Computed tomography simulator for estimating dose and image quality

Abstract

A computer-implemented method for simulating a computed tomography (CT) system is disclosed. The method includes receiving, via a user interface, a selected scanning protocol and one or more characteristics of a patient or group of patients. Using a CT simulator, deterministic parameter settings for scanning the patient or the group of patients are determined. The method further includes determining a projected image quality measure and a dose using the CT simulator, and generating a customized scanning protocol for the patient or the group of patients based on the projected image quality measure and the dose.

Description

Technical Field

[0001] The embodiments of the subject matter disclosed herein relate to computed tomography (CT) imaging systems, and more specifically, to analog imaging protocols. Background Technology

[0002] In a computed tomography (CT) imaging system, an electron beam generated by a cathode is directed at a target within an X-ray tube. The fan-shaped or cone-shaped X-ray beam, produced by the collision of electrons with the target, is then directed at the subject, such as a patient. After being attenuated by the object, the X-rays strike an array of radiation detector elements. An electrical signal is generated at each detector element, and this signal is transmitted to a data processing system for analysis, ultimately producing an image.

[0003] During a scan to acquire projection data, it is generally desirable to reduce the X-ray dose received by the patient and improve image quality. Within a CT protocol, there can be many scan settings that influence the trade-off between dose and image quality. The scan settings established by the CT protocol may not produce images of the desired quality, thus the CT system operator can adjust one or more scan settings of the protocol to improve image quality or reduce dose. However, determining the optimal combination of scan settings to achieve the desired quality / dose balance can be difficult. Therefore, various diagnostic scans may be performed on the patient to achieve the desired image, thereby increasing the patient's radiation exposure.

[0004] Additionally, CT users (e.g., medical physicists) use phantom scans to optimize and validate the clinical efficacy of protocols. This can be a cumbersome and time-consuming process, especially for sites with numerous protocols. Furthermore, many sites may only have one or two phantoms that do not span the entire anatomical region, clinical setting, or patient body size. Summary of the Invention

[0005] This disclosure relates to a simulated computed tomography (CT) system and method for optimizing a scan protocol. The method involves receiving a selected scan protocol and one or more characteristics of a patient or patient group via a user interface. Using a CT simulator, deterministic parameter settings for scanning the patient or patient group are determined. The CT simulator then calculates projected image quality and dose based on these parameter settings. A customized scan protocol is generated for the patient or patient group based on the projected image quality and dose. The system includes: a user interface for receiving the scan protocol and patient characteristics; a CT simulator for determining the parameter settings and projecting image quality and dose; a display device for displaying the projected image quality and dose; and a memory for storing the customized scan protocol. The system can be remotely operated from a CT imaging system and can extract patient characteristics from localization scans. The user interface allows for verification and adjustment of parameter settings to ensure that the customized scan protocol meets desired criteria.

[0006] The above-described advantages, as well as other advantages and features, of this specification will become apparent from the following detailed description when considered alone or in conjunction with the accompanying drawings. It should be understood that the above summary is provided to present a series of concepts further described in the detailed description in a simplified form. This is not intended to identify key or essential features of the claimed subject matter, the scope of which is uniquely defined by the claims following the detailed description. Furthermore, the claimed subject matter is not limited to specific implementations that address any shortcomings pointed out above or in any part of this disclosure. Attached Figure Description

[0007] A better understanding of the various aspects of this disclosure can be achieved by reading the following detailed description and referring to the accompanying drawings, in which:

[0008] Figure 1 A drawing view of a simulated computed tomography (CT) imaging system according to one or more embodiments of the present disclosure is shown;

[0009] Figure 2 A more detailed schematic block diagram of an example simulated CT imaging system according to one or more embodiments of the present disclosure is shown;

[0010] Figure 3 This is a flowchart illustrating a method for simulating a diagnostic scan to be performed using a CT imaging system, according to an embodiment of the present disclosure;

[0011] Figure 4 This is a flowchart illustrating a method for estimating a dose curve based on patient body type by simulating protocols for patients of various body types, according to an embodiment of the present disclosure;

[0012] Figure 5An exemplary graphical user interface (GUI) of a CT simulation system according to an embodiment of the present disclosure is shown;

[0013] Figure 6 Another exemplary graphical user interface (GUI) or part of a GUI is depicted for use in simulating a CT system; and

[0014] Figure 7 The above is a graph showing a comparison between a first dose curve based on the patient's body size and a second similar dose curve estimated using a CT simulation system, according to an embodiment of the present disclosure. Detailed Implementation

[0015] Specific embodiments and implementations of the subject matter disclosed herein relate to computed tomography (CT) imaging systems. Specifically, systems and methods for simulating projection image quality (IQ) measures or projection dose prior to performing a scan using actual patient data are disclosed. Patient data may include one or more patient characteristics for a given patient, such as body size, which may be used to configure a protocol for the patient or patient group. In various implementations, patient characteristics may be extracted from CT locator images (also referred to herein as locator images). The scan parameters included in the protocol can then be optimized or customized by an operator for the patient or patient group, wherein the operator can adjust the scan parameters and simulate a diagnostic scan to determine the desired IQ / dose balance for performing the diagnostic scan.

[0016] In some CT systems, a gantry is used to rotate the radiation source and detector array around the object being imaged within the imaging plane, causing the angle at which the radiation beam intersects the object to continuously change. A set of radiation attenuation measurements (e.g., projection data) from the detector array at a single gantry angle is called a "view." A "scan" of the object comprises a set of views acquired at different gantry angles or viewing angles during a single rotation of the radiation source and detector. The term "view" is used to refer to a single data acquisition whenever multiple data acquisitions from different angles are possible.

[0017] Typically, to plan an optimal diagnostic scan, the patient undergoes a positioning scan. This positioning scan is usually a two-dimensional (2D) scan of the patient, producing 2D positioning projection data. To perform a 3D positioning scan, the patient is positioned within the imaging space of the imaging system. The stage of the imaging system can be controlled, for example, via a stage motor controller, to move so that the region of interest to be imaged is within the gantry aperture. The imaging system is then controlled to acquire positioning projection data at a reduced radiation dose compared to a typical diagnostic scan. For example, a positioning scan can be performed with a lower tube current and a higher pitch compared to a typical diagnostic scan. During the positioning scan, the subject can be moved through the gantry aperture while the X-ray source is controlled to generate a low-dose X-ray beam. For a higher pitch, one or more of the stage movement speed and the rotational speed of the X-ray source around the gantry aperture can be increased relative to a normal scan.

[0018] Reconstructing a 2D image (e.g., a localization image) from 2D localization projection data, similar to a conventional radiographic image, can be used to determine and confirm the approximate location of specific anatomical structures or another region of interest before performing a full diagnostic scan. Using the localization image, the operator can identify anatomical landmarks to ensure target anatomical structures are in the field of view and allows for the selection of appropriate techniques for different areas of the patient. During the localization scan, the patient's attenuation data can be determined and stored in the memory of a computing device. After the localization scan, a diagnostic scan can be performed based on the selected technique.

[0019] Diagnostic scans can be performed based on various scanning parameters of the imaging system, which can be set before the scan is performed. Before performing a diagnostic scan, the operator can select the desired protocol for the scan. In various implementations, the scan parameters can be automatically generated by one or more AI algorithms based on the selected protocol. One or more scan parameters can be configured based on a positioning scan. For example, the patient's body shape can be determined based on a positioning scan, and the patient's body shape can be used to set various scan parameters. The scan parameters specifically determine the radiation dose to be applied to the patient to obtain a desired image quality (IQ) metric of the image reconstructed from projection data acquired during the diagnostic scan. To achieve a higher IQ metric, the radiation dose can be increased. Conversely, if a reduced radiation dose is used, the IQ can be decreased.

[0020] Due to this natural trade-off between radiation dose and IQ, operators can choose to adjust one or more parameter settings before performing a diagnostic scan to reduce patient radiation exposure or achieve a desired IQ measurement. However, determining which parameters to adjust and the ideal settings for those adjustments may not be straightforward. The effectiveness of such adjustments in achieving both the desired dose and the desired IQ measurement may depend on operator experience and trial and error.

[0021] For example, an operator might perform a diagnostic scan based on a protocol and reconstruct an image using a first IQ metric at a first dose. The image may not have the desired quality, so the operator might make a first set of adjustments to the scan parameters and perform a second diagnostic scan to achieve a reconstructed image with the desired IQ metric at an acceptable dose. The first set of adjustments may not achieve the desired IQ metric, so the operator might make a second set of adjustments to the scan parameters and perform a third diagnostic scan to achieve the desired IQ metric. As a result of performing three diagnostic scans, the patient is exposed to a higher dose of radiation than expected to achieve the desired image. Alternatively, the first set of adjustments may achieve an IQ metric greater than sufficient for diagnostic work, also exposing the patient to more radiation than expected. Due to patient variability, the large number of adjustable parameters, and the interactions between parameters, determining the optimal set of adjustments for achieving the desired dose / IQ balance can be difficult and may require repeated diagnostic scans.

[0022] Furthermore, since it is difficult to determine the optimal parameter settings for a given type of scan, region of interest, patient, etc., optimization of standard protocols used for multiple patients may involve performing a large number of scans on different phantoms, which can be time-consuming and may reduce the availability of the imaging system for performing patient scans, thereby reducing the functionality and efficiency of the imaging system.

[0023] To address these issues, this paper presents a software-based tool that allows users to preview estimated dose and image quality (IQ) data for a patient or patient group based on one or more patient physical characteristics (e.g., body size) and a selected protocol. In various implementations, one or more patient characteristics can be extracted from the positioning images. The software-based tool simulates a front-end CT scanner console and allows users to input patient data and / or load previously acquired patient positioning DICOM images. Once one or more positioning images are loaded, the user can select the desired protocol and simulate scanning the patient according to the selected protocol based on the positioning images (and / or patient data). The system can calculate and display the projection noise index and projection dose data, including the projection CT dose index (CTDI), for the selected protocol, scan range, and scan settings. vol This includes the projection dose-length product (DLP) and projection exposure duration. For features that automatically determine certain scan parameters based on patient body size, users can also see which settings have been selected.

[0024] Furthermore, this tool allows users to adjust scan parameters and view real-time visual and quantitative dose and IQ feedback on the effects of these adjustments. Manual changes to scan settings update the dose and image quality projections accordingly. In this way, users can determine a set of scan parameters for scanning a specific patient or patient group before performing a scan, achieving the desired balance between patient radiation dose and image quality, without relying on repeated diagnostic scans.

[0025] Furthermore, this tool enables users to obtain accurate projections of IQ measures and dose, and visualize predictive system behavior for clinical protocols across a range of anatomical regions and patient body types from actual patient positioning. Using this tool, local outliers and undesirable behaviors can be prevented by selecting appropriate parameters for each part of the imaging space before any real patient is imaged at a single site. This allows medical physicists to obtain accurate estimates of image quality and dose across numerous protocols and patient body types, facilitating faster optimization and validation of protocols for the general population. For example, protocol scan settings can be tuned based on patient body type to achieve a target dose or dose range; more consistent dose profiles can be achieved based on body type (e.g., ensuring dose increases consistently with patient body type); and / or consistent image quality can be achieved based on patient body type and / or imaging scenario. The tool's output can be plotted against patient body type (as determined from positioning images) to visualize and validate dose and image quality across a range of patient body types. Doing this on top of a large number of pre-existing positioning locations allows for protocol optimization without being limited by scanning phantoms or slowly building experience from real patient scans over time. Therefore, when comparing quantitative measurements over time, if protocol optimization is poorly implemented, consistent image quality for efficient diagnostic readings can be generated across similar patients, and / or consistent image quality over time can be generated for duplicate patients, the quantitative measurement will have inherent variability not attributable to changes in disease state.

[0026] Now refer to the attached diagram, Figure 1An exemplary simulated CT system 100 is illustrated. The example simulated CT system includes an operator workstation 102 and a CT simulator 104 accessible using the operator workstation 102. The example CT simulator 104 may reside on a server within a hospital system and may be accessed via cloud access. The simulated CT system 100 may be operatively / communically coupled to one or more user input devices and display devices. For example, user input devices may include a keyboard and mouse or similar devices coupled to a computer, and display devices may include a monitor coupled to a computer. Instead of or in addition to a mouse and keyboard, other input devices may be included, including but not limited to touchscreens, touchpads, microphones, and cameras. The input devices allow an operator (e.g., a medical physicist) to select one or more inputs to the CT simulator 104. Inputs may include a patient's electronic medical records or history, previous patient scans (such as localization scans and / or diagnostic images), and a library of other images related to the patient's symptoms and / or physician instructions. The CT simulator 104 processes these inputs for the selected imaging protocol. The CT simulator then outputs an optimized scanning protocol, including parameter settings for the scanning protocol used to perform localization and / or diagnostic scans on a patient or patient group. For example, a localization scan for a large adult patient can be entered, and the protocol for the chest scan can be selected via an operator workstation. The CT simulator 104 can simulate multiple variations of the parameters for the protocol to determine the optimal parameters that balance acceptable IQ metrics with the dose to the patient. The output parameters can then be used on a CT imaging system for localization and / or diagnostic scans on large adult patients requiring chest scans. In some examples, localization scans for patients of multiple body sizes can be selected simultaneously, and the CT simulator 104 can output parameters for each patient group.

[0027] The simulated CT system 100 includes a processor configured to execute machine-readable instructions stored in non-transitory memory. The processor may be single-core or multi-core, and the programs executing on it may be configured for parallel or distributed processing. In some embodiments, the processor may optionally include separate components distributed across two or more devices, these separate components may be located remotely and / or configured for collaborative processing. In some embodiments, one or more aspects of the processor may be virtualized and executed by a remotely accessible networked computing device configured in a cloud computing configuration. The non-transitory memory may store one or more simulated CT scanner software applications, which may include software applications mirrored on the operator console and / or operator workstation 102 of the CT imaging system, and used to operate the CT scanner to acquire projection data during scanning and reconstruct images based on the acquired projection data.

[0028] Figure 2 Depicting Figure 1 A more detailed block diagram of an example CT imaging system is provided. The simulated CT system 100 can be a standalone system, meaning it may not be part of or coupled to the imaging system 201. In various embodiments, the simulated CT system 100 may be mounted on a radiologist's or other user's computing device. For example, part of the simulated CT system may be located at a device (e.g., an edge device, server, etc.) communicatively coupled to the imaging system 201 via a wired and / or wireless connection. The example CT simulator 104 includes an internet browser 202. The internet browser 202 enables a user to access the CT simulator 104 from an operator workstation 102. The internet browser 202 also enables access to a server 204. The server accesses a scan simulator user interface (UI) file 203, which includes an interface allowing the user to interact with the CT simulator. Figure 5 The example user interface is depicted, and this example user interface may include areas for input or prompts to be selected by the user and areas for outputting information.

[0029] Through server 204, CT simulator 104 can access protocol database 206 via protocol provider service 208. Protocol database 206 stores existing protocols, from which users can select protocols for optimization using CT simulator 104. (For example, in combination...) Figure 1 As discussed, users can use the input device of the operator workstation to select protocols from the protocol database 206, such as protocols for chest scans.

[0030] Additionally, users can access the radiology information server 210 via patient information service 212 and server 204. The radiology information server may include patient data available to the hospital system. For example, patient data may include a patient's medical records, which may include height, weight, demographic information, etc. Patient data may also include previous patient scans (e.g., localization scans, diagnostic scans) and diagnostic information (e.g., information related to the patient's diagnosis, such as cancer diagnosis, cardiac condition diagnosis, etc.). Any patient information can be used to categorize patients into patient groups. The CT simulator can then use scan data from one or more patients in the identified patient groups to optimize scan parameters for protocols used with the patient groups. Patient groups may be based on body size (e.g., small adult, medium adult, large adult, pediatric, etc.), clinical group, and / or diagnostic information (e.g., cardiac condition). Furthermore, the example CT simulator can also simulate how projected IQ measurements and doses vary across groups and can plot the distribution of patients across, for example, different body types.

[0031] Users can also access the Medical Digital Imaging and Communication (DICOM) image library 214 via image provider service 216. DICOM images can be used as input for the CT simulator 104, in addition to or replacing the patient's localization scan. The DICOM image library 214 may each include multiple DICOM images acquired using a CT system. The DICOM image library 214 may be a non-limiting example of a Picture Archiving and Communication System (PACS) or included therein. Specifically, the DICOM image library 214 may include multiple localization images. The CT simulator 104 can receive localization images from the DICOM image library 214 and process the localization images to calculate estimated metrics (CTDlvol and DLP) and / or estimate image quality (IQ) measures of the images reconstructed from projection data acquired from the patient during the scan, as described in more detail below.

[0032] Example CT simulator 104 includes at least one dose algorithm service 218. Dose algorithm service 218 may include a dose algorithm equivalent to a dose algorithm running on a CT imaging system. The dose algorithm uses user-provided input and outputs a dose or dose curve. Dose algorithm service 218 may include instructions for estimating the projected dose of a scan using a selected scan protocol based on scan settings output by CT simulator 104 according to a protocol. Dose algorithm service 218 can model the performance of the CT scanner and estimate the projected dose. Specifically, dose algorithm service 218 may include instructions that, when executed by a processor, cause the simulated CT system 100 to perform one or more steps of method 300.

[0033] The example CT simulator 104 may also include an IQ algorithm service 222. The IQ algorithm service 222 may include one or more algorithms that can be used to determine parameters of a scan protocol optimized to balance dose and IQ for a patient or patient group. Example algorithms may mirror what runs on the CT imaging system 201. Example algorithms may include a noise-based automatic exposure control (AEC) algorithm to determine the amount of noise that may be expected in images produced when scanning using a scan protocol and selected parameters for the patient or patient group. When using a selected scan protocol, a dose-based AEC algorithm may be run to minimize the dose for the patient. The example CT simulator may also include a patient-specific service 220 that provides information on patient-related parameters determined by the CT simulator. For example, an automatic prescription algorithm may be used to determine a set of scan settings for scanning the patient according to the protocol. That is, a user of the simulated CT system 100 can specify the protocol to be used for scanning via a user input device, and one or more AI models from a plurality of AI models can be used to configure the CT scanner based on the protocol. Additionally, the algorithms of the patient-specific service 220 may determine the scan extent (e.g., scan start position, scan end position) for the patient or patient group. Examples of one or more algorithms, including Dosing Algorithm Service 218, IQ Algorithm Service 222, and Patient-Specific Service 220, together determine the parameters to be used with the selected protocol to optimize the balance between dose and IQ for the resulting images from the CT scan.

[0034] Turn now Figure 3 An exemplary method 300 for simulating a diagnostic scan and previewing projection dose and image quality (IQ) data for a patient based on a selected protocol and provided patient data is illustrated. Method 300 can be performed by a simulated CT system 100. The operation of method 300 can be stored in the non-transitory memory of the simulated CT system 100 and executed by the processor of the simulated CT system. It should be understood that, in various examples, one or more steps of method 300 can be performed multiple times, for example, iteratively.

[0035] Method 300 begins at 301, wherein method 300 includes launching CT simulator 104. In some examples, launching the simulated CT system includes launching a user interface (e.g., via scan simulator user interface file 203) using browser 202 of CT simulator 104. In various examples, CT simulator 104 may be installed on a user's computing device, such as an operator of a CT imaging system (e.g., a radiologist or medical physicist). Alternatively, CT simulator 104 is stored on a server accessible by operator workstation 102, which can be used by radiologists and / or medical physicists. CT simulator 104 may be launched by the user before and / or when preparing to perform a CT imaging scan on a patient. When CT simulator 104 is launched, the GUI of CT simulator 104 may be displayed on the display screen of simulated CT system 100 (e.g., the monitor of operator workstation 102).

[0036] At 302, method 300 includes receiving a protocol to be used during subsequent diagnostic scans of the patient. The protocol can be selected from a plurality of protocols (e.g., from a user-available protocol database 206, which may correspond to protocols available to the CT imaging system 201).

[0037] At 304, method 400 includes receiving one or more patient characteristics, which can be used to configure the received protocol for the patient or patient group. One or more patient characteristics can be received from a user of the CT simulator 104 via a GUI. For example, the one or more patient characteristics may include the patient's body size, or the patient's body mass index (BMI), or the patient's water equivalent diameter (WED), or different body characteristics of the patient or patient group.

[0038] In various examples, patient characteristics can be extracted from patient images or a set of measurements performed on the patient. For example, at 305, method 300 may include extracting patient characteristics (such as patient body size) from patient locator (e.g., positioning) images. These characteristics can be extracted from storage locations on a computing device or storage devices coupled to the computing device (such as image libraries of CT imaging systems, e.g., Figure 2 The DICOM image library 214 receives positioning images. For example, a user can specify positioning images to be received via the GUI. In some implementations, the user can use the GUI to browse or search multiple positioning images stored in or on one or more locations on the computing device or on the network of the computing device, and select the desired positioning image to load into the CT simulation system. In other examples, patient characteristics can be extracted from 3D camera images of the patient taken during positioning scans, or from electrocardiograms (EKGs) recorded by the patient, or from different types of patient data collected from the patient.

[0039] The CT simulator 104 GUI (e.g., the GUI) may include the same or similar control groups as the CT imaging system GUI displayed in the operator console (e.g., the operator console) of the CT imaging system, and is used to perform scans on patients. That is, the GUI can provide similar functionality to the CT imaging system GUI, and can be accessed in a similar manner to the CT imaging system GUI via controls having a similar appearance. For example, a user can load a locator image (e.g., a localization scan), select a protocol for performing a diagnostic scan, request recommended scan parameters according to the protocol, and / or manually set multiple scan settings using controls in the GUI similar to the corresponding controls in the CT imaging system GUI. In this way, the familiarity with the controls and UI design of the CT simulator 104 system GUI can reduce the learning curve for using the CT simulation system and facilitate quick and easy use of the CT simulation system by the user.

[0040] At 306, method 300 includes determining parameter settings (also referred to herein as scan settings) for scanning the patient based on the received protocol and one or more patient characteristics. In various embodiments, the parameter settings may be determined by one or more algorithms, such as those included in... Figure 2 The patient-specific server 220 or IQ algorithm server 222 may contain a dose algorithm server, a noise-based AEC algorithm, a dose-based AEC algorithm, an intelligent planning algorithm, an automatic prescription algorithm, a GSI-assisted algorithm, an automatic gating algorithm, and a kV-assisted algorithm. For example, the algorithms may include an AEC system, a scan range selection system, etc. That is, one or more algorithms can take the received scan protocol and additional patient characteristics as input and can output one or more sets of scan parameters for performing the scan according to the protocol. One or more sets of scan parameters can be displayed on a screen for user viewing.

[0041] At 308, method 300 includes simulating a patient's diagnostic scan in a CT simulation system based on one or more sets of scan parameters. While the scan is simulated, the CT simulation system can calculate projection (e.g., estimate) dose data for the simulated scan. The projection dose can be an estimate of the dose relative to the applied scan settings or parameters (e.g., kV, mA, rotation time, collimation, pitch, etc.). Calculating the projection dose data can include, for example, calculating the projection CTDI for the scan. vol Projection DLP and / or body type-specific dose estimation (SSDE). Projection dose data may also include the duration of projection exposure and settings or parameters specific to the scanning protocol. The effective dose for a patient scan can be estimated using projection dose data and patient characteristics such as patient body type, the anatomical region being scanned, and / or other factors.

[0042] The applied scan settings or parameters can be input into the CT scanner model, and the CT scanner model can output projection dose data, projection IQ data, and / or other projection data. In some implementations, the CT scanner model may rely on a set of predicted values ​​for a specific scan parameter and may apply a set of correction factors based on the actual applied settings of the scan modified by the user. Projection IQ data can be generated from the projection dose data and can be used to display exemplary images corresponding to the projection dose data. For example, projection IQ data may include the projection noise index (NI) of the scan, and the projection NI can be used to generate exemplary images. If a diagnostic scan is performed on a patient, the projection dose and IQ data may be the same as those seen in a clinical setting.

[0043] Projection dose, IQ data, and images can be displayed on the operator workstation screen via the CT simulator user interface. See below for reference. Figure 5 Describe an exemplary CT simulator user interface.

[0044] The projected NI of the scan can be compared with the projected dose index (CTDI). vol The projection dose is inversely proportional to the projected NI (i.e., the projection IQ can decrease as the projection dose increases). Therefore, before performing a diagnostic scan on a patient, the user can use the CT simulator 104 (e.g., via the CT simulator UI) to see examples of different IQs that can be achieved at different doses, in order to customize scan parameters for the patient and achieve the desired IQ metric while keeping the dose within the desired or acceptable range.

[0045] At 310, method 300 includes determining whether the scan parameter settings have been confirmed by the user using the CT simulator UI. If it is determined at 310 that the parameter settings have not been confirmed, method 300 continues to 312. At 312, method 300 includes receiving the adjusted scan parameters, and method 300 returns to 308 to re-simulate the patient's scan based on the adjusted scan parameters. For example, one or more scan parameter settings can be adjusted by the user via separate controls for each parameter setting in the CT simulator UI, as referenced below. Figure 5 As described above, after adjusting the scan parameters, updated IQ measurements and dose data can be displayed in real time in the CT simulation GUI. In this way, users can test various adjustments to the parameter settings to determine the combination of settings that achieves the desired image quality with an acceptable dose.

[0046] Alternatively, if it is determined at 310 that the parameter settings are confirmed, it can be inferred that the parameter settings are acceptable to the user, thus method 300 proceeds to 314. At 314, method 300 includes modifying the protocol to generate a customized protocol for the patient, wherein the customized protocol includes adjusted scan settings. At 316, method 300 includes storing the scan parameter settings in a memory accessible by the CT imaging system 201.

[0047] The stored parameter settings can be exported to the CT imaging system for subsequent diagnostic scans of the patient or patient group. By performing diagnostic scans using adjusted parameter settings determined by the simulated CT system 100, rather than recommended parameter settings automatically generated based on protocols, the target IQ metric of the image reconstructed from projection data acquired during the diagnostic scan can be achieved more accurately using a lower radiation dose than that generated using recommended parameter settings. In this way, a specific IQ / dose balance can be customized for the patient in an efficient and rapid manner. Furthermore, because the simulated CT system 100 is implemented as a standalone product and does not depend on the processor of the CT imaging system, the customized IQ / dose balance can be determined offline, meaning that the resources of the CT imaging system are not used. For example, the simulated CT system 100 can be used in parallel by multiple users while the CT imaging system is used to perform diagnostic scans on other patients, or the simulated CT system 100 can be used when the CT imaging system is not started or powered. Therefore, while using the simulated CT system 100, the resources of the CT imaging system can be used for other tasks, thereby improving the efficiency and functionality of the CT imaging system.

[0048] Because the customized parameter settings are determined offline using the simulated CT system, meaning they are independent of the CT imaging system, the CT imaging system can remain available for diagnostic scans of more patients compared to alternative scenarios where the simulated CT system is unavailable. In alternative scenarios, the operator can monopolize the CT imaging system for a longer period of time because multiple diagnostic scans are performed on the patient to achieve images of the desired quality.

[0049] See now Figure 4 An exemplary method 400 is illustrated, which is used to modify the protocol of diagnostic scans for multiple patients using a simulated CT simulation system 100 to achieve a smoother dose profile based on patient body size. (See above reference...) Figure 3 The simulated CT system 100 allows users to preview projection dose and image quality (IQ) data for patients of different body types. The operations of method 300 can be stored in the non-transitory memory of the simulated CT system 100 and executed by the processor of the simulated CT system 100.

[0050] Method 400 begins at 402, wherein method 400 includes receiving multiple localization images of corresponding multiple patients, wherein the patients have a range of different body types. Multiple localization images may be received from one or more libraries of DICOM images (such as a DICOM image library).

[0051] At 404, method 400 includes receiving a protocol (e.g., an initial protocol) to be used during diagnostic scans of multiple patients. The initial protocol can be received by a user of the simulated CT system 100 via the GUI of the CT simulation system (such as...). Figure 5 Use the GUI shown to select.

[0052] At 406, method 400 includes generating parameter settings to be used in diagnostic scans performed on multiple patients based on the received initial protocol. A first portion of the parameter settings may be configured based on patient characteristics, such as patient body size, which is calculated from localization images. A second portion of the parameter settings may be generated by one or more algorithms, such as an automated scan prescription algorithm.

[0053] At 408, method 400 includes simulating a diagnostic scan of the patient for each of a plurality of positioning images. While simulating the diagnostic scan, projected dose and IQ data for the diagnostic scan can be displayed on a display device (such as a display device). The user can review the projected dose and IQ data to determine whether the projected IQ metric of the image reconstructed from the diagnostic scan exceeds a threshold quality. Method 400 also includes receiving adjustments to parameter settings for the patient from the user. That is, for each positioning image, the user can adjust one or more parameter settings via a GUI and view updated projected dose and IQ data for the corresponding patient's simulated diagnostic scan. The user can adjust one or more parameter settings multiple times during the iteration process to achieve the desired IQ metric at an acceptable dose. When the user determines the parameter settings that achieve the desired IQ metric at an acceptable dose, the user can confirm the parameter settings via controls in the UI. When the patient's parameter settings are confirmed, the parameter settings, the resulting projected IQ metric value, and the patient's corresponding projected dose can be stored in the system's non-transitory memory.

[0054] At 410, method 400 includes calculating a dose curve for multiple patients based on the projected dose for each of the multiple patients and according to the patient's body shape. That is, after simulating diagnostic scans for each patient in each of the multiple positioning images, the multiple patients can be sorted according to their body shape using the corresponding parameter settings collected for each simulated diagnostic scan, and the curve can be fitted to the projected dose for each patient based on their body shape.

[0055] Brief reference Figure 7 An exemplary dose curve 700 is shown, illustrating the dose based on patient body shape data relative to a diagnostic scan, both from simulated and actual patient data. As described above, the patient body shape can be calculated from positioning images and may include, for example, the patient's anterior-posterior (AP) or front-to-back body shape measured in centimeters, and the patient's lateral (LAT) left-to-right body shape. The dose curve 700 is plotted on the y-axis using CTDI. vol The dose applied to the patient is indicated, and the patient's body size corresponding to the dose is indicated on the x-axis of the dose curve 700. The dose curve 700 includes two plots of the dose curve. A first dose curve 702 is plotted based on a first protocol, wherein the first protocol indicates a first set of parameter settings for each patient. A second dose curve 704 is plotted based on a second protocol, wherein simulated (e.g., projected) dose data is associated with each patient, where the dose data is generated as a result of simulating a diagnostic scan of the patient using a CT simulation system. Specifically, the dose data of the second dose curve 704 is based on adjusted parameter settings generated as described in methods 300 and 400. In other words, the second protocol is a version of the first protocol customized for each patient by the user of the CT simulation system. On each dose curve, the amount of dose measured in mGy for each patient is shown.

[0056] like Figure 7 As can be seen, the first dose curve 702 does not show a smooth evolution of the dose according to the patient's body size. Specifically, the first portion 706 of the first dose curve 702 indicates an equivalent dose (11.3 mGy) for patients with a body size ranging from approximately 58 cm to 67 cm. The second portion 708 of the first dose curve 702 indicates a sharp increase in dose for patients with a body size ranging from approximately 67 cm to 69 cm. The third portion 710 of the first dose curve 702 indicates an equivalent dose (18.5 mGy) for patients with a body size ranging from approximately 69 cm to 90 cm. Therefore, if the first protocol is used to perform a diagnostic scan, patients whose size decreases or increases during treatment may be administered a dose that is not well tailored to their body size, which may result in suboptimal image quality (if the patient does not receive an adequate dose) or a dose higher than required to achieve the desired image quality.

[0057] In contrast, the second dose curve 704 shows a smoother dose evolution according to patient body size than the first dose curve 702, where different doses are consistently applied to patients of different body sizes in similar increments. Therefore, if a second customized protocol is used to perform diagnostic scans, a more precise dose tailored to the patient's body size can be applied to patients whose body size decreases or increases during treatment, thus achieving a better trade-off between radiation dose and image quality.

[0058] Return to Figure 4 At 412, method 400 includes modifying the protocol based on a calculated dose profile. That is, when appropriate adjusted parameter settings for each localization image / patient are collected from the user, these parameter settings generate a dose profile with desired characteristics, such as those obtained from... Figure 7 The dose shown in the second dose curve 704, which smoothly evolves according to the patient's body size, allows the protocol to be modified to include appropriate adjusted parameter settings. The modified protocol can be used to set parameter settings for future diagnostic scans of patients with different body sizes, instead of the initial protocol. The modified protocol can specify parameter settings for each patient of different body sizes, which adjusts the dose applied to the patient more smoothly according to body size than the initial protocol.

[0059] At 414, method 400 includes storing the modified protocol in a memory accessible by the CT scanner. During subsequent diagnostic scans, the modified protocol can be retrieved from the memory and applied by the CT scanner operator. Method 400 ends.

[0060] Figure 5 An exemplary GUI 500 for a simulated CT system 100 is shown, which can be used in methods 300 and 400 described above to simulate a diagnostic scan performed on a patient on a CT scanner. It should be understood that the GUI 500 is provided for illustrative purposes and not for limiting purposes, and in other embodiments, the GUI 500 may include more or fewer components or different components without departing from the scope of this disclosure.

[0061] The GUI 500 may include a top bar 502, which provides space for various advanced controls, such as login or logout functionality, user profiles, and / or other advanced menu options. In some examples, the GUI 500 may provide a tabbed view, where data from different scans or patients can be presented in multiple tabs accessible from the top bar 502.

[0062] In the depicted implementation, the GUI 500 includes a first display panel 510, a second display panel 520, a third display panel 522, a fourth display panel 524, and a fifth display panel 526, which can display various types of patient data. Specifically, the first display panel 510 includes a progress bar that can display the progress of a scan being performed. The second display panel 520 can include general high-level information about the selected patient or case. For example, a user of the GUI 500 can select a patient via a menu accessed through a top bar 502, which can display multiple patients, such as those from a healthcare system. Data for the selected patient can be retrieved from a storage location and displayed in the GUI 500. The storage location can be the memory of the analog CT system 100 or the storage location of a different system accessible via a network. High-level information can include, for example, patient identification information, patient health problems, image availability, laboratory results, historical data (such as procedures performed on the patient), etc. The second display panel 520 may also include control elements, such as one or more buttons for performing various tasks or viewing different types of patient data. Specifically, the second display panel 520 may include control elements for initiating a simulation of a diagnostic scan of the patient, as referenced above. Figure 3 As stated above.

[0063] The third display panel 522 and the fourth display panel 524 can be used to display parameter settings associated with the selected protocol. For example, a user can select a protocol to be used in a future diagnostic scan of the patient. In some embodiments, the protocol can be selected from a pop-up menu that appears as a result of the user selecting a control element for initiating a diagnostic scan. When a protocol is selected, parameter settings associated with the protocol can be displayed in one or both of the third display panel 522 and the fourth display panel 524. The parameter settings can be configured or determined by one or more algorithms, such as an automated scan prescription algorithm. In some examples, the user can manually select one or more algorithms using the control elements of the GUI 500, while in other examples, one or more algorithms can be selected automatically. One or more algorithms can take patient data and the protocol as input and output a corresponding set of parameter settings for the protocol. Patient data can include one or more patient characteristics, such as patient body size. In some embodiments, patient data can include a localization image obtained from the patient at a previous time or extracted from such a localization image. In some examples, the localization image can be displayed in the seventh display panel 530 and / or the eighth display panel 532 of the GUI 500.

[0064] Scanning parameters generated by one or more AI models and displayed in the third display panel 522 and / or the fourth display panel 524 can be user-editable (e.g., adjustable). As described above, the user can adjust one or more scanning parameters for a selected protocol. Specifically, the user can use the protocol's parameter settings to initiate a simulation of a diagnostic scan of a patient and view the projected dose and IQ data for the simulated diagnostic scan based on the parameter settings. The user can then adjust one or more of the scanning parameters and view updated projected dose and IQ data for the simulated diagnostic scan based on the adjusted parameter settings. In this way, the user can iteratively determine customized parameter settings to be applied as part of the protocol for the patient in future diagnostic scans. The projected dose and IQ data can be displayed in the fifth display panel 526. In some cases, visualization of the updated parameter settings can be additionally or alternatively displayed in one or more of the display panels 522, 524, 526, 530, and 532. For example, users can adjust the start and end positions of a diagnostic scan and visualize the adjusted start and end positions of the diagnostic scan on the positioning images displayed in display panels 530 and 532.

[0065] For example, a sample settings summary display panel can be displayed in the second display panel 520 of the GUI 500. The settings summary display panel includes various categories of parameter settings associated with the selected protocol, with each setting within each category summarized. For example, display panel 520 summarizes anatomical structure selection parameter settings, kV and mA control parameter settings, contrast parameter settings, timing parameter settings, scan type parameter settings, coverage speed parameter settings, primary reconstruction parameter settings, and gating and tracking parameter settings. The settings summary can be displayed in the same or similar manner as when displaying parameter settings to the operator of the CT scanner via the operator console of the CT imaging system. Therefore, the display of parameter settings in the settings summary display panel 520 can be familiar to the user of the GUI 500.

[0066] In various examples, an exemplary projection dose display panel may be displayed in a fifth display panel 526 of the GUI 500. The projection dose display panel 525 may display projection dose data for a simulated diagnostic scan initiated via the GUI 500. The projection dose data may be based on parameter settings of a selected protocol or user-generated and adjusted parameter settings. In the depicted implementation, the projection dose data includes a total projection dose value (e.g., 101.39), which may be generated from various dose data components. The dose data components may include, for example, CTDI measured in mGy. volValue; DLP dose value measured in mGy*cm; dose efficacy, which indicates the percentage of dose used to generate the image; and the size of the CTDI phantom in cm used when calculating CTDI and dose efficacy, wherein the phantom may be a body phantom comprising a 32cm cylindrical phantom or a head phantom comprising a 16cm cylindrical phantom.

[0067] The projected dose value is a measure of the dose to the phantom for the applied scan settings (e.g., kV, mA, rotation time, collimation, pitch, etc.) and can be calculated by looking up a set of predicted values ​​for a specific setting and then applying a set of correction factors based on the actual application settings of the scan, as described above.

[0068] If the user is satisfied with the projection IQ measurement and projection dose, they can select a control element to confirm the parameter settings displayed in the GUI500. If the user is not satisfied with the projection IQ measurement and projection dose, they can adjust one or more parameter settings and re-simulate the diagnostic scan to obtain different projection IQ measurement and dose data. Users can use different parameter settings to simulate various diagnostic scan times to determine the ideal parameter settings for the patient and protocol. Once the ideal parameter settings are obtained, the user can confirm the settings via the control element. When the user selects a control element, the selected protocol can be modified to include the adjusted parameter settings, thereby generating a customized protocol for the patient. The customized protocol can be used during future diagnostic scans of the patient via a CT scanner.

[0069] An exemplary visualization of the start and end points of a simulated diagnostic scan according to one implementation scheme can be displayed. Figure 5 The location image is displayed in the GUI 500, for example, in the seventh display panel 530 and the eighth display panel 532. When the user selects a protocol, the selected portion of the patient's anatomy to be scanned in the diagnostic scan can be indicated by a first box on the first view of the location image displayed in the seventh display panel 530 and a second box on the second view of the location image displayed in the eighth display panel 532. In some examples, Figure 2 The exemplary patient-specific service 220 can be used to identify selected portions of a patient's anatomy. The start point of a diagnostic scan can be indicated by the upper line of the first frame and the leftmost line of the second frame. The end point of a diagnostic scan can be indicated by the lower line of the first frame and the rightmost line of the second frame.

[0070] Users can adjust the start and end parameters of a simulated diagnostic scan. When users edit the start and end parameters, selected portions of the patient's anatomy to be scanned in the diagnostic scan can be updated in the visualization. The updated selected portions of the anatomy are indicated by a first frame on a first view of the localization image displayed in the seventh display panel 530 and a second frame on a second view of the localization image displayed in the eighth display panel 532. The start point of the updated diagnostic scan can be indicated by the upper line of the first dashed frame and the leftmost line of the second dashed frame. The end point of the diagnostic scan can be indicated by the lower line of the first dashed frame and the rightmost line of the second dashed frame. Therefore, the visualization can visualize the impact of adjustments made to the start and end parameters on the localization image via the anatomy selection display panel in a textual manner, making it easier for users to identify the ideal start and end parameters for the diagnostic scan.

[0071] In some implementations, the upper line, lower line, leftmost line, and rightmost line can be selected, allowing the user to interactively adjust the position of one or more of these lines to reflect the desired start and / or end point. As the user interactively adjusts the position, the corresponding start and / or end point parameters can be automatically updated in the simulated CT system and anatomical structure selection display panel.

[0072] Figure 6 Another example user interface 600 that can be displayed on operator workstation 102 when using a simulated CT system 100 is depicted. The example user interface 600 includes estimated patient size and projection examination dose for multiple patients simultaneously. The example user interface 600 depicts three simulated patients of three different body types (e.g., small adult, medium adult, and large adult). However, any number of simulated patients can be depicted. In the illustrated example, an insight is available for simulated patient 1. In such cases, the insight box 602 can be depicted in a different color than when no insight is available. The example insight includes suggested adjustments to the patient's intelligent plan, such as adjusting the start or stop position of the scan of the patient's body. Another example insight includes adjusting kV to meet recommended noise requirements.

[0073] The advantage of simulating a patient's diagnostic scan performed by a CT imaging system and allowing users of the simulated CT system to adjust parameter settings for a selected protocol used for the diagnostic scan and view projection dose and image quality data of the simulated diagnostic scan is that it can generate a customized protocol for the patient that produces a reconstructed image with the desired image quality measurement without wasting the operator's time and resources of the CT imaging system in repeated diagnostic scans.

[0074] When describing elements of various embodiments of this disclosure, the articles “a,” “an,” and “the” are intended to indicate the presence of one or more such elements. The terms “first,” “second,” etc., do not indicate any order, quantity, or importance, but are used to distinguish one element from another. The terms “comprising,” “including,” and “having” are intended to be inclusive and indicate that additional elements may exist in addition to the listed elements. As used herein, the terms “connected to,” “coupled to,” etc., indicate that an object (e.g., a material, element, structure, component, etc.) may be connected to or coupled to another object, regardless of whether the one object is directly connected to or coupled to the other object, or whether one or more intervening objects exist between the one object and the other object. Furthermore, it should be understood that references to “an embodiment” or “an embodiment” of this disclosure are not intended to be construed as excluding the existence of additional embodiments also incorporating the referenced features.

[0075] In addition to any modifications previously indicated, many other variations and alternative arrangements can be devised by those skilled in the art without departing from the spirit and scope of this specification, and the appended claims are intended to cover such modifications and arrangements. Therefore, although the information has been described in particular and in detail above in conjunction with what is now considered to be the most practical and preferred aspects, it will be apparent to those skilled in the art that many modifications can be made without departing from the principles and concepts set forth herein, including but not limited to changes in form, function, mode of operation, and purpose. Likewise, as used herein, embodiments and implementations are meant to be illustrative in all respects and should not be construed as limiting in any way.

Claims

1. A computer-implemented method for simulating a computed tomography (CT) system, the method comprising: Receive the selected scanning protocol via the user interface; Receive one or more characteristics of a patient or patient group via the user interface; Use a CT simulator to determine the parameter settings for scanning the patient or group of patients; The CT simulator is used to determine the quality of the projected image or the projection dose. as well as Generate a customized scanning protocol for the patient or patient group.

2. The method according to claim 1, further comprising displaying the quality and dose of the projected image on a display of the simulated CT system.

3. The method of claim 1, further comprising starting a CT simulator on an operator workstation, wherein the operator workstation is located away from the CT imaging system.

4. The method of claim 1, wherein receiving one or more characteristics of the patient or group of patients includes extracting characteristics from a localization scan.

5. The method of claim 1, wherein determining the quality and dose of the projected image comprises simulating a scan of the patient or group of patients based on the selected scanning protocol, characteristics, and parameter settings.

6. The method of claim 1, the method further comprising receiving confirmation from the user that the parameter settings are acceptable.

7. The method of claim 6, wherein when the parameter settings are unacceptable, the adjusted parameter settings are received via the user interface.

8. The method of claim 1, further comprising storing the customized scanning protocol in a memory accessible by the CT system.

9. A simulated computed tomography (CT) system, the simulated computed tomography system comprising: Operator workstation; A CT simulator, accessible via the operator workstation, is configured to: The selected scanning protocol is received via a user interface displayed on the operator workstation; Receive one or more characteristics of a patient or patient group via the user interface; Determine the parameter settings used to scan the patient or group of patients; Determine the quality and dosage of the projected image; as well as Generate a customized scanning protocol for the patient or patient group.

10. The system of claim 9, wherein the CT simulator is further configured to display the quality and dose of the projected image via the user interface on the operator workstation.

11. The system of claim 1, wherein one or more features received by the patient or group of patients are extracted features from a localization scan.

12. The system of claim 1, wherein the quality and dose of the projected image are determined by simulating a scan of the patient or group of patients based on the selected scanning protocol, characteristics, and parameter settings.

13. The system of claim 1, wherein the CT simulator is further configured to receive confirmation from the user that the parameter settings are acceptable.

14. The system of claim 13, wherein when the parameter settings are unacceptable, the CT simulator is further configured to receive adjusted parameter settings via the user interface.

15. The system of claim 1, further comprising a CT system, wherein the customized protocol is stored in a memory accessible by the CT system.

16. A computer-implemented method for simulating a computed tomography (CT) system, the method comprising: Receive multiple location images; Receive the protocol to be used during diagnostic scanning; Generate parameter settings to be used on the diagnostic scan; Simulate the diagnostic scans for multiple patients; Calculate dose curves for the multiple patients based on their body types; as well as The protocol is modified based on the dose curve.

17. The method of claim 16, wherein the method further stores the modified protocol in a memory accessible by a CT scanner.

18. The method of claim 16, wherein the dose curve is based on a projected dose for each patient determined using the simulated diagnostic scan for the plurality of patients.

19. The method of claim 16, wherein receiving the protocol includes the user selecting from a protocol database.

20. The method of claim 16, wherein receiving a plurality of location images includes a user selecting from an image library.

Images