop a low level of fibrinogen due to
sustained bleeding, resulting in a dangerous situation which can be
countered by the addition of blood products. On the other side of
the spectrum elevated levels of fibrinogen are found to be
correlated with an elevated risk of myocardial infarction,
thrombosis and prolonged inflammatory processes such as rheumatoid
arthritis.
[0005] As a result of these varying fibrinogen levels and
associated pathologies, the fibrinogen level test is a valuable
clinical test. Many methods have been developed to accurately
detect the level of fibrinogen in a plasma or blood sample, see for
example Palarati et al. for an overview of available techniques.
Unfortunately, all present methods are either very labor-intensive,
such as the clot-recovery method, or need a standard curve derived
from a plasma sample with a known fibrinogen level to infer the
sample's fibrinogen level, such as the Clauss assay or
prothrombin-time-derived method. Whereas the former involves a lot
of hands on time and therefore is difficult to automate, the latter
needs calibration plasmas to be included in the test kit, thereby
making these methods less suitable to incorporate in e.g. a
handheld point of care (POC) system to detect the level of
fibrinogen.
[0006] Since reliable point of care fibrinogen tests are not
available and central lab test ordering in general takes too long
for time-critical situations, there is a need for an improved
system and method.
SUMMARY OF THE INVENTION
[0007] It is an object of the present invention to provide a device
for determining the fibrinogen level in a sample that is more
reliable, easy to use and independent from external references.
Furthermore, a corresponding system and method shall be
provided.
[0008] According to a first aspect of the present invention a
device for determining a fibrinogen level in a sample is presented
comprising, a first input for obtaining an attenuance signal over
time indicative of a fibrin polymerization of said sample, a second
input for obtaining a reactant concentration signal over time
indicative of a reactant concentration in said sample, wherein the
reactant is any substance leading to the cleavage of fibrinogen to
fibrin, a simulation unit running a model using the reactant
concentration signal as an input to provide a simulated attenuance
signal over time, and an evaluation unit configured to infer the
fibrinogen level of said sample by comparing the attenuance signal
over time with the simulated attenuance signal over time.
[0009] According to a second aspect of the present invention a
system for determining a fibrinogen level in a sample is presented
comprising, a measuring unit for providing an attenuance signal
over time indicative of a fibrin polymerization of said sample, and
a device comprising, a first input for obtaining an attenuance
signal over time indicative of a fibrin polymerization of said
sample, a second input for obtaining a reactant concentration
signal over time indicative of a reactant concentration in said
sample, wherein the reactant is any substance leading to the
cleavage of fibrinogen to fibrin, a simulation unit running a model
using the reactant concentration signal as an input to provide a
simulated attenuance signal over time, and an evaluation unit
configured to infer the fibrinogen level of said sample by
comparing the attenuance signal over time with the simulated
attenuance signal over time.
[0010] According to a third aspect of the present invention a
method for determining the fibrinogen level in a sample is
presented comprising, obtaining an attenuance signal over time
indicative of a fibrin polymerization of said sample, obtaining a
reactant concentration signal over time indicative of a reactant
concentration in said sample, wherein the reactant is any substance
leading to the cleavage of fibrinogen to fibrin, running a model
using the reactant concentration signal as an input to provide a
simulated attenuance signal over time, and inferring the fibrinogen
level of the sample by comparing the attenuance signal over time
with the simulated attenuance signal over time.
[0011] In yet further aspects of the present invention, there are
provided a computer program which comprises program code means for
causing a computer to perform the steps of the method disclosed
herein when said computer program is carried out on a computer as
well as a non-transitory computer-readable recording medium that
stores therein a computer program product, which, when executed by
a processor, causes the method disclosed herein to be
performed.
[0012] The present invention is based on the general idea of
simulating the coagulation process, in particular the turbidity
build-up over time, of plasma or a blood sample using a model
representative of the underlying biochemical reactions, and by
comparing the results thereof with actual measurements taken from
the sample after the coagulation process has been initiated by
adding a reagent to the sample. The model, for instance a
computational model, is designed to simulate aspects of the
coagulation process using time variant concentration levels of one
or more reactant of the reagent as its input. Herein a reactant is
any substance leading to the cleavage of fibrinogen to fibrin,
resulting in the polymerization of fibrin monomer. Preferable, the
reactant is thrombin.
[0013] Subsequently, the fibrinogen level of the sample may be
derived from the comparison of the simulated data and the actual
measurements using analytical methods.
[0014] Advantageously, the present invention requires no additional
references. In particular, the present invention requires no
standard curves or reference plasma to derive the fibrinogen level
of the sample. Therefore, the invention may be used in a
standalone, and preferably mobile, point of care system, such that
an off-site and time consuming central lab test becomes obsolete.
Hence, the present invention may advantageously be used in
time-critical situations, e.g. in the operating environment or
emergency department.
[0015] Finally, the present invention offers more precise results
than equivalent tests, since the results are built around the
actual underlying biochemical reactions of the coagulation process.
In other words, the model is based on analytical data rather than
empirical derived data of the coagulation process. Additionally,
the model may be further enhanced and optimized if more aspects of
the coagulation process should emerge in the future.
[0016] Preferred embodiments of the invention are defined in the
dependent claims. It shall be understood that the claimed methods,
processor, computer program and medium have similar and/or
identical preferred embodiments as the claimed system and as
defined in the dependent claims.
[0017] According to an embodiment, the simulation unit is
configured to provide to the evaluation unit multiple simulated
attenuance signals over time for a range of fibrinogen levels. In
this case the fibrinogen level of the sample is inferred from the
plurality of simulated attenuance signals. For that, preferably, a
characteristic feature of these signals is extracted and
interpolated as a function of fibrinogen levels, such that an
equivalent feature extracted from the measured attenuance signal
may be mapped against said function to determine the fibrinogen
level of the sample. Advantageously, the simulation runs only once
to produce the necessary output from the model and can run in
parallel with the measurement. Furthermore, the simulated data may
be used for multiple subsequent measurements.
[0018] According to a further embodiment, the evaluation unit is
configured to extract one or more characteristic features from the
attenuance signal and further one or more characteristic features
from the simulated attenuance signal, wherein the evaluation unit
is further configured to match the one or more characteristic
features with the further one or more characteristic features.
Extracting only specific features of the signal facilitates an
easier matching of the simulated and measured signals and thus
produces more reliable results, since certain deficiency in the
measurement or the simulation may be canceled out. Furthermore, the
computation complexity may be reduced using this approach, since
only parts of the signals have to be compared with one another,
instead of the whole signal.
[0019] Preferably, at least one of the one or more characteristic
features and at least one of the further one or more characteristic
features is defined by the difference between an initial attenuance
and a final, that is after the clotting process is (near) fully
developed, attenuance of the attenuance signal and the simulated
attenuance signal. Since the attenuance signals generally have a
sigmoid-like shape with an initial plateau at the beginning and a
final plateau at the end, the initial and final attenuance
represent an easy to extract, yet highly distinguishing feature of
said attenuance signals.
[0020] According to a further embodiment, the simulation unit is
configured to rerun the model at least one more time with a
parameter provided by the evaluation unit, such that an error
between the attenuance signal and the simulated attenuance signal
is minimized. Such iterative approach may make use of well-known
algorithm such as the simplex algorithm, (quasi-)Newton method,
gradient descent, genetic algorithm, or differential evolution, and
may as such use standard and optimized libraries and modules
available in common simulation tools. This way a simple and highly
efficient implementation of the model is feasible.
[0021] According to a further embodiment, the simulation unit is
configured to run the model that uses at least one ordinary
differential equation indicative of a chemical reaction of fibrin
polymerization. Ordinary differential equations (ODEs) have proven
to be very well suited to model the reactions rates of the
underlying chemical reactions. Chemical reactions in the form of
A+BC can straightforwardly be converted into computer-interpretable
(algebraic) equations by constructing ODEs or sets of ODEs.
Enzymatic and complex assembly processes taken place in the fibrin
polymerization can be represented by a set of chemical reactions of
the above mentioned form.
[0022] Preferably, a state variable of said at least one ordinary
differential equation is the reactant concentration signal. Having
a time-variant input, such as the reactant concentration over time
in the sample, produces very accurate and reliable results, since
the underlying chemicals reactions are better and more
realistically reflected by such input.
[0023] According to a further embodiment, the simulation unit is
configured to run the model that uses a set of coupled ordinary
differential equations, each being indicative of a chemical
reaction of fibrin polymerization, and said set is being solved by
the simulation unit numerically. Sets of ODEs may advantageously be
solved numerically using standard ODE-solvers available in common
simulation tools. This way, an easy and robust implementation of
the model using common simulation tools is feasible.
[0024] According to a further embodiment, the simulation unit is
configured to run the model that uses at least a first algorithm to
determine concentrations of protein complexes, a second algorithm
to determine the average mass/length ratio of fibrin molecules from
said concentrations, and a third algorithm to determine the
attenuance of the sample from said mass/length ratio. Such a model
connects straightforwardly the input signal, namely a reactant
concentration signal, with the output, namely a simulated signal of
the attenuance.
[0025] According to a further embodiment, the reactant
concentration signal over time is interpolated from a time-discrete
signal to a continuous signal using a reactant specific
interpolation formula. If the reactant concentration is determined
by measurement, the measured signal will generally be a
time-discrete signal, oftentimes showing a high variation.
Advantageously, by interpolating such signal using a proven
interpolation function a more suitable input for the model may be
derived that better reflects the actual concentration levels in the
sample.
[0026] According to a further embodiment, the reactant
concentration is a thrombin concentration. Thrombin is a preferred
clotting trigger as it directly converts soluble fibrinogen in the
sample into insoluble strands of fibrin and additionally catalyzes
many other coagulation-related reactions. Furthermore, a thrombin
concentration in a sample can be determined by measurement.
[0027] According to a further embodiment, the system comprises a
further measuring unit to provide an actual measurement of a
reactant concentration of the sample. By measuring the actual
reactant concentration of the sample a more realistic input for the
model may be provided, such that more accurate simulations may be
performed.
[0028] Preferably, said further measurement unit is configured to
monitor the cleaving of a fluorogenic substrate and to compare it
to a constant known reactant activity in a parallel, non-clotting
sample. Such a measurement, especially for the determination of a
thrombin concentration, provides very precise results and leads to
a more accurate simulation.
BRIEF DESCRIPTION OF THE DRAWINGS
[0029] These and other aspects of the invention will be apparent
from and elucidated with reference to the embodiment(s) described
hereinafter. In the following drawings
[0030] FIG. 1 shows a schematic diagram of an embodiment of a
device according to the first aspect of the present invention,
[0031] FIG. 2 shows an example of a measured time-discrete signal,
showing a high variation reactant concentration signal over time
(thin line) and interpolated reactant concentration signal over
time (thick line) that serves as input for the model,
[0032] FIG. 3 shows an example of multiple simulated attenuance
signals over time for the same reactant concentration signal over
time with increasing values of fibrinogen resulting in a stepwise
increase in attenuance,
[0033] FIG. 4 shows an example of an extracted feature of the
simulated attenuance signals as a function of fibrinogen
levels,
[0034] FIG. 5 shows an example of an error signal derived from the
comparison of the measured and the simulated attenuance signal as a
function of fibrinogen levels,
[0035] FIG. 6 shows an embodiment of a system according to the
second aspect of the present invention, and
[0036] FIG. 7 shows a method according to the third aspect of the
present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0037] FIG. 1 shows a first embodiment of the device according to
the present invention. The device is denoted in its entirety with
reference numeral 10. The device comprises a first input 12, a
second input 14, a simulation unit 16 and an evaluation unit 18 to
determine the fibrinogen level 20 of a sample 22.
[0038] The sample 22 is preferably a blood plasma sample,
alternatively it can be a whole-blood sample, obtained preferably
by venipuncture or alternatively a sample of capillary blood
obtained using for example a blood lancet in combination with
capillary forces.
[0039] The first input 12 can be configured to obtain an attenuance
signal 24 indicative of a polymerization of the sample 22 after a
clotting trigger 26 has been applied thereto. The attenuance signal
24 is representative of the formation of a fibrin network taking
place during blood coagulation. In short, proteins in human plasma,
called coagulation factors, respond in a complex cascade as result
of a clotting trigger resulting ultimately in the formation of
fibrin monomers that polymerize to form fibrin strands. These
fibrin strands are highly connected and as a result have a gel-like
structure.
[0040] The attenuance of a coagulating plasma or blood sample
changes over time as a result of the fibrin network being formed
during clotting of the sample. Fibrin fibers are being formed after
a clotting trigger is added to the sample. These fibrin fibers
result in scattering of the incident light resulting in less
photons arriving at the detector. Actual absorbance of the photons
and other causes of photon loss e.g. due to interference are
considered to be constant over time during clotting, hence the
attenuance and thereby decrease in transmittance and increase in
optical density, which is the base-10 logarithm of the
transmittance, is considered solely due to scattering of the
incident light by the fibrin fibers formed in the sample. The
attenuance of a material is log 10(P.sub.0/P), where P.sub.0 is the
radiant power incident on a sample, and P is that transmitted by
it. This quantity is also -log 10(T), where T is the transmittance.
Attenuance is often referred to in the literature by terms such as
`optical density`, `turbidity` or `extinction`. Also the name
`absorbance` (symbol: A) is often used for this quantity, but this
is clearly inappropriate for the quantity when the attenuation of
the radiation is due to scattering rather than absorption. The
quantity itself is called attenuance (symbol: D), with the remark
that attenuance reduces to absorbance when there is negligible
scattering or reflection. It shall be noted that in the case that
attenuance reduces to scattering, scientist may use the term
`turbidity`, which is typically considered as -ln(T). In the latter
case, `turbidity` may be estimated by measuring transmittance. To
actually measure scattering due to particles in solution,
specialized techniques are available such as small-angle scattering
or nephelometry. A person skilled in the art is able to convert
what is claimed herein to the turbidity, transmittance, optical
density, absorbance and possible other measures of light
attenuation, or more preferable scattering due to particles in
solution, in a sample.
[0041] The attenuance signal 24 may be an analogous or digital
signal indicative of a intensity attenuation of transmitted light
due to scattering or absorption of light in the sample 22, from
which a turbidity or a absorbance property of the sample may be
derived.
[0042] The second input 14 can be configured to obtain a reactant
concentration signal 28 indicative of a reactant concentration in
the sample 22. The reactant concentration signal 28 may be an
analogous or digital signal representing a concentration of a
reagent added to the sample as clotting trigger 26 or any other
concentration of intermediate reactants involved in the coagulation
process. It shall be noted that the second input 14 is not limited
to obtain a single signal, but may also receive further signals
indicative of reagent concentrations involved in the coagulation
process or other process variables. The second input 14 may obtain
the reactant concentration signal 28 directly from the amount of
clotting trigger 26 added to the sample 22, for instance, as a
manual input, or by an actual measurement taken from the sample 22
after a clotting trigger 26 has been added, wherein the latter is
preferred.
[0043] In a preferred embodiment the reactant concentration signal
28 may be indicative of a concentration of thrombin available as
clotting trigger 26 to the sample 22 as described in more detail
with regard to FIG. 2. It shall be noted that the coagulation does
not need to be started with the addition of thrombin. Other tissue
factor may be added instead and the concentration of thrombin is
measured over time to derive the reactant concentration signal 28.
In a preferred embodiment the thrombin concentration added is
greater than 1 NIH U/mL.
[0044] Alternatively, in another embodiment, a snake venom
thrombin-like enzyme (SVTLE) such as batroxobin or reptilase may be
used to trigger the coagulation, wherein, advantageously, the SVTLE
is not inhibited by natural inhibitors in the plasma sample.
[0045] The reactant concentration signal 28 and the attenuance
signal 24 represent the input to the simulation unit 16 and the
evaluation unit 18 which in combination are capable of determining
the fibrinogen level 20 in the sample 22. In a preferred
embodiment, the simulation unit 16 and the evaluation unit 18 are
combined in a single computing device as illustrated here by the
computer 30. The computing device may be a standalone PC, a
workstation, one or more module in a Clinical Decision Support
(CDS) system, a dedicated computing device, or distributed
computing means provided, for instance, as a web service.
[0046] The simulation unit 16 is configured to execute and run a
model 32 using one or more reactant concentration signal 28 as
input. Preferably, the model is a computational model. An output of
the simulation unit 16 may inter alia include one or more simulated
attenuance signals for a range of different fibrinogen levels as
denoted here with reference numeral 34.
[0047] The evaluation unit 18 is configured to infer the actual
fibrinogen level 20 of the sample 22 from the measured attenuance
signal 24 and the one or more simulated attenuance signal 34
provided by the simulation unit 16.
[0048] In the following, the model 32 run by the simulation unit 16
and inferring of the actual fibrinogen level 20 by the evaluation
unit 18 is explained in greater detail with reference to FIGS. 2
and 3 and FIGS. 4 and 5, respectively.
[0049] The model 32 may be a mathematical representation of fibrin
polymerization, wherein the polymerization of fibrin is a
combination of enzymatic and polymerization reactions which can be
described as chemical reactions in the form of A+BC.
[0050] The model 32 incorporates these chemical reactions as
computer-interpretable (algebraic) equations in order to simulate
the fibrin polymerization. Preferably, the chemical reactions are
represented hereto, as a set of coupled ordinary differential
equations (ODEs) describing the reaction rates of the chemical
reactions. In general form an ODE is given by:
dy dt = f .function. ( t , y , .theta. ) ##EQU00001## y .function.
( t = 0 ) = y 0 ##EQU00001.2##
With .theta. being an m-dimensional vector containing all reaction
rate parameters, y being an n-dimensional vector of the states
(here concentrations of the different enzymes and polymerization
elements included in the model), t being time, and y.sub.0 being a
vector of numerical values for y at t=0. Function f is a given
vector function, which is a representation of the reactions
incorporated in the model.
[0051] Examples of individual reactions incorporated in the model
may be the following:
[0052] representing the cleavage of fibrinopeptide A from the
inactivated fibrinogen monomer. First F2a binds to the A-site and
subsequently F2a and fibrinogen can either dissociate or F2a can
cleave the fibrinogen monomer:
Fg + F .times. 2 .times. a .times. .fwdarw. k 1 .rarw. k - 1
.times. Fg - F .times. 2 .times. a .function. ( A ) .times. .times.
.times. .fwdarw. k cat .times. 1 .times. desAA .times. .times. Fn +
F .times. 2 .times. a + 2 .times. FpA ##EQU00002##
as r1, but now fibrinopeptide B is cleaved:
Fg + F .times. 2 .times. a .times. .fwdarw. k 2 .rarw. k - 2
.times. Fg - F .times. 2 .times. a .function. ( B ) .times. .times.
.times. .fwdarw. k cat .times. 2 .times. desBB .times. .times. Fn +
F .times. 2 .times. a + 2 .times. FpB ##EQU00003##
as r2, but now fibrinopeptide B is cleaved from the partially
activated desAA fibrin monomer, which can be part of a
protofibril:
desAA .times. .times. Fn + F .times. 2 .times. a .times. .fwdarw. k
3 .rarw. k - 3 .times. desAA .times. .times. Fn - F .times. 2
.times. a .times. .times. .times. .fwdarw. k cat .times. 3 .times.
Fn + F .times. 2 .times. a + 2 .times. FpB ##EQU00004##
as r1, but now fibrinopeptide A is cleaved from the partially
activated fibrin monomer:
desBB .times. .times. Fn + F .times. 2 .times. a .times. .fwdarw. k
4 .rarw. k - 4 .times. desBB .times. .times. Fn - F .times. 2
.times. a .times. .times. .times. .fwdarw. k cat .times. 4 .times.
Fn + F .times. 2 .times. a + 2 .times. FpA ##EQU00005##
another F2a binds to the unoccupied B-site of the Fn-F2a(A)
complex. This complex can either dissociate or F2a can cleave off
FpA from the complex:
Fg - F .times. 2 .times. a .function. ( A ) + F .times. 2 .times. a
.times. .fwdarw. k 5 .rarw. k - 5 .times. Fg - F .times. 2 .times.
a .function. ( A ) - F .times. 2 .times. a .function. ( B ) .times.
.times. .times. .fwdarw. k cat .times. 5 .times. desAA .times.
.times. Fn - F .times. 2 .times. a + F .times. 2 .times. a + 2
.times. FpA ##EQU00006##
as r5, but here F2a binds to the unoccupied A-site and FpA is
cleaved off:
Fg - F .times. 2 .times. a .function. ( B ) + F .times. 2 .times. a
.times. .fwdarw. k 6 .rarw. k - 6 .times. Fg - F .times. 2 .times.
a .function. ( A ) - F .times. 2 .times. a .function. ( B ) .times.
.times. .times. .fwdarw. k cat .times. 6 .times. desBB .times.
.times. Fn - F .times. 2 .times. a + F .times. 2 .times. a + 2
.times. FpB ##EQU00007##
Protofibril formation/growth Vn, m=1, . . . , 29 with Pi being
desAA Fn or Fn:
P n + P m .times. .fwdarw. k pf .times. P n + m ##EQU00008##
Fiber initiation, F1 are protofibrils of a certain length with
F.sub.1=P.sub.n with P.sub.n .A-inverted.n=1, . . . , 30:
F 1 + F 2 .times. .fwdarw. k ffi .times. F 2 ##EQU00009##
Fiber growth .A-inverted.k=1, . . . ,11,/=1, . . . ,10:
F k + F i .times. .fwdarw. k ffg .times. F k + l ##EQU00010##
[0053] Such chemical reactions may be converted into reaction rate
equations representing the rate of change of concentrations of the
involved molecules. For a reversible conversion of molecule A and B
into molecule C
( i . e . .times. A + B .times. .fwdarw. k + .rarw. k - .times. C )
##EQU00011##
the reaction rate v may be given as v=k.sub.+[A][B]-k.sub.-[C] with
the brackets denoting concentrations. The associated ODEs can be
expressed as:
d .function. [ A ] dt = - v ##EQU00012## d .function. [ B ] dt = -
v ##EQU00012.2## d .function. [ C ] dt = + v ##EQU00012.3##
[0054] For irreversible reactions the term k.sub.-[C] may be set to
zero. The ODE of a particular molecule is the summation of all
reaction rates the molecule is involved in.
[0055] In a preferred embodiment the model may result in 144
ODEs/states of which 12 belong to the enzymatic part and 132 to the
protofibril and fiber formation. Such a set of coupled ODEs may be
solved numerically using standard ODE-solver available, for
instance, in MATLAB (The MathWorks Inc., Natick, Mass., USA) or
other numerical computation tools.
[0056] From the molecule concentrations obtained by the ODEs over
time a simulated attenuance of the sample may be derived. In a
sample of polymerizing fibrin most of the attenuation of light is a
result of light scattering on the surface of the formed fibers.
Therefore, the attenuation of the light intensity may be defined as
the integral over all scattering angles. The scattering due to thin
rod-like particles, like fibers, can be estimated using the
Rayleigh scattering theory which describes the elastic scattering
of light or other electromagnetic radiation by particles much
smaller than the wavelength of the light.
[0057] To be able to connect the simulated time-profiles of the
concentrations of protein (complexes) obtained from the ODEs to the
attenuance, the mass/length of the simulated fibrin molecules may
be determined. The average mass/length ratio of the simulated
fibrin molecules (in whatever configuration, e.g. monomers,
protofibrils, fibers) is the mass/length ratio of each particle
weighted by their concentration:
.mu. mdl = i = 1 n .times. c i c total .times. .mu. i
##EQU00013##
[0058] With c.sub.i being the concentration of a particle i,
c.sub.total being the concentration of all particles, and
.mu..sub.i being the mass/length ratio of particle i calculated by
using the number of monomers and position of the monomers in the
particle (e.g. monomer, protofibril, fiber, etc.) in combination
with the weight and length of a single monomer. For every particle
the average number of monomers in the longitudinal and lateral
direction may be monitored during the simulation, thereby making it
possible to calculate the mass/length ratio at every time point.
Furthermore, the length of a particle containing more than one
fibrin monomers may be approximated using:
L.sub.p=1/2(N.sub.longitudinal+1)L.sub.monomer
[0059] With N.sub.longitudinal being the (average) number of
monomers in the longitudinal direction of the fiber and
L.sub.monomer being the length of a single monomer, i.e. 45 nm. The
factor 1/2 is the result of the half-staggered formation of fibers.
Obviously, fibrinogen and fibrin monomers are assigned a length of
45 nm.
[0060] The average radius r of the particles needed in order to
calculate the attenuance may be derived by estimating the average
radius of the particles in the solution using the known density of
a fibrin network, which is approximately 0.28 g/cm.sup.3, in
combination with the assumption that the shape of fibers are by
approximation equal to a cylindrical volume.
[0061] Finally, taking the above estimations into account, the
simulated attenuance may be calculated using:
.tau. = c .lamda. 3 .function. ( A .mu. + B .pi..rho. .times. N A
.times. .lamda. 2 ) ##EQU00014##
[0062] With N.sub.A being Avogadro's number to transform the
density to Da/cm.sup.3, .mu. being the average mass/length ratio of
the fibers in Dalton per centimeter, and A and B being lumped
parameters that can be determined in separate experiments or by
measuring the attenuance of a fixed mass/length ratio of known
solute concentrations at different wave lengths. In a preferred
embodiment values for A and B at a wavelength of 632.8 nm may be
6.76.times.10.sup.22 and 1.41.times.10.sup.24, respectively.
[0063] FIG. 2 depicts in a diagram an example of a reactant
concentration signal 28 which may be used as input to the model 32
of the simulation unit 16. Here, the reactant concentration signal
28 represents a thrombin concentration 36 (axis of ordinate) in the
sample 22. Thrombin may be used as preferred clotting trigger 26.
It acts as a serine protease that converts soluble fibrinogen in
the sample 22 into insoluble strands of fibrin and catalyzes many
other coagulation-related reactions. The fibrin strands
subsequently polymerize by forming a fibrin network, causing a
gelation of the plasma that can be measured inter alia by
determining the attenuance as explained above. It shall be noted
that the system is not limited to thrombin as reagent as
illustrated here; other protein with similar activity towards
fibrinogen or even a combination of different reagents are
conceivable as well.
[0064] The thrombin concentration 36 depicted in FIG. 2 results
from an actual measurement 38 of the thrombin concentration in the
sample over time 40 (axis of abscissas). In another embodiment the
thrombin concentration of the sample may be derived by the amount
of thrombin added as clotting trigger 26 to the sample 22.
Alternatively, the thrombin concentration may be estimated by its
initial concentration values and treated as constant value over
time. Generally, an actual measurement 38 of the reactant
concentration in the sample over time is preferred. Such
measurement may be conducted in parallel, in series, or
simultaneously to the measurement of the attenuance signal 24.
[0065] Furthermore, the actual time-discrete measurement 38 of the
thrombin concentration may be approximated by means of
interpolation, for instance, using the following interpolation
formula (Wagenvoord et al. J Thromb Haem 4: 1331-1338):
W=abc.times.e.sup.-bc(t-t.sup.0.sup.).times.(e.sup.b(t-t.sup.0.sup.)-1).-
sup.c-1
[0066] With t being time, and a, b, c and to being positive
constants that have been fitted to the experimentally determined
thrombin concentration data.
[0067] In a preferred embodiment the interpolation may be further
enhanced by a hybrid interpolation of the time discrete attenuance
signal 38 using a cross-over fit of an exponential fit combined
with the above stated W-function. The hybrid fit will follow the
fitted exponential curve until it crosses with the fitted
W-function, wherein the transition may be made at a thrombin
concentration of 20 nM arbitrarily if the two functions do not
intersect. The result of the interpolation is a continuous signal
42, which is subsequently being used as input to the model 32. In
other words, the input to the model 32 is preferably an
interpolated, continuous signal 42 derived from a time-discrete or
continuous measurement 38.
[0068] With reference to FIG. 3 an example of an output of the
model 32 is described. The diagram shows a plot 44 of multiple
simulated attenuance signals 34 over time for a range of different
fibrinogen levels. The attenuance 46 is plotted here on the
vertical axis and time 40 on the horizontal axis. Reference numeral
48, for instance, denotes a simulated attenuance signal for a
fibrinogen level of 2 g/L. The individual simulated attenuance
signals represented by the plot 44 are generally characterized by a
sigmoid shape having a starting plateau, an end plateau, and a
slope in between, wherein the starting plateau defines an initial
attenuance 50 and the end plateau a final attenuance 52,
respectively. The difference between the initial attenuance 50 and
the final attenuance 52 defines a .DELTA.attenuance as denoted here
with reference numeral 54 for the exemplary attenuance signal 48
for a fibrinogen level of 2 g/L. The .DELTA.attenuance 54
represents a preferred feature of the simulated attenuance signals
44, which is easy to extracted and yet very characteristic. The
.DELTA.attenuance of the simulated attenuance signals 44 and a
.DELTA.attenuance extracted from the measured attenuance signal 24
may be used for the comparison of the simulated and the measured
attenuance to infer the fibrinogen level of the sample as explained
in greater detail with reference to FIG. 4 and FIG. 5 in the
following
[0069] From the model output and the measured attenuance signal 24,
the evaluation unit 18 may infer the actual fibrinogen level 20 of
the sample 22 by comparing the two inputs with one another. This
can be done in a number of ways, for example, by comparing a
specific extracted feature, such as the .DELTA.attenuance 54, from
the measured attenuance signal with the same feature extracted from
the simulated attenuance signals 34. Preferably, from the feature
extracted from the plurality of simulated attenuance signals 44 a
function of said feature over fibrinogen levels is derived.
Subsequently, .DELTA.attenuance extracted of the measured
attenuance signal 24 is mapped against said function to determine
the fibrinogen level 20.
[0070] It shall be noted that such procedure is not limited to
.DELTA.attenuance as feature. Other features such as the whole
curve, maximum slope of the attenuance signal (max rate), lag time,
time to maximum slope, time to plateau and time to lower plateau
and so forth, may be used similarly to infer the fibrinogen level.
It is also conceivable that multiple features may be used in
combination to achieve more reliable results. Furthermore, the
comparison may also be based on other outputs of the model of
fibrin polymerization, for instance, the time evolution of the
average mass/length ratio of the fibrin fibers formed during the
polymerization process.
[0071] With reference to FIG. 4 an example of such a comparison
using the .DELTA.attenuance 54 as the relevant feature is
illustrated. FIG. 4 shows a plot 56 of simulated .DELTA.attenuance
54 as a function of fibrinogen level 58. From the plot 56 the
fibrinogen level 20 of the sample may be derived by mapping the
.DELTA.attenuance 60 extracted from the measured attenuance signal
against this function 56. Here, for example, an actual observed
.DELTA.attenuance 60 of 0.83 relates to a fibrinogen level 20 of
3.14159 g/L.
[0072] With reference to FIG. 5 an alternative approach to infer
the fibrinogen level from the measured and the simulated attenuance
signal is illustrated. Here, the difference between the measured
and simulated attenuance signal is minimized by adapting the input
parameter for the fibrinogen level of the simulation runs in such a
way that the difference between the attenuance signal and the
simulated the attenuance signal is minimized. In other word, the
evaluation unit reruns the simulation by the simulation unit at
least one more time with adapted parameters, in particular
different fibrinogen levels, such that a difference between the
measured and the simulated attenuance signal, or feature(s) derived
thereof, remains under a certain threshold. It shall be noted that
the adapted parameters are not limited to different fibrinogen
levels. Other parameters are conceivable as well. Known algorithms
to be used for such a procedure are, for instance, the simplex
algorithm, (quasi-)Newton method, gradient descent, genetic
algorithm, and differential evolution.
[0073] FIG. 5 illustrates the results of such a procedure, in which
an error between the observed attenuance signal and the simulated
attenuance signal is being minimized by changing the parameter for
the fibrinogen level with each simulation run. The plot 62 of FIG.
5 shows the sum of the squared error 64 as function of fibrinogen
level 62, wherein the point reflecting the smallest error, which is
here the minimal turning point 66, marks the fibrinogen level of
the sample. Here, for instance, a fibrinogen level of 3.14159 g/L
is determined as indicated by the open circle. In the given
example, the complete signals have been compared. Alternatively,
only features of the signal may be used for the comparison
instead.
[0074] FIG. 6 shows an exemplary embodiment of a system according
to the present invention. The system comprises in this embodiment,
a device 10 as explained in detailed with reference to FIG. 1, a
measuring unit 13 and a signaling unit 15.
[0075] The measuring unit 13 may be any device configured to obtain
an attenuance signal 24 indicative of a fibrin polymerization of
the sample 22. Preferably, the measuring unit 13 comprises a light
source and a corresponding light detector to determine the
intensity of light passing through the sample as a function over
time. The measurement is preferably provided as an analogous or
digital signal and passed on to the first input 12 of the device 10
for processing.
[0076] Additionally, the system may comprise a signaling unit 15
which can be any device configured to provide a reactant
concentration signal 28 indicative of a reactant concentration in
the sample 22. In one embodiment the signaling unit 15 can be a
simple input unit for manually providing an initial reactant
concentration as a single constant. In a preferred embodiment, the
signaling unit 15 comprises a further measuring unit configured to
provide an actual continuous measurement indicative of a reactant
concentration over time. For that, the further measuring unit may
continuously measure the amount of clotting trigger 26 added to the
sample 22 as denoted by reference numeral 68, or preferred, the
further measuring unit determines the actual reactant concentration
from the sample directly. This may be done, for instance, using a
calibrated automated thrombin measurement (CAT-TGA) as denoted here
with reference numeral 70.
[0077] It shall be noted that the signaling unit 15 is not limited
to provide a single system. It is conceivable that the signaling
unit 15 provides further signals to the input 14 to be used by the
simulation unit 16. Furthermore, it shall be noted that the input
12 and the input 14 may only be separate units on a logical level.
Input 12 and 14 may as well be combined into a single interface
capable of obtaining the relevant signals. Input 12 and input 14
could thus be realized as a single network adapter or as USB
port.
[0078] From the signal provided by the measuring unit 13 and the
signaling unit 15 the device 10 determines the fibrinogen level as
explained in detail with reference to FIGS. 1 to 5.
[0079] In another embodiment the system may preferably be divided
into a testing kit, which comprises cartridges, reagents and so
forth to perform the necessary lab experiments to obtain the
required input signals, and a device 10, which receives said input
signals and performs the simulation and evaluation to determine the
fibrinogen level of the sample. The testing kit can be a one-way
kit which is disposed after use, whereas the device 10 is
preferably reusable.
[0080] In another embodiment, the testing kit may be a portable
device having two intakes as holding fixtures for the sample and a
reagent. A sample may be inserted into the intake and applied with
an appropriate reagent inserted into the other intake. Preferably,
the reagent will be applied to the sample automatically to avoid
any manual error. The portable device may further include measuring
units, which take from the sample the necessary measurements to
obtain the signals necessary for the simulation and evaluation. The
simulation and evaluation is preferably not performed by the
portable device itself, but by a computing device link to the
portable device. For that, the portable device may be hooked up,
preferably wirelessly, to a workstation or a terminal of a clinical
decision support system, which may perform the required
calculations. The results of said calculations may be return to the
portable device and display thereupon, or stored with in the
CDS.
[0081] With reference to FIG. 7 the individual steps of a method
100 according to the present invention are illustrated. The method
starts with the input of plasma or a blood sample which is to be
analyzed. In a first step 102 an attenuance signal over time is
obtained, preferably, from a continuous measurement of the
intensity attenuation of light transmitted thought the sample. Such
attenuance signal over time may be represented as intensity of
light passed through the sample relative to the intensity of a
light source that is used to illuminate the sample. Generally, the
obtained attenuance signal is a time-discrete signal with
time-discrete values. Such signal may be further interpolated to be
represented as a continuous signal.
[0082] In the following step 104 a further input signal is
obtained, namely a reactant concentration signal over time
indicative of a reactant concentration in said sample. Such signal
may be obtained by a given initial concentration of a reagent or by
a direct measurement of the reactant concentration in the sample.
The latter may be achieved in case of thrombin being one reactant
by a so called Calibrated Automated Thrombin Measurement (CAT-TGA).
For that, the cleaving of a fluorogenic substrate will be monitored
and compared to a constant known reactant activity in a parallel,
non-clotting sample. A standard thrombin generation assay measures
every tens of seconds the fluorescence.
[0083] Preferably, such measurement is taken from said sample under
the same conditions than the measurement of the attenuance signal.
Even more preferably, both measurements take place simultaneously
with respect to one another. In the alternative, the measurements
are conducted in series. The retrieved time-discrete signal may be
transferred to a continuous signal as explained in detail with
reference to FIG. 2.
[0084] Having obtained the attenuance signal over time and the
reactant concentration signal over time a model is executed under
step 106 with the reactant concentration signal as input. The
output of the simulation comprises at least one simulated
attenuance signal, which may subsequently be used to infer the
fibrinogen level under step 108.
[0085] Step 108 can be carried out in multiple ways. The simulated
attenuance signal may be a single signal that is iteratively
adapted by changing the input parameter for the fibrinogen level to
fit the simulated attenuance signal to the previously measured
attenuance signal. For that, the simulation may be rerun multiple
times as indicated here by the dashed arrow 110 until an error
between the simulated and the measured signal, or features thereof,
has been minimized. Once the error has been minimized the input
parameter for the fibrinogen level represents the fibrinogen level
20 of the sample and the method ends.
[0086] Alternatively, there is a plurality of simulated attenuance
signals produced by the simulation under step 106. In this case
under step 108 a comparison of the measured attenuance signal or
features thereof with the simulated attenuance signal is conducted
to derive the fibrinogen level 20 of the sample. In a preferred
exemplary embodiment the differences of the initial and the final
value of the attenuance signals may be determined and interpolated
as a function of fibrinogen levels. From said function and the
difference of the measured initial and final attenuance the
fibrinogen level 20 of the sample may be determined. Other features
or the whole signal may be used in the alternative, or additionally
to optimize the determination of the fibrinogen level 20. Such
other features may be the slope of the signal (max rate), lag time,
time to maximum slope, time to plateau, or time to lower
plateau.
[0087] Additionally, it shall be noted that other outputs of the
simulation under step 106 may be used to determine the fibrinogen
level 20. One specific alternative may be the time evolution of the
average mass/length ratio of the fibrin fibers formed during the
polymerization process.
[0088] While the individual steps 102 to 108 may be carried out
manually, an automated or semi-automated process is preferred.
Moreover, method steps or the whole method 100 may be carried out
by means of a computer program implemented on a computing device
such as a common PC or a workstation. Additionally, the method
steps may be executed in different order than depicted in FIG. 7,
or may be performed in parallel in respect to one another. It may
also be possible to perform some simulation aspects in advance such
that in time critical situation only parts of the simulation have
to be executed.
[0089] Furthermore, simulated data may be stored and reused for
subsequent measurements, or to optimize the parameters of the model
itself. Finally, it shall be noted that the method 100 is not
limited to the model as disclosed herein, but may be used with
other models representative of fibrin polymerization as well.
[0090] While the invention has been illustrated and described in
detail in the drawings and foregoing description, such illustration
and description are to be considered illustrative or exemplary and
not restrictive; the invention is not limited to the disclosed
embodiments. Other variations to the disclosed embodiments can be
understood and effected by those skilled in the art in practicing
the claimed invention, from a study of the drawings, the
disclosure, and the appended claims.
[0091] In the claims, the word "comprising" does not exclude other
elements or steps, and the indefinite article "a" or "an" does not
exclude a plurality. A single element or other unit may fulfill the
functions of several items recited in the claims. The mere fact
that certain measures are recited in mutually different dependent
claims does not indicate that a combination of these measures
cannot be used to advantage.
[0092] A computer program may be stored/distributed on a suitable
non-transitory medium, such as an optical storage medium or a
solid-state medium supplied together with or as part of other
hardware, but may also be distributed in other forms, such as via
the Internet or other wired or wireless telecommunication
systems.
[0093] Any reference signs in the claims should not be construed as
limiting the scope.
* * * * *