CN114764133B - Ablation calculation method and ablation calculation system - Google Patents
Ablation calculation method and ablation calculation system Download PDFInfo
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- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
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- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
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- G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
- G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
- G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
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- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
- G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
- G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
- G01R33/5615—Echo train techniques involving acquiring plural, differently encoded, echo signals after one RF excitation, e.g. using gradient refocusing in echo planar imaging [EPI], RF refocusing in rapid acquisition with relaxation enhancement [RARE] or using both RF and gradient refocusing in gradient and spin echo imaging [GRASE]
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Abstract
The application discloses an ablation calculation method and an ablation calculation system, wherein the ablation calculation method comprises the following steps: scanning a target to be detected by using a gradient echo sequence containing i different echo times to obtain a phase diagram corresponding to the echo times, wherein i is a positive integer greater than or equal to 2; selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams; obtaining a temperature map according to the temperature difference map; calculating an ablation condition according to the temperature map; the ablation computing system comprises an ablation computing module capable of performing the ablation computing method of the present invention.
Description
Technical Field
The present application relates to the field of medical devices, and more particularly, to an ablation computing method and an ablation computing system.
Background
The magnetic resonance temperature imaging (Magnetic Resonance Temperature Imaging, MRTI) can realize noninvasive, real-time and in-vivo monitoring of temperature distribution and change in the tested object, and has important application in the ablation monitoring process of minimally invasive and noninvasive hyperthermia, such as magnetic resonance interstitial hyperthermia, focused ultrasound therapy and the like.
One of the current magnetic resonance temperature imaging methods is a temperature measurement method based on proton resonance frequency (Proton Resonance Frequency, PRF) displacement, and in the practical process, the temperature measurement method based on proton resonance frequency displacement is found to be greatly influenced by objective environmental factors such as magnetic resonance coil magnetic field uniformity, tissue magnetic susceptibility distribution non-uniformity, tissue motion caused by respiration/blood flow pulsation and the like, common errors caused by the induction include phase unwrapping errors, errors caused by magnetic susceptibility rapid change, errors caused by motion and the like, and the problem of great difference between a finally acquired temperature map and actual temperature is easily caused, so that the temperature map loses reference significance.
How to perform more accurate ablation calculation according to magnetic resonance data is a technical problem still to be solved in the art.
Disclosure of Invention
In order to solve the technical problems, the application provides an ablation computing method and a related ablation computing system.
In a first aspect of the present invention, there is provided an ablation calculation method comprising:
scanning a target to be detected by using a gradient echo sequence containing i different echo times to obtain a phase diagram corresponding to the echo times, wherein i is a positive integer greater than or equal to 2;
Selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
obtaining a temperature map according to the temperature difference map;
and calculating the ablation condition (of each pixel) according to the temperature map.
Further, in the method, the obtaining of the temperature difference map is performed as follows: subtracting the phase diagram of the reference time from the phase diagram of any time to obtain a phase diagram of the time, selecting at least one phase diagram corresponding to the echo time as a reference phase diagram, and calibrating the phase diagrams to be calibrated corresponding to other echo times based on the reference phase diagram to obtain a calibrated phase diagram, wherein the echo time corresponding to the reference phase diagram is smaller than the echo time corresponding to the calibrated phase diagram; a temperature difference map at that time is calculated using the reference phase difference map and the calibrated phase difference map.
Wherein the echo time corresponding to the at least one reference phase difference map does not exceed one of the following: 18ms,17ms,16ms,15ms,14ms,13ms,12ms,11ms,10ms,9ms,8ms,7ms,6ms,5ms or 4ms.
Further, in the method, the calibration is performed as follows:
according to the proportional relation between the phase difference diagram and the echo time, calculating to obtain an estimated value of the phase difference diagram to be calibrated based on the echo time and the reference phase difference diagram;
And unwrapping the phase difference diagram to be calibrated according to the phase periodicity by using the estimated value of the phase difference diagram to be calibrated to obtain the phase difference diagram after calibration.
Optionally, the ablation calculation method of the present invention further comprises the step of eliminating phase drift caused by the magnetic resonance system, (e.g., B0 drift error); further, in the step of eliminating the phase drift caused by the magnetic resonance system, a plurality of areas which have stable physical temperature and uniform tissues are selected as thermal reference points, and the phase drift correction is performed by subtracting the average phase difference of the thermal reference points or the average temperature variation of the thermal reference points from each phase difference image or the temperature variation graph.
Optionally, the ablation calculating method of the present invention further includes a step of correcting an error caused by magnetic susceptibility, the magnetic susceptibility correcting step being performed on a phase difference map or a temperature difference map, the step including:
the step of correcting magnetic susceptibility on the temperature difference map includes:
obtaining a first temperature map according to the reference phase difference map, obtaining a corresponding second temperature map according to the calibrated phase difference map,
judging whether the absolute value of the difference value between the temperature value corresponding to each pixel in the second temperature map and the temperature value corresponding to the corresponding pixel in the first temperature map exceeds a preset temperature threshold value, and if so, correcting the temperature value corresponding to the corresponding pixel in the second temperature map;
The step of performing susceptibility correction on the phase difference map includes:
and judging whether the absolute value of the difference value of the phase difference value corresponding to each pixel in the calibrated phase difference graph and the phase difference value corresponding to the corresponding pixel in the reference phase graph exceeds a preset phase difference threshold value, and if so, correcting the phase difference corresponding to the corresponding pixel in the calibrated phase difference graph.
Optionally, the ablation calculation method of the invention further comprises a step of correcting the motion induced phase error by removing the motion induced phase error by using a linear least squares fit of at least two sets of phase maps corresponding to different echo times at each pixel.
Optionally, the ablation computing method of the present invention further includes a step of acquiring a weighted temperature map obtained by weighting a temperature map obtained by at least one reference phase difference map and a temperature map obtained by at least one calibrated phase difference map. Wherein the at least one calibrated phase difference plot corresponds to an echo time of no less than 20ms,19ms,18ms,17ms,16ms,15ms,14ms,13ms, or 12ms.
The above optional steps of eliminating phase drift caused by the magnetic resonance system, correcting errors caused by magnetic susceptibility, correcting phase errors caused by motion, and acquiring weighted temperature maps are all within the scope of the present disclosure as selected individually, partially or fully as part of the ablation calculation method of the present invention.
Optionally, in the ablation calculating method of the present invention, the ablation of the pixels is calculated using the following formula:
wherein E is a Representing activation energy, a is a frequency factor, R is a universal gas constant, T (τ) is a function of temperature (°c) and time τ, T is the current time, and pixels with Ω values exceeding a set threshold (e.g., 1) are considered ablated. Other methods and parameters for temperature-based ablation calculations known to those skilled in the art may be used as an alternative as part of the present invention.
In a second aspect of the present invention, there is provided a storage medium having stored thereon program code which when executed implements the ablation calculation method of the present invention.
In a third aspect of the present invention, an ablation computing system is provided comprising an ablation computing module capable of performing the ablation computing method of the present invention. Further, the ablation calculation module may further include:
the information acquisition module is used for receiving or acquiring magnetic resonance information, wherein the magnetic resonance information at least comprises a phase diagram corresponding to echo time, which is obtained by scanning a target to be detected by using a gradient echo sequence containing i different echo times, and i is a positive integer greater than or equal to 2;
The temperature difference calculation module is used for selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
a temperature map calculation module, configured to obtain a temperature map according to the temperature difference map, where the temperature map may be a weighted temperature map;
and the ablation calculation module is used for calculating the ablation condition of each pixel according to the temperature map.
A phase drift correction module for performing the step of eliminating phase drift caused by the magnetic resonance system,
a susceptibility error correction module for performing the step of correcting susceptibility induced errors,
a motion error correction module for performing the step of correcting motion induced phase errors.
In a fourth aspect of the present invention, there is provided a laser interstitial thermal therapeutic apparatus comprising: the system comprises a host computer, laser ablation equipment and an optical fiber component, wherein the host computer comprises a processor and is loaded with program codes, and the program codes realize the ablation calculation method when being executed.
The innovative aspects of embodiments of the present invention include one or more of the following:
1. the problem of error occurrence during phase difference graphic wrapping of the echo sequence corresponding to partial echo time is solved;
2. the problems that the temperature is abnormal and the temperature and ablation conditions cannot be displayed due to the fact that the magnetic susceptibility of a part of the region is abnormal caused by temperature rise are solved;
3. Abnormal temperature errors caused by movements of cerebrospinal fluid, heart beat, etc., such as abnormal temperature in ventricle, are eliminated.
4. The method uses a non-traceability algorithm or an iterative algorithm, has small operation amount, saves calculation time, and can quickly obtain temperature and ablation results.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings may be obtained according to the provided drawings without inventive effort to a person skilled in the art.
Figure 1 is a diagram of amplitude, phase and temperature of magnetic resonance data acquired in an ex vivo and in vivo environment of the prior art;
FIG. 2 is a flow chart of an ablation calculation method according to an embodiment of the present application;
FIG. 3 is a phase diagram, a phase difference diagram, and a temperature diagram obtained as provided by one embodiment of the present application;
FIG. 4 is a partial flow chart of an ablation calculation method according to another embodiment of the present application;
FIG. 5 is a schematic diagram of an experimental apparatus provided in one embodiment of the present application;
FIG. 6 is a partial enlargement of a laser interstitial thermotherapy temperature map of an in vitro pork experiment according to one embodiment of the present application;
FIG. 7 is a graph showing temperature over time during experiments with gel tissue mimics (FIG. 7 (a)) or ex vivo pork (FIG. 7 (b)) provided in one embodiment of the present application;
FIG. 8 is a representative temperature plot of dog 01 in an in vivo experiment provided in one embodiment of the present application;
FIG. 9 is a graph showing laser interstitial hyperthermia ablation results for 3 representative dogs (dogs 01-03) provided in accordance with one embodiment of the present application;
fig. 10 is a schematic diagram of an estimated ablation predicted by an ablation calculation method for a post-ablation T2w image and all six other cases of different ablation laser dosages (dog 04-09) provided by an embodiment of the present application.
Detailed Description
The magnetic resonance temperature imaging can guide various energy delivery type treatment means, such as laser interstitial thermotherapy, focused ultrasound therapy, radio frequency ablation and the like, and monitor the temperature of target tissues and the ablation effect. The method of the invention is described by taking laser interstitial hyperthermia guided by magnetic resonance temperature imaging as an example, which is a minimally invasive treatment means and creates a new choice for treating tumors located at surgically challenging sites (anatomies or functionalities). The method can rapidly coagulate tissues and induce tumor cell necrosis through protein denaturation by applying a temperature of 50-80 ℃ or higher for several tens of seconds. Laser interstitial hyperthermia can more accurately target tumors and reduce discomfort and infective wind direction, and shorten patient hospitalization times, compared to open surgery. In the ablation process of laser interstitial hyperthermia, concurrent magnetic resonance thermal imaging plays an important role in more effectively ablating tumor cells and better protecting healthy surrounding cells and critical structures. Most laser interstitial hyperthermia ablation procedures depend on thermometry based on proton resonance frequency shift.
However, as described in the background art, the existing magnetic resonance temperature imaging method is greatly affected by factors such as environment, and is easy to cause a problem that the temperature map obtained finally is greatly different from the actual temperature.
During ablation of laser interstitial hyperthermia, the inventors found through research that the main sources of errors in the acquired temperature map were phase errors caused by unreeling misalignment, susceptibility errors and phase errors caused by movement. As the ablation laser dose changes, the susceptibility can lead to a decrease in image amplitude and corresponding errors in image phase, thereby destroying the heating center and its surrounding reconstructed temperature map. Errors in reconstructing the temperature map may lead to erroneous estimates of the ablation region, which may lead to variations in the therapeutic effect and thermal damage to critical tissue. Thus, accurate temperature imaging is critical to the effectiveness and safety of laser interstitial hyperthermia, especially when applied to tight ablation regions in brain tissue.
The inventors have found through further studies that the thermometry based on shift of proton resonance frequency is based on the following facts: the resonant frequency of hydrogen protons varies with the temperature in water molecules. For aqueous tissue, the local magnetic field variation with temperature can be described as:
Wherein α is a proton resonance frequency coefficient with temperature, and herein 0.008-0.015 ppm/. Degree.C. The corresponding resonance frequency change of the temperature-affected water protons can be expressed as:
Δf＝αγB 0 ·ΔT； (2)
wherein DeltaT represents temperature change, deltaf represents resonance frequency change, gamma represents gyromagnetic ratio, and B 0 Representing the static magnetic field strength.
Changes in resonance frequency due to temperature changes can be observed in the phases of complex magnetic resonance imaging. For a given interval TE of the gradient echo sequence, the relative temperature change Δt can be calculated from the phase difference ΔΦ, which equation can be expressed as:
the gradient echo sequence is a sequence used in a thermometry based on a shift in proton resonance frequency. From equation (3), the longer the gradient echo sequence, the greater the phase difference may be caused by the same temperature change, indicating that a higher temperature sensitivity may be obtained.
Referring to fig. 1, as the echo time of the gradient echo sequence increases, both the phase contrast and the phase wrap increase, which indicates that the temperature sensitivity is higher and the phase unwrapping procedure is more in the later echo time. In fig. 1, the amplitudes (upper row) and phases (second row) of the first to fourth echoes obtained by the gradient echo sequence containing 4 different echo times used in the embodiments of the present application are in (a) (ex vivo, pig brain) and (b) (in vivo). A temperature map (lower row) is calculated from each TE (echo time) setting using a conventional PRF algorithm. More phase wrapping occurs over longer echo times, as the image contrast increases accordingly. Note that intense laser heating can result in signal loss due to changes in susceptibility and can also translate into phase and temperature errors for pixels around the heating center. In vivo experiments, note that cerebrospinal fluid (Cerebrospinal Fluid, CSF) motion (motion) can cause inappropriately high temperatures on the MRTI, which is more pronounced in the previous echo, because shorter TEs have lower tolerance to similar phase errors introduced.
For example, inter-scan motion can be a major problem in thermometry based on proton resonance frequency shift measurement due to movement of cerebrospinal fluid in the brain. The magnitude and phase signals of the cerebrospinal fluid are often altered over the pulse gradient echo sequence by the normal dynamic motion of the cerebrospinal fluid, which may confound the temperature estimation. Cerebrospinal fluid movement may also cause pixel movement in the ventricles and surrounding ventricles, resulting in error in the phase contrast map. As shown in fig. 1b, the in vivo temperature map shows pseudo-hyperthermia in the third brain chamber due to cerebrospinal fluid movement. The temperature errors are more pronounced on pulse gradient echo sequences of shorter echo times, because they are less tolerant of the phase shift intensities introduced by the cerebrospinal fluid flow in (3).
In fact, the local magnetic field of the water protons should also take into account the magnetic susceptibility x 0 Equation (1) becomes:
wherein, the liquid crystal display device comprises a liquid crystal display device,indicating the local magnetic field change caused by susceptibility.
Further studies have found that laser heating can cause significant magnetization artifacts in GRE imaging around the laser tip. Still referring to fig. 1, the heating center (shown by the arrow in fig. 1 (a)) with sharp temperature changes shows serious signal loss on the order of longer echo time. Intra-voxel spin phase shift is caused by local magnetic field inhomogeneities caused by temperature and susceptibility changes.
Magnetization artifacts caused by laser heating, in particular in images corresponding to gradient echo sequences of longer echo times, are an important cause of errors. Still referring to fig. 1, in an ex vivo or in vivo experiment, the phase error around the heating center translates into a pseudo low temperature on the magnetic resonance thermal imaging. In general, summarizing the imaging process, it is recommended to use gradient pulse sequences with echo times as short as possible to minimize susceptibility artifacts. However, a longer echo time gradient pulse sequence may provide better temperature sensitivity and signal-to-noise ratio, which is currently a dilemma of choice.
In order to achieve the combination of temperature sensitivity, signal-to-noise ratio and low error, an embodiment of the present application provides an ablation calculation method, which includes:
scanning a target to be detected by using a gradient echo sequence containing i different echo times to obtain a phase diagram corresponding to the echo times, wherein i is a positive integer greater than or equal to 2;
selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
obtaining a temperature map according to the temperature difference map;
and calculating the ablation condition of each pixel according to the temperature map.
The ablation calculation method is characterized in that i groups of phase diagrams are obtained based on gradient echo sequences containing i different echo times, at least two groups of phase diagrams corresponding to different echo times are selected to obtain corresponding phase diagrams, and a temperature diagram is obtained according to the temperature difference diagrams. The inventor finds that the echo time of the gradient echo sequence is in a direct proportion relation with the size of the magnetic susceptibility artifact, so that the phase diagram obtained by the gradient echo sequence corresponding to the smaller echo time is least influenced by the magnetic susceptibility change caused by heating, and the image data of the phase diagram still keeps the correct phase, so that the temperature diagram can be obtained based on i groups of phase diagrams and phase difference diagrams obtained by the gradient echo sequence containing i different echo times, thereby reducing the error of the finally obtained temperature diagram and improving the accuracy of the obtained temperature diagram.
Furthermore, the ablation calculation method is not a traceability algorithm or an iterative algorithm, has small calculation amount, can provide a nearly real-time temperature map, and has higher reference significance.
An embodiment of the present application provides an ablation calculating method, as shown in fig. 2, including:
s101: scanning a target to be detected by using a gradient echo sequence containing i different echo times to obtain i groups of phase diagrams corresponding to the echo times, wherein i is a positive integer greater than or equal to 2;
In step S101, the minimum value and the maximum value of the echo time in the gradient echo sequence may be determined according to actual requirements, and in general, in order to reduce the susceptibility artifact caused by the susceptibility change as much as possible, the minimum value of the echo time in the gradient echo sequence may be the minimum value that can be obtained by the magnetic resonance temperature imaging device, and the maximum value of the echo time in the gradient echo sequence generally does not exceed the upper limit of the range of the echo time for imaging the target to be detected. For example, for head imaging, the echo time of the optional gradient time sequence is in the range of 3-30 ms, and the specific echo time included in the gradient echo sequence is in the range of the echo time.
Referring to fig. 3, and specifically to fig. 3 (a), the acquired phase diagram is shown in fig. 3 (a). Then, as shown in fig. 3 (b), a phase difference map is calculated by a complex subtraction procedure. Complex subtraction can avoid problematic phase wrapping.
The gradient echo sequence information containing i different echo times can be read or received from a server or other storage devices, or can be obtained in real time according to the setting of a staff.
S102: selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
optionally, between step S102 and step S103, static magnetic field intensity drift correction for the phase diagram and the phase difference diagram may be further included to eliminate errors caused by the static magnetic field intensity.
S103: and obtaining a temperature map according to the temperature difference map.
S104: calculating the ablation of each pixel from the temperature map, the ablation may be calculated using various methods of calculating the ablation based on temperature and time parameters, for example using the following formula:
wherein E is a Representing activation energy, a is a frequency factor, R is a universal gas constant, T (τ) is a function of temperature (°c) and time τ, T is the current time, and pixels with Ω values exceeding a set threshold (e.g., 1) are considered ablated.
Possible implementations of each step of the ablation computation method provided in the embodiments of the present application are described below.
Based on the above embodiments, in one embodiment of the present application, the specific steps for obtaining the temperature difference map include:
subtracting the phase map of the reference time from the phase map of any one of the different times to obtain a phase difference map of the time, wherein the reference time is any time before energy (such as heat energy, light energy, radio frequency ablation and cryoablation) is transmitted to the target tissue, preferably is a time immediately before energy transmission, such as a time about to transmit energy; selecting a phase difference diagram corresponding to at least one echo time at the moment as a reference phase difference diagram, and calibrating the phase difference diagrams corresponding to other echo times to obtain a calibrated phase difference diagram, wherein the echo time corresponding to the reference phase difference diagram is smaller than the echo time corresponding to the calibrated phase difference diagram;
A temperature difference map at that time is calculated using the reference phase difference map and the calibrated phase difference map.
Optionally, the echo time of the reference phase difference map has a value less than or equal to 18ms, preferably the echo time of the reference phase difference map has a value not exceeding 17ms,16ms,15ms,14ms,13ms,12ms,11ms,10ms,9ms,8ms or 7ms, more preferably the echo time of the reference phase difference map has a value not exceeding 6ms,5ms or 4ms.
Alternatively, a phase map corresponding to the minimum echo time in the gradient echo sequence may be used as the reference phase map, and the reference phase map may be obtained based on the reference phase map to minimize the influence of the change in susceptibility due to heating to which the phase map is subjected as much as possible. As previously mentioned, the minimum echo time in the gradient echo sequence may be the minimum value that can be taken by the magnetic resonance temperature imaging device.
The step of selecting a phase difference diagram corresponding to at least one echo time at the moment as a reference phase difference diagram and calibrating the phase difference diagrams corresponding to other echo times comprises the following steps:
using the reference phase difference diagram and the phase difference diagram corresponding to the echo time to be calibrated, and calculating to obtain an estimated value of the phase difference diagram corresponding to the echo time to be calibrated based on the phase difference of the echo time and the reference phase difference diagram according to the proportional relation between the phase difference and the echo time; and then deconvoluting the phase difference to be calibrated according to the phase periodicity by using the estimated value to obtain the calibrated phase difference.
On the basis of the above embodiment, in another embodiment of the present application, the ablation calculating method further includes:
s105: a step of eliminating phase drift caused by the magnetic resonance system, which is performed on a phase difference map or a temperature difference map.
The step of eliminating the phase shift caused by the magnetic resonance system on the phase difference graph comprises the following steps:
selecting a plurality of thermal reference points (Region ofInterest, ROIs) by subtracting an average phase difference of the thermal reference points from each phase difference map;
the step of eliminating phase drift caused by the magnetic resonance system on the temperature difference map comprises the steps of:
the average temperature difference of any of the thermal reference points is subtracted from the temperature difference map for correction.
On the basis of the above embodiment, in another embodiment of the present application, the ablation calculating method further includes:
s106: a step of correcting magnetic susceptibility, which is performed on a phase difference map or a temperature difference map;
the step of correcting magnetic susceptibility on the temperature difference map includes:
obtaining a first temperature map according to the reference phase difference map, and obtaining a corresponding second temperature map according to the calibrated phase difference map;
Optionally, determining a preset area in the first temperature map and each of the second temperature maps;
judging whether the absolute value of the difference value between the temperature value corresponding to each pixel in the second temperature map and the temperature value corresponding to the corresponding pixel in the preset area in the first temperature map exceeds a preset temperature threshold value, and if so, correcting the temperature value corresponding to the corresponding pixel in the second temperature map; there are various ways of correcting, for example, the temperature value of the first temperature map in the pixel may be used to replace the temperature value of the second temperature map, or the temperature value of the adjacent pixel in the second temperature map may be used to replace the temperature value of the pixel in the second temperature map, or an approximate temperature may be fitted to replace the temperature value of the second temperature map based on the temperature value of the adjacent pixel and the temperature value of the first temperature map;
the step of performing susceptibility correction on the phase difference map includes:
determining a preset area in the reference phase difference diagram and the calibrated phase difference diagram;
judging whether the absolute value of the difference value of the phase difference value corresponding to each pixel in the calibrated phase difference diagram and the corresponding pixel in the preset area in the reference phase diagram exceeds a preset phase difference threshold value, if so, correcting the phase difference in the calibrated phase difference diagram, wherein the correction method is similar to the previous one and is not repeated.
On the basis of the above embodiment, in yet another embodiment of the present application, the ablation calculating method further includes:
s107: a step of correcting a phase error caused by the motion performed on the phase difference map or the temperature difference map;
the step of correcting the motion-induced phase error performed on the phase difference map includes:
removing motion-induced phase errors by using a linear least squares fit of the reference phase difference map and the calibrated phase difference map at each pixel;
the step of correcting the motion-induced phase error performed on the temperature difference map includes:
obtaining a first temperature map according to the reference phase difference map, and obtaining a corresponding second temperature map according to the calibrated phase difference map;
the motion-induced phase error is removed by a linear least squares fit at each pixel using the first temperature map and the second temperature map.
Still referring to fig. 4 (c), fig. 4 (c) shows the phase difference (first row) and the relative temperature change (second row) as a function of time without (left) and with (right) motion error correction. For shorter echo times, the phase error Δφ (x, y) bias Larger temperature deviations may be introduced but may be properly eliminated after the linear least squares fit.
As described above, steps S105, S106 and S107 may be performed on the phase difference map level or on the temperature difference map. I.e. the step of eliminating the phase shift caused by the magnetic resonance system is performed on the phase difference map and/or the temperature difference map, and the step of correcting the magnetic susceptibility is performed on the phase difference map and/or the temperature difference map. The step of correcting the motion induced phase error is performed on a phase difference map and/or a temperature difference map.
Still referring to fig. 3, fig. 3 (c) shows a unwrapped and drift corrected phase difference map, fig. 3 (d) shows a temperature map, fig. 3 (e) shows a susceptibility corrected image, and fig. 3 (f) shows a motion error corrected image.
On the basis of the above embodiment, in yet another embodiment of the present application, the obtaining a temperature map according to the temperature difference map includes:
s1031: calculating the temperature by using the reference phase difference diagram and the calibrated phase difference diagram, and weighting the calculated temperature to obtain a temperature diagram of the target to be measured;
or (b)
And carrying out weighted average on the reference phase difference diagram and the calibrated phase difference diagram to obtain an average temperature difference, and calculating a temperature diagram of the target to be measured according to the average temperature difference.
In step S1031, the weighting may be various weighting methods, such as average weighting, or the temperature map may be a temperature map corresponding to a single echo time, that is, the weighting coefficient of the temperature map is 1, and the weighting coefficients of the other phase temperature maps are 0.
After step S1031, the method may further include:
s108: and carrying out multiple interpolation processing on the temperature map of the target to be detected, and calculating an ablation area boundary by using the temperature map of the target to be detected after the interpolation processing.
The purpose of performing multiple interpolation processing on the temperature map of the target to be measured is to obtain a smoother ablation region boundary, and the specific number of times of difference processing can be 2 or 3 times.
In calculating the boundary of the ablation region, the following formula is specifically used:
wherein E is a The activation energy is represented by A being a frequency factor, R being a universal gas constant, T (τ) being a function of temperature (. Degree. C.) and time τ, T being the current time. Pixels with omega values exceeding a set threshold (e.g. 1) are considered ablated.
The ablation calculation method provided in the embodiment of the present application is verified in combination with a specific experiment.
The gel tissue simulant (gel mold) is heated using a laser ablation system comprising a 10w, 480 nm diode laser and a cooled laser applicator system. Phase (C) Bit images were acquired using a multi-echo time gradient echo sequence using 16 receive coils in a 3T MR scanner (Ingenia, philips Healthcare, best, netherlands): flip angle = 30 °, TE = 6/12/18/24ms, tr = 22ms, matrix = 176 x 176, fov = 200x 200mm 2 Slice thickness = 5mm,3 s/image.
As shown in fig. 5, two MR compatible fiber optic temperature probes were also inserted into the tissue simulant with the probe tip positioned near the ablating fiber to obtain the gel temperature at each point. Since the fiber optic probe is affected by the ablating fiber during heating, the thermometer monitors only the cooling phase. In fig. 5. Specifically, fig. 5 shows the insertion of an ablation fiber and two fiber optic temperature probes in a gel tissue simulator, with a gel filled reference tube fixed around as an insulated reference.
In vitro experiments of pork and pig brain were performed using the same scan parameters as the tissue mimic experiments. Two experiments were performed on each type of tissue (gel, pork, pig brain), one of which was heated by several laser cycles and the other was continuously heated and cooled. The root mean square error between the MR measured temperature and the fiber measured temperature is calculated as a measure of temperature accuracy.
Du Bingou in vivo experiments have been approved by the ethical review Committee of the university of Qinghai. Nine adults Du Bingou received laser interstitial hyperthermia. The heating process was monitored on a 3T MR scanner (Ingenia, philips Healthcare, best, netherlands) with 32 receiver head coils using a multi-echo time gradient echo sequence.
After an ablation procedure, in order to obtain detailed information about the actual extent of the ablation zone, post-ablation images were acquired, including T1 gadolinium (t1+gd) contrast images, fluid attenuation inversion recovery (FLAIR), diffusion weighted MR (distortion corrected by FSL 5.0 by augmentation or by EPSI methods), and T2 weighted images.
Still referring to fig. 3 and 4, fig. 3 and 4 illustrate one example of temperature calculation for the ablation calculation method provided by embodiments of the present application. FIG. 3 (a), at one time obtained during laser hyperthermia, first a coil combination phase image is obtained by a multiple TE echo sequence; fig. 3 (b), then a phase difference map is obtained, and white arrows indicate phase wrapping occurring on the phase map around the heating center; fig. 3 (c) shows a phase difference diagram after phase unwrapping and B0 drift correction. Fig. 3 (d) is a temperature map calculated from fig. 3 (c) according to the PRF offset method. White arrows highlight susceptibility induced errors. Fig. 3 (e) temperature diagram after susceptibility correction. White arrows show residual CSF movement induced errors. Fig. 3 (f) temperature diagram of motion correction.
In fig. 4, one exemplary method flow for a representative pixel includes: step 1, obtaining a phase difference image and a phase difference image obtained by unwrapping a reference phase difference image (TE 1), wherein the phase difference image corresponding to some echo time is wrapped under the condition of rapid temperature change as shown by black arrows. Step 2, a phase unwrapping map is acquired, step 3, a static magnetic field strength (magnetic resonance system) drift correction, namely a B0 drift correction is used for reducing system fluctuation, and step 4), a phase error correction caused by magnetic susceptibility is performed, and a temperature error caused by magnetic susceptibility change (black arrow) on a longer echo time is corrected by using the shortest echo Time (TE). Step 5, phase error correction caused by motion. The first and second line graphs are the time-dependent phase difference and the corresponding time-dependent temperature change, respectively. For multiple echo times, the motion-induced phase error (black arrow) is nearly the same, thus resulting in more pronounced temperature errors at shorter TEs. The result of correcting the motion error shows a smoother phase and temperature profile.
Tissue mimics and ex vivo experimental results:
fig. 6 shows a representative temperature profile of an ex vivo pork experiment during laser interstitial thermotherapy. Six representative images (# 50 represents the 50 th frame, #146 represents the 146 th frame), and so on) are selected from 300 frames (3 s/frame) acquired during the thermal cycle. The first row and the second row are each phase unwrapped using a conventional phase unwrapped method and the multi-echo time based phase unwrapped method (multi-TE unwrapped) presented in the embodiments of the present application. With the prior art phase unwrapping method, the pixels on the temperature map would be severely damaged due to the change in susceptibility caused by the laser heat, and cannot be recovered even without using the laser. The technical principle is as follows: the phase unwrapping method of the prior art is applied to the time dimension for phase jump detection, and if the phase difference map of the current frame is unwrapped by mistake, all the subsequent frames are affected. On the other hand, the ablation calculation method is performed on the basis of multi-echo dimension, so that interference from the previous frame is avoided. The third row is a single echo time temperature plot with phase unwrapping and susceptibility correction, with the damaged pixels around the heating center having recovered correctly. The last line is the multi-echo time data combination result using the ablation calculation method provided by the embodiments of the present application. The resulting magnetic resonance thermal imaging is shown to be more uniform in temperature at the hot spot.
Fig. 7 shows the temperature over time during the gel tissue simulant (fig. 7 (a)) or the ex vivo pork (fig. 7 (b)) experiments, calculated from two thermometry fiber measurements (red bars) and the method provided in the examples of the present application, respectively (dashed black bars). In the case of multiple heating (fig. 7 (a)) or single heating (fig. 7 (b)), the temperature-time behavior of the Proton Resonance Frequency (PRF) calculation is very matched to the measured temperature-time measured by the fiber optic temperature probe (also called thermometric fiber) during the cool down phase. Table 2 lists Root Mean Square Error (RMSE) values between MR calculated values and thermometry fiber measurements, which represent the temperature accuracy of the proposed algorithm. Experiment 1 performed several laser cycles of heating, while experiment 2 was a continuous heating and cooling phase. The results show that in most cases the RMSE error of the gel, pork or pig brain tissue is less than 0.5 ℃. In fig. 7, a probe (left) represents a left side temperature measuring optical fiber, and a probe (right) represents a right side temperature measuring optical fiber.
Table 2. The method provided by the examples of the present application compares between the temperature measured by the fiber and the temperature calculated by the MR.
Abbreviations: RMSE, root mean square error; experiment, experiment L (R), left (right) fiber optic temperature probe.
Fig. 8 shows a representative temperature profile of dog 01 in an in vivo experiment. It should be noted that the ablation zone is located near the third ventricle and the lateral ventricle. 100 frames (3 s/frame) of images acquired during laser ablation are selected to be superimposed on post-ablation T2w magnetic resonance thermal imaging. From top to bottom are temperature maps calculated by prior art algorithms from single echo Time (TE) data (te=6 ms and te=24 ms), respectively, and from multiple (joint) TE echo sequences using the proposed algorithm of the present invention. The first line (te=6 ms) shows the third ventricle and the pseudo-high temperature in the ventricle, indicating that the short TE calculation temperature is severely affected by CSF flow artefacts. CSF-induced third brain indoor artifact (indicated by white arrow) is still present in the second row (te=24 ms), but well suppressed by the proposed joint TE echo sequence algorithm. The second row shows that a longer TE (te=24 ms) can provide smoother boundaries and better temperature SNR than a shorter TE (te=6 ms), but as described above, pixels around the heating center can be damaged due to changes in susceptibility. On the other hand, we propose a method that integrates the information of multiple echoes, so that the obtained temperature map simultaneously eliminates CSF-induced errors and susceptibility-induced errors, showing a more uniform and symmetrical heating region.
Figure 9 shows laser interstitial thermotherapy ablation results for 3 representative dogs (dogs 01-03). The first column is T2w images after thermal ablation and gadolinium administration (post-operative-T 2 ). The location of the ablative fibers can be clearly shown on T2w MRI. The second column shows the final estimated ablation lesions at a given laser dose, and the proposed method of the present invention, superimposed on the ablated T2w image in red (darker color on the gray scale). Thus demonstrating good agreement between the estimated ablations calculated by the method of the present invention and the post-ablative MRI. The area of the ablation zone estimated by the method of the invention is displayed in the upper left corner of the ablation image. The third column is a representative temperature map obtained when laser heating is most intense. The last three columns are post-ablation FLAIR, DWI and T1w images, respectively, after gadolinium administration. They all show a sharp transition between dead tissue and living tissue.
Figure 10 shows post-ablation T2w images of all other six cases of different ablative laser doses (dog 04-09) and final algorithmic predicted lesion estimates. The calculated ablation values (second row) match well with the post-ablation evaluation values (first row). The algorithmically estimated ablation region is shown in the upper left corner of the T2w image. The laser ablated area ranges from less than 30 square millimeters to approximately 90 square millimeters, depending on the duration of the laser heating.
The above experimental results show that the error caused by the magnetic susceptibility in the proton resonance frequency temperature map caused by heating the laser itself can be corrected using the ablation calculation method provided by the embodiments of the present application. We first propose the application of a multi-echo time gradient echo pulse sequence to magnetic resonance thermal imaging by proton resonance frequency shift method. Multiple gradient echo sequences can provide more information than single echo sequences without additional scan time, and provide new methods for phase unwrapping and artifact cancellation.
Shorter echo times can tolerate susceptibility artifacts but are sensitive to noise, while longer echo times have better temperature sensitivity and signal-to-noise ratio but are greatly affected by susceptibility artifacts. The ablation calculation method provided by the invention combines the advantages of different echoes to obtain a better temperature map measurement result. Moreover, the ablation calculation method can remarkably improve the robustness and the signal-to-noise ratio of the magnetic resonance thermal imaging, thereby avoiding damage to healthy tissues caused by misestimation of low temperature.
The method of the present invention also has excellent cerebrospinal fluid flow error suppression capability and can provide accurate temperature measurements in or around the ventricle. Compensating for errors caused by cerebrospinal fluid movements is clinically important for laser interstitial hyperthermia treatment of periventricular brain lesions. Furthermore, the proposed algorithm is online compatible, does not require iterative calculations, and is therefore well suited for magnetic resonance thermal imaging, since a very near real-time temperature map is required.
The following describes a magnetic resonance temperature imaging system provided in an embodiment of the present application, and the magnetic resonance temperature imaging system described below may be referred to in correspondence with the ablation calculation method described above.
Accordingly, embodiments of the present application also provide an ablation computing system, which includes an ablation computing module capable of performing the ablation computing method of the present invention. Further, the ablation calculation module may further include:
the information acquisition module is used for receiving or acquiring magnetic resonance information, wherein the magnetic resonance information at least comprises a phase diagram corresponding to echo time, which is obtained by scanning a target to be detected by using a gradient echo sequence containing i different echo times, and i is a positive integer greater than or equal to 2;
the temperature difference calculation module is used for selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
a temperature map calculation module, configured to obtain a temperature map according to the temperature difference map, where the temperature map may be a weighted temperature map;
and the ablation calculation module is used for calculating the ablation condition of each pixel according to the temperature map.
A phase drift correction module for performing the step of eliminating phase drift caused by the magnetic resonance system,
A susceptibility error correction module for performing the step of correcting susceptibility induced errors,
a motion error correction module for performing the step of correcting motion induced phase errors.
In a fourth aspect of the present invention, there is provided a laser interstitial thermal therapeutic apparatus comprising: the system comprises a host computer, laser ablation equipment and an optical fiber component, wherein the host computer comprises a processor and is loaded with program codes, and the program codes realize the ablation calculation method when being executed.
Another magnetic resonance temperature imaging system is provided according to an embodiment of the present application, including:
a data transmission module configured to receive the magnetic resonance sequence images and to determine image integrity;
a temperature calculation module configured to select a sequence, calculate a phase difference, calibrate a phase difference, calculate a temperature;
a temperature display module configured to display the temperature in a pseudo-color pattern or isotherm pattern;
an ablation calculation module configured to calculate and display an ablation result;
wherein the system performs a complete calculation for no more than 1s.
In some embodiments of the present application, the system preferably does not take more than 0.5s, most preferably not more than 0.1s, for a complete calculation.
Accordingly, embodiments of the present application also provide a magnetic resonance temperature imaging system, including: a memory and a processor;
the memory is configured to store program code, and the processor is configured to invoke the program code, where the program code is configured to perform the ablation calculation method according to any of the embodiments described above.
Correspondingly, the embodiment of the application also provides a storage medium, wherein the storage medium stores program codes, and the program codes are executed to realize the ablation calculation method of any embodiment.
In summary, the embodiment of the application provides an ablation computing method and a related device, wherein the ablation computing method is not a retrospective algorithm or an iterative algorithm, has small operand, can provide a nearly real-time temperature map, and has higher reference significance.
Features described in the embodiments in this specification may be replaced or combined with each other, and each embodiment is mainly described in the differences from the other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. An ablation computation method, comprising:
scanning a target to be detected by using a gradient echo sequence containing i different echo times to obtain a phase diagram corresponding to the echo times, wherein i is a positive integer greater than or equal to 2;
selecting at least two groups of phase diagrams corresponding to different echo times to obtain corresponding temperature difference diagrams;
obtaining a temperature map according to the temperature difference map;
calculating an ablation condition according to the temperature map;
wherein the obtaining of the temperature difference map is performed by:
the phase diagram of any moment is used for subtracting the phase diagram of the reference moment to obtain a phase diagram of the moment, the phase diagram corresponding to at least one echo time is selected as a reference phase diagram, the phase diagrams to be calibrated corresponding to other echo times are calibrated based on the reference phase diagram, and a calibrated phase diagram is obtained, wherein the echo time corresponding to the reference phase diagram is smaller than the echo time corresponding to the phase diagram calibrated by the reference phase diagram; a temperature difference map at that time is calculated using the reference phase difference map and the calibrated phase difference map.
2. The ablation computing method according to claim 1, wherein the calibration is performed as follows:
According to the proportional relation between the phase difference diagram and the echo time, calculating to obtain an estimated value of the phase difference diagram to be calibrated based on the echo time and the reference phase difference diagram;
and unwrapping the phase difference diagram to be calibrated according to the phase periodicity by using the estimated value to obtain a calibrated phase difference diagram.
3. The ablation computing method of claim 1, further comprising the step of eliminating phase drift caused by the magnetic resonance system.
4. The ablation computing method according to claim 3, wherein in the step of eliminating the phase drift caused by the magnetic resonance system, a plurality of regions which are stable in physical temperature and uniform in tissue are selected as thermal reference points, and the phase drift correction is performed by subtracting the average phase difference of the thermal reference points or the average temperature variation of the thermal reference points from each phase difference image or the temperature variation map.
5. The ablation computing method according to claim 1, further comprising a step of correcting an error caused by magnetic susceptibility, the step of correcting magnetic susceptibility being performed on a phase difference map or a temperature difference map, the step comprising:
the step of correcting magnetic susceptibility on the temperature difference map includes:
Obtaining a first temperature map according to the reference phase difference map, obtaining a corresponding second temperature map according to the calibrated phase difference map,
judging whether the absolute value of the difference value between the temperature value corresponding to each pixel in the second temperature map and the temperature value corresponding to the corresponding pixel in the first temperature map exceeds a preset temperature threshold value, and if so, correcting the temperature value corresponding to the corresponding pixel in the second temperature map;
the step of performing susceptibility correction on the phase difference map includes:
and judging whether the absolute value of the difference value of the phase difference value corresponding to each pixel in the calibrated phase difference graph and the phase difference value corresponding to the corresponding pixel in the reference phase difference graph exceeds a preset phase difference threshold value, and if so, correcting the phase difference corresponding to the corresponding pixel in the calibrated phase difference graph.
6. The ablation computing method according to claim 1, further comprising a step of correcting a motion-induced phase error by removing the motion-induced phase error by using a linear least squares fit of at least two sets of phase maps corresponding to different echo times at each pixel.
7. The ablation calculation method according to any one of claims 1 to 6, wherein the temperature map is a weighted temperature map obtained by weighting a temperature map obtained by at least one reference phase difference map and a temperature map obtained by at least one calibrated phase difference map.
8. The ablation calculation method of claim 1, wherein the ablation is calculated using the formula:
wherein E is a The activation energy is represented by a frequency factor, R is a universal gas constant, T (τ) is a function of temperature (c) and time τ, T is the current time, and pixels with Ω values exceeding a set threshold are considered ablated.
9. A storage medium having stored thereon program code which, when executed, implements the ablation calculation method of any of claims 1 to 8.
10. An ablation computing system comprising an ablation computing module capable of performing the ablation computing method of any one of claims 1 to 8.
11. A laser interstitial hyperthermia apparatus, comprising: a host computer, a laser ablation device and a fiber optic assembly, the host computer comprising a processor loaded with program code that when executed implements the ablation calculation method of any of claims 1-8.
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