Computed tomography simulator for estimating dose and image quality

Abstract

This invention provides a computer implementation method for a simulated computed tomography (CT) system. [Solution] The method includes receiving a selected scan protocol and one or more characteristics of a patient or patient group via a user interface. Using a CT simulator, parameter settings for scanning the patient or patient group are determined. The method further includes using a CT simulator to determine a predicted image quality index and dose, and generating a customized scan protocol for the patient or patient group based on the predicted image quality index and dose.

Description

Technical Field

[0001] Embodiments of the subject matter disclosed herein relate to computer tomography (CT) imaging systems, and more particularly, to simulation of imaging protocols.

Background Art

[0002] In a computer tomography (CT) imaging system, an electron beam generated by a cathode is directed at a target within an X-ray tube. A fan-shaped or conical X-ray beam generated by electrons colliding with the target is directed at a subject such as a patient. After being attenuated by the subject, the X-rays collide with an array of radiation detectors. An electrical signal is generated by each detector element, and the electrical signals generated by the detector elements are transmitted to a data processing system, and finally an image is generated.

[0003] During a scan to acquire projection data, generally, it is desirable to reduce the X-ray dose received by the subject and improve the image quality. There can be a number of scan settings within a CT protocol that affect the trade-off between dose and image quality. The scan settings established by a CT protocol may not result in an image of the desired image quality, whereby the operator of the CT system can adjust one or more of the scan settings of the protocol to improve the image quality or reduce the dose. However, it can be difficult to determine the optimal combination of scan settings to achieve the desired image quality / dose balance. As a result, various diagnostic scans may be performed on the patient to achieve the desired image, and the amount of radiation to which the patient is exposed may increase.

[0004] Furthermore, CT users (e.g., medical physicists) optimize and validate the clinical effectiveness of protocols through phantom scans. This can be a burdensome and time-consuming process, especially for facilities with many protocols. Moreover, many facilities may only have one or two phantoms that do not cover the entire anatomical region, clinical scenario, or patient size. [Overview of the Initiative]

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

[0006] The advantages and other advantages and features of this specification will be readily apparent from the following detailed description, either on its own or in conjunction with the accompanying drawings. It should be understood that the above summary is provided to introduce in a simplified form a selection of concepts further described in the detailed description. It is not intended to identify any important or essential features of the claimed subject matter, the scope of which is independently defined by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to embodiments that address any of the defects pointed out above or in any part of this disclosure. [Brief explanation of the drawing]

[0007] Various aspects of this disclosure can be better understood by reading the following detailed description and referring to the drawings. [Figure 1] Figure 1 is a pictorial perspective view of a simulated computed tomography (CT) imaging system according to one or more embodiments of the present disclosure. [Figure 2] This is a more detailed block schematic diagram of an exemplary simulated CT imaging system according to one or more embodiments of the present disclosure. [Figure 3] This flowchart shows a method for simulating a diagnostic scan performed using a CT imaging system according to embodiments of the present disclosure. [Figure 4] This flowchart shows a method for estimating a dose curve as a function of patient size by simulating protocols for patients of various sizes according to embodiments of the present disclosure. [Figure 5] This figure shows an exemplary graphical user interface (GUI) of a CT simulation system according to an embodiment of the present disclosure. [Figure 6] This figure shows another example of a simulated CT system's graphical user interface (GUI) or a portion of a GUI. [Figure 7]This is a graph comparing a first dose curve showing the dose as a function of patient size according to an embodiment of the present disclosure with a second similar dose curve estimated using a CT simulation system. [Modes for carrying out the invention]

[0008] This specification and embodiments of the subject matter disclosed herein relate to computed tomography (CT) imaging systems. In particular, systems and methods are disclosed for simulating predicted image quality (IQ) measurements or predicted doses before performing scans using actual patient data. Patient data may include one or more patient characteristics of a given patient, such as size, which can be used to construct protocols for a patient or group of patients. In various embodiments, patient characteristics can be extracted from CT localizer images, also referred to herein as scout images. The scan parameters included in the protocol may then be optimized or customized by the operator for a patient or group of patients, and the operator may simulate a diagnostic scan by adjusting the scan parameters to determine a desired IQ / dose balance for performing a diagnostic scan.

[0009] In some CT systems, the radiation source and detector array rotate with the gantry within the imaging plane and around the object being imaged so that the angle at which the radiation beam intersects the object is constantly changing. A set of radiation attenuation measurements from the detector array at a given gantry angle, such as projection data, is called a “view.” A “scan” of an object includes a series of views taken at different gantry angles, i.e., view angles, during one rotation of the radiation source and detector. The term “view” is used to mean a single data acquisition whenever there are multiple data acquisitions from different angles.

[0010] Typically, a patient undergoes a scout scan to plan an optimal diagnostic scan. A scout scan is conventionally a two-dimensional (2D) scan of the patient, generating 2D scout projection data. To perform a 2D scout scan, the patient is positioned within the imaging space of the imaging system. The imaging system's table is controlled, for example, via a table motor control device, to move so that the region of interest to be imaged is within the gantry bore. The imaging system is then controlled to acquire scout projection data with reduced radiation doses compared to a typical diagnostic scan. For example, a scout scan can be performed with lower tube current and a higher helical pitch compared to a typical diagnostic scan. During a scout scan, the subject can move within the gantry bore while the X-ray source is controlled to generate a low-dose X-ray beam. When the helical pitch is increased, one or more of the table's movement speed and the rotation speed of the X-ray source around the gantry bore can be increased compared to a normal scan.

[0011] Two-dimensional images similar to plain radiographic images (e.g., scout images) are reconstructed from two-dimensional scout projection data, which can be used to determine and confirm the approximate location of specific anatomical structures or other areas of interest before performing a full diagnostic scan. By using scout images, operators can identify anatomical landmarks, confirm that target anatomical structures are within the field of view, and select appropriate techniques for different areas of the patient. Once the scout scan is performed, the patient's attenuated data is determined and stored in the memory of the computing device. After the scout scan is performed, a diagnostic scan may be performed based on the selected technique.

[0012] A diagnostic scan may be performed according to various scan parameters of the imaging system that can be set before performing the diagnostic scan. Before performing the diagnostic scan, the operator can select a desired protocol for performing the scan. In various embodiments, the scan parameters may be automatically generated by one or more AI algorithms based on the selected protocol. One or more scan parameters may be configured based on a scout scan. For example, the patient size may be determined from the scout scan, and the patient size may be used to set various scan parameters. The scan parameters, in particular, determine the radiation dose applied to the patient for a desired image quality (IQ) measurement of the image reconstructed from projection data acquired during the diagnostic scan. To achieve a higher IQ index, the radiation dose can be increased. Conversely, decreasing the radiation dose will decrease the IQ.

[0013] Given this natural trade-off between radiation dose and IQ, operators may choose to adjust one or more parameter settings before performing a diagnostic scan to reduce the patient's radiation exposure or to achieve a desired IQ index. However, deciding which parameters to adjust and determining the ideal settings for those adjusted parameters may not be straightforward. The effectiveness of such adjustments in achieving both the desired dose and the desired IQ index may depend on the operator's experience and trial and error.

[0014] For example, an operator can perform a diagnostic scan according to a protocol and reconstruct an image with a first IQ index at a first dose. This image may not be of the desired quality, in which case the operator makes a first adjustment to the scan parameters and performs a second diagnostic scan to obtain a reconstructed image with the desired IQ index at an acceptable dose. The first adjustment set may not achieve the desired IQ, in which case the operator can perform a second adjustment set to the scan parameters and perform a third diagnostic scan to achieve the desired IQ. As a result of performing three diagnostic scans, the patient will be exposed to more radiation than desired in order to obtain an ideal image. Alternatively, even if a sufficient IQ for diagnosis is obtained with the first adjustment, the patient will be exposed to more radiation than necessary. Due to patient variability, a large number of adjustable parameters, and interactions between parameters, it is difficult to determine the optimal adjustment set to achieve the desired dose / IQ balance, and repeated diagnostic scans may be necessary.

[0015] Furthermore, because it is difficult to determine the optimal parameter settings for a given scan type, region of interest, patient, etc., optimizing a standard protocol used for multiple patients may involve performing numerous scans on different phantoms. This is time-consuming and reduces the availability of the imaging system for performing patient scans, thereby potentially reducing the functionality and efficiency of the imaging system.

[0016] To address these issues, a software-based tool is provided herein that allows a user to preview estimated dose and image quality (IQ) data for a patient or patient group based on one or more physical characteristics of the patient (e.g., size) and a selected protocol. In various embodiments, one or more patient characteristics may be extracted from scout images. The software-based tool simulates a front-end CT scanner console and allows the user to input patient data and / or load previously acquired patient scout DICOM images. Once the scout images or images are loaded, the user can select a desired protocol and perform a simulation of scanning the patient according to the selected protocol based on the scout images (and / or patient data). The system calculates the projected noise index, projected CT dose index (CTDI) for the selected protocol, scan range, and scan settings. vol The system can calculate and display projected dose data, including a projected noise index (CTDIvol), a projected dose-length product (DLP), and a projected exposure duration for the selected protocol, scan range, and scan settings. For features that automatically determine specific scan parameters based on patient size, it is also possible to check which settings have been selected.

[0017] Furthermore, this tool allows users to adjust scan parameters and instantly see visual and quantitative feedback on the effects of these adjustments on dose and IQ. Manually changing scan settings updates the dose and image quality predictions accordingly. In this way, users can determine a set of scan parameters for a specific patient or group of patients before performing a scan on them, achieving the desired balance between radiation dose and image quality for that patient, thus avoiding reliance on repeated diagnostic scans.

[0018] Furthermore, this tool allows users to obtain accurate predictions of IQ indices and doses across anatomical regions and patient size ranges from actual patient scouts, and visualize the predicted system behavior of clinical protocols. By using this tool, localized outliers and undesirable behavior can be prevented by selecting appropriate parameters for each part of the imaging space before imaging actual patients. This allows medical physicists to obtain accurate estimates of image quality and dose across many protocols and patient sizes, enabling more rapid optimization and validation of protocols for a general population. For example, the scan settings of a protocol can be adjusted to achieve a target dose or dose range as a function of patient size, to achieve a more consistent dose curve as a function of size (e.g., so that the dose consistently increases with patient size), and / or to achieve consistent image quality as a function of patient size and / or imaging scenario. The output of this tool can be plotted against patient size (as determined from scout images), allowing for visualization and validation of dose and image quality across patient size ranges. By doing this for a large number of existing scouts, the protocol can be optimized without being limited to scanning phantoms. As a result, consistent image quality can be generated across similar patients for efficient diagnostic interpretation, and / or consistent image quality over time for repeat patients when comparing quantitative measurements as a function of time, which would have inherent variability not attributable to changes in disease state if the protocol optimization were poorly performed.

[0019] Referring here to the figure, Figure 1 shows an exemplary simulated CT system 100. The exemplary simulated CT system includes an operator workstation 102 and a CT simulator 104 accessible using the operator workstation 102. The exemplary CT simulator 104 may be located on a server within the hospital system or may be accessible via cloud access. The simulated CT system 100 may be operable / communicatively coupled to one or more user input devices and display devices. For example, the user input device may include a keyboard and mouse or similar device coupled to a computer, and the display device may include a monitor coupled to a computer. In place of, or in addition to, a mouse and keyboard, other input devices may include, but are not limited to, a touchscreen, trackpad, microphone, and camera. The input devices allow the operator (e.g., a medical physicist) to select one or more inputs to the CT simulator 104. Inputs may include a library of other images related to the patient's symptoms and / or physician's instructions, such as patented electronic medical records or history, scout scans and / or diagnostic images. The CT simulator 104 processes these inputs with respect to the selected imaging protocol. The CT simulator then outputs an optimized scan protocol, including parameter settings for the scan protocol to perform a scout scan and / or diagnostic scan on a patient or group of patients. For example, a scout scan for a large adult patient may be input, and a chest scan protocol may be selected via the operator workstation. The CT simulator 104 can simulate multiple variations of the protocol parameters to determine the optimal parameters that balance acceptable IQ countermeasures with the dose to the patient. The output parameters can then be used in the CT imaging system for a scout scan and / or diagnostic scan of a large adult patient requiring a chest scan.In some embodiments, scout scans for patients of multiple sizes can be selected simultaneously, and the CT simulator 104 can output parameters for each patient group.

[0020] The simulated CT system 100 includes a processor configured to execute machine-readable instructions stored in a non-transitory memory. The processor may be a single-core or multi-core processor, and the program executed thereon may be configured for parallel processing or distributed processing. In some embodiments, the processor can optionally include individual components distributed across two or more devices, which may be remotely located and / or configured for cooperative processing. In some embodiments, one or more aspects of the processor may be virtualized and executed by a remotely accessible network computing device configured in a cloud computing configuration. The non-transitory memory can store one or more simulated CT scanner software applications that can include software applications that mirror what is used to operate a CT scanner to acquire projection data during a scan and reconstruct an image based on the acquired projection data, which are installed on the operator console and / or operator workstation 102 of the CT imaging system.

[0021] FIG. 2 shows a more detailed block diagram of the exemplary CT imaging system of FIG. 1. The simulated CT system 100 may be a stand-alone system, i.e., the simulated CT system 100 may not be part of the imaging system 201 and may not be coupled to the imaging system 201. In various embodiments, the simulated CT system 100 may be installed on a computing device of a radiologic technologist or other user. For example, a part of the simulated CT system may be disposed in a device (e.g., an edge device, a server, etc.) communicatively coupled to the imaging system 201 via a wired and / or wireless connection. The exemplary CT simulator 104 includes an Internet browser 202. The Internet browser 202 enables a user to access the CT simulator 104 from the operator workstation 102. The Internet browser 202 enables access to a server 204. The server accesses a user interface (UI) file 203 of the scan simulator and includes an interface for the user to interact with the CT simulator. The exemplary user interface is depicted in FIG. 5 and may include areas for inputs or prompts selected by the user and areas for output of information.

[0022] Via the server 204, the CT simulator 104 can access a protocol database 206 via a protocol provider service 208. The protocol database 206 stores existing protocols from which the user can select a protocol to be optimized using the CT simulator 104. As described in connection with FIG. 1, the user can select a protocol, such as a protocol for a chest scan, from the protocol database 206 using an input device of the operator workstation.

[0023] Furthermore, users can access the radiology information server 210 via the patient information service 212 and server 204. The radiology information server may contain patient data available in the hospital system. For example, patient data may include the patient's medical records, including height, weight, demographic information, etc. Patient data may also include past patient scans (e.g., scout scans, diagnostic scans) and diagnostic information (e.g., information related to the patient's diagnosis, e.g., cancer diagnosis, cardiac diagnosis, etc.). Patients can be classified into patient groups using any of the patient information. The CT simulator can then optimize the scan parameters of the protocol for the patient group using scan data from one or more patients within the identified patient group. Patient groups may be based on size (e.g., small adult, medium adult, large adult, pediatric, etc.), clinical group, and / or diagnostic information (e.g., cardiac status). Furthermore, the exemplary CT simulator can also simulate how predicted IQ indices and doses change across groups, for example, by plotting the distribution across patients of different sizes.

[0024] The user can also access the DICOM (Digital Imaging and Communications in Medicine) image library 214 via the image provider service 216. DICOM images can be used as input to the CT simulator 104 in addition to or instead of the patient's scout scan. The DICOM image library 214 may contain multiple DICOM images, each acquired using a CT system. The DICOM image library 214 may be an unspecified example of a picture archiving and communications system (PACS), or may be included in a picture archiving and communications system (PACS). In particular, the DICOM image library 214 may contain multiple scout images. The CT simulator 104 can receive scout images from the DICOM image library 214, process the scout images to calculate estimated doses (CTD1 vol and DLP), and / or estimate the image quality (IQ) scale of the image reconstructed from projection data acquired from the patient in the scout image during the scan, as described in more detail below.

[0025] An exemplary CT simulator 104 includes at least one dose algorithm service 218. The dose algorithm service 218 may include a dose algorithm equivalent to one performed on a CT imaging system. The dose algorithm uses user-provided inputs and outputs a dose or dose curve. The dose algorithm service 218 may include instructions for estimating the predicted dose of a scan using a selected scan protocol, according to the scan settings output by the CT simulator 104 based on the protocol. The dose algorithm service 218 may model the performance of a CT scanner and estimate the predicted dose. In particular, when executed by the processor, the dose algorithm service 218 may include instructions for causing the simulated CT system 100 to perform one or more steps of method 300.

[0026] The exemplary CT simulator 104 may further include an IQ algorithm service 222. The IQ algorithm service 222 may include one or more algorithms that can be used to determine scan protocol parameters optimized to balance dose and IQ for a patient or group of patients. The exemplary algorithm may reflect those performed in a CT imaging system 201. The exemplary algorithm may include a noise-based automatic exposure control (AEC) algorithm that determines the amount of noise that can be expected in the resulting image using the scan protocol and selected parameters for a patient or group of patients. A dose-based AEC algorithm may be performed to minimize the patient's dose when using the selected scan protocol. The exemplary CT simulator may also include a patient specificity service 220 that provides information about patient-related parameters determined by the CT simulator. For example, an automatic prescription algorithm can be used to determine a set of scan settings to be used to scan a patient according to a protocol. That is, a user of the simulated CT system 100 can specify the protocol to use 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. Furthermore, the algorithm of the patient-specific service 220 may determine the scan range for a patient or patient group (e.g., scan start position, scan end position). One or more exemplary algorithms of the dose algorithm service 218, the IQ algorithm service 222, and the patient-specific service 220 together determine the parameters to be used in a selected protocol to optimize the balance between dose and IQ for the resulting images from the CT scan.

[0027] Next, turning to Figure 3, an exemplary method 300 is shown for simulating a diagnostic scan and previewing patient predicted dose and image quality (IQ) data based on a selected protocol and provided patient data. Method 300 can be performed by a simulated CT system 100. The operations of Method 300 may be stored in the non-transient memory of the simulated CT system 100 and executed by the processor of the simulated CT system. It should be understood that in various embodiments, one or more steps of Method 300 may be performed multiple times, for example, in an iterative manner.

[0028] Method 300 begins with 301, where Method 300 includes starting the CT simulator 104. In some embodiments, starting the simulated CT system includes starting the user interface using the browser 202 of the CT simulator 104 (e.g., via the scan simulator user interface file 203). In various embodiments, the CT simulator 104 may be installed on the computing device of a user, such as an operator of a CT imaging system (e.g., a radiologist or medical physicist). Alternatively, the CT simulator 104 may be stored on a server accessible by an operator workstation 102 used by a radiologist and / or medical physicist. The CT simulator 104 may be started by the user before and / or in preparation for performing a CT imaging scan on a patient. Once the CT simulator 104 is started, the GUI of the CT simulator 104 may be displayed on the display screen of the simulated CT system 100 (e.g., the display of the operator workstation 102).

[0029] In 302, method 300 includes receiving a protocol to be used during a subsequent diagnostic scan of the patient. The protocol can be selected from a number of protocols (for example, the user can select from a protocol database 206 that is available to the CT imaging system 201, which can correspond to available protocols).

[0030] In 304, method 400 includes receiving one or more patient characteristics of a patient that can be used to constitute a protocol received for a patient or group of patients. One or more patient characteristics can be received from a user of the CT simulator 104 via a GUI. For example, one or more patient characteristics may include the patient's size, or the patient's body mass index (BMI), or the patient's water equivalent diameter (WED), or different physical characteristics of the patient or group of patients.

[0031] In various embodiments, patient characteristics may be extracted from patient images or a set of patient measurements. For example, in 305, method 300 may include extracting patient characteristics (such as patient size) from patient localizer (e.g., scout) images. Scout images can be received from a storage location on a computing device, or a storage device coupled to a computing device, such as the image repository of the CT imaging system (e.g., the DICOM image library 214 in Figure 2). For example, a user may specify the scout images to receive via a GUI. In some embodiments, a user may use a GUI to browse or search for multiple scout images stored in one or more locations within the computing device or on a network of computing devices and select the desired scout images to load into the CT simulation system. In other examples, patient characteristics may be extracted from 3D camera images of the patient taken during a scout scan, or from an electrocardiogram (EKG) recorded from the patient, or from another type of patient data obtained from the patient.

[0032] The GUI of the CT simulator 104 (e.g., the GUI) may include a set of controls that are the same as or similar to the set of controls of the GUI of the CT imaging system used to perform scans on a patient, and which is displayed on the operator console of the CT imaging system (e.g., the operator console). That is, the GUI may provide similar functionality to the CT imaging system GUI and be accessible in a similar manner to the CT imaging system GUI, through controls that have a similar appearance to the controls of the CT imaging system GUI. For example, a user may load localizer images (e.g., scout scans), select a protocol for performing a diagnostic scan, request recommended scan parameters according to the protocol, and / or manually set multiple scan settings using GUI controls similar to the corresponding controls of the CT imaging system GUI. In this way, 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 the user's quick and easy use of the CT simulation system.

[0033] In 306, method 300 includes determining a parameter setting (also referred to herein as scan setting) for scanning a patient based on a received protocol and one or more patient characteristics. In various embodiments, the parameter setting may be determined by one or more algorithms, such as the dose algorithm service, the noise-based AEC algorithm, the dose-based AEC algorithm, the smartplan algorithm, the auto prescription algorithm, the GSI assist algorithm, the autogating algorithm, and the kV assist algorithm, which may be included in the patient specificity service 220 or IQ algorithm service 222 in Figure 2. For example, the algorithms may include an AEC system, a scan range selection system, etc. That is, one or more algorithms may take a received scan protocol and additional patient characteristics as input and output one or more sets of scan parameters for performing a scan according to the protocol. One or more sets of scan parameters may be displayed on a display screen for the user to view.

[0034] In 308, method 300 includes simulating a patient's diagnostic scan in a CT simulation system based on one or more sets of scan parameters. Once the scan is simulated, the CT simulation system can calculate predicted (e.g., estimated) dose data for the simulated scan. The predicted dose may be an estimate of the dose for the applied scan settings or parameters (e.g., kV, mA, rotation time, collimation, helical pitch, etc.). The calculation of the predicted dose data may involve, for example, the predicted CTDI of the scan. vol This may include the calculation of predicted DLP and / or a size-specific dose estimate (SSDE). Furthermore, the predicted dose data may include a projected exposure duration for the scan protocol and settings or parameters. The predicted dose data may be used in conjunction with patient characteristics such as patient size, the anatomical area being scanned, and / or other factors for estimating the effective dose of the scan to the patient.

[0035] Applied scan settings or parameters may be input to a CT scanner model, which may output projected dose data, projected IQ data, and / or other projected data. In some embodiments, the CT scanner model may rely on a set of pre-measured values ​​for specific scan parameters, or it may apply a set of correction factors based on the actual applied settings of the scan modified by the user. Projected IQ data may be generated from projected dose data and may be used to display exemplary images corresponding to the projected dose data. For example, projected IQ data may include a projected noise index (NI) of the scan, and the projected NI may be used to generate exemplary images. The projected dose and IQ data may be identical to those seen in a clinical setting when a diagnostic scan is performed on a patient.

[0036] The predicted dose, IQ data, and images may be displayed on the operator workstation's display screen via the CT simulator user interface. An exemplary CT simulator user interface is described below with reference to Figure 5.

[0037] The predicted NI of the scan is the predicted dose index (CTDI). vol ) may be inversely proportional to the predicted dose. That is, as the predicted dose increases, the predicted NI may decrease (e.g., increase IQ). 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 display examples of different IQs that can be achieved at different doses, customize the scan parameters for the patient, and maintain the dose within a desired or acceptable range while achieving the desired IQ index.

[0038] In step 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 in step 310 that the parameter settings have not been confirmed, method 300 proceeds to step 312. In step 312, method 300 includes receiving the adjusted scan parameters, and method 300 returns to step 308 to resimulate the patient scan based on the adjusted scan parameters. For example, one or more scan parameter settings may be adjusted by the user via individual controls for each parameter setting within the CT simulator UI, as described later with reference to Figure 5. After the scan parameters have been adjusted, the updated IQ index and dose data may be displayed in real time in the CT simulation GUI. In this way, the user can test various different adjustments to the parameter settings to determine a combination of settings that achieves the desired image quality at an acceptable dose.

[0039] Alternatively, if it is determined in 310 that the parameter settings have been verified, it can be inferred that the parameter settings are acceptable to the user, and thus method 300 proceeds to 314. In 314, method 300 includes modifying the protocol to generate a customized protocol for the patient, the customized protocol including the adjusted scan settings. In 316, method 300 includes storing the scan parameter settings in a memory accessible by the CT imaging system 201.

[0040] The stored parameter settings can be exported to the CT imaging system for use in subsequent diagnostic scans of a patient or group of patients. By performing a diagnostic scan using adjusted parameter settings determined using the simulated CT system 100, rather than the recommended parameter settings automatically generated based on the protocol, the target IQ index of the image reconstructed from projection data acquired during the diagnostic scan may be achieved more accurately with a lower radiation dose than that generated using the recommended parameter settings. In this way, a specific IQ / dose balance can be efficiently and quickly customized for the patient. Furthermore, since 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, i.e., without using the resources of the CT imaging system. For example, the simulated CT system 100 may be used in parallel by multiple users while the CT imaging system is being used to perform diagnostic scans on other patients, or the simulated CT system 100 may be used while the CT imaging system is not running or is not receiving power. As a result, the resources of the CT imaging system become available for other tasks while the simulated CT system 100 is in use, improving the efficiency and functionality of the CT imaging system.

[0041] Because customized parameter settings are determined using a simulated CT system in an offline manner independent of the CT imaging system, the CT imaging system may remain available for diagnostic scans of more patients compared to an alternative scenario where a simulated CT system is unavailable. In the alternative scenario, the operator may monopolize the CT imaging system for a longer period to perform multiple diagnostic scans on a patient to obtain images of the desired quality.

[0042] Referring next to Figure 4, an exemplary method 400 is shown for modifying a diagnostic scan protocol for multiple patients to achieve a smoother dose curve as a function of patient size using a simulated CT simulation system 100. The simulated CT system 100 allows the user to preview predicted dose and image quality (IQ) data for patients of different sizes, as described above with reference to Figure 3. The operation of method 300 can be stored in the non-transient memory of the simulated CT system 100 and executed by the processor of the simulated CT system 100.

[0043] Method 400 begins with 402 and includes receiving multiple scout images for each of multiple patients, where the patients have a range of different sizes. The multiple scout images can be received from one or more repositories of DICOM images, such as a DICOM image library.

[0044] In 404, method 400 includes receiving protocols (e.g., initial protocols) to be used during diagnostic scans of multiple patients. The initial protocols are provided by the user of the simulation CT system 100 via a GUI of the CT simulation system, such as the GUI shown in Figure 5.

[0045] In 406, method 400 includes generating a parameter setting to be used in a diagnostic scan performed on multiple patients, based on an initial protocol received. The first part of the parameter setting may consist of patient characteristics, such as patient size, which is calculated from scout images. The second part of the parameter setting may be generated by one or more algorithms, such as an automated scan prescription algorithm.

[0046] In 408, Method 400 includes simulating a diagnostic scan on a patient of the scout image for each of the plurality of scout images. Once the diagnostic scan is simulated, the predicted dose and IQ data of the diagnostic scan may be displayed on a display device such as a display device. The user may view the predicted dose and IQ data to determine whether the predicted IQ index of the image reconstructed from the diagnostic scan exceeds a threshold quality. Method 400 also includes receiving adjustments to the parameter settings for the patient from the user. That is, for each scout image, the user can adjust one or more parameter settings via a GUI and view the updated predicted dose and IQ data of the simulated diagnostic scan for the corresponding patient. The user can adjust one or more parameter settings in various ways in an iterative process to achieve a desired IQ index at an acceptable dose. Once the user has determined the parameter settings that achieve the desired IQ index at an acceptable dose, the user can confirm the parameter settings via control elements of the UI. Once the parameter settings for the patient are confirmed, the parameter settings, the resulting predicted IQ index, and the corresponding predicted dose for the patient may be stored in the system's non-transient memory.

[0047] In 410, method 400 includes calculating dose curves for multiple patients as a function of patient size based on the predicted dose for each patient of multiple patients. That is, a diagnostic scan is simulated for each patient in each scout image of multiple scout images, and after corresponding parameter setting adjustments are collected for each simulated diagnostic scan, the multiple patients are ordered according to patient size, and a curve can be fitted to the predicted dose for each patient with respect to patient size.

[0048] Referring briefly to Figure 7, an exemplary dose curve graph 700 is shown, which illustrates the dose as a function of patient size for simulated and actual patient data related to a diagnostic scan. Patient size can be calculated from the scout image, as described above, and may include, for example, the anterior-posterior (AP) size or anterior-posterior size, and the lateral (LAT) size, measured in centimeters. The dose applied to the patient is plotted on the y-axis of the dose curve graph 700 as CTDI. vol The patient size corresponding to the dose is shown on the x-axis of dose curve graph 700. Dose curve graph 700 includes two plots of dose curves. The first dose curve 702 is plotted based on the first protocol and has a first set of parameter settings indicated by the first protocol for each patient. The second dose curve 704 is plotted based on the second protocol and has simulated (e.g., predicted) dose data associated with each patient, the dose data being generated as a result of simulating a diagnostic scan of the patient using a CT simulation system. In particular, the dose data for the second dose curve 704 is based on the 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 for each patient is shown in mGy.

[0049] As can be seen in Figure 7, the first dose curve 702 does not show a smooth progression of dose as a function of patient size. In particular, the first portion 706 of the first dose curve 702 shows that an equivalent dose (11.3 mGy) is delivered to patients with a size in the range of approximately 58 cm to 67 cm. The second portion 708 of the first dose curve 702 shows that the dose increases sharply for patients with a size in the range of approximately 67 cm to 69 cm. The third portion 710 of the first dose curve 702 shows that an equivalent dose (18.5 mGy) is delivered to patients with a size in the range of approximately 69 cm to 90 cm. Therefore, when diagnostic scans are performed using the first protocol, patients whose size decreases or increases over the course of treatment may be given a dose that is not well adjusted to the patient's size, which may result in suboptimal image quality or a dose higher than necessary to achieve the desired image quality (if the patient does not receive an adequate dose).

[0050] In contrast, the second dose curve 704 shows a smoother change in dose as a function of patient size than the first dose curve 702, and different doses are consistently applied to patients of different sizes with similar increments. Therefore, when diagnostic scans are performed using the second customized protocol, patients whose size decreases or increases during the course of treatment are given a dose that is more precisely matched to the patient's size, which may result in a more optimal trade-off between radiation dose and image quality.

[0051] Returning to Figure 4, in 412, method 400 includes modifying the protocol based on the calculated dose curve. That is, for each scout image / patient that generates a dose curve with desired characteristics such as the smooth evolution of dose as a function of patient size shown by the second dose curve 704 in Figure 7, the protocol may be modified to include the appropriate adjusted parameter settings once appropriate adjusted parameter settings have been collected from the user. The modified protocol may be used to set parameter settings for future diagnostic scans of patients of varying sizes, rather than the initial protocol. The modified protocol can specify parameter settings for each of patients of varying sizes that more smoothly adjust the dose applied to the patient as a function of size than the initial protocol.

[0052] In 414, method 400 includes storing the modified protocol in memory accessible by the CT scanner. During a subsequent diagnostic scan, the modified protocol can be retrieved from memory and applied by the CT scanner operator. Method 400 then terminates.

[0053] Figure 5 shows an exemplary GUI 500 of a simulated CT system 100 that may be used in the methods 300 and 400 described above to simulate a patient's diagnostic scan on a CT scanner. It should be understood that GUI 500 is provided for illustrative purposes only and is not intended to limit, and in other embodiments, GUI 500 may include more or fewer components, or different components, without departing from the scope of this disclosure.

[0054] GUI500 may include a top bar 502 that can provide space for various high-level controls, such as login or exit functions, user profiles, and / or other high-level menu options. In some examples, GUI500 may provide a tabbed view in which different scan or patient data can be presented in multiple tabs accessible from the top bar 502.

[0055] In the embodiment depicted, 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 in progress. The second display panel 520 may include general high-level information about a selected patient or case. For example, a user of the GUI 500 can select a patient via a menu accessed via the top bar 502, which can display, for example, multiple patients in a medical system. Data for the selected patient is retrieved from a storage location and displayed in the GUI 500. The storage location may be the memory of a simulated CT system 100 or a storage location in another system accessible via a network. High-level information may include, for example, patient identification information, patient health problems, image availability, test results, and historical data such as procedures performed on the patient. The second display panel 520 may also include control elements such as one or more buttons for performing various tasks or displaying different types of patient data. In particular, the second display panel 520 may include control elements for initiating a simulation of a diagnostic scan for a patient, as described above with reference to Figure 3.

[0056] The third display panel 522 and the fourth display panel 524 can be used to display parameter settings related to the selected protocol. For example, the user can select a protocol to be used in a future diagnostic scan of a 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 to start a simulation of a diagnostic scan. Once a protocol is selected, the parameter settings related to the protocol may be displayed on one or both of the third display panel 522 and the fourth display panel 524. The parameter settings may be composed of or determined by one or more algorithms, such as automated scan prescription algorithms. 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 a protocol as input and output a set of parameter settings for each protocol. Patient data may include one or more patient characteristics, such as patient size. In some embodiments, patient data may include or be extracted from scout images obtained from the patient at a previous time. In some examples, the scout image may be displayed on the seventh display panel 530 and / or the eighth display panel 532 of the GUI 500.

[0057] Scan parameters generated by one or more AI models and displayed in the third display panel 522 and / or the fourth display panel 524 may be editable (e.g., adjustable) by the user. As described above, the user can adjust one or more of the scan parameters of the selected protocol. In particular, the user can start a simulation of a diagnostic scan for a patient using the protocol's parameter settings and view the predicted dose and IQ data of the simulated diagnostic scan based on the parameter settings. The user can then adjust one or more of the scan parameters and view the updated predicted dose and IQ data of 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 patient protocol in future diagnostic scans. The predicted dose and IQ data may be displayed in the fifth display panel 526. In some cases, a visualization of the updated parameter settings may be displayed additionally or alternatively in one or more of the display panels 522, 524, 526, 530, and 532. For example, the user can adjust the start and end positions of the diagnostic scan, and the adjusted start and end positions of the diagnostic scan can be visualized on the scout image displayed on display panels 530 and 532.

[0058] An exemplary settings summary display panel may be displayed, for example, on the second display panel 520 of GUI 500. The settings summary display panel includes various categories of parameter settings related to the selected protocol, with individual settings within each category summarized and displayed. For example, anatomy 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 trace parameter settings are summarized on display panel 520. The settings summary may be displayed in the same or similar manner as the parameter settings are displayed to the operator of the CT scanner via the operator console of the CT imaging system. Thus, the display of parameter settings on the settings summary display panel 520 may be familiar to the user of GUI 500.

[0059] An exemplary predicted dose display panel may be displayed on a fifth display panel 526 of the GUI 500 in various embodiments. The predicted dose display panel 525 can display predicted dose data for a simulated diagnostic scan initiated via the GUI 500. The predicted dose data may be based on the parameter settings of the selected protocol or on user-generated adjusted parameter settings. In the embodiments depicted, the predicted dose data includes an overall predicted dose value (e.g., 101.39) which may be generated from various dose data components. The dose data components may be, for example, CTDI measured in mGy units. volThe values ​​may include: a DLP dose value measured in mGy*cm units; a dose efficiency value indicating the percentage of the dose used to generate the image; and the size in cm of the CTDI phantom used when calculating the CTDI and dose efficiency, where the phantom may be a body phantom consisting of a 32cm cylindrical phantom, or a head phantom consisting of a 16cm cylindrical phantom.

[0060] The predicted dose value is a measure of the dose to the phantom for the applied scan settings (e.g., kV, mA, rotation time, collimation, helical pitch, etc.) and can be calculated by examining a set of prior measurements for a particular setting and then applying a set of correction factors based on the actual applied settings of the scan, as described above.

[0061] If the user is satisfied with the predicted IQ index and predicted dose, they can select a control element and confirm the parameter settings displayed in GUI500. If the user is not satisfied with the predicted IQ index and predicted dose, they can adjust one or more parameter settings and resimulate the diagnostic scan to obtain different predicted IQ index and dose data. The user can simulate the diagnostic scan in various ways with different parameter settings 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 is modified to include the adjusted parameter settings, thereby generating a customized protocol for the patient. The customized protocol may be used during future diagnostic scans of the patient via the CT scanner.

[0062] Exemplary visualizations of the start and end points of a simulated diagnostic scan, according to the embodiments, may be displayed on the scout image shown in the GUI 500 of Figure 5, for example, on the seventh display panel 530 and the eighth display panel 532. When a protocol is selected by the user, the selected portion of the patient's anatomical structure to be scanned in the diagnostic scan may be indicated by a first box on the first view of the scout image displayed on the seventh display panel 530, and by a second box on the second view of the scout image displayed on the eighth display panel 532. In some embodiments, the exemplary patient specificity service 220 of Figure 2 may be used to identify the selected portion of the patient's anatomical structure. The start point of the diagnostic scan may be indicated by the upper line of the first box and the leftmost line of the second box. The end point of the diagnostic scan may be indicated by the lower line of the first box and the rightmost line of the second box.

[0063] The user can adjust the start and end point parameters of the simulated diagnostic scan. When the user edits the start and end point parameters, the selected portion of the patient's anatomical structure scanned in the diagnostic scan may be updated in the visualization. The updated selected portion of the anatomical structure is indicated by a first box on the first view of the scout image displayed on the seventh display panel 530, and a second box on the second view of the scout image displayed on the eighth display panel 532. The updated start point of the diagnostic scan may be indicated by the upper line of the first dotted box and the leftmost line of the second dotted box. The end point of the diagnostic scan is indicated by the lower line of the first dotted box and the rightmost line of the second dotted box. In this way, the visualization can visualize the effect of adjustments to the start and end point parameters that are made textually via the anatomical selection display panel on the scout image, which may make it easier for the user to identify the ideal starting and ending point parameters for the diagnostic scan.

[0064] In some embodiments, the upper line, lower line, left-most line, and right-most line may be selectable, allowing the user to interactively adjust the position of one or more of these lines to reflect a desired start and / or end point. When the user interactively adjusts the position, the corresponding start and / or end point parameters may be automatically updated in the simulated CT system and anatomical selection display panel.

[0065] Figure 6 shows another exemplary user interface 600 that may be displayed on the operator workstation 102 when using the simulated CT system 100. The exemplary user interface 600 simultaneously includes estimated patient size and predicted examination dose for multiple patients. The exemplary user interface 600 depicts three simulated patients of three different sizes (e.g., small adult, medium adult, and large adult). However, any number of simulated patients may be depicted. In the illustrated example, there are available insights for simulated patient 1. In such cases, the insight box 602 may be depicted in a different color than when there are no available insights. Examples of insights include suggested adjustments to the patient's smart plan, such as adjusting the start or stop position of the scan on the patient's body. Another example of an insight is adjusting the kV to meet recommended noise requirements.

[0066] The technical effect of simulating a patient's diagnostic scan performed by a CT imaging system, allowing the user of the simulated CT system to adjust the parameter settings of a selected protocol for the diagnostic scan, and to view the predicted dose and image quality data of the simulated diagnostic scan, is that it is possible to generate customized protocols for the patient that result in reconstructed images of the desired image quality scale without wasting the time and resources of the CT imaging system operator in repeated diagnostic scans.

[0067] Further aspects of the present invention are provided by the subject matter of the following clauses. [Embodiment 1] A computer-implemented method for a simulated computed tomography (CT) system, The steps include receiving a selected scan protocol via a user interface, The steps include receiving, via the user interface, one or more characteristics of a patient or patient group, The steps include determining, using a CT simulator, parameter settings for scanning the patient or patient group, The steps include determining a projected image quality measure or projected dose using the CT simulator, The steps include generating a customized scan protocol for the patient or patient group, Methods that include... [Embodiment 2] The method according to any prior embodiment, further comprising the step of displaying the projected image quality measure and dose on a display of the simulated CT system. [Embodiment 3] The method of any of the prior embodiments, further comprising the step of launching a CT simulator on an operator workstation, wherein the operator workstation is remote from a CT imaging system. [Embodiment 4] The method according to any of the preceding embodiments, wherein receiving one or more characteristics of a patient or patient group includes extracting characteristics from a scout scan. [Embodiment 5] The method according to any prior embodiment, wherein determining the projected image quality measure and dose includes simulating a scan of the patient or patient group based on the selected scan protocol, characteristic, and parameter settings. [Embodiment 6] The method of any prior embodiment, further comprising the step of receiving confirmation from a user that the parameter settings are acceptable. [Embodiment 7] The method according to any of the preceding embodiments, wherein when the parameter settings are not acceptable, adjusted parameter settings are received via the user interface. [Embodiment 8] The method of any prior embodiment, further comprising the step of saving the customized scan protocol in a memory accessible by the CT system. [Embodiment 9] A simulated computed tomography (CT) system, An operator workstation and A CT simulator accessible via the operator workstation, wherein the CT simulator is The selected scan protocol is received via a user interface displayed on the operator workstation. The user interface receives one or more characteristics of a patient or patient group. Determine the parameter settings for scanning the patient or patient group. Determine a projected image quality measure and dose. A system configured to generate a customized scan protocol for the patient or patient group. [Embodiment 10] The system according to any of the prior embodiments, wherein the CT simulator is further configured to display the projected image quality measure and dose via the user interface on the operator workstation. [Embodiment 11] The system according to any of the preceding embodiments, wherein the received one or more characteristics of a patient or patient group are extracted characteristics from a scout scan. [Embodiment 12] The system according to any of the prior embodiments, wherein the projected image quality mreasure and dose are determined by simulating a scan of the patient or patient group based on the selected scan protocol, characteristics, and parameter settings. [Embodiment 13] The system according to any of the preceding embodiments, wherein the CT simulator is further configured to receive confirmation from a user that the parameter settings are acceptable. [Embodiment 14] The system according to any of the preceding embodiments, wherein if the parameter settings are not acceptable, the CT simulator is further configured to receive adjusted parameter settings via the user interface. [Embodiment 15] The system according to any of the preceding embodiments, further comprising a CT system, wherein the customized protocol is saved in a memory accessible by the CT system. [Embodiment 16] A computer implementation method for a simulated computed tomography (CT) system, the method being: The steps include receiving a plurality of scout images, The steps include receiving a protocol to be used during a diagnostic scan, The steps include generating parameter settings to be used on the diagnostic scan, The steps include: simulating the diagnostic scan for a plurality of patients; The steps include: calculating a dose curve for the plurality of patients as a function of patient size; A method comprising the step of modifying the protocol based on the dose curve. [Embodiment 17] The method according to any prior embodiment, further comprising the step of storing the modified protocol in a memory accessible by a CT scanner. [Embodiment 18] The method according to any of the prior embodiments, wherein the dose curve is based on a projected dose of each patient determined using the simulated diagnostic scan for the plurality of patients. [Embodiment 19] The method according to any of the preceding embodiments, wherein receiving a protocol includes a user selecting from a database of protocols. [Embodiment 20] The method according to any of the prior embodiments, wherein receiving a plurality of scout images includes a user selecting from a library of images.

[0068] When describing elements of various embodiments of this disclosure, the articles “a,” “an,” and “the” are intended to indicate that there is one or more elements. Terms such as “first,” “second,” etc., do not indicate order, quantity, or importance, but rather are used to distinguish one element from others. Terms such as “comprising,” “including,” and “having” are intended to be comprehensive and mean that there may be additional elements other than those listed. As terms such as “connected,” and “joined” are used herein, one object (e.g., material, element, structure, member, etc.) may be connected to or joined to another object, whether one object is directly connected to or joined to another object, or whether there is one or more intervening objects between one object and another object. In addition, it should be understood that any reference to “one embodiment” or “one embodiment” in this disclosure is not intended to be construed as excluding the existence of additional embodiments that also incorporate the mentioned features.

[0069] In addition to the modifications described herein, numerous 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. Thus, although the above has been described with specificity and detail in relation to what is considered to be the most practical and preferred embodiment at present, it will be apparent to those skilled in the art that numerous modifications, including but not limited to form, function, method of operation and method of use, can be made without departing from the principles and concepts described herein. Furthermore, as used herein, the examples and embodiments are illustrative in all respects and should not be construed as limiting in any way. [Explanation of Symbols]

[0070] 100: CT System 102: Operator Workstation 104: CT Simulator 201: Imaging System 202: Internet Browser 203: User Interface (UI) File 204: Server 206: Protocol Database 208: Protocol Provider Service 210: Radiation Information Server 212: Patient Information Service 214: DICOM Image Library 216: Image Provider Service 218: Dose Algorithm Service 220: Patient Specificity Service 222: IQ Algorithm Service 500: GUI 502: Top Bar 510: First Display Panel 520: Second Display Panel 522: Third Display Panel 524: Fourth Display Panel 526: Fifth Display Panel 530: Seventh Display Panel 532: Eighth Display Panel 600: User Interface 602: Insight Box 702: First Dose Curve 704: Second Dose Curve 706: Part 1 708: Part 2

Claims

1. A computer-aided method for a simulated computed tomography (CT) system, The steps include receiving the selected scan protocol via the user interface, The steps include receiving one or more characteristics of a patient or a group of patients via the user interface, The steps include determining parameter settings for scanning the patient or group of patients using a CT simulator, The steps include determining a predicted image quality index or predicted dose using the CT simulator, The steps include generating a customized scan protocol for the patient or patient group, Methods that include...

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

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

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

5. The method according to claim 1, wherein determining the predicted image quality index and predicted dose includes the step of simulating a scan of the patient or group of patients based on the selected scan protocol, characteristics and parameter settings.

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

7. The method according to claim 6, wherein if the aforementioned parameter settings are unacceptable, the adjusted parameter settings are received via the user interface.

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

9. A simulated computed tomography (CT) system, Operator workstation and A CT simulator accessible via the operator workstation, wherein the CT simulator is The selected scan protocol is received via the user interface displayed on the operator workstation. Through the aforementioned user interface, one or more characteristics of a patient or patient group are received. Determine the parameter settings for scanning the aforementioned patient or patient group, Determine the predicted image quality index and dose, A system configured to generate a customized scan protocol for the aforementioned patient or group of patients.

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

11. The system according to claim 9, wherein the one or more characteristics received by the patient or patient group are characteristics extracted from a scout scan.

12. The system according to claim 9, wherein the predicted image quality index and dose are determined by simulating the scan of the patient or group of patients based on the selected scan protocol, characteristics and parameter settings.

13. The system according to claim 9, wherein the CT simulator is further configured to receive confirmation from the user that the parameter settings are acceptable.

14. If the parameter settings are unacceptable, the CT simulator is further configured to receive adjusted parameter settings via the user interface, according to claim 13.

15. The system according to claim 9, further comprising a CT system, wherein the customized protocol is stored in a memory accessible by the CT system.

16. A computer implementation method for a simulated computed tomography (CT) system, the method being: The steps include receiving multiple scout images, A step of receiving the protocol to be used during the diagnostic scan, The steps include generating parameter settings used in the diagnostic scan, A step of simulating the diagnostic scan for multiple patients, A step of calculating the dose curves of the plurality of patients as a function of patient size, A method comprising the step of modifying the protocol based on the dose curve.

17. The method according to claim 16, further comprising the step of storing the modified protocol in a memory accessible by the CT scanner.

18. The method according to claim 16, wherein the dose curve is based on the predicted dose for each patient determined using the simulated diagnostic scans for the plurality of patients.

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

20. The method according to claim 16, wherein receiving multiple scout images includes the user selecting from a library of images.

Images