JP6325188B2 - Magnetic resonance imaging apparatus and image processing apparatus - Google Patents

Description

  Embodiments described herein relate generally to a magnetic resonance imaging apparatus and an image processing apparatus.

  Conventionally, in the examination of breast cancer or the like, non-contrast-Brest Magnetic Resonance Imaging (NC-BMRI) that picks up an MR image of the chest without using a contrast agent can be used to distinguish a tumor that has occurred in the breast. Has been done. In this discrimination method by NC-BMRI, for example, a plurality of BBTIs (Black Blood Time to Inversion) are changed using a Time-SLIP (Time Spatial Labeling Inversion Pulse) method capable of rendering blood flow without contrast. MR images of the chest are taken. Then, based on each captured MR image, a perfusion curve is created with BBTI on the horizontal axis and signal intensity on the vertical axis, and the benign / malignant discrimination of the tumor is performed from the inclination of the perfusion curve.

JP 2010-201154 A

  The problem to be solved by the present invention is to provide a magnetic resonance imaging apparatus and an image processing apparatus that can distinguish between benign and malignant tumors without using a contrast agent.

A magnetic resonance imaging (MRI) apparatus according to an embodiment includes a sequence control unit, a generation unit, and a discrimination unit. The sequence control unit performs a sequence of starting the collection of the magnetic resonance data after the inversion time has elapsed after applying the inversion recovery pulse enabling the blood flow in the breast of the subject to be identified multiple times with different inversion times. Run. The generation unit generates a plurality of blood flow images having different inversion times based on the magnetic resonance data collected by the sequence. Discriminating unit, for said plurality of inversion time is different Chiryuga Zoso respectively, to evaluate the number of blood flow images representative value of luminance values in the region of interest is equal to or greater than a predetermined threshold value, the corresponding blood The greater the number of flow images, the higher the malignancy of the tumor .

FIG. 1 is a diagram showing an overall configuration of the MRI apparatus according to the first embodiment. FIG. 2 is a diagram for explaining tumor malignancy and angiogenesis. FIG. 3 is a block diagram showing a detailed configuration of the MRI apparatus according to the first embodiment. FIG. 4 is a diagram illustrating the setting of the labeling region by the tag region setting unit according to the first embodiment. FIG. 5 is a diagram (1) for explaining setting of a threshold value by the tumor discrimination unit according to the first embodiment. FIG. 6 is a diagram (2) for explaining setting of a threshold value by the tumor discrimination unit according to the first embodiment. FIG. 7 is a diagram (1) illustrating a display example of the discrimination result by the tumor discrimination unit according to the first embodiment. FIG. 8 is a diagram (2) illustrating a display example of the discrimination result by the tumor discrimination unit according to the first embodiment. FIG. 9 is a flowchart showing the flow of benign / malignant discrimination by the MRI apparatus according to the first embodiment. FIG. 10 is a diagram illustrating a configuration of an image processing apparatus according to the second embodiment.

  Hereinafter, embodiments of an MRI apparatus and an image processing apparatus will be described with reference to the drawings. In the embodiment described below, a case where a benign / malignant tumor in a breast of a subject is differentiated will be described. However, the MRI apparatus and the image processing apparatus according to the present embodiment can detect tumors occurring in a region other than the breast. The same can be applied to the discrimination between benign and malignant.

(First embodiment)
First, the first embodiment will be described. FIG. 1 is a diagram showing an overall configuration of an MRI apparatus 100 according to the first embodiment. As shown in FIG. 1, the MRI apparatus 100 includes a gantry unit 10, a gradient magnetic field power supply 20, a transmission unit 30, a reception unit 40, a sequence control unit 50, a bed unit 60, a bed control unit 70, And a computer system 80.

  The gantry 10 includes an opening into which the subject P is inserted, and a collection unit that collects MR signals representing the inside of the subject P inserted into the opening. The collecting means here irradiates a subject P placed in a static magnetic field with a high-frequency magnetic field, thereby collecting MR signals emitted from the subject P. The gantry unit 10 includes a static magnetic field magnet 11, a gradient magnetic field coil 12, a transmission RF (Radio Frequency) coil 13, and a reception RF coil 14 as collection means.

  The static magnetic field magnet 11 is formed in a hollow cylindrical shape, and generates a uniform static magnetic field in a space in the cylinder. For example, a permanent magnet or a superconducting magnet is used as the static magnetic field magnet 11.

  The gradient coil 12 is formed in a hollow cylindrical shape and is disposed inside the static magnetic field magnet 11. The gradient coil 12 has three coils corresponding to the X, Y, and Z axes orthogonal to each other. Each coil receives a current supply from a gradient magnetic field power source 20 described later, and generates a gradient magnetic field whose magnetic field intensity changes along each of the X, Y, and Z axes. The Z-axis direction is the same as the static magnetic field.

  The gradient magnetic fields of the X, Y, and Z axes generated by the gradient coil 12 correspond to, for example, the slice selection gradient magnetic field Gs, the phase encoding gradient magnetic field Ge, and the readout gradient magnetic field Gr, respectively. The slice selection gradient magnetic field Gs is used to arbitrarily determine an imaging section. The phase encoding gradient magnetic field Ge is used to change the phase of a magnetic resonance signal (MR signal) according to a spatial position. The readout gradient magnetic field Gr is used for changing the frequency of the magnetic resonance signal in accordance with the spatial position.

  The transmission RF coil 13 is arranged inside the gradient magnetic field coil 12 and generates a high frequency magnetic field by receiving a supply of a high frequency pulse from a transmission unit 30 described later.

  The reception RF coil 14 is disposed inside the gradient magnetic field coil 12 and receives a magnetic resonance signal radiated from the subject P due to the influence of the high-frequency magnetic field generated by the transmission RF coil 13. Then, the receiving RF coil 14 outputs the received magnetic resonance signal to the receiving unit 40. Note that the receiving RF coil 14 used in the first embodiment is a breast imaging coil, and is mounted on the chest of the subject placed on the top board 61. Here, the reception RF coil 14 may be used that is incorporated in the top board 61 as a coil for breast imaging. In this case, the subject P is placed on the receiving RF coil 14 in the prone position at the time of diagnosis.

  The gradient magnetic field power supply 20 supplies a current to the gradient magnetic field coil 12. The transmission unit 30 transmits a high-frequency pulse corresponding to the Larmor frequency to the transmission RF coil 13. The receiving unit 40 generates magnetic resonance data by digitizing the MR signal output from the receiving RF coil 14, and transmits the generated magnetic resonance data to the sequence control unit 50.

  The sequence control unit 50 scans the subject P by driving the gradient magnetic field power source 20, the transmission unit 30, and the reception unit 40 based on the sequence information transmitted from the computer system 80. When the magnetic resonance data is transmitted from the receiving unit 40 as a result of scanning the subject P, the sequence control unit 50 transfers the magnetic resonance data to the computer system 80.

  The sequence information here means the strength of power supplied to the gradient coil 12 by the sequence controller 50 and the timing of supplying power, the strength of the RF signal transmitted from the transmitter 30 to the RF coil 13 for transmission, and RF. This is information defining a procedure for performing a scan, such as a signal transmission timing and a timing at which the receiving unit 40 detects a magnetic resonance signal.

  The bed unit 60 includes a top plate 61 on which the subject P is placed, and the top plate 61 is inserted into the opening of the gantry unit 10 together with the subject P. The bed part 60 is installed such that the longitudinal direction is parallel to the central axis of the static magnetic field magnet 11.

  Under the control of the computer system 80, the bed control unit 70 drives the bed unit 60 to move the table 61 in the longitudinal direction and the vertical direction.

  The computer system 80 is a device that performs overall control of the MRI apparatus 100, data collection, image reconstruction, and the like, and includes an interface unit 81, an input unit 82, a display unit 83, a storage unit 84, and a data processing unit 85. And a control unit 86.

  The interface unit 81 controls input / output of various signals exchanged with the sequence control unit 50. For example, the interface unit 81 transmits sequence information to the sequence control unit 50 and receives magnetic resonance data from the sequence control unit 50. Further, when receiving the magnetic resonance data, the interface unit 81 stores the received magnetic resonance data in the storage unit 84 for each subject P.

  The input unit 82 receives various instructions and information input from the operator. For example, the input unit 82 receives setting of imaging conditions from the operator. As the input unit 82, for example, a pointing device such as a mouse or a trackball, a selection device such as a mode switch, or an input device such as a keyboard is used.

  The display unit 83 displays various images referred to by the operator and a GUI (Graphical User Interface) for receiving various operations from the operator. As the display unit 83, for example, a display device such as a liquid crystal monitor or a CRT monitor is used.

  The storage unit 84 stores the magnetic resonance data transmitted from the sequence control unit 50 and the image data generated by the data processing unit 85 described later for each subject P.

  The data processing unit 85 generates image data representing the inside of the subject P by performing post-processing, that is, reconstruction processing such as Fourier transform processing on the magnetic resonance data stored in the storage unit 84.

  The control unit 86 performs overall control of the MRI apparatus 100 by performing control movement between the above-described function units and data transfer between the function units and the storage unit. The control unit 86 includes a CPU (Central Processing Unit) and a memory, and controls various units included in the MRI apparatus 100 by executing various programs using them. For example, the control unit 86 generates sequence information based on the imaging conditions set by the operator, and transmits the generated sequence information to the sequence control unit 50 to execute various types of imaging.

  The overall configuration of the MRI apparatus 100 according to the first embodiment has been described above. Based on such a configuration, the MRI apparatus 100 according to the first embodiment provides a discrimination method capable of accurately discriminating between benign and malignant tumors without using a contrast agent.

  Conventionally, in examinations such as breast cancer, diagnosis using contrast-enhanced MRI is performed in addition to diagnosis by X-ray mammography images and ultrasonic images. In this diagnosis by contrast-enhanced MRI, for example, tumor discrimination is performed using an MR image of the breast (Breast) imaged by dynamic enhanced breast MRI (DE-BMRI).

  Specifically, in the tumor discrimination method by DE-BMRI, a time-series contrast dynamic (DCE: Dynamic Contrast Enhancement) image in the chest is taken by dynamically imaging a subject in which a contrast medium has been injected in advance. Then, a perfusion curve representing a contrast effect by the contrast agent, that is, a change in the temporal dyeing state of the chest due to the contrast agent is created based on each DCE image taken, and the inflow of the contrast agent in the perfusion curve By examining temporal changes in the (Wash-in) portion and the outflow (Wash-out) portion, benign / malignant differentiation of the tumor depicted in the DCE image is performed.

  On the other hand, there is also a method using NC-BMRI as a method for distinguishing tumors without using a contrast agent. In this discrimination method using NC-BMRI, for example, MR images of a plurality of breasts with different BBTIs are captured using a Time-SLIP method capable of rendering a blood flow without contrast. Then, based on each captured MR image, a perfusion curve is created with BBTI on the horizontal axis and signal intensity on the vertical axis, and the benign / malignant discrimination of the tumor is performed from the inclination of the perfusion curve. In this method, it is assumed that when the tumor is malignant, the slope of the perfusion curve is larger than when it is benign.

  As described above, there are various methods in the prior art relating to the differentiation of a tumor in the breast, but each has the following problems.

  For example, in DE-BMRI, a Gd (gadolinium) -based contrast agent is administered. Recently, there is a relationship between a Gd-based contrast agent and nephrogenic systemic fibrosis (NSF). It has been pointed out that there is. In addition, administration of a Gd-based contrast agent is contraindicated in hemochromatosis patients.

  Moreover, in the tumor discrimination method by DE-BMRI, since the first time phase in which a blood flow image is obtained with sufficient contrast is the inflow portion within about 60 seconds after the contrast agent is injected, the contrast agent is injected. A blood flow image cannot be obtained with sufficient contrast unless the first dyeing point due to the contrast medium is acquired as a contrast effect within about 60 seconds. For this reason, there exists a subject that time resolution has restrictions.

  Moreover, in the tumor discrimination method by NC-BMRI, as described above, when the tumor is malignant, it is assumed that the slope of the perfusion curve becomes larger than that when it is benign. This assumption is based on the assumption that when the tumor is malignant, it is fed at a faster rate from the feeding vessel, but this assumption is considered to be valid when a contrast agent is used. In other words, when a contrast agent is used, the contrast agent is not only taken into the tumor by physical inflow from vegetative blood vessels, but is also taken into the tumor by the uptake of cells by the phagocytosis of cancer cells. The premise is that nourishment takes place at a faster rate than in normal areas. However, NC-BMRI, which observes only the nutrient vessels that enter the tumor, does not necessarily hold this premise. From this, it is considered difficult to discriminate between benign and malignant tumors from the slope of the linear perfusion curve obtained by NC-BMRI.

  In response to such a problem in the prior art, the MRI apparatus 100 according to the first embodiment provides a tumor differentiation method that does not use a contrast agent from a new viewpoint. Specifically, the tumor discrimination method according to the first embodiment is based on the fact that when the tumor becomes malignant, angiogenesis increases as the malignancy increases.

  FIG. 2 is a diagram for explaining tumor malignancy and angiogenesis. (A)-(f) of FIG. 2 has shown the tumor and the nutritional blood vessel, and has shown a mode that the nutritional blood vessel is gradually born with malignant transformation of the tumor. Specifically, (a) in FIG. 2 shows a state before the tumor 1 becomes malignant, and (b) in FIG. 2 shows that the tumor 1 starts to become malignant, and accordingly, from the feeding blood vessel 2. The state where the new nutrition blood vessel 3 has begun to be born is shown. Moreover, (c) of FIG. 2 shows a state in which cancer cells have proliferated and malignant transformation of the tumor has progressed, and a number of vegetative blood vessels 3 have been regenerated around the tumor, and (d) of FIG. The state of the branched part of the basic nutritional blood vessel 2 and the newly formed nutritional blood vessel 3 is shown. 2 (e) shows a state in which a new tumor 4 has developed due to metastasis, and FIG. 2 (f) shows that malignant transformation of the new tumor 4 has progressed, and there are feeding vessels 5 around it. Indicates a newly born state.

  As shown in (a) to (f) of FIG. 2, when a tumor starts to become malignant, a blood vessel is gradually formed, and further, as the cancer cell grows (malignancy increases), the tumor develops a blood vessel. It becomes. Thus, angiogenesis always accompanies tumor malignancy. Therefore, benign and malignant tumors are thought to depend on the number of nutrient vessels, not the blood flow velocity of the nutrient vessels supplying the tumor.

  Therefore, for example, the MRI apparatus 100 according to the first embodiment executes a sequence for rendering the blood flow in the breast of the subject non-contrast a plurality of times, and based on the collected magnetic resonance data, A plurality of blood flow images are generated. Then, the MRI apparatus 100 evaluates a blood flow image including a luminance value equal to or higher than a predetermined threshold among the plurality of blood flow images, and discriminates whether the tumor generated in the breast is benign or malignant.

  As described above, when a tumor becomes malignant, the number of nutritional blood vessels that supply nutrients to the tumor increases due to angiogenesis. For this reason, the higher the malignancy of the tumor, the more blood is drawn around the tumor in the blood flow image. In addition, it is assumed that a plurality of nutritional blood vessels that increase due to angiogenesis are different in thickness and length, and the blood flow velocity in each blood vessel is also different. For this reason, when the number of vegetative blood vessels increases due to angiogenesis, blood is drawn around the tumor at more time points in a plurality of blood flow images captured in time series. In other words, the higher the malignancy of the tumor, the more blood is drawn around the tumor in the blood flow image taken in time series, and the blood is drawn around the tumor at more points in time. become.

  According to the MRI apparatus 100 according to the first embodiment, among a plurality of blood flow images generated in time series, a blood flow image including a luminance value equal to or higher than a predetermined threshold is evaluated, and tumor differentiation is performed. Therefore, benign and malignant tumors are identified based on whether or not the number of vegetative blood vessels has increased due to angiogenesis. Therefore, according to the first embodiment, it is possible to differentiate between benign and malignant tumors in a subject with high accuracy without invasion such as contrast, exposure, or biopsy.

  Hereinafter, the configuration of the MRI apparatus 100 described above will be described in detail.

  FIG. 3 is a block diagram showing a detailed configuration of the MRI apparatus 100 according to the first embodiment. FIG. 3 shows only the sequence control unit 50 and the computer system 80 among the units shown in FIG. For the computer system 80, only the storage unit 84, the data processing unit 85, and the control unit 86 are shown. As shown in FIG. 3, the storage unit 84 includes a magnetic resonance data storage unit 84a and an image data storage unit 84b.

  The magnetic resonance data storage unit 84a stores the magnetic resonance data transmitted from the sequence control unit 50. For example, the magnetic resonance data storage unit 84a stores magnetic resonance data collected by executing the sequence set by the anatomical image acquisition sequence setting unit 86b. In addition, for example, the magnetic resonance data storage unit 84a stores magnetic resonance data collected by executing a Time-SLIP sequence set by a Time-SLIP sequence setting unit 86c described later.

  The image data storage unit 84b stores the image data generated by the data processing unit 85. For example, the image data storage unit 84b stores an anatomical image generated by an anatomical image generation unit 85a described later, a blood flow image generated by a blood flow image generation unit 85b described later, and the like. Furthermore, the image data storage unit 84b also stores images captured by other modalities. For example, an X-ray mammography image captured by an X-ray mammography apparatus, an ultrasound diagnostic image captured by an ultrasound diagnostic apparatus, and the like are stored.

  Further, as shown in FIG. 3, the control unit 86 includes an imaging condition setting unit 86a. The imaging condition setting unit 86a receives input of various imaging parameters from an operator via the input unit 82, and sets imaging conditions based on the input imaging parameters. Then, the imaging condition setting unit 86a generates sequence information based on the set imaging conditions, and transmits the generated sequence information to the sequence control unit 50, thereby executing sequences by various imaging methods.

  For example, the imaging condition setting unit 86a sets a sequence for acquiring an anatomical image. Further, for example, the imaging condition setting unit 86a sets a sequence of the Time-SLIP method or the like as a sequence for rendering the blood flow in the breast of the subject without contrast. Specifically, the imaging condition setting unit 86a includes an anatomical image acquisition sequence setting unit 86b and a Time-SLIP sequence setting unit 86c.

  The anatomical image acquisition sequence setting unit 86b sets a sequence for acquiring an anatomical image. For example, the anatomical image acquisition sequence setting unit 86b sets a sequence for acquiring a T1W (T1 Weighted) image, a sequence for acquiring a T2W (T2 Weighted) image, and the like.

  The Time-SLIP sequence setting unit 86c sets an imaging sequence using the Time-SLIP method with the anatomical image acquired by executing the sequence set by the anatomical image acquisition sequence setting unit 86b as a reference image. Specifically, the Time-SLIP sequence setting unit 86c includes a tag area setting unit 86d and a BBTI setting unit 86e.

  In the Time-SLIP method, an inversion recovery (IR) pulse called a spin labeling pulse for labeling (also referred to as labeling or tagging) or identifying blood flowing into an imaging region is used as a pre-pulse as FBI (Fresh Blood). This is a method for controlling the contrast of an image by applying it prior to an imaging sequence such as an imaging (SS) sequence or an SSFP (Steady State Free Precession) sequence. A spin labeling pulse for labeling blood is called an ASL (Arterial Spin Labeling) pulse. In the Time-SLIP method, a Time-SLIP pulse composed of a plurality of ASL pulses is applied.

  The Time-SLIP pulse is applied after a certain delay time has elapsed from the R wave of the ECG signal, and after the BBTI corresponding to the inversion time has elapsed from the timing at which the Time-SLIP pulse is applied, the RF in the imaging sequence is applied. An excitation pulse is applied. Then, after the effective echo time has elapsed from the application of the RF excitation pulse, the magnetic resonance signals at the center of the k space are collected. For this reason, it is possible to emphasize or suppress the signal intensity of only the blood that has reached the imaging region after BBTI has elapsed.

  The Time-SLIP pulse is composed of a region non-selective IR pulse and a region selective IR pulse. For example, if the longitudinal magnetization is reversed by labeling the labeled region set in the imaging region with the region-selected IR pulse with the region non-selective IR pulse turned off, it flows into the labeled region after the BBTI has elapsed. The signal intensity of the part where the blood that has not been labeled (that is, the longitudinal magnetization is not reversed) has reached becomes high. For this reason, the moving direction and distance of blood can be grasped. That is, it is possible to selectively emphasize or suppress the signal intensity of only blood that has reached the imaging region after the inversion time.

  The tag area setting unit 86d sets a labeling area to which the Time-SLIP pulse is applied, using the anatomical image obtained by imaging the breast of the subject as a reference image. Specifically, the tag area setting unit 86 d receives an operation for designating an area on the anatomical image from the operator via the input unit 82 using the anatomical image displayed on the display unit 83 as a reference image. Then, the tag area setting unit 86d sets an area designated on the anatomical image as a labeling area.

  FIG. 4 is a diagram illustrating the setting of the labeling region by the tag region setting unit 86d according to the first embodiment. As illustrated in FIG. 4, for example, the tag region setting unit 86 d sets the labeling region 9 on the anatomical image 6 so as to include the region of interest 7 and the epidermis 8 which are tumor regions. Since the blood vessels that pass through the breasts run close to the epidermis, the labeling region is set so that the region of interest and the epidermis are included in this way, so that new blood vessels near the region of interest are also included in the labeling region 9 It comes to be.

  Returning to FIG. 3, the BBTI setting unit 86e sets the BBTI in the sequence of the Time-SLIP method. In the first embodiment, the BBTI setting unit 86e sets a plurality of different values of BBTI in order to execute the Time-SLIP method sequence a plurality of times while changing the BBTI. Specifically, the BBTI setting unit 86e receives input of a plurality of different BBTI values from the operator via the input unit 82. Then, the BBTI setting unit 86e sets a plurality of BBTIs used in a sequence by the Time-SLIP method using the plurality of input BBTI values.

  The sequence control unit 50 executes various sequences based on the imaging conditions set by the imaging condition setting unit 86a. Then, the sequence control unit 50 stores the magnetic resonance data collected by the various executed sequences in the magnetic resonance data storage unit 84a.

  Specifically, the sequence control unit 50 executes the sequence set by the anatomical image acquisition sequence setting unit 86b. For example, the sequence control unit 50 executes a sequence for acquiring a T1W image and a sequence for acquiring a T2W image.

  Further, the sequence control unit 50 executes a sequence for rendering the blood flow in the breast of the subject non-contrast a plurality of times. Specifically, the sequence control unit 50 sequentially uses the plurality of BBTIs set by the BBTI setting unit 86e, and changes the BBTI while changing the time-SLIP method sequence set by the Time-SLIP sequence setting unit 86c. Run multiple times.

  As shown in FIG. 3, the data processing unit 85 includes an anatomical image generation unit 85a, a blood flow image generation unit 85b, and a tumor discrimination unit 85c.

  The anatomical image generation unit 85a generates an anatomical image based on the magnetic resonance data collected by executing the sequence set by the anatomical image acquisition sequence setting unit 86b. Specifically, the anatomical image generation unit 85a, after the sequence control unit 50 executes the sequence set by the anatomical image acquisition sequence setting unit 86b, the magnetic resonance data collected by the sequence is stored in the magnetic resonance data storage unit. Read from 84a. Then, the anatomical image generation unit 85a generates a anatomical image by performing predetermined image processing determined for each type of image on the read magnetic resonance data. For example, the anatomical image generation unit 85a generates a T1W image, a T2W image, or the like as the anatomical image. Then, the anatomical image generation unit 85a stores the generated anatomical image data in the image data storage unit 84b.

  The blood flow image generation unit 85b generates a plurality of blood flow images in time series based on the magnetic resonance data collected by the sequence for rendering the blood flow in the breast of the subject without contrast. Specifically, the blood flow image generation unit 85b executes the sequence of the time-SLIP method set by the time-SLIP sequence setting unit 86c a plurality of times while changing the BBTI after the sequence control unit 50 performs each sequence. The collected magnetic resonance data is read from the magnetic resonance data storage unit 84a. Then, the blood flow image generation unit 85b generates a blood flow image for each BBTI based on the read magnetic resonance data. Then, the blood flow image generation unit 85b stores the data of the generated blood flow image in the image data storage unit 84b.

  The tumor discrimination unit 85c evaluates a blood flow image including a luminance value equal to or higher than a predetermined threshold among the plurality of blood flow images generated by the blood flow image generation unit 85b, and the tumor generated in the breast is benign. Distinguish between malignant and malignant. Specifically, the tumor discrimination unit 85c evaluates the number of blood flow images including a luminance value equal to or higher than a predetermined threshold, and discriminates that the greater the number of corresponding blood flow images, the higher the malignancy of the tumor. The predetermined threshold used by the tumor discrimination unit 85c is set to an arbitrary value by the operator, for example. Alternatively, the predetermined threshold used by the tumor discrimination unit 85c may be set based on a blood flow image related to the breast on the opposite side of the breast to be diagnosed.

  5 and 6 are diagrams for explaining threshold setting by the tumor discrimination unit 85c according to the first embodiment. 5 and 6, the horizontal axis represents the BBTI of each blood flow image, and the vertical axis represents the luminance value of each blood flow image. Here, the luminance value of each blood flow image is a representative value of a plurality of luminance values at pixel positions in the region of interest, which is a tumor region depicted in the blood flow image. The representative value here is, for example, an average value, median value, maximum value, minimum value, or the like. 5 and 6, black circles indicate the luminance value of the blood flow image relating to the breast to be diagnosed, and white circles indicate the luminance value of the blood flow image relating to the opposite breast.

  For example, as illustrated in FIG. 5, the tumor discrimination unit 85c sets a threshold value T of the luminance value for each BBTI. For example, the tumor discrimination unit 85c sets a threshold value for each of the plurality of blood flow images related to the breast to be diagnosed based on the luminance value of the corresponding blood flow image among the plurality of blood flow images related to the opposite breast. Specifically, when setting a threshold value for a blood flow image related to the breast to be diagnosed, the tumor discrimination unit 85c first refers to the image data storage unit 84b, and among the plurality of blood flow images related to the opposite breast A blood flow image of the same BBTI is acquired. And the tumor discrimination | determination part 85c calculates | requires the representative value of the luminance value contained in the area | region in the same position as the region of interest in the blood-flow image regarding the breast to be diagnosed in the acquired blood-flow image. Thereafter, the tumor discrimination unit 85c sets a value obtained by multiplying the obtained representative value by 1 to N times (N is a real number) as a threshold used for a blood flow image related to the breast to be diagnosed. Here, the real number N is estimated by, for example, statistically estimating the relationship between the luminance value of the tumor to be distinguished from malignant and the luminance value of the normal region using a blood flow image of the breast imaged in the past. Set according to the relationship. Note that the example shown in FIG. 5 shows a case where N = 2.

  Moreover, as shown in FIG. 6, the tumor discrimination | determination part 85c may set the same threshold value T for every BBTI. For example, the tumor discrimination unit 85c calculates an average value of luminance values from a plurality of blood flow images related to the breast on the opposite side of the breast to be diagnosed, and sets a threshold value based on the calculated average value. Specifically, when setting a threshold value for a blood flow image related to the breast to be diagnosed, the tumor discrimination unit 85c first refers to the image data storage unit 84b and acquires a plurality of blood flow images related to the opposite breast. To do. And the tumor discrimination | determination part 85c calculates | requires the representative value of the luminance value contained in the area | region in the same position as the region of interest in the blood flow image regarding the breast to be diagnosed for each acquired blood flow image. Furthermore, the tumor discrimination part 85c calculates | requires the average value of the representative value calculated | required for every blood-flow image. Thereafter, the tumor discrimination unit 85c sets a value obtained by multiplying the obtained representative value by 1 to M times (M is a real number) as a threshold used for a blood flow image related to the breast to be diagnosed. Here, the real number N is estimated by, for example, statistically estimating the relationship between the luminance value of the tumor to be distinguished from malignant and the luminance value of the normal region using a blood flow image of the breast imaged in the past. Set according to the relationship. The example shown in FIG. 6 shows a case where M = 2.

  In this way, by setting the predetermined threshold used by the tumor discrimination unit 85c based on the blood flow image related to the breast on the opposite side of the breast to be diagnosed, a different threshold is set for each subject. . That is, by setting the threshold value in this way, an appropriate threshold value can be set according to each subject.

  After setting the threshold value in this way, the tumor discrimination unit 85c specifies a blood flow image including a luminance value equal to or higher than the threshold value among the plurality of blood flow images generated for each BBTI by the blood flow image generation unit 85b. And the tumor discrimination | determination part 85c discriminate | determines that the malignancy degree of a tumor is so high that there are many specified blood-flow images. For example, the tumor discrimination unit 85c sets a plurality of threshold values for determining malignancy in stages, and compares the number of identified blood flow images with each threshold to differentiate malignancy in stages. .

  As a specific example, for example, the tumor discrimination unit 85c sets a first threshold for determining malignancy and a second threshold smaller than the first threshold, and the number of identified blood flow images is If it is greater than or equal to the first threshold, the malignancy is determined to be “high”. Moreover, the tumor discrimination | determination part 85c determines that a malignancy is "medium", when the number of the specified blood-flow images is less than a 1st threshold value and is more than a 2nd threshold value. Moreover, the tumor discrimination | determination part 85c determines that a malignancy is "low", when the number of the specified blood-flow images is less than a 2nd threshold value.

  Then, the tumor discrimination unit 85 c displays the discrimination result on the display unit 83. For example, the tumor discrimination unit 85c arranges and outputs a plurality of breast blood flow images generated for each BBTI by the blood flow image generation unit 85b on the display unit 83, and also displays the result of discrimination between benign and malignant tumors. Output to.

  7 and 8 are diagrams showing display examples of discrimination results by the tumor discrimination unit 85c according to the first embodiment. Here, FIG. 7 is a display example when the malignancy of the tumor is high, and FIG. 8 is a display example when the malignancy of the tumor is low. 7 and 8, white arrows indicate regions where the luminance value is equal to or greater than a predetermined threshold, that is, tumor regions.

  For example, when five blood flow images having different BBTIs are used, it is assumed that the first threshold value in the above-described example is “4” and the second threshold value is set to “2”. In that case, for example, as shown in FIG. 7, when there are four blood flow images including a luminance value equal to or higher than a predetermined threshold among the five blood flow images, the tumor discrimination unit 85 c has a malignancy of “ It is determined that it is “high”. Then, the tumor discrimination unit 85c displays the letters “malignancy: high” on the display unit 83 together with the blood flow images. For example, as shown in FIG. 8, when there is one blood flow image including a luminance value equal to or higher than a predetermined threshold among the five blood flow images, the tumor discrimination unit 85c has a malignancy of “low”. Judge that there is. Then, the tumor discrimination unit 85c displays the characters “malignancy: low” on the display unit 83 together with each blood flow image.

  In addition, the display examples shown in FIGS. 7 and 8 are examples, and the display examples by the tumor discrimination unit 85c are not limited thereto. For example, a different color may be defined for each level of malignancy, and a color corresponding to the determined malignancy may be displayed over the tumor region. For example, as shown in FIGS. 5 and 6, the display unit 83 may display the result of plotting the luminance value of each blood flow image with the horizontal axis as BBTI and the vertical axis as the luminance value.

  Next, the flow of benign / malignant discrimination by the MRI apparatus 100 according to the first embodiment will be described. FIG. 9 is a flowchart showing a flow of benign / malignant discrimination by the MRI apparatus 100 according to the first embodiment.

  As shown in FIG. 9, first, the MRI apparatus 100 captures an anatomical image of a breast to be diagnosed (step S101). Specifically, the anatomical image acquisition sequence setting unit 86b sets a sequence for acquiring the anatomical image of the breast to be diagnosed. Thereafter, the sequence control unit 50 executes the sequence set by the anatomical image acquisition sequence setting unit 86b. Then, the anatomical image generation unit 85a generates an anatomical image based on the magnetic resonance data collected by executing the sequence set by the anatomical image acquisition sequence setting unit 86b.

  Subsequently, the MRI apparatus 100 displays the captured anatomical image (step S102). Specifically, in response to a display request from the operator, the control unit 86 reads out the anatomical image of the breast generated by the anatomical image generation unit 85a from the image data storage unit 84b and causes the display unit 83 to display it. For example, the control unit 86 causes the display unit 83 to display a T1W image or a T2W image as an anatomical image.

  Subsequently, the MRI apparatus 100 displays an X-ray mammography image and an ultrasonic diagnostic image of the breast to be diagnosed on the display unit 83 (step S103). Specifically, in response to a display request from the operator, the control unit 86 reads out an X-ray mammography image or an ultrasonic diagnostic image in which a breast to be diagnosed is imaged from the image data storage unit 84b, and together with the anatomical image It is displayed on the display unit 83. At this time, for example, an operator (for example, a doctor) of the MRI apparatus 100 detects the tumor on the anatomical image with reference to the tumor found in the X-ray mammography image or the ultrasonic diagnostic image. Then, the operator evaluates the shape and size of the detected tumor.

  Subsequently, the MRI apparatus 100 sets a labeled region of the Time-SLIP pulse using the anatomical image as a reference image (step S104). Specifically, the tag region setting unit 86d accepts an operation for designating a region on the anatomical image using the anatomical image displayed on the display unit 83 as a reference image, and the region designated on the anatomical image. Is set as a labeling region.

  Subsequently, the MRI apparatus 100 sets a plurality of different BBTIs (step S105). Specifically, the BBTI setting unit 86e receives input of a plurality of different BBTI values from the operator, and sets a plurality of BBTIs used in a sequence by the Time-SLIP method using the plurality of input BBTI values. .

  Subsequently, the MRI apparatus 100 collects a plurality of blood flow images having different BBTIs by the Time-SLIP method (Step S106). Specifically, the sequence control unit 50 sequentially uses the plurality of BBTIs set by the BBTI setting unit 86e to change the BBTI, and changes the sequence of the Time-SLIP method set by the Time-SLIP sequence setting unit 86c. Run multiple times. Then, the blood flow image generation unit 85b generates a blood flow image for each BBTI based on the magnetic resonance data collected by the sequence of the Time-SLIP method.

  Subsequently, the MRI apparatus 100 distinguishes whether the tumor is benign or malignant using a plurality of blood flow images (step S107). Specifically, the tumor discrimination unit 85c evaluates a blood flow image including a luminance value equal to or higher than a predetermined threshold among a plurality of blood flow images generated by the blood flow image generation unit 85b, and is generated in the breast. Differentiate whether the tumor is benign or malignant. At this time, the tumor discrimination unit 85c evaluates the number of blood flow images including a luminance value equal to or greater than a predetermined threshold, and discriminates that the greater the number of corresponding blood flow images, the higher the malignancy of the tumor.

  Subsequently, the MRI apparatus 100 displays the discrimination result (step S108). Specifically, the tumor discrimination unit 85c causes the display unit 83 to display a result of discriminating whether the tumor is benign or malignant. For example, the tumor discrimination unit 85c causes the display unit 83 to display the level of malignancy of the tumor together with a plurality of blood flow images having different BBTIs.

  As described above, according to the MRI apparatus 100 according to the first embodiment, a plurality of time-series blood flow images in which blood flow in the breast of the subject is depicted without contrast is collected, and the collected plurality of blood flows A blood flow image including a luminance value equal to or higher than a predetermined threshold is evaluated from the images to discriminate benign or malignant tumors in the breast. Therefore, it becomes possible to differentiate between benign and malignant tumors taking into account the neovascularization associated with tumor malignancy, and the benign and malignant tumors in the subject can be accurately detected without invasion such as imaging, exposure or biopsy. Can be distinguished.

(First modification according to the first embodiment)
In the first embodiment described above, the tumor discrimination unit 85c evaluates the number of blood flow images including a luminance value equal to or higher than a predetermined threshold, and the more the number of corresponding blood flow images, the more malignant the tumor is. The example which discriminate | determines as high was demonstrated. However, the method of identifying a tumor is not limited to this. For example, the tumor discriminating unit 85c evaluates the variation between the blood flow images of the area occupied by the pixel having the luminance value equal to or higher than a predetermined threshold, and discriminates that the greater the variation in the area, the higher the malignancy of the tumor. Also good. The threshold value in this case may be set to an arbitrary value by the operator, for example, or may be set based on a blood flow image related to the breast on the opposite side of the breast to be diagnosed.

  In this case, for example, the tumor discrimination unit 85c specifies a blood flow image including a luminance value equal to or higher than a predetermined threshold among a plurality of blood flow images generated for each BBTI by the blood flow image generation unit 85b. Moreover, the tumor discrimination | determination part 85c calculates | requires the area which the luminance value more than a predetermined threshold occupies about each specified blood-flow image. Thereafter, the tumor discrimination unit 85c calculates the standard deviation of the area between the blood flow images using the area obtained for each blood flow image. And the tumor discrimination | determination part 85c discriminate | determines that the malignancy of a tumor is so high that the calculated standard deviation is large. For example, the tumor discrimination unit 85c sets a plurality of threshold values for determining the malignancy in stages, and compares the calculated standard deviation with each threshold to differentiate the malignancy in stages.

(Second modification according to the first embodiment)
Further, in the first embodiment described above, the example in which the blood flow image is generated by the flow-in method for rendering the unlabeled blood flowing into the labeled region labeled by the Time-SLIP pulse has been described. However, the method for generating a blood flow image by the Time-SLIP method is not limited to this. For example, a blood flow image may be generated by a flow-out method in which a labeled region including a main blood vessel is set outside a region of interest including a tumor to label the blood itself to be drawn. In the case of the flow-out method, labeled blood flowing into the region of interest is drawn on a blood flow image.

  Note that the definitions of the flow-in method and the flow-out method are not limited to those described above, and depending on the definition, they may be referred to by their reverse names or other names. The setting of the imaging area and the labeling area can be arbitrarily changed according to the imaging purpose. Moreover, the position of the labeling region to which the Time-SLIP pulse is applied and the number of labeling regions can be arbitrarily changed.

  In addition to the IR pulse, a SAT (SATuration) pulse, a SPAMM (Spatial Modulation of Magnetization) pulse, a DANTE (Delays Alternating with Nutations for Tailored Excitation) pulse, or the like may be used as a pulse for labeling. . The SAT pulse is a pulse that saturates the longitudinal magnetization component by tilting the magnetization vector of the labeled region by 90 °. The SPAMM pulse and the DANTE pulse are pulses that form a region saturated with a desired pattern such as a stripe pattern, a grid pattern, or a radial pattern by adjusting the gradient magnetic field.

(Second Embodiment)
Next, a second embodiment will be described. FIG. 10 is a diagram illustrating a configuration of an image processing apparatus 200 according to the second embodiment. As shown in FIG. 10, the image processing apparatus 200 is connected to the MRI apparatus 100 via a network 300. For example, the image processing apparatus 200 is placed in a place different from the radiographing room in which the MRI apparatus 100 is installed, and is used by an interpretation doctor or a diagnostician. The image processing apparatus 200 may be an image storage server that stores various medical images, a workstation that displays various medical images, or the like.

  The MRI apparatus 100 is an apparatus that images a subject using a magnetic resonance phenomenon. Specifically, the MRI apparatus 100 receives input of various imaging parameters from the operator, and sets imaging conditions based on the input imaging parameters. Then, the MRI apparatus 100 causes sequences based on various imaging methods to be executed based on the set imaging conditions. For example, the MRI apparatus 100 executes a sequence for rendering the blood flow in the breast of the subject without contrast. As a specific example, for example, the MRI apparatus 100 executes an imaging sequence by the Time-SLIP method, as in the first embodiment.

  Further, the MRI apparatus 100 generates various MR images based on magnetic resonance data collected by executing various sequences. For example, the MRI apparatus 100 generates a plurality of blood flow images in time series based on magnetic resonance data collected by a sequence for rendering blood flow in the breast of a subject without contrast. As a specific example, for example, the MRI apparatus 100 performs the Time-SLIP method sequence a plurality of times while changing the BBTI, as in the first embodiment, and then based on the collected magnetic resonance data. A blood flow image is generated every time.

  Then, when the MRI apparatus 100 generates various MR images, the MRI apparatus 100 transmits the generated MR images to the image processing apparatus 200 via the network 300. For example, in the MRI apparatus 100, the image acquisition unit 210 performs a plurality of time series obtained by executing a sequence for rendering the blood flow in the breast of the subject non-contrast multiple times with respect to the image processing apparatus 200. Send blood flow image. As a specific example, for example, the MRI apparatus 100 transmits, to the image processing apparatus 200, a plurality of blood flow images having different BBTIs obtained by the Time-SLIP method sequence.

  The image processing apparatus 200 is an apparatus that processes various medical images. For example, the image processing apparatus 200 processes the MR image generated by the MRI apparatus 100. Specifically, the image processing apparatus 200 includes an image acquisition unit 210, an input unit 220, a display unit 230, a storage unit 240, and a control unit 250.

  The image acquisition unit 210 acquires various medical images. For example, the image acquisition unit 210 acquires, from the MRI apparatus, a plurality of time-series blood flow images obtained by executing a sequence for rendering the blood flow in the breast of the subject non-contrast a plurality of times. As a specific example, for example, the image acquisition unit 210 acquires, from the MRI apparatus 100, a plurality of blood flow images having different BBTIs obtained by the Time-SLIP method sequence. When the image acquisition unit 210 acquires various medical images, the image acquisition unit 210 stores the acquired medical images in an image data storage unit 241 described later.

  The input unit 220 receives various instructions and information input from the operator. As the input unit 82, for example, a pointing device such as a mouse or a trackball, or an input device such as a keyboard is used. For example, the input unit 220 receives an operation requesting display of a medical image from the operator. In addition, the input unit 220 receives an operation requesting to discriminate between benign and malignant tumors based on a blood flow image related to a diagnosis target breast from an operator.

  The display unit 230 displays various images referred to by the operator and a GUI (Graphical User Interface) for receiving various operations from the operator. As the display unit 83, for example, a display device such as a liquid crystal monitor or a CRT monitor is used.

  The storage unit 240 stores various data processed by the image processing apparatus 200. Specifically, the storage unit 240 includes an image data storage unit 241. The image data storage unit 241 stores data of various medical images acquired by the image acquisition unit 210. For example, the image data storage unit 241 stores the MR image acquired from the MRI apparatus 100 by the image acquisition unit 210. As a specific example, the image data storage unit 241 stores a plurality of blood flow images having different BBTIs acquired from the MRI apparatus 100.

  The control unit 250 includes a CPU (Central Processing Unit) and a memory, and controls the operation of the image processing apparatus 200 by executing various programs using these. Specifically, the control unit 250 includes a tumor discrimination unit 251.

  The tumor discrimination unit 251 evaluates a blood flow image including a luminance value equal to or higher than a predetermined threshold among the plurality of blood flow images acquired by the image acquisition unit 210, and the tumor generated in the breast is benign or malignant. Differentiate if there is. For example, as in the first embodiment, the tumor discrimination unit 251 evaluates the number of blood flow images including a luminance value equal to or higher than a predetermined threshold, and the greater the number of corresponding blood flow images, the more malignant the tumor is. Differentiated as high. In addition, for example, the tumor discrimination unit 251 evaluates the variation between the blood flow images of the area occupied by the pixel having the luminance value equal to or higher than the predetermined threshold, similarly to the first modification example according to the first embodiment. Alternatively, the greater the variation in the area, the higher the malignancy of the tumor.

  Then, the tumor discrimination unit 251 displays the discrimination result on the display unit 83. For example, as in the first embodiment, the tumor discrimination unit 251 arranges and outputs blood flow images of a plurality of breasts with different BBTI acquired by the image acquisition unit 210 on the display unit 230, and determines whether the tumor is benign or malignant. The discrimination result is output to the display unit 230.

  As described above, according to the image processing apparatus 200 according to the second embodiment, a plurality of time-series blood flow images in which the blood flow in the breast of the subject is depicted in a non-contrast manner are acquired. A blood flow image including a luminance value equal to or higher than a predetermined threshold is evaluated from the blood flow images, and benign or malignant tumors in the breast are discriminated. Therefore, as in the first embodiment, it becomes possible to differentiate between benign and malignant tumors in consideration of angiogenesis associated with tumor malignancy, and the subject can be identified without invasion such as contrast, exposure, or biopsy. It becomes possible to distinguish benign and malignant tumors of the tumor with high accuracy.

  According to at least one embodiment described above, it is possible to differentiate between benign and malignant tumors with high accuracy without using a contrast agent.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 100 MRI apparatus 50 Sequence control part 80 Computer system 85 Data processing part 85b Blood flow image generation part 85c Tumor discrimination part

Claims (6)

Sequence control unit that executes a sequence of starting collection of magnetic resonance data after an inversion time has elapsed after applying an inversion recovery pulse that makes it possible to identify a blood flow in the breast of a subject multiple times with different inversion times When,
Based on the magnetic resonance data collected by the sequence, a generating unit that generates a plurality of blood flow images having different inversion times;
For each of the plurality of blood flow images having different inversion times, the number of blood flow images in which the representative value of the luminance value in the region of interest is equal to or greater than a predetermined threshold is evaluated. A magnetic resonance imaging apparatus comprising: a discrimination unit that discriminates that malignancy is high . For each of the plurality of blood flow images related to the breast to be diagnosed, the discrimination unit sets the threshold based on the luminance value of the corresponding blood flow image among the plurality of blood flow images related to the opposite breast, The magnetic resonance imaging apparatus according to claim 1 , wherein the tumor is identified as benign or malignant. The discrimination unit calculates an average value of luminance values from a plurality of blood flow images related to a breast on the opposite side of the breast to be diagnosed, sets the threshold based on the calculated average value, and the tumor is benign 2. The magnetic resonance imaging apparatus according to claim 1 , wherein the magnetic resonance imaging apparatus discriminates whether the patient is malignant or malignant. An anatomical image obtained by imaging the breast of the subject as a reference image, further comprising a region setting unit for setting a labeling region to which the inversion recovery pulse is applied,
Said sequence control unit, the reversal by applying a recovery pulse to labeled area set by the area setting unit, to any one of claims 1-3, characterized in that to perform a plurality of times said sequence The magnetic resonance imaging apparatus described. A sequence in which a sequence for starting collection of magnetic resonance data after a reversal time has elapsed after applying a reversal recovery pulse that makes it possible to identify a blood flow in a predetermined part of a subject is executed a plurality of times with different reversal times. A control unit;
Based on the magnetic resonance data collected by the sequence, a generating unit that generates a plurality of blood flow images having different inversion times;
For each of the plurality of blood flow images having different inversion times, the number of blood flow images in which the representative value of the luminance value in the region of interest is equal to or greater than a predetermined threshold is evaluated. A magnetic resonance imaging apparatus comprising: a discrimination unit that discriminates that malignancy is high . Obtained by executing a sequence of starting the collection of magnetic resonance data after the inversion time has elapsed after applying the inversion recovery pulse that makes it possible to identify the blood flow in the breast of the subject multiple times with different inversion times. An acquisition unit for acquiring a plurality of blood flow images having different inversion times;
For each of the plurality of blood flow images having different inversion times, the number of blood flow images in which the representative value of the luminance value in the region of interest is equal to or greater than a predetermined threshold is evaluated. An image processing apparatus comprising: a discrimination unit that discriminates that the degree of malignancy is high .

Images