METHOD AND SYSTEM USING MAGNETIC RESONANCE IMAGING FOR TISSUE CLASSIFICATION AND BULK-DENSITY ASSIGNMENT

Abstract

An apparatus includes a magnetic resonance imaging system, a processor for controlling the apparatus, and a memory containing machine executable instructions and a pulse sequence. The machine executable instructions and pulse sequence cause the processor to control the apparatus to: acquire magnetic resonance data from an imaging volume, wherein the magnetic resonance data includes gradient echo data; segment the magnetic resonance data into a plurality of segments, the segments including a fat segment, a water segment, a cortical bone segment, and an air segment; and create a bulk density map of the imaging volume from the segments.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS

This is a continuation-in-part patent application under 35 U.S.C. §120 of U.S. patent application Ser. No. 14/126,979, filed on 17 Dec. 2013, which is a U.S. national stage application under 35 U.S.C. §371 of International Application PCT/IB2012/053,050, filed on 18 Jun. 2012, which claims priority from European patent application 11171444.0, filed on 27 Jun. 2011, and U.S. Provisional Patent Application Ser. No. 61/636,102, filed on 20 Apr. 2012. Priority to all of these patent applications is claimed, and all of these patent applications are all hereby incorporated by reference in their entirety as if fully set forth herein.

TECHNICAL FIELD

The invention relates to magnetic resonance imaging, in particular to the use of magnetic resonance imaging for radiation therapy planning

BACKGROUND AND SUMMARY

Magnetic Resonance (MR) images that can separate tissue, bone, and air are beneficial for all applications where MR is used in combination with irradiating imaging techniques, such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), and with planning for irradiating therapy techniques, such as Magnetic Resonance—Radio Therapy simulation. Unlike Hounsfield units used in CT, there is no simple relation between the MR image intensity and tissue density. For instance, using conventional MR sequences, cortical bone and air filled cavities both show no signal intensity whereas their densities are substantially different. Ultimately the ability to reliably identify additional tissue types in an MR image while the MR-acquisition time should be kept at a minimum would be beneficial. Additionally, the ability to reliably assign accurate electron densities to different voxels of an MR image would be beneficial for allowing creation of a treatment dose plan based only on MR imaging, without the need for registering MR images with separately generated CT images of an imaging volume.

Embodiments of the invention may provide apparatus, systems, methods, and computer-readable storage medium for identifying different tissue types within a subject using magnetic resonance imaging. Embodiments may achieve this by using a pulse sequence which can include commands to acquire free induction decay data and one or more gradient echoes. The free induction decay data is acquired at an echo time on a timescale of microseconds. This enables the acquisition of free induction decay data from bone tissue. Data from one or more gradient echoes is also acquired. The commendation of acquiring the free induction decay data and gradient echo data allows a variety of images to be constructed: an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image. Using a pulse sequence which may be used to reconstruct such different images may be beneficial because all of the image data necessary for radiation therapy dose planning and/or reconstructing images from radio-isotope imaging systems is provided. Using such a pulse sequence may also be beneficial because it may reduce the time necessary to acquire the images.

An embodiment of the invention may provide for a pulse sequence for magnetic resonance imaging which combines the features of an ultra-short echo time (UTE) pulse sequence with one or more gradient echoes and DIXON reconstruction. For example the pulse sequence may be a UTE triple-echo (UTILE) MR-sequence combining the UTE and DIXON acquisition in a single acquisition. This example may be implemented using a pulse sequence that samples fast induced decay (FID) at short echo times, at time TE1, followed by two gradient echoes, at times TE2 and TE3. The echo times TE2 and TE3 may be optionally adjusted to where water and fat are almost opposed-phase and in-phase, respectively.

Cortical bone may be segmented from the calculated relative difference between the magnitude information of echo one (MD and the reconstructed in-phase image by an empirically determined global threshold after masking out air areas, potentially by thresholding. Soft tissue and adipose tissue decomposition may be achieved by applying a three point Dixon signal modeling technique using the magnitude and the unwrapped phase information of all three echoes. This single acquisition may provide 5 or more sets of images:

1. images of bone

2. water-only images (i.e., fat-saturated images)

3. fat-only images (i.e., water-saturated images)

4. in-phase images

5. opposed-phase images

Embodiments of the invention may also generate a tissue mask of an MR imaging volume which represents relevant anatomical structures in different colors or grayscale values.

Embodiments of the invention may create a bulk density map of an MR imaging volume which can be used to create a does plan for treatment.

A ‘computer-readable storage medium’ as used herein encompasses any tangible storage medium which may store instructions which are executable by a processor of a computing device. The computer-readable storage medium may be referred to as a computer-readable non-transitory storage medium. The computer-readable storage medium may also be referred to as a tangible computer-readable medium. In some embodiments, a computer-readable storage medium may also be able to store data which is able to be accessed by the processor of the computing device. Examples of computer-readable storage media include, but are not limited to: a floppy disk, a magnetic hard disk drive, a solid state hard disk, flash memory, a USB thumb drive, Random Access Memory (RAM), Read Only Memory (ROM), an optical disk, a magneto-optical disk, and the register file of the processor. Examples of optical disks include Compact Disks (CD) and Digital Versatile Disks (DVD), for example CD-ROM, CD-RW, CD-R, DVD-ROM, DVD-RW, or DVD-R disks. The term computer readable-storage medium also refers to various types of recording media capable of being accessed by the computer device via a network or communication link. For example a data may be retrieved over a modem, over the internet, or over a local area network. References to a computer-readable storage medium should be interpreted as possibly being multiple computer-readable storage mediums. Various executable components of a program or programs may be stored in different locations. The computer-readable storage medium may for instance be multiple computer-readable storage medium within the same computer system. The computer-readable storage medium may also be computer-readable storage medium distributed amongst multiple computer systems or computing devices.

‘Computer memory’ or ‘memory’ is an example of a computer-readable storage medium. Computer memory is any memory which is directly accessible to a processor. Examples of computer memory include, but are not limited to: RAM memory, registers, and register files. References to ‘computer memory’ or ‘memory’ should be interpreted as possibly being multiple memories. The memory may for instance be multiple memories within the same computer system. The memory may also be multiple memories distributed amongst multiple computer systems or computing devices.

‘Computer storage’ or ‘storage’ is an example of a computer-readable storage medium. Computer storage is any non-volatile computer-readable storage medium. Examples of computer storage include, but are not limited to: a hard disk drive, a USB thumb drive, a floppy drive, a smart card, a DVD, a CD-ROM, and a solid state hard drive. In some embodiments computer storage may also be computer memory or vice versa. References to ‘computer storage’ or ‘storage’ should be interpreted as possibly including multiple storage devices or components. For instance, the storage may include multiple storage devices within the same computer system or computing device. The storage may also include multiple storages distributed amongst multiple computer systems or computing devices.

A ‘processor’ as used herein encompasses an electronic component which is able to execute a program or machine executable instruction. References to the computing device comprising “a processor” should be interpreted as possibly containing more than one processor or processing core. The processor may for instance be a multi-core processor. A processor may also refer to a collection of processors within a single computer system or distributed amongst multiple computer systems. The term computing device should also be interpreted to possibly refer to a collection or network of computing devices each comprising a processor or processors. Many programs have their instructions performed by multiple processors that may be within the same computing device or which may even be distributed across multiple computing devices.

A ‘user interface’ as used herein is an interface which allows a user or operator to interact with a computer or computer system. A ‘user interface’ may also be referred to as a ‘human interface device.’ A user interface may provide information or data to the operator and/or receive information or data from the operator. A user interface may enable input from an operator to be received by the computer and may provide output to the user from the computer. In other words, the user interface may allow an operator to control or manipulate a computer and the interface may allow the computer indicate the effects of the operator's control or manipulation. The display of data or information on a display or a graphical user interface is an example of providing information to an operator. The receiving of data through a keyboard, mouse, trackball, touchpad, pointing stick, graphics tablet, joystick, gamepad, webcam, headset, gear sticks, steering wheel, pedals, wired glove, dance pad, remote control, and accelerometer are all examples of user interface components which enable the receiving of information or data from an operator.

A ‘hardware interface’ as used herein encompasses an interface which enables the processor of a computer system to interact with and/or control an external computing device and/or apparatus. A hardware interface may allow a processor to send control signals or instructions to an external computing device and/or apparatus. A hardware interface may also enable a processor to exchange data with an external computing device and/or apparatus. Examples of a hardware interface include, but are not limited to: a universal serial bus, IEEE 1394 port, parallel port, IEEE 1284 port, serial port, RS-232 port, IEEE-488 port, Bluetooth connection, Wireless local area network connection, TCP/IP connection, Ethernet connection, control voltage interface, MIDI interface, analog input interface, and digital input interface.

A ‘display’ or ‘display device’ as used herein encompasses an output device or a user interface adapted for displaying images or data. A display may output visual, audio, and or tactile data. Examples of a display include, but are not limited to: a computer monitor, a television screen, a touch screen, tactile electronic display, Braille screen, Cathode ray tube (CRT), Storage tube, Bistable display, Electronic paper, Vector display, Flat panel display, Vacuum fluorescent display (VF), Light-emitting diode (LED) displays, Electroluminescent display (ELD), Plasma display panels (PDP), Liquid crystal display (LCD), Organic light-emitting diode displays (OLED), a projector, and Head-mounted display.

Radio-isotope imaging data is defined herein as two or three dimensional data that has been acquired using a medical imaging scanner that is configured to detect the radioactive decay of radioisotopes. A radio-isotope imaging system is defined herein as an apparatus adapted for acquiring information about the physical structure of a patient and construct sets of two dimensional or three dimensional medical image data by detecting radiation emitted by radioactive markers or traces within the patient. Radio-isotope imaging data can be used to construct visualizations which are useful for diagnosis by a physician. This visualization can be performed using a computer.

Magnetic Resonance (MR) data is defined herein as being the recorded measurements of radio frequency signals emitted by atomic spins by the antenna of a Magnetic resonance apparatus during a magnetic resonance imaging scan. A Magnetic Resonance Imaging (MRI) image is defined herein as being the reconstructed two or three dimensional visualization of anatomic data contained within the magnetic resonance imaging data. This visualization can be performed using a computer.

In one aspect the invention provides an apparatus comprising: a magnetic resonance imaging system which acquires magnetic resonance data from an imaging volume; a processor for controlling the apparatus; and a memory containing machine executable instructions and a pulse sequence. The magnetic resonance data is acquired using the pulse sequence includes gradient echo data. Execution of the machine executable instructions causes the processor to: acquire the magnetic resonance data using the magnetic resonance imaging system and the pulse sequence; and segment the magnetic resonance data into a plurality of segments, including a fat segment, a water segment, a cortical bone segment, and an air segment; and create a bulk density map of the imaging volume from the segments.

The processor may be replaced by a controller or a control system.

A pulse sequence as used herein can encompass a set of instructions or operations performed as a function of time which together may be used to control or to generate commands for controlling the magnetic resonance imaging system to acquire the magnetic resonance data. The pulse sequence can be in a machine executable form or it can be in a graphical form which is adapted for manipulation or change by a human operator on a graphical user interface. If in graphical form the pulse sequence may be converted into a machine executable form by a suitable program or program module.

In some embodiments, the magnetic resonance data acquired using the pulse sequence may include free induction decay data and gradient echo data. Free induction decay data as used herein encompasses a measurement of the free induction decay curve measured during the acquisition of the magnetic resonance data. The free induction decay data may for instance be free induction decay which decays in a characteristic time constant T2 or T2*. An echo signal is a signal which is generated from a free induction decay using a bipolar switched magnetic gradient. There is an echo which is produced when the magnetic field gradient is reversed. Gradient echo data as used herein encompasses the measurement recording of such an echo signal. Gradient echo data as used herein encompasses the recording of one or more echo signals.

Execution of the machine executable instructions can cause the processor to acquire the magnetic resonance data using the magnetic resonance imaging system in accordance with the pulse sequence. This is to say that the pulse sequence commands or control sequences can be used to control the magnetic resonance imaging system to acquire the magnetic resonance data.

A fat segment, which also may be referred to as a water-saturated segment, can indicate the concentration or location of fat or adipose tissue within the imaging volume.

Likewise, a water segment, which also may be referred to as a fat-saturated segment, can show the concentration or location of water protons, with the fat protons removed, within the imaging volume.

A cortical bone segment can encompass magnetic resonance data which contains free induction decay data which is descriptive of the location(s) of cortical bone within the imaging volume.

Similarly, an air segment can encompass magnetic resonance data which is descriptive of the location(s) of air within the imaging volume.

In some embodiments, an ultra-short echo time image can be used for differentiating between bone and air.

In some embodiments, execution of the instructions can further cause the processor to create the bulk density map from the segments by: determining for each of a plurality of voxels of the imaging volume, which element among fat, water, cortical bone and air segment is primarily represented in the voxel; and assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone and air is primarily represented in the voxel.

In some embodiments, execution of the instructions can further cause the processor to create the bulk density map from the segments by: assigning corresponding bulk density values to fat, water, cortical bone and air; determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to the voxel, including a fat fraction, a water fraction, a cortical bone fraction, and an air fraction; and for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

In some embodiments, execution of the instructions can further cause the processor to generate one or more digitally reconstructed radiographs (DRRs) from the magnetic resonance data.

In some versions of these embodiments, execution of the instructions can further cause the processor to transfer the one or more DRRs to a radiation treatment planning system.

In some embodiments, execution of the instructions can further cause the processor to generate an artificial computed tomography image based on fractions of fat, water, air, and cortical bone in each voxel of the imaging volume.

In some embodiments, execution of the instructions can further cause the processor to reconstruct an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image, and to produce the cortical bone segment by subtracting the in-phase image from the ultra-short echo time image.

In some embodiments, execution of the instructions can further cause the processor to reconstruct an opposed phase image from the magnetic resonance data. An opposed phase image as used herein encompasses an image with a signal from two distinct components such as fat and water signals are 180 degrees out of phase which causes the destructive interference of the nuclear magnetic resonance signal within a particular voxel. This embodiment may be beneficial when performing radiation therapy planning on particular types of tissue. For instance it may be beneficial in identifying lesions in the liver or the adrenal glands. It may also be beneficial for identifying the various pathological regions in the brain. The opposed phase image may for instance be displayed on the graphical user interface during the radiation therapy planning or it may for instance be used as an input for the radiation therapy planning program module.

In some embodiments, execution of the instructions can further cause the processor to reconstruct one or more echo images. An echo image is an image reconstructed from the recorded magnetic resonance data of a gradient echo. Echo images are images each reconstructed from the magnetic resonance data of multiple gradient echoes. The in-phase image, the fat-saturated image, the water-saturated image, and the ultra-short echo time image are constructed from the magnetic resonance data using a Dixon signal model. For instance the Dixon signal model may be a two-point Dixon signal model, a three-point Dixon signal model, or a four-point Dixon signal model. This embodiment may be advantageous because this provides for an effective and accurate means of constructing these images. The three-point Dixon signal model may be used in some embodiments to reconstruct the opposed phase image from the magnetic resonance data at the same time that the other images are also reconstructed

An in-phase image as used herein can encompass an image reconstructed from magnetic resonance data that comprises the T1 and regular proton weighted image.

An ultra-short echo time image as used herein can encompass an image reconstructed from a free induction decay data where the free induction decay occurred on an extremely short timescale. The free induction decay may have a time constant on the order of several hundreds of microseconds. The ultra-short echo time enables the imaging of tissue with extremely small free induction decay values such as tendons or bone.

In some embodiments, execution of the instructions can further cause the processor to reconstruct an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image from the magnetic resonance data, and to produce the cortical bone segment by automatically thresholding a noise level in the in-phase image and subsequently removing background noise.

In some versions of these embodiments, execution of the instructions can further cause the processor to produce the cortical bone segment by registering the in-phase image with a bone probability atlas.

In some embodiments, execution of the instructions can further cause the processor to transfer the bulk density map to a radiation treatment planning system.

In some embodiments, execution of the instructions can further cause the processor to display a fat segment, a water segment, a cortical bone segment and an air segment of magnetic imaging data from an imaging volume on a graphical user interface.

In some embodiments, execution of the instructions can further cause the processor to receive radiation therapy planning data from a graphical user interface. In some embodiments the electron bulk density map and/or one or more DRRs can be used along with input from the graphical user interface to calculate the radiation therapy planning data. This embodiment may be particularly beneficial because the data necessary for an operator or a physician to plan a radiation session or therapy is displayed on the graphical user interface. The user or operator may study the images and then use a mouse or other human input device to manipulate shapes and controls on the graphical user interface. The user's entry may then be translated into the radiation therapy planning data. This embodiment may be particularly beneficial because the data necessary for performing the radiation therapy may have been presented and acquired in a single magnetic resonance acquisition. This may result in an increase in the speed in which radiation therapy planning can be performed.

In another embodiment execution of the instructions can further cause the processor to generate radiation therapy planning data using the electron bulk density mask and/or one or more DRRs, and a treatment plan using a radiation therapy planning program module. A treatment plan as used herein encompasses a data file descriptive of a plan for performing a radiation therapy. For instance the treatment plan may contain anatomical data descriptive of the patient or subject in conjunction with regions of the subject to be treated. The radiation therapy planning program module may contain executable code which is able to interpret the treatment plan and register it to at least one of the electron bulk density mask and/or one or more DRRs. This embodiment may have the advantage that the medical apparatus is able to acquire the magnetic resonance data and then proceed with planning and executing a radiation therapy on the patient or subject

In some embodiments the apparatus can further include a radiation therapy system. Execution of the instructions can further cause the processor to generate radiation therapy control commands using the radiation therapy planning data. Execution of the instructions can further cause the processor to treat the subject with the radiation therapy system by executing the radiation therapy control commands. The radiation therapy control commands as used herein encompass machine executable commands which control a radiation therapy system.

In some embodiments the radiation therapy system can be a linear accelerator.

In some embodiments the radiation therapy system can be a gamma knife.

In some embodiments the radiation therapy system can be a charged particle therapy system. A charged particle therapy system as used herein is a system which is adapted for shooting charged particles such as charged nuclei or molecules at a target region of the subject. For example carbon nuclei or protons may be directed at a target zone of the subject.

In some embodiments the radiation therapy system can be a proton therapy system. A proton therapy system as used herein is a therapy system which is adapted for shooting proton such as hydrogen nuclei at a target zone of the subject.

In some embodiments the radiation therapy system can be an x-ray therapy system. An x-ray therapy system as used herein encompasses a system for directing x-rays in a target zone of a subject for performing radiation therapy.

In some embodiments the radiation therapy system can be an external beam radiation system. An external beam radiation system as used herein encompasses a radiation therapy system for directing an external radiation beam at a target zone of a subject.

In some embodiments the radiation therapy system can be a brachytherapy system.

Another aspect the invention provides a method of operating an apparatus, such as a medical apparatus. The method includes: acquiring magnetic resonance data from an imaging volume via a magnetic resonance imaging system and a pulse sequence, wherein the magnetic resonance data includes gradient echo data; segmenting the magnetic resonance data into a plurality of segments, the segments including a fat segment, a water segment, a cortical bone segment, and an air segment; and creating a bulk density map of the imaging volume from the segments.

In some embodiments, creating the bulk density map from the segments can comprise: determining, for each of a plurality of voxels of the imaging volume, which element among fat, water, air and cortical bone is primarily represented in the voxel; and assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone, and air is primarily represented in the voxel.

In some embodiments, creating the bulk density map from the segments can comprise: assigning corresponding bulk density values to fat, water, cortical bone and air; determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to the voxel, including an a fat fraction, a water fraction, a cortical bone fraction and an air fraction; and for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

In some embodiments, the method can further comprise generating one or more digitally reconstructed radiographs (DRRs) from the magnetic resonance data.

In some versions of these embodiments, the method can further comprise transferring the one or more DRRs to a radiation treatment planning system.

In some embodiments, the method can further comprise generating an artificial computed tomography image based on fractions of fat, water, cortical bone, and air in each voxel of the imaging volume.

In some embodiments, the method can further comprise: reconstructing an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image from the magnetic resonance data; and producing the cortical bone segment by subtracting the in-phase image from the ultra-short echo time image.

In some embodiments, the method can further comprise: reconstructing an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image from the magnetic resonance data; and producing the cortical bone segment by automatically thresholding a noise level in the in-phase image and subsequently removing background noise.

In some embodiments, producing the cortical bone segment can further comprise registering the in-phase image with a bone probability atlas.

Yet another aspect of the invention provides a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium has stored therein a pulse sequence and machine readable instructions configured to be executed by a processor to control an apparatus including a magnetic resonance imaging system. The machine readable instructions are configured in conjunction with the pulse sequence to cause the apparatus to execute a process. The process comprises: acquiring magnetic resonance data from an imaging volume using the magnetic resonance imaging system and the pulse sequence, wherein the magnetic resonance data includes gradient echo data; segmenting the magnetic resonance data into a plurality of segments by executing a set of instructions, the segments including a fat segment, a water segment, a cortical bone segment, and an air segment; and creating a bulk density map of the imaging volume from the segments.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be more readily understood from the detailed description of exemplary embodiments presented below considered in conjunction with the accompanying drawings, as follows.

FIG. 1 shows a flow chart which illustrates an embodiment of a method of acquiring and processing magnetic resonance data.

FIG. 2 shows a flow chart which illustrates a further embodiment of a method of acquiring and processing magnetic resonance data.

FIG. 3 illustrates a pulse sequence in the form of a timing diagram.

FIG. 4 shows a cortical bone image.

FIG. 5 shows a medullary bone image.

FIG. 6 shows a complete bone image.

FIG. 7 shows a fat-saturated image.

FIG. 8 shows an in-phase image.

FIG. 9 shows the ultra-short echo time phase image.

FIG. 10 shows a block diagram which illustrates one embodiment of a medical apparatus.

FIG. 11 shows a block diagram which illustrates another embodiment of a medical apparatus.

FIG. 12 shows a block diagram which illustrates a further embodiment of a medical apparatus.

FIG. 13 shows images for four subjects which include Digital Reconstructed Radiographs (DRRs).

FIG. 14 shows a flow chart which illustrates an embodiment of a method of acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

FIG. 15 shows a flow chart which illustrates another embodiment of a method of acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

FIG. 16 shows a flow chart which illustrates yet another embodiment of a method of acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

FIG. 17 shows some example images which may be generated from magnetic image data for treatment planning.

FIG. 18 shows yet another embodiment of a medical apparatus.

FIG. 19 illustrates an example embodiment of operations which may be performed by a system and method which acquire magnetic resonance data and process the magnetic resonance data for treatment planning.

FIG. 20 shows an example embodiment of modules and a corresponding work flow for a system and method which acquire magnetic resonance data and process the magnetic resonance data for treatment planning.

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which embodiments of the present invention are shown. The present invention may, however, be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided as teaching examples of the invention. Within the present disclosure and claims, when something is said to have approximately a certain value, then it means that it is within 10% of that value, and when something is said to have about a certain value, then it means that it is within 25% of that value.

Like numbered elements in these figures are either equivalent elements or perform the same function. Elements which have been discussed previously will not necessarily be discussed in later figures if the function is equivalent.

FIG. 1 shows a flow diagram which illustrates a method of acquiring and processing magnetic resonance data. In step 100 magnetic resonance data is acquired using an MRI system and a pulse sequence. The pulse sequence may for instance be a pulse sequence as is demonstrated in FIG. 3. Next in step 102 an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image may be reconstructed from the magnetic resonance data. The ultra-short echo time image comprises bone image data.

FIG. 2 shows a block diagram which illustrates a further embodiment of a method of acquiring and processing magnetic resonance data. In step 200 magnetic resonance data is acquired using the MRI system and a pulse sequence. In step 202 an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image are reconstructed from the magnetic resonance imaging data. The ultra-short echo time image comprises bone image data. A bone image data is image data which is descriptive of the anatomy of bone tissue within a patient or a subject. In step 204 a medullary bone image is constructed from the water-saturated image. In some embodiments this step may include removing information from the image using a model, for instance removing adipose tissue from the image. Next in step 206 a cortical bone image is constructed by subtracting the in-phase image from the ultra-short echo time image. Next in step 208 a complete bone image is constructed by adding the medullary bone image to the cortical bone image. Finally in step 210 a spatially dependent radiation attenuation coefficient is calculated. In step 210 this may include using the complete bone image, the fat-saturated image, the in-phase image, and/or the ultra-short echo time image.

FIG. 3 illustrates a pulse sequence 300 in the form of a timing diagram. In this pulse sequence 300 there are four timelines, there is timeline 302 which illustrates when radio frequency energy is applied. Timeline 304 illustrates the readout gradient. Timeline 306 illustrates a gate for data acquisition. Timeline 308 illustrates the nuclear magnetic resonance signal. On timeline 302 a radio frequency pulse 310 is applied during time Trf. On timeline 308 a free induction decay 314, a first gradient echo 316 and a second gradient echo 318 are shown. On timeline 308 there are three gradient pulses. Timeline 304 shows when a first gradient pulse 320, a second gradient pulse 322, and a third gradient pulse 324 are applied. The first gradient pulse 320 is applied during the free induction decay 314. The second gradient pulse 322 causes the first gradient echo 316. The third gradient pulse 324 causes the second gradient echo 318. The characteristic time rate at which the free induction decay 314 decays such as the T1, the T2, or T2* time constant is indicated as TE1 326. The first gradient echo 316 has a maximum at TE2 328. The second gradient echo 318 has a maximum at TE3 330.

Timeline 306 shows when magnetic resonance data is acquired. The free induction decay data is acquired during time interval Taq1 332. The first gradient echo data is acquired during time interval 334. The second gradient echo data is acquired during time interval 336. The pulse sequence illustrated in FIG. 3 is representative. Changes in the pulse sequence may be made. For instance the time when the free induction decay data is acquired may be delayed until the time marked 338.

In the example shown in FIG. 3, the echo times are chosen such that the echo times are acquired at in-phase and opposed-phase times. However, they do not need to be in-phase of opposed-phase echo times. An appropriate Dixon model may be used such that the gradient echoes may be acquired at non-specific echo time. For instance, various Dixon models will work for 2, 3, or 4 non-specific echo times.

FIG. 4 shows an example of a cortical bone image 400. In this image 400 cortical bone 402 is shown. The cortical bone image 400 was constructed by subtracting a scaled multiple (k) of the in-phase image (IP) from the ultra-short echo time image (UTE) (i.e., UTE−k*IP, where k could be 1 or another appropriate scale factor).

FIG. 5 shows a fat-only (water-saturated) image 500. Medullary bone 502 is clearly shown in the fat-only image 500. Image 500 includes medullary bone and subcutaneous fat.

FIG. 6 shows a bone image 600 that was constructed by adding images 400 and 500. Image 600 includes cortical bone, medullary bone, and subcutaneous fat. In region 602 cortical plus medullary bone is shown.

FIG. 7 shows a fat-saturated image 700.

FIG. 8 shows an in-phase image 800.

FIG. 9 shows the ultra-short echo time image 900 for phase. An air cavity 902 is visible in this image.

FIG. 10 shows a block diagram which illustrates a medical apparatus 1000. The medical apparatus 1000 comprises a magnetic resonance imaging system 1002. The magnetic resonance imaging system 1002 is shown as comprising a magnet 1004. The magnet 1004 shown in FIG. 10 is a cylindrical type superconducting magnet. The magnet 1004 has a liquid helium cooled cryostat with superconducting coils. It is also possible to use permanent or resistive magnets. The use of different types of magnets is also possible for instance it is also possible to use both a split cylindrical magnet and a so called open magnet. A split cylindrical magnet is similar to a standard cylindrical magnet, except that the cryostat has been split into two sections to allow access to the iso-plane of the magnet, such magnets may for instance be used in conjunction with charged particle beam therapy. An open magnet has two magnet sections, one above the other with a space in-between that is large enough to receive a subject: the arrangement of the two sections area similar to that of a Helmholtz coil. Open magnets are popular, because the subject is less confined. Inside the cryostat of the cylindrical magnet there is a collection of superconducting coils. Within the bore 1006 of the cylindrical magnet 1004 there is an imaging zone 1008 where the magnetic field is strong and uniform enough to perform magnetic resonance imaging.

Within the bore 1006 of the magnet 1004 there is also a magnetic field gradient coil 1010 which is used for acquisition of magnetic resonance data to spatially encode magnetic spins within the imaging zone 1008 of the magnet 1004. The magnetic field gradient coil 1010 is connected to a magnetic field gradient coil power supply 1012. The magnetic field gradient coil 1010 is intended to be representative. Typically magnetic field gradient coils 1010 contain three separate sets of coils for spatially encoding in three orthogonal spatial directions. A magnetic field gradient power supply supplies current to the magnetic field gradient coils. The current supplied to the magnetic field coils is controlled as a function of time and may be ramped or pulsed.

Adjacent to the imaging zone 1008 is a radio frequency coil 1014 for manipulating the orientations of magnetic spins within the imaging zone 1008 and for receiving radio transmissions from spins also within the imaging zone 1008. The radio frequency coil may contain multiple coil elements. The radio frequency coil or each of any multiple coil elements may also be referred to as a channel. The radio frequency coil may also be referred to as an antenna. The radio frequency coil 1014 is connected to a radio frequency transceiver 1016. The radio frequency coil 1014 and radio frequency transceiver 1016 may be replaced by separate transmit and receive coils and a separate transmitter and receiver. It is understood that the radio frequency coil 1014 and the radio frequency transceiver 1016 are representative. The radio frequency coil 1014 is intended to also represent a dedicated transmit antenna and a dedicated receive antenna. Likewise the transceiver 1016 may also represent a separate transmitter and receivers.

The transceiver 1016 and the magnetic field gradient coil power supply 1012 are connected to a hardware interface 1024 of a computer system 1022. The computer system 1022 further comprises a processor 1026. The processor is connected to the hardware interface 1024 which enables the processor 1026 to control the operation and function of the medical apparatus 1000. The processor 1026 is further connected to user interface 1028. The processor 1026 is also connected to computer storage 1030 and computer memory 1032.

The computer storage 1030 is shown as containing a pulse sequence 1034. The pulse sequence 1034 may be used for controlling the magnetic resonance imaging system 1002. The computer storage 1030 is shown as further containing magnetic resonance data 1036 that was acquired from the magnetic resonance imaging system 1002 using the pulse sequence 1034. The computer storage 1030 is further shown as containing an in-phase image 1038, a fat-saturated image 1040, a water-saturated image 1042 and an ultra-short echo time image 1044 that was reconstructed from the magnetic resonance data 1036. The computer storage 1030 is also shown as containing an opposed phase image 1046 that was reconstructed from the magnetic resonance data 1036. The opposed phase image 1046 is not calculated or reconstructed in all embodiments.

The computer storage 1030 is further shown as containing a medullary bone image 1048 reconstructed from the water-saturated image 1042. The computer storage 1030 is further shown as containing a cortical bone image 1050 reconstructed by subtracting the in-phase image 1038 from the ultra-short echo time image 1044. The computer storage 1030 is shown as further containing a complete bone image 1052 which is constructed by adding the medullary bone image 1048 to the cortical bone image 1050. The computer storage 1030 is shown as containing a spatially dependent radiation attenuation coefficient 1054 which is not present in all embodiments. The computer storage 1030 is further shown as containing a radiation therapy planning data 1056. The radiation therapy planning data 1056 is optional and is not present in all embodiments. The computer storage 1030 is further shown as containing a treatment plan 1058 which is optional also.

The computer memory 1032 contains computer executable instructions for controlling the operation and functioning of the medical apparatus 1000. The computer memory 1032 is shown as containing a control module 1060. The control module 1060 contains computer executable code which allows the processor 1026 to control the operation and function of the medical apparatus 1000. The computer storage 1032 is further shown as containing an image reconstruction module 1062. The image reconstruction module 1062 contains computer executable code for reconstructing the images 1038, 1040, 1042, 1044, 1046 contained within the computer storage 1030. The computer memory 1032 further contains an image manipulation module 1064 which allows the processor 1026 to manipulate such as adding and subtracting images.

The computer memory 1032 is shown as optionally containing a three-point Dixon signal model 1066 which may be used by the image reconstruction module 1062. The computer memory 1032 is further shown as containing an image segmentation module 1068. In some embodiments the image segmentation module may be used to segment any of the images contained within the computer storage 1030. The computer memory 1032 is further shown as containing the radiation attenuation coefficient calculation module 1070. The radiation attenuation coefficient calculation module 1070 may in some embodiments be used to calculate the spatially dependent radiation attenuation coefficient 1054 from the complete bone image 1052, the fat-saturated image 1040, the in-phase image 1038, and the ultra-short echo time image 1044.

In some embodiments there may be a radiation therapy planning data generation module 1072 present in the computer memory 1032. The radiation therapy planning generation module 1072 is adapted for automatically generating the radiation therapy planning data 1056 using the treatment plan 1058 and the spatially dependent radiation attenuation coefficient 1054. Some embodiments may also have a graphical user interface control module 1074 present in the computer memory 1032 for controlling the operation and function of a graphical user interface 1076. The optional graphical user interface 1076 is shown as displaying a complete bone image 600, a fat-saturated image 700, an in-phase image 800, and an ultra-short echo time image 900. The graphical user interface 1076 further contains a radiation therapy planning interface 1078 where an operator or physician may enter radiation therapy planning data 1056.

FIG. 11 shows an embodiment of a medical apparatus 1100 similar to that shown in FIG. 10. The medical apparatus shown in FIG. 11 includes a radiation therapy system 1122. The magnet 1004 is a superconducting magnet and includes a cryostat 1124 with several superconducting coils 1126. There is also a compensation coil 1128 which creates an area of reduced magnetic field 1130 which surrounds the magnet 1004. The radiation therapy system 1122 in this embodiment is intended to be representative of radiation therapy systems in general. The components shown here are typical for LINAC and x-ray therapy systems. However with minor modifications such as using a split magnet charged particles or beta particle radiation therapy systems can also be illustrated using this diagram. There is a gantry 1132 which is used to rotate a radiotherapy source 1134 about the magnet 1004. The gantry 1132 is rotated about the axis of rotation 1133 by a rotation actuator 1135. There is a radiation therapy source 1134 which is rotated by the gantry 1132. The radiotherapy source 1134 generates a radiation beam 1138 which passes through collimator 1136. In FIG. 11, a target zone labeled 1142 which is irradiated by the radiation beam 1138 is shown. As the radiation source 1134 rotates about the axis of rotation 1133 the target zone 1142 is irradiated. There is also a support positioning system 1140 for positioning the support 1020 to optimize the location of the target zone 1142 relative to the radiation therapy system 1122.

The hardware interface 1024 is shown as being connected to the transceiver 1016, the power supply 1012, the rotation actuator 1135, and the support positioning system 1140. The hardware interface 1024 allows the processor 1026 to send and receive control signals to all of these components 1012, 1016, 1135, 1140.

The computer storage 1030 is shown as containing radiation therapy control commands 1150. The radiation therapy control commands 1150 comprise instructions that when executed by the radiation therapy system 1122 cause the radiation therapy system 1122 to treat the target zone 1142. The computer memory 1032 is shown as containing a radiation therapy control command generation module 1152. The radiation therapy control command generation module 1152 contains instructions which allow the processor 1026 to generate the radiation therapy control commands 1150 from the radiation therapy planning data 1056.

FIG. 12 illustrates a medical apparatus 1200 similar to that shown in FIG. 10. In this embodiment a radio isotope imaging system 1202 has been integrated into the medical apparatus 1200. The radio-isotope imaging system 1202 comprises a scintillator ring 1204 adapted for detecting ionizing radiation. The individual scintillators which make up the scintillator ring may be connected to a set of light pipes 1206 or fiber optics which are led out of the magnet 1004 to a series of light detectors 1208. Within the subject 1018 is shown a concentration of radio-isotope 1210. Ionizing radiation is emitted 1212 and is absorbed in the scintillator ring 1204. Within the computer storage 1030 is shown the radio-isotope imaging data 1220. The radio-isotope imaging data 1220 is the recorded data acquired by the light detectors 1208. The computer storage 1030 is further shown as containing a medical image 1222. The medical image is an image, reconstruction, or rendering of the radio-isotope imaging data which is descriptive of the location of radio-isotope 1210 within the subject.

The medical image 1222 was reconstructed from the radio-isotope imaging data 1220. The radio-isotope imaging system 1202 may for instance be a positron emission tomography system or a single photon emission computer tomography system. The computer memory 1032 is shown as containing a medical image reconstruction module 1230. The medical image reconstruction module 1230 contains computer executable code which the processor 1026 may use to reconstruct the medical image 1222 from the radio-isotope imaging data 1220. The computers 1022 shown in the embodiments of FIGS. 10, 11, and 12 are equivalent as is the software and data stored within the computer memory 1032 and computer storage 1030 respectively.

FIG. 13 shows images for four subjects. Each row includes images for one subject generated by the single imaging sequence. The columns of images from left to right include bone-enhanced images 400, water-only images 700, in-phase images 800, opposed-phase images 1046, fat-only images 500, and digital reconstructed radiographs (DRRs) 1240. The bone enhanced images 400 contrast cortical bone corresponding to FIG. 4 and are constructed by subtracting the in-phase image 800 from the ultra-short echo time image corresponding to FIG. 9. The difference between the images of FIG. 4 and the column of bone enhanced images includes a weighting of the in-phase image which reduces the presence of the brain. The water-only images 700 are T1w images with fat-saturation corresponding to FIG. 7. The in-phase images 800 correspond to FIG. 8. The fat-only images 500 correspond to FIG. 5 and include medullary bone. The last column includes the DRRs 1240. The DRR is constructed as a 2-dimensional projection of the 3-dimensional volume of the bone-enhance image 400. Alternatively, the DRR is constructed as a 2-dimensional projection of the weighted in-phase image subtracted from the ultra-short echo time image. The projections are shown as sagittal perspectives. The DRRs are of sufficient quality to be used in 2-dimensional patient matching. Patient matching is used to position the subject 1018 in radiation therapy. Adjustments to the subject 1018 position are done by the support positioning system 1140. The DRR images can replace conventional CT images.

In another embodiment, the bone enhanced image or cortical bone image are used to register the images with other images including other imaging modalities such as PET, SPECT, CT, etc. The images generated from the pulse sequence 300 are inherently registered. The bone-enhanced images provide both registration and density information for attenuation. Furthermore, the generated MR images from the pulse sequence include soft-tissue images which further enhance attenuation.

FIG. 14 shows a flow chart which illustrates an embodiment of a method 1400 of acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

In an operation 1405, magnetic resonance data is acquired using an MRI system and a pulse sequence. In some embodiments, the pulse sequence may for instance be a pulse sequence as is illustrated in FIG. 3. In some embodiments, the free induction decay data for the ultra-short echo time image may be omitted, for example when the imaging volume is a pelvic area or other area where no cortical bone/air adjacencies are expected to exist such that bone and air segments may be separated, for example, by reference to a priori knowledge of human anatomy (e.g., by use of a bone probability atlas).

In an operation 1410 the magnetic resonance data is segmented into a fat segment, a water segment, a cortical bone segment, and an air segment. In some embodiments, the fat segment and the water segment may be obtained via a Dixon acquisition. In some embodiments, the cortical bone segment may be obtained as explained above by subtracting an in-phase image from an ultra-short echo time image. In other embodiments, the cortical bone segment may be obtained by inverting the in-phase image and registration with a bone probability atlas. In some embodiments, the air segment may be obtained by adding the in-phase image to a cortical bone image generated according to embodiments set forth above.

In an operation 1415, a bulk density map (i.e., an electron bulk density map) is created using the fat, water, cortical bone, and air segments.

In some embodiments, a predetermined bulk density value for fat is assigned to the fat segment, a predetermined bulk density value for water is assigned to the water segment, a predetermined bulk density value for cortical bone is assigned to the cortical bone segment, and a predetermined bulk density value for air is assigned to the air segment. Then, the various segments with the corresponding assigned bulk density values may be combined to produce a bulk density map for the imaging volume. In some embodiments, the predetermined bulk density values may be determined based on empirical data for a plurality of individuals. In some embodiments, the predetermined bulk density values may be determined at least in part based on characteristics of an individual patient, which may include the patient's age, sex, etc.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, which element among fat, water, cortical bone and air segment is primarily represented in the voxel; and assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone and air is primarily represented in the voxel.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to that voxel, including a fat fraction, a water fraction, a cortical bone fraction, and an air fraction; and for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

FIG. 15 shows a flow chart which illustrates another embodiment of a method 1500 acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

In an operation 1505, magnetic resonance data is acquired using an MRI system and a pulse sequence. In some embodiments, the pulse sequence may for instance be a pulse sequence as is illustrated in FIG. 3. In some embodiments, the free induction decay data for the ultra-short echo time image may be omitted, for example when the imaging volume is a pelvic area or other area where no cortical bone/air adjacencies are expected to exist such that bone and air segments may be separated, for example, by reference to a priori knowledge of human anatomy (e.g., by use of a bone probability atlas).

In an operation 1510 the magnetic resonance data is segmented into a fat segment, a water segment, a cortical bone segment, and an air segment. In some embodiments, the fat segment and the water segment may be obtained via a Dixon acquisition. In some embodiments, the cortical bone segment may be obtained as explained above by subtracting an in-phase image from an ultra-short echo time image. In other embodiments when the imaging volume is a pelvic area or other area where no cortical bone/air adjacencies are expected to exist, the cortical bone segment may be obtained by inverting the in-phase image and registration with a bone probability atlas. In some embodiments, the air segment may be obtained by adding the in-phase image to a cortical bone image generated according to embodiments set forth above.

In an operation 1515, a predetermined bulk density value for fat is assigned to the fat segment, a predetermined bulk density value for water is assigned to the water segment, a predetermined bulk density value for cortical bone is assigned to the cortical bone segment, and a predetermined bulk density value for air is assigned to the air segment. Then, the various segments with the corresponding assigned bulk density values may be combined to produce a bulk density map for the imaging volume. In some embodiments, the predetermined bulk density values may be determined based on empirical data for a plurality of individuals. In some embodiments, the predetermined bulk density values may be determined at least in part based on characteristics of an individual patient, which may include the patient's age, sex, etc.

In an operation 1520, a bulk density map (i.e., an electron bulk density map) is created using the fat, water, cortical bone, and air segments.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, which element among fat, water, cortical bone and air segment is primarily represented in the voxel; and assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone and air is primarily represented in the voxel.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to that voxel, including a fat fraction, a water fraction, a cortical bone fraction, and an air fraction; and for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

In an operation 1525, one or more digitally reconstructed radiographs (DRRs) are created using the electron bulk density map created in operation 1520. In some embodiments, operation 1525 may be omitted.

In an operation 1530, one or more artificial computed tomography images are generated based on the fat, water, cortical bone, and air fractions in each voxel. In some embodiments, operation 1530 may be omitted.

In an operation 1535, a bulk density map, one or more DRRS, and/or one or more artificial computed tomography images are transferred to a radiation treatment planning system. In some embodiments, images may be transferred in accordance with the Digital Imaging and Communications in Medicine (DICOM) standard. In some embodiments, the DRRs may be generated by a magnetic resonance imaging system or apparatus in operation 1525, and transferred to a treatment planning system in operation 1535. In other embodiments, DRRs may be generated by the treatment planning system, for example using the electron bulk density map.

FIG. 16 shows a flow chart which illustrates yet another embodiment of a method 1600 of acquiring magnetic resonance data and processing the magnetic resonance data for treatment planning.

In an operation 1605, magnetic resonance data is acquired using an MRI system and a pulse sequence. In some embodiments, the pulse sequence may for instance be a pulse sequence as is illustrated in FIG. 3. In some embodiments, the free induction decay data for the ultra-short echo time image may be omitted, for example when the imaging volume is a pelvic area or other area where no cortical bone/air adjacencies are expected to exist such that bone and air segments may be separated, for example, by reference to a priori knowledge of human anatomy (e.g., by use of a bone probability atlas).

In an operation 1610, an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image are reconstructed from the magnetic resonance imaging data.

In an operation 1615, background noise is filtered or removed from the in-phase image. In some embodiments, background noise may be removed by automatic intensity thresholding. In some embodiments, this may yield bone-enhanced images. In some embodiments, operation 1615 may be omitted.

In an operation 1620, the in-phase image (or the noise-filtered in-phase image) is registered with a bone probability atlas. The bone probability atlas may have been generated based on magnetic resonance data generated for a plurality of sample patients or subjects. In some embodiments, operation 1620 may be omitted.

In an operation 1625, a cortical bone image is generated from the in-phase image. In some embodiments, the cortical bone image may be obtained as explained above by subtracting an in-phase image from an ultra-short echo time image. In other embodiments when the imaging volume is a pelvic area or other area where no cortical bone/air adjacencies are expected to exist, the cortical bone image may be obtained by inverting the in-phase image and registration with a bone probability atlas.

In an operation 1630 the magnetic resonance data is segmented into a fat segment, a water segment, a cortical bone segment, and an air segment using the images which were reconstructed in operations 1610 through 1625. In some embodiments, the fat segment and the water segment may be obtained via a Dixon acquisition. In some embodiments, the air segment may be obtained by adding the in-phase image to the cortical bone image generated according to operations set forth above.

In an operation 1635, a predetermined bulk density value for fat is assigned to the fat segment, a predetermined bulk density value for water is assigned to the water segment, a predetermined bulk density value for cortical bone is assigned to the cortical bone segment, and a predetermined bulk density value for air is assigned to the air segment. Then, the various segments with the corresponding assigned bulk density values may be combined to produce a bulk density map for the imaging volume. In some embodiments, the predetermined bulk density values may be determined based on empirical data for a plurality of individuals. In some embodiments, the predetermined bulk density values may be determined at least in part based on characteristics of an individual patient, which may include the patient's age, sex, etc.

In an operation 1640, a bulk density map (i.e., an electron bulk density map) is created using the fat, water, cortical bone, and air segments.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, which element among fat, water, cortical bone and air segment is primarily represented in the voxel; and assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone and air is primarily represented in the voxel.

In some embodiments, the bulk density map is created from the segments by: determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to that voxel, including a fat fraction, a water fraction, a cortical bone fraction, and an air fraction; and for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

In an operation 1645, one or more digitally reconstructed radiographs (DRRs) are created using the electron bulk density map created in operation 1520. In some embodiments, operation 1645 may be omitted.

In an operation 1650, one or more artificial computed tomography images are generated based on the fat, water, cortical bone, and air fractions in each voxel. In some embodiments, operation 1650 may be omitted.

Although not illustrated in FIG. 16, in some embodiments the method may further include an operation of transferring a bulk density map, one or more DRRS, and/or one or more artificial computed tomography images to a radiation treatment planning system. In some embodiments, images may be transferred in accordance with the Digital Imaging and Communications in Medicine (DICOM) standard. In other embodiments, DRRs may be generated by the treatment planning system, for example using the electron bulk density map.

FIG. 17 shows some example images which may be generated from magnetic image data for treatment planning. In particular, FIG. 17 illustrates some example images which may be generated in methods 1400, 1500 and/or 1600 described above. FIG. 18 shows a Dixon in-phase image 1710, a bulk density map 1720, and an artificial computed tomography (CT) image 1730.

FIG. 18 shows yet another embodiment of a medical apparatus 1800.

Medical apparatus 1800 is similar to medical apparatus 1100 described above. However, medical apparatus 1800 includes in storage 1030 and memory 1032 instructions, data, and software modules which allow it to execute one or all of the methods 1400, 1500, and 1600. In particular, storage 1030 includes bulk density map generation commands 1850 for executing one or more of the methods 1400, 1500 and 1600, and memory 1032 includes bulk density map generation command generation module 1852.

Also, although not specifically illustrated in FIG. 18, in some embodiments storage 1030 may include a plurality of segments of the magnetic resonance data, including a fat segment, a water segment, a cortical bone segment, and an air segment. Additionally, although not specifically illustrated in FIG. 18, in some embodiments storage 1030 may include a plurality of predetermined bulk density values to fat, water, cortical bone and air. Moreover, in some embodiments, although not specifically illustrated in FIG. 18, storage 1030 may include one or more automated computed tomography (CT) images. Furthermore, in some embodiments, storage 1030 may include a bone probability atlas.

Similarly, although not specifically illustrated in FIG. 18, in some embodiments memory 1032 may include an imaging volume segmentation module, a bulk density value assignment module, an automated computed tomography image generation module, and/or a bone probability atlas registration module.

Accordingly, medical apparatus 1800 may be configured to execute one or more of the methods 1400, 1500 and 1600 described above.

FIG. 19 illustrates an example embodiment of operations which may be performed by a system and method which acquire magnetic resonance data and process the magnetic resonance data for treatment planning. In particular, FIG. 19 illustrates: a magnetic resonance data acquisition operation 1910 which produces first and second echo images; a Dixon reconstruction operation 1920 which produces an in-phase image 1922, a water image 1924, and a fat image 1926; a tissue classification and electron bulk density assignment operation 1930 which produces a bone-enhanced image 1932 and an electron bulk density map 1934, and a filtering operation 1940 which filters bone-enhanced image 1932 and electron bulk density map 1934 with a bone probability atlas 1936 to produce a filtered bone-enhanced image 1942 and a filtered electron bulk density map 1944.

FIG. 20 shows an example embodiment of modules and corresponding work flow for a system and method which acquire magnetic resonance data and process the magnetic resonance data for treatment planning. In particular, FIG. 20 illustrates a magnetic resonance image and registration module 2010, an automated segmentation and tissue classification module 2020, an imaging/planning interface 2030, and a simulation and planning platform 2040. Magnetic resonance image and registration module 2010 produces a bone image 2012 (e.g., from a T1 weighted ultra-short time echo (UTE), water/fat images 2014 (e.g., by employing a Dixon algorithm), a pathologic image 2016 (e.g., a T2-weighted image), and a functional MR image 2018 (e.g., a T2 image, a dynamic contrast enhanced (DCE) image, a diffusion weighted image (DWI), etc.). Automated segmentation and tissue classification module 2020 receives from images 2012, 2014, 2016 and 2018 and generates therefrom segments 2022, corresponding to bone, air and soft tissue (e.g., a water segment and a fat segment), and one or more images 2024 of a tumor, target organ and risk strictures for treatment planning. Imaging/planning interface 2030 communicates or transfers a magnetic resonance volume image 2032 (e.g., in DICOM format), an electron bulk density map and/or one or more automated computed tomography images(s) 2034 (e.g., in DICOM format), and a tissue mask for autocontouring (e.g., in DICOM format). Simulation and planning platform 2040 receives images 2032, 2034 and 2036 and generates therefrom a treatment plan 2042.

While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments.

Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measured cannot be used to advantage. A computer program may be stored/distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems. Any reference signs in the claims should not be construed as limiting the scope.

LIST OF REFERENCE NUMERALS X

• • 300 pulse sequence
  • 302 RF
  • 304 read out gradient
  • 306 data acquisition gate
  • 308 nuclear magnetic resonance signal
  • 310 radio frequency pulse
  • 312 time T_RF
  • 314 free induction decay
  • 316 first gradient echo
  • 318 second gradient echo
  • 320 first gradient pulse
  • 322 second gradient pulse
  • 324 third gradient pulse
  • 326 TE₁
  • 328 TE₂
  • 330 TE₃
  • 332 TAQ1
  • 334 TAQ2
  • 336 TAQ3
  • 400 cortical bone image
  • 402 cortical bone
  • 500 fat-only (water-saturated) image
  • 502 medullary bone
  • 600 complete bone image
  • 602 cortical plus medullary bone
  • 700 fat-saturated image
  • 800 in-phase image
  • 900 ultra-short echo time image (phase)
  • 902 air
  • 1000 medical apparatus
  • 1002 magnetic resonance imaging system
  • 1004 magnet
  • 1006 bore of magnet
  • 1008 imaging zone
  • 1010 magnetic field gradient coil
  • 1012 magnetic field gradient coil power supply
  • 1014 radio frequency coil
  • 1016 transceiver
  • 1018 subject
  • 1020 subject support
  • 1022 computer
  • 1024 hardware interface
  • 1026 processor
  • 1028 user interface
  • 1030 computer storage
  • 1032 computer memory
  • 1034 pulse sequence
  • 1036 magnetic resonance data
  • 1038 in-phase image
  • 1040 fat-saturated image
  • 1042 water-saturated image
  • 1044 ultra-short echo time image
  • 1046 opposed phase image
  • 1048 medullary bone image
  • 1050 cortical bone image
  • 1052 complete bone image
  • 1054 spatially dependent radiation attenuation coefficient
  • 1056 radiation therapy planning data
  • 1058 treatment plan
  • 1060 control module
  • 1062 image reconstruction module
  • 1064 image manipulation module
  • 1066 three-point Dixon signal model
  • 1068 image segmentation module
  • 1070 radiation attenuation coefficient calculation module
  • 1072 radiation therapy planning data generation module
  • 1074 graphical user interface control module
  • 1076 graphical user interface
  • 1078 radiation therapy planning interface
  • 1122 radiation therapy system
  • 1124 cryostat
  • 1126 superconducting coil
  • 1128 compensation coil
  • 1130 reduced magnetic field region
  • 1132 gantry
  • 1133 axis of rotation
  • 1134 radiotherapy source
  • 1135 rotational actuator
  • 1138 radiation beam
  • 1140 support positioning system
  • 1142 target zone
  • 1150 radiation therapy control commands
  • 1152 radiation therapy control command generation module
  • 1200 medical apparatus
  • 1202 radio-isotope imaging system
  • 1204 scintillator ring
  • 1206 light pipes
  • 1208 light detectors
  • 1210 concentration of radio isotope
  • 1212 radiation
  • 1220 radio-isotope imaging data
  • 1222 medical image
  • 1230 medical image reconstruction module
  • 1240 digital reconstructed radiograph (DRR)
  • 1710 Dixon in-phase image
  • 1720 bulk density map
  • 1730 artificial computed tomography image
  • 1800 medical apparatus
  • 1850 bulk density map generation commands
  • 1852 bulk density map generation command generation module
  • 1910 magnetic image acquisition operation
  • 1920 Dixon reconstruction operation
  • 1922 in-phase image
  • 1924 water image
  • 1926 fat image
  • 1930 tissue classification and electron bulk density assignment operation
  • 1932 bone-enhanced image
  • 1934 electron bulk density map
  • 1936 bone probability map
  • 1940 filtering operation
  • 1942 filtered bone-enhanced image
  • 1944 filtered electron bulk density map
  • 2010 magnetic resonance imaging and registration operation
  • 2012 cortical bone image
  • 2014 water/fat image
  • 2016 pathologic image
  • 2018 functional magnetic resonance image
  • 2020 automatic segmentation and classification operation
  • 2022 bone, air, fat, water segmentation
  • 2024 tissue, tumor, risk structure classification
  • 2030 imaging and planning interface
  • 2032 magnetic resonance volume
  • 2034 bulk density mask
  • 2036 tissue mask for autocontouring
  • 2040 simulation and treatment planning platform
  • 2042 treatment plan

Claims

1. An apparatus, comprising:

a magnetic resonance imaging system which acquires magnetic resonance data from an imaging volume;

a processor for controlling the apparatus; and

a memory containing machine executable instructions and a pulse sequence, wherein the magnetic resonance data is acquired using the pulse sequence includes gradient echo data, wherein execution of the instructions causes the processor to: acquire the magnetic resonance data using the magnetic resonance imaging system and the pulse sequence; and segment the magnetic resonance data into a plurality of segments, including a fat segment, a water segment, a cortical bone segment, and an air segment; and create a bulk density map of the imaging volume from the segments.

2. The apparatus of claim 1, wherein execution of the instructions further causes the processor to create the bulk density map from the segments by:

determining for each of a plurality of voxels of the imaging volume, which element among fat, water, cortical bone and air segment is primarily represented in the voxel; and

assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone and air is primarily represented in the voxel.

3. The apparatus of claim 1, wherein execution of the instructions further causes the processor to create the bulk density map from the segments by:

assigning corresponding bulk density values to fat, water, cortical bone and air;

determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to the voxel, including a fat fraction, a water fraction, a cortical bone fraction, and an air fraction; and

for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

4. The apparatus of claim 1, wherein execution of the instructions further causes the processor to generate one or more digitally reconstructed radiographs (DRRs) from the magnetic resonance data.

5. The apparatus of claim 4, wherein execution of the instructions further causes the processor to transfer the one or more DRRs to a radiation treatment planning system.

6. The apparatus of claim 1, wherein execution of the instructions further causes the processor to generate an artificial computed tomography image based on fractions of fat, water, air, and cortical bone in each voxel of the imaging volume.

7. The apparatus of claim 1, wherein execution of the instructions further causes the processor to reconstruct an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image from the magnetic resonance data, and to produce the cortical bone segment by subtracting a scaled multiple of the in-phase image from the ultra-short echo time image.

8. The apparatus of claim 1, wherein execution of the instructions further causes the processor to reconstruct an in-phase image, a fat-saturated image, and a water-saturated image from the magnetic resonance data, and to produce the cortical bone segment by automatically thresholding a noise level in the in-phase image and subsequently removing background noise.

9. The apparatus of claim 8, wherein execution of the instructions further causes the processor to produce the cortical bone segment by registering the in-phase image with a bone probability atlas.

10. The apparatus of claim 1, wherein execution of the instructions further causes the processor to transfer the bulk density map to a radiation treatment planning system.

11. A method, comprising:

acquiring magnetic resonance data from an imaging volume via a magnetic resonance imaging system and a pulse sequence, wherein the magnetic resonance data includes gradient echo data;

segmenting the magnetic resonance data into a plurality of segments, the segments including a fat segment, a water segment, a cortical bone segment, and an air segment; and

creating a bulk density map of the imaging volume from the segments.

12. The method of claim 11, wherein creating the bulk density map from the segments comprises:

determining, for each of a plurality of voxels of the imaging volume, which element among fat, water, air and cortical bone is primarily represented in the voxel; and

assigning a corresponding bulk density value to each voxel, where the assigned bulk density value depends on which element among fat, water, cortical bone, and air is primarily represented in the voxel.

13. The method of claim 11, wherein creating the bulk density map from the segments comprises:

assigning corresponding bulk density values to fat, water, cortical bone and air;

determining, for each of a plurality of voxels of the imaging volume, a plurality of fractions which pertain to the voxel, including an a fat fraction, a water fraction, a cortical bone fraction and an air fraction; and

for each of the plurality of voxels, weighting each of the plurality of fractions by the corresponding bulk density value.

14. The method of claim 11, further comprising generating one or more digitally reconstructed radiographs (DRRs) from the magnetic resonance data.

15. The method of claim 14, further comprising transferring the one or more DRRs to a radiation treatment planning system.

16. The method of claim 11, further comprising generating an artificial computed tomography image based on fractions of fat, water, cortical bone, and air in each voxel of the imaging volume.

17. The method of claim 11, further comprising:

reconstructing an in-phase image, a fat-saturated image, a water-saturated image, and an ultra-short echo time image from the magnetic resonance data; and

producing the cortical bone segment by subtracting a scaled multiple of the in-phase image from the ultra-short echo time image.

18. The method of claim 11, further comprising:

reconstructing an in-phase image, a fat-saturated image, and a water-saturated image from the magnetic resonance data; and

producing the cortical bone segment by automatically thresholding a noise level in the in-phase image and subsequently removing background noise.

19. The method of claim 18, wherein producing the cortical bone segment further comprises registering the in-phase image with a bone probability atlas.

20. A non-transitory computer-readable storage medium having stored therein a pulse sequence and machine readable instructions configured to be executed by a processor to control an apparatus including a magnetic resonance imaging system, the machine readable instructions being configured in conjunction with the pulse sequence to cause the apparatus to execute a process comprising:

acquiring magnetic resonance data from an imaging volume using the magnetic resonance imaging system and the pulse sequence, wherein the magnetic resonance data includes gradient echo data;

segmenting the magnetic resonance data into a plurality of segments, the segments including a fat segment, a water segment, a cortical bone segment, and an air segment; and

creating a bulk density map of the imaging volume from the segments.