Interactive vessel-based bolus ROI placement and scan planning using 3D CT Surview

Abstract

A system (FS) and associated method for facilitating contrast-based tomography. A graphics display generator (GDG) generates a graphical user interface (GUI) graphics display (GD) for display on a display device (DD). The graphics display (GD) may include a visualization of a segmentation within a 3D survey image and a visualization of a slider element indicating a reference position (m-ROI) along the segmentation. The reference position can be used to monitor the presence of contrast relative to a target anatomical feature (TAF) during a contrast-assisted imaging phase. An event handler receives user input and directs the graphics display generator (GDG) to update the graphics display (GD) and slides the slider element along the segmentation, thereby causing the slider to indicate one or more different reference positions.

Description

[Technical Field]

[0001] The present invention relates to systems, associated methods, imaging arrangements, computer program elements, and computer readable media that facilitate contrast-based tomography. [Background technology]

[0002] 2D (two-dimensional) projection surview images acquired prior to a diagnostic CT (computed tomography) scan play an important role in assisting the clinical technician (the "user") with proper patient positioning and achieving optimal image quality.

[0003] In addition to traditional 2D surveys (e.g., frontal or sagittal), it is now possible to acquire 3D (reconstructed) survey images (image volumes) at clinically acceptable doses. These offer several advantages over traditional 2D surveys and open up new possibilities for optimizing CT workflows that were not possible before.

[0004] In CT imaging, it is common to perform a 2D survey scan covering the entire region of interest, including the expected "bolus" tracking location. A bolus is a volume of contrast agent, such as iodine, administered. Contrast agents are sometimes used to enhance image contrast of anatomical structures of interest that weakly absorb radiation, such as cardiovascular structures in cardiac imaging. The user then manually selects a Z-position on such a 2D survey, and corresponding axial images, also known as "locators," are acquired and reconstructed to define ("place") a region of interest ("ROI") for bolus tracking or bolus arrival monitoring. The bolus travels with the blood flow and accumulates in the anatomical structure of interest for a period of time. The object is to trigger imaging at the appropriate time to capture high-contrast images before bolus washout.

[0005] Multiple locator scans may be required to find the appropriate location for the tracking ROI. The ROI captured to track the bolus is placed within this locator slice, and the arrival of the contrast bolus is monitored by repeatedly acquiring this single axial slice. Reaching a threshold contrast-induced density within this ROI triggers a subsequent diagnostic CTA (CT angiography) acquisition.

[0006] The main drawback of traditional bolus tracking using 2D survey images, or bolus tracking in general, is that planning bolus tracking during the scanning procedure is complex and highly dependent on the clinical user's skill and experience. This process is error-prone, requiring manual user intervention, such as manually selecting Z slices and placing ROIs on acquired locator slices. Human error in locating anatomical structures and placing ROIs on localizer images can result in the diagnostic CT scan being initiated at a suboptimal time. This can result in poor image quality, misdiagnosis, unnecessary contrast re-administration and re-imaging, and potentially adverse effects for the patient and / or medical staff. Furthermore, the manual localization process is subject to intra- and inter-individual variability. Another drawback is the need to acquire special locator scans, which requires additional time and dose. Summary of the Invention [Problem to be solved by the invention]

[0007] Therefore, there may be a need to improve the efficient operation of imaging devices, and in particular to ensure that the correct timing for initiating imaging operations of such imaging devices is established. [Means for solving the problem]

[0008] The object of the present invention is achieved by the subject matter of the independent claims, and further embodiments are incorporated in the dependent claims. It is noted that the following aspects of the present invention equally apply to the related methods, image arrangements, computer program elements and computer-readable media.

[0009] According to a first aspect of the present invention, 1. A system for facilitating tomographic imaging using a contrast agent, the system comprising: an input interface for receiving a 3D survey image volume of at least a portion of a patient, acquired by a tomography apparatus in a preparatory stage prior to a contrast agent-assisted imaging stage, said 3D survey image volume including segmentations for blood vessels through which a contrast agent will pass in a subsequent contrast agent-assisted imaging stage; a graphics display generator configured to generate a graphics display of a graphical user interface for display on a display device, said graphics display including a visualization of said segmentation and a visualization of a slider element indicating a reference position along said segmentation, said reference position suitable for monitoring for a presence of contrast agent relative to at least one target anatomical feature in said subsequent contrast agent-assisted imaging stage; an event handler configured to, upon receiving user input, instruct the graphics display generator to update the graphics display such that the slider element slides along the segmentation, the slider indicating one or more different reference positions; and A system is provided, comprising:

[0010] The segmentation is preferably calculated / derived from 3D survey images, for example using machine learning (deep learning models).

[0011] In an embodiment of the system, the graphics display generator is operable to adapt the spatial extent (e.g., shape, orientation, size) of the slider element to correspond to and vary accordingly with the geometric aspects (e.g., cross-section) of the segmentation at said different reference positions.

[0012] In embodiments, the graphics display generator is operable to lock the slider element to a direction defined by the segmentation, allowing the user to define clinically meaningful monitoring locations in a less "tedious" manner, particularly in stressful situations where defining accurate bolus monitoring can be difficult.

[0013] In an embodiment, the direction is along the centerline of the segmentation.

[0014] In embodiments, the visualization of the segmentation is configured to clearly represent the wall portions of the vessel. For example, the wall portions may be highlighted by color or gray value modulation, rendered as dashed lines, bold lines, a different color relative to the background and / or the interior of the segmentation, etc. The clear visualization of the wall portions may be adjusted to distinguish between calcified and non-calcified portions, or between various levels of calcification. This allows the user to avoid placing monitoring ROIs in calcified or heavily calcified vessel portions, as such portions have been found to be less useful for bolus monitoring purposes. Spectral imaging may be used when recording survey images to more precisely define calcification.

[0015] In an embodiment, the graphics display generator is operable to cause the graphics display to include information regarding i) the distance of the at least one target anatomical feature, a) to a reference position of the blood vessel corresponding to the current slider position, and / or b) to one or more anatomical landmarks, and / or ii) an estimated time of arrival of contrast agent at the reference position.

[0016] In an embodiment, the system may include an output interface for passing a user-selected one of one or more reference positions to the imaging device to define one end of a subset within the image area (called a "scan box") for projection data collected by the imaging device during the imaging phase.

[0017] In embodiments, the graphics display generator is operable to generate a graphics display further comprising a visualization of said subset, said slider element being located at one end of said visualization of said subset.

[0018] In an embodiment, the system includes an output interface for passing a user-selected one of one or more reference positions to instruct the imaging device to acquire a first set of projection data while a contrast agent propagates within a patient, and a reconstructor for reconstructing, based on the projection data, a cross-sectional tracker image in a plane passing through the selected reference position with a first image quality.

[0019] In an embodiment, the arrival time is based on hemodynamic modeling.

[0020] In embodiments, the blood vessel includes at least a portion of the aorta.

[0021] Therefore, the Facilitator system provides user interface functionality. Users of the Facilitator system can use it in conjunction with a fully automated segmenter system [machine learning (ML)-based or otherwise]. While such a segmentation system may in some cases find a completely satisfactory proposal for the definition of an appropriate bolus monitoring region, it is often still beneficial for a human clinical user to be able to fine-tune the solution proposed by such an automated segmentation system. Therefore, the proposed user interface functionality provides an intuitive user input solution, allowing users to quickly and safely perform this fine-tuning task with good results, ultimately finding an appropriate bolus monitoring region. In particular, by way of example, the proposed interface functionality allows, among other things (but not exclusively), visualization of results from the ML-based solution and the user to make such fine-tuning changes if they deem necessary.

[0022] The above results suggest that the proposed interface functionality allows for a more accurate and reliable method of establishing the correct timing for diagnostic projection data acquisition. It reduces the likelihood of image retakes, thereby lowering staff and patient radiation dose, increasing imaging throughput, and reducing machine wear, which is a particular concern in radiography where certain machine components, such as the anode disk, are exposed to large temperature gradients during data acquisition.

[0023] The proposed user feature achieves a good balance between giving users the freedom to fine-tune the initial position of the monitoring region, combined with a set of useful, clinically motivated constraints that provide meaningful guidance. Users, even novice or stressed clinical users, can achieve better results in m-ROI definition more quickly and safely.

[0024] The proposed user features can be used in combination with the automated segmentation described above, although such an automated system is not required here. Thus, the proposed user features can be used without such an automated segmentation system and instead, if desired, can be used, for example, to confirm manually segmented m-ROIs of the same or another user. While intended for use with fully automatic, semi-automatic, or manual segmentation tools, the proposed user interface features may be particularly useful with fully automatic or semi-automatic segmentation tools.

[0025] The proposed system allows for a higher degree of interaction in planning the bolus tracking ROI compared to fully automated systems. Therefore, an embodiment of the present specification proposes a vascular-based interactive bolus ROI placement and scan planning method based on 3D CT Surview. The proposed user functionality is directed toward the placement of bolus monitoring ROIs in 3D Surview scans. Working with 3D Surview images, as opposed to simply 2D Surview data, can overcome the following drawbacks observed when working with 2D Surview image data:

[0026] 2D Surview has the inherent drawback of being unable to calculate the exact 3D distance between the bolus ROI and the target anatomical structure, and therefore unable to estimate the time required for the contrast agent to reach the target anatomical region, which often results in increased contrast agent dosage and suboptimal image quality.

[0027] The placement of the bolus ROI during scan planning is a complex task that is highly dependent on the clinician's expertise.

[0028] Special locator scans (single Z slices) must be acquired, which requires additional time and patient dose. In 3D Surview, these slices are acquired automatically because the field of view is already covered by axial slices.

[0029] Human user error in localizing anatomy and placing ROIs on localizer images can cause the CT scan to be initiated at a suboptimal time, resulting in poor image quality and potentially leading to incorrect diagnoses, reacquisition of images, patient re-examination, and unnecessary administration of contrast agents with potential side effects.

[0030] The proposed system provides a user-interactive way to place m-ROIs, which improves user convenience and allows users to place m-ROIs according to their preferences.

[0031] The proposed system provides a segmentation of the blood vessel through which the bolus is expected to pass. The blood vessel may be, for example, the entire or a portion of the aorta, or it may be a partial or complete segmentation of another vasculature of interest. The segmentation of the bolus's vascular path allows the user to visualize the relative position of the aortic wall compared to the placed or moved bolus ROI symbol (circle, ellipse, etc.). In a preferred embodiment, the wall of the blood vessel (e.g., the aorta) is explicitly presented to the user in addition to the placed bolus m-ROI. Such a system also allows the user, for example, to visualize calcifications in the aorta and place the bolus m-ROI accordingly by avoiding calcified regions within the specifically selected m-ROI. Material-selective imaging, such as spectral imaging, may be particularly beneficial in this regard.

[0032] The proposed interactive bolus m-ROI placement system and suggested visualization techniques can help users better place bolus m-ROIs relative to other important anatomical landmarks. For example, landmarks may include one or more various subsections of a blood vessel, such as the aorta. Subsections may include the aortic arch, ascending aorta, and descending aorta. Landmarks in blood vessel sections can be labeled or highlighted differently, allowing users greater control and more informed decisions when placing bolus m-ROIs relative to prominent anatomical landmarks. Additionally, or alternatively, visualization can provide users with information regarding distance and travel time estimates relative to one or more landmarks.

[0033] The proposed system and associated methods (see below) allow users to better adjust / modify a given m-ROI placement definition along the centerline of a vessel such as the aorta, using distances to anatomical landmarks and visualization of the aortic wall / diameter.

[0034] In yet another aspect, there is provided an imaging arrangement including the system of any of the above-described embodiments and one or more of an imaging device, a display device, a contrast agent administration device for administering a contrast agent, and a segmenter configured to provide segmentation of the survey image.

[0035] In a further embodiment, the imaging device may further include a bolus monitoring system configured for in-image monitoring and performing monitoring based on the tracker image within a predefined image neighborhood within the tracker image around the reference location. In an embodiment, the bolus monitoring system may be configured to instruct the imaging device, via the controller, to acquire a second projection data set at a second image quality higher than the first image quality when the in-image monitoring unit issues a trigger signal based on the one or more monitored image values ​​within the image neighborhood.

[0036] In another aspect, there is provided a method for facilitating tomographic imaging using a contrast agent, the method comprising: receiving a 3D survey image volume of at least a portion of a patient acquired by a tomography apparatus in a preparatory stage prior to a contrast agent-assisted imaging stage, said 3D survey image volume including segmentations for blood vessels through which a contrast agent will pass in a subsequent contrast agent-assisted imaging stage; generating a graphics representation of a graphical user interface for display on a display device, said graphics representation including a visualization of said segmentation and a visualization of a slider element indicating a reference position along said segmentation, said reference position suitable for monitoring for the presence of contrast agent relative to at least one target anatomical feature during said subsequent contrast agent-assisted imaging stage; instructing the graphics display generator to update the graphics display such that the slider element slides along the segmentation upon receiving user input, the slider indicating one or more different reference positions; A method is provided, comprising:

[0037] In yet another aspect, there is provided a computer program element configured, when executed by at least one processing unit, to cause the processing unit to perform a method.

[0038] In yet another aspect, at least one computer-readable medium having program elements stored thereon is provided.

[0039] The system and associated methods (see below) are primarily intended for use in the medical field herein, although the principles described herein can also be used in other fields, such as the inspection of inaccessible hydraulic and piping systems using contrast agents (e.g., dyes), and hydrological inspections to understand groundwater movement, etc. As with medical imaging, the system and method allow for optimized timing to begin acquisition at the moment when the best image can be collected, thereby reducing wear on imaging equipment and avoiding repetitive imaging.

[0040] "User" refers to a person operating an imaging device or overseeing an imaging procedure, such as a medical professional. In other words, the user is generally not the patient.

[0041] "Object" is used herein in a general sense to include living "objects" such as human or animal patients, or anatomical parts thereof, but also inanimate objects such as security check luggage or non-destructive testing products. However, because the proposed system is described primarily in the medical field, we will refer to an "object" as a "patient" or a part of a patient, such as a patient's anatomy, organ, or group of anatomical structures or organs.

[0042] As used herein, a "survey image" is a 3D image volume acquired with a larger field of view (FOV) at a lower radiation dose cost than the dose cost and field of view (FOV) of a subsequent diagnostic image volume. Diagnostic image volumes are necessary to perform or support medical tasks, such as diagnosis or treatment. Surveillance images are not typically used for such tasks, but may be used, for example, for planning. The FOV of a survey image volume includes not only the anatomical structures of interest that are the objective of the medical task itself, but also other landmark anatomical structures that generally do not serve the medical task and only function as ancillary to imaging. The FOV can be a whole-body scan, but need not be in all cases. Typically, the FOV of a survey image captures a larger anatomical cross-section, such as the abdomen or chest.

[0043] As used herein, a "Z position" or similar term refers to an example of a reference position within the image region contemplated herein for the definition of a tracker image. The "Z position" generally refers to a position on one of three spatial coordinate axes (the "Z axis") that span the image region. Typically, this Z axis corresponds to the axis of rotation of a rotational tomography device or the virtual axis of rotation of the imaging device of a fifth generation scanner. However, the aforementioned Z axis may differ from the axis of rotation of a reformatted survey volume also contemplated herein.

[0044] By "image processing" in this regard, it is understood that the processing of images contemplated and described herein, e.g., survey images or segmentation of vessels, landmarks, m-ROIs, etc., regardless of embodiment and configuration or setting, specifically includes not only processing in the image domain of image values ​​(e.g., HU values, etc.), but also processing in transform domains such as the frequency domain, or other domains where the survey image is first transformed, at least a portion of the processing is performed there, and optionally transformed back to the image domain as needed. Transforms contemplated herein include Fourier-based transforms (e.g., Laplace transform, discrete cosine transform, etc.), wavelet transforms, Hilbert transforms, Haar transforms, distance transforms, etc.

[0045] Exemplary embodiments of the present invention are described with reference to the following drawings, which are not to scale unless otherwise noted. [Brief explanation of the drawings]

[0046] [Figure 1] 1 shows a schematic block diagram of a medical imaging device. [Figure 2] 1 illustrates a contrast agent-based imaging protocol. [Figure 3] 1 illustrates the steps of a facilitation system for facilitating contrast-assisted tomography. [Figure 4] 1 shows a block diagram of a facilitator system using a graphical display generator as contemplated in an embodiment. [Figure 5] 5 shows a schematic block diagram of a graphics display generator of the facilitator system of FIG. 4. [Figure 6] Illustrative examples of graphics displays that can be generated by the system of FIGS. [Figure 7] 10 shows another view of a graphic display according to one optional embodiment. [Figure 8] 1 shows a flowchart of a computer-implemented method for graphical user interface-assisted contrast agent-based imaging. DETAILED DESCRIPTION OF THE INVENTION

[0047] First, reference is made to Fig. 1, which shows a schematic block diagram of a medical imaging device MAR envisaged in an embodiment of the present invention. The device IAR can include a medical imaging device IA (abbreviated as "imager"), preferably of the tomographic X-ray based type. The imager can therefore be a computed tomography (CT) scanner, e.g., a C-arm / U-arm type, but is not excluded here. In the case of other embodiments, other tomography methods, such as MRI, PET, etc., are also not excluded. The medical imaging device is preferably envisaged for contrast-based imaging protocols, such as angiography.

[0048] The arrangement IAR further includes a computing system CS operable generally to process data, including image data, provided by the imager. The computing system also controls the operation of the imager. The computing system may be located remotely from the imaging device IA or may be located near the imaging device IA, such as by being integrated into an operator console CS through which a user can operate the imaging device. Specifically, the computing system may control imaging operations to obtain medical images for diagnostic, therapeutic, planning (e.g., radiation therapy), etc.

[0049] Generally, as described in more detail below, the computing system CS includes a facilitator system FS that can be used to establish the appropriate timing for triggering imaging operations to ensure good quality (contrast-rich) images are obtained. Additionally or alternatively, the facilitator system FS supports user input UI functionality that allows a clinical user to adjust, fine-tune, or even define from scratch a contrast bolus monitoring region ("m-ROI") that monitors contrast accumulation to accurately establish the timing for triggering imaging operations relative to the target anatomical feature TAF. The computing system CS, and in particular its facilitator system FS, can be implemented as a cloud solution running on one or more servers. The imaging device 1A can be installed in a clinical facility, such as a hospital. The computing system may be installed or used in a control room adjacent to the imaging room in which the imaging device IA is located. In some embodiments, the computing system may be integrated into the imaging device IA. The imager IA may be communicatively coupled to a computing system CS via a wired or wireless (or partly both) communication channel CC. The computing system CS may be configured as a fixed computing system such as a desktop computer or as a said server, or as a mobile device such as a laptop, smartphone, tablet, etc. For example, the computing system CS may be located on a workstation WS associated with the imager IA.

[0050] Before describing the operation of the Facilitator System FS in more detail, we first refer to the components of the Imager IA that are the subject of the following description related to the Facilitator System FS.

[0051] The imaging device IA operates to generate, in particular acquire, projection data λ, which are transferred via a communication channel to a computing system CS and reconstructed into tomographic (cross-sectional) images. The computing system CS executes one or more reconstruction units RECON, which implement one or more reconstruction algorithms. In general, a reconstruction algorithm implements a mapping of the projection data λ in a projection domain to an image domain. The image domain is a part of 3D space and is located in an examination area ER of the imaging device, while the projection domain is 2D and is located in an (X-ray) detector XD of the imaging device IA.

[0052] As mentioned above, the imaging device IA is preferably of the tomographic type and is preferably configured for multidirectional projection image acquisition. The imaging device IA is therefore able to acquire projection images λ along different projection directions α relative to the examination region ER and thus the anatomical region of interest (“ROI”) of the patient. In an embodiment, the acquisition is performed by a rotation system in which at least the X-ray source XS is arranged in a movable gantry MG.

[0053] The movable gantry (and in embodiments the associated X-ray source XS) is rotatable within the fixed gantry SG around the examination region ER, in which the patient / ROI is present during imaging. Opposite the X-ray source in the movable gantry is an X-ray detector XD, which rotates together with the gantry and X-ray source around the examination region ER to achieve different projection directions α.

[0054] As shown schematically in FIG. 1 , the patient's longitudinal axis or imaging axis Z may extend into the examination region ER during imaging. The patient PAT may rest on a patient support PS, such as a bed, that is positioned at least partially within the examination region ER during imaging. In some, but not all, embodiments, helical imaging protocols are contemplated herein where there is relative lateral movement along the longitudinal axis Z between the x-ray source XS and the patient PAT. For example, the patient support PS may be advanced through the examination region ER during multi-directional projection image acquisition, e.g., to rotate the x-ray source XS around the patient.

[0055] The CT scanner configuration shown in FIG. 1 is merely one embodiment, and other tomographic imaging equipment, such as C-arm or U-arm scanners, cone-beam CT devices, mammography imaging devices, etc., are not excluded herein. In some embodiments, a C-arm cone-beam imaging device is preferred. Furthermore, multidirectional acquisition capabilities are not necessarily obtained from a rotational system such as that shown in FIG. 1. Non-rotational imaging systems are also contemplated, such as fourth- or fifth-generation CT scanners, in which multiple X-ray sources are arranged around the examination region, e.g., in a source ring. Additionally, or alternatively, detectors XD may be arranged as a detector ring around the examination region. Thus, in such systems, rotation of the X-ray source XS and / or detectors XD does not occur.

[0056] There may be an operator console OC that allows a user, such as a medical professional, to control the imaging operations. For example, the user may request the start of image acquisition, request reconstruction or other operations, initiate transmission of data to the computing system CS, and stop such transmission if necessary.

[0057] During imaging, an X-ray beam XB is emitted from the focal spot of the X-ray source XS along various projection directions α. The beam XB passes through the examination region where the patient is located. The X-rays interact with the patient's tissue. As a result of this interaction, the X-ray beam XB is modified. Generally, such modifications of the X-ray beam XB include attenuation and scattering of the original incident X-ray beam. The modified X-rays are detected as a spatial distribution of various intensities at the X-ray sensitive pixels of the detector XD.

[0058] Here, it is not necessary to acquire the projection image λ over the entire 360-degree angular range around the examination region ER. Acquisition over a partial angular range, such as 270 degrees, 180 degrees, or even less, may be sufficient. The X-ray detector is preferably configured to acquire 2D projection images with rows and columns of intensity values ​​registered by the detector pixels. That is, the detector pixels themselves may be arranged in a matrix layout. Such 2D layouts can be used with diverging imaging geometries, such as cone beams or fan beams. However, one-dimensional detector pixel layouts (e.g., along a single line) are not excluded here, nor are parallel beam geometries excluded.

[0059] The reconstructor RECON implements one or more reconstruction algorithms for processing the projection images. Specifically, the reconstructor RECON can calculate cross-sectional images V of the examination region (including the patient) for diagnostic, therapeutic, or other purposes. The reconstructor RECON may be capable of generating cross-sectional volumetric image data ("image volume") V. However, this does not preclude generating a single image slice of the examination region, if desired. Thus, a reconstructed image may be referred to herein as V, which may include the entire volume, a partial volume, or a specific section thereof. Volume reconstruction may be facilitated by a 2D layout and / or spiral motion of the X-ray detector XD. The scan box SB may be defined by the user, particularly using user input UI features supported by the facilitator system FS. The scan box CB is a portion of space within the image region. Therefore, it is referred to as a scan box because it is a 3D object but can be visualized as a rectangle in a 2D view. The scan box defines the volume that is scanned to acquire projection data for reconstructing the volume of space defined by the scan box. The scan box generally includes a region of interest (m)—ROI, a target anatomical feature (TAF), and optionally one or more anatomical landmarks (LM).

[0060] The reconstructed volume image V is stored in memory MEM or otherwise processed as needed. The reconstructed volume image V may be visualized by a visualizer VIZ, which may generate a graphics display of the volume or identified slices. The graphics display is displayed on a display device DD. The visualizer VIZ may map part or all of the image volume V to a gray value or color palette. The visualizer VIZ controls a video circuit via an appropriate interface to generate the graphics display on the display device DD. In addition to or instead of displaying, the reconstructed image V may also be saved in memory for later review or further processing. Such memory may include an image repository, such as a database (e.g., a PACS), or other (preferably) non-volatile data storage structure.

[0061] The reconstructed volumetric image V can be manipulated, for example by reformatting, to define different planes than those defined by the image geometry. Such reformatting allows the medical user to better identify tissue types and anatomical details within the patient, depending on the medical goal at hand, such as diagnosis or preparation for some kind of treatment.

[0062] Such a reconstructed volume V may be referred to herein as a target image acquired during the target or operational phase of a contrast-assisted imaging procedure. This reconstructed image V is envisioned as a diagnostic image representing the target anatomical feature TAF (e.g., target anatomy, organ, part of an organ, group of organs, different tissue types, etc.) displayed with sufficient contrast to safely inform a treatment or diagnostic decision, or other medical decision such as possibly performing further imaging sessions using other imaging modalities, or other tasks (e.g., tests) that need to be performed in light of the image.

[0063] The (target) projection image λ from which the target volume V is reconstructed is acquired at a sufficient dose by appropriately controlling the dose used via the operator console OC. This can be achieved by controlling the voltage and / or tube amperage settings of the X-ray source XS to ensure consistent diagnostic image quality. As previously mentioned, the imaging protocol envisioned herein is preferably contrast-based to ensure sufficient contrast imaging of the target anatomical feature TAF, which may be inherently less radiopaque. Such a target projection image acquired at a sufficiently high dose may also be referred to herein as a diagnostic projection image λ to adhere to established terminology. However, this naming convention does not preclude this projection data λ and its reconstruction V from being used for non-diagnostic tasks, such as treatment (e.g., catheterization lab), planning, or other tasks.

[0064] The target anatomical feature TAF is related to the medical purpose of the imaging. So if a patient's liver needs to be examined, the target anatomical feature for TAF is the liver. That is, the purpose and target of the abdominal scan is the liver.

[0065] Each target anatomical feature TAF is typically associated with an imaging protocol, a set of specifications that prescribes certain preferred imaging settings, the required image contrast to be achieved, the radiation dose to be used for the target anatomical feature TAF for a given purpose, the source X voltage / amperage settings to be used, collimation, etc., preferably in terms of the patient's biological characteristics (age, weight, sex, height, BMI, medical records, etc.). In other words, an imaging protocol encapsulates medical knowledge about a particular imaging task, objectives, target anatomical feature TAF, etc.

[0066] Prior to acquiring such a diagnostic projection image λ, and for such a low-radiopacity anatomical feature TAF, a quantity of contrast agent CA, such as iodine or another suitable substance, is administered to the patient's PAT via an administration device ADA (e.g., a pump). This quantity of contrast agent CA (sometimes called a "bolus") propagates through the patient's body with the bloodstream and accumulates at the target anatomical feature TAF. Ideally, a diagnostic projection image of diagnostic quality should be acquired only when sufficient contrast agent CA has accumulated at the target anatomical feature TAF. Therefore, the timing of the acquisition of the diagnostic projection image λ of the target image V by the imaging device IA is an important consideration, as it must ensure sufficient contrast agent concentration at the target anatomical feature. Only then can the reconstructable image region target volume V be expected to have the required IQ (image quality) according to the protocol or otherwise specified image contrast. If not, repeat imaging may be necessary, but repeat imaging should be avoided due to cost, time wastage, increased radiation dose, and mechanical wear (especially on the anode disk of the XS tube). Therefore, the consideration here is to get the timing of diagnostic acquisition "right the first time."

[0067] The facilitator system FS envisioned here facilitates such acquisition at the appropriate time in contrast-assisted imaging protocols. The facilitator FS ensures that the acquisition of diagnostic projection images is reproducibly and reliably triggered at the appropriate time when sufficient contrast has actually accumulated in the target anatomical feature TAF.

[0068] The facilitator system operates in two phases: a search or preparation phase (PP) and a monitoring phase. Both of these phases precede a target phase, in which a target volume (V) is acquired. Before all such phases, an initial phase is performed, in which an initial view image (V0) is acquired. This initial image (V0) is preferably a 3D (image domain) survey volume, itself reconstructed from a first set of projection images. However, this first / initial set of projection images (λ0) is acquired with lower image quality than the projection images (λ) acquired later in the target phase and used to reconstruct the target image (V). In particular, acquiring (λ0) results in lower radiation exposure compared to the radiation dose incurred later in the diagnostic scan to acquire the diagnostic projection images (λ). This is both to conserve patient PAT dose and because the 3D survey volume (V0) serves an entirely different purpose than the target volume (V). The purpose of the survey volume / image (V0) is essentially one of navigation, as explained in detail herein. That is, the Surview image V0 is used to find the appropriate location for monitoring bolus arrival and ensure that imaging of the target anatomical feature TAF begins at the appropriate time and that the target volume V has the expected diagnostic-grade contrast.

[0069] The contrast-assisted imaging protocol is shown schematically in Figure 2 Next, with reference to Figure 2 , the operation of the facilitator system FS will be described in detail.

[0070] As previously mentioned, the contrast agent CA enhances the image contrast of the target structure TAF, which has low inherent radiopacity. In this regard, more specifically, reference is made to Figure 2, which is a schematic diagram illustrating a portion of a blood vessel into which a bolus CA is administered by a contrast agent administration device ADA or other device at an access point (indicated by an "X").

[0071] Target vessels in cardiac imaging, such as cardiac arteries and veins, are soft tissues with low radiopacity. Therefore, they appear with low contrast when using non-contrast scans. The contrast agent CA volume moves with the blood flow and propagates through the bloodstream until its concentration accumulates in the target feature TAF, at which point the target phase can begin, where a projection image of the target volume V is acquired with higher image quality.

[0072] Preferably, the target anatomical feature is upstream of the TAF (the blood flow direction is the vector shown in Figure 2). In the initial survey image (shown in TIFF2026500750000002.tif1310), a monitoring region m-ROI is defined by an image neighborhood U, as explained in more detail below. This neighborhood U is based on a 3D segmentation m0 in the initial survey image V0. The neighborhood U and the segmentation m0 may be relative to anatomical landmarks (e.g., aortic arch, descending portion of aorta, etc.) where contrast concentration monitoring is performed. That is, although the precise and specific location within the identified volume is provided by the facilitator FS, the monitoring region m-ROI may initially be defined in terms of anatomical landmarks according to medical knowledge.

[0073] Therefore, for example, to take into account the latency of image acquisition, it is preferable to monitor the concentration of the contrast agent CA upstream of the actual target anatomical feature TAF. When the concentration monitored in the monitoring region m-ROI reaches a certain minimum concentration that can be measured by setting a threshold in the time series (t) of tracker images r(t) (explained in more detail below), it can be estimated that by that time, thanks to blood flow, the concentration of the target anatomical feature TAF has reached an acceptable minimum concentration, and therefore acquisition of the current diagnostic projection data λ for the target volume V may be initiated.

[0074] The spatial distance between the monitoring region m-ROI and the actual target anatomical feature TAF is primarily based on clinical knowledge and / or determined by patient characteristics, knowledge of blood flow velocity, etc. All such medical context information, including the landmark m-ROI-TAF distance used to monitor the m-ROI region, etc., is encoded in the aforementioned imaging protocol / specification, tailored to the current imaging task / purpose.

[0075] Generally, the Facilitator System FS can include a Surveillance Region Finder MRF configured to quickly, and as previously described, reliably, reproducibly, and accurately find the correct surveillance region m = m - ROI for a given patient and target anatomical feature TAF within the survey volume V. Preferably, operation of the Facilitator System FS is suitably integrated into an existing CT workflow.

[0076] The supervised region finder MRF can be implemented as a segmenter SEG, for example, based on a machine learning ("ML") model M. Examples of such models M include artificial neural networks, particularly convolutional ones. CNNs capable of multi-scale processing, such as the U-net architecture, can be used. Other machine learning models can also be used. Instead of ML, more classical segmentation techniques, such as region growing or shape model-based segmentation, can also be used.

[0077] While the monitoring region finder MRF of the facilitator system FS can operate fully automatically and provide the monitoring region m-ROI without further / any user input (other than the identification of the imaging protocol or the target anatomical feature TAF), it is specifically envisioned herein that the facilitator FS includes a user interface function UI that enables user interaction with the estimated m-ROI location m0. Specifically, the facilitator FS prompts the user for interaction. It is specifically provided herein that certain components of the monitoring region finding procedure can be freely adjusted by the clinical user through a user interface UI, such as a graphical user interface (GUI) specifically configured for such user interaction. Such user requests for m0 adjustments may be passed to the bolus monitoring system MS (see Figure 3 below) via a touch screen TS, a pointer tool (computer mouse CM, stylus STY), or the like. Such user interaction is preferably envisioned herein as a dynamic, real-time experience. That is, depending on the adjustments requested by the user regarding the discovered monitoring region m-ROI, recalculation of the associated components may be triggered and their display updated as many times as the user requests such changes or adjustments.

[0078] In this way, the facilitator system FS, in particular thanks to its user interface function UI, is able to find the appropriate monitoring area, thereby facilitating finding the right moment t=t0 to start the targeting phase and control the imaging device IA to ensure the acquisition of high-quality projection images λ from which the target volume V can be reconstructed.

[0079] Before going into the details of the operation of the user functional UI, please refer first to Figure 3. This figure shows the basic operational aspects of the proposed facilitator system FS in association with the (optional) monitoring region finder MRF in conjunction with the bolus monitoring system MS, which is part of the computing system CS. Specifically, as shown in A), the initial 3D survey volume V0 is segmented to one or more suitable anatomical landmarks that serve as the bolus monitoring region m—ROI.

[0080] Based on the estimated m-ROI segmentation m0, a reference position z0 within the volume is identified, which can be, for example, a set position along the rotation / imaging axis Z of the imager IA. Preferably, a reference point P, such as a centroid, is defined within the 3D segmentation sub-volume m0. Point P can be projected onto the Z axis to define the reference position z0.

[0081] Then, from each set of low-dose projection images acquired at an appropriate sampling interval around the reference position z, a time series of tracker images r t will be reconstructed.

[0082] In some or each of these tracker images r(t), a monitoring neighborhood U (shown as a small circle) B) is automatically defined based on the reference point P. The neighborhood U around P can be an ellipsoid, a sphere, etc. (or an elliptical circle in a 2D view, etc.). Thanks to the proposed user interactivity, the event handler EH can be used to allow the user to modify one or more of P, z0, or U as needed. Thus, it can be seen that the monitoring region m—ROI—is defined by two elements: its location in 3D identified by the reference position z0, and the spatial range of the monitoring purpose (defined by the neighborhood U) represented in the tracker image r(t). When at least one of the elements P, z0, or U is modified, one or more of the other elements are automatically modified accordingly.

[0083] In a series of tracker images r(t), the concentration of contrast agent arriving after the bolus injection is monitored at a set monitoring location m—a neighborhood defining the ROI. For example, the contrast curve c in a given tracker image and image neighborhood U (C) U (t) is shown. In such a curve, the contrast value HU (Hounsfield units) of a neighborhood U is recorded over time t. The CA concentration, i.e., the contrast agent, is expected to increase over time in the ramp-up phase, then plateau and reach saturation in the plateau phase, and then decrease in the drop-up phase as the contrast agent is washed out. Only the ramp-up phase is shown in Figure 3.

[0084] A thresholding policy based on image values ​​can be used to trigger an acquisition signal for acquiring diagnostic projection images from which the target volume V can be reconstructed during monitoring in the vicinity U. This acquisition of λ should be initiated after the contrast agent concentration (or HU value of the contrast enhancement curve c) reaches a certain minimum value. This minimum value may be lower than the expected maximum value in the target anatomical feature TFA, which is expected to be located slightly downstream of the monitored region m-ROI / U. Instead of basing the above thresholding on monitoring absolute HU values, the gradient of HU values ​​can also be monitored instead or, if necessary, in addition.

[0085] However, in some embodiments where delay is not an issue, the monitored region and the target anatomical feature may coincide, in which case thresholding can be performed such that the maximum density value of the plateau phase triggers acquisition of a diagnostic projection image, which can be found, for example, using a gradient-based method.

[0086] The set of projection images acquired at a set sample rate from which the tracker image is reconstructed will be of similarly lower quality (lower dose) than the projection images λ of the later diagnostic acquisition stage. For example, the image quality may be similar to the quality of the projection images acquired from which the surview image V0 is reconstructed.

[0087] The size (field of view ["FOV"]) of the surview (also called "scout") image volume V0 is preferably selected to include not only the target feature TAF but also at least one of the anatomical landmarks where bolus monitoring is expected to occur. When in doubt, a whole-body scan can be the surview scan, although a whole-body scan is not always necessary, as a scan of an applicable body region, such as an abdominal scan, head scan, chest scan, or leg scan, may be sufficient.

[0088] Although such a survey image V0 typically has very low contrast due to the low dose, it may still be sufficient to roughly locate the m-ROI landmarks and, optionally, the target anatomical feature TAF, which can also be manually marked up by the user (see below).

[0089] Once the reference position z0 is found by the system FS based on the segmentation m0, it may be necessary to adjust the imaging geometry, for example, by moving the patient table relative to the gantry, so that a tracker image around the reference position can be obtained by reconstructing a series of projection images acquired at the aforementioned sampling interval. However, in a preferred embodiment, such repositioning of the table or gantry is not necessary because the distance between the target anatomical feature and the monitoring location is roughly known and the monitoring volume V0 is preferably acquired from the beginning to cover a sufficiently large volume. For example, the FOV of the survey scout volume V0 may be linked to automatic planning, so a very large FOV survey is generally not required to collect anatomical context information, such as landmark detection. Such automatic planning is a function that can detect the target anatomical feature TAF in the survey image V0 and define the FOV to be used. The automatic planning function can be implemented by appropriate image processing (e.g., segmentation) if necessary. However, the detection and knowledge of the TAF location can be provided manually by the user or by any method, whether machine learning-based or not. In general, it is assumed herein that the location of the target anatomical feature TAF is known, and the primary focus of this disclosure is to reliably identify the region of interest m-ROI.

[0090] m—ROI segmentation m0 is a 3D segmentation, i.e., defined by a 3D subvolume in the survey image (m0 ⊂ V0). This subvolume, with its spatial extension in all three spatial directions (X, Y, Z), is preferably anatomically aware, in that its shape, size, and orientation correspond to and specifically match the spatial structure of the anatomical structure at its location. For example, segmentation m0 may conform to the spatial structure of anatomical landmarks associated with the target anatomical structure. Thus, the segmentation follows, at least in part, the anatomical / tissue boundaries of the landmarks. This allows the user to quickly visually verify, at a glance, whether the segmentation m0 proposed by the Surveillance Region Finder MRF is medically meaningful.

[0091] Typically, a relatively small segmented anatomical structure m0 is used to define a reference position Z0 and, separately, a neighborhood U in the tracker slice image that passes through said reference position Z0. As mentioned above, the reference position z0 can be located on the imaging axis Z. However, this is not necessary, as the initial survey volume V0 can also be provided as a reformatted volume, and the reference position z0 can be a point on any geometric line of the reformatted volume and therefore can be different from the rotation / imaging axis Z.

[0092] It is noteworthy that the initial locator-tracker image r0 can be synthesized from the survey volume V0 purely computationally, eliminating the need for separate projection data acquisition and saving dose. Specifically, the neighborhood U to be used in the "live" tracker image for live monitoring of bolus arrival can be defined on this proto-tracker image synthesized from the already available survey 3D image V0. No dose expense is required to determine the neighborhood U, which represents the spatial extension of the monitored region m—the ROI—representable in the tracker image. Furthermore, the determination of the reference position and neighborhood U can be performed in a single step based solely on the survey image V0 and the synthesized locator-tracker image r0. This is more convenient and faster for clinical users, and this single-step operation can be easily integrated into existing CT workflows practiced in medical facilities worldwide. It will be understood that the use of the locator-tracker image r0 is independent of its display, and that such a display is not required in all embodiments for the purpose of defining the neighborhood U described in the single-step setup.

[0093] It will be understood that the above-mentioned Surveillance Region Finder MRF is merely an optional component of the Facilitator System FS as contemplated herein. In fact, the initial representation of the surveillance region m0 can be provided entirely manually as a segmentation of the surveillance volume V0. It does not necessarily have to come from a Surveillance Region Finder MRF or other similar automated computer system. In fact, it is the user who provides the manual annotations, and may later change their mind, or another clinical user may provide instructions for the location of the surveillance region, etc.

[0094] However, the present invention contemplates that the facilitator system FS includes a graphics display generator GDG, as shown schematically in the block diagram of Figure 4. The graphics display generator GDG is operable to generate a graphics display GD on a display device DD. The graphics display GD includes a visualization of at least a portion of a segment s of the vessel of interest, such as the aorta, and a graphics representation SL of the current location of the monitored region. This may be provided through a user or by a computerized automated system such as a monitored region finder MRF.

[0095] The Graphics Display Generator GDG interactively assists the (clinical) user in finding the correct monitoring region by changing the position of the Graphics Display SL. The Graphics Display Generator GDG allows the user to change the current position of the monitoring region graphical indicator SL through the supported user interface UI. The Graphical Display SL is "anatomy aware" and dynamically adjusts to fit the current anatomical environment according to the segmented vessels. Optionally, additional useful context information (such as landmarks, associated distances, expected bolus arrival time, etc.) is displayed corresponding to the current position of the Graphical Display SL. This is described in more detail below.

[0096] The graphics display generator, the display device DD including the visualization of the graphics display GD, and the user input device UI interact to form the preferred interactive graphical user interface GUI of the present invention. As shown in FIG. 4, the graphics display generator GDG receives as input a 3D survey volume including a segmentation s(VS) of the vessel of interest VS and a definition D of the location currently marked up as the monitored region. Regardless of how this initial definition D = m0 is obtained, it may include a single 3D coordinate or a set of such coordinates within the 3D segmented survey volume V0, such as one or more of a reference point P, a neighborhood U around P, and an associated z0 location, as shown in FIG. 3. A view of at least a portion of the volume V0 and vessel segmentation s = s(VS) is rendered for display, including a graphical indicator SL displayed to mark up the current location of the monitored region m—ROI—based on the received definition m0 = D. The graphical indicator SL may be rendered as a circle, ellipse, or other markup symbol or region definition. Preferably, the shape and orientation are such that the graphical indicator SL is within the region boundary of the segmentation.

[0097] To further elaborate on vessel segmentation, in some embodiments of the proposed approach, vessels are segmented according to the anatomical structure being scanned (e.g., the aorta for the heart, the liver, or the pulmonary artery for abdominal examinations). This may be specified in the image protocol, as previously described. The segmentation is based on low-dose survey images, rather than the high-dose images used later in diagnostic scans. Displaying vessel segmentation in addition to the bolus ROI (e.g., represented by circles in other geometric diagrams) is particularly helpful in helping users place m-ROIs more confidently in a clinically relevant manner. For example, in some embodiments, this guidance function is facilitated by including additional segmentation of intravascular calcifications in the displayed vessel segmentation. Calcifications are typically areas that one wishes to avoid when placing a bolus m-ROI. Therefore, survey images can be recorded using an imager configured for spectral imaging (e.g., dual-energy), and the images are spectrally processed using material decomposition algorithms for clearer definition of calcified wall regions. The calcified wall portion of a vessel w may appear graphically different from the non-calcified wall portion.

[0098] Reference is now made to the block diagram of Figure 5, which illustrates in more detail the operation of the graphics display generator that is part of the Facilitator FS. Proceeding from left to right, the imaging device operates as described to acquire a low-dose survey 3D volume V0. While in some less preferred embodiments, 2D surveys may also be considered, the technical and clinical advantages of the proposed Facilitator FS come most to the fore in the context of 3D survey images.

[0099] The surview 3D volume V0 may be provided by the imager IA, preferably in an online setting, although subsequent retrieval from an image database is not excluded here.

[0100] The Surveillance Region Finder MRF can provide an initial segmentation m0 of the m-ROI. The Surveillance Region Finder MRF may or may not be integrated into the Facilitator FS, but either case is optional. One possible detection / output from the Surveillance Region Finder MRF could be one or more landmarks LM around which to place the m-ROI circle.

[0101] In fact, the surveillance region finder MRF may be an external system and not functionally connected to the facilitator FS. Of course, the facilitator FS may also interface to the surveillance region finder MRF, such as a hospital information system, via a wireless or wired network connection to form a more extensive image support configuration. The surveillance region finder MRF may be implemented, for example, in a cloud system, and process images generated by the imager IA, which are then segmented on-demand or automatically. The segmented volume V0 may be stored and loaded by the facilitator system FS when needed for display and surveillance region adjustment. In either embodiment, the surveillance region finder MRF may be a segmentation component that utilizes a machine learning model M to segment an initial spatial definition D of the surveillance region within this low-quality (high-noise) 3D volume.

[0102] Optionally, an initial definition of the location of the surveillance regions within the segmentation D = m0(s) = m0 can be manually provided by the user, for example by leaving annotations applied through an appropriate user interface UI. Of course, the surveillance region finder MRF can also be omitted entirely.

[0103] Segmentation of structures of vessels of interest VS within the survey volume VO may be provided by a standalone (vessel) segmentation device SEG, or the segmentation device SEG may be part of the monitored region finder MRF. Even if a monitored region finder MRF is used, the vessel segmentation device SEG remains a standalone component and does not need to be associated with the optional monitored region finder MRF. In some embodiments, the vessel segmentation device SEG is part of a facilitation device system.

[0104] The segmenter SEG that provides the vessel segmentation s(VS) can be based on ML-based (e.g., deep learning), shape model-based (MBS), or other segmentation algorithms such as region growing. In either case, it is configured to address the low SNR of the low-dose survey image to achieve good segmentation. As with the initial segmentation m0 of the initial m-ROI, the vessel segmentation s = s(VS) is a 3D segmentation, forming a subvolume within the survey volume V0. In embodiments, the vessel segmenter SEG can be configured to transfer the contrast segmentation from the spectral CT image to a virtual non-contrast image. ML-based methods can be used. The segmenter SEG can use an ML model M', such as an artificial neural network (NN), particularly a convolutional neural network (CNN). Neural networks or other models configured for multiscale processing can be used, such as NN models with a U-net architecture or other bottleneck-type models that use convolutional operators followed by deconvolutional operators. Examples of such models include the U-net architecture described by O. Ronneberger et al., "U-Net: Convolutional Networks for Biomedical Image Segmentation," available online on the arXiv repository under citation code arXiv:1505.04597 (2015), and its related models. Segmentation SEG can also be used to extract the centerline (CL) and / or radius of a blood vessel (e.g., the aorta) segmentation. This can be performed using existing skeletonization or distance transform methods. The centerline (CL) can be visualized, as described in more detail below.

[0105] Alternatively, such a segmentation tool, SEG, is not used, and instead the user provides a vessel segmentation based on 3D annotations, which can be tedious and time-consuming.

[0106] The vessel VS may represent, for example, all or part of the aorta, however segmented, or it may also represent all or part of any other vessel that is relevant to the medical task at hand and through which the bolus is expected to pass.

[0107] The vessel segmentation s(VS) in the survey volume V0 and the initial definition m0 of the monitoring region position therein are processed by a graphics display generator GDG to generate a graphics display GD that is displayed on a display device DD. The graphics display generator GDG controls the display device DD via an appropriate video circuit interface to display the graphics display GD on the display device DD. The graphics display GD includes a visualization of the segmentation s=s(VS) or a portion thereof, and a visualization of the monitoring region indicator SL within the region of the segmentation s based on the initial position definition m0. This is shown schematically on the right side of Figure 5.

[0108] When the graphics display GD is displayed on the display device DD, a user can request a change of the currently displayed monitoring area according to the graphical indicator widget SL using a user input device UI, such as a keyboard KB, a stylus STY, a computer mouse CM, or other pointer tool. Alternatively, the graphics display generator GDG can support a touch screen TS function as another embodiment of a user interface UI function that can interact with the display device DD to input a request for a change of the currently displayed monitoring area. In some of the aforementioned UI embodiments, such as the pointer tool STY, CM, or the aforementioned touch screen TS function, a user can interact with the indicator widget SL to request a repositioning and / or resizing of the currently identified monitoring area. For this purpose, and preferably herein, the indicator is configured herein as a sliding element SL that can slide along the segmentation s, thereby allowing a user to reposition the currently proposed position of the monitoring area to a more appropriate position based on medical knowledge. It has been found that this type of slide element provides immediate visual feedback and can support a user in quickly achieving a satisfactory monitoring location definition even in time-critical and stressful situations (such as a trauma room or a busy clinical setting with an overwhelming workload, staff shortages, etc.). Furthermore, the slide element allows for fast and intuitive input of such repositioning requests. Accordingly, throughout much of this disclosure, the indicators SL will be referred to herein as slider elements or simply "sliders" SL. The sliders SL may also support reorientation and / or resize requests, as desired, e.g., via click-and-drag actions.However, as described in more detail below, the slider SL is preferably automatically and dynamically resized / reoriented by the graphics display generator GDG, for example, when the slider SL is slid along the segmentation s (such as along the centerline of the segmentation s) or when the user requests a change in the view rendering / reformatting of the volume.

[0109] When such a user request for position adjustment via the user input UI is received by the graphical display generator, the event handler EH captures this adjustment request event and passes it to the graphics display generator GDG. The event may include specifying the nature of the request, such as the next intended position or size of the slider SL. Alternatively, the event may be mapped to such a specification. The graphics display generator GDG processes the event specification and updates the graphics display accordingly. The updated graphics display GDG will now show the new position of the monitored area by changing the position of the SL element along the segmentation. The geometry of the slider element SL may change accordingly when it is rendered to display it in the new position. This is explained in more detail below.

[0110] The user can adjust the slider SL position as many times as desired. Once the user is convinced that a suitable position has been found, the position of the m-ROI indicated by the slider SL can be transmitted via the output interface OUT as the final monitoring position m(s). This final position m(s) is passed to the imaging device, e.g., the operator console OC, via a suitable control interface, which initiates a monitoring phase coordinated by the (bolus) monitoring system MS. During this monitoring phase, based on the position (and extent) of the currently indicated monitoring region m-ROI, the monitoring system MS instructs the imaging device IA to acquire a stream of tracker projection data around this region m-ROI. Coordinated by the monitoring system MS, the tomographic reconstructor RECON reconstructs from the stream of tracker images monitored for changes in voxel values ​​in the monitored region by the intra-image monitoring unit of the monitoring system MS. For example, image values, such as HU values, for each tracker image stream are thresholded. Alternatively, or in combination with thresholding, other monitoring policies can also be used. A change in image values ​​is an indication of the arrival of the bolus. When the monitoring unit of the monitoring system MS determines, based on threshold settings or other applicable monitoring policies, that the bolus has indeed reached the identified position m(s), the monitoring system MS issues a new signal for the imager IA to acquire a new projection data set, this time at a diagnostic dose higher than that used for the Survue scan V0 or tracker image r(t). From the diagnostic projection data, the reconstructor RECON can reconstruct a fully enhanced target volume V. The target volume V is displayed on the display device DD or other display device to assist the user with the clinical goal / purpose of the imaging. The purpose may be one or more of treatment, diagnosis, planning, medical analysis, etc., depending on the clinical situation, or other purposes. The target volume V can then be processed (e.g., analyzed), stored, or sent as needed.

[0111] FIG. 6 is a diagram of a graphics display GD that can be generated by a graphics display generator GDG according to one embodiment.

[0112] The graphics display GD displays a view of the volume V in a 3D rendering (e.g., isosurface) or as a 2D cross-section at a user-selectable cross-sectional plane as shown in Fig. 6, together with a visualization of the segmentation s = s(SV) of the vessel of interest S. In the example shown in Fig. 6, the vessel of interest is a portion of the aorta shown in a sagittal view. As a third visualization component, there is a graphical widget of a slider SL that is rendered as an ellipse, but can be of any shape or size as long as it is within the region / volume marked by the segmentation of the vessel of interest VS.

[0113] The view can be in any plane, not necessarily the sagittal plane as shown in Figure 6. Frontal and lateral views are also considered standard views herein, as are non-standard reformatting in planes different from the standard plane defined by the image domain. When a change of view (reformatted or standard) is requested, the visual elements of the graphics display are adjusted accordingly. For example, the segmented aorta and slider symbol SL are re-rendered with a correct and consistent geometric perspective. The user can request a view change at any convenient time by issuing a request event through the UI. The event handler EH intercepts this and mediates the view change. To this end, the graphics display generator includes a geometric graphical view generator configured to recognize the geometry of the image domain and apply geometric operations of projection geometry to re-render the graphics display into any view, resulting in the re-rendering of visual components including the segmentation and slider SL, as described above.

[0114] The segmentation boundary of the aorta VS is shown with a dashed line, and this rendering is actually assumed. Therefore, it is preferable that the segmentation include a clear visual modulation to represent the wall W of a blood vessel VS, such as the aorta. We found that such a clear visual representation of the blood vessel wall portion W is more helpful to users in placing / positioning the slider element SL of the defined monitoring region. This allows even novice users or users in stressful situations to quickly achieve realistic and clinically meaningful spatial specification of the monitoring region m—ROI. Visual modulation of the wall portion allows for the distinction between calcified and non-calcified blood vessel wall portions, as previously described.

[0115] The graphics display generator GDG may further include fail-safe measures to help the user better position the slider FL for m-ROI identification. This can be achieved by the graphics display generator GDG restricting the apparent movement of the slider SL to one dimension during adjustment, sliding it primarily along the direction of the vessel, which may also include curved portions.

[0116] More specifically, in an embodiment, the slider is fixed to the vessel's path as defined by a tangent to its centerline / curve. Therefore, the slider SL may be slidable / movable only along a tangent to the centerline CL of the vessel segmentation s. The centerline CL is also visualized in the graphics display GD, as shown, for example, by the dotted line in FIG. 6 . Any line style can be used for the centerline and wall W representation of the vessel segmentation s, and the selected dashed and dotted line variations are merely exemplary embodiments herein. Separate visual modulation by color, hue, or gray value coding can be used in addition to or instead of line style modulation to set the centerline apart from the walls W and / or the remaining body of the vessel segmentation.

[0117] Depending on the adjustment request, the slide element SL may be dragged from the position indicated by (1) to the next position (2) and then to (3), as indicated by the arrows associated with the numbers in parentheses in FIG. 6 .

[0118] The slider element SL itself can have any suitable form or shape. Preferably, the shape depends on the rendered view and remains consistent as the view changes. For example, the slider may be rendered as an ellipse, a circle, or some other shape. The shape may change when the user requests a new view, such as from a sagittal to a transverse plane. For example, the shape may be elliptical in a sagittal view, but change to a circle when the user requests a view in the transverse plane. The change of view may also be requested by the user interface UI. For example, manipulating the pointer tool in a predefined way (such as a right-click of the mouse) may cause a pop-up drop-down menu widget to appear, allowing the user to select a new view. This new view is rendered on the display device DD by the graphics display generator GDG.

[0119] The user can also request resizing or reorienting the slider SL using the user interface UI. The size adjustment may be limited by the area defined by the vessel segmentation. In a preferred embodiment, when the user requests sliding the slider element within the segmented region along the centerline SL, the size of the slider SL is automatically adjusted to fit the diameter or width of the segmented region. In other words, the size of the slider element SL of a given geometric shape (e.g., an ellipse) is adapted to a maximum size but remains within the segmented wall W. For example, a circle with a certain diameter is inscribed around the segmented centerline, and that circle is preferably completely inside the segmented vessel region s. Thus, the slider SL always appears to touch the wall portion W of the segmentation s when slid along the centerline SL, but this sliding occurs when the user issues a corresponding position adjustment request through the user input interface UI. To the user, this automatic adaptation of the slider SL to the shape of the vessel segmentation may appear as the slider SL dynamically expanding or contracting as it is dragged through the vessel segmentation at different widths (cross sections).An automatic adaptation of the slider to the vessel segmentation shape is also provided, regardless of whether the slider SL is slid along a curved or straight portion of the segmentation s(VS).

[0120] Sliding of the sliding element along a tangent to the centerline SL may be performed simply by keyboard strokes, as one possible embodiment of the user interface UI contemplated herein. Accordingly, in such an embodiment or a similar embodiment, the user is prompted to press one of two specified keyboard keys to issue a slider SL repositioning event. For example, each key indicates one of two directions of slider SL movement (up or down in one view), as shown in FIG. 6 , which may correspond to left or right in other views. Additionally or alternatively, the user interface may allow the user to increase / decrease the diameter of the bolus ROI circle. For example, this may be achieved in a touchscreen embodiment by the user performing a specific predefined gesture. Alternatively, in a keyboard-based embodiment, the user may press a predefined sequence of keys to request a change in the displayed m-ROI size. For example, the “plus / minus” keys may be appropriately assigned to allow user requests such as m-ROI size changes.

[0121] In some embodiments, adjustments to the position of the slider SL are restricted to occur only in a direction tangential to the center CL of the segmentation. Thus, the slider movement is fixed to the course of the segmentation. Therefore, the graphics display generator GDG is configured in a preferred embodiment to only support repositioning of the monitoring region m-ROI, and therefore of the slider SL along the segmentation. Other repositioning requests may be ignored or translated to keep the slider SL within the bounds of the segmentation. If the initial definition m0 of the current monitoring region m-ROI violates this policy, the initial definition may be automatically corrected so that the slider SL at this initial position is within the segmentation. The user may be notified of this automatic correction.

[0122] Some methods of user interaction supported by the Graphics Display Generator GDG may involve instructions via mechanical input. For example, in a touchscreen interaction TS, the user places a finger at the current location and performs a drag motion on the screen to slide a sliding element. Other examples include a computer mouse CM or stylus STY event indicating a drag operation. In such mechanical user interface configurations, where the user describes a motion via a touchscreen action, stylus, mouse, etc., the registered motion is analyzed by the event handler EH and resolved into components that include a component parallel to the current centerline CL, which is tangent to the current position of the slider SL. The event handler of the Graphics Display Generator GDG projects this parallel component of the requested motion onto the tangent to said centerline. Only this projected parallel component is used to slide the slider SL to the next position. Therefore, the graphics display generator GDG performs motion of the slider SL along the tangent only in proportion to the projected motion component. Thus, by projecting the motion component onto the instantaneous tangent to the centerline SL, the apparent motion of the slider can be restricted to occur only along the centerline, and is therefore fixed to the segmentation.

[0123] As can be seen above, the Graphics Display Generator GDG supports several constraints, such as automatic adaptation of the slider SL size, adapting the shape of its graphical representation to the segmentation width, and a lock function that locks the requested repositioning to the course of the segmentation (e.g., the centerline). These constraints form useful fail-safe measures that can be optionally disabled if necessary, as shown in the current view. The ability to adjust the slider SL size depending on the instantaneous segmentation width and the lock function that forces linear repositioning allows even novice or stressed users to quickly find a realistic bolus monitoring position, thereby reducing the possibility of retests and improving patient throughput, etc.

[0124] However, it will be appreciated that fixing the sliding motion to a tangent to the vessel segmentation is not necessarily required in all embodiments. Furthermore, the graphics display generator GDG may include functionality that allows the user to override one or more constraints to allow more freedom in positioning the sliding element SL, as may be desired.

[0125] As an additional optional feature, the Graphics Display Generator GDG supports the display of useful medical context information in addition to the display of the segmentation s and the slider SL within or around the segmentation s. The mentioned medical context information may be provided by a Medical Context Information Provider MCP. The Medical Context Information Provider MCP may be part of the Facilitator System FS or the Facilitator System FS may be configured to appropriately interface with such a Medical Context Information Provider MCP. The Medical Context Information Provider MCP may include a Landmark Segmenter LMS module or a Physiological Modeling Machine PMM configured to provide distance d and / or transit time information.

[0126] Thus, in some embodiments, as shown in FIG. 6 , the graphics display generator GDG can operate to display medical context information, such as the bolus transit time T and / or the distance d to a particular anatomical landmark LM, ANAj, as a function of the current slider SL position (illustrated as j=1-5). Such medical context information can be usefully and contextually displayed in information popup widgets CL1-CL3. Such widgets (callout-type popups are shown in FIG. 6 ) are generated by the graphics display generator GDG in relation to the changing positions (1), (2), and (3) of the sliding element SL, and the information in popups CL1-CL3 is dynamically updated. The popups CL1, CL2, and CL3 may include information regarding the distance d to various landmarks LM measured from the respective current position ((1), (2), or (3)) of the slider SL and the expected arrival time T of the bolus. In addition to or instead of the information regarding the time T and distance d to the landmark LM, the time T and / or distance d may refer to the target anatomical feature TAF being imaged. Pop-ups are either invoked on user request or automatically when the slider SL is slid along the segmentation. Pop-ups Cl1 to Cl3 may be displayed permanently or with a time limit. If permanent, the user can force its dismissal by issuing a close request, for example by clicking on the popup. If permanently displayed automatically on user request, the time and / or distance information is updated automatically and dynamically.

[0127] Useful landmark LMs, particularly for cardiac applications, include one or more of the aortic valve, coronary ostia, and bifurcation points of the renal and hepatic arteries; any such landmark LM can be included to facilitate better planning. Knowing the 3D locations of such landmarks enables a useful differentiator for 3D survey-based planning: the ability to incorporate the actual 3D distance between the bolus tracking ROI and the associated landmark in the plan.

[0128] Regarding transit time, the physiological modeling machine (PMM) can optionally be configured to implement a hemodynamic model to calculate an estimate of the transit time T to a distance d from a landmark. For example, the distance of the survey volume V0 can be determined based on landmark segmentation provided by the landmark segmentation LMS module. The hemodynamic model may include textbook knowledge of blood flow velocity, patient-specific information such as current heart rate and blood pressure, and a model of the patient's vasculature obtained from 3D surveys. Using transit time, the bolus tracking position can be standardized with respect to time delay, providing information to the technician when repositioning the bolus m-ROI. Therefore, distance and transit time information can be obtained by a medical context information provider to implement such hemodynamic modeling or to perform queries via an appropriate interface database to find such distance and transit time models.

[0129] In an embodiment, the graphics display GD may include visualization of certain aspects of the hemodynamic modeling, such as color-coded streamlines, velocity fields, and pressure fields.

[0130] Popups CL1-3 are particularly effective when used in combination with a locking feature that locks the slider movement to the course of the centerline CL. Locking the slider SL to the centerline in this way avoids the time-consuming user interaction of freely positioning the bolus tracking ROI (typically a circle) and instead provides a guided experience, allowing the user to "slide" the ROI along the centerline. For example, for each location or several possible locations, the distance d to the associated landmark ANAj is displayed in popup CL1-3. This helps standardize bolus tracking, for example, "For coronary artery scans, always place the ROI 10 cm downstream of the left coronary artery ostium." Furthermore, the radius of the bolus tracking ROI can be dynamically adjusted based on the local radius of the aorta VS.

[0131] In addition to displaying such popups, the location of relevant landmarks can also be indicated by indicator widgets (e.g., boxes, circles, or ellipses). Information about the location of landmarks LM may already be segmented within the survey volume v0 upon receipt, or the facilitator system FS may include one or more landmark segmenter modules LMS, as described above, based on ML, MBS, or any other technology, as long as the segmentation modules LMS are appropriately configured to address the low signal-to-noise ratio (SNR) expected for low-dose acquisitions. Furthermore, similar to vessel segmentation, the segmentation of landmarks LM is 3D, and the 3D subset of the survey volume V0 is also 3D. Segmentation of such anatomical landmarks LM can be achieved using ML-based landmark detection techniques, segmentation of blobs around landmarks, or more traditional image processing approaches that consider the geometric and anatomical characteristics of landmarks relative to the aorta or other target vessels, such as MBS shape segmentation techniques.

[0132] Once a suitable placement has been found according to the current position of the slider SL, the user may indicate this by issuing a specific event through the user interface UI, such as pressing a specific key or, in touch screen embodiments, performing a specific gesture, click event, etc. In either case, the extent and current position of the slider SL are taken to be indicative of the monitoring region m—ROI, whose current position / extent (size) is sent via output port OUT to the imaging device and monitoring system MS, which initiates the acquisition of tracker images as described above, facilitating the acquisition of the final full-contrast image V.

[0133] 7 shows a diagram of a second embodiment of the graphics display GD. In addition to the slider element SL, the scan box SB area is indicated by a rectangular area, e.g., dashed, dotted, solid, or other line style. This visualization of the scan box SB is adjusted to the position of the sliding element, as shown in FIG. 2. At a given moment, the scan box, shown by the solid line, is associated with one position of the slider element SL, but when the slider SL is moved, the scan box also moves to the next position, shown by the dashed line.

[0134] One edge of the scan box, e.g., its edge / plane, passes through the currently displayed slider element SL. The edge of the scan box defines a 3D subset within the image domain along the rotation / imaging axis Z direction, from which a tracker projection image r(t) is acquired once a suitable location for the monitored area (indicated by the slider SL) is found. The monitored area is contained within the scan box, preferably at its edge / end. By default, the scan box is selected within the volume to include the TAF and, preferably, one or more landmarks ANAj, according to the applicable scanning protocol. In this way, a graphical representation of the scan box SB, together with the underlying segmentation and the position of the slider SL, allows the user to better evaluate or understand the imaging operation that needs to be performed.

[0135] Therefore, in embodiments herein, it is envisioned that planning of the bolus tracking m-ROI can be combined with synchronization planning of the reconstruction box SB. Since it is usually preferable to start the scan from the bolus tracking position so that there is no need to change the table position before starting the scan, manipulating the ROI position can be combined with defining the upper or lower reconstruction box limit.

[0136] Depending on the selected protocol and target anatomy, the user can use the UI to position the bolus m-ROI slider SL around the centerline CL of the aortic wall W at the top or bottom of the plan box SB. Such placement ideally initiates scans at each start / end position of the target organ TAF, avoiding the table movement required to cover the entire target organ.

[0137] The size of the scan box, its lower and upper bounds, can be estimated by the ML model M used in the Surveillance Region Finder MRF. This model estimates not only m—ROI m0, but also the size of the applicable scan box. Alternatively, the scan box size can be specified in the imaging protocol, obtained from the Graphics Display Generator GDG, and used to render the scan box as shown in Figure 7. Alternatively, the scan box SB can be manually marked out graphically by the user using the user interface UI. As yet another alternative, the vessel segmentation SEG estimates the scan box together with the vessel segmentation s(VS). Image protocol information may be used as context information for this estimation.

[0138] In some embodiments, the action of placing the slider SL in its final position can automatically initiate (through interaction with the monitoring system MS) a scan at each start / end position of the target organ according to the scan box SB, avoiding any movement of the table PS that may be required to cover the entire target organ TAF.

[0139] Thus, in an embodiment, the reconstruction box SB planning can be combined with the adjustment of the bolus tracking position m according to the user interface UI.

[0140] It will be understood from the disclosure herein that Figures 6 and 7 are highly schematic and merely illustrative of embodiments. As such, the specific configurations and renderings of the slider SL, vessel / organ segmentation, centerline CL, wall W, popups CL1-3, etc. are exemplary, and any modifications of these elements are contemplated herein as long as they support the above-described benefits and guiding functions of enabling rapid, consistent, and reproducible accurate placement of the region of interest m-ROI on a (preferably 3D) Surveillance scan.

[0141] Reference is now made to Figure 8, which illustrates a flowchart of a method for facilitating a contrast agent-assisted imaging protocol, particularly in locating and adjusting the location and extent of a monitoring region, based on the graphics display generator and its graphics display described above, although it will be understood that the procedures described below are not necessarily tied to the system described above.

[0142] In step S810, a segmentation s of a target vessel VS within a survey low-dose reconstruction volume V0 is received, along with an initial indication of a monitoring position for the segmentation. The survey low-dose reconstruction volume V0 may also be received.

[0143] In step S820, a segmentation showing the current monitoring position is visualized in a graphics display against the background of a view of the survey volume V. This can be done, for example, as an overlay graphic on the survey image. The current position of the bolus monitoring region may be indicated by a slider graphic element LS having a shape (oval, circle, etc.) matching the width and size of the segmentation of the current position. The slider S GUI widget is preferably placed within the segmentation.

[0144] In step S830, the event handler listens for a user-issued request to change the position of the current monitoring region.

[0145] If such a request is received, the monitoring location is changed accordingly by changing the slider position in step S840.

[0146] Preferably, the user request for a slider position change received in S840 is modified so that the apparent movement of the graphical slide element from its current position on the segmentation to the newly requested position is restricted to movement only along the segmentation. Thus, the repositioning operation is locked in the direction tangent to each of the segmentation centerlines. Thus, the slider moves to a new position along the centerline. Other directional components in the request are transformed (e.g., by projection) to act only along the centerline of the elongated segmentation region / volume of the vessel.

[0147] Optionally, also in step S840, the size (e.g. width) of the shape of the graphical indicator of the monitored area is automatically adjusted to vary according to the width of the segmentation, so that the graphical slider SL always fits within the boundary of the segmentation. Preferably, the size is increased or decreased in response to variations in the segmentation width, so that the slider SL slides along and contacts within the boundary portion of the segmentation rendered in the visualization.

[0148] In step S850, a graphics display is rendered, optionally including one or more additional visualizations, such as a scan box for subsequent tracker images, information regarding bolus arrival / passage and / or distance to landmarks, and a separate graphical representation of the vessel wall (e.g., outline, highlight, etc.).

[0149] Landmark distance and transit / arrival time are relative to the current position of the monitored area according to the sliders set.

[0150] The scan box may be displayed as a graphical indicator such as a rectangle or square. The scan box marks the area domain where projection data is acquired for track image and / or final contrast image acquisition. The scan box volume includes the surveillance area, the target anatomical feature TAF, and optionally one or more landmarks. This scan box visualization is preferably rendered to change as the positional requirements of the surveillance area change. Preferably, the scan box is rendered and positioned such that one of its edges, e.g., one side of the edge of a rectangular representation, passes through the currently indicated position of the slider element.

[0151] The step S850 of rendering the graphics display may further include a dedicated visualization of the vessel boundaries (separate from the visualization of the main segmentation body).

[0152] After one or more requests to change the position of the monitoring location, the appropriate position / size / orientation of the monitoring region m-ROI is established, a corresponding acknowledgement signal is issued in step S860, the coordinates of the currently indicated position of the slider SL are passed to the imaging device to request the acquisition of a low-dose tracker projection image and its reconstruction at that position, and a series of tracker images are generated in step S870 to allow monitoring of changes in image values ​​due to the arrival of a bolus at that position.

[0153] In step S880, the tracker image at the commanded location is monitored for changes in image values ​​that indicate the impending arrival of a bolus.

[0154] Once it is determined in step S870 that a sufficient amount of contrast agent has accumulated such that the contrast agent concentration in the downstream target anatomical feature TAF enters the plateau phase PP, a second signal for projection data acquisition is issued in step S890 to acquire a fully contrast-enhanced diagnostic projection image at a higher dose so that a contrast-enhanced target image volume V can be reconstructed in step S900.

[0155] The segmenter SEG used to compute the (vascular VS) segmentation of the survey image V0 may be ML-based. In an ML approach, an ML model (e.g., a convolutional neural network (CNN)) is trained based on training data. The training data may include a survey input image x. The survey input image x, like other survey images, has very low contrast, and it is not always possible for a human expert to reliably annotate the ground truth m-ROI. In such situations, the training data generation system can operate to generate training data (x, y) pairs based on noise simulation as follows: A set of existing, historical 3D diagnostic images (spectral or non-spectral) of the body part of interest on which the model is trained is localized to a database query in a medical database, such as a PACS. These diagnostic images allow clinical experts to easily create annotations to define the location and extent of the m-ROI. Next, the high IQ (image quality) of the diagnostic images used for annotation is artificially reduced by simulating noise and adding this noise to the diagnostic images to simulate low-dose effects in the survey images and obtain artificially generated samples that fairly accurately represent the instances in the survey volume. Thus, the noise-corrupted 3D image samples serve as training inputs x, and the annotations from the high-quality images serve as the associated ground truth y. The training data generation system therefore includes a noise simulator and a noise adder, which, as mentioned above, can generate as many training data pairs as needed. However, as mentioned above, the facilitator system FS can be used with any segmenter system, whether ML-based or not.

[0156] The components of the Facilitator System FS are implemented as one or more software modules and run on one or more general purpose processing units PU, such as workstations associated with an imager IA, or on a server computer associated with a group of imagers.

[0157] Alternatively, some or all components of the facilitator system FS may be implemented in hardware integrated into the imaging system IA as a suitably programmed microcontroller or microprocessor, such as an FPGA (Field Programmable Gate Array), or as a hardwired IC chip, application specific integrated circuit (ASIC). In yet another embodiment, the facilitator system FS may be implemented partly in software and partly in hardware.

[0158] The various components of the Facilitator System FS may be implemented on a single data processing unit PU, or several or several components may be implemented on different processing units PU, located remotely in a distributed architecture and connectable to a suitable communication network, such as in a cloud or client-server configuration.

[0159] One or more features described herein may be configured or implemented as or using circuitry encoded in a computer-readable medium and / or combinations thereof, including discrete and / or integrated circuits, systems-on-chips (SOCs), and combinations thereof, machines, computer systems, processors and memories, computer programs, etc.

[0160] In another exemplary embodiment of the invention, a computer program or a computer program element is provided, characterized in that it is configured to perform, on a suitable system, the method steps of the method according to one of the previous embodiments.

[0161] Thus, the computer program element may be stored in a computing unit which may be part of an embodiment of the present invention. This computing unit may be configured to perform or direct the execution of the steps of the above-mentioned method. Furthermore, the computing unit may be configured to operate each component of the above-mentioned device. The computing unit may be configured to operate automatically and / or to execute a user's order. The computer program may be loaded into the working memory of a data processor. The data processor may thus be equipped to perform the method of the present invention.

[0162] This exemplary embodiment of the present invention encompasses both computer programs that use the present invention from the beginning, and computer programs that, through updates, turn existing programs into programs that use the present invention.

[0163] Furthermore, the computer program element may be capable of providing all the steps required to fulfill the procedures of the exemplary embodiments of the methods described above.

[0164] According to a further exemplary embodiment of the present invention, a computer readable medium, such as a CD-ROM, is presented, the computer readable medium having stored thereon a computer program element, the computer program element being as described in the preceding section.

[0165] The computer program may be stored and / or distributed on a suitable medium (particularly, but not necessarily, a non-transitory 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 telecommunications systems.

[0166] However, the computer program may also be presented over a network such as the World Wide Web and can be downloaded into the working memory of a data processor from such a network. According to a further exemplary embodiment of the present invention, a medium for making a computer program element available for downloading is provided, the computer program element being configured to perform a method according to one of the aforementioned embodiments of the present invention.

[0167] It should be noted that the embodiments of the present invention are described with reference to different subject matters. In particular, some embodiments are described with reference to method-type claims, and other embodiments are described with reference to apparatus-type claims. However, those skilled in the art will understand from the above and below description that, unless otherwise specified, any combination of features belonging to one type of subject matter, as well as any combination between features relating to different subject matters, is considered to be disclosed in the present application. However, all features can be combined to provide a synergistic effect greater than the simple sum of the features.

[0168] While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered exemplary or explanatory 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 dependent claims.

[0169] In the claims, the word "comprise" 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 referred to in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be interpreted as limiting the scope. Such reference signs may consist of numbers, letters or alphanumeric combinations.

Claims

1. 1. A system for facilitating tomographic imaging using a contrast agent, the system comprising: an input interface for receiving a 3D survey image volume of at least a portion of a patient, acquired by a tomography apparatus in a preparatory stage prior to a contrast agent-assisted imaging stage, said 3D survey image volume including segmentations for blood vessels through which a contrast agent will pass in a subsequent contrast agent-assisted imaging stage; a graphics display generator configured to generate a graphics display of a graphical user interface for display on a display device, said graphics display including a visualization of said segmentation and a visualization of a slider element indicating a reference position along said segmentation, said reference position suitable for monitoring for a presence of contrast agent relative to at least one target anatomical feature in said subsequent contrast agent-assisted imaging stage; an event handler configured to, upon receiving user input, instruct the graphics display generator to update the graphics display such that the slider element slides along the segmentation, the slider indicating one or more different reference positions; and A system having:

2. The system of claim 1 , wherein the graphics display generator is operable to adapt the spatial extent of the slider element to correspond to and vary accordingly with geometric aspects of the segmentation at the different reference positions.

3. 3. A system according to any preceding claim, wherein the graphics display generator is operable to lock the slider element in a direction defined by the segmentation.

4. The system of claim 3 , wherein the direction is along a centerline of the segmentation.

5. The system of claim 1 , wherein the visualization of the segmentation is configured to clearly represent wall portions of the blood vessel.

6. 6. The system of claim 1, wherein the graphics display generator is operable to include in the graphics display information regarding i) the distance of the at least one target anatomical feature, a) to a reference position of the blood vessel corresponding to the current slider position, and / or b) to one or more anatomical landmarks, and / or ii) an estimated time of arrival of contrast agent at the reference position.

7. 7. The system of claim 1, further comprising an output interface for providing the imaging device with one of one or more reference positions selected by a user to define one end of a subset within an image area from which projection data is collected by the imaging device during the imaging stage.

8. 8. The system of claim 1, wherein the graphics display generator is operable to generate a graphics display further comprising a visualization of the subset, and wherein the slider element is positioned at one end of the visualization of the subset.

9. 9. The system of claim 1, further comprising an output interface for passing a user-selected one of the one or more reference positions to instruct the imaging device to acquire a first set of projection data while a contrast agent propagates within a patient, and a reconstructor for reconstructing, based on the projection data, a cross-sectional tracker image with a first image quality in a plane passing through the selected reference position.

10. The system of claim 6 , wherein the arrival time is based on hemodynamic modeling.

11. The system of claim 1 , wherein the blood vessel comprises at least a portion of an aorta.

12. 1. A method for facilitating tomography using a contrast agent, comprising: receiving a 3D survey image volume of at least a portion of a patient acquired by a tomography apparatus in a preparatory stage prior to a contrast agent-assisted imaging stage, said 3D survey image volume including segmentations for blood vessels through which a contrast agent will pass in a subsequent contrast agent-assisted imaging stage; generating a graphics representation of a graphical user interface for display on a display device, said graphics representation including a visualization of said segmentation and a visualization of a slider element indicating a reference position along said segmentation, said reference position suitable for monitoring for the presence of contrast agent relative to at least one target anatomical feature during said subsequent contrast agent-assisted imaging stage; instructing the graphics display generator to update the graphics display such that the slider element slides along the segmentation upon receiving user input, the slider indicating one or more different reference positions; A method comprising:

13. 12. An imaging arrangement comprising the system of any one of claims 1 to 11 and one or more of the imaging device, the display device, a contrast agent administration device for administering a contrast agent, a segmenter configured to provide the segmentation, and a bolus monitoring system.

14. A computer program element configured, when executed by at least one processing unit, to cause the processing unit to perform the method of claim 12.

15. At least one computer readable medium storing a program element according to claim 14.

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