Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical
Reexamination Certificate
2001-02-09
2003-03-18
Bui, Bryan (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Biological or biochemical
C702S084000, C702S150000, C600S415000
Reexamination Certificate
active
06535821
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of Invention
The present invention generally relates to a system and method for optimization of tomographic angiography utilizing a bolus propagation model, which can be applied to CT angiography that relies on bolus peak prediction, real-time CT observation and adaptive table transport.
2. Description of Prior Art
As known in the prior art, administration of a contrast material or bolus provides a short temporal window for optimally imaging the vasculature, lesions and tumors.
Optimization of contrast enhancement becomes increasingly crucial with the wide use of CT and Magnetic Resonant Image (“MRI”) technology, given the dramatically shortened image acquisition time.
Recently, CT began a transition into sub-second scanning, cone-beam geometry and real-time imaging with the introduction of multi-slice systems.
A number of clinical studies were reported on contrast enhancement for CT over the past decade. However, the results on modeling of CT contrast bolus dynamics are limited to the compartmental model, which describes contrast enhancement specific to each entire compartment (organ or vessel).
To obtain the highest image quality in CT angiography at the lowest dosage of contrast material, strategies for bolus administration and CT data acquisition must be individualized and optimized. It is desirable to scan when the intravascular concentration of contrast material is at its peak.
Scanning too early may result in over-estimation of stenosis, while scanning too late may result in overlap of venous structures.
Three methods have been developed to individualize scan timing:
(1) test-bolus timing,
(2) region of interest (ROI) threshold triggering, and
(3) visual cue triggering.
For the test-bolus method, there is a risk of decreasing target lesion conspicuity due to equilibration of the test-bolus. For the two triggering methods, they are vulnerable to patient motion, usually related to breathing, which may displace the target organ or vessel from the scan plane.
Moreover, one of the fundamental limitations with all the three methods is that they provide little data for matching the table translation to the contrast bolus propagation. Bolus dynamics is complicated by multiple interacting factors involving the contrast administration protocol, imaging techniques, and patient characteristics. In particular, the current patient table is translated at a pre-specified speed during data acquisition, which cannot be altered adaptively to chase the contrast bolus for optimally enhanced CT images.
With a pre-set scanning speed, it is difficult and often impossible to synchronize the central scanning plane with the longitudinal bolus position. This mis-alignment becomes more problematic to image quality when spiral scanning speed is fast (with multi-slice spiral CT), contrast volume is small and/or injection rate is high (leading to reduced peak duration), as well as when there are large or small capacity vessels, either from aneurysm formation or occlusive disease.
Therefore, there is a need to develop a new system and method for synchronization of contrast administration and CT imaging that can maximize the signal differences between arteries and background and can be utilized to provide better tomographic angiography.
SUMMARY OF THE INVENTION
The present invention is directed towards a system and method for optimization of contrast enhancement utilizing a bolus propagation model, which can be applied to CT angiography that relies on bolus peak prediction, real-time CT observation and adaptive table transport. In particular, the discrepancy between the bolus location predicted by a bolus propagation model and the real-time CT observation is reconciled via a computerized predictor such as a linear extrapolator or a Kalman filter and fed into an adaptive table transport system to drive the table to chase the contrast bolus for optimally enhanced CT images.
In one embodiment of the present invention, a system of utilizing bolus propagation for contrast enhancement has a monitoring means for measuring the position of a bolus moving along a path in a biological structure, wherein the biological structure has a plurality of organs and vessels and is positioned on a table. The system also has a processing means for performing the steps of determining a predicted position of the bolus using a bolus propagation model with a set of parameters prior to the arrival of the bolus at a location of the path, and comparing the predicted position of the bolus with the measured position of the bolus. The system further has a filtering means for reconciling discrepancy, if any, between the predicted position of the bolus and the measured position of the bolus to extrapolate a set of control parameters, and a control means for receiving the set of control parameters to adaptively transport the table to chase the motion of the bolus. The filtering means includes a computerized predictor such as a linear extrapolator or a Kalman filter.
In another embodiment, the present invention relates to a system for utilizing bolus propagation for contrast enhancement. The system has an output device for injecting a bolus into a biological structure having a plurality of organs and vessels and being positioned on a table, a scanner for generating CT fluoroscopy image data of the bolus along a path in the biological structure, and a processor, which performs the steps of determining a predicted position of the bolus using a bolus propagation model with a set of parameters prior to the arrival of the bolus at a location of the path by performing the substeps of:
(1) Defining an extended vascular operator for one of the plurality of organs and vessels with three parameters T, D and L, where T is the time counting from the bolus injection, D is the dispersion and L is the length of the path;
(2) Selecting a plurality of locations p
i
along the path, i=0, 1, . . . , N, N is an integer greater than one, where real-time measurements can be made on each location p
i
by the monitoring means;
(3) Selecting a time threshold value &egr; and a dispersion threshold value &dgr;;
(4) Defining a velocity variable A
i
and a relative dispersion variable B
i
for each of the plurality of locations p
i
along the path, where i=i+1;
(5) Setting A
i
=A
i−1
and B
i
=B
i−1
, wherein A
0
=L/T, and B
0
=D/T;
(6) Predicting the peak arrival time t(p
i
) and the relative dispersion B(p
i
) of the bolus at the location p
i
according to the following:
t
(
p
i
)=
t
(
p
i−1
)+(
p
i
−p
i−1
)/
A
i
,
and
B
(
p
i
)=
B
i
;
(7) Measuring the peak arrival time t′(p
i
) and the relative dispersion B′(p
i
) of the bolus at the location p
i
;
(8) If |t′(p
i
)−t(p
i
)|>&egr;, updating the velocity variable A
i
according to the following formula:
A
i
=(
p
i
−p
i−1
)/(
t′
i
−t′
i−1
);
(9) If |B′(p
i
)−B(p
i
)|>&dgr;, updating the relative dispersion B(p
i
) of the bolus according to the following formula:
B
i
=B
′(
p
i
);
(10) Updating T and D according to the following:
T=t
i
+(
L−p
i
)/
A
i
;
and
D=B
i
;
and
(11) repeating steps (6)-(10) until all points of interest in the plurality of locations p
i
along the path have been selected;
and comparing the predicted position of the bolus with the image data of the bolus.
Moreover, the system includes a computerized predictor such as a linear extrapolator or a Kalman filter for reconciling discrepancy, if any, between the predicted position of the bolus and the image data of the bolus to extrapolate a set of control parameters, and a table transport system for adaptively transporting the table to chase the motion of the bolus to the set of control parameters.
In yet another embodiment, the present invention relates to a computer-readable, digital storage device storing executable instructions which cause a processor to utilize
Vannier Michael W.
Wang Ge
Bui Bryan
Needle & Rosenberg PC
University of Iowa Research Foundation
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