Method for automatically determining a set of at least one optimal characteristic parameter of an acquisition sequence by means of magnetic resonance

Abstract

The invention relates to a method for determining an optimal characteristic set (TIopt) of at least one characteristic parameter of an acquisition sequence for acquiring an image of a region to be imaged by magnetic resonance, the acquisition sequence being configured to substantially cancel out medical signals from at least one predetermined tissue, the method comprising the computer-implemented step of selecting an optimal characteristic image having a larger number of pixels of an intensity that is lower than or equal to a given intensity threshold (SI) from among a plurality of characteristic images (IKi) of a characteristic region of the region to be imaged which are generated by means of respective acquisition sequences having different respective sets of at least one characteristic parameter (TIi), the optimal characteristic set (TIopt) being the characteristic set (TIi) of the acquisition sequence by means of which the optimal characteristic image was generated.

Description

[0001] Description

[0002] Title: METHOD FOR AUTOMATICALLY DETERMINING A SET OF AT LEAST ONE OPTIMAL CHARACTERISTIC PARAMETER OF A MAGNETIC RESONANCE ACQUISITION SEQUENCE

[0003] Field of invention

[0004] The invention relates to the field of magnetic resonance imaging (MRI), in particular, cardiac magnetic resonance imaging.

[0005] It concerns magnetic resonance imaging in which an acquisition sequence is configured to cancel a signal from at least one predetermined tissue, such as late gadolinium enhancement magnetic resonance imaging or LGE, in reference to the Anglo-Saxon expression "Late Gadolinium Enhancement".

[0006] The gold standard for assessing regional scar formation and myocardial fibrosis is bright-blood late gadolinium enhancement (BR-LGE). In this type of imaging, viable myocardial signal cancellation is induced using inversion-recovery pulses, allowing scars to be visualized with high contrast between healthy myocardial tissue and scars. However, for myocardial scars adjacent to the blood chambers of the heart (right and left ventricles), the high signal intensity from the blood prevents clear visualization and precise delineation of scars, particularly subendocardial scars. To circumvent this problem, dark-blood LGE (BL-LGE) imaging techniques have been proposed.They allow simultaneous cancellation of signals from healthy myocardium and blood, thus providing high contrast both between scars and between blood and between scars and healthy myocardium.

[0007] Blood signal cancellation, to obtain a "black blood" contrast, is achieved by applying, to an area to be imaged in a patient, a radiofrequency (RF) inversion-recovery sequence comprising a 180° pulse followed by a T1-rho preparatory module and a reading module. The time between the 180° pulse and the reading module is called the inversion time.

[0008] The aim is to acquire the signals to generate the image of the area to be imaged with an acquisition sequence such that the inversion time of the sequence is optimal so that at the time of reading the longitudinal magnetizations, the longitudinal magnetizations of the blood and the healthy myocardium cancel each other out, which makes it possible to obtain the MRI image with the best contrast between the scars and the blood and the adjacent healthy myocardium. The choice of the inversion time is fundamental since the contrast of the image has a direct impact on the visualization, detection and delimitation of the scars and therefore on the diagnosis and prognosis of the patient.

[0009] However, this inversion time depends on the patient, the static magnetic field, as well as the time between the acquisition sequence and the injection of the contrast agent. It is therefore necessary to determine the optimal invention time, for each patient, before acquiring the medical images of the myocardium on which a specialist or a detection program is intended to detect or visualize and locate the myocardial scars.

[0010] State of the art

[0011] Methods are known for automatically determining the optimal inversion time from MRI images acquired using inversion-recovery acquisition sequences having distinct respective inversion times in BR-LGE MRI imaging, based on artificial intelligence techniques.

[0012] In particular, a method is known based on the analysis of the spatial and temporal characteristics of the different images by a neural network. A method is also known based on a segmentation technique by a convolutional neural network followed by the analysis of the pixel intensities in a region of interest obtained by the segmentation.

[0013] However, the use of these methods in the clinic is not simple, because their installation on an MRI imaging device is complex (specific calculation libraries and software must be installed for these methods to work) and is currently mainly used for research purposes on dedicated sites. Patent US9104783B2 discloses a system for automatically determining imaging parameters for BL-LGE imaging based on a model linking the inversion time to the electrocardiogram (ECG). This method is however completely dependent on ECG acquisition, the presence of blood flow, non-functional in the presence of stagnant blood on the walls, and restricted to 2D applications.

[0014] One aim of the invention is to limit at least one of the aforementioned drawbacks.

[0015] To this end, the subject of the invention is a method for determining an optimal characteristic set of at least one characteristic parameter of a medical signal acquisition sequence for generating a medical image of an area to be imaged by magnetic resonance, the acquisition sequence being configured to substantially cancel medical signals originating from at least one predetermined tissue, the method comprising the selection, implemented by computer, of an optimal characteristic image having a greater number of pixels of intensity less than or equal to a given intensity threshold from among a plurality of characteristic images of an area characteristic of the area to be imaged generated from signals acquired by respective acquisition sequences having distinct sets of at least one respective characteristic parameter,the optimal characteristic set being the characteristic set of the signal acquisition sequence by means of which the optimal characteristic image was generated.,

[0016] In a particular embodiment, the medical signal acquisition sequence is a late gadolinium enhancement dark blood acquisition sequence.

[0017] In a particular embodiment, the characteristic area comprises only portions of the myocardium and blood.

[0018] In a particular embodiment, the characteristic set is an inversion time.

[0019] In a particular embodiment, the method comprises determining the intensity threshold, this step comprising:

[0020] - calculation of histograms of the characteristic images of the characteristic zone, - determination of an intensity of the global maximum of the histograms.

[0021] In a particular embodiment, the method comprises selecting characteristic images of the characteristic area from images of the area to be imaged.

[0022] In a particular embodiment, the method comprises the following sequence of steps:

[0023] - acquisition of signals by means of the respective acquisition sequences,

[0024] - generation of characteristic images from the signals. Advantageously, the sequence of steps and the selection of the optimal characteristic image are repeated with inversion times different from those of the acquisition sequences when the optimal inversion time is a maximum or minimum inversion time of the acquisition sequences.

[0025] The invention also relates to a method for generating a medical image of the area to be imaged comprising determining the optimal set of at least one characteristic parameter by the method according to the invention. This method further comprises acquiring medical signals by the medical acquisition sequence having the optimal characteristic set and generating the medical image from the medical signals.

[0026] The invention relates to a processing system comprising a processor configured to implement the steps of the method according to the invention.

[0027] The invention also relates to a computer program product comprising instructions which, when the program is executed by a computer, cause the latter to implement the steps of the method according to the invention.

[0028] The invention further relates to a computer-readable recording medium comprising instructions which, when executed by a computer, cause the latter to implement the method according to the invention.

[0029] Furthermore, the invention relates to a magnetic resonance imaging system comprising a magnetic resonance system comprising a static magnetic field generator, a gradient generator, a radiofrequency device and a processing and control system configured to implement the calculation steps of the method according to the invention and to control the magnetic resonance system so that the imaging system implements the method according to the invention.

[0030] Benefits

[0031] The method according to the invention makes it possible to determine the inversion time in a reliable, robust, computationally inexpensive, reproducible and simple manner.

[0032] It can be easily integrated into an existing MRI device without significant modification to existing acquisition sequences.

[0033] Moreover, this process does not give additional workload to the manipulator.

[0034] In addition, the process is rapid (of the order of a few tens of ms), which is advantageous since the optimal inversion time is likely to change during the examination taking into account the kinetics of gadolinium elimination.

[0035] The method according to the invention allows the choice of the step between the inversion times or, more generally, between the values ​​of the parameters of the different characteristic sets of the different acquisition sequences, which makes it possible to obtain the optimal inversion time or the optimal set with good precision, which is, ultimately, favorable to the good detection and precise localization of the characteristics.

[0036] Brief description of the figures

[0037] Other characteristics and advantages of the invention will emerge from reading the detailed description which follows, with reference to the appended figures, which illustrate:

[0038] Fig. 1: a schematic representation of the MRI imaging system according to the invention,

[0039] Fig. 2: A schematic representation of a BL-LGE MRI acquisition sequence,

[0040] Fig. 3: a schematic representation of the steps of the method according to a first embodiment, Fig. 4: a flowchart of the steps of a method for acquiring MRI images according to the invention,

[0041] Fig. 5: a flowchart of the steps of an exemplary embodiment of a global method according to the invention.

[0042] Description of invention

[0043] The invention relates to the field of magnetic resonance imaging or MRI.

[0044] It relates more particularly to MRI imaging in which it is desired to configure a medical signal acquisition sequence to obtain a substantially zero signal for one or more predetermined tissues. In other words, it is desired to configure the medical signal acquisition sequence to generate a substantially black image of a predetermined tissue.

[0045] It concerns, for example, MRI imaging in black blood.

[0046] The invention relates in particular to magnetic resonance imaging requiring the injection of a contrast product, for example gadolinium.

[0047] This concerns, for example, late gadolinium enhancement imaging in black blood (BL-LGE).

[0048] The invention applies to cardiac imaging, but also to angiography.

[0049] MRI system

[0050] Figure 1 schematically represents a magnetic resonance imaging system according to the invention comprising a set A of excitation and measurement equipment and a processing and control system C.

[0051] In a manner known per se, the set A of excitation and measurement equipment comprises an MRI imaging device B comprising a static magnetic field generator 1 comprising a main polarization magnet, a gradient generator 2 and a radiofrequency device 3.

[0052] The static magnetic field generator 1 comprises a main polarization magnet for generating a static magnetic field of substantially uniform polarization in a polarization zone (generally a tunnel) intended to comprise the area to be imaged of the patient, for example the heart.

[0053] The gradient generator 2 comprises three gradient coils or solenoids arranged and configured to vary the intensity of the magnetic field in the polarization zone along respective orthogonal axes conventionally denoted x, y and z fixed relative to the polarization zone. The choice of the intensities circulating in these coils makes it possible to select, from several possible ones, a thickness and a cutting plane in which the magnetization of the area to be imaged of the patient received in the polarization zone will be measured.

[0054] The radiofrequency device 3 comprises coils or solenoids and is capable of generating MRI acquisition sequences comprising 180° inversion pulses, preparatory modules for the magnetization of the area to be imaged and modules for reading signals from the area to be imaged.

[0055] Generally, the acquisition sequence is composed of sub-sequences called modules, each comprising at least one radiofrequency pulse of predetermined and adjustable frequency, shape, duration, phase and amplitude.

[0056] The preparatory module is configured to excite, i.e. modify the direction of magnetization of the tissues in the area to be imaged.

[0057] The reading module is configured to measure the magnetization of the area to be imaged resulting from the preparation module.

[0058] Set A advantageously comprises an electrocardiograph 4 intended to acquire an electrocardiogram of the patient.

[0059] The processing and control system C comprises a processing and control module 10 configured to generate commands to the MRI device B, in particular to the RF device 3, to generate the acquisition sequences and to generate two-dimensional grayscale images of the area to be imaged from the signals measured by the RF magnetic field generator using reconstruction techniques known to those skilled in the art.

[0060] The generated image is a grayscale matrix image. It comprises a set of pixels each characterized by an intensity I capable of taking a set of N values ​​(N being a finite integer greater than 1) corresponding to N grayscale levels ranging from 0 to N-1. For example, this value can take 256 values ​​between 0 and 255 but N is not limited to 256.

[0061] Representations of the images generated by the processing and control module 10 are intended to be displayed on a screen of the human-machine interface 11 of the processing and control system C.

[0062] Acquisition sequence

[0063] Figure 2 represents an example of a black blood MRI acquisition sequence of a myocardial image. A schematic representation of an electrocardiogram (ECG) likely to be acquired by the electrocardiograph 4 during a heartbeat as well as the acquisition sequence applied to the area to be imaged are represented in the upper part of Figure 2. The lower part of Figure 2 represents the variation of the longitudinal magnetization of the tissues of the area to be imaged as a function of time t as well as an image I reconstructed from signals acquired during a reading module starting at a time t= te corresponding to the cancellation of the longitudinal magnetizations of the blood and the healthy myocardium.

[0064] For BL-LGE MRI acquisition, a Gadolinium-based contrast agent is advantageously injected intravenously into the patient, 10 to 15 minutes before the application of the acquisition sequences in order to obtain images with maximum contrast between scars and healthy tissues and blood. In the heart, the contrast is rapidly eliminated from the healthy myocardium, but accumulates for a prolonged period in the myocardial scars. The effect of gadolinium has the effect of shortening the T1 relaxation time of the tissues where it accumulates. The relaxation of the magnetization of the scars following an impulse is thus faster than that of the blood and healthy myocardium.

[0065] The aim is to generate images with a black blood contrast. In an image of this type, the intensity of the pixels corresponding to the blood is zero (black pixels) or substantially zero because it is acquired when the longitudinal magnetization of the blood is zero.

[0066] In order to generate such an image, the RF device 3 generates an inversion-recovery acquisition sequence. This acquisition sequence includes a preparatory module comprising an inversion pulse denoted 180° in Figure 2, which switches the longitudinal magnetization of the tissues in the imaged area in the opposite direction, i.e. which reverses the longitudinal magnetization. In Figure 2, it can be seen that the magnetization of the area to be imaged changes from Mz to -Mz under the effect of the inversion pulse. Due to the longitudinal relaxation, the longitudinal magnetization of the different tissues present in the area to be imaged increases to return to its initial value, passing through the zero value. Naturally, the relaxation kinetics of the different tissues are different.

[0067] In a manner known per se, the preparatory module includes, for example, an adiabatic module in T1-rho (Tip) of duration noted TSL (acronym for the Anglo-Saxon expression “Time of Spin Lock”) or a module weighted in T2, or of the MTC type (acronym for the Anglo-Saxon expression “Magnetization Transfer Contrast”).

[0068] The preparatory module (180°, Tip) is configured so that the longitudinal magnetization of the blood and that of the healthy myocardium cancel each other out at the same instant te.

[0069] At this same instant te, the longitudinal magnetization of the scars is clearly greater than zero. By acquiring the signals from the area to be imaged at this instant te, we obtain an image with a very high contrast between the pixels corresponding to the blood and healthy myocardium, which are black, and the pixels corresponding to the scars, which are generally white.

[0070] The inversion-recovery sequence then includes an LE readout module comprising a 90° pulse applied at time te and a readout gradient to read the transverse magnetization of the area to be imaged.

[0071] The inversion time Tl is the time separating the 180° pulse from the reading module, i.e. from the first instant of image acquisition in the Fourier domain. In order to obtain the best contrast between the myocardial scars and the blood and healthy myocardium, we seek to start the reading sequence at the instant te where the longitudinal magnetizations of the blood and the myocardium cancel each other out in order to generate the image with the best contrast. The inversion time is then optimal, it is noted Tl op t in Figure 2.

[0072] Determination of the optimal inversion time Tl op t Figure 3 shows the steps of the method according to the invention.

[0073] The method according to the invention is a computer-implemented method for determining the optimal inversion time Tl op t from a plurality of characteristic images IKj of a characteristic area of ​​the area to be imaged generated by applying acquisition sequences differing from each other only by their respective inversion times Th.

[0074] As visible in Figure 3, the characteristic images IKj present different contrasts (with i = 1 to K, K being at least equal to 2 and equal to 11 in the non-limiting example of Figure 3).

[0075] This optimal inversion time Tl opt is advantageously stored in a memory of the system C and used, by the processing and control module 10, to generate a command intended for the system A, in particular the RF device 3 so that it carries out the acquisition of so-called medical signals, by a so-called medical acquisition sequence, the inversion time T1 of which is the optimal inversion time T1 op t so that the processing and control device generates an image from these signals.

[0076] According to the invention, the method for automatically determining the optimal inversion time Tl opt comprises, as visible in Figure 3, the computer-implemented selection of an optimal characteristic image IKopt, which has a greater number of pixels of intensity less than or equal to a given intensity threshold SI, in the plurality of characteristic images IKj with i = 1 to K. The intensity threshold SI used is the same for all images IKj with i = 1 to K.

[0077] The optimal inversion time Tl op t is the inversion time Th of the acquisition sequence by means of which the optimal elementary image IK op you were generated.

[0078] We will now describe in more detail a preferred embodiment of the selection step, represented in Figure 4, of the optimal elementary image IK op t which is the elementary image IKj which presents a greater number of pixels of intensity less than or equal to an intensity threshold SI, among the elementary images IKj.

[0079] This step advantageously comprises the following steps, each being implemented by computer, by the processing and control module 10: - calculation 21 of histograms HISTi of the characteristic images IKj for i = 1 to K,

[0080] - determination 22 of the global maximum M of the HISTi histograms by a classic method of detecting a global maximum,

[0081] - determination 23 of an SI intensity of the global maximum M

[0082] The intensity threshold SI is the intensity of the global maximum M of the HISTi histograms.

[0083] Each histogram HISTi contains, for each of the N possible values ​​of intensity I, the number of pixels in the image having this intensity I.

[0084] For clarity, the histograms shown in Figure 3 are partial. Only the portions of these histograms relating to intensity values ​​(gray level) between 0 and 60 are shown in Figure 3.

[0085] The process then includes the following steps:

[0086] - calculation 24, for each characteristic image IKj of the number Nh of pixels of the image IKj presenting an intensity less than or equal to the intensity threshold SI,

[0087] - determination 25 of the optimal characteristic image IKopt presenting, among the images IKj with i = 1 to K, the largest number Nh of pixels of intensity less than or equal to SI.

[0088] The optimal inversion time Tl op t is the inversion time of the acquisition sequence by means of which the signals used to generate the optimal characteristic image IK opt presenting the greatest number of pixels of intensity less than or equal to the intensity threshold SI.

[0089] In other words, the proposed method allows the selection of the image which presents the most low intensity pixels.

[0090] Calculating the SI intensity threshold from the characteristic IKj images makes it possible to adapt the threshold according to the patient and to select a reliable optimal inversion time.

[0091] Furthermore, it should be noted that in images comprising only the myocardium and blood, only the scars normally present a high intensity on the image obtained from an acquisition sequence presenting the Tl opt. It may happen that the image presents high intensity artifacts. The intensity threshold SI used in the method according to the invention is not affected by the value of these pixels which would have been different with a threshold equal to the average value of the maximums of the histograms.

[0092] Alternatively, the intensity threshold SI constitutes data used by the method according to the invention. This intensity threshold SI is, for example, previously stored in a memory of the system C. The method is then devoid of steps 22 and 23.

[0093] Feature images

[0094] Advantageously, it is desired to configure the acquisition sequence to simultaneously acquire substantially zero signals from at least one tissue of the characteristic zone. In other words, the tissue(s) concerned simultaneously have(s) substantially zero longitudinal magnetization at the time of the reading sequence, that is to say that the image of this(these) tissue(s) reconstructed from the signals from this(these) tissue(s) measured during the acquisition sequence is black or substantially black.

[0095] Advantageously, the characteristic area comprises this(these) tissue(s). When applied to BL-LGE cardiac imaging, the method according to the invention advantageously uses characteristic images IKj of a characteristic area comprising only a part of the myocardium and blood.

[0096] The method according to the invention is then very reliable. Indeed, in this case, the acquisition sequence is configured to substantially simultaneously cancel the longitudinal magnetizations of the healthy myocardium and the blood. The area of ​​interest is the part of the myocardium affected by the scars. This area is in the minority, the image will be predominantly substantially black.

[0097] In angiography, we want to visualize the vessels and therefore the blood. The acquisition sequence is configured to substantially cancel the signal from the myocardium and other tissues such as the muscles of the back and chest, unlike that of the blood. A contrast agent, for example gadolinium, is advantageously injected intravenously and the acquisition sequence is implemented early so that the blood appears white (bright) on the images.

[0098] Advantageously, the characteristic area comprises only tissues from which substantially impaired signals are to be acquired by means of the acquisition sequence. Advantageously, the characteristic area comprises only tissues from which substantially impaired signals are to be acquired by means of the acquisition sequence and blood and predominantly the tissues from which substantially impaired signals are to be acquired.

[0099] Determination of a characteristic set

[0100] The invention relates more generally to a method for automatically determining an optimal characteristic set. The characteristic set consists of one or more characteristic parameters of an MRI acquisition sequence. The aim of the invention is to determine the optimal characteristic set comprising respective values ​​of the characteristic parameters such that the contrast of the image acquired by means of an acquisition sequence characterized by this characteristic set is maximum.

[0101] The process steps implemented are the same as the steps described with reference to Figure 4.

[0102] The method then uses characteristic images of the characteristic area acquired by respective acquisition sequences differing only in their characteristic sets, i.e. in values ​​of the characteristic parameters of the set.

[0103] The characteristic set may in particular comprise at least one parameter taken from: the inversion time Tl, the preparatory module, a parameter of the preparatory module, for example the duration TSL of the module in Tip, the number of pulses of the preparatory module, the time spacing between two consecutive pulses of the preparatory module, the intensity, the phase shift, the frequency, the amplitude of each pulse, the shape, the duration, the phase, of at least one or each of the pulses of the preparation module.

[0104] Each characteristic parameter can take different values. In other words, each characteristic parameter is adjustable by the MRI system A, C.

[0105] The choice of the value of each of the characteristic parameters has an influence on the evolution of the value of the longitudinal magnetization of each tissue present in the image as a function of time and therefore the contrast of the image.

[0106] These parameters can be independent of each other or not. The optimal characteristic set is the inversion time of the signal acquisition sequence by means of which the IK image op t with the largest number of pixels with intensity less than or equal to the SI intensity threshold was generated.

[0107] Overall process

[0108] The invention also relates to a global method for generating medical images of an area to be imaged, the steps of which are represented in Figure 5.

[0109] This overall method includes a method for determining an optimal characteristic set including for example:

[0110] - possible injection 111 of a contrast product, for example gadolinium, intravenously into the patient,

[0111] - generation 112 of a command for acquiring signals from the area to be imaged by means of K respective acquisition sequences differing only by their characteristic set of at least one characteristic parameter, by the processing and control module 10,

[0112] - acquisition 113 of the signals from the area to be imaged by means of Ks acquisition sequences by the RF device 3,

[0113] - generation 114 of K two-dimensional global images IMj (i = 1 to K) of the area to be imaged by means of signals acquired during step 112, by the processing and control module 10,

[0114] - selection 115 of the K characteristic images IKj (i = 1 to K) being portions of the respective global images IMj, by the processing and control module 10,

[0115] - determination 116 of the optimal set, for example the optimal inversion time Tl opt by means of the method for determining the optimal set previously described from the characteristic images IKj, by the processing and control module 10. The overall method then comprises the following steps:

[0116] - generation 120, by the processing and control module 10 of an acquisition command to acquire the so-called medical signals for the generation of a set of at least one medical image of the area to be imaged from at least one acquisition sequence characterized by the optimal characteristic set,

[0117] - acquisition 130, by the RF device, 3, of the medical signals of the area to be imaged by means of the acquisition sequence(s) characterized by the optimal characteristic set,

[0118] - generation 140, by the processing and control module 10, of the set of at least one medical image of the area to be imaged from the medical signals of the area to be imaged acquired during step 130,

[0119] - display 150 of representations of medical images, by the human-machine interface 11.

[0120] Advantageously, signals are acquired during step 130 making it possible to generate, during step 140, several medical images according to different section planes. For this purpose, the gradient generator generates different gradients during the acquisition sequences.

[0121] The invention also relates to the system A, C configured to implement the method according to the invention.

[0122] Advantageously, the acquisition step 113 is implemented between 10 and 15 minutes after the injection of gadolinium in the non-limiting case of BL-LGE imaging. It is triggered and controlled by the commands generated during step 112.

[0123] The signals of the area to be imaged are acquired, during step 113, by means of respective acquisition sequences differing from each other only by their respective characteristic sets. Furthermore, the other acquisition conditions, namely the magnetic field generated by the static magnetic field generator 1 and the gradient generated by the gradient generator, are the same during these sequences. The acquisition sequences are advantageously synchronized, by the processing and control module 10, with the heart rate, using the signals measured by the electrocardiograph 4, so as to be implemented during respective consecutive heartbeats. An acquisition sequence is implemented at each heartbeat.

[0124] Thus, the IMj global images are images of the heart produced according to the same section plane of the area to be imaged.

[0125] In cardiac imaging, the section plane is, for example, a short-axis section plane. This section plane has the advantage of allowing visualization of the entire myocardium in section and therefore promotes the detection and visualization of myocardial scars.

[0126] Other cutting planes may be advantageous for other types of detection, for example for functional imaging.

[0127] Advantageously, in the case of BL-LGE cardiac imaging, the acquisition sequences include respective inversion times ranging from 60 ms to 160 ms when the static magnetic field is 1.5 Tesla. Indeed, the applicant has found, by means of tests carried out on different patients, that the inversion times are typically between 60 ms and 160 ms for this type of imaging.

[0128] Generally, the respective inversion times can be between 0 sec and 300 ms.

[0129] For example, the acquisition sequences include different inversion times ranging from 60 ms to 160 ms, separated by one step in pairs.

[0130] The step for example equals 10 ms.

[0131] Alternatively, the step is less or greater than 10ms. The choice of the step depends on the compromise chosen between the acquisition time (the smaller the step, the greater the number of images) and the precision with which one wishes to define the optimal inversion time, knowing that below a certain step, the gain in precision on the optimal Tl and therefore in contrast on the medical image is not perceptible to the naked eye on medical images for diagnosis.

[0132] The step can be fixed or variable over the interval.

[0133] Step 114 of generating two-dimensional global images is carried out using MRI image reconstruction techniques known to those skilled in the art. Parallel reconstruction algorithms are known in particular, such as the GRAPPA or SENSE algorithm (acronym for the English expression “SENSitivity Encoding”).

[0134] Step 115 of selecting the characteristic images IKj, i.e. portions of the images IMj, can be carried out in different ways.

[0135] In a particular embodiment, the selection step 114, implemented by computer, for example by the system C, comprises two steps:

[0136] - selection, on each image IM i of a portion of image POi of image IMj, this portion of image POi is represented in the second line of figure 3 and corresponds to the portion POi of image IMj delimited by the white frame represented on image IMi,

[0137] - selection, for each image portion of image POi, of the characteristic image I Kj being a portion of the image portion POi this characteristic image IKj is represented in the third line of figure 3 and corresponds to the portion of the image POi delimited by the white frame represented on the image portion POi.

[0138] The selection of the POi image portion comprises, for example, the acquisition, by the processing and control module 10, of the coordinates, dimensions and orientation of a first frame completely surrounding and delimiting the POi image portion. This frame is the white frame shown in the IMi images of FIG. 3.

[0139] In cardiac imaging, this frame is advantageously centered on the heart, delimits the section of the heart in the section plane and contains the entire section of the heart located in the section plane. Advantageously, the frame is a polygon, for example a rectangle, each of whose sides delimits the section of the heart in the section plane.

[0140] This frame is, for example, drawn by an operator on a representation of one of the IMi images displayed on a screen of the HMI 11 by means of an element of the HMI, for example a mouse of the HMI whose movement causes a cursor to move on the screen of the HMI.

[0141] This frame is, for example, a Shim box, usually drawn by the user on one of the images to select the portion POi within which the magnetic field must be homogenized. The coordinates, dimensions and orientation of this frame in the image frame are calculated by the processing and control module 10 from the position, orientation and dimensions of the frame on the screen and stored in a memory of the system C. The processing module 10 selects the portions POi of the images IMj from the coordinates, dimensions and orientation of the frame. The portions POi are stored in the memory of the system C.

[0142] Advantageously, the selection of the characteristic image IKj is the selection of a central portion of the image portion POi being equal to the size of the portion of the image POi divided by a predetermined factor.

[0143] In cardiac imaging, the factor is advantageously defined so that the characteristic image IKj includes only blood and part of the myocardium.

[0144] The factor is, for example, between 2 and 3. It is, for example, equal to 2.5. The applicant tested different values ​​of the factor on different patients in order to obtain this factor.

[0145] Alternatively, the selection 115 of the K characteristic images IKj (i = 1 to K) comprises a segmentation step known to those skilled in the art implemented by the processing and control module 10 so as to select the portion POi of the image which completely surrounds and delimits the section of the heart in the section plane. Such a segmentation step is, for example, described in the following document “Automated Deep-Learning-based Inversion Time Selection for Cardiac Late Gadolinium Enhancement Imaging, ISMRM 2020, Seung Su Yoon, Michaela Schmidt, Bernd J Wintersperger, Teodora Chitiboi, Puneet Sharma, Christoph Tillmanns, Andreas Maier, and Jens Wetzl”, the algorithm having to be trained by images acquired by a BL-LGE acquisition sequence in the case of BL-LGE imaging and in the following document “Dark blood ischemic LGE segmentation using a deep learning approach” C.Torlasco and Al, European Heart Journal - Cardiovascular Imaging, Volume 22, Issue Supplement_2, June 2021).

[0146] Alternatively, the selection 115 comprises the acquisition of a position of the center of the section of the heart in the section plane of the images on one of the images IMj and the determination, by the processing and control module 10, of a portion of the image IMj centered on the image and of predefined size stored in a memory of the system C.

[0147] The selection step 115 makes it possible, in cardiac imaging, to select a part of the IMj image comprising only blood and the myocardium. It does not require the implementation of precise heart segmentation algorithms.

[0148] Alternatively, the characteristic images IKj are the global images IMj or the portions of images POi.

[0149] Step 116 of determining the optimal set or more specifically the optimal inversion time Tl opt is implemented as described previously, by the processing and control module 10.

[0150] Advantageously, when the optimal inversion time Tl op t is the maximum inversion time, or respectively the minimum inversion time, of the signal acquisition sequences used to generate the characteristic images IKj, then the sequence of steps 112 to 116 of the method is repeated with inversion sequences having respective acquisition times of which the minimum inversion time is the maximum inversion time of the acquisition sequences used to generate the images IKj, or respectively the maximum inversion time is the minimum inversion time of the acquisition sequences used to generate the images IKj. This makes it possible to find the truly optimal inversion time.

[0151] Hardware part

[0152] From a hardware point of view, the processing and control system C, represented in Figure 1, can be seen as a computer interacting with a computer program product.

[0153] System C is a computer, for example, a microcomputer, a computer network, an electronic component a tablet, a smartphone or a personal digital assistant (PDA).

[0154] The system C comprises the processing and control module 10. This processing and control module comprises, for example, one or more processors capable of interpreting instructions in the form of a computer program, a programmable logic circuit, such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a programmable logic device (PLD) and programmable logic arrays (PLA), a system-on-chip (SOC)), an electronic card in which the steps of the method according to the invention are implemented in hardware elements. Steps of the method according to the invention can be executed by a processor, simultaneously or sequentially and / or by one or more processors.

[0155] The processing and control module 10 includes a data processing circuit for performing calculations, a memory operatively coupled to the data processing circuit, a computer-readable medium, and optionally a reader adapted to read the computer-readable medium.

[0156] System C also includes the HMI 11 comprising an input device, an output device and a communication device.

[0157] Each function of the system C is performed by causing the data processing circuit to read a predetermined program from hardware such as the memory of the processing and control module 10 such that the data processing circuit performs calculations, controls communications performed by the communication device and reads and / or writes data to the memory of the calculation module and the computer-readable medium.

[0158] The process is performed on a single computer or on a system distributed among multiple computers (particularly through the use of cloud computing).

[0159] The memory is a computer-readable storage medium and may be configured with, for example, at least one of the following: a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a random access memory (RAM) and another suitable storage medium. The memory may include an operating system and load the programs according to the invention. It includes registers adapted to store parameter variables created and modified during the execution of the aforementioned programs.The program product may include the computer-readable recording medium which is a tangible device, not being a transient signal in itself, may be configured with, for example, at least one of the following: a removable medium, for example, but not limited to, a magneto-optical disc (e.g., a Compact Disc Read-Only Memory (CD-ROM), a Digital Versatile Disc or DVD), a removable disk, a hard disk drive, a smart card, a flash memory device (e.g., a card, a key), a magnetic tape, a database, a server, and other suitable storage medium.

[0160] Alternatively, the program instructions are obtained from an external source and downloaded via a network. This is particularly the case for applications. In this case, the computer program product comprises a computer-readable data carrier on which the program instructions are stored or a data carrier signal on which the program instructions are encoded.

[0161] The invention relates to a computer program product comprising the computer-readable medium containing instructions which, when executed by the data processing circuit, cause the system C to implement the steps of the method according to the invention.

[0162] The form of the program instructions is, for example, a source code form, a computer-executable form, or any intermediate form between a source code and a computer-executable form, such as the form resulting from the conversion of the source code via an interpreter, an assembler, a compiler, a linker, or a locator. Alternatively, the program instructions are microcode, firmware instructions, state definition data, integrated circuit configuration data (e.g., VHDL), or object code. The program instructions are written in any combination of one or more programming languages, for example, an object-oriented programming language (C++, JAVA, Python), a procedural programming language (e.g., C language).

[0163] The user interface or HMI 11 comprises an input device and an output device. The user interface 11 comprises an input device for allowing the user to enter data or commands, for example the Shim box, so as to be able to interact with the programs according to the invention. The input device comprises, for example, a keyboard or a pointing interface, such as a mouse, a light pen, a touchpad, a remote control, a voice recognition device, a haptic device.

[0164] The output device is designed to provide information to a user, either sensorily or electrically, such as visually or audibly. The output interface includes, for example, a graphical interface. The output interface may be the input device, for example, in the case of a touchscreen tablet.

[0165] The display step is implemented by the output device.

[0166] The set of at least one communication device allows communication between the elements of the system C and possibly between at least one element of the system and a device external to the system C, for example the system A. This communication device can establish a physical link between elements of the system C and / or between an element of the system C and a device external to the system C and / or a remote communication link (wireless) between elements of the system C and / or between an element of the system and a device external to the system C.

Claims

CLAIMS Method for determining an optimal characteristic set (Tl op (t) of at least one characteristic parameter (Tl) of a medical signal acquisition sequence for generating a medical image of an area to be imaged by magnetic resonance, the acquisition sequence being configured to substantially cancel medical signals from at least one predetermined tissue, the method comprising the computer-implemented selection of an optimal characteristic image (IK) op t) exhibiting a greater number of pixels of intensity less than or equal to a given intensity threshold (SI) among a plurality of characteristic images (IKj) of a characteristic area of ​​the area to be imaged generated from signals acquired by respective acquisition sequences having sets of at least one distinct respective characteristic parameter (Th), the optimal characteristic set (Tl opt) being the characteristic set (Th) of the signal acquisition sequence by means of which the optimal characteristic image (IK) op t) was generated. Method according to claim 1, wherein the medical signal acquisition sequence is a late gadolinium-enhanced dark blood acquisition sequence. Method according to claim 2, wherein the characteristic area comprises only portions of the myocardium and blood. Method according to any one of the preceding claims, wherein the characteristic set is an inversion time. Method according to any one of the preceding claims, comprising the determination of the intensity threshold (IT) comprising: ■ Calculation (21) of histograms (HISTj) of the characteristic images (IKj) of the characteristic area, ■ determination (22) of an intensity of the global maximum (M) of the histograms (HISTj).

6. A method according to any one of the preceding claims, comprising selecting characteristic images (IKj) of the characteristic area from images of the area to be imaged (IMj).

7. A method according to any one of the preceding claims, comprising the following sequence of steps: ■ Acquisition of signals using the respective acquisition sequences, ■ generation of characteristic images (I Kj) from the signals.

8. Method according to claim 7, wherein the step sequence and the selection of the optimal characteristic image are repeated with inversion times different from those of the acquisition sequences when the optimal inversion time is a maximum or minimum inversion time of the acquisition sequences.

9. Method for generating a medical image of the area to be imaged comprising determining the optimal set of at least one characteristic parameter by the method according to any one of claims 1 to 8, and acquiring medical signals by a medical acquisition sequence having the optimal characteristic set and generating the medical image from the medical signals.

10. Processing system (C) comprising a processor configured to implement the steps of the process according to any one of claims 1 to 6.

11. Product computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the process according to any one of claims 1 to 6. A computer-readable recording medium comprising instructions which, when executed by a computer, cause the computer to carry out the process according to any one of claims 1 to 6. A magnetic resonance imaging system comprising a magnetic resonance system (A) comprising a static magnetic field generator (1), a gradient generator (2), a radio frequency device (3) and a processing and control system (C) configured to carry out the steps of the process according to any one of claims 1 and 6 and to control the magnetic resonance system (A) so that the imaging system carries out the process according to any one of claims 7 to 9.

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