Determining a trigger signal for imaging

Abstract

The invention provides a system (100) and a method for determining a trigger signal for imaging with an imaging system (40). The method comprises the steps of: measuring (S10) a patient-specific property of a patient (30), the patient-specific property being measured while the patient (30) is positioned at a first position (51) relative to the imaging system (40); generating (S20) a patient-specific model based on the patient-specific property, measuring (S30) a trigger waveform of the patient (30). The trigger waveform is measured while the patient (30) is positioned at a second position (52) relative to the imaging system (40). The second position (52) is different from the first position (51); determining (S40) the trigger signal based on the patient-specific model and the trigger waveform. The trigger signal is configured to trigger the imaging system (40) to acquire images of the patient (30) in a time-resolved manner.

Description

Technical Field

[0001] The present invention relates to a system and method for determining a trigger signal for imaging using an imaging system. Background Technology

[0002] Electrocardiography (ECG) and contact photoplethysmography (PPG), such as those measured with a finger pulse oximeter, have been used in standard magnetic resonance imaging (MRI) and computed tomography (CT) systems for triggering or gating scans of the heart.

[0003] MRI typically uses ECG-based triggering for scans that need to be synchronized with the heartbeat and / or cardiac phasing. ECG measurements have a so-called R-peak, which indicates the electrical activity that begins myocardial contraction, i.e., the onset of systole. Based on the R-peak, an MRI trigger sequence is initiated, including a pre-pulse and multiple acquisition windows. Such ECG-based triggering can suffer from drawbacks such as complex electrode placement and multiple wires, which can limit patient comfort and degrade image quality due to magnetic field interference.

[0004] Therefore, the feasibility of using camera-based PPG on the human face for cardiac-triggered MRI has emerged. Fully automated or semi-automated non-contact camera-PPG solutions can significantly simplify clinical MRI workflows because they eliminate the need for contact sensors and remove interference from magnetic fields on the signal.

[0005] However, a potential limitation of camera-PPG-based triggering compared to ECG-based triggering is the patient-specific delay between the R-peak commonly used for cardiac triggering and the triggering signal from the PPG. This delay is caused by the pulse travel time from the heart to the surrounding skin and can lead to inaccurate triggering unless compensated for.

[0006] US Patent 2017055934A1 discloses a method and system for determining a trigger signal. The method for determining a trigger signal for an imaging device is based on a film received from a surface of a first body part of a patient. In one embodiment, image values ​​within a region of the image in the film are averaged. Averaging reduces noise in the image values ​​within the region. Based on the averaging, the film is transformed into a time signal series. The transformation occurs in such a way that the time series is a measure of the temporal pattern of blood circulation in the region.

[0007] Camera-based PPGs require a significant amount of processing to achieve robust trigger detection. This can lead to costly delays in the workflow before an actual trigger scan can begin.

[0008] Therefore, there is a need to improve the speed and accuracy of triggered imaging. Summary of the Invention

[0009] The purpose of this invention is to provide a method and system for improving the speed and accuracy of triggered imaging.

[0010] This invention is defined by the independent claims. Advantageous embodiments are defined in the dependent claims.

[0011] According to a first aspect of the present invention, a method is provided for determining a trigger signal for imaging using an imaging system. The method includes the following steps:

[0012] Measure patient-specific characteristics. Measure the patient-specific characteristics while the patient is positioned relative to the imaging system in a first location.

[0013] A patient-specific model is generated based on the aforementioned patient-specific characteristics;

[0014] The trigger waveform of the patient is measured. The trigger waveform is measured when the patient is positioned at a second location relative to the imaging system. The second location is different from the first location.

[0015] A trigger signal is determined based on the patient-specific model and the trigger waveform. The trigger signal is configured to trigger the imaging system to acquire images of the patient in a time-resolved manner.

[0016] The patient-specific characteristic is a measured characteristic related to the patient's physiological or physical characteristics, such as, but not limited to, heart rate, respiration, oxygenation, blood pressure, cardiac cycle, temperature, weight, height, body mass index, etc. The patient-specific characteristic can be a physiological measurement constant, one or more measurement points, amplitude, frequency, phase, shape, signal-to-noise ratio, etc. This characteristic or a combination of characteristics can be used to model patient-specific parameters in the patient-specific model. Similarly, the trigger waveform is a time-resolved measurement of the patient's physiological parameters, such as, but not limited to, heart rate, respiration, oxygenation, cardiac cycle, temperature, etc. The trigger signal directly or indirectly triggers the acquisition of an image of the patient using an imaging system at a certain moment.

[0017] The proposed method is potentially advantageous for the speed and accuracy of imaging triggering workflows because one or more patient-specific characteristics can be measured before the patient is positioned at the second location where the trigger waveform is measured, and a patient-specific model can be generated based on these characteristics. This second location may also be the patient's position when the trigger imaging system acquires an image of the patient. In this way, the combination of patient-specific information and the measured trigger waveform can form the basis for accurate imaging triggering without causing unnecessary delays to the workflow.

[0018] In an embodiment of the invention, in a first position, the anatomical structure of the patient of interest is substantially located outside the bore of the imaging system, and in a second position, the anatomical structure of the patient of interest is substantially located inside the bore of the imaging system.

[0019] The patient's anatomy of interest is part of the patient, where the imaging system determines the body parts to be triggered and / or imaged. Patient-specific characteristics can be measured outside the imaging system's chamber (e.g., during patient preparation), reducing in-chamber patient time. This can shorten overall workflow time and improve patient comfort. The imaging system's chamber can be, for example, that of a computed tomography (CT) system, a magnetic resonance imaging (MRI) system, or a molecular imaging system (such as positron emission tomography (PET) or single-photon emission computed tomography (SPECT)), or any combination of these systems.

[0020] In embodiments of the present invention, the trigger waveform includes a waveform from photoplethysmography (PPG), and the step of measuring the trigger waveform includes measurement using a sensor (preferably a camera).

[0021] Using, for example, a camera-based PPG to measure the trigger waveform, instead of using multiple electrocardiogram (ECG) sensors that come into contact with the patient, can have several advantages, such as automating or simplifying the workflow and avoiding magnetic field interference with the ECG signal.

[0022] The sensor is preferably, for example, a 2D or 3D camera sensor or the like, configured to non-contactly measure PPG parameters from visible or infrared light or other wavelengths. However, other sensor technologies may also be considered for measuring waveforms derived from the PPG, such as transmissive or reflective PPG sensors that are close to or in contact with the patient, non-contact measurements using RADAR or LIDAR, etc.

[0023] In embodiments of the present invention, the patient-specific characteristics include characteristics derived from PPG, and the step of measuring the patient-specific characteristics includes measurement using a sensor (preferably a camera).

[0024] Similar to trigger waveforms, using, for example, camera-based PPG to measure patient-specific parameters (alone or in combination with other measurements) can accelerate and streamline imaging and / or patient preparation workflows.

[0025] The sensor used to measure patient-specific characteristics (including characteristics derived from PPG) can be the same sensor used to measure the trigger waveform. The sensor can also be a separate sensor of the same, similar, or different type or function as the sensor used to measure the trigger waveform. For example, both sensors could be configured to measure camera-based PPG signals.

[0026] In an embodiment of the present invention, the patient-specific model includes a patient-specific PPG waveform profile.

[0027] Modeling a patient-specific model that includes a PPG waveform profile (e.g., template morphology and / or waveform amplitude) facilitates rapid and accurate imaging triggering. This can be especially important when the trigger waveform includes waveforms derived from the PPG.

[0028] In embodiments of the present invention, the patient-specific model includes patient-specific pulse transit time.

[0029] Similar to patient-specific waveform profiles, information about patient-specific pulse transit time may be helpful for rapid and accurate imaging triggering.

[0030] In embodiments of the present invention, the patient-specific model includes a patient-specific reliability factor based on camera PPG parameters.

[0031] Patient-specific reliability factors can provide an indication of the reliability, quality, and / or robustness of a camera-based PPG for a specific patient and / or situation. For example, if reliability is low, additional or alternative measurements of the camera-based PPG may be required to ensure accurate triggering based on the trigger waveform. Obtaining this information at an early stage can save borehole time and / or avoid the need for repeated image acquisition.

[0032] In an embodiment of the present invention, the step of determining the trigger signal includes calculating a plurality of PPG markers, wherein the PPG markers are derived from the trigger waveform and / or the patient-specific PPG waveform profile, wherein the PPG markers are configured to predict R peaks.

[0033] PPG markers are specific PPG features of a PPG waveform, such as pulse interval, waveform characteristics, phase, etc. Calculating multiple PPG markers can be advantageous because they can improve the accuracy and / or robustness of predicting R-peaks from, for example, camera-based PPGs.

[0034] In embodiments of the present invention, the PPG markers described above include diastolic PPG markers and blast phase PPG markers.

[0035] In an embodiment of the present invention, the method further includes the following steps:

[0036] Derivate timing parameters based on the trigger waveform and / or patient-specific model, and

[0037] The patient is scanned by a trigger signal, wherein the scan is configured to generate imaging scan data.

[0038] In an embodiment of the present invention, the method further includes an image forming step, wherein the image forming step forms an image of the patient based on processing imaging scan data and timing parameters.

[0039] This can be advantageous because using timing parameters derived from trigger waveforms and / or patient-specific models can help improve the quality and / or speed of image formation.

[0040] According to another aspect of the present invention, a computer program unit is provided, which, when run by at least one processing unit, is adapted to cause the processing unit to perform any computer-executable method steps according to any of the methods described above.

[0041] According to another aspect of the present invention, a computer-readable medium on which computer program units as described above are stored is provided.

[0042] According to a second aspect of the invention, a system is provided for determining a trigger signal for imaging a patient using an imaging system, the system comprising:

[0043] A patient-specific characteristic sensor is configured to measure patient-specific characteristics of the patient when the patient is positioned relative to the imaging system in a first location.

[0044] A trigger waveform sensor is configured to measure the trigger waveform of the patient when the patient is positioned at a second location relative to the imaging system.

[0045] The processing unit is configured to: receive the patient-specific characteristics, generate a patient-specific model based on the patient-specific characteristics, receive a trigger waveform, and determine an imaging trigger signal based on the patient-specific model and the trigger waveform.

[0046] In embodiments of the present invention, at least one of the patient-specific characteristic sensor and / or the trigger waveform sensor is a sensor, preferably a camera, and the sensor is configured to measure sensor-based PPG signals.

[0047] According to another aspect of the invention, an imaging system is provided, comprising the system for determining a trigger signal, wherein the imaging system is preferably a computed tomography system or a magnetic resonance imaging system.

[0048] These and other aspects of the invention will become apparent and will be explained with reference to the embodiments described herein. Attached Figure Description

[0049] Figure 1 The illustration shows a schematic diagram of a system for determining a trigger signal according to an embodiment of the present invention.

[0050] Figure 2 The illustration shows a schematic diagram of the measurement and processing of signals according to an embodiment of the present invention.

[0051] Figure 3 The image illustrates palm and face camera-PPG signals for determining a patient-specific model according to an embodiment of the present invention.

[0052] Figure 4 The illustration shows the determination of multiple PPG markers according to an embodiment of the present invention.

[0053] Figure 5 A flowchart of a method for determining a trigger signal according to an embodiment of the present invention is shown.

[0054] Figure 6 A flowchart illustrating a method for determining a trigger signal for initiating a scan according to an embodiment of the present invention is shown.

[0055] Figure 7 A flowchart illustrating an image forming method according to an embodiment of the present invention is shown.

[0056] Figure Labels

[0057] 100 System for determining trigger signals

[0058] 10 Patient-Specific Sensors

[0059] 20 Trigger Waveform Sensor

[0060] 30 patients

[0061] 40 Imaging System

[0062] 51 First position

[0063] 52 Second position

[0064] S10 measures patient-specific characteristics

[0065] S20 generates patient-specific models

[0066] S30 measures the trigger waveform

[0067] S35 Export Timing Parameters

[0068] S40 determines the trigger signal

[0069] S50 scan patient

[0070] S60 Image Formation Process Detailed Implementation

[0071] Figure 1 The figure illustrates a schematic diagram of a system 100 for determining a trigger signal according to an embodiment of the present invention. A patient 30 is positioned on the stage of an imaging system 40. In this example, it is suggested that an extra-cavity camera sensor 10 be used to measure patient-specific characteristics, which can be used to model patient-specific physiology during the preparation phase, before the patient is inserted into the borehole for a trigger scan using an intra-cavity camera sensor 20.

[0072] Many imaging system environments already offer ceiling-mounted cameras, allowing patient monitoring during the preparation phase before the worktable is moved into the chamber. Therefore, such camera sensors can be further used for remote PPG analysis, etc. Patient-specific characteristic sensor 10 and trigger waveform sensor 20 are connected to the processing unit (not shown) via wired or wireless connections.

[0073] exist Figure 1 In the example illustrated, the two sensors are independent camera sensors positioned at different locations. However, it is also possible that the patient-specific characteristic sensor 10 and the trigger waveform sensor 20 are the same sensor and / or positioned at the same location. This could be, for example, a camera-based sensor having a field of view both inside and outside the chamber of the imaging system 40.

[0074] exist Figure 1 In position a, patient 30 is positioned in first position 51 during the preparation phase. In first position 51, the patient's anatomical structures of interest (e.g., chest, head, or other body parts) are substantially outside the chamber of imaging system 40. Notably, although... Figure 1 The combined imaging system illustration shows the patient on the table, but it is also possible to expect the first position 51 to be further away from the imaging system, for example, in another room used for preparation.

[0075] exist Figure 1During the phase illustrated in Figure a, when the patient is in the first position 51, patient-specific characteristics are measured using camera sensor 10. These measurements may be combined with measurements performed by additional sensors, either remotely or in contact with the patient. Examples of such measured characteristics include, but are not limited to, characteristics derived from PPG, such as pulse waveform, heart rate, respiratory rate, blood pressure, the relationship between pulsation characteristics and ECG R peaks, PPG peak detection rate, etc. Based on one or more patient-specific characteristics, a patient-specific model can be created in the processing unit. Non-limiting examples of such a patient-specific model that can be created based on patient-specific characteristics measured using camera sensor 10 include patient-specific PPG waveform profiles, patient-specific characteristic pulse transit time, or patient-specific reliability factors based on camera-specific PPG parameters.

[0076] exist Figure 1 In position b, patient 30 is located in second position 52 during the scanning phase. In second position 52, the patient's anatomy of interest is substantially within the bore of imaging system 40. In second position 52, a trigger waveform is measured using camera sensor 20, in this example, an in-bore camera. The trigger waveform can be derived from camera-based PPG measurements using camera sensor 20. The processing unit receives the trigger waveform and determines an imaging trigger signal. The trigger signal is configured to trigger imaging system 40 to acquire images of patient 30 in a time-resolved manner.

[0077] It can be expected that... Figure 1 The system shown has several potential advantages, including the ability to measure patient-specific characteristics during patient preparation and / or at least before the patient 30 is further moved into the chamber of the imaging system 40. Examples include;

[0078] By understanding patient-specific PPG models (such as PPG waveform morphology, PPG amplitude, pulse transit time delay, etc.), accurate and rapid timing of camera-based MRI and CT acquisition windows can be simplified.

[0079] Images from MRI cardiac cine are typically annotated using timestamps relative to the R-peak, which is defined as the time zero point. This is possible by utilizing prior knowledge of the delay.

[0080] MRI cardiac cine is typically presented for diagnosis and comparison, starting from the time of the R-peak. This is possible by utilizing prior knowledge of the delay.

[0081] By utilizing knowledge about the time relative to the R peak, functional assessments of cardiac images, such as ejection fraction and wall motion, can be simplified and / or made more accurate.

[0082] Triggering with low latency between the R-peak and the trigger requires a patient-specific PPG template, thus necessitating some initial calibration time to initialize the model. Costly intra-nacelle time can be saved when the processing unit can perform such calibrations in advance without relying on intra-nacelle measurements.

[0083] When the quality of camera-based PPG signals can be assessed in advance, calculating the patient-specific reliability factor for camera-based PPG parameters can have a significant positive impact on workflow time. For example, in the case of triggered MRI, if the patient is already in the thoracolumbar region and the in-thoracolumbar camera 20 detects insufficient patient-specific PPG signal quality, the workflow will be significantly prolonged. In this situation, the patient 30 may have to be removed again, the MR coil removed, the ECG electrodes applied, the MR coil applied again, and then the patient 30 must be reinserted into the thoracolumbar region.

[0084] exist Figure 1 In the example illustrated, an extracorporeal camera 10 is positioned above (or to the side of) a patient 30 located on a table and measures physiological signals from the patient's skin (e.g., chest or facial area). These physiological signals can be PPG signals, but may also include other physiological signals. In some cases, an ECG sensor is also used. The ECG signal measured using the ECG sensor can be measured, for example, synchronously with the camera-PPG signal.

[0085] Currently, ECG detection triggered by MRI typically relies on at least four electrodes on an exposed chest. At least four electrodes are usually required for robust R-peak detection intracavitary because the ECG signal here can be compromised by interference from the MR field. To simultaneously measure ECG using a PPG outside the chest to measure patient-specific characteristics and initialize the calculation of a patient-specific model, only two ECG electrodes can be applied. The electrodes can be applied to the patient's wrist or hand. Such an ECG setup can greatly simplify the workflow. Furthermore, in cases where the electrodes are removed before the patient enters the chest, the ECG electrodes, leads, and detection circuitry do not need to be MR-compatible because of the use of a camera-PPG or similar method to measure the intracavitary trigger waveform. It is conceivable that in some cases, the ECG electrodes might simply be simple handles or conductive fields on either side of the patient support, which the patient can grasp for a few seconds whenever data is needed to calibrate the model.

[0086] Figure 2 The illustration shows an example of the relationship between patient-specific characteristics, patient-specific models, and trigger signals measured when patient 30 is in the first position 51 and in the second position 52.

[0087] Figure 2This schematically illustrates patient-specific characteristics measured when patient 30 is in the first position 51. In this example, a patient-specific characteristic sensor 10 (e.g., a camera PPG sensor) measures the signal derived from the PPG. Additionally, an ECG sensor is used to measure the electrocardiogram signal. The synchronized camera-PPG derived signal and ECG signal can be used to calculate a patient-specific model, such as... Figure 2 b and Figure 2 As shown in c.

[0088] Figure 2 Figure b illustrates the created PPG waveform profile, which can be used as a patient-specific PPG template for rapid triggering. The PPG waveform profile is a robust PPG cardiac cycle derived from averaging multiple PPG cycles, for example, from... Figure 2 The face or chest is measured by a PPG camera in a. Because the model is based on patient-specific characteristics measured when the patient is in the first position 51, the model can be initialized before the patient moves further into the bore of the imaging system 40.

[0089] Similarly, Figure 2 Figure c illustrates the created R-peak regression model that models the relationship between camera-PPG features and measured ECG R-peaks. The model's input comes from patient-specific characteristics measured at a first location 51. This model correlates specific PPG features (e.g., heart rate interval, waveform characteristics, phase) (i.e., so-called PPG markers) with the pulse transit time between the R-peak and trough of the camera-PPG signal. Therefore, this regression model can be used to predict / regress R-peak locations based on camera-based PPG waveforms.

[0090] Figure 2 Figure d illustrates the trigger waveform measured as the patient 30 moves further into the chamber of the imaging system 40. In this example, when the patient is in the second position 52, the trigger waveform is derived solely from camera-based PPG measurements. Therefore, an ECG within the imaging system is not required to measure the trigger waveform.

[0091] As in Figure 2 As shown in e, the previously created PPG waveform profile can be utilized. Figure 2 (b) This allows for the rapid identification of the PPG cycle in the trigger waveform, which can then be used for trigger detection. Since the model is initialized early in the workflow, rapid triggering can be enabled.

[0092] Similarly, as in Figure 2 As shown in f, the pre-built R-peak regression model ( Figure 2 c) It can be used to achieve accurate triggering by predicting the ECG R peak based on the camera-based trigger waveform.

[0093] Based on the identified cardiac cycle and R peak, a trigger signal is generated, thereby triggering the imaging system to acquire images of the patient.

[0094] exist Figure 2 In the example illustrated in the middle, patient-specific characteristics used to model patient-specific pulse transit time are measured during patient preparation using a combination of camera-based PPG and ECG. Alternatively, pulse transit time and related parameters can also be modeled using PPG measurements (e.g., multi-spot PPG imaging) without ECG.

[0095] Figure 3 The illustration shows multi-point PPG imaging, where PPG signals are simultaneously acquired from the patient's face and palm using a ceiling camera, which can be a patient-specific sensor 10. Information about the signals emitted simultaneously from the face and palm can be used to estimate the surrogate transit time. This surrogate transit time can then be used to improve the accuracy of PPG signal R-peak regression.

[0096] Additional parameters such as patient height, age, and body mass index can be used to further improve the model.

[0097] To improve the robustness of detecting PPG markers from trigger waveforms, multiple PPG markers can be generated by combining patient-specific PPG waveform profiles. In this way, one marker can predict the next marker, thereby improving the robustness of the model.

[0098] In addition to creating individual patient-specific PPG waveform profiles, multiple profiles can be created associated with a specific cardiac cycle duration or a range of cardiac cycle durations. Creating different profiles based on the range of cycle durations is likely due to the fact that if heart rate changes, the time curve of the heartbeat and related physiological quantities (such as arterial blood flow velocity and PPG signals) do not simply scale linearly. Instead, some parts of the cardiac cycle lengthen over time (typically the resting period of diastole), while others remain more or less unchanged (such as the systolic period).

[0099] Within each waveform profile, one or more PPG markers can be defined. Zero-crossings in the signal are particularly important. Negative zero-crossings correlate with the highest blood volume change at the observation point, such as the forehead during camera-PPG in response to cardiac contraction. Positive zero-crossings correlate with diastole and typically occur before the ECG R peak. Multiple markers can be generated from a single waveform profile, enabling the tracking of the current phase of the PPG signal throughout the cardiac cycle.

[0100] PPG marker detection can be performed, for example, as follows: The waveform profile can be moved so that it begins and ends at a zero-crossing point. In this way, two waveform profiles are created, each with a complete heart waveform: one starting and ending at a positive zero-crossing point, and the other starting and ending at a negative zero-crossing point.

[0101] Both waveforms are displayed Figure 4 In step a, the PPG waveform profile is stretched or time-distorted to cover 33 samples. The purpose is to check if the latest received sample of the incoming PPG waveform corresponds to the last sample in these prototypes. If so, a corresponding marker is generated.

[0102] Patient-specific models can be used to decompose patient-specific PPG signals. This model describes the waveform as consisting of three parts: the PPG waveform profile, the low-frequency (LF) signal component, and the noise component. The LF signal component can be modeled as a low-order polynomial. More formally, let the discrete-time PPG signal segment be represented as s(n), n = [1,…,N], the prototype as p(n), and the LF signal component as b(n), then the signal is described as:

[0103] s = αp + b + e,

[0104] Where e(n) is the error signal describing noise (e.g., measurement noise) and interference, and α is a scaling factor. Signal component b captures signal drift in respiration-related PPG and PPG variations (and therefore has a frequency lower than heart rate). Various methods are known to achieve such a decomposition; for example, the decomposition can be obtained using a least-squares fitting procedure, where windows can be used to emphasize the importance of certain parts of the fitted segments.

[0105] The strength of the decomposed signal can be analyzed, for example, in terms of energy. A good fit can be achieved if the energy associated with the PPG component p is significantly greater than the energy associated with e. Further evidence supporting label generation is that the coefficient α is positive. Further evidence is that when considering the next segment consisting of a simple shifted input signal, the coefficient α becomes lower, or the balance between the energy in (αp) and e becomes less favorable. Through these or other means, a decision can be made regarding what has happened in labeling.

[0106] Since the length of the current cardiac cycle is unknown, the system will operate at different lengths. Therefore, the detection has an additional dimension—the dimension along the scale (cardiac cycle length). Various cues indicating their presence must also be observed through this additional dimension. Difficult decisions can be made based on thresholding, more statistical methods can be used, or a neural network can be trained to create the final decision-making mechanism.

[0107] Figure 4 b illustrates an example of generating multiple PPG markers to improve R-peak prediction. More importantly, prediction can be improved by selecting at least one marker that precedes but is close to the R-peak and at least one second marker indicating its presence, for example, by observing changes in blood volume caused by induced cardiac contraction. In this case, the PPG markers are generated during or near the moment of greatest blood volume change in diastole (i.e., the flush phase). Diastolic PPG markers ( Figure 4 The asterisk (in b) usually appears before the R peak, while the PPG marker during the jet stream ( Figure 4 The circle in b) usually appears after the R peak. Therefore, combining the two can improve the timely prediction ability of the R peak.

[0108] Several embodiments of the present invention have been described in detail above. Figure 5 Another aspect of the invention is also illustrated, showing a flowchart of a method for determining a trigger signal. The method includes the following steps:

[0109] Measure patient-specific characteristics of patient 30 in S10 when the patient is positioned relative to the imaging system in a first position.

[0110] The patient-specific model described in S20 is generated based on the aforementioned patient-specific characteristics.

[0111] Measure the trigger waveform of the patient described in S30. The trigger waveform is measured when the patient is positioned at a second location relative to the imaging system. The second location is different from the first location.

[0112] The trigger signal in step S40 is determined based on the patient-specific model and the trigger waveform. The trigger signal is configured to trigger the imaging system to acquire images of the patient in a time-resolved manner.

[0113] Similarly, Figure 6 A flowchart illustrating a method for determining a trigger signal for initiating a scan according to an embodiment of the present invention is shown. In this case, the method, in addition to Figure 5 In addition to the method shown, the method also includes the following steps: deriving timing parameters for S35 from a trigger waveform and / or a patient-specific model, and triggering a patient scan for S50 by a trigger signal, wherein the patient scan for S50 is configured to generate imaging scan data.

[0114] In addition to achieving more robust triggering from measured trigger waveforms, patient-specific models (e.g., including PPG markers) may contain timing parameters that can be further utilized in the imaging workflow. In the image formation process S60, where scan data is combined into image or video sequences, these timing parameters can be used as additional information to control the image formation process. For example, by weighting or as compensation factors for data acquired at different data acquisition windows.

[0115] For example, in MRI, knowledge of time parameters (such as the distance between prepulse generation and data acquisition time) can be used to improve image formation. Alternatively, triggering mechanisms can be configured to maintain a more stringent requirement for a constant prepulse-to-acquisition window distance. In this case, information about each MR sequence event occurring, such as the motion state of the myocardium, can be used during image formation.

[0116] Figure 7 The illustrations show embodiments of the present invention, wherein, as Figure 6 The method shown also includes an image forming step S60, wherein the image forming step S60 forms an image of the patient based on the processing of imaging scan data and timing parameters.

[0117] It should be noted that the embodiments mentioned above are exemplary and not limiting of the invention, and those skilled in the art can devise many alternative embodiments without departing from the scope of the appended claims. Any reference numerals placed in parentheses in the claims should not constitute a limitation of the claims. The word "comprising" does not exclude the presence of elements or steps other than those listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements, and by means of a suitably programmed processor. In device-type claims that enumerate several devices, several of these devices may be implemented by the same item of hardware. Measures recited in mutually different dependent claims can be advantageously combined.

Claims

1. A method for determining a trigger signal for imaging using an imaging system (40), the method comprising the steps of: Measure (S10) patient-specific characteristics of patient (30), wherein the patient-specific characteristics are measured when the patient (30) is positioned in a first position (51) relative to the imaging system (40) and the patient anatomy of interest is substantially located outside the bore of the imaging system (40); Based on the aforementioned patient-specific characteristics, a patient-specific model is generated (S20). Measure (S30) the trigger waveform of the patient (30), wherein the trigger waveform is measured when the patient is positioned in a second position (52) relative to the imaging system (40) and the anatomical structure of interest is substantially positioned inside the chamber of the imaging system (40), wherein the second position (52) is different from the first position (51), and The trigger signal is determined (S40) based on the patient-specific model and the trigger waveform, wherein the trigger signal is configured to trigger the imaging system (40) to acquire images of the patient (30) in a time-resolved manner.

2. The method according to claim 1, wherein, The trigger waveform includes a waveform derived from photoplethysmography (PPG), and the step of measuring the trigger waveform includes measurement using a sensor.

3. The method according to claim 2, wherein, The sensor includes a camera.

4. The method according to claim 1 or 2, wherein, The patient-specific characteristics include characteristics derived from PPG, and the step of measuring the patient-specific characteristics includes measurement using a sensor.

5. The method according to claim 4, wherein, The sensor includes a camera.

6. The method according to claim 1 or 2, wherein, The patient-specific model includes a patient-specific PPG waveform profile.

7. The method according to claim 1 or 2, wherein, The patient-specific model includes patient-specific pulse transit time.

8. The method according to claim 1 or 2, wherein, The patient-specific model includes a patient-specific reliability factor based on camera-specific PPG parameters.

9. The method according to claim 6, wherein, The step of determining the trigger signal includes calculating a plurality of PPG markers, wherein the PPG markers are derived based on the trigger waveform and / or the patient-specific PPG waveform profile, and wherein the PPG markers are configured to predict R peaks.

10. The method according to claim 9, wherein, The PPG markers include diastolic PPG markers and blast phase PPG markers.

11. The method according to claim 1 or 2, further comprising the following step: (S35) Timing parameters are derived based on the trigger waveform and / or the patient-specific model. A scan of the patient is performed (S50), which is triggered by the trigger signal, wherein the scan is configured to generate imaging scan data, and Image formation (S60), wherein an image of the patient (30) is formed based on the processing of the imaging scan data and the timing parameters.

12. A computer program unit adapted to cause the processing unit to perform the steps of the method according to any one of claims 1-11 when run by at least one processing unit.

13. A computer-readable medium having a program unit stored thereon according to claim 12.

14. A system (100) for determining a trigger signal for imaging a patient (30) using an imaging system (40), the system (100) comprising: A patient-specific characteristic sensor (10) is configured to measure patient-specific characteristics of the patient (30) when the patient (30) is positioned at a first location (51) relative to the imaging system (40) and the anatomical structures of interest are substantially located outside the bore of the imaging system (40). A trigger waveform sensor (20) is configured to measure the trigger waveform of the patient (30) when the patient (30) is positioned at a second position (52) relative to the imaging system (40) and the anatomical structure of interest is substantially located inside the chamber of the imaging system (40). The processing unit is configured to: receive the patient-specific characteristics, generate a patient-specific model based on the patient-specific characteristics, receive the trigger waveform, and determine an imaging trigger signal based on the patient-specific model and the trigger waveform.

15. An imaging system (40) comprising the system (100) for determining a trigger signal according to claim 14.

16. The imaging system according to claim 15, wherein, The imaging system (40) is a computed tomography system or a magnetic resonance imaging system.

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