Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
  • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
  • G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
  • G01T1/2914—Measurement of spatial distribution of radiation
  • G01T1/2985—In depth localisation, e.g. using positron emitters; Tomographic imaging (longitudinal and transverse section imaging; apparatus for radiation diagnosis sequentially in different planes, steroscopic radiation diagnosis)
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
  • A61B6/03—Computed tomography [CT]
  • A61B6/037—Emission tomography
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
  • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
  • G01T1/16—Measuring radiation intensity
  • G01T1/161—Applications in the field of nuclear medicine, e.g. in vivo counting
  • G01T1/164—Scintigraphy
  • G01T1/1641—Static instruments for imaging the distribution of radioactivity in one or two dimensions using one or several scintillating elements; Radio-isotope cameras
  • G01T1/1647—Processing of scintigraphic data
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T12/00—Tomographic reconstruction from projections
  • G06T12/10—Image preprocessing, e.g. calibration, positioning of sources or scatter correction

Definitions

• PET Positron Emission Tomography
• CBM continuous bed motion
• detector arrays detect pairs of gamma photon's emitted from a positron annihilation event in a subject.
• the pairs of detected gamma photon's determine a line of response (LOR).
• a time-of-flight (TOF) PET adds an estimate of the originating location where the annihilation event occurred based on the mean time difference between detection of each photon pair. The estimate is a distance along the LOR.
• Detected coincident pairs and TOF information can be recorded in an event list called list mode data. One or more images are reconstructed from the list mode data.
• Clinical workflow includes the time to scan the patient and the time to reconstruct one or more images. Clinical time is valuable.
• Clinical workflow can include imaging with one or more imaging modalities such as X-ray computed tomography (CT).
• CT X-ray computed tomography
• One approach to improving clinical workflow is to generate images quickly while reducing overall scan time.
• the patient support moves to a first position, stops, and a first region of the patient is imaged. After imaging the first region, the support is moved to a second position, stopped, and a second region is imaged, and so forth. For uniform sampling, the regions of the patient are overlapped, e.g. by 50%.
• CBM continuous bed movement
• the CBM shortens the overall scan time because the bed is in continuous motion and data is collected continuously. The time to start and stop the bed in the step and shoot method is eliminated.
• a single large data set is collected and image reconstruction is deferred until all data is acquired.
• each sinogram includes data contributions from the full length of the data set.
• the data cannot be binned into sinograms until all the data is collected.
• the image reconstruction is deferred until the end which uses intensive computing resources.
• the patient is not released from the scanner until the reconstructed image has been received and approved causing a bottleneck in the workflow.
• combining the reconstructed images with images from other modalities is deferred which adds to the computing resource bottleneck.
• the combination with other modalities utilizes imaging components such as attenuation maps.
• a positron emission tomography (PET) system includes a memory, a subject support, a categorizing unit, and a reconstruction unit.
• the memory continuously records detected coincident event pairs detected by PET detectors.
• the subject support supports a subject and moves in a continuous movement through a field of view of the PET detectors.
• the categorizing unit categorizes the recorded coincident pairs into each of a plurality of spatially defined virtual frame.
• the reconstruction unit reconstructs the categorized coincident pairs of each virtual frame into a frame image and combines the frame images into a common elongated image.
• a method of positron emission tomography includes moving a subject on a subject support continuously through a field of view of PET detectors while recording detected coincident event pairs in a memory. Recorded coincident event pairs are categorized into each of a plurality of spatially defined virtual frames. The categorized coincident events of each virtual frame are reconstructed into a common elongated image.
• a time-of-flight (TOF) positron emission tomography (PET) system includes a PET detector array, a subject support, and one or more processors.
• the PET detector array detects and records coincident events in a list mode.
• the subject support supports a subject and moves in a continuous movement through a field of view of the PET detector array.
• the one or more processors are configured to categorize the recorded coincident pairs into contiguous virtual frames based on time-of-flight information.
• the one or more processors are further configured to reconstruct a frame image from each virtual frame and combine frame images into a continuous elongated field of view.
• One advantage is improved patient comfort.
• Another advantage resides in integrated multi-modal workflow.
• Another advantage resides in efficient concurrent reconstruction with distributed processing.
• Another advantage includes shorten scan latency.
• Another advantage is a uniform axial sensitivity profile.
• Another advantage resides in better axial sampling and spatial resolution.
• Another advantage includes region of interest adapted acquisition.
• the invention may take form in various components and arrangements of components, and in various steps and arrangement of steps.
• the drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
• FIGURE 1 schematically illustrates an embodiment of a CBM with virtual frames PET system.
• FIGURE 2 schematically illustrates an exemplary CBM acquisition with virtual frames.
• FIGURE 3 schematically illustrates an exemplary CBM using time-of-flight (TOF) virtual frame categorization of events.
• TOF time-of-flight
• FIGURE 4 flowcharts one method of using an embodiment of CBM with virtual frames.
• the system 1 includes a TOF-PET scanner 2 shown in a cross section.
• a non-TOF PET is also contemplated.
• the scanner is configured with a subject support or bed 3 which moves in a continuous movement through a PET detector array 4.
• the detectors are disposed about an opening or bore 6 through which the subject support moves in an axial direction 8.
• the disposition of the detectors 4 about the opening define a field of view 10.
• the subject support 3 supports a subject 12 who is injected with a radiopharmaceutical. As the subject support 3 moves through the field of view 10, the radiopharmaceutical decays as it is taken up by tissue then washes out.
• positrons are emitted which cause annihilation events that emit gamma photons as coincident pairs.
• the coincident pairs of gamma photons from the field of view 10 are detected by the detectors 4.
• the CBM or movement of the subject support is recorded such as an initial position, constant speed and elapsed time, and/or by positional sensors which record the exact position at a time synchronized with the detectors.
• the data for each detector event includes the time each event of the pair was detected, a detector location at which each event was detected, and support location at the time of detection.
• the volume or subject to be imaged 12 is divided into contiguous spatial virtual frames 14 defined by a distance along the axial direction of the movement of the subject support.
• the virtual frames 14 can be any length and are configured by a framing unit 16.
• the length of each virtual frame 14 configured by the framing unit 16 can be based on a variety of factors such as a protocol of a scan, a length of the field of view, a distributed computing configuration, a velocity of the subject support, an expected image quality, anatomical features of the subject from another imaging modality and the like.
• one frame may be sized to the brain, and another frame to the heart, another to the abdomen, etc.
• the frames can be longer, shorter, or the same size as the field of view 10.
• many virtual frames can be used to distribute the reconstruction workload. With a high rate of speed for the subject support, longer virtual frames are indicated.
• the detected coincident pair events are recorded in list mode.
• the detectors 4 are connected to a list mode memory 18 which records the coincident pair events in order.
• the list mode includes the time and location of each detected gamma photon, from which time-of-flight information is derived.
• Event data is acquired continuously in the list mode as the subject support 3 moves continuously through the field of view 10.
• Each virtual frame 14 moves into the field of view, through the field of view, and passes out of the field of view.
• the list mode memory can be either transitory or non-transitory.
• the non-transitory memory includes storage mediums such as disk, virtual disks, cloud based storage and the like.
• a categorizing unit 20 categorizes the coincident pairs into one of a virtual frame 14 based on a spatial location at which the annihilation decay event occurred.
• the categorization includes a translation from the coordinate system of the detectors to the coordinate system of the subject support. If the subject does not move, then the subject support and the subject shared the same coordinate system. The two coordinate systems share the same planar position or x-y coordinate and differ only in the z or axial direction.
• the categorization resolves the difference between the Zd or detector coordinate and the z s or subject support coordinate. The resolution can be performed using the time from the list mode and the relative position of the subject support at the same time.
• the position of the z s is known at time ti and t 2 and an acquisition timestamp indicates that the time of the event occurred at t d where ti ⁇ t d ⁇ t 2 and the speed is relatively constant, then the position z s can be interpolated at time t d .
• Each coincident pair can be categorized in real time as the pair is received or retrospectively from the list mode memory.
• the categorization can include adding an index identifying its virtual frame to the coincident pair in list mode memory, and/or sorting the coincident pair into the corresponding separate list for each virtual frame 21.
• the coincident pair events are categorized by spatial location, not by time of detection. Particularly when an interface between two frames is moving through the field of view, the events of the two adjoining frames will be temporally interspersed.
• each virtual frame can be reconstructed separately by a reconstruction unit 22.
• the reconstruction unit 22 reconstructs each virtual frame with the coincident pairs categorized for the respective virtual frame.
• the virtual frame represents a complete unit of work for reconstruction which can utilize distributed processing techniques. For example, a first virtual frame can be assigned to a first processor configured to perform the reconstruction, such as Cartesian based reconstruction, sinogram based reconstruction, or the like. While the first processor reconstructs the first frame into an image, data is continually acquired for subsequent virtual frames.
• a second processor is assigned reconstruction of the second virtual frame. As reconstruction of each virtual frame into an image completes, then the processor can be reassigned to another virtual frame reconstruction.
• Processors can include multi-core processors and multiple processors and/or combinations.
• the frame image is combined with the other reconstructed images of the elongated image and can be displayed on a display device 24 such as a display device of a workstation 26.
• the display device can include a computer monitor, a television screen, a touch screen, Cathode ray tube (CRT), Flat panel display, 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 the like.
• the workstation 26 includes an electronic processor or electronic processing device 28, and one or more input devices 30.
• the display 24 displays the elongated reconstructed image or each virtual frame, and menus, panels, and user controls, such as entry or selection of configuration information utilized by the framing unit 16.
• the workstation 20 can be a desktop computer, a laptop, a tablet, a mobile computing device, a smartphone, and the like.
• the input device can be a keyboard, a mouse, a microphone, and the like.
• the various units 16, 20, 22 are suitably embodied by an electronic data processing device programmed to perform the function of the various units, and can include an electronic processor or electronic processing device 28 of the workstation 26, or by a network-based server computer operatively connected with the workstation 26 or so forth.
• the disclosed framing, categorizing, and reconstruction techniques are suitably implemented using a non-transitory storage medium storing instructions (e.g., software) readable by an electronic data processing device and executable by the electronic data processing device to perform the disclosed framing, categorizing and reconstruction techniques.
• instructions e.g., software
• the images of each virtual frame can be reassembled into an image volume and stored in a storage management system such as a Picture Archiving and Communication Systems (PACS), Radiology Information System, and the like.
• PACS Picture Archiving and Communication Systems
• Radiology Information System Radiology Information System
• FIGURE 2 schematically illustrates an exemplary CBM acquisition with virtual frames 14.
• the volume of a subject to be imaged starts at a starting point 32 and ends at an ending point 34.
• the volume is divided into contiguous virtual frames 14.
• Data acquisition or axial scanner coverage extends from an initial time 36 as the leading edge of the first frame enters the field of view to an end time 38 as the trailing edge of the last frame passes from the field of view.
• a complete data acquisition 40 for each virtual frame 14 includes a leading component 42, main component 44, and a trailing component 46.
• the leading component includes LORs which include one end point within the virtual frame and one in a leading frame.
• the main component includes LORs with both end points in the virtual frame, and the trailing component with one end point in the virtual frame and one in a following frame.
• the geometry of the detectors affects the length of the leading and trailing components.
• the size of the bore and the axial span of the detectors determine possible LORs.
• Many LORs occur at angles not orthogonal to the axis of movement.
• LORs can cross virtual frames, which means that data acquisition overlaps between frames.
• FIGURE 3 schematically illustrates an exemplary CBM with TOF virtual frame categorization of the coincident event pairs that span two frames.
• the coincident detected event pair of a first 50 and a second 52 detected gamma photon define end points of a line of response (LOR) 54.
• a position of an annihilation event, such as El 56 or E2 58 which emitted the detected gamma photon's occurs along the LOR, is resolved by the time of flight information.
• the TOF information provides information to determine the location or a probabilistic curve of a range of locations along the LOR at which the annihilation event occurred.
• the relative position of the subject support using the synchronized time and/or position of the subject support provides the translation to the coordinate system of the subject support.
• the time of flight provides the estimate which determines in the example the event occurred at a location El or at a location E2.
• the recorded coincident event is categorized in virtual frame A by resolving the coordinate difference between the detector and subject support.
• the recorded coincident event is categorized in virtual frame B. Categorization is performed by the categorization unit 20.
• Gamma photon pairs are located based on the position in the coordinate system of the subject support. This includes the coordinate system of the subject who is not moving relative to the subject support. Gamma photon pairs are detected as coincident pairs by the detectors in the coordinate system of the detectors. Categorization resolves the difference between the two coordinate systems. In the instance of when the TOF information indicates the event occurring at a frame boundary, then the event can be resolved by either categorizing the event in both frames and weighting the boundary in the reconstruction for overlap, categorizing according to the leading edge, categorizing according to the trailing edge, etc.
• Categorization can include adding an identifier such as an index to the list mode data and/or sorting the list mode data into separate lists. Separate lists can be used to reduce file contention prevention and improve data access during reconstruction.
• the El event sorts into a list file for virtual frame A 60 and the E2 event sorts into a list file for virtual frame B 62 based on the axial coordinate at a time t.
• Each list of virtual frame A 60 and virtual frame B 62 includes the categorized coincident pairs or events for the respective virtual frame.
• the annihilation event is assigned to the frame which is traversed by the largest portion of the LOR. In another example, the annihilation event is assigned proportionally to both frames, e.g. based on LOR portion.
• FIGURE 4 flowcharts one method of using an embodiment of CBM with virtual frames.
• the virtual frames 14 are configured by the framing unit 16.
• the configuration of the virtual frames defines the length of the virtual frame along the axial direction 8 of the CBM.
• the virtual frames 14 are configured based on input from the healthcare practitioner, the subject medical record, configuration information for the TOF- PET scanner, distributed computing resources, etc.
• the healthcare practitioner After administering the radiopharmaceutical, and placement of the subject 12 on the subject support 3, the healthcare practitioner initiates start of the continuous bed movement (CBM) or movement of the subject support in a step 66.
• CBM continuous bed movement
• the subject support moves in a continuous motion and preferably at a substantially constant speed. Positional sensors and/or time determine the precise position of the subject support and the virtual frames.
• the continuous motion provides for patient comfort over step and shoot techniques.
• the system continuously receives detected coincident pairs that define LORs in list mode.
• the detected coincident pairs include time of flight information.
• the detected coincident pairs are recorded in the list mode memory. While the subject support is in motion, the system can receive the detected data continuously.
• the CBM through the detectors along the axial position provides a more uniform axial sensitivity profile.
• the sampling along the axial length which passes through the detectors provides better axial sampling and spatial resolution.
• the information from other modalities such as CT is used to define the virtual frame to begin acquisition for region of interest adapted acquisition.
• the recorded coincident pairs in list mode memory 18 are categorized in a step 70 by the categorization unit 20.
• the categorization can begin as soon as each coincident pair event is recorded in the list mode memory 18 and continues as events are added to the memory.
• the categorization resolves the difference between the coordinate system of the detectors 4 and the subject support 3 and categorizes the event into the virtual frame in which the annihilation event was determined or projected to have occurred.
• the categorized virtual frame can include an identifier added to the list mode memory or the categorized virtual frame can include sorting the event into the separate list for each virtual frame, respectively.
• the reconstruction unit 22 reconstructs each categorized virtual frame. Reconstruction of each frame uses the separate list of each virtual frame or the index of identifiers into the list mode memory. For example a first virtual frame is reconstructed in a step 66, and a final virtual frame N is is reconstructed separately in step 68. Reconstructing the virtual frames separately provides for distributed computing techniques to be applied for reducing computing bottlenecks and efficient concurrent image reconstruction. The information such as attenuation maps from other modalities can be applied to each concurrent reconstruction.
• the reconstructed image of each virtual frame is optionally displayed on the display device 24 in a series of concurrent steps 76.
• the image of the first virtual frame is displayed on the display device in a step 72.
• Subsequent virtual frames can be displayed side by side, in overlay, etc.
• the display can continue for each virtual frame ending with a final virtual frame N in a step 74.
• the frames are reassembled 78 into a continuous elongated image.
• the elongated image displayed, stored in patient archives, and the like.
• the healthcare practitioner can interact with the system using the input device 30.
• particular elements or components described herein may have their functionality suitably implemented via hardware, software, firmware or a combination thereof. Additionally, it is to be appreciated that certain elements described herein as incorporated together may under suitable circumstances be stand-alone elements or otherwise divided. Similarly, a plurality of particular functions described as being carried out by one particular element may be carried out by a plurality of distinct elements acting independently to carry out individual functions, or certain individual functions may be split- up and carried out by a plurality of distinct elements acting in concert. Alternately, some elements or components otherwise described and/or shown herein as distinct from one another may be physically or functionally combined where appropriate.

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